Content uploaded by Mariusz Postol
Author content
All content in this area was uploaded by Mariusz Postol on Jul 05, 2019
Content may be subject to copyright.
doc: R-110202E04-Koncepcja_ISC_CaseStudy/Ver:8 1
Adding Intelligence to Distribution Networks
Warsaw Heating Network Case Study
INTRODUCTION
In Poland 15% to 20% of generated heat is lost in transit from the manufacturer (Combined Heat Power plants CHP, heat
plants) to consumers, which gives a value of hundreds of millions Euro for several biggest national networks. In most cases,
nonrenewable conventional fossil-fuel must be used up in order to produce that heat, i.e. natural resources must be depleted
and the environment must be polluted. Following the concept of smart grids, more and more heating companies decide to start
working on smart heating networks that are to improve the performance of the heating system, limit energy consumption,
reduce water losses during heat transmission to consumers and enable the consumers to monitor heat consumption and have
effect on its economical use on a current basis.
Warsaw Heating System
The heating system of Warsaw is the largest centralized district heating system in Poland and one of the largest in the
world
1
. The origins of central heating go back to the second half of the 20th century. SPEC S.A. was established in 1952. At
present the supplied city area is 190 km2 and total capacity of buildings amounts to over 230 million m3. Through the district
heating network common for the whole city area, it provides heat to almost 19 thousand buildings in Warsaw, thus satisfying
ca. 80% of the demand. The district heating system of SPEC S.A. consists of almost 1700 km of network, including main
pipelines (of nominal diameters DN 400) – 18%, distributing pipelines – 40% and service lines – 42%. Power transmitted
from the sources amounts to ca. 5200 MW. Ca. 10000 GWh of heat is supplied to the consumers via the district heating
network. Losses in the heating network and exchanger substations exceed a bit 10%. The company is composed of seven Heat
Supply Plants: ZEC Żoliborz, Ochota, Wola, Mokotów, Śródmieście, Praga Północ and Praga Południe. Those Heat Supply
Plants provide current maintenance of the network and substations in their areas.
district heating system of Warsaw– 1676 km
district heating system in Międzylesie – 14 km
district heating system in Ursus – 10 km
Important components of the district heating system that are involved in heat transmission to the customers are water
pumping stations that start working if pressure is too low (there are four pumping stations within the municipal heating
network). Each pumping station includes fittings, a control system and pumps that pump water in the transmit lines supplied
from the CHP plant and the return water.
An important component of any district heating system is a consumer exchanger substation, i.e. termination of the heating
network in a building. In Warsaw there are ca. 15000 substations composed of a single-stage central heating exchanger and
two-stage hot water exchanger. Each substation is provided with a heat meter and an electronic weather compensator that uses
outside temperature sensors, supply and return lines temperature sensors to control the exchanged heat amount. That device
responds to the ambient temperature, thus adjusting the amount of heat supplied to the building. Heat chambers should also be
mentioned – there are ca. 5 thousand heat chambers in Warsaw.
1
"Warszawski system ciepłowniczy a wybrane systemy europejskie" („Warsaw Heating System Versus Selected European
Systems”); inż. Mikołaj Włoch, Politechnika Warszawska, inż. Piotr Brzeziński, Politechnika Warszawska; Warszawa, May
2010; www.warszawskiecieplo.pl
doc: R-110202E04-Koncepcja_ISC_CaseStudy/Ver:8 2
Smart Heating Network (SHN) Project
SPEC S.A. is the first Polish company that decided to launch the Smart Heating Network project. The SHN project covers
the Warsaw Heating System (WHS) and is intended to provide the system with measuring devices, data transmission
infrastructure and software applications to ensure optimal control of operation under normal conditions and in emergency. The
main aim of the SHN is to support all processes connected with the WHS operation so as to guarantee their high performance
according to the selected objective functions. The SHN shall provide optimum control of the district heating network taking the
operation of heat sources and pumping stations as well as relevant elements into consideration. In order to achieve that
objective, the SHN must make relevant functions and data available, including but not limited to:
efficient communication with distributed objects of the district heating network,
remote control and monitoring of the technological objects,
optimal control of the heat transmission according to the selected quality indicators,
reports that make assessment of the operation process effectiveness possible,
support for a modeling framework to be used in analyses concerning the development and prediction of the district
heating network behavior.
Works on the project of the Smart Heating Network were started by CAS in 2009. The company was to prepare the
technical and economic fusibility study for the project execution. The developed approach provides answers to two key
questions:
What needs to be implemented: an analysis of the options for technical solutions,
Why the individual options should be implemented: an analysis of economic efficiency of the SHN project
Answering these questions is necessary before the commencement of the individual stages of the SHN implementation, i.e.
before the design phase and before drafting of a detailed description of the possibly independent contracts scope.
OPTIMIZATION, THAT IS, A PREREQUISITE
Problems of network operators
Heat purchasing costs are the main budget item of any district heating network operator. If heat is supplied to the heating
network from various sources and heat prices are different, one may seek savings. If that is the case, technical solutions shall
lead to such optimization methods that minimize the necessity of heat purchase from more expensive sources. Water flowing
through pipelines is a means of thermal energy transfer from the sources to the consumers. Therefore, to be able to transmit
heat, water circulation must be provided by means of pumps at the heat sources. If distances or flow are a problem, the heat
transmit will require additional main pumping stations to overcome hydraulic resistance. Costs connected with pumping
depend on flow rate, so they are a function of the supply temperature at the heat source and the present heat demand.
Minimization of those costs is another possible source of effects. When transmitting heat to the consumers, one shall bear in
Citizens: ~ 1.7M
CHP: 2
Heat Plants: 3
Total thermal load: ~ 5 200 MW
Electric power: ~ 870 MW
Length of heating networks: ~ 1 700 km
Number of substations: ~ 15 000
Number of chambers: ~ 5 000
Production in co-generation:
hot water, electricity, process steam
doc: R-110202E04-Koncepcja_ISC_CaseStudy/Ver:8 3
mind that any pipeline is also some type of a radiator which causes that a part of the heat is dissipated to the atmosphere. The
dissipated heat amount depends on the design (insulation) and medium temperature. The temperature shall, therefore, be kept
on a level that is lowest possible but still guarantees that water of appropriate parameters will be delivered to consumers and
that technological limits will be observed. In any district heating network there occur smaller or bigger network leaks that
cause circulating water losses. The lost water is expensive because it must be subject to an expensive treatment process before
it is pumped into the system. Additionally, when we loose water we also loose heat transmitted by the water. Supported by
appropriate IT systems and distributed process control systems, we can shorten time necessary for finding the failure and
shutting off the damaged section, which will result in the reduction of loss costs. Another important element of that method is
minimization of the area that is not supplied with heat and the reduction of repair time. It is aimed at minimizing losses
resulting from lost profits and supplier’s prestige. Of course losses of water caused by the system leakages are unavoidable
and, therefore, it is necessary to top the system up with water. Here, one shall also consider water purchasing costs that depend
on the source – it is possible to minimize the purchasing costs by topping up with water from a cheaper source whenever
possible.
Apart from cost drivers of technological nature, personnel costs are another important budget item of any heat supply
company. Optimization of those costs is a deeply unpopular topic because it is associated with displacing people by cyber-
solutions. But it happens to be very effective from the economic point of view wherever the personnel costs are very high and
the “employment” of automation is possible. Pumping stations are such places and they can work as completely unmanned
plants. Long-standing experience shows that this results in an improvement of the plant reliability because unavoidable human
errors are eliminated, which is of additional benefit.
Objectives of the SHN
Generally speaking, the task of the SHN is to support all processes that will make improvement in its operational
effectiveness possible. The first step of the concept development is to define the quality index that will make assessment of the
proposed solutions possible. The final criterion of the usefulness of the proposed solutions is an economic analysis and the risk
associated with the implementation. The analyses are done in the context of global solutions, i.e. considering expenses to be
incurred when implementing the proposed solutions and considering the risks occurring in a chain of interdependent solutions.
Like any other product, heat has two features: quality and price. A measure of the heat quality can be assumed to be thermal
and hydraulic fit state, i.e. the ability to supply the consumer with such an amount of heat that he/she needs at a given moment.
The price is a function of many factors; among other things, it depends on the following variable costs:
purchasing costs,
transmission costs, including losses.
Thus we can separate two tasks for the systems that support the operation of heating networks:
to guarantee the quality – to supply heat in necessary amounts and in due time,
to minimize the mentioned costs – to optimize the distribution process.
A parallel performance of both the tasks is contradictory to some extent, e.g. when minimizing the purchased heat amount
we cannot ignore the consumer’s needs. On the other hand, purchasing of heat from a more expensive source will cause an
increase in costs. In order to eliminate this conflict we assume that the task of cost minimization can be carried out only if there
are observed technological restriction that guarantee that the main functions of the district heating networks are fulfilled, i.e.
consumers’ demand for heat is met. In other words, the objective of the heating network optimization is minimization of costs
simultaneously with the observance of restrictions that are vital for proper operation of the network. In the case concerned,
correct operation requires that there is secured the right:
supply temperature
differential pressure
Both of them determine minimum values of differential temperature and pressure respectively, that guarantee the possibility
of supplying the consumer with such an amount of heat that is sufficient for the consumer’s thermal comfort. The consumer is
supported by local controllers of the exchanger substation, that decide about the amount of consumed heat and the mentioned
minimums must be secured for each substation (draw-off point) separately in order that the automatic devices can work
correctly.
doc: R-110202E04-Koncepcja_ISC_CaseStudy/Ver:8 4
Optimization is a method of determining the best (optimal) solution. It is a search for an extreme of a certain function from
the point of view of a specific criterion (index) (e.g. cost, temperature, time, etc.). For a district heating network, whose main
task is to transmit heat from the supplier (producer) to the consumer, the following optimization objectives can be considered:
minimization of heat losses in transit,
minimization of heat purchasing costs,
minimization of pumping costs for pumping stations within the network,
minimization of water losses and costs of failure consequences,
minimization of topping up costs,
minimization of personnel costs connected with the network operation.
The mentioned objectives and appropriate quality indexes are defined in the implementation projects proposed by CAS to
be executed in order to build a smart heating network based on the present network of SPEC S.A. The SHN project is divided
into individual implementation subprojects so as to conduct an analysis of investment effectiveness. The starting point for
defining the implementation projects is the possibility of determining a direct and measurable quality index for each of them.
Determination of the measurable objectives consists in defining a certain index that allows us to quantitatively assess possible
savings at the stage of headwork and next, after the project has been executed, it will be used to verify whether the project
objective has been accomplished. Thanks to that, each implementation project outlines the boundary of the economic
effectiveness analyses. In other words, each implementation project precisely defines supplies and works indispensable for
producing the SHN within the definite scope essential to the achievement of the objective set.
The study assumes that each implementation project defined therein can be carried out as a single investment project or
several investment projects aimed at completing selected deliveries and executing selected works. The completion of all
deliveries and works specified in the implementation project is a prerequisite for separating the investment projects.
Separation of the investment projects is aimed at better suiting (in terms of the competence) the investment project scope to
potential contractors. The investment projects are to outline contractual limits that will permit to better control the course of
works against the time schedule and the extent of budget utilization.
SMART NETWORK REQUIRES SMART BUILDINGBLOCKS
The centralized heating system of Warsaw consists of interconnected objects including the following most important ones:
heat sources – producers of heat and water who supply the network according to the distributor’s requirements (5
sources),
main pumping stations – the pumping stations that increases the differential pressure if the pumping stations at the
sources do not guaranty a proper differential pressure availability throughout the network (4 pumping stations),
heat chambers – places where pipeline sections join and where heat is distributed to individual supply areas (5000
chambers),
heat substations – points where heat is provided to the consumers, which requires heat accounting (heat meter) and ad-
justment (exchanger) of the medium parameters (15000 substations).
Because of its complexity, the proposed SHN control system requires an appropriate distribution of tasks among subsystems
that must be interconnected to commonly achieve the defined objective function. The system components must communicate
with each other irrespective of the structure that is strongly dependent on the enterprise organizational culture.
Adaptation of the sources to operation within the SHN is not included in the study; therefore the sources are treated like the
network supplying points where – to put it simply – the parameters determined as a result of the optimization processes, i.e. set
points for the pressure and temperature shall be met.
Smart main pumping station
From the point of view of process optimization, the adaptation of the pumping stations to operation within the SHN is aimed
at:
minimizing the pumping costs,
making unmanned operation possible.
doc: R-110202E04-Koncepcja_ISC_CaseStudy/Ver:8 5
The pumping stations have the task of maintaining an appropriate differential pressure throughout the heating network. That
task is performed by a smooth adjustment to pumps load and selection of the number of running pumps. To make minimization
of pumping costs possible, the solutions proposed under the SHN project must permit to set the parameters of the pumping
station operation within the heating system taking the situation at other facilities into account.
To accomplish the other objective of the pumping station adaptation to operation within the SHN, i.e. to make unmanned
operation possible, the scope of functions fulfilled by the pumping station automation systems must be extended by functions
that, at present, are performed by operators. The modernization of the existing system is planned in order that the pumping
stations can be operated unmanned and are prepared for remote control. To that end, each pumping station operated within the
SHN must fulfill the following functions:
remote control of equipment in order to guarantee appropriate parameters of the medium,
local monitoring and control of the pumping units and fittings taking the set points of the supervisory control system
into consideration,
monitoring and control of the pumping station power supply system,
diagnostic evaluation of correct running and monitoring of the readiness for unmanned operation,
acquisition of values, conversion and validation of selected signals measured at the pumping station,
calculation of aggregated values of measurements and determination of analytical values,
reading data from the intrusion detection system,
reading data from the fire protection system,
remote monitoring and recording using industrial television.
Fulfillment of the above mentioned functions provides full autonomy in order that each facility may work if communication
is broken temporarily, and overcomes the problem of single point of failure, i.e. guaranties stepwise degradation of functions in
order that the pumping station basic functions are performed if single damages occur.
Smart heat chamber
Heat chambers are the next building-block of the SHN included in the study. To be capable of integration with the SHN,
any heat chamber must offer relevant functionalities as required by the SHN. It especially must guarantee: changeover of
heating network areas supplied by a given heat source, changing of the distribution of source loads and pressure maintenance.
Using the chamber fittings to stabilize pressure at the selected points of the heating network requires that appropriate
algorithms of pressure control in the chamber are proposed and changes of the pressure values by the supervisory control
system are enabled.
The most important tasks performed by the SHN chamber field controllers are:
acquisition of process data, conversion and validation of selected signals measured in the chamber,
calculation of aggregate values of measurements and determination of analytical values,
control of the chamber power supply system including starting emergency power supply sources and alternative power
supply sources such as a generating set, water and wind turbine, solar panel, etc.,
direct control of fittings, processing of control algorithms and sequences of operations connected with changeovers of
the supplying areas and leakages localization,
detection of events and emergency situations – those events are handled locally (if possible) and transmitted to super-
visory control systems,
handling of additional tasks associated with the protection (intrusion detection and fire/flow protection),
remote communication with the supervisory control system.
Measurements make monitoring of the selected network parameters (pressure, temperature, flow etc.) on a current basis
possible and they serve the optimization of the heat transmission process. Apart from the network parameters, there are also
measured other signals, which enable to secure uninterrupted power supply and protect the chamber against such undesirable
circumstances as breaking, failures, flooding. Since the Warsaw heating system consists of a huge number of chambers (5000),
the SHN study selects the chambers to be adapted for operation within the SHN. Modernization stages of the existing
doc: R-110202E04-Koncepcja_ISC_CaseStudy/Ver:8 6
chambers and automation of the next chambers are divided according to the defined implementation projects and,
consequently, using the chambers for the fulfillment of specific quality indexes.
Smart heat substation
An exchanger substation is the next building-block of the SHN. It is of special importance to the optimization processes
because appropriate thermal and hydraulic conditions must be guaranteed here to be able to meet the heat demand of the
consumers. The trouble is that the Warsaw heating system has fifteen thousand substations. When adapting the substations to
the SHN requirements, we take the fact that they are equipped with heat meters and weather compensators into consideration.
The heat meters are an especially interesting information source from the point of view of optimization feasibility. They
provide information about current supply and return temperatures, heat consumption and water flow. Access to data current
values is a prerequisite for the processing of the optimization algorithms. But those values can be available only if the meters
are provided with right communication modules, which ensure their connection to the selected communication network that
provides data transfer to the supervisory control system. Since they do not provide pressure measurements, those values must
be measured independently in the selected network locations.
Remote reading of the meters implemented in order to automate heat consumption accounting processes is a solution that
has already been used. A prerequisite for its engagement as the process data source in the SHN is exposing real-time
measurement data and transferring the same to the optimization systems and supervisory controllers. To that end, it should be
provided with an appropriate communication interface acceptable to those systems.
It should be stressed here that an important conclusion of the analyses done is a thesis that optimization is a direct objective
of the implementation of the remote reading of heat meters (a smart metering class solution), whereas automation of the
settlements with consumers is an important objective but only an indirect one, a by-product.
SHN ARCHITECTURE
In order to make a design and analysis of such an elaborate system as SHN possible, it is necessary to section off certain
function groups that are logically associated, using the component system concept. A well defined functionality boundary must
be a distinguishing feature of each system of that type. To perform their functions, those systems must communicate creating
mutual links. The system mutual links re-define the internal structure of the whole SHN system. Functions distribution to semi-
autonomic subsystems and the structure defined by mutual relationship (associations) create the SHN system architecture.
The figure below shows the Smart Heating Network architecture. It includes the following component systems:
Optimization: adjustment and optimal control of industrial processes
Telemetry: remote control and data acquisition
Repository: database management systems to archive process data
doc: R-110202E04-Koncepcja_ISC_CaseStudy/Ver:8 7
«system»
Telemetry
«system»
Source «system»
Substation «system»
Repository
«system»
Pumping station
«system»
Optimization
«system»
Chamber
OPC UA
SQL
Internal architecture of the SHN system
The Telemetry system represents all functions responsible for data acquisition and remote control of geographically
dispersed objects - islands of automation.
As it is shown in the figure, extensions (a closed arrow ) of the Telemetry system are subsystems that represent the
following objects integrated (closely coupled) with SHN and discussed above:
Pumping station: local control and measurements at the pumping stations
Chamber: local control and measurements at the heat chambers
Substation: measurements at the exchanger substations – smart metering subsystem
Source: measurements at the heat sources
The above mentioned component systems are semi-autonomous, i.e. they must fulfill their functions without communication
with the Telemetry system in case of its temporary loss due to any failure. But they still constitute an integral part of that
system, which means that Telemetry represents the homogenous state of heating network objects and available functions
intended for their control as one whole.
Since the Telemetry system is a middleware layer in the proposed architecture it should expose process data and make
process control functions available in a uniform way using an open international standard. For the architecture under
discussion it is assumed that OPC Unified Architecture will be used (an OPC UA interface is shown in the figure). Getting of
the underlying communication management functionality and unification process data and meta-data representation together in
this layer makes it “process observer”. Additionally, this layer can provide state observer functionality if simulation of
unmeasured signals is implemented.
Process data representing the process current state is archived using the Repository system to make analyses of the process
behavior over time possible. Repository manages archival data and exposes the same to processes carried out in the
Optimization system. Open arrows ( ) in the figure show how data is utilized and not data flow. The Telemetry system
is responsible for archiving process data in the repository.
One of the basic tasks of the Telemetry system is to provide access to process current data in the Optimization system.
Algorithms processed within the Optimization system may calculate values that are used - via the Telemetry system – to
control an object or archived by the Repository system.
To guarantee a gradual migration to the target architecture as shown in the figure, one shall assume that it is possible to
operate the heating network without the Optimization and Repository systems. With that assumption, the Telemetry system
must at least offer the functions of process visualization within such a scope that enables an operator to make operational
decisions. In this case it plays a similar role to typical SCADA or even HMI solutions.
doc: R-110202E04-Koncepcja_ISC_CaseStudy/Ver:8 8
Repository
Repository is the process data central database and offers modern and efficient services in the field of archival data
management to other systems.
The basic source of data logged in Repository is the Telemetry subsystem that deposits current process data in the database.
Data is logged cyclically to allow optimization algorithms to analyze historical process behavior. The logging schedule is
determined by the data acquisition pooling process in the Telemetry system. The archiving process is automatic and, if
possible, without human participation. If data acquisition in the Telemetry process is impossible the operator must be able to
provide data manually on the grounds of information acquired from outside the system.
It should be emphasized that breaking down of measuring paths that are the main data source is an unavoidable event for the
class of applications under discussion. If that is the case, there can be a single point of failure and it can prevent main
functionality from working for trivial reasons. To avoid this problem, an algorithm calculating supplementary data shall be
implemented. The selection of supplementary data calculation algorithms must take the controlled process sensitivity to
latency and assessment quality into consideration. If it is impossible to locate processing of the above mentioned algorithms in
this system they may be distributed to functions that directly utilize them, which may adversely affect the processing
performance, because of the necessity of redundant calculation.
Systems from outside SHN can be beneficiaries of the Repository system thanks to the mechanisms of data import and
export.
Telemetry
According to the SHN system architecture there is distinguished the Telemetry system that must offer the following
functionalities:
Communication – communication management with remote objects and acquisition of process data
Data logging – archiving of current process data
Management – system configuration and diagnostics
Communication is responsible for communication management in order to provide interconnection with geographically
dispersed plant floor and field controllers. Process data management is of vital importance to the system reliability,
transmission costs and processing loops latency. Reliability is absolutely critical to the control processes. Missing
communication means that the object becomes non-controllable which can result in huge costs in certain circumstances. The
communication media may have various features but in any case there can be determined a certain parameter which defines the
data transmission cost that should be minimized by that functionality. A throughput is a limitation that affects the availability
of current data. Not all data is of the same importance at a given moment. The importance of data can change with time. Those
factors shall be taken into consideration when selecting appropriate data acquisition time scheduling algorithms to avoid
starvation problem.
Communication is responsible for management of underlying communication via various media and protocols. The data
format can also vary depending on the manufacturer of equipment used in the remote systems.
Apart from internal process data, the Communication function shall expose also data provided by external systems. An
example can be here the weather forecast that is usually available from an FTP server or sent as an email message and must be
used by prediction algorithms processed in the Optimization subsystem.
Measurement data is volatile, i.e. the measurement process can be repeated but the received value is already a new one. We
say that measurements have a value and time attribute associated therewith. To be able to analyze the process behavior over
time, all measurement data and data determined therefrom must be archived. The Data logging function is responsible for it. It
uses the Repository system to save selected data to the Repository subsystem.
In order to provide an open solution, the system under discussion will expose data using the OPC Unified Architecture
standard.
Optimization
The Optimization system is to support:
remote process control – according to the optimization methods as described above,
doc: R-110202E04-Koncepcja_ISC_CaseStudy/Ver:8 9
monitoring of the process behavior, including optimization processes,
communication between operators at the heat source and heat distributor.
The Optimization system is responsible for the accomplishment of the optimization methods described above, using
available solutions offered by artificial intelligence.
It is assumed that the users will use a graphical interface to verify whether the network operation is correct. It should be
stressed that the interface should support monitoring of the correctness of processes occurring in the heating network objects
and not only their state. To meet that requirement, the system offers two types of user interfaces:
Synoptic table – process visualization using simplified graphical symbols
Geospatial - process visualization using maps to locate process data in the context of infrastructure, e.g. temperature
layout over selected network section.
OPC UA within SHN architecture
OPC Unified Architecture is a set of specifications for the development of software connected with such systems as ERP,
SAP, GIS, MES or process control systems. These very systems are designed for information exchange and they are used for
the control and supervision of real-time industrial processes. OPC UA defines the infrastructure modeling concept in order to
facilitate the exchange of process data. The whole architecture of the new standard improves and extends the previous OPC
(now called classic) capabilities in the field of application security, stability, event tracking and data management, thus
improving the interoperability of the distributed architecture components.
OPC UA permits easier cooperation and data exchange between the process control and business management layers. It is
designed so as to support a wide range of devices from the lowest level with PLCs to the distributed systems dealing with IT
management at an enterprise.
It is worth noting that OPC UA technology is based on services and objects. For more than one decade the software authors
have been using solutions based on objects and services but those solutions have never been transferred directly to industrial
applications. OPC Unified Architecture has become the first standard close to the technological process that is of a dual nature,
both object oriented (Object Oriented Architecture - OOA) and service oriented (Service Oriented Architecture - SOA).
The application of OPC Unified Architecture standard to the SHN architecture will enable us to:
standardize communication between component systems of the SHN
create a consistent information model that is available to all systems and illustrates the Warsaw heating system struc-
ture
create a database model (metadata) based on an OPC UA information model, thus giving applications that use Reposi-
tory access not only to process data but also to metadata describing the Warsaw heating system objects.
provide open solutions, i.e. the possibility of free connection of the next components in the future.
SUMMARY
The feasibility study of the Smart Heating Network, developed by CAS, is a complex solution based on the synergy of the
latest achievements in the following domains: technology, automation, IT and telecommunication to control the district heat
distribution process in order to improve the performance of industrial processes and efficiency of business processes.
The OPC UA standard allows us to get an open, interoperable and scalable architecture, thus making the development of the
infrastructure and its use for other tasks in the future possible. As the proposed architecture bases on the open connectivity
standards it provides a framework for the integration of highly distributed “islands of automation” with top level applicatio ns
employing the artificial intelligence idea for optimal control of the heat transmission process. It seems that most results from
this project can be a foundation for designing other smart distribution networks, like utilities, oil and natural gas, smart grids,
etc.
www.commsvr.com
www.cas.eu
commserver@cas.eu