ChapterPDF Available

Building Energy Management Systems (BEMS)

  • Sohag University Faculty of Engineering

Abstract and Figures

Energy systems are essential part of buildings and facilities, which are associated with high costs, and considered key success factor of businesses and services produced from the building or facility. Energy management will protect the underlying business by allowing accurate and automated management of energy systems and supply. Energy management systems (BEMS) are computer‐based automated systems that monitor and control all energy‐related systems from mechanical and electrical equipment in buildings. Building management systems (BMS) are commonly used to automate all services and functions within the building, which include energy management. BMS connects building components with a central computer to enable the control of different variables and parameters within the building. This chapter presents energy management system (EMS) and possible ways to achieve energy monitoring, savings, and smart homes. Case studies will be discussed to analyze energy savings and reduce electricity bills. To achieve full deployment and integration with smart grids, it is essential to implement BMS and BEMS.
Content may be subject to copyright.
CH02 05/04/2018 16:42:41 Page 15
Sohag University, Egypt University of Ontario Institute of Technology, Canada
Faculty of Energy Systems and Nuclear Science & Engineering and Applied
Science, University of Ontario Institute of Technology, 2000 Simcoe Street North,
Oshawa, L1H7K4, ON, Canada
Building energy management systems (BEMS) are computer-based control sys-
tems that control and monitor the mechanical and electrical equipment in buildings
such as ventilation, heating, lighting, power systems, and so on. This is sometimes
called building management systems (BMS); they connect the building services
plant back to a central computer to enable control of on/off times, humidity,
temperatures, and so on. Data cables connect the controlled plant through a series
of hubs called outstations around the building back to a master station that is
central supervisor computer where building operators can supervisory control and
monitor the building. Energy management systems can save millions on annual
energy bills while increasing prosperity in your building and making it easier to
run. Todays energy management systems (EMS) make managing energy utiliza-
tion (and bills) easier than ever.
Energy management systems allow your facility to power equipment only when
needed. For many facilities, this eliminates the waste of lighting, heating, and
cooling portions of the building that are not used around-the-clock. Optimized
controls enhance your buildings current mechanical systems and increase your
ability to manage comfort and air quality throughout the building. By reducing
unnecessary use of equipment, energy management systems can prolong the life of
your buildings mechanical and lighting systems, and reduce maintenance
costs [1].
Energy Conservation in Residential, Commercial, and Industrial Facilities, First Edition.
Edited by Hossam A. Gabbar.
2018 The Institute of Electrical and Electronics Engineers, Inc. Published 2018 by John Wiley & Sons, Inc.
CH02 05/04/2018 16:42:41 Page 16
A wide variety of systems and methodologies have been proposed in the
literature to address the issue of decreasing energy consumption in residential and
commercial buildings [25]. These proposals are based on different yet comple-
mentary perspectives, and often take an interdisciplinary approach, which makes it
hard to obtain a comprehensive view of the state of the art in the energy
management of buildings.
The lack of a structured and unifying view over the available approaches and
methodologies to be adopted during the design of such energy-aware systems was
the main trigger for undertaking the research underlying this survey. We speci-
cally focused on the underlying architectures and methodologies, as well as on the
necessary techniques that go beyond the well-established smart home paradigm,
thus progressing toward intelligent building management systems (BMSs), in
accordance with the ambient intelligence (AMI) vision. The ideal application
scenario for AMI considers the user as the focus of a pervasive environment
augmented with sensors and actuators, where an intelligent system monitors
environmental conditions and takes proper actions to satisfy user requirements [6].
AMI systems are characterized by a low intrusiveness and by the capability to
adapt themselves to the usersbehavior and to anticipate their requirements. In the
specic context of a BMS for energy saving, this visionary goal becomes even
more complex due to the presence of contrasting goals, that is, a satisfaction of user
requirements by minimization of the consumed electrical energy. Throughout this
review of literature, the main components constituting a BMS will be identied,
namely, a sensory infrastructure for monitoring energy consumption and environ-
mental features, a data processing software for processing sensory data and
performing energy-saving strategies, a subsystem for user interactive interface,
and an actuation infrastructure for modifying the environmental state. The different
solutions presented in the literature will analyze for each component. Whenever
possible, qualitative comparisons of various approaches will be provided with
respect to their specic features.
To qualitatively evaluate different BEMS, a set of relevant characteristics will be
identied. Through this assessment procedure, the end users have a relevant role;
besides being affected by too tough energy-saving policies, users might be bothered
by other structural features, such as a set of instrumental devices, or by algorithmic
features, such as learning methods that force them to have a continuous interaction.
However, we will refer to these topics such as the user comfort,and we will
underline the characteristics of various BEMS solutions in terms of scalability and
complexity of the system architecture [7], the intrusiveness of the deployed sensory
and actuating devices, and the expected inuence of technology on user comfort.
The BEMS software provides monitoring, control functions, and alarms and
enables the operators to optimize building performance. BEMS are vital compo-
nents for managing energy demand, in particular in large complex buildings and
multibuilding sites [8].
Digital and analog input signals transfer to the BEMS the values of temperature,
humidity, and so on the building is running at. Inputs might also contain whether
CH02 05/04/2018 16:42:41 Page 17
equipment like fans, pumps, and boilers are working or not. Analog/digital outputs
then transmit signals from the central supervisory controller PC to site equipment
such as pumps, valves, fans, and so on to command their settings or to switch
devices on and off, resulting in variation in comfort conditions. BEMS can be used
to control very nearly anything and it is being widely used to control lighting and to
monitor critical systems. Outstations programs automatically provide the local
hubs to connect these inputs and outputs into the central supervisory master station
(see Figure 2.1).
This enables the operator to program when things automatically switch on and off
and what setting they operate at, for example, temperature, pressure, and humidity. A
BEMS is really a tool for monitoring and controlling the building and a good operator
can use the BEMS to optimize settings to maximize energy saving without com-
promising comfort and services. The outstations plants are usually linked through a
local area network (LAN). Software normally support a graphical user interface
GUI or humanmachine interfaces HMI that is based on images of the plant being
controlled. These dynamic displays offer real-time plant operation conditions that
give an instantaneous window on what is happening in the building, which is called
event loggers. As a core function, BEMS would control heating system, boilers, and
pumps and then locally control the mixture of heat to achieve the optimum required
room temperature. In air-conditioned buildings, BEMS would control chillers,
cooling systems, and the systems thatspread air throughout the building (for example,
by operating fans or opening/closing dampers). BEMS can also control lighting or
any other energy-consuming equipment and can also be used to log energy meters.
FIGURE 2.1 Typical structure of a BEMS.
CH02 05/04/2018 16:42:41 Page 18
Modern systems have distributed intelligence in the outstations and also allow
multisite data acquisition and control with remote monitoring via the wireless,
telephone network, and satellite systems. They are increasingly becoming con-
nected to smart devices like palmtop devices and mobile phones with alarms that
tell on-call staff of problems or events in the building. BEMS can signicantly
promote the overall management and performance of buildings, promoting a
holistic approach to controls and supporting operational feedback. Energy savings
of 1020% can be achieved by installing a BEMS compared with independent
controllers for each system. However, BEMS cannot recompense for wrongly
designed systems, incorrect maintenance, or poor management.
BEMS are ideal for providing control of multibuilding sites and large complex
buildings. They are also used by large organizations to control buildings spread
across wide areas like whole local authorities, health trusts, and even remote
buildings across the whole country. Modern systems have intelligent outstations
that can be investigated locally in a plant room to track down local problems. They
can also have wireless connections to some devices to reduce or avoid cabling. A
BEMS needs to be well specied and designed, with good documentation and an
intuitive graphical user interface if it is to be used efciently. In very small
buildings, it is possible to achieve reasonable control using stand-alone controls for
lighting, heating, and so on and this may be a cheaper option than a full BEMS.
However, costs of controls have come down such that mini-BEMS are now
competitive and hybrid systems that interconnect a series of local controllers are
also available. So BEMS can be considered for controlling almost any size of
buildings, but the improvement in management really becomes apparent in large
distributed and complex sites/buildings. Ensuring good user interfaces with a
BEMS is essential. Modern BEMS can be accessed in a number of ways (see
Figure 2.2), for example, through web browsers via the Internet, through hand-held
tablets and laptops, or through palm devices and smart mobile phones. Providing
convenient access routes allows building operators to use the BEMS in a way that
ts their role and the way they work and encourages them to utilize the system as a
building optimization tool. Poor access or a lack of feedback normally results in
facilities managers leaving the BEMS ignored in a corner of the operations room as
a silent controller rather than a window into the buildings performance. To
optimize internal conditions and make ongoing savings, BEMS need to be
regularly maintained. BEMS settings need to be checked at least every month
and check that settings meet actual building requirements. When inspecting the
system, focus on the following:
General: Check the integrity of any cabling and connections and any cabinets
or panels in the installation.
Sensors: Test accuracy and review the suitability of their locations.
Actuators: Examine control outputs and ensure that controlled devices are
working over their full operating range.
Digital inputs: Conrm that inputs are operational and working correctly.
CH02 05/04/2018 16:42:41 Page 19
Calibrate or adjust switching devices if necessary:
Controllers: Verify that battery supplies are adequate and that controllers
automatically restart the following interruption to power supplies.
Record-Keeping: Document key changes to the BEMS, including any
alterations to set points and control strategies, software upgrades, additions
to the network, any faults identied, or maintenance performed.
Maintaining controls really matters and underpins the building performance.
The preferred maintenance regimes need to be determined at the beginning of
the project. The important question to be answered by the client is whether they
an independent installation (independent of the control manufacturer) with a
separate maintenance contract that can be moved according to contractual
It is important that the BEMS maintenance contractor is consulted at the start of
the build, during the design, and retained by the client to provide maintenance for
the nished building. The on-site maintenance team can then have a good
relationship with the controls subcontractor, allowing them to use continuous
commissioning and rectify faults quickly.
FIGURE 2.2 Typical BEMS user interfaces.
CH02 05/04/2018 16:42:41 Page 20
BEMS can achieve lower running costs, improved comfort, maintenance, and
building management through better system feedback on the performance of
building on energy utilization and comfort. The monitoring facilities of a BEMS
enable monitoring of plant status, environmental conditions, and energy utiliza-
tion, providing the building operator with a real-time reporting of the building
operation process. This can often lead to the identication of problems that may
have gone unnoticed, for example, high-energy usage or plant left running
continuously. Energy meters connected to a BEMS, providing real-time energy
consumption patterns and ultimately a historical record of the buildings energy
performance, can be logged and analyzed in a number of ways, both numerically
and graphically. BEMS can, therefore, improve management information by trend
logging performance, beneting forward planning/costing. This can also encour-
age greater awareness of energy efciency among staff. Energy efciency
improvements of 1020% are common. However, it is important to establish
the suitability of existing buildings and equipment to ensure the maximum savings.
For a BEMS to work effectively in an existing building, it must be possible to zone
the heating, ventilation, and lighting systems according to the use made in different
The main advantage of a BEMS installation is the ease with which users can
review the performance of controls and conveniently make adjustments. Other
advantages include the following:
Close control of environmental conditions, providing better comfort for
Energy-saving control functions that will reduce energy bills (e.g., weather
Ability to log and archive data for energy management purposes.
Provision of events or rapid information on plant status.
Automatic generation of system alarms for equipment failure or violation of
normal condition.
Identication of both planned and unplanned maintenance requirements
(e.g., systems can record the number of hours that motors have run, or
identify lters on air supply systems that have become blocked).
Ease of expansion to control other plant, spaces, or buildings.
Once a BEMS has been installed and fully commissioned properly, it can be
used as a tool to optimize building performance. Even the best designed and
commissioned control strategy is likely to evolve with the users and the buildings
requirements. A well-trained BEMS operator can carry out regular reviews of
BEMS settings to gradually reduce room set points, operating times, and energy
consumption without compromising comfort conditions.
This ne-tuning of the building controls often requires one or two full heating
seasons to reach optimum settings. But the process does not end here: As the
CH02 05/04/2018 16:42:41 Page 21
building usage and requirements change, so will set points and times; so this
optimization is a continuous process as the building use changes.
This optimization process is particularly important where BEMS are controlling
large multibuilding sites and buildings spread across a wide area. The BEMS
operator can keep a watchful eye on operations and energy use from afar without
having to visit the buildings. This central BEMS bureau approach is highly cost-
effective and common in large estates and through FM providers.
As a result of this continuous optimization, it is important to maintain records of
all changes to the system during the lifetime of the building with good reasons as to
why changes have been made. Too many buildings have high operating hours and
set points that have been badly programmed many years ago often as a result of
occupant complaints. It is still very common to nd buildings fully on running
everything at high levels for 24 ×7, where just a little optimization can save a lot of
energy, money, and carbon emissions with little or no investment.
A BEMS is only as good as the people who use it. It is essential that staff who
will be operating and maintaining the system are trained appropriately. All
reputable BEMS suppliers can provide and do encourage training as it is in their
interest that the system works well. If installing a new BEMS involves key staff at
the beginning of the project, ensure that they are aware of what the system can do
and how to keep it performing efciently.
Access through mobiles: It is essential to train staff to use the BEMS as a tool to
manage the building. Ensuring staff have easy access through mobile devices can
encourage this. The greater the understanding, the more likely the energy savings.
This will involve training on the BEMS hardware and the software built into the
BEMS. BEMS is a powerful tool for managing buildings, but it is still only as good
as the staff operating it! All staff with access to the BEMS should develop
experience in managing the building using it on a routine basis. Most BEMS have
alarms set and staff should know what to do when these alarms show on the central
As discussed earlier, in existing systems an annual review of control settings is
essential and also important to ensure that the system is optimized in relation to the
occupancy and requirement of the building. However, too many building operators
leave this to the maintenance contractor under an annual contract. This often results
in the building management relinquishing their responsibilities to the BEMS
contractor and the building gradually drifts away from optimized settings. The
provision for future retraining in the event of staff changes is very important to
minimize this day-to-day reliance on suppliers for simple maintenance measures.
Ensuring suitable BEMS user documentation for system fault nding and mainte-
nance also plays a key part in this common mistake.
A BEMS installation is very site specic. Larger systems may require a
feasibility study to identify the size, shape, and complexity of the BEMS required.
This will establish what is to be controlled and monitored, the connections,
hardware, and cabling required and the resulting benets. It will also establish
the architecture of the system, ring-shaped, star-shaped, and so on, and the location
CH02 05/04/2018 16:42:41 Page 22
and capacity required in the outstation. The nancial justication for a BEMS
should ideally include a full life cycle costing calculation based on discounted cash
ow. Estimates of potential savings should, where possible, account for contribu-
tions from improved maintenance and increased reliability, in addition to reduced
energy consumption.
Planning and designing good controls at the outset is essential to achieving a
good building. A clients brief for a good control system aims for energy efciency
while maintaining comfort. Designersspecications need to set out the key energy
features, so contractors appreciate what the control system needs to do. Low
carbon buildings are best achieved when clients state an aim to have a low carbon
building in operation in the client brief. The design, selection, installation, and
operation of the resultant control system relate directly to these initial statements.
Without such clear directions to the design team, a low carbon building is seldom
The scope for system expansion at each outstation should be carefully
considered. Often the addition of a single point may require a complete outstation
at considerable cost if all points on the original are occupied. If you already have a
BEMS, then an upgrade or even extending it may bring very signicant advan-
tages. Really old systems may well need full replacement and may no longer be
supported by the manufacturers. It is possible to connect meters to a BEMS for
logging energy to provide a valuable tool for identifying savings. However, where
larger buildings/sites are being submetered, it may often be better to have a
dedicated automatic meter reading system with specialist software for meter
logging, analysis, and reporting. How well your BEMS performs is reliant on
a clear brief, good design, followed by good installation/commissioning. Some
BEMS manufacturers offer their own design/installation service and some may
even insist on this; others work with approved contractors. Either way, you should
ask for references from sites similar to your own.
Building energy management systems are computer-based systems that help to
manage, control, and monitor building technical services (HVAC, lighting, etc.)
and the energy consumption by devices used in the building. They provide the
information and the tools that building managers need both to understand the
energy usage of their buildings and to control and improve their buildingsenergy
Building management system offers dependable and user-friendly building
control solutions to commercial, education, health care, leisure buildings, and
more as shown in Figure 2.3. This includes delivering the worlds fully integrated
building solution encompassing HVAC, lighting, and access products.
The building automation is geared toward energy management that has been
one of the key concerns of every building owner. Having a healthy and productive
CH02 05/04/2018 16:42:41 Page 23
FIGURE 2.3 Overview of BEMS.
CH02 05/04/2018 16:42:42 Page 24
environment while keeping your energy costs and your carbon footprint down
makes your facility more valuable. Building automation offers complete end-to-
end energy management solutions as shown in Figure 2.4. It helps in energy
consumption reduction and save money.
The integrated building automation solutions are designed to simplify the
management and protection of industrial, commercial, and residential buildings.
These solutions answer to the rising emphasis on producing green facilities. BMS
buildings can not only achieve certication but also perform at high levels with
operational cost savings to property owners and managers. This solution can be
implemented in both existing and new buildings. The building management
system is an intelligent and integrated system for HVAC, re, security, and access
management in a building, as shown in Figure 2.5.
The BEMS sector is growing as organizations realize that it is one of the
most effective solutions for optimizing energy efciency in a building
providing the quick win that organizations are seeking. Energy managers and
building owners might have previously installed systems in larger buildings, but
new-generation technologies can cost-effectively extend the savings even to
smaller buildings.
FIGURE 2.3 (Continued )
CH02 05/04/2018 16:42:42 Page 25
Greater energy efciency and cost reduction is the main driver, but modern new
systems also have the dual benet of acting as an automatic monitoring and
targeting system, monitoring, measuring, and analyzing consumption to assist with
carbon reporting and managing efciency. This enables users to collate, analyze,
and transform these data into meaningful information, allowing them to monitor
energy consumption, identify waste, and highlight areas for improvement and
benchmark consumption against other similar buildings or organizations.
Automatic monitoring and targeting are particularly useful in monitoring
multiple sites, enabling managers to gain both detailed analysis and a big picture
overview of energy consumption across the business, while drilling down into
specic locations. The reporting capabilities of some BEMS are necessary to meet
increasing environmental legislation, such as the CRC energy efciency scheme.
The best systems will typically reduce consumption by 25% to deliver rapid
payback on investment and reduce taxes on carbon emissions. Return on invest-
ment for typical system can be achieved within 1260 months. Recent installations
of BMS for boiler-optimized controls have delivered savings of 2854% giving an
indication of the energy savings from installing a BEMS by using our energy
savings calculator.
The increased drive to energy efciency coupled with reluctance by organiza-
tions to make any capital expenditure has prompted innovative nancial models to
FIGURE 2.4 Building automation solution with energy management.
CH02 05/04/2018 16:42:42 Page 26
increase access to new technologies. Guaranteed Savings Contract is an energy
performance contract scheme that provides the option of procuring energy controls
technology on a pay-as-you-savebasis. Organizations can then benet from
immediate energy savings without any capital investment or installation and
commissioning costs. As part of the energy performance contract, energy and
operational cost savings offset the investment.
The two acronyms tend to be misused to describe the same thing; however,
BMS provide a computer-based system that seeks to integrate a comprehensive
range of building services. These services can integrate building controls and
FIGURE 2.5 The integrated building management system.
CH02 05/04/2018 16:42:42 Page 27
monitoring, covering such systems as mechanical and electrical equipment,
HVAC, lighting, power systems, re systems, and security systems.
BEMS are generally designed to provide a totally integrated computerized
control and monitoring systems of energy-related plant and equipment such as
HVAC and lighting, but would not normally provide for the integration of systems
such as re and security as these are not considered to be energy-related systems.
Critical parts of the BEMS hardware and software can deteriorate without
regular servicing or maintenance. For example, temperature sensors can deteriorate
and fall outside their calibration accuracy or simply become broken or damaged;
control dampers and valves can fail to function correctly due to age or wear. The
other most common problems occur with temperature dead bands and free cooling
options. In addition, control software can become out dated. Ultimately, failure to
address problems means that the BEMS no longer serves the intended purpose and
is relegated to serving as a gloried time clock to start/stop the energy systems
thus failing to deliver the original intention of energy, CO
and cost savings.
Many organizations are wasting energy through inefcient boilers. This is
because typical boilers will often re up and consume energy when it is not
necessary to do so instead of using the residual heat that is already available
within the system. This is known as dry cyclingand can add more than 30% to
the cost of an organizations heating bill. Building energy management systems
include boiler optimizer controls to ensure that the boiler is demand driven and
only operates when required, and only at the temperature required to satisfy
demand. This reduces energy consumption and avoids unnecessary wear of the
After introducing the general architecture of a BMS for energy efciency and
briey describing the main functionalities it should implement, we now survey a
number of architectural solutions proposed in the literature, and we analyze and
compare them from different viewpoints, such as architectural model (e.g.,
centralized versus distributed), internal organization (e.g., single layer versus
multilayer), networking protocols, ability to support heterogeneity in sensing
technologies, and so on. Moreover, we compare different solutions with respect to
such software quality attributes as modularity,extensibility, and interoperability.
2.4.1 Plain Support for Energy Awareness
The rst considered solution is a monitoring system based on Web-enabled power
outlets [8]. Since the system is only intended to stimulate user awareness to energy
consumption, there is no actuation infrastructure. A Web-based user interaction
interface is responsible for sending appropriate notication messages to the user.
Each appliance is connected to a power outlet, that is, a power meter that measures
CH02 05/04/2018 16:42:42 Page 28
the energy consumption of the appliance and sends the acquired information to a
Gateway, using a standard communication protocol (e.g., Bluetooth or ZigBee).
By providing an Application Programming Interface (API), the Gateway seam-
lessly integrates the smart power outlets into the Web [9]. This allows users to
easily access their energy consumption through a Web browser. At the same time,
it opens the system to application developers. Such an approach would appear
overly simplistic with respect to the ideal BMS; complete focus on energy
monitoring does not allow relating consumption to the current environmental
state, nor does it allow automatically controlling actuators. A very ne-grained
energy monitoring by unintrusive devices would, on the other hand, be advisable
for the realization of an ideal BMS, possibly based on a more complex architecture.
In the previous solution, the integration of power outlets with the World Wide
Web is mediated through an intermediate gateway. A further evolution consists of
a direct integration of power meters, and possibly any other smart device, by
exploiting theWeb-of-Things (WoT) paradigm. The latter is the extension of the
well-known Internet of Things (IoT) paradigm to the Web [10,11]. Following the
WoT approach, any smart object (e.g., power meter, sensor, actuator) hosts a tiny
web server. Hence, it can be fully integrated into the Web by reusing and adapting
technologies and patterns commonly used for traditional Web content. An
application framework for a smart home following the WoT paradigms has
been proposed in Home Web [11]; this solution is characterized by some degree
of modularity because it is based on a Web-service approach. The solutions
discussed so far rely on a centralized architecture and are able to support
heterogeneous embedded devices, thus providing a basic support for inter-
operability and extensibility, even if these potential characteristics are not fully
2.4.2 Integration of Actuators and Environmental Sensors
A centralized architecture consisting of a central server that interacts with
heterogeneous sensory and actuator devices is also implemented (Figure 2.6).
Specically, a Wireless Sensor Network (WSN) is used to monitor environ-
mental conditions and to measure energy consumptions, while actuation is
performed by X10 [X10 2013] devices connected to the server via power
line communication (PLC). Since wireless sensors have a limited transmission
range, they may not be able to communicate directly with the server. Hence, to
extend the system coverage, sensing devices send their data to a local base
station. Base stations are then connected to the server through an Ethernet high-
speed LAN.
Rules are dened by the system administrator by means of a high-level
language and translated into service requests for the actuators. iPower paves the
way for an interoperable, modular, and extensible solution. The iPower solution,
despite the adoption of slightly more intrusive sensors and actuators, allows
monitoring environmental quantities, besides energy consumption; moreover, a
CH02 05/04/2018 16:42:42 Page 29
hierarchical organization vouches for medium scalability. However, it is our
belief that a greater effort is necessary in terms of scalability, also with respect
to the software components devoted to reasoning. The rule-based engine
guarantees a coherent source of reasoning, albeit a reactive one, and does
not support the prediction. Finally, the actuating infrastructure appears too
simple to enact automatic control of actuators, and merely allows tuning their
supply power.
A centralized approach, similar to that used in iPower, is also considered by
Green-Building [12]. Unlike iPower,Green Building uses an unstructured (i.e.,
single-tier) architecture and combines the energy monitoring and control func-
tionalities into a single infrastructure (i.e., power meters are also actuators). In
addition, sensing devices for environmental monitoring can be fully integrated
into the same unique wireless infrastructure. A similar solution is also proposed
in Ref. [13], where a prototype of a wireless actuation module is presented that
can be fully integrated within the monitoring WSN. Using a single (wireless)
infrastructure for monitoring and control lessens the burden of technology
integration. On the other hand, it reduces the exibility in deciding the
granularity of the monitoring/control process. As for iPower, this architectural
solution aims at the right direction but does not appear fully adequate yet
because of the simple actuating system and the lack of explicit support for
intelligent reasoning.
FIGURE 2.6 BMS architecture.
CH02 05/04/2018 16:42:44 Page 30
Energy systems monitoring can be classied according to various criteria, for
example, the type of sensors they use, or the spatial granularity used for collecting
data. With respect to sensors, it is possible to distinguish between direct,indirect,
and hybrid monitoring systems. Direct monitoring systems use electricity sensors
for directly measuring energy consumption, while indirect systems infer energy
consumption by measuring other quantities such as temperature and/or noise.
Finally, hybrid systems rely on both approaches. Direct monitoring systems can be
further classied into ne-grained,medium-grained, and coarse-grained systems,
depending on the level of spatial granularity they use in collecting data about
electrical energy consumption. The taxonomy is graphically summarized in
Figure 2.7.
2.5.1 Indirect Monitoring
As expected, indirect monitoring systems are so called because they do not use
electricity sensors for measuring the energy consumption of appliances. Instead,
they indirectly infer information about energy consumption by measuring other
physical quantities that are somewhat related to energy consumption.
This approach leverages the fact that appliances typically affect other observ-
able environmental variables, such as temperature, ambient noise, vibrations, or
electromagnetic eld. Specically, data provided by sensors are combined with a
consumption model of the appliance in order to obtain an estimate of its energy
consumption. An indirect monitoring system is proposed in Ref. [14], where a
wireless sensor network is used to measure physical quantities such as noise,
temperature, and vibrations. Each appliance is identied by a specic pattern of its
sensory measurements. For instance, switching on a kettle is associated with the
temperature rising, a variation in vibration, and ambient noise. However, the paper
does not specify how the system is provided with the association between sensory
patterns and specic operating appliance; additionally, the simplicity of this
Energy systems
energy monitoring
energy monitoring
energy monitoring
FIGURE 2.7 Taxonomy of energy monitoring systems.
CH02 05/04/2018 16:42:44 Page 31
approach limits its applicability to feedback-based systems. Given the use of
signature-based models for environmental measurements, this solution could be
viable in centralized intelligence architectures, using a distributed sensor
Whenever a model for appliance energy consumption is available, any system
capable of automatically detecting appliances could be used for performing
indirect energy monitoring. These systems include the approach proposed in
Ref. [15], which exploits information coming from the energy distribution net-
work, other than explicit energy consumption. The proposed approach analyzes
high-frequency electromagnetic interferences generated by the electronic devices
powered through a switch-mode power supply (SMPS) (used in uorescent
lighting and in many electronic devices). Due to the limited applicability to a
specic class of actuators, such technology should be just regarded as comple-
mentary to the energy monitoring system. For instance, this approach could be
suitable for fully centralized architectures where the pervasiveness of sensory
devices is minimal.
With reference to the ideal BMS, indirect energy monitoring systems are not
suitable because their use would require building models for actuators, which,
especially when environmental measurements are involved, would have to be done
in situ, thus being invasive for users, not well generalizable, and consequently
slowing down the deployment of the entire BMS.
2.5.2 Direct Monitoring
Unlike indirect systems, direct monitoring system measures energy consumption
through ad hoc electricity sensors, typically referred to as power meters. The
granularity used for direct energy monitoring spans from a single point of metering
to the monitoring of individual appliances. The rationale for using only a single
power meter is keeping intrusiveness at a very low level. These coarse-grained
systems are referred to as NILM (non-intrusive load monitoring) systems, or
NALM (non-intrusive application load monitoring) systems if the focus is on
individual appliances.
On the opposite end, ne-grained systems allow monitoring individual appli-
ances with a high precision but require the deployment of a large number of power
meters. Obviously, the granularity of monitoring affects the approach to the
articial reasoning carried on the collected sensory data and, indirectly, also
the possible energy-saving policies that can be used.
Such detailed monitoring, not available in the approaches mentioned so far, is
useful to avoid using consumption models for those appliances, thus eliminating
the initial training phase with its costs in terms of user discomfort.
2.5.3 Hybrid Monitoring
Finally, a hybrid approach to monitoring, including both direct and indirect parts,
involves using both specic sensors for energy measurement (typically in a single
CH02 05/04/2018 16:42:44 Page 32
power meter at the root of the distribution tree) and indirect sensors for recognizing
the operating status of appliances. A monitoring system based on WSNs with
magnetic, light, and noise sensors and including a power meter is used for
monitoring the overall energy consumption. An automated calibration method
integrates two types of models for learning the combination of appliances that best
ts the collected sensory data and the global consumption. Specically, a model of
the inuence of magnetic eld, depending on two a priori unknown calibration
parameters, is used for more complex appliances with many operating modes. On
the contrary, appliances with fewer operating modes only require models associ-
ating the relative consumption to each specic mode, which is estimated via the
noise and light sensors. The main disadvantage of this work is that the calibration is
to be performed in situ and cannot be carried out before the deployment because
many unpredictable external factors may inuence the measured environmental
variables. It is worth pointing out that hybrid systems are typically characterized by
a coarse-grained direct monitoring of energy, with a single sensor at the root of the
energy distribution tree. This is usually coupled with a ne-grained indirect
2.5.4 Comparison of Different Energy Monitoring Systems
An ideal BMS that is able to provide an accurate description for actuator
consumption without demanding excessively intrusive deployment naturally calls
for ne-grained direct monitoring. However, when deployment costs are prohibi-
tive, it is possible to reduce the number of used devices and to rely on a
disaggregation technique, starting from the branches of the energy distribution
Figure 2.7 reports a comparison of different energy monitoring systems
together with some of the previously discussed architectural solutions according
to two qualitative dimensions, namely, the overall intrusiveness experienced by
users and the details on attainable monitoring. Values along the rst dimension
were attributed to assess both the intrusiveness of deployed devices and the
discomfort perceived by the users during the training phase, while the second
dimension is tightly related to the position of the assessed solutions within the
taxonomy depicted in Figure 2.7. Note that, as regard the sensory infrastructure,
costs get higher as the systems get closer to the ideal one. When it is important to
keep installation costs below a given threshold, it will be necessary to trade part of
the functionalities of the nal BMS for cost.
2.5.5 Devices for Energy Sensing
Besides the different approaches to energy monitoring, it is also necessary to
consider the technology to be used for creating the sensory infrastructure. In this
section, we will mainly focus on the available technologies for energy sensing.
However, we will not consider sensors for environmental monitoring, as they are
CH02 05/04/2018 16:42:44 Page 33
beyond the scope of this survey, although they are exploited into indirect and
hybrid monitoring systems. A wide selection of sensor technologies for energy
sensing is currently available on the shelf. The choice of a given technology
directly affects the complexity of the architecture supporting the monitoring
system and providing the integration with the rest of the BMS. Energy consump-
tion models of individual appliances represent an alternative tool for energy
monitoring, as they allow estimating the overall energy consumption of buildings
simply relying on the knowledge about the status of each appliance (i.e., without
requiring any specic sensing infrastructure). For some devices, the corresponding
energy consumption in different operating modes can be retrieved from their
technical specications, such as the Code of Conduct (CoC) edited by the
European Commission, which, however, do not cover the entire set of available
2.5.6 Integrated Control of Active and Passive Heating, Cooling,
Lighting, Shading, and Ventilation Systems
Buildings account for nearly 40% of global energy consumption [7]. Of this, about
40 and 15% are consumed by HVAC and lighting systems, respectively. In view of
the increasing energy cost, government mandates for energy efciency [8], and the
rising human comfort requirements, controlling shading blinds and natural venti-
lation to make effective use of natural resources can reduce energy consumption
and is therefore of great interest [9,10]. In addition, improving the HVAC control
can also result in signicant cost savings [11]. HVACs, lights, shading blinds, and
natural ventilation interact with each other in energy consumption via thermal
phenomena and in satisfying human comfort requirements for temperature,
humidity, fresh air quantied by CO concentration, and illuminance in each
room. As shown in Figure 2.8, the indoor temperature is affected by all the
above-mentioned devices; both indoor humidity and CO concentration are affected
by HVAC and natural ventilation, and illuminance by lights and shading blinds. In
summer, for example, if blinds are open for using the daylight, energy consump-
tion of lights is reduced. However, energy consumed by HVAC will increase due
to the increased solar heat brought by inlet sunlight [9]. Therefore, the control of
FIGURE 2.8 Couplings of different devices on human comfort. T: temperature,
H: humidity; I: illuminance; C: CO concentration.
CH02 05/04/2018 16:42:44 Page 34
blinds must consider not only the energy consumption of lights but also that of
HVAC. Integrated control of these devices is important to manage such inter-
actions. In addition, individual rooms share an HVAC system and are coupled in
competing for its limited capacity. Integrated control of these devices is therefore
also important for preventing the cooling demand from exceeding HVAC capacity
and essential for human comfort [11]. In most of the buildings, active and passive
sources of heating, cooling, lighting, shading, and ventilation, however, are not
coordinated. Analytical studies on their optimal integrated control have not been
found in the literature. Possible reasons might be that (i) it is difcult to establish
models that have a good balance between accuracy and simplicity for optimization;
(ii) models are difcult to calibrate [16]; and (iii) the interactions between devices
and the coupling among rooms make it time-consuming to search for the optimal or
effective control strategy.
2.5.7 Electricity Network Architectures
Traditional electrical power system architectures reect historical strategic policy
drivers for building large-scale, centralized, thermal (hydrocarbon and nuclear)-
based power stations providing bulk energy supplies for loading centers through
integrated electricity transmission (high voltage: 400, 275, and 132 kV) and
distribution (medium, low voltage: 33, 11, 3.3 and 440 V) three-phase systems.
In the mature economies, these designs have been predominant, but as a result of
industry restructuring and international policy drivers for low-carbon renewable
energy production, they have been underinvested and are now in question as to
their future sustainability with regard to anticipated future energy scenarios that
may compromise their ability to support innovation. The hierarchical control
structures for these traditional designs differ across the transmission and distribu-
tion levels with greater automation (and complexity) obvious at the high-voltage
levels, with centralized control-room-based operational management and reason-
ably pervasive communications capabilities for automatic control and system
protection. At the distribution level, conventional network design has led to less
sophisticated system control and management structures with lower levels of
automation in place. Figure 2.9 indicates the high-level changes emerging in
electrical power system architectures in response to managing aging assets and
increasing levels of distributed generation connections. Given the signicant
growth and penetration of renewable sources and other forms of distributed
generation, there are now increasing pressures on distribution networks to cope
with new system stability (voltage, transient, and dynamic), power quality, and
network operational challenges brought about by embedding generation sources
that would have been, more typically, larger scale, thermal, and connected to the
grid at the transmission levels. Consequently, we are approaching a problem
inversion situation where, similar to conventional transmission networks, more
active network strategies and technologies will be required at the distribution
level. Figure 2.9 presents a number of issues in network management and the
CH02 05/04/2018 16:42:44 Page 35
resulting changes to conventional methods of system control. The term active
is signicant because the medium-voltage distribution network (unlike the high-
voltage transmission net- work) has traditionally been a passive means to pass
power from bulk supply points to customers. The quality of supply has been
ensured by planning a degree of redundancy and by some centralized ability to
switch connection points. Single-circuit radial distribution lines are vulnerable to
faults and the rst priority of power system protection schemes is to isolate
faulted sections and plant. Restoration of customers that are off supply can be a
relatively lengthy process because automated restoration relies on methods run
by controllers that are written for only a small number of scenarios. If the
scenarios do not apply, then restoration is through manual control. Voltage
proles in the network are assessed at the planning stage and transformer tap-
changers (perhaps with line-drop compensation) used to accommodate load
The inclusion of distributed generation sources calls for a greater degree of
control, including control of distributed generation reactive power. It is therefore
not straightforward to integrate new distributed generation and effect its connec-
tion to the network. Without active network management, the full network capacity
FIGURE 2.9 Evolution of electrical power system architectures.
CH02 05/04/2018 16:42:45 Page 36
potential cannot be realized. Active network management is about the integration
of distributed generation into network control with greater coordination of power
system operation, rather than its straightforward connection. Active network
management can also make use of other distributed resource, such as storage,
to relieve constraints that arise in networks where energy use and demand patterns
have changed. Technical analyses have demonstrated that by employing active
network management methods, distribution networks can accommodate about
three times more distributed generation connections than equivalent networks
without active management (Figure 2.10).
Building energy management systems have the ability to save energy and improve
productivity by creating a comfortable working environment. Our worldis currently
facing two particularly important trends: rising fossil fuel prices and concerns about
climate change. Both create strong incentives for energy conservation.
The World Business Council for Sustainable Development identied buildings
as one of the ve main energy users, where mega-trendsare needed to transform
energy efciency. Buildings account for 40% of primary energy in most countries
and consumption is rising. The International Energy Agency (IEA) estimates that
for buildings, current trends in energy demand will stimulate approximately half
the energy supply investments through 2030.
Building energy management systems have the ability to save energy and
improve productivity by creating a comfortable working environment. BEMS
FIGURE 2.10 A schematic of a semiautonomous power system or power cell capable of
managed islanding from the main grid.
CH02 05/04/2018 16:42:45 Page 37
optimization create improved energy management; however, regular building
audits and ne-tuning are necessary to ensure the energy management is main-
tained. The technical strategies for achieving energy savings are summarized while
optimizing occupant comfort. BEMS optimization is dependent on the physical
plant, operator, level of controls, and zoning, as well as the type of environment to
which the system is being applied. This information is targeted to internal energy
savings implementation professionals, looking for a resource to guide them in
changing parameters, tuning building management systems, and recommissioning
existing systems.
2.6.1 Energy Savings Opportunities
The easiest way to create savings is to reappraise and/or relax set points. Caution
must be applied as the changes need to be made in accordance with the overall
building scheme, as the settings may be a crucial part of an overall control strategy.
A shift can be applied in accordance with external conditions; for example, with an
air-conditioned building, the summer set point for cooling can be increased relative
to an increase in outside temperature (within a predened band).
A regular review of set points and modication is an essential part of the
ongoing energy cycle and must be continually reviewed, looking for opportunities
for further savings. When an opportunity for set point savings has been identied,
minor set point changes over a period of time ensure a smooth transition; for
example, a stepped changes of 0.5 °Cor1°F at a time for room temperature.
Shifting/relaxing set points in line with a combination of external conditions
and time/calendar rationalization can typically equate to 520% savings. A set
point reduction can equate to 10% savings per degree on your heating bill, with
potentially higher savings on cooling/chiller bills.
Occupancy-Time Schedule Ensuring your building operates according to
occupancy levels is a key energy saving action and requires continuous reviewing
to ensure the settings are representative. For example, occupancy patterns of
schools and universities continually change due to activities such as after-school
school clubs, evening classes, and so on. It would be easy to apply a carte
blancheapproach, setting a broad range time pattern, but this would equate to
unnecessary periods of heating and cooling. Regular review of occupancy levels
would highlight the possibility to change set points for multiple periods of
occupancy on different days. In addition to a permanent change, the ability to
extend a time operation on a one-shot basis or on a 030 min timer ensures that a
one-off change in occupancy, such as would occur with an unexpected late
meeting, is changed for that one period and then revert to the normal occupancy
Zoning A cost-effective way to save additional energy is to apply further zoning
to areas where there are different occupancy patterns. These zoned areas are only
CH02 05/04/2018 16:42:45 Page 38
heated or cooled when required. Each zone can have occupancy times, compen-
sation, and optimization applied to maximize the savings potential.
Calendar Schedules BEMS offer advanced time scheduling capabilities, and
within this is the ability to apply schedule patterns for different calendar dates. This
enables variable time scheduling to match varying work patterns to be pro-
grammed well in advance. This option can be applied to areas where occupancy
levels are constantly changing week to week, such as exhibition halls or meeting
rooms. Operator time is thus reduced because congurations are made once as
opposed to making changes on a weekly basis.
Holiday/Vacation Periods To ensure energy savings during public holidays
when businesses are closed, holiday schedules are used in conjunction with time
schedules. For example, In the United Kingdom, typically there are eight public
holidays. To determine the energy savings for a commercial property, multiply the
facility availability of 52 weeks by 5 working days =260; therefore, eight public
holidays equates to over 3% possible energy savings.
With an integrated systems approach, a single change to a core time schedule or
holiday schedule can propagate to all integrated systems, including lighting,
security, and access control. This ensures HVAC systems work in empathy
with the actual required occupancy, therefore maximizing energy savings through-
out the building by reducing operating costs.
Optimizers Prior to the introduction of optimizers in the mid-1970s, many
buildings were controlled entirely by a mechanical time clock. These were often
set to switch on the building at a specic time and often assumed the worst
weather conditions, such as heavy snowfall, thus running the buildings central
heating system from the early hours of the morning till the late evening, without
Synonymous with energy savings is the Optimizer.Prior to the introduction
of the BEMS, an optimizer was a stand-alone controller with an outside tempera-
ture sensor located on a north wall and internal space temperature sensor(s). A
temperature rise rate was calculated in accordance with how cold it was outside
and this became a time factor that was tuned based on the heat loss of the building
and the difference between the internal temperature and the desired occupancy
Based on this, the plant was switched on at a time prior to the required
occupancy time, which equated to putting in the optimalamount of energy. The
start time depended on the external temperature, the indoor temperature, and how
much energy was required to meet the desired occupancy space temperature at start
The optimum offfunction that worked the opposite way was the next
innovation to follow. It predicted the off timebased on the external temperature,
the room temperature, and the earliest possible time the building could have its
CH02 05/04/2018 16:42:45 Page 39
heating plant switched off, while still retaining comfort conditions at the end of the
occupancy period.
A low-temperature protection setting is applied to protect the internal fabric
of the building that can be damaged through condensation should the tempera-
ture/humidity condition reach dew point. Optimizers provided typical energy
savings of 525% (potentially higher with cooling/chiller plant) compared
with standard controllers where a limit of 2 h is applied to the start-up time
(Figure 2.11).
The BEMS provides extensive reports on the optimizersoperations and they
must be regularly reviewed to ensure the maximum savings are achieved. This can
be done after different external temperature conditions and on different days of the
week. The BEMS optimizer has additional boostfunctions that may be applied if
the internal temperature did not reach occupancy levels in the previous 24 h, such
as would be the case on a Monday morning. This is enabled automatically to ensure
comfort levels are achieved.
Frost Protection It is fundamental that when a building is switched off either in
normal operation or in holiday/vacation mode, a frost protection strategy is in
place. Frost protection strategies will allow pumps and the heating system to
remain off when the building is not occupied to save energy. The pumps and
heating system will energize when the temperature outside, in the main pipework
or in the space, fall outside of acceptable ranges.
FIGURE 2.11 Desired potential saving.
CH02 05/04/2018 16:42:45 Page 40
Overrides In instances where systems are occasionally manually overridden, a
regular review or identication is essential to ensure energy is not used
Compensation With a water-based system, such as radiators, compensation is
normally applied whereby the temperature in the circuit varies in accordance with
the external temperature. The more the colder outside, the higher the water
temperature in the circuit. There is a minimum and a maximum setting applied.
This must be reviewed regularly or after any overhaul to ensure the compensation
parameters are still representative and prevent overheating, which typically saves
510% on energy use.
Standard compensation can be enhanced by the addition of room inuence,
solar inuence, and wind inuence, whereby a number of sensors are fed back into
the control loop and inuence the set point. This, in turn, provides improved
comfort conditions and prevents overheating. It is important to ensure that the
maximum ΔT(temperature difference) for your system is achieved/maintained for
any boost period to ensure the quickest consistent run-up and boiler efciency.
Outside High Limit A water-based heating system, even with compensation
applied, can be switched off if the outdoor temperature exceeds a preset value
where the difference between internal and external temperatures is minimal or even
negative. Heating is not normally required in a building when the outdoor
temperature exceeds 16 °Cor61°F, depending on the building type. It is important
that hysteresis is applied to prevent plant turning on and off rapidly with a minor
temperature change outside. Hysteresis is a method of control that will keep the
plant turned off until the temperature rises a few degrees above the set point
similar to a household thermostat. Each building is different and the set point
should be calculated accordingly.
A low limit can be applied with cooling to ensure free cooling is used when the
external temperature is below a preset value by closing a cooling valve, zone, or
disabling the primary chilled water plant (see Enthalpy Controlsection). For
example, a chilled water plant is disabled when the external temperature falls
beneath 1214 °Cor5457 °F. Providing cooling is not required for process or
there are no signicant heat sources within the building.
Disable Humidication If the humidity (outdoor moisture content) is above the
required level and satisfactory humidity levels are achieved in the return duct, then
humidication systems can often be disabled. This application must be reviewed
on an individual air-handling unit basis to ensure the control scheme allows this.
Some air handlers rely on 100% humidied air to reheat the supply to the desired
level. Location of people and equipment is a consideration.
Control Stability A lack of stable control increases energy usage by typically
35%, and decreases the life of valves and actuators. Primary heating, chilled
CH02 05/04/2018 16:42:45 Page 41
water, and central air-handling units must provide a stable supply temperature to
their served areas, such as distributed air-handling units, VAV boxes, or fan coil
units. Unstable primary plant and/or the local plant control having incorrect PID
settings cause hunting. Hunting occurs when a system rst overcorrects itself in
one direction and then overcorrects itself in the opposite direction and does not
settle into a stable position. Figure 2.11 shows a graph of unstable control where
the supply temperature increases and then decreases continually. This can cause
overheating followed by overcooling, which may only equate to a slight +/
variation around the temperature set point, but causes mechanical wear and tear, as
well as inefcient energy usage.
By physically watching the control items for movement, the BEMStrend
analysis capability monitors valve positions and assists in the ne-tuning of the
control loop to maximize savings. Unstable control can occur due to changing
plant performances and efciencies. For example, a blocked lter reduces airow.
Regular reviewing of control loop performance is important to highlight failing
loops or those that are hunting.
Air-Handling Systems: Damper Economy Override Most air-handling unit
systems consist of a supply and extract with a recirculation duct with dampers on
each side to recirculate the already heated or air-conditioned return air or to utilize
fresh air as a free cooling source. Fresh air brought into the building is usually set to
axed percentage (typically 10%). By using an air quality sensor in the return duct,
the percentage of fresh air can be reduced when air quality is good, which is
normally at the beginning of a working day, equating to energy savings and
increased occupant productivity. Variable air volume systems need to maintain air
by volume that can be used in conjunction with air quality.
Enthalpy Control Enthalpy is the total heat content of the air. This can be
applied to air-handling unit systems with heating and cooling and humidity
control. The principle is that even though the outside air may be warmer than
the return air, there can be less total heat in kJ/kg of energy. A software algorithm is
used to set this switch and dampers are positioned to utilize the warmeroutside
air that has a lower total heat content (Figure 2.12).
Demand Programming This program will constantly look at the heating and
cooling control valve positions to determine if there is a load on its associated
system. If any (or a low percentage) of the valves are open more than 5%, then the
systems operate normally to satisfy the demands. If all the valves (or a high
percentage) are less than 5% open, then the secondary pumps are disabled.
After a time delay, the primary pumps and main heating or cooling systems
are disabled, provided there are no other load demands from any other systems.
This improves the efciency of the primary system, as it only operates during a
predened time schedule if there is a genuine demand and not just because the
time schedule is on.
CH02 05/04/2018 16:42:45 Page 42
Night Purge/Summer Precooling If the cooling load at the start of building
occupancy is required and if the nighttime external air is cooler than the required
occupancy temperature, then night purge can be applied. This sequence enables
central heating and chilled water plants to be disabled and air-handling unit
systems to run in full fresh air mode for a period of time, typically 30 min, in the
early morning hours, before the sun has risen. This lls the building with fresh,
cool air and reduces the initial load on the primary system at occupancy start.
Flushing the building with fresh air also clears out residual carbon dioxide/vitiated
air and provides building occupants with cleaner air.
Electricity Savings: Load Cycling Load cycling refers to switching off an
electrical load for a period of time on a regular basis. Load cycling can be applied to
background systems, such as a fan or pump so that it will not result in conse-
quential inconvenience. You should override load cycling if conditions exceed a
preset value, such as a low space temperature. For example, if the system is
switched off for 5 min within a 20 min period, then the savings per hour equals
20 min or 25%. When applied, load cycling typically results in 525% savings on
the electricity bill, depending on the size of the plant.
Disadvantages of load cycling are that regularly starting and stopping plant may
cause an increase in electrical load during start-up and could decrease the overall
life of the plant. In these cases, the use of variable speed drives should be
considered (Figure 2.13).
Variable Speed Drives The use of variable speed drives in various aspects of a
building is now prevalent. Many are used mainly as soft start-up and then operate
at a xed speed. The information held within the BEMS can relate to
FIGURE 2.12 Psychrometric chart.
CH02 05/04/2018 16:42:45 Page 43
environmental conditions and occupancy levels from access control, with these
data algorithms relating to demand. For example, varying the air volume through
the working day, based on occupancy levels from the access control or air quality
sensors, ensures that the minimum amount of energy is used on any partially
occupied area of the building. Reducing a 50 Hz motor by 20% to 40 Hz equates to
50% energy reduction.
Maximum Demand Maximum demand sets a limit for the maximum consump-
tion allowed (normally over a 30 min period) and is a cost-reduction measure by
preventing this limit from being exceeded. If anyone exceeds the limit, then a
penaltyis applied to the electricity bill that could equate to paying a higher tariff
per kW/h consumed. Therefore, the aim is to ensure that the maximum demand
limit is not exceeded. Cost reduction associated with maximum demand imple-
mentation can be substantial if demands were regularly exceeded and penalties
A controller is synchronized with the maximum demand meter and forecasts
whether the limit will be exceeded by monitoring the rate of electricity
consumption versus the amount of remaining energy and time. The algorithm
associated with maximum demand is complicated, but the net result is that site-
wide electrical loads are shed if the algorithm predicts the limit will be exceeded.
Electrical loads are reinstated after the danger period has passed. Electrical loads
are shed in rotation per priority level and a matrix enables the choice of load
criticality. The rate at which they are shed and restored is continually reviewed
by the calculations.
The required demand target can be determined using the BEMS if further
reductions in electricity consumption are required. Determining which electrical
FIGURE 2.13 Load cycling for electricity saving.
CH02 05/04/2018 16:42:45 Page 44
loads can be shed can be complicated. The lowest level may be electrical water
heaters, the highest level may be one of a number of chillers, whereby it may be out
of sequence for a period of time as it goes through a shutdown sequence before it is
reintroduced to the control scheme. Indirect reduction of maximum demand could
be applied by overriding the amount that a chilled water control valve can open to.
This would indirectly reduce the load to the chilled water plant and, therefore,
reduce electricity consumption; however, the time the valve takes to do so may not
be practical, but may be possible on parallel routines. The maximum demand
reduction is shown in Figure 2.14.
2.6.2 The Intelligent Building Approach
Intelligent integrated building solutions are becoming standard. Building integra-
tion can include access control, intruder detection, security, chillers, lighting,
digital video, power measurement, variable speed drives, and so on. The integrated
approach provides access to all building systems through one coherent and
customizable user interface. Additionally, building integration reduces training
costs and standardizes alarms and logged data.
Integrated building systems also lower capital expenditures because data
networks are shared, there are fewer computers and servers, and devices have
numerous uses. For example, a passive infrared detector, normally only used by the
intruder systems, can also trigger CCTV recording, relax set points for HVAC
control, and turn off lighting when no occupancy is detected. Another example,
when access control is used to gain entry to a building, this signal is used by the
FIGURE 2.14 Maximum demand reduction.
CH02 05/04/2018 16:42:45 Page 45
lighting control and HVAC systems to change from economy levels to occupied
Ongoing operating expenses are also reduced because there are fewer comput-
ers and networks to maintain and fewer user interfaces, ensuring those who operate
them are more efcient and productive. Integrated control strategies offer extended
energy savings by allowing the building systems to work in empathy with each
other. Using information from all the systems, strategies can be deployed to reduce
the use of energy-consuming devices and create a comfortable and productive
2.6.3 Energy Monitoring, Proling, and Modeling
Energy monitoring, proling, and modeling applications provide the information
needed to make informed decisions based on energy usage patterns. Understanding
and reducing the building base load is a primary step in reducing utility costs. The
required data for energy monitoring application is shown in Figure 2.15. The
system data can be gathered in intervals (15, 30, 60 min) by the electricity utilities
data provider (mandatory where consumption exceeds 100 kW/h in some markets).
Gas and water meters are often connected to spare inputs. With the customers
approval, utility grade data are accessed along with the hardwired or soft-
calculated BEMS meters and are further processed to enable presentation and
data analysis through a secure Internet site. This information can be graphed
throughout the day allowing you to see energy use rise when building systems start
and energy use decrease when occupancy and building use decreases.
FIGURE 2.15 Data required in energy monitoring applications.
CH02 05/04/2018 16:42:46 Page 46
This information is used to validate energy consumption; for example, you can
ensure energy consumption matches the actual occupancy of a building, taking into
account any preheat/cool cycles. The load prole is the focus for energy optimi-
zation to (a) understand and optimize the building base load consumption, (b)
reduce peaks, and (c) reduce daytime use. The ability to compare and benchmark
information by overlaying equivalent days such as a Mondays prole or a specic
weeks prole provides an accurate picture and highlights anomalies for
Modeling enables what-ifscenarios to run on existing data factors. For
example, What if I reduce my energy by 10% between 09:00 and 11:30, or by
16 kW between 17.30 and 19.59?with visual feedback in terms of energy
reduction, CO
, carbon, and so on. The utility modeling cost-reduction techniques
can deliver savings for various industries. The modeling tool is easy to use and is
provided as a web service on a day +1 basis.
Utility performance visibility complements the real-time alarm and controls
facilities of the BEMS software. Importantly, it extends the benets of a single
utility meter, as meters can be soft calculated for smaller areas of the building,
giving additional perspectives of the sites performance, such as a consumption
prole for a given department or tenant, as well as trends and savings achieved
through investments and so on.
Energy Aggregation Energy aggregation is used when there is more than one
site involved. The use of technology can collect, aggregate, and analyze total
energy usage and more importantly the overall consumption prole, spanning all
buildings (Figure 2.16). The data can be used to negotiate improved tariffs; based
on the aggregated prole, signicant savings can be negotiated.
Asmart home may be dened as a well-designed structure with sufcient access to
assets, communication, controls, data, and information technologies for enhancing
the occupantsquality of life through comfort, convenience, reduced costs, and
increased connectivity [12]. The idea has been widely acknowledged for decades,
but few people have ever seen a smart home, and fewer still have occupied one. A
commonly cited reason for this slow growth has been the exorbitant cost associated
with upgrading existing building stock to include smarttechnologies such as
network-connected appliances. However, consumers have historically been will-
ing to incur signicant costs for new communication technologies, such as cellular
telephones, broadband Internet connections, and television services.
A home is already a well-designed connector for power transfer between the
electricity grid and energy-consuming appliances. A smart home also functions as
a switchboard for data ow among appliances and participants such as the end-
user, the electric utility, and a third-party aggregator [17,18]. This evolved
CH02 05/04/2018 16:42:46 Page 47
capability benets stakeholders on both sides of the interface utility customers,
utilities, and third-party energy management rms because there are strong
incentives for all sides to help the others function smoothly. For instance, a
homeowner may not inherently care about the peak demand issues faced by the
utility, but electricity prices and supply reliability are tied to operational practices
of the service provider. On the other hand, a utility may be primarily concerned
with meeting the requirements of public utility commissions, but unhappy rate
payers may result in business and regulatory risks. Looking outward, a smart
residential building has two-way communication with the utility grid, enabled by a
smart meter, so that it can interact dynamically with the grid system, receiving
signals from the service provider and responding to information on usage and
diagnostics. This bidirectional information exchange is enabled by the rapid
adoption of advanced metering infrastructure (AMI).
Looking inward, a smart home employs automated home energy management
(AHEM), an elegant network that self-manages end-use systems based on
information owing from the occupants and the smart meter. The value of
AHEM is in reconciliation of the energy use of connected systems in a house
with the occupants objectives of comfort and cost as well as the information
received from the service provider. Sensors and controls work together via a
wireless home area network (HAN) to gather relevant data [11], process the
information using effective algorithms, and implement control strategies that
FIGURE 2.16 Total energy usage.
CH02 05/04/2018 16:42:46 Page 48
simultaneously co-optimize several objectives: comfort and convenience at mini-
mal cost to the occupant, efciency in energy consumption, and timely response to
the request of the service provider. An example of a smart home is constructed in a
laboratory setting at NREL [16].
2.7.1 Economic Feasibility and Likelihood of Widespread Adoption
Several market and technology trends are expected to accelerate the development
of cost-effective AHEM systems that enable smart homes. These include the
Implementation of smart grids and continued growth in home ofces will
expand market penetration of secure HANs.
Growth in web-based cloud computing applications will enable low-cost
home energy data storage, data display, and data analysis for AHEM trend
analysis [19].
Advancements in smartphone technology such as batteries, user interfaces,
and material [12] are expected to aid the development and adoption of
AHEM systems.
Manufacturers of residential equipment and appliances continue to embed
additional sensors and control capabilities in new, smart home appliances
that are Internet-ready, can respond to requests from service providers, and
offer advanced cycle controls such as multimode or variable speed controls
and fault diagnostic sensors for space-conditioning equipment and eco
modes for dishwashers, clothes washers, and other major appliances [13].
Integration of energy services into other networked product offerings, such as
security systems and television and telephony service.
A key strategy to engaging all stakeholders may lie in changes to the end-user
electricity pricing structures from xed tariffs to dynamic prices that may change
several times over a day that reect the use of the assets on the grid at any given
time. If these structures are implemented to provide a tangible nancial incentive
for customers to respond to the requests of the service providers for demand
reduction, the customers can receive measurable monetary value for their partici-
pation, in addition to the increased reliability of their service. Financial incentives
are but one motivating factor for the adoption of smart homes.
2.7.2 Smart Home Energy Management
Large-scale demonstration efforts have thus far approached smart home research
with a strong utility focus and less homeowner focus. Currently, the incentive for
homeowner participation is limited to relatively small nancial gain via utility
pricing structures; otherwise, the motivation is primarily altruistic (i.e.,
CH02 05/04/2018 16:42:46 Page 49
environmental benets). Most utilities offer incentives for energy upgrades and
many have leveraged load-shedding technologies that cycle air conditioners during
peak load events. Increasingly, utilities are funding more elegant efforts for on-
request load reduction in the residential sector to demonstrate a load reduction
system that can alter air conditioner and water heater set points and pool pump
operation at the end-user facility during peak load times to enable substantial peak
savings with limited impact on their customers [18]. Some utilities provide near-
real-time data to homeowners, along with several pricing structures and load
reduction requests [20]. Many companies have recently incorporated web-based
user interfaces, so a homeowner can adjust thermostat settings or turn off lights
from a smartphone, or a web browser [13].
Advanced grid measurements using AMI infrastructure are being rolled out in
some utilities [21]. These projects have a multipronged focus on better integration
of renewables, enhancement of efciency, and optimization of consumer demands
with utility needs on a community scale. Emerging nonintrusive load measurement
systems can provide enabling data, but these modern measurement techniques are
not yet robust, accurate, easy to install, or cost-effective for integration at the
meter [22]. The available legacy methods for load disaggregation use algorithms
supplemented with estimation; so the results may have less relevance to a given
household than across an aggregated population [22].
2.7.3 Assets and Controls
In smart homes, many loads can be considered as assets that can participate in the
efcient use of electric energy: thermal loads, electric vehicles, and smart
appliances. By intelligently controlling their behavior in either a reactive or a
coordinated manner, these assets can provide leverage for energy and cost
savings [23]. Thermal loads, such as air-conditioning, electric space heating,
and water heating, can be controlled by intelligentthermostats. Contrary to
traditional thermostats operating according to the hysteresis principle, an advanced
thermostat such as the Nest has a learning capability that can automatically learn
from user behavior patterns [24]. Then, the thermostat adapts the room temperature
efciently, for example, by autoscheduling heating according to arrival and
departure times and by detecting when the users are away [24,25]. These strategies
can help reduce energy consumption, especially when traditional or programmable
thermostats are not congured properly, or cannot detect that users are away.
Detailed control of household loads would allow the inherent thermal inertia of
smart housing stock to be used for energy storage. The controller could learnthe
thermal response of the home, including factors such as weather forecasts, weather
observations, and load levels from monitored devices. The resulting model would
better predict future loads, which could be used locally or aggregated for the utility
to plan short-term control options. For example, a smart home controller could
precool a house in the morning, before the system peak load, reducing air-
conditioning loads when signaled from the utility.
CH02 05/04/2018 16:42:46 Page 50
Plug-in electric vehicles, including hybrids, are expected to represent 1.73.5%
of all US light duty vehicles by 2025 [26]. These correspond to a signicant
domestic load interfaced with power electronics that can also help make homes
smarter. Using the vehicle-to-home technology, they can temporarily power the
household, for example, during demand peaks when power may become more
expensive and the battery can provide a part of the total demand, or during outages
by powering the entire household until the battery reaches its lower state-of-charge
threshold [27,28]. Adapting the charging schedule according to grid supply
conditions offers additional possibilities. The utility of such distributed storage
may be improved when used together with distributed generation sources, such as
photovoltaic panels [27].
A growing number of domestic loads use DC power internally, including
electronics, solid-state lighting, and variable-speed motors. Most small, distrib-
uted, renewable energy sources generate DC power, which must be converted to
AC for grid connection. Some recent work has considered household-sized
distributed storage systems for local backup power and ancillary service provi-
sion [29,30]. The convergence of these sources and loads provides an interesting
opportunity for signicant advances in the granular control of loads and high
penetration of small-rated DC-powered assets.
A smart home could also integrate a low-voltage DC bus. Renewable resources,
battery storage, and potentially vehicle charging could all interconnect on a DC
bus. The DC bus would be integrated at a single point, and many inverters and
converters would be reduced to DCDC converters. When high volumes drive
down costs, this simplication could reduce the cost and improve the efciency of
renewable systems, solid-state lighting, and electronic loads. However, this
paradigm shift presents challenges in electrical protection, rewiring, and standard-
ization. At present, standards for DC distribution and usage are being developed,
including 24 and 380 V distribution systems [31]. Use of DC power distribution
remains a retrot challenge for existing US housing stock, but researchers are
studying combined AC/DC distribution using existing building wiring [32].
Appliances also hold potential for smarter energy use. Dishwashers, washing
machines, and clothes dryers can be scheduled in advance, and do not need to be
directly controlled by the user. The starting time can be postponed by several
hours, with no impact on the user as long as the cycle is over when the user
requested it initially. A similar strategy can be used to control freezer and
refrigerator cycle so as to reduce peak demand by coordinating their operation [30].
Finally, many other loads can provide resources for smart energy use and increase
the comfort of the user, including automatic blinds that adjust based on daylight
intensity, adaptive lighting, and autonomous vacuum cleaning robots. These
devices exploit the possibilities offered by the extensive use of sensors, sometimes
forming wireless sensor networks, and actuators controlled by smart, adaptive, and
possibly learning algorithms.
Almost all loads are, or could be, equipped with intelligent controllers, ranging
from simple on/off control of state lighting to sophisticated controllers for
CH02 05/04/2018 16:42:46 Page 51
photovoltaic systems, vehicle chargers, and large loads such as air-conditioning.
With appropriate standardization and high volumes, practical, low-cost commu-
nication systems could connect most loads to a central household controller. The
controller could provide detailed monitoring and control for occupants. With
proper AMI interfacing, the home could further aggregate the resources for system
users, requested by the service provider. A block diagram of the centrally
controlled smart home and its constituent assets is presented in Figure 2.17.
If properly designed, controllers could also monitor loads and identify system
issues, such as unexpected increases in power draw, current harmonics, or
vibration. Signicant value economic and personal could be derived from
identifying issues in advance of catastrophic failure. For many utilities, a smart
meter constitutes a smart grid. For others, these smart meters can be put to greater
use and provide more substantial value to the utility, the grid, and the end-users via
coordination. Analogously, smart homes may span the spectrum from the simple
addition of discrete features such as smart appliances or remotely controllable
lighting and thermostats to an automatically controlled, highly coordinated self-
learning system with grid interaction. In the latter case, the control system serves as
the brain of the smart home by automating domestic chores and providing
sufcient feedback and communication. This symbiotic relationship improves
the users quality of life and allows active participation in bulk power system
FIGURE 2.17 Schematic diagram of a centrally controlled smart home.
CH02 05/04/2018 16:42:46 Page 52
There are two schools of thought about the overall purpose of the smart home
control system. The rst school of thought posits that an ideal smart home control
system should be entirely automated, predicting a users every whim and reacting
accordingly so as to maintain user-centered optimal comfort, convenience, and if
applicable, savings [14]. One of the tenets of this prevailing theory envisions
minimal user input. The control system may incorporate a machine learning
algorithm to predict a users desires as they occur. The second and competing
school of thought envisions smart homes with well-informed and engaged users
that value energy sustainability and are thus active participants in the everyday
electricity management of the home [20]. In this case, the consumer is enabled with
timely feedback on costs, energy, and emissions to inuence the appropriate
control strategy.
Machine learning, rule-based, multiagent, and decision-making systems [14]
constitute the state of the art in control strategy paradigms for the smart home.
Although several smart home control systems are commercially available, they are
currently cost-prohibitive to the average consumer; these are expected to become
affordable as enabling technologies mature.
Smart home products not only make your life safer, more convenient, and more
fun, they can also help you to save energy and money. As a member of the Flex
Your Power energy efciency campaign, we can show you how to be a friend to
the environment and your wallet through energy conservation. The average home
spends almost $2000 on energy costs every year. Lower your energy bills and
improve comfort by making your home more energy efcient. The average
household could cut a third of its current energy bill by switching to energy-
efcient appliances, equipment, and lighting. From lighting to thermostat control
products, smart home offers a variety of products that homeowners can purchase to
begin saving on energy costs today.
2.8.1 Heating and Cooling
As shown in Figure 2.18, nearly half of a typical utility bill goes toward heating
and cooling in a typical house. A programmable thermostat offers the exibility
34% Lighting and appliances
Heating and cooling
Water heating
FIGURE 2.18 Percent of residential energy usage.
CH02 05/04/2018 16:42:46 Page 53
and power to control the climate in your home efciently to save energy and lower
energy bills. With a programmable thermostat, you can set the temperature to
different levels during set times throughout the week. For example, during the
winter, you can set the inside temperature to a lower level when you are at work
and the house is unoccupied. This can save you nearly $150 on your yearly utility
bills depending on climate, home insulation, and other factors. With home
automation technology, one can lower the thermostat setting and also turn off
all the lights and appliances in your home by hitting a single preprogrammed
button on the way out the door.
2.8.2 Lights
While 34% of a typical energy bill goes toward lights and appliances, a full 25% of
the utility bill is actually spent on just lights. Reduce your energy usage by simply
turning off lights when you do not need them with automatic timers and motion
detectors. You can also use light dimmers to reduce wattage and output to save
2.8.3 Automatic Timers
Program timers are used to turn on holiday and/or porch lights after sunset and off
at bedtime.
2.8.4 Motion Sensors
Never forget to turn lights off by using motion sensors that automatically turn off
lights when a room is left unoccupied for a long period of time perfect for
garages, hallways, and bathrooms. Occupancy sensors can cut lighting costs by as
much as 50%.
2.8.5 Light Dimmer
You often do not need the full brightness of lights in a room, especially in the den
while watching TV or having a romantic meal in the dining room. Use technology
to preset brightness levels to match the occasion.
2.8.6 Energy-Efcient Light Bulbs
It only takes 18 s to change a light bulb. Save money and energy by swapping your
existing incandescent bulbs for energy-efcient compact uorescent lights (CFLs).
For the same amount of light, the CFLs use up to 75% less energy and also last 10
times longer, according to Home Energy Saver. Click here to see our uorescent
bulbs and LEDs.
CH02 05/04/2018 16:42:46 Page 54
Local energy production and consumption means in a Smart Home can be
managed by a building energy management system. Advanced BEMS makes it
possible to deploy new kinds of energy management strategies that may change
the way of consuming and producing energy by supporting occupants to reach a
better energy performance and comfort. A smart home is a residential dwelling
equipped with sensors and possibly actuators to collect data and send control
according to occupantsactivities and expectations [18,20]. Potential applica-
tions for smart homes are described in Ref. [21]. The goal of these applications is
to improve home comfort, convenience, security, and entertainment. Thanks to
the communication network, a load management mechanism has been proposed
in Ref. [22]. Since then, several studies have been conducted in order to design
an optimized electric BEMS able to determine the best energy assignment plan
according to a given criteria. In Ref. [23], an analysis of the load management
technique is detailed. According to Ref. [24], energy management system
contains methods that coordinate the activities of energy consumers and energy
providers in order to best t energy production capabilities with consumer needs.
With such solutions, electricity can be reduced to support the grid. During the
last 2 years, many research projects have focused on demand side management
and loads control of domestic smart grid technologies for many reasons. First,
energy use in buildings currently account for about 32% of total global energy
consumption. In terms of primary energy consumption, buildings represent
around 40% in most IEA (International Energy Agency) countries [25] and 65%
of the total electric consumption [26]. Buildings are also responsible for 36% of
the EU CO
emissions. Not only energy performance, but also load management
in buildings is a key issue to achieve the EU climate and energy objectives,
namely, 20% reduction of the greenhouse gases emissions by 2020 and 20%
energy savings by 2020 [27]. These technologies may modify the domestic
energy use (electricity and heat) and adjust the electricity consumption/produc-
tion in dwellings [28,29]. These research works can be divided into two
complementary categories: predictive energy management and real-time control.
This control uses prediction model in addition to measured data in order to
forecast the optimum control strategy that will be implemented. Similar
researches have been carried out on predictive controllers using stochastic
models [30]. Both short-term (1020 min) and long-term (days) prediction
errors lay within acceptable ranges in terms of both temperature and humidity
levels. The second category of research also uses the predictive control, but it
introduces real-time control algorithms in order to give more benets contrary to
Refs [31,32], which do not study the price prediction. Most of these researchers
studied the real-time electricity pricing environments to encourage users to
adjust load peaks for two goals: reducing their electricity bill and reducing the
CH02 05/04/2018 16:42:46 Page 55
peak-to-average ratio (PAR) in load demand [33,34]. The BEMS are usually
based on simple models because it is difcult to determine the parameters of
detailed models that ts actual measurements. BEMS has to be appropriateto
detailed models. The problem of the evaluation of the degree of appropriation
and then the evaluation of the proposed solutions by the BEMS is rarely treated
as a research problem. This work deals with an analysis of a global model-based
anticipative building energy management system (GMBA-BEMS) managing
household energy. Most anticipative approaches of energy management problem
focus on specic appliances such as electrical water heater in Ref. [34] and
HVAC (heating, ventilation, and air-conditioning) system in Ref. [33]. HVAC is
the technology of indoor and vehicular environmental comfort. HVAC system
design is a subdiscipline of mechanical engineering, based on the principles of
thermodynamics, uid mechanics, and heat transfer. According to Ref. [35], the
approach of GMBA-BEMS called G-home Tech used in this paper is general
enough to handle a large set of electric appliances: electrical heater, washing
machine, dishwasher, fridge, and so on. It represents 80% of the total residential
consumption [36].
As detailed below, BEMS are based on simple models because it is difcult to
determine the parameters of detailed models that t actual measurements; BEMS
has to be appropriateto details models: It requires validation scenarios and a
building simulator connected to a BEMS. Regarding the proposed test bench, the
energy management strategy aims to minimize the households electricity cost
taking into account price signals from the grid by optimally scheduling the
operation and energy consumption of each appliance according to user comfort
expectations. As in Ref. [33], a time-varying curve of electricity price is used.
The household load management is based on price and consumption forecasts
considering userscomfort to meet an optimization objective that compromises
minimum payment and maximum comfort. Real-time adjustments are then done
according to real-time electricity market prices actual interest. However, in this
study, it is done according to the total available power: the PV production
(according to solar radiation curves) and the power limitation (subscription), to
the electricity market prices, and the power consumption of the other appliances
(Figure 2.18). Note that PV is a method of generating electrical power by
converting solar radiation into direct current electricity using semiconductors
that exhibit the photovoltaic effect. Photovoltaic power generation employs
solar panels composed of a number of solar cells containing a photovoltaic
The validation test bench is not only concerned with the heating control such
as in Refs [37,38] but also with the electrical appliances making the problem
more complex. It aims to introduce a real-time energy management decision
based on both reactive and anticipative global algorithms [39] contrary to
Refs [40,41] where the authors use a predictive control to anticipate a solution
for heating systems [35] and Ref. [42] details the BEMS algorithm selected for
CH02 05/04/2018 16:42:46 Page 56
the proposed analysis. The anticipative layer assigns energy references by
taking into account predicted events. Concerning the reactive layer, it intervenes
when the anticipative plan cannot be followed because of unforecasted events
and it decides whether some appliances have to be switched on or off.Onthe
other hand, to validate a BEMS, two parts must be presented: the simulator and
the energy management algorithms (Figure 2.19). In the BEMS, the
multilayers algorithms are in interaction with external data that come from
the weather, the energy marketer, the humanmachine interface (HMI), and the
real-time simulator. The HMI can be used by the occupant to provide instruc-
tions to the BEMS. Simulators replace a dwelling and its HVAC systems to
simulate their response to the BEMS as described in Ref. [38]. They are
used to improve product development, to train BEMS operators, to tune
actuators, and to simulate faulty situations [43]. Then, the validation of a
BEMS should be done through a simulator model. The simulation models
include in addition to the HVAC many electrical appliances such as lighting,
aps, washing machine, dishwasher, and fridge. Some simulators are presented
in the literature. For example, the software PME Comfortis used to simulate
the thermal comfort of dwelling [44]. Solene[45] simulates the sunshine,
light, and radiation. ESP-r[46] and FLOVENT[47] simulate the movement
of air in dwellings.
The BEMS is fed up with simplied models compatible with a mixed integer
linear programming formulation (Figure 2.20) [48]. But the behavior of a real
dwelling is much more complex. Therefore, simulation requires ner dwelling
models than the BEMS. To summarize, the objective of the chapter is to analyze
a BEMS in a context of variable pricing. To do this, three steps must be
performed: choose building simulator, congure the GMBA-BEMS, and ana-
lyze the results.
External data, weather
conditions, and prices
Predictive and
reactive optimizer
light levels
consumed energy
Dwelling power generation and
distribution modules
FIGURE 2.19 Virtual cosimulation general scheme for BEMS validation.
CH02 05/04/2018 16:42:46 Page 57
A connected smart home energy monitoring system makes it easy to view your
electricity usage and save money. We have written extensively on the benets of
home automation for energy management, particularly on how smart thermostats
that allow you to easily adjust your homes temperature, even while you are away,
to save money and make your house more comfortable. However, there is one
important aspect that we left out smart energy management is more than just
automating how your thermostat goes up or down. Real energy management
requires an energy monitoring system, which means knowing how much energy
you are using. If the amount and time of energy of a certain home are known, one
can better respond to that usage and take control of that home energy costs. Before
smart home systems, energy monitoring mostly meant scanning your electricity
bill each month and then telling your family to shut off the lights. New technology
makes the process much easier.
There are several ways you can monitor (and then respond to) your homes
electricity usage. Some methods let you monitor only the appliance you have
connected to the monitoring device, while other systems take a whole-house
approach. Here are a few energy monitoring systems worth checking out.
FIGURE 2.20 Exchanged command from BEMS and data from appliances.
CH02 05/04/2018 16:42:46 Page 58
The Home Energy Monitoring System uses your homes existing power lines to
monitor energy usage in real time. It can actually tackle up to 32 individual circuits,
as well as individual rooms. That way, you can keep tabs on devices that are energy
hogs and unplug them accordingly.
The electricity monitor uses measuring devices that clamp onto the main
conductors inside your breaker panel. The devices then send the data that are
measured over your homes power lines. No extra wiring is needed! Those data are
collected in a receiving unit, which you can plug into any outlet around the house.
Inside, the receiving unit has the companys Footprints software, which can store
and track up to 10 yearsworth of energy data. Homeowners can keep tabs on that
information via any web-enabled device (e.g., smartphone). You can even opt to
receive customized alerts via text or e-mail messages. Other features include
colored LEDs to alert users to different parameters, as well as the option to turn
loads on and off based on the cost of electricity and use.
The smart grid is a nationwide project to modernize the 100-year-old power
infrastructure by integrating the state-of-the-art information technology for two
ultimate goals: (i) balance the power demand (consumption) with the supply via
active interoperation among energy resources and (ii) accelerate the use of
environment-friendly renewable energy sources. In the smart grid context, build-
ing facilities, including industrial, commercial, and residential sectors, have been
primary energy consumers; they consume 72% of total energy in the United
States [49]. In the future, the facilities will be capable of generating and storing
energy with the potential inclusion of electric vehicles (EVs), solar panels, and
batteries. To manage such complicating energy resources, the research community
has developed an intelligent energy management system. Its eventual goal is to
maximize energy efciency in a building and to minimize the electricity cost by
making the best use of energy resources available in a building. To this end, the
EMS communicates with individual building equipment to collect its energy data
and to control them separately: ne-grained management. The EMS, then, analyzes
the data collection so as to detect any inefcient building operations and failures.
From the smart grid perspective, the customers building facility becomes the
most important entity to interoperate, as its energy capability (demand, generation,
and storage) dramatically increases. For instance, when the bulk power source
confronts a shortage of power supply, the customer is able to reduce current power
consumption, which can prevent blackouts. The EMS in the facility is required to
support such smart grid interoperation by enabling customer energy resources to
interact with other systems outside the facility. However, the existing EMS has
been designed as a stand-alone system without any consideration of the interop-
eration aspect.
CH02 05/04/2018 16:42:46 Page 59
To resolve the issue, we propose a new design of EMS, named premises
automation system (PAS). PAS aims at accommodating both the customer need of
efcient energy management and the grid need of customer interoperation.
To address the customer need, PAS inherits fundamental design issues from the
existing EMS model. It connects to customer energy resources that use heteroge-
neous communication protocols and technologies and manages them in a ne-
grained manner. To address the grid need, we rst review existing and potential
energy services that realize the customer interoperation and then classify them into
two categories: grid services and customer services. Under grid services, the
customer facility receives and consumes service data delivered from the smart grid,
while the facility provides service data to the grid in a customer service. For each
category of services, we examine functional requirements of the EMS in the four
aspects of service data type: a communication interface to realize the service,
required intelligence (data processing and knowledge generation), security, and
To demonstrate the feasibility of PAS, we develop and deploy a testbed in our
campus. In the testbed, PAS connects to and manages various types of energy
resources, consumes an automated demand response service, generates valuable
energy forecast data, and provides energy services to smart grid based on a service
model in a secure manner.
2.11.1 Smart Grid and Customer Interoperation
The smart grid aims at making the existing power grid more intelligent and
interoperable by allowing bidirectional ows of information and electrical power.
By integrating the state-of-the-art information and communication technologies to
the power infrastructure, energy resources with embedded sensors generate
valuable data that are then shared with all other resources in the smart grid.
Such information ow enables smart grid to monitor the status of power generation
and consumption accurately and respond quickly to potential failure. The smart
grid also allows a bidirectional ow of electricity, compared with todays power
grid electricity ows from central bulk generators to end consumers. Various types
of renewables can be installed on the consumersside and supply power back to the
grid reversely. On top of the information and power network, the operational goal
of a smart grid system is to maximize interoperations among energy resources so as
to balance the power demand with the supply, which eventually makes the power
grid more reliable and sustainable. To facilitate the interoperations, National
Institute of Standards and Technology (NIST) presents a conceptual model
consisting of seven domains, each of which represents a high-level grouping of
smart grid entities having similar objectives [50].
Customer domain in the conceptual model represents customer facilities (e.g.,
ofce, campus, and home) that consume more than 70% of total energy in the
United States. Traditionally, a building automation system (BAS) controls facility
equipment for the purpose of occupant comfort and optimal business operations.
CH02 05/04/2018 16:42:46 Page 60
Today, the introduction of smart grid changes the customersawareness and
expectation about their energy management. They want to see breakdowns of
energy usage and to take actions to reduce energy costs. Moreover, they are
interested in instrumenting new types of energy resources like solar panel within
the facilities.
To meet the emerging customer needs, recent research on the customer domain
has developed an advanced energy management system to build a smart building.
It performs ne-grained energy measurements and controls, say, at individual
home/ofce appliance level. It optionally analyzes the collected data and controls
equipment in a way to maximize the energy efciency inside the customer facility.
Although the existing EMS research makes the customer facility more intelligent
to satisfy the customer needs, it has barely taken the grid need of interoperation
into consideration.
As the customerscapabilities of energy consumption, generation, and storage
increase, it becomes most important to interoperate with the facility for the purpose
of energy balance in the smart grid. And the EMS is expected to play a gateway
role interconnecting the facility to other domains for the interoperation. Thus, the
design of the EMS must be enhanced so as to enable customer energy resources to
interact with other smart grid entities outside the facility, that is, supporting customer
interoperation. Figure 2.21 shows information system architecture around the
customer domain, including PAS, a premises network, energy resources, external
domains, service providers, and energy services.
2.11.2 Customer Interoperation and Energy Service
Customer interoperation is an interaction of the customer facility with external
domains in which the customers own resources are engaged.
FIGURE 2.21 An information system architecture around the customer domain.
CH02 05/04/2018 16:42:47 Page 61
The interoperable energy services are divided into two categories: grid service
and customer service. In the grid service, a customer facility receives and
consumes service data delivered from an external domain. For instance, the
facility becomes a client of a service that a local utility company provides.
In the customer service, the customer facility plays as a service provider, and
external domains use facilitys services as clients. Each category of service is
characterized by four aspects that must be considered in customer interoperation:
(i) Service data could be energy measurement, energy forecast, control
message, conventional information such as weather forecast, and power
(ii) Service interface enables interdomain communications of which there are
three issues of interface abstraction, data representation, and interaction
(iii) The intelligent unit performs interpretation of external data, knowledge
generation, and decision making to take energy-related actions.
(iv) Security addresses the most critical security concern at each category of
energy service.
Taking these aspects into consideration, the smart grid energy management
system can be designed, and sometimes called premises automation system.
Building automation systems provide automatic control of the conditions of indoor
environments. The automation of heating, ventilation, and air-conditioning sys-
tems in large functional buildings is the historical root and still core domain of
BAS. The primary goal is to realize signicant savings in energy and reduce cost.
Yet, the reach of BAS has extended to include information from all kinds of
building systems, working toward the goal of intelligent buildings.Since these
systems are diverse by tradition, integration issues are of particular importance.
When compared with the eld of industrial automation, building automation
exhibits specic, differing characteristics. This chapter introduces the task of
building automation and the systems and communications infrastructure necessary
to address it. Basic requirements are covered as well as standard application
models and typical services. An overview of relevant standards is given, including
BACnet, LonWorks, and EIB/KNX as open systems of key signicance in the
building automation domain. This chapter focuses on the automation of large
functional buildings, which in the following will be referred to as buildingsfor
simplicity. Examples include ofce buildings, hospitals, warehouses, or depart-
ment stores as well as largely distributed complexes of smaller installations such as
retail chains or gas stations. These types of buildings are especially interesting
CH02 05/04/2018 16:42:47 Page 62
since their size, scale, and complexity hold considerable potential for optimization,
but also challenges.
2.12.1 Building Automation System
Building automation is the automatic centralized control of a buildings heating,
ventilation, and air-conditioning, lighting, and other systems through a building
management system or building automation system. The objectives of building
automation are improved occupant comfort, efcient operation of building sys-
tems, reduction in energy consumption and operating costs, and improved life
cycle of utilities.
Building automation is an example of a distributed control system the
computer networking of electronic devices designed to monitor and control
the mechanical, security, re and ood safety, lighting (especially emergency
lighting), HVAC and humidity control, and ventilation systems in a building
(Figure 2.22).
BAS core functionality keeps building climate within a specied range,
provides light to rooms based on an occupancy schedule (in the absence of overt
switches to the contrary), monitors performance and device failures in all systems,
and provides malfunction alarms to building maintenance staff. A BAS should
reduce building energy and maintenance costs compared to a noncontrolled
building. Most commercial, institutional, and industrial buildings built after
Human interface device
computer workstation
logic controller
Secondary bus
Central plant
Package unit
device Lon tal
Secondary bus
logic controller
FIGURE 2.22 Building automation example.
CH02 05/04/2018 16:42:47 Page 63
2000 include a BAS. Many older buildings have been retrotted with a new BAS,
typically nanced through energy and insurance savings, and other savings
associated with pre-emptive maintenance and fault detection.
A building controlled by a BAS is often referred to as an intelligent building,
smart building,or (if a residence) a smart home.Commercial and industrial
buildings have historically relied on robust proven protocols (like BACnet), while
proprietary protocols like X-10 were used in homes. Recent IEEE standards
(notably IEEE 802.15.4, IEEE 1901 and IEEE 1905.1, IEEE 802.21, IEEE
802.11ac, IEEE 802.3at) and consortia efforts like nVoy (which veries IEEE
1905.1 compliance) or QIVICON have provided a standards-based foundation for
heterogeneous networking of many devices on many physical networks for diverse
purposes, and quality of service and failover guarantees appropriate to support
human health and safety. Accordingly, commercial, industrial, military, and other
institutional users now use systems that differ from home systems mostly in scale.
Almost all multistory green buildings are designed to accommodate a BAS for
the energy, air, and water conservation characteristics. Electrical device demand
response is a typical function of a BAS, as it is the more sophisticated ventilation
and humidity monitoring required of tightinsulated buildings. Most green
buildings also use as many low-power DC devices as possible, typically integrated
with power over Ethernet wiring, so by denition always accessible to a BAS
through the Ethernet connectivity. Even a Passivhaus design intended to consume
no net energy whatsoever will typically require a BAS to manage heat capture,
shading and venting, and scheduling device use.
2.12.2 Busses and Protocols
Most building automation networks consist of a primary and secondary bus that
connect high-level controllers (generally specialized for building automation, but
may be generic programmable logic controllers) with lower level controllers,
input/output devices, and a user interface (also known as a human interface
device). ASHRAEs open protocol BACnet or the open protocol LonTalk specify
how most such devices interoperate. Modern systems use SNMP to track events,
building on decades of history with SNMP-based protocols in the computer
networking world.
Physical connectivity between devices was historically provided by dedicated
optical ber, Ethernet, ARCNET, RS-232, RS-485, or a low-bandwidth special-
purpose wireless network. Modern systems rely on standards-based multiprotocol
heterogeneous networking such as that specied in the IEEE 1905.1 standard and
veried by the nVoy auditing mark. These accommodate typically only IP-based
networking, but can make use of any existing wiring, and also integrate power line
networking over AC circuits, power over Ethernet low-power DC circuits, high-
bandwidth wireless networks such as LTE and IEEE 802.11n and IEEE 802.11ac
and often integrate these using the building-specic wireless mesh open standard
CH02 05/04/2018 16:42:47 Page 64
Proprietary hardware dominates the controller market. Each company has
controllers for specic applications. Some are designed with limited controls
and no interoperability, such as simple packaged roof top units for HVAC.
Software will typically not integrate well with packages from other vendors.
Cooperation is at the Zigbee/BACnet/LonTalk level only.
Current systems provide interoperability at the application level, allowing users
to mix-and-match devices from different manufacturers and to provide integration
with other compatible building control systems. These typically rely on SNMP,
long used for this same purpose to integrate diverse computer networking devices
into one coherent network.
The communication protocol BACnet was specially developed for the require-
ments of buildings. It is suited for both the automation and the management level.
The emphasis is placed on building automation and control with a view to HVAC
plants, re control panels, intrusion detection, and access control systems. BACnet
is continually being extended for additional building-specic systems such as
escalators and elevators. By integrating new IT technologies such as IPv6 and Web
services, the BACnet standard is further developing into a modern, IT-friendly, and
multidisciplinary building protocol. At the same time, standardized ASHRAE or
AMEV device proles ensure a high level of quality and planning reliability with a
strict testing and certication procedure.
Highest investment protection, thanks to the use of the open, worldwide ISO
16484-5 standard.
Continued incremental development by ASHRAE, always focusing on the
requirements in and around buildings.
No license fees.
Guaranteed reliability, thanks to independent test houses and certication
bodies for BACnet devices.
Different transmission media, such as BACnet IP, BACnet LonTalk, or
BACnet MS/TP can be combined and support the most exible topologies.
Integration of the most diverse types of plants and vendors without having to
use special hardware.
Siemens is involved in the BACnet organizations worldwide in order to
promote the development of the standard.
KNX is an open, worldwide standard used for more than 20 years, conforming
to EN 50090 and ISO/IEC 14543, which is supported by more than 300 vendors.
With KNX technology, advanced multiple disciplines as well as simple solutions
can be implemented to satisfy individual requirements in room and building
automation in a exible way. KNX products for the control of lighting systems,
shading, and room climate plus energy management and security functions excel in
ease of installation and commissioning. A vendor-independent tool (ETS) is
CH02 05/04/2018 16:42:47 Page 65
available for commissioning. KNX can use twisted pair cables, radio frequency
(RF), or data transmission networks in connection with the Internet Protocol for
communication between the devices. Coordinated room and building management
often demands the integration of other technologies and systems. Hence, KNX
links and interfaces for connection to Ethernet/IP, RF, lighting control with DALI,
and building automation and control systems are provided.
Investment protection and interoperability, thanks to the standardized, world-
wide KNX standard.
Highest level of comfort and security while ensuring low energy
Matching products and systems for comprehensive room and building
Straightforward connection to higher level building automation systems.
Vendor- and product-independent commissioning software provides stan-
dardized commissioning procedures (ETS).
Choice of transmission media: KNX TP, KNX RF, and KNX IP.
Corresponds to the former European Installation Bus (EIB) and is backward-
Siemens is member of the KNX Association and actively takes part in the
evolution of the KNX standard.
KNX PL-Link fully complies with the KNX standard. Communication between
the room automation stations PXC3 of Desigo Total Room Automation (TRA) and
peripheral devices with KNX PL-Link has been optimized within the framework of
the KNX standard to the extent that plug-and-play functionality is available with
automatic device recognition. KNX PL-Link devices are congured using the
Desigo tools. The KNX commissioning software (ETS) is not needed.
Automatic recognition of devices with KNX PL-Link
Simplest conguration of devices with KNX PL-Link using the Desigo
Comprehensive portfolio of devices with KNX PL-Link for all technical
disciplines in the room.
Integrated monitoring of devices with KNX PL-Link using room automation
stations PXC3.
Replacement of a device with KNX PL-Link without any tools.
Two-wire standard cable for up to 64 peripheral devices in line or star
topologies with a maximum line length of 1000 m.
Feeding of up to 64 peripheral devices directly via the bus line.
Fast event-oriented communication for lighting and shading applications.
CH02 05/04/2018 16:42:47 Page 66
Room automation stations PXC3 allow simultaneous integration of devices
with KNX PL-Link and KNX S-Mode on a single bus line.
Devices with KNX S-Mode are commissioned using ETS.
The LonWorks-based communication protocol is one of the most widely
deployed technologies worldwide. Using the protocol, complete networks
made up of interoperable products can be created. This is proven by the fact
that more than 700 LonMark®-certied products from more than 400 companies in
the elds of building automation and control, trafc, and energy supply are used.
Owing to its worldwide use and being a global standard, LonWorks is also of great
importance to Siemens, focusing on HVAC functions in room automation and at
the eld level.
The protocol conforms to ISO/IEC 14908 (worldwide), EN 14908 (Europe),
ANSI/CEA-709/852 (the United States), and is also standardized in China.
LonWorks is suited for use with different types of transmission media, such
as twisted pair cables, power line, RF, ber optics, or IP (both TCP/IP and
UDP/IP), which makes it very exible.
Straightforward installation with a choice of different cabling topologies
(e.g., star or line).
The connection of objects via bindings (e.g., standard network variables
(SNVTs), standard conguration properties (SCPTs)) can be dened at the
project engineering stage or can be adapted in the eld. This simplies the
engineering process and helps prevent errors.
Siemens is involved in the organization LonMark®International with the
objective to protect and further develop the standard.
Siemens Products Featuring LonWorks Communication
Desigo RXC room controllers
Room operator units QAX5x.x
Climatix lines
DALI (Digital Addressable Lighting Interface) is a standardized interface for
lighting control. Electronic ballasts for uorescent lamps, transformers, and
sensors of lighting systems communicate with the building automation and control
system via DALI.
Extensive installation capacity and system exibility, thanks to the support of
up to 64 electronic ballasts, 16 groups, and 16 scenes.
Increased reliability owing to bidirectional communication with feedback of
operating state (dim level, lamp failure, etc.).
CH02 05/04/2018 16:42:47 Page 67
Polarity-free two-wire link in line, star or mixed topology with a maximum
cable length of 300 m.
Individually addressable operating units with free and exible assignment of
lamps with no need for making wiring changes.
Integration of emergency lighting in general lighting systems.
Siemens is a member of the work group DALI and participates, therefore,
actively in the further development of the standard.
Worldwide leading companies operating in the eld of building infrastructure
have joined to form the EnOcean Alliance, aimed at implementing innovative RF
solutions for sustainable building projects. Core technology is the self-powered RF
technology developed by EnOcean for maintenance-free sensors, which can be
installed wherever desired. The EnOcean Alliance stands for the incremental
development of the interoperable standard and for a secure future of the innovative
RF sensor technology.
EnOcean combines wireless communication with methods developed to
produce energy, aimed at minimizing product maintenance and the number
of batteries in use.
Standardized EnOcean communication affords access to a large number of
easy-to-integrate eld devices.
Modbus is an open and widely used de facto standard applied in a large number
of application areas, such as the industrial sector, buildings, trafc, and energy.
The Modbus protocol is used to establish masterslave/client-server communication
between intelligent devices. Using Modbus, a master (e.g., automation station) and
several slaves (e.g., chillers) can be interconnected. Data transmission takes place
through one of the three operating modes: Modbus ASCII, RTU, or TCP.
M-Bus (Meter Bus) M-bus is a European standard covering
remote readout of meters and can be used with different types of consumption
meters and various types of valves and actuators. Data (e.g., heat energy) can be
read out electronically. In that case, transmission is serial via a two-wire line with
reversed polarity protection, from the connected slaves (meters) to a master. M-bus
meters are available for the acquisition of heat, water, electricity, and gas.
OPC OPC is a standardized software interface facil-
itating the exchange of data between different types of devices, control systems,
and applications of different vendors. This interface is frequently used to collect
the process values of third-party devices for further handling by a building
automation and control system.
Web (IT Standard Technology) This is a generic term for a number of
standardized communication protocols used in the IT world, be it within a local
CH02 05/04/2018 16:42:47 Page 68
plant or via the Internet. Included are protocols that users work with when
communicating with plants and products, such as graphic user interfaces that
can be operated via Web browsers and/or touch panels, e-mail messages to service
personnel, or implementation of rmware changes. In addition, this comprises an
increasing number of protocols for direct communication between machines, such
as the exchange of device management information, or so-called Web services for
the connection of plants, even beyond the boundaries of building automation (e.g.,
to external building or energy management systems).
Standardized Communication Protocols for More Economical Operation
Open communication in building technology is important and facilitates the
straightforward and secure integration of third-party systems at all levels. In the
eld of building automation, all communication protocols listed above are
supported with no restriction to standards as in Figure 2.23. These are commu-
nication standards that were developed for the successful creation and mainte-
nance of projects. These make communication more secure, support efcient
engineering, and simplify maintenance and interoperability, thereby improving
the investment protection.
FIGURE 2.23 Standardized communication protocols for economical operation.
CH02 05/04/2018 16:42:47 Page 69
The Building Technologies Division of Siemens supplies complete building
automation and control systems and in addition to heating, ventilation, and air-
conditioning integrates lighting, shading, re safety and security, lifts, distribu-
tion of electrical energy and other forms of energy, and so on.
Building automation and control systems from Siemens and solutions based on
them make use of the standards listed above. The standardized and independent
communication protocols are subject to incremental development and ensure a
consistent exchange of information between devices and systems.
To allow for a better structuring of the diversity of technical systems, it is worth
taking a closer look at the various building management tasks. Usually, the
following three task areas are distinguished:
Commercial management is performed by specialized systems that support
the companys business processes and comprises various subareas from
purchasing to logistics to sales and maintenance. These systems are more or
less integrated, depending on the solution, and can be combined under the
name ERP (Enterprise Resource Planning). Among the most well-known
companies in this eld are SAP and Oracle, for example.
Infrastructural building management comprises, among other things, sys-
tems for the maintenance of the building, for example, the facility manage-
ment systems (FMS), which manage the maintenance of the technical
Technical building management comprises the building automation and
security management. While the building automation deals with, for exam-
ple, heating, ventilation, air-conditioning (HVAC), light, and lifts, the
security management deals with re detection, burglar alarm, access control,
video surveillance, and other security topics.
The operating behavior of the systems can be optimized in a simple manner via
the management station and provides for an energy-efcient operation of the entire
building installations.
2.13.1 Main Functions of the Building Management System
Operator control and monitoring
Fast and selective monitoring and operation of the system with practical
plant and room diagrams.
Time programs
Central programming of all time-controlled building functions.
CH02 05/04/2018 16:42:47 Page 70
Alarm handling
Detailed overview of the alarms for a fast localization and elimination of
faults. Central elements of the alarm handling are therefore the danger
identication, danger alarm, and an adequate intervention. This is supported
by the exible transmission of alarms to mobile devices, for example, printers
or pagers.
Event control
System-wide monitoring of systems and processes with regard to the
occurrence of certain criteria for the triggering of certain predened actions.
Modern management stations today work with integrated database applica-
tions. This allows for the storage of an almost unlimited number of past events
and their recorded handling. With these plant-specic records and the
corresponding query options, the following questions can be answered,
for example:
What has happened in the past 24 h?
How many interferences occurred within a certain period?
Who has done what and when following yesterdays burglar alarm?
To provide this main function, a whole range of additional functions is required,
which so to speak forms the infrastructure of the building management system. The
most important of these additional functions are, for example, access rights
concept, user administration, password administration, object management in
tree and graphic structures, and graphic level management.
2.13.2 Planning of a Building Management System
Within the scope of BMS projects, there are individual project phases comprising
different contents and responsibilities. The rst project phases are described in the
The customer/user must dene objectives; this serves as a basis for the
preparation of a requirements specication.
The denition of objectives comprises the following elements:
Scope of the building automation and security management subsystems to be
Denition of the integration:
Combining all subsystems of building installations (re alarm, gas warning,
burglar alarm, access control or video surveillance, HVAC systems, lighting, and
further external systems) by integrating them into a building management system
brings the following advantages:
CH02 05/04/2018 16:42:47 Page 71
Improved overview and thus increased safety.
Lower costs in comparison to several independent control centers with regard
to acquisition, conguration, and maintenance.
Consistent operational concept and thus less training time and effort, and no
danger of confusion in an emergency.
Only one system has to be integrated into the in-house IT infrastructure.
Interactions between the subsystems are possible in a much easier way.
Alarm escalation and alarm transmission is done in a more uniform way.
Integrated video systems allow for a direct view of the fault cause.
The objective is, therefore, to integrate all subsystems as completely as possible
into the building management system.
Expected improvements compared to a single-system solution.
Demands on the failure safety (redundancy solutions).
Demands on the power supply (e.g., UPS).
Description of the workplaces and tasks of the employees at the workplaces.
From the denition of objectives, a requirements specication has to be
prepared with the collaboration of the user and planner.
Due to the increasingenergy costs, saving energy becomes more and more important
on every sector. At the same time, ecological goals are to be attained, for example,
the specications with regard to the reduction of emissions and greenhouse gases.
This results rst of all in the selection of energy-efcient components, but it also
necessitates an ecological and economic power management.
In the planning phase, the property costs are to be kept as low as possible, while
the operator is interested in minimizing the operating costs. When planning the
electrical power distribution, the basics for the power management should be
established. The following aspects are to be taken into account:
Provide the required components with interfaces for measurements and
Use standardized bus systems and communication capable devices.
Ensure expandability (e.g., expandable cable laying and installation of
transformers in cabinets) to keep interruptions during operation at a
The focus of a power management system is on the request for improved
transparency of energy consumption and energy quality as well as on ensuring the
CH02 05/04/2018 16:42:47 Page 72
availability of power distribution. An all-round transparency is the basis for an
optimization of energy costs and consumption. The obtained information provides
a realistic basis for a cost center allocation as well as for measures to improve the
energy performance. Moreover, savings are documented. The functional overview
of the power management system is illustrated in Figure 2.24.
Functions of the power management system are summarized as follows:
Analysis of the energy data/energy ows with specic load curve diagrams.
Visualization of the interdependencies.
Detection of savings potentials, assessed minimum and maximum values.
Energy measurements for accounting purposes (internal cost center alloca-
tion, external billing).
Benchmarking, internal (product line/building part) or external (property/
installations with comparable use based on obtained measured values).
Visualization of the power supply with switching states and energy ows.
Preparation of decisions, for example, for power supply extensions.
Veriable efciency improvements.
Targeted troubleshooting via fast and detailed information on events
and faults that occur in the power distribution within the installations/
Logging of fault and event messages (e.g., switching sequences) with a date
and time stamp so that downtimes can be documented and fault processes can
be traced and analyzed later using the data recorded.
Compliance with purchasing contracts via the selective control of consuming
Automatic notication of the service personnel.
Consumption cost allocation
according to the user pays
Data export
Logs Electricity
Energy procurement
Data analyses
Data acquisation and processing subsystem
Switching status acquisition and
measurements in the power distribution
Switchgear and
Measurements and
measuring instruments
Data acquisition and
Graphical representation
Operator control
and monitoring
Load management
Power management module
FIGURE 2.24 Functional overview of the power management system.
CH02 05/04/2018 16:42:47 Page 73
2.14.1 Levels of the Power Management System
Power management is the special energy point of view of an industrial plant, a
functional building, or other piece of property. The view begins with the energy
import, expands to its distribution, and ends at the supply to the consuming devices
themselves. It comprises the following levels:
Acquisition for status and measurements.
Operator control and monitoring with visualization, archiving, reports,
import optimization, and control of switchgear.
The data acquisition level is connected to the processing level by means of eld
buses and the processing level communicates with the visualization system and
data archive via LAN (Local Area Network) as illustrated in Figure 2.25.
The acquired status information is depicted on the status displays in the control
center, thus enabling remote control. Measured value readings are displayed.
2.14.2 Switching Status Acquisition and Measurements in the
Power Distribution
In order to command of optimum purchase/consumption quantity records during
the utilization phase, the required measuring points and the power distribution
components to be monitored must be planned and congured at an early stage.
FIGURE 2.25 Probus connects the acquisition and processing level.
CH02 05/04/2018 16:42:47 Page 74
Important information for that
Types of energy
Components of the power supply (e.g., also UPS, emergency generators)
Division of the power demand according to the planned scenarios of use
For the various levels and components of power distribution (Figure 2.26), it
has to be taken into account which measurements and messages are required
during operation as well as the various requirements for:
Critical areas/consuming devices (availability)
Billing values (plausibility, contract monitoring, cost center management)
Transparency for operation (measured values, status)
Utilization (expansions, energy import monitoring)
2.14.3 Switchgear and Communications
The basis of each power management system are the measured values and data
from the eld level in which the energy in consumed. A large number of devices
can already be evaluated via bus systems such as Probus by a power management
system with regard to some specic data.
Circuit-Breaker-Protected Switchgear: Circuit-Breakers Circuit-breaker-
protected switchgear can be equipped or retrotted with the following signals
(Figure 2.27):
FIGURE 2.26 Levels and components of power distribution.
CH02 05/04/2018 16:42:47 Page 75
1. The auxiliary on/off switch signalizes the status of the circuit-breaker, on or
2. The alarm switch signalizes whether the breaker has tripped.
3. The motorized drive acts on the switching rods and permits remote control
of the breaker.
4. The release operates in parallel to the overcurrent release and acts directly
upon the switch-off mechanism of the circuit-breaker. Voltage and under-
voltage releases are to be distinguished as follows: voltage releases switch
when voltage is applied, undervoltage releases switch when voltage is
5. The alarm switch signalizes the status of the withdrawable unit. Only if all
withdrawable circuit-breaker units have been properly pushed in (i.e.,
contacted) can electric energy be switched.
Control Center The visualization screen shows the circuit-breaker status with
the aid of the pictograph on/off/tripped/withdrawable unit pushed inand
additionally by means of the color coding for event/fault/acknowledged/not
The circuit-breaker can be operated remotely from the user interface.
Fuse-Protected Switchgear: Switch Disconnector Fuse-protected switch-
gear can be equipped or retrotted with the following signals as shown in
Figure 2.28:
6. The auxiliary on/off switch signalizes the status of the switch disconnector,
on or off.
7. The fuse monitor signalizes a triggered/tripped fuse.
FIGURE 2.27 Circuit-breaker-protected switchgear.
CH02 05/04/2018 16:42:47 Page 76
Control Center The visualization screen shows the switch disconnector status
with the aid of the pictograph on/off/trippedand additionally by means of the
color coding for event/fault/acknowledged/not acknowledged.A switch dis-
connector cannot be operated remotely.
Measurements Measuring instruments (multifunction instruments, electricity
meters, motor management) can produce calculated data (phase displacement,
work, power) in addition to current and voltage readings (Figure 2.29).
1. Current transformers convert/transform current measurements into stan-
dard values (1 A or 5 A), as the currents typically used in low-voltage
distribution (up to 6300 A) cannot be processed directly.
2. The voltage tap directly acquires the voltages applied/measured.
FIGURE 2.28 Fuse-protected switchgear.
FIGURE 2.29 Measurement procedures.
CH02 05/04/2018 16:42:48 Page 77
Control Center The visualization screen shows measurement data for phase
currents/phase voltages/phase displacement/power/workandalsoidenties
limit value violations/acknowledged/not acknowledgedby means of the color
Measuring Instruments Measuring instruments acquire current and voltage
values in the electric power distribution and, according to their specied scope of
performance, they perform the following calculations (Figure 2.30): wattages,
phase displacement, work, and voltage characteristics in line with DIN EN
50160 (voltage characteristics of electricity supplied by public distribution
Multifunction Measuring Instruments Built-in device for electric power
supply systems with direct measurement display large back-lit high-resolution
graphic display, suitable for connection in three-phase networks, in three-wire
and four-wire design, for identical loads or different loads, also suitable for
single-phase networks, for industrial networks up to 3690/400 V (e.g.,
Parameterization can easily be performed by using either the front keys on the
instrument panel or the PC-based parameterization software. The number of
measuring screens and their contents, that is, measured quantities, can be con-
gured by the user as desired. The instrument has parameterizable digital inputs/
outputs for counter/energy pulses, status monitoring, limit value violations,
measuring period synchronization, high-rate/low-rate changeover, and switching
FIGURE 2.30 Typical measured values in electric power distributions.
CH02 05/04/2018 16:42:48 Page 78
to remote control via system software. The measured quantities are summarized as
Rms values of phase currents and voltages, PEN conductor current.
Network frequency.
Active, reactive, and apparent power per phase and for the entire system.
Electricity meter for high-rate and low-rate price.
Power factor per phase and for the entire system.
Symmetry factor of currents and voltages.
Harmonic contents of voltages and currents.
Total harmonic distortion (THD).
Electricity Meters
E-meters for single-phase operation; E-meters for three/four-wire connection
Drum-type register for electricity consumed (kWh).
S0 interface (pulses).
E-meter for three/four-wire connection; multirate meter
Drum-type registers for electricity consumed (kWh) for high-rate and
low-rate price
S0 interface (pulses) per rate type
Built-in modular device for electric power distribution systems with direct
measurement display large back-lit graphic display, suitable for connection in
three-phase networks, in three-wire and four-wire design, for identical loads or
different loads, also suitable for single-phase networks. The measured quantities in
this system are summarized as follows:
Rms values of phase currents and voltages.
Network frequency.
Active power per phase and for the entire system.
Apparent power per phase.
Reactive power for the entire system.
Power factor for the entire system.
Active energy import, export for the entire system at high-rate and low-rate
Reactive energy, inductive and capacitive, for the entire system at high-rate
and low-rate price.
Apparent energy for the entire system at high-rate and low-rate price.
CH02 05/04/2018 16:42:48 Page 79
If the meters are to be used for accounting energy quantities, meters that are
suitable for an accurate recording of consumptions are required (meters have to be
replaced/calibrated at regular intervals). These meters must be identied
Motor Management System Motor management systems carry out all motor
protection and control functions, collect operational, diagnostic and statistic data,
and handle the communication between the automation system and the motor
feeder. They are parameterized using PC-based parameterization software.
Measured Quantities
Rms and maximum values of phase currents.
R.m.s values of phase voltages.
Active and apparent power for the entire system.
Power factor for the entire system.
Phase asymmetry.
Circuit-Breakers The circuit-breaker (ACB) has a back-lit graphic display for
direct value displaying. This display is located at the release, integrated in the
circuit-breaker. It can be easily parameterized using a PC-based parameterization
software. The number of measuring screens and their contents, that is, measured
quantities, can be congured by the user as desired.
Measured Quantities
Rms values of phase currents, phase voltages, and PEN conductor current.
Ground-fault current.
Network frequency.
Active, reactive, and apparent power per phase and for the entire system.
Power factor per phase and for the entire system.
Symmetry factor of currents and voltages.
Harmonic contents of voltages and currents up to the 29th order.
Total harmonic distortion (THD).
Active, reactive, and apparent work for the entire system and their direction.
Other types of energy can be measured additionally using standard interfaces.
The following standard interfaces are customary:
Analog values 020 mA.
Analog values 420 mA.
Analog values 10 V.
CH02 05/04/2018 16:42:48 Page 80
Analog values PT100 for temperatures.
Pulses for energy quantities.
Measured values via bus interfaces.
A device-specic block library allows for a direct view of the multifunctional
measuring instruments and the device status with a simple integration via Probus
communication. These are called device drivers for multifunction measuring
instruments. Blocks are available for faceplates (view) as a user interface for
operator control and monitoring that allow for different views to display measured
values and to reset limit values for warnings and alarms. Driver block interface to
the faceplates and diagnostic blocks are necessary for multifunction measuring
instruments. Further device drivers are available as addons for control systems, for
example, for SIMOCODE for motor control.
2.14.4 Power Management Module
A power management module, as add-on for control systems, provides blocks for
the acquisition, preparation, and representation of energy data and offers special
functions up to energy-specic reports. The use of certied blocks and standard
interfaces as well as means of the control system provides an integrated application
requiring low maintenance effort that is suited for long-term use.
Data Acquisition and Processing
Complete recording and standardization of energy data from different media
as pulses, metered values (work values), or power values.
Time synchronization or with ripple control signal.
Buffering of the mean energy and power values.
Calculation and archiving of the mean power and work values based on a
freely denable period in the archive of the control system.
Determination of the consumption trend for a period based on the current
Open interfaces for customer-specic calculation functions (e.g., amount of
Block for batch-related energy detection.
AHEM: automated home energy management
BAS: building automation system
CFLs: compact uorescent lights
CoC: code of conduct
CH02 05/04/2018 16:42:48 Page 81
EMS: energy management system
EV: electric vehicle
GMBA-BEMS: global model-based anticipative building energy management
GUI: graphical user interface
HAN: home area network
HMI: humanmachine interface
HVAC: heating, ventilation, and air-conditioning system
IEA: The International Energy Agency
IoT: Internet of Things
NILM: nonintrusive load monitoring
NIST: National Institute of Standards and Technology
OSGi: Open Service Gateway initiative
PAR: peak-to-average ratio
PAS: premises automation system
PLC: power line communication
SMPS: switch-mode power supply
THD: total harmonic distortion
WoT: Web-of-Things
WSN: wireless sensor network
1. Remagnino, P. and Foresti, G.L. (2005) Ambient intelligence: a new multidisciplinary
paradigm. IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and
Humans, 35 (1), 16.
2. Sivaneasan, B., Kumar, K.N., Tan, K.T., and So, P.L. (2015) Preemptive demand
response management for buildings. IEEE Transactions on Sustainable Energy, 6 (2),
3. Nguyen, N.-H., Tran, Q.-T., Leger, J.-M., and Vuong, T.-P. (2010) A real-time control
using wireless sensor network for intelligent energy management system in buildings.
IEEE Workshop on Environmental Energy and Structural Monitoring Systems,
pp. 8792.
4. Javed, A., Larijani, H., Ahmadinia, A., Emmanuel, R., Mannion, M., and Gibson, D.
(2017) Design and implementation of a cloud enabled random neural network-based
decentralized smart controller with intelligent sensor nodes for HVAC. IEEE Internet
of Things Journal, 4 (2), 393403.
5. Sivaneasan, B., Kumar, K.N., Tan, K.T., and So, P.L. (2015) Preemptive demand
response management for buildings. IEEE Transactions on Sustainable Energy, 6 (2),
6. Lee, S., Kwon, B., and Lee, S. (2014) Joint energy management system of electric
supply and demand in houses and buildings. IEEE Transactions on Power Systems,
29 (6), 28042812.
CH02 05/04/2018 16:42:48 Page 82
7. Manic, M., Wijayasekara, D., Amarasinghe, K., and Rodriguez-Andina, J.J. (2016)
Building energy management systems: the age of intelligent and adaptive buildings.
IEEE Industrial Electronics Magazine, 10 (1), 2539.
8. Guinard, D., Ion, I., and Mayer, S. (2011) Search of an Internet of Things
Service Architecture:RESTorWS-? A DevelopersPerspective (Proceedings of
9. Belimpasakis, P. and Moloney, S. (2009) A platform for proving family oriented
RESTful services hosted at home. IEEE Transactions on Consumer Electronics, 55 (2),
10. Wang, K., Wang, Y., Sun, Y., Guo, S., and Wu, J. (2016) Green industrial internet of
things architecture: an energy-efcient perspective. IEEE Communications Magazine,
54 (12), 4854.
11. Schachinger, D., Stampfel, C., and Kastner, W. (2015) Interoperable integration of
building automation systems using RESTful BACnet Web services. IECON 2015
41st Annual Conference of the IEEE Industrial Electronics Society,
pp. 003899003904.
12. Corucci, F., Anastasi, G., and Marcelloni., F. (2011) A WSN-based Testbed for Energy
Efciency in Buildings. Proceedings of the 16th IEEE Symposium on Computers and
Communications (ISCC11), pp. 990993.
13. Wen, Y.-J. and Agogino, A.M. (2008) Wireless networked lighting systems for
optimizing energy savings and user satisfaction. IEEE Wireless Hive Networks
Conference, pp. 17.
14. Schoofs, A., Ruzzelli, A., and OHare, G. (2010) Appliance activity monitoring
using wireless sensors. Proceedings of the 9th International Conference on Infor-
mation Processing in Sensor Networks, IPSN 2010, April 1216, 2010, Stockholm,
15. Kim, W.H., Lee, S., and Hwang, J. (2011) Real-time energy monitoring and controlling
system based on ZigBee sensor networks. Procedia Computer Science, 5, 794797.
16. Yeh, L.W., Lu, C.Y., Kou, C.W., Tseng, Y.C., and Yi, C.W. (2010) Autonomous light
control by wireless sensor and actuator networks. IEEE Sensors Journal, 10 (6),
17. Guvensan, M.A., Taysi, Z.C., and Melodia, T. (2013) Energy monitoring in residential
spaces with audio sensor nodes: TinyEARS. Ad Hoc Networks, 11, 15391555.
18. Sayed, K. and Gabbar, H.A. (2016) Scada and smart energy grid control automation, in
Smart Energy Grid Engineering, Academic Press, pp. 481514.
19. BeniniOpens, L., Farella, E., and Guiducci, C. (2006) Wireless sensor networks:
enabling technology for ambient intelligence. Mechatronics Journal, 37 (12),
20. Zhao, P., Suryanarayanan, S., and Simões, M.G. (2013) An energy management
system for building structures using a multi-agent decision-making control methodol-
ogy. IEEE Transactions on Industry Applications, 49 (1), 19.
21. Sun, B., Luh, P.B., Jia, Q.-S., Jiang, Z., Wang, F., and Song, C. (2013) Building energy
management: integrated control of active and passive heating, cooling, lighting,
shading, and ventilation systems. IEEE Transactions on Automation Science and
Engineering, 10 (3), 588602.
CH02 05/04/2018 16:42:48 Page 83
22. Barr, J. and Majumder, R. (2015) Integration of distributed generation in the Volt/VAR
management system for active distribution networks. IEEE Transactions on Smart
Grid, 6 (2), 576586.
23. Missaoui, R., Joumaa, H., Ploix, S., and Bacha, S. (2014) Managing energy smart
homes according to energy prices: analysis of a building energy management system.
Energy and Buildings, 71, 155167.
24. Lausten, J. (2008) Energy Efciency Requirements in Building Codes, Energy Ef-
ciency Policies for New Buildings, International Energy Agency, Paris, France.
25. China Energy Conservation Investment Corporation (2009) China Energy Conserva-
tion and Emission Reduction Development Report (in Chinese), China Water Power
Press, Beijing.
26. Tzempelikos, A. and Athienitis, A.K. (2007) The impact of shading design and control
on building cooling and lighting demand. Solar Energy, 81, 369382.
27. Moeseke, G., Bruyere, I., and Herde, A.D. (2007) Impact of control rules on the
efciency of shading devices and free cooling for ofce buildings. Building and
Environment, 42, 784793.
28. Xu, J., Luh, P.B., Blankson, W.E., Jerdonek, R., and Shaikh, K. (2005) An optimiza-
tion-based approach for facility energy management with uncertainties. HVAC&R
Research, 11 (2), 215237.
29. Clarke, J.A., Cockroft, J., Conner, S., Hand, J.W., Kelly, N.J., Moore, R., OBrien, T.,
and Strachan, P. (2002) Simulation-assisted control in building energy management
systems. Energy and Buildings, 34, 933940.
30. Ricquebourg, V., Menga, D., Durand, D., Marhic, B., Delahoche, L., and Loge, C.
(2006) The smarthome concept: our immediate future. 1st IEEE International Confer-
ence on E-Learning in Industrial Electronics, December, Hammamet, Tunis, pp. 15.
31. Wacks, K. (1993) The impact of home automation on power electronics. Proceedings
of Applied Power Electronics Conference and Exposition, March, pp. 39.
32. Pan, M.S., Yeh, L.W., Chen, Y.A., Lin, Y.H., and Tseng, Y.C. (2008) A WSN-based
intelligent light control system considering user activities and proles. IEEE Sensors
Journal, 8 (10), 17101721.
33. Jia, Q.-S., Shen, J.-X., Xu, Z.-B., and Guan, X.-H. (2012) Simulation-based policy
improvement for energy management in commercial ofce buildings. IEEE Transac-
tions on Smart Grid, 3 (4), 22112223.
34. Paracha, Z. and Doulai, P. (1998) Load management: techniques and methods in
electric power system. Proceedings of IEEE Energy Management and Power Delivery,
March, vol. 1, pp. 213217.
35. Wacks, K. (1991) Utility load management using home automation. IEEE Transac-
tions on Consumer Electronics, 37 (2), 168174.
36. Mohsenian-Rad, A.H., Wong, V., Jatskevich, J., and Schober, R. (2010) Optimal and
autonomous incentive-based energy consumption scheduling algorithm for smart grid.
Innovative Smart Grid Technologies (ISGT), January, Gothenburg, Sweden, pp. 16.
37. Mohsenian-Rad, A. and Leon-Garcia, A. (2010) Optimal residential load control with
price prediction in real-time electricity pricing environments. IEEE Transactions on
Smart Grid, 1 (2), 120133. (Pengwei, D. and Ning, L. (2011) Appliance commitment
for household load scheduling. IEEE transactions on Smart Grid, 2, 411419).
CH02 05/04/2018 16:42:48 Page 84
38. Ha, D. Long., Joumaa, H., Ploix, S., and Jacomino, M. (2012) An optimal approach for
electrical management problem in dwellings. Energy and Buildings, 45, 114.
39. Paris, B., Eynard, J., Grieu, S., Talbert, T., and Polit, M. (2010) Heating control
schemes for energy management in buildings. Energy and Buildings, 42, 19081917.
40. Clarke, J., Cockroft, J., Conner, S., Hand, J., Kelly, N., Moore, R., Brien, T., and
Strachan, P. (2002) Simulation-assisted control in building energy management
systems. Energy and Buildings, 34, 933940.
41. Ha, D.L., Ploix, S., Zamai, E., and Jacomino, M. (2006) Tabu search for the
optimization of household energy consumption. IEEE International Conference on
Information Reuse and Integration, Waikoloa, Hawaii, USA, September, pp. 8692.
42. Oldewurtel, F., Parisio, A., Jones, C., Gyalistras, D., Gwerder, M., Stauch, V.,
Lehmann, B., and Morari, M. (2012) Use of model predictive control and weather
forecasts for energy efcient building climate control. Energy and Buildings, 45,
43. Balan, R., Cooper, J., Chao, K., Stan, S., and Donca, R. (2011) Parameter identication
and model-based predictive control of temperature inside a house. Energy and
Buildings, 43, 748758.
44. Ha, D.L., Ploix, S., Jacomino, M., and Le, M.H. (2012) Chapter 5, in Home Energy
Management Problem: Towards an Optimal and Robust Solution Energy Manage-
ment, INTECH, pp. 77105.
45. Kelly, G.E., May, W.B., Kao, J.Y., and Park, C. (1994) Using emulators to evaluate the
performance of building energy management systems. ASHRAE Transactions: Sym-
posium, 100, 14821493.
46. Fanger, P.O., Stberg, A., Nicholl, A.G., Breum, N.O., and Jerking, E. (1974) Thermal
comfort conditions during day and night. European Journal of Applied Physiology and
Occupational Physiology, 33, 255263.
47. Thevenard, D. and Haddad, K. (2006) Ground reectivity in the context of building
energy simulation. Energy and Buildings, 38, 972980.
48. Lucas, F., Mara, T.A., Garde, F., and Boyer, H. (1998) A comparison between
CODYRUN and TRNSYS, simulation models for thermal buildings behaviour. World
Renewable Energy Congress, Florence, Italy.
49. Lee, E.-K. (2016) Advancing Building Energy Management System to Enable Smart
Grid Interoperation, International Journal of Distributed Sensor Networks,112.
50. Milam, M. and Venayagamoorthy, G.K. (2014) Smart meter deployment: US initia-
tives. Innovative Smart Grid Technologies Conference (ISGT), IEEE PES ISGT 2014,
pp. 1- 5.
... Y€ uksek and Karadayi (2017) reiterated the same sentiment that there is increasing concern about energy use during the operation phase of buildings and its potential environmental effects. Empirical research has shown that the building industry accounts for 40% of primary energy in both developed and emerging countries and is a core sector of energy conservation and decarbonisation prospects (Sayed and Gabbar, 2018;Manic et al., 2016). What is more astounding is that the projected figure for the building sector's energy consumption is set to grow by a whopping 15.7% in the years between 2013 and 2035, due to the negative effects of global warming and population growth (Yang et al., 2016). ...
... Therefore, the adoption of smart energy-saving technologies in HVAC systems would be useful in minimising the energy consumption in buildings (Mills and Schleich, 2012). These technologies may include but not limited to Human-In-The-Loop (HITL) or Human Centred (HC) systems (Jung and Jazizadeh, 2019) and building energy management control systems (Gatea et al., 2020;Sayed and Gabbar, 2018;Ock et al., 2016). ...
... In recent times, Building Energy Management Systems (BEMS) have gained momentum as a result of increasing interest in building energy conservation and savings (Ock et al., 2016). According to Sayed and Gabbar (2018), BEMS are computer-based automated systems that track and manage all energy-related systems from mechanical and electrical equipment in buildings. This device is widely used to automate all facilities and operations inside the facility, including energy control. ...
Purpose Heating, ventilation and air-conditioning (HVAC) systems account for approximately half of all energy usage in the operational phase of a building's lifecycle. The disproportionate amount of energy usage in HVAC systems against other utilities within buildings has proved a huge cause for alarm, as this practice contributes significantly to global warming and climate change. This paper reviews the status and current trends of energy consumption associated with HVAC systems with the aim of interrogating energy efficiency practices for improving HVAC systems' consumption in buildings in the context of developing countries. Design/methodology/approach The study relied predominantly on secondary data by analysing the relevant body of literature and proposing conceptual insights regarding best practices for improving the energy efficiency of HVAC systems in buildings. The systematic review of the literature (SLR) was aided by the PRISMA guiding principle. Content analysis technique was adopted to examine germane scholarly articles and finally grouped them into themes. Findings Based on the SLR, measures for enhancing the energy efficiency of HVAC systems in buildings were classified based on economic considerations ranging from low-cost measures such as the cost of tuning the system, installing zonal control systems, adopting building integrated greenery systems and passive solar designs to major approaches such as HVAC smart technologies for energy management which have multi-year pay-back periods. Further, it was established that practices to improve energy efficiency in buildings range from integrated greening system into buildings to HVAC system which are human-centred and controlled to meet human modalities. Practical implications There is a need to incorporate these energy efficiency practices into building regulations or codes so that built environment professionals would have a framework within which to design their buildings to be energy efficient. This energy efficient solution may serve as a prerequisite for newly constructed buildings. Originality/value To this end, the authors develop an integrated optimization conceptual framework mimicking energy efficiency options that may complement HVAC systems operations in buildings.
... It is an essential tool to control and monitor various measurements of the wind turbine generation system (WTGs), and it's usual to include it together with the wind turbines. SCADA serves as the primary interface between the wind power plant operator and the wind farm equipment [1][2][3][4]. It allows integrating all the info about WTGs, meteorological mast, and substation in a single point of control, recapturing, and storing operation data from the WTGs and various alarm signals. ...
... However, all the data from the wind farm are collected and sent over the communication link such as optical-fiber cables to the master-station (control center). The SCADA server in the WPP is an industrial computer which is considered as masters in the SCADA system while all RTUs act as slaves [1]. Sometimes, one RTU acts as a master to collect information from slave RTUs. ...
... The SCADA system enables operators to monitor, control, and record wind power plant data from a remote location called a central control station [1,2]. It consists of three main components as shown in Fig. 20. ...
Full-text available
The objective of this chapter is to introduce the state of the art technology in wind power plant control and automation. This chapter starts with a historical background about supervisory control and automation evolution in the last decades. Several remarks are made regarding the use of SCADA Systems in wind turbine power plants. The Supervisory Control and Data Acquisition (SCADA) systems are responsible for controlling and monitoring many of the processes that make life in the industrial world possible, such as power distribution, oil flow, communications, and many more. In this chapter, an overview of SCADA at the wind power plant is presented, and operational concerns are addressed and examined. Notes on future trends will be provided. Finally, recommendations are provided regarding SCADA systems and their application in the wind power plant environment. One of the most significant aspects of SCADA is its ability to evolve with the ever-changing face of Information Technology (IT) systems.
... Smart plug load controls are receptacles and power strips that automatically turn off power to equipment that can detect the major load, such as a computer, and adjust the operation of peripheral devices appropriately. Plug load schedules can be incorporated into lighting and buildings' management systems (BMS) for centralized control [44]. ...
Full-text available
Machine learning can be used to automate a wide range of tasks. Smart buildings, which use the Internet of Things (IoT) to connect building operations, enable activities, such as monitoring temperature, safety, and maintenance, for easier controlling via mobile devices and computers. Smart buildings are becoming core aspects in larger system integrations as the IoT is becoming increasingly widespread. The IoT plays an important role in smart buildings and provides facilities that improve human security by using effective technology-based life-saving strategies. This review highlights the role of IoT devices in smart buildings. The IoT devices platform and its components are highlighted in this review. Furthermore, this review provides security challenges regarding IoT and smart buildings. The main factors pertaining to smart buildings are described and the different methods of machine learning in combination with IoT technologies are also described to improve the effectiveness of smart buildings to make them energy efficient.
... For buildings that have already been built and used, physical methods become more and more incapable of predicting such buildings due to the complexity of the building inside environment and the uncertainty of occupancy levels and patterns. As more and more premises have been equipped with building energy management system (BEMS) [5], it is easier to get access to building energy consumption data and some related information. The prosperity of data provides a solid foundation for the research of artificial intelligence methods in building energy consumption prediction. ...
Due to millions of loosely coupled devices, the smart-home security is gaining the attention of industry professionals, attackers, and academic researchers. The smart home is a typical home where many sensors, actuators, and IoT devices are used to automate home users’ daily activities. Although a smart home provides comfort, safety, and satisfaction to users, it opens up multiple challenging security issues when automating and offering intelligent services. Recent studies have investigated not only blockchain but SDN and NFV to address these challenges. We present a comprehensive survey on blockchain, SDN, and NFV for smart-home security. The paper also proposes a new architecture of the smart-home security. First, we describe the features of the smart home and its current security issues. Next, we outline the characteristics of blockchain, SDN, and NFV, including their contribution to improving the smart-home security. While SDN enhances the management and access control of the home network by providing a programmable controller to home nodes, NFV implements the functions of network appliances (e.g., network monitoring, firewall) as virtual machines and ensures the high availability of the network. Blockchain reinforces IoT data’s privacy, integrity, and security and improves the trust in transactions among untrusted IoT devices. Finally, we discuss open issues and challenges in the field and propose recommendations towards high-level security for the smart home.
This paper provides an overview of trends in the application of digital technologies in the energy management system of commercial buildings. In recent years, energy management in buildings, based on digital technologies, has resulted in the reduction in energy consumption of up to 50%. The paper covers trends in the development and application of digital devices and software in various technological areas such as Internet of Things, Edge Computing, Cloud Computing, Big Data, Artificial Intelligence, and Blockchain. Based on the review of the results of the conducted experiments as well as the characteristics of the technologies themselves, automation has been defined as a cornerstone of maximization of energy savings and digital transformation of the energy management system in buildings.
Purpose To achieve the building and property by 2050, decarbonisation goals will now require a significant increase in the rate of improvement in the energy performance of buildings. Occupant behaviour is crucial. This study seeks to guide the application of smart building technology in existing building stock to support improved building energy performance and occupant comfort. Design/methodology/approach This study follows a logical partitioning approach to the development of a schema for building energy performance and occupant comfort. A review of the literature is presented to identify the characteristics that label and structure the problem elements. A smart building technology framework is overlaid on the schema. The framework is then applied to configure and demonstrate an actual technology implementation for existing building stock. Findings The developed schema represents the key components and relationships of building energy performance when combined with occupant comfort. This schema provides a basis for the definition of a smart building technologies framework for existing building stock. The study demonstrates a viable configuration of available smart building technologies that couple building energy performance with occupant comfort in the existing building stock. Technical limitations (such as relatively simple building management control regimes) and pragmatic limitations (such as change management issues) are noted for consideration. Originality/value This is the first development of a schema to represent how building energy performance can be coupled with occupant comfort in existing building stock using smart building technologies. The demonstration study applies one of many possible technology configurations currently available, and promotes the use of open source applications with push-pull functionality. The schema provides a common basis and guide for future studies.
Home Automation (HA) has a long history becoming Smart Home (SH) or Smart Building (SB) when human-to-machine and machine-to-machine communications are able to turn each Things into a global system that is able to interact and make decisions. Based on European directives, energy-efficient technologies are one of the main levers of its development. Energy monitoring, and especially Measure and Verification (M&V), allows Energy Performance Contract (EPC) to help guarantying building performances from design to reality, while real-time feedback to occupants helps them to understand and better use their systems. Many metrics are available at building level in order to compare building performances, summarized here according to the International Energy Agency (IEA). SB is also open to outside, since it is integrated now into smart-district and smart-city, widening the interactions with other intelligent Things, referred for instance by Smart Readiness Indicator (SRI).
Full-text available
The advent and development of the smart grid concept to operate the electric power grids and microgrids have introduced a number of opportunities for improving efficiencies and overall performance. A supervisory control and data acquisition (SCADA) system provides an appealing scheme for remote control and observation of renewable energy sources (RES). SCADA systems have been used widely in various industrial applications, and have helped improve the efficiency of such systems. SCADA systems, however, still face some challenges in the effort to ensure reliability, safety, and security for power generation, transmission, and distribution. One of the considerations in designing the capabilities of the smart grid is the integration of SCADA systems to enable the remote control of electric microgrids and grids, supervise and control the electric network equipment as a means of fulfilling reliability and desired efficiencies for the whole utility. Given the ability of these systems to control the flow of electricity throughout the network, additional planning is required to ensure that all possible measures for preventing compromise are considered. This chapter discusses the current overall system architecture and some of the security measures used. More importantly, it considers simplifying the implementation of the many required standards. Because of the unpredictable characteristics of the RES, it has become important to constantly monitor their states in order to determine the amount of energy that is generated at all times. This will help in planning power usage and save energy when the sources are not enough for power generation. It will be practically impossible, however, to station personnel who will monitor the state of the sources constantly, hence the need for a remote monitoring system. This chapter provides an overview of utilization of SCADA systems in electric power systems, including the RES. It presents the main components of SCADA platforms, including the master station hardware and software. The outstation hardware, including data acquisition devices such as remote terminal units and programmable logic controllers, will be presented. These devices are integrated with substations' intelligent electronic devices, data concentrators, and other communication equipment. The fundamentals and possible application functions of SCADA systems unveil the potential of the smart grid and inspire more minds to get involved in the development process. A large amount of data is collected by SCADA systems installed on the wind turbines, solar photovoltaic (PV) arrays, and fuel cells (FCs), data that can be very helpful. SCADA systems can optimize and improve PV generation and can improve wind farm performance during operation. This chapter looks at the automation of RES such as solar PV plants, wind farms, and FC power plants.
Full-text available
The Internet of Things (IoT) can support collaboration and communication between objects automatically. However, with the increasing number of involved devices, IoT systems may consume substantial amounts of energy. Thus, the relevant energy efficiency issues have recently been attracting much attention from both academia and industry. In this article we adopt an energy-efficient architecture for Industrial IoT (IIoT), which consists of a sense entities domain, RESTful service hosted networks, a cloud server, and user applications. Under this architecture, we focus on the sense entities domain where huge amounts of energy are consumed by a tremendous number of nodes. The proposed framework includes three layers: the sense layer, the gateway layer, and the control layer. This hierarchical framework balances the traffic load and enables a longer lifetimeof the whole system. Based on this deployment, a sleep scheduling and wake-up protocol is designed, supporting the prediction of sleep intervals. The shifts of states support the use of the entire system resources in an energy-efficient way. Simulation results demonstrate the significant advantages of our proposed architecture in resource utilization and energy consumption.
Full-text available
With the emerging concept of smart grid, a customer’s building facility is able to consume, generate, and store energy. At the center of the facility, an energy management system is required to perform an efficient energy management and to enable smart grid interoperation. However, the existing EMS is designed only for the management function and does not support the interoperation. To resolve the issue, this paper designs the interoperation function and proposes a new EMS model, named Premises Automation System (PAS), that also inherits the existing management function. To identify functional requirements, we bring out four design aspects out of energy services. Then, we design two categories of interoperable energy services to achieve customer interoperation. To demonstrate the feasibility of PAS, we implement and deploy a testbed in a campus. We conduct experiments with a microgrid scenario and present interesting measurements and findings.
Smart Energy Grid Engineering provides in-depth detail on the various important engineering challenges of smart energy grid design and operation by focusing on advanced methods and practices for designing different components and their integration within the grid. Governments around the world are investing heavily in smart energy grids to ensure optimum energy use and supply, enable better planning for outage responses and recovery, and facilitate the integration of heterogeneous technologies such as renewable energy systems, electrical vehicle networks, and smart homes around the grid. By looking at case studies and best practices that illustrate how to implement smart energy grid infrastructures and analyze the technical details involved in tackling emerging challenges, this valuable reference considers the important engineering aspects of design and implementation, energy generation, utilization and energy conservation, intelligent control and monitoring data analysis security, and asset integrity. Includes detailed support to integrate systems for smart grid infrastructures Features global case studies outlining design components and their integration within the grid Provides examples and best practices from industry that will assist in the migration to smart grids.
Building Energy Management Systems (BEMS) monitor and control the Heating Ventilation and Air Conditioning (HVAC) of buildings in addition to many other building systems and utilities. Wireless Sensor Networks (WSN) have become the integral part of BEMS at the initial implementation phase or latter when retro fitting is required to upgrade older buildings. WSN enabled BEMS however have several challenges which are managing data, controllers, actuators, intelligence, and power usage of wireless components (which might be battery powered). The wireless sensor nodes have limited processing power and memory for embedding intelligence in the sensor nodes. In this work, we present a random neural network (RNN) based smart controller on a Internet of Things (IoT) platform integrated with cloud processing for training the RNN which has been implemented and tested in an environment chamber. The IoT platform is modular and not limited to but has several sensors for measuring temperature, humidity, inlet air coming from the HVAC duct and PIR. The smart RNN controller has three main components:base station, sensor nodes, and the cloud with embedded intelligence on each component for different tasks. This IoT platform is integrated with cloud processing for training the RNN. The RNN based occupancy estimator is embedded in sensor node which estimates the number of occupants inside the room and sends this information to the base station. The base station is embedded with RNN models to control the HVAC on the basis of setpoints for heating and cooling. The HVAC of the environment chamber consumes 27.12% less energy with smart controller as compared to simple rule based controllers. The occupancy estimation time is reduced by our proposed hybrid algorithm for occupancy estimation that combines RNN based occupancy estimator with door sensor node (equipped with PIR and magnetic reed switch). The results show that accuracy of hybrid RNN occupancy estimator is 88%.
Building automation systems (BAS), or building control systems (BCS), typically consist of building energy management systems (BEMSs), physical security and access control, fire/life safety, and other systems (elevators, public announcements, and closed-circuit television). BEMSs control heating, ventilation, and air conditioning (HVAC) and lighting systems in buildings; more specifically, they control HVAC's primary components such as air handling units (AHUs), chillers, and heating elements. BEMSs are essential components of modern buildings, tasked with seemingly contradicting requirements-minimizing energy consumption while maintaining occupants' comfort [1]. In the United States, about 40% of total energy consumption and 70% of electricity consumption are spent on buildings every year. These numbers are comparable to global statistics that about 30% of total energy consumption and 60% of electricity consumption are spent on buildings. Buildings are an integral part of global cyberphysical systems (smart cities) and evolve and interact with their surroundings (Figure 1) [2]. As buildings undergo years of exploitation, their thermal characteristics deteriorate, indoor spaces (especially in commercial buildings) get rearranged, and usage patterns change. In time, their inner (and outer) microclimates adjust to changes in surrounding buildings, overshadowing patterns, and city climates, not to mention building retrofitting [3], [4]. Thus, even in cases of "ideally" designed BEMS/HVAC systems, because of ever-changing and uncertain indoor and outdoor environments, their performance frequently falls short of expectations. Unfortunately, the complexity of BEMSs, large amounts of constantly changing data, and evolving interrelations among sensor feeds make identifying these suboptimal behaviors difficult [1], [5]. Therefore, traditional data-mining algorithms and data-analysis tools are often inadequate.
An evaluation of performance capabilities of building energy management systems (BEMS) were conducted using emulators. Major topics discussed include the setting up of a BEMS and an emulator, evaluating system/command and DDC software, as well as methodologies for testing BEMS application algorithms. An evaluation of the programming capabilities of a BEMS is presented together with a brief discussion of the software involved.
A building energy management system (BEMS), which forms an integral part of a smart grid, enables building operators to monitor, manage, and control the energy utilized in their buildings, thus reducing the demand and consumption of energy. Building operators are responsible for the day-to-day maintenance and operation of their buildings’ heating, cooling, mechanical, and electrical systems. This paper proposes an intelligent preemptive demand response management (DRM) using the BEMS to ensure contracted capacity or demand limit (CC/DL) is not exceeded and at the same time reduce energy consumption in buildings. In this paper, dynamic electric vehicle (EV) charge scheduling, speed control of air conditioning (AC) system’s variable speed drive (VSD), and priority-based load shedding are considered in the DRM program. The performance of the proposed DRM program to keep the building power demand within the CC/DL and reduce the energy consumption is tested and analyzed using the BEMS.