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The ‘Mind the Gap’ project: Investigating the difference, in performance, between design and the building ‘in-use’

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  • AJL Associates
  • GreenRock Energy

Abstract and Figures

We have the ability to design and construct high performance buildings; and the knowledge and skills to operate them in an effective and efficient manner — so why does it not happen? The underpinning reasons for this gap in performance are generally unknown; there is a lot of speculation and hypothesis but little investigation and hard evidence. The ‘Mind the Gap’ project aims to collect evidence from typical exemplars of office buildings investigate the reasons for their performance and determine the underpinning causes. The first phase of the project will produce a methodology based on the learnings from five trial buildings and then rolled out in a second phase over a larger number of buildings. This paper presents some initial data and findings.
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* Corresponding author: LewryA@bre.co.uk
The Mind the Gap project: Investigating the difference, in
performance, between design and the building in-use
Andy Lewry1, *, Mindy Hadi2, Jaie Bennett3, and Richard Peters4
1 BREEAM Existing Buildings Team, BRE Global, WD25 9XX, UK
2 Social Research, BRE, WD25 9XX, UK
3 GreenRock Energy, Trowbridge, BA14 9NL, UK
4 Peters Research Ltd, Great Missenden, HP16 9AZ, UK
Abstract. We have the ability to design and construct high performance buildings; and the knowledge and
skills to operate them in an effective and efficient manner so why does it not happen? The underpinning
reasons for this gap in performance are generally unknown; there is a lot of speculation and hypothesis but
little investigation and hard evidence. The Mind the Gap project aims to collect evidence from typical
exemplars of office buildings investigate the reasons for their performance and determine the underpinning
causes. The first phase of the project will produce a methodology based on the learnings from five trial
buildings and then rolled out in a second phase over a larger number of buildings. This paper presents some
initial data and findings.
1 INTRODUCTION
The difference in performance between those predicted
from the design and those found in actual operation are
well documented [1,2]. The construction industry has in
general been ‘designing for compliance using software
with standardised driving conditions; where standard
conditions in terms of occupant behaviour and plant
performance are assumed (see below). This is the start of
the gap with real performance in-use; where the
compliance software allows assets to be compared but
the performance of the actual building in-use is not
estimated properly. We know how to build good
performance buildings, but the issue seems to be having
the design intentions and predictions of performance
feed through to performance in-use [3]. We can start to
bridge this gap by baselining the predicted
performance of the building by using the Green Deal
(GD) tool or Dynamic Simulation Models (DSMs)
which allow the input of non-standard operating
conditions, hours of operation and occupancy patterns,
etc. By defining these aspects of the building in use,
the predicted energy performance of the asset can be
brought closer to the in-use reality [4]. This has been
recognised by sustainability standards such as the BRE
Environmental Assessment Method (BREEAM); the
latest scheme to be updated BREEAM New UK
Construction 2018 [5] has credits for using DSMs in the
Energy Prediction and Post Occupancy Assessment
Methodology [6]; the intention is to extend this to the
UK BREEAM Refurbishment and Fit Out and the
corresponding international schemes in the future.
However, this only deals with the initial and smaller part
of the poor performance issue but does baseline the
building. All of this has led to what has been termed the
performance gap. In reality, this has two components
(see Figure 1):
The compliance gap; and
Actual performance gap.
The overall gap has been estimated at between 200–450
per cent [7] of which the modellers estimate 50–70 per
cent is the compliance gap [8] and can be solved with
more realistic modelling, such as DSMs, mirroring the
conditions in operation more closely as described earlier.
However, the underpinning reasons for the second and
larger actual performance gap are generally unknown.
There is a lot of speculation and hypothesis but little
investigation and hard evidence. The Mind the Gap
project is set-up to investigate this aspect in particular.
2 THE PERFORMANCE GAP
2.1 Why is this so important?
The management of real estate investments aims to
maximise property value and return on investment (ROI)
[9] via:
Effective risk management;
Efficient property management;
Identification and implementation of valuable
improvements.
A high-performing building generates maximum profit
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© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0
(http://creativecommons.org/licenses/by/4.0/).
via:
High and continuous rental income;
Low operating and maintenance cost;
Low depreciation.
Fig. 1. The difference between design and the building in-use
However, poor operational management also undermines
the aims of asset management [1, 2] and leads to:
Increased tenant complaints regarding comfort
conditions and loss of reputation;
Higher service charges;
Longer void periods leading to a reduction of
income;
Lower and shorter rental values, as a consequence
of high service charges and poor comfort
conditions;
Capital expenditure on heating, ventilation and air
conditioning (HVAC) equipment failures, due to
poor maintenance;
Tenants wanting to renegotiate rent values based
on comfort and maintenance issues.
On a pure cost basis, the operation energy or the energy
used in using a building is up to 50 per cent of the
operation costs or 40 per cent of the total cost of a
building (see Figure 2).
Fig. 2. The life costs of a building
If this is inflated by a multiple of 2 to 4.5 [2] the cost to
the end user is considerable. However, if the occupier is
leasing these may just be passed onto them and they
more not have much say in the management of the
building.
The effect on the asset and its value is just as dramatic
with:
Deterioration of value;
Service life of plant reduced;
Fabric lifetime reduced;
Costly remedial works to maintain value;
In void’ periods where there is likely to be still
further deterioration through lack of use;
Loss of reputation.
2.2 So why does the performance gap persist?
The following have been put forward by various parties
as the underpinning reasons:
Lack of knowledge
o How assets and their components perform
in practice;
o What is buildable and functional;
o How design strategies perform in practice;
Poor communication and buy-in
o The design intent gets lost
§ designers constructors/installers
building managers
o No feedback on actual performance
§ Building managers
constructors/designers designers;
Rarely any consequences
o For designers, contractors and suppliers
when actual energy consumption exceeds
predictions;
o The occupier ends up picking up the bill;
The contractual model is wrong
o Based on lowest cost rather than value for
money;
o Insufficient resources in place;
o Authority not being devolved along with
responsibility;
o Roles and responsibilities unclearly
defined and understood;
o Management structure unable to act on this
knowledge;
o Skills sets lacking, and training needed;
o Insufficient good quality data and not
being captured properly;
o Insufficient knowledge and expertise;
o Unable to turn data into information;
o None or inaccessible specialists in the
supply chain.
2.3 Investigating the gap
The BRE has previously attempted to close the gap by
using the GD tool to map Energy Performance
Certificates (EPCs) onto Meter readings [4,10] although
this approach has merit, the sliding energy management
scale has little underpinning research to support the
assumptions and no verification has been carried out to
support these judgment calls by expert groups.
Anecdotal evidence from the asset management industry
has indicated several possible reasons:
Issues with the management structure and
governance;
Lack of maintenance due to resource and skills
shortage;
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Limited data;
Lack of practical solutions and their costs.
In fact, nobody knows the reasons why; which presents
an opportunity for whoever finds the evidence for the
underpinning causes and practical solutions to solve
them.
This has been recognised by the construction industry
and priorities that were fed back from the UKGBC
Delivering Building Performance task group [1], the UK
Innovate Building Performance project [2] and a BSRIA
event on building efficiency [11] were:
There was data on the performance gap but no
systematic investigation of the reasons why and
the magnitude of the issues what was needed
was a controlled study to investigate this; not
attempting to link datasets;
Design was not considered an issue, but operation
and the associated issues seemed to be the cause,
however there is only anecdotal evidence to
support this. A study is needed to codify and
quantify the causes of poor performance in use;
The ‘gap seems to increase with time, again
anecdotal evidence is available with no
quantification of the underlying reasons; with a
long-term study needed to identify, qualify and
quantify any affect;
Health and wellbeing is associated with this effect
but, as before, there is not true quantification,
model or tool; as a result, a monetary value
cannot be assigned to the loss/gain of productivity
leading to an incomplete business case. A desk
study is needed to identify knowledge gaps
followed by a field study producing data leading
to a model/tool for quantification of productivity
loss/gains.
A recent study on refurbishment has supported this view
point in that a holistic people-centric renovation of a
typical office building can lead to up to a 12% increase
in productivity. At a European scale, that could be worth
up to 500 billion [12].
The main barrier to providing systematics solutions is
the lack of quality data from a large enough sample with
full access to the building and their occupants BRE
and its partners have been presented with that
opportunity.
We now have real-life exemplars to investigate the
actual causes of the performance gap and propose
practical solutions.
2.4 Themind the gapresearch project
This research project is in two stages: where the on-
going first stage defines the methodology using five trial
buildings to determine the correct data to collect and the
right questions to ask; with a proposed second stage
rolling this out over a larger number of buildings.
The objective of this project is:
1. Scope proposed buildings and choose suitable
five trial buildings which are typical exemplars
of office buildings for the purpose of collection
and analysis of metered, asset and energy audit
data (see Figure 3).
2. Using the results from the scoping phase,
propose reasons for the performance gap;
produce operational and asset
recommendations; and model the benefits.
3. Based on the learning from these trial buildings
produce a methodology that can be rolled out to
a larger number of buildings.
4. Propose a second phase covering more office
buildings, which covers the breath of the
building stock in this sector and aims to
produce a tested generic methodology for the
office sector, which includes:
a. Fully air-conditioned;
b. Mechanical vented; and
c. Naturally ventilated.
Fig. 2. The choice of exemplar buildings
2.5 The initial methodology
The initial methodology is laid out in the following
steps:
1. To scope proposed buildings and choose
suitable exemplars;
2. Hold an inception meeting for each of the
buildings, along with targeted follow-up, to
map the data and produce a data gap analysis.
From this and consideration of the other
research questions produce a full project action
plan for the project;
3. The modelled data will be in the form of a NCT
file from the interface to Simplified Energy
Model (iSBEM) software [4] The NCT file will
be checked to ensure it reflects the buildings
current geometry, usage and servicing:
a. The metered data will be in a half
hourly form and transferred into a
spreadsheet
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b. Operational data will be required and
collected by a mini-audit including
interviewing key members of the
operational, facilities and maintenance
staff (see Appendix 1);
4. Basic information about the population and lifts
were sourced from the building operators.
These inputs were used to run simulations using
the generic Energy Model in the Elevate
elevator simulation software [13]. Calibration
of the model was based on measurements made
as part of a research project with ThyssenKrupp
[14]. The simulations were run applying a full
day traffic demand template, reflecting the rise
and fall of passenger demand during a typical
day, and the impact this has on energy
consumption. Out of hours and weekend energy
consumption was assumed to reflect standby
load only. Lifts of the same basic specification
from different sources have dramatically
different energy performance, thus the results
are indicative only. There is insufficient
measurement data in the public domain at this
point to be able to give a range of expected
results;
5. Determine any data gaps on completion of steps
1–4 for each building and proposed how they
will be filled;
6. On the basis of the gap analysis above install
and commission sub-metering if required on a
building-by-building basis;
7. Collect additional data if required, especially
with respect to energy management activities
this will include the use of energy matrices
[15];
8. Analyse the modelled data and input into the
GD tool along with energy management,
operational and bill data to join the asset and
operational data up. Carry out a calculation of
the lift energy usage.
9. Analyse the metered and produce energy
profiles [15] for day/night, weekday/weekend
and seasonal; look for high base consumption
and any unusual usage patterns. Compare to the
Real Estate Environmental Benchmark (REEB)
- for energy [16] these are produced by the
Better Building Partnership (BBP):
a. Based on the performance of buildings
in-use;
b. Publicly available operational
benchmarks;
c. Based on the annual consumption of
BBP members property portfolios;
d. Based on a three-year rolling average;
e. Updated each year;
f. Office sample size for air-condition can
be considered representative (185
assets);
g. Limited sample (25 assets) for naturally
ventilated offices
10. Carry out a targeted energy audit, in line with
BS EN 16247 [17] and best practice [18] to:
a. Investigate user behaviour;
b. Investigate working practices including
maintenance regimes;
c. Examine high and unusual energy
consumption patterns;
11. From consideration of the analysis of the asset
and operations data, use the GD tool to run
recommendations based on business case
parameters and best practice [19].
12. The final methodology for the roll-out in the
second phase will be based on the learnings
from the trial buildings and aims to streamline
the process with the aim of designing a second
phase where this will be run out over a larger
number of buildings to produce a statistically
significant sample which covers office
buildings with a full range of servicing and age.
2.6 People, roles and behaviours
The This builds on the initial methodology and takes into
account issues such as communication, motivation and
behaviours from the whole range of stakeholders who
have influence on energy use in a building [20]. These
will be different for different stakeholder groups,
depending on roles and responsibilities within the
organisational structure. As a result, it is essential to
carry out a Stakeholder mapping exercise [21] which
includes as many as the below as possible:
Building owners;
Landlords;
Facilities/building manager;
Other operational staff eg security, cleaners;
Occupying organisation (Tenant);
End users ie staff, visitors.
It is also essential to examine the organisational role
breakdown for energy-saving behaviours. Firstly, the
organisation owning or leasing the building will have an
impact on its energy consumption, depending, for
example, on occupancy patterns (for example, hours of
operation needed for business requirements), which
might greatly differ from the original design
assumptions.
In addition, the organisation's approach to sustainability
and the environment and the costs and benefits of action
has an influence on the introduction and effectiveness of
energy-saving interventions and campaigns.
In a leased building, the landlord will often be
responsible for the common areas and will also need to
work in partnership with tenant organisations in order to
reduce energy use.
Facilities managers operating the building will also play
an important role, for example, by avoiding unnecessary
energy use through the use of building controls,
changing thermostat settings or by installing low energy
technological interventions.
The actual occupants and users of the building might be
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far down the chain of command and have little
responsibility for the building and its operation and little
interest in any savings that might ensue. Their main
concern is having a comfortable working environment
that supports their productivity and wellbeing.
Finally, in public access buildings, such as sports
centres, retail stores or libraries, there are the customers
who have little interest or ownership in the organisation
apart from its role as a service provider.
2.6.1 Survey Methodology
The methodology will consist of an analysis of the
organisational structure of the people responsible for day
to day operation and management of the buildings and a
questionnaire to ascertain the actual roles,
responsibilities and behaviours and working practices in
terms of energy management. This will enable us to
identify factors and impacts that distinguish a well-
managed building from one that is less well managed,
and to produce operational and asset recommendations
that will allow a methodology to be developed to roll out
more extensively.
The Questionnaires will:
Based on Energy Efficient Best Practice
Programme Energy Management Matrices [15];
Provide an overview of current energy
management practices and priorities;
Cover four key aspects:
o Energy management;
o Financial management;
o Awareness and information;
o Technical issues.
An additional section has been included covering
communication and monitoring of the impact of the
building on the occupants.
For each question, respondents are asked to select the
statement from a list of five that best describes the
situation in their building. The questionnaire form was
designed using the Qualtrics Research Suite Platform, a
software system that BRE uses to conduct online survey
research.
Respondents will be emailed an electronic link that takes
them straight through to the questionnaire form for easy
response. The data will be kept confidential to the
research team though will not be anonymous. However,
no names or other identifiers of individuals will be
included in any reports to the client.
The data will be analysed using SPSS statistical
software. As the numbers are small we will use mainly
descriptive statistics although we will also hope to carry
out some comparative analysis between the buildings.
3 INITIAL RESULTS AND DISCUSSION
The initial results in terms of energy performance are
given in Table 1. This table shows energy performance
in terms of:
The modelled asset usage including lift energy;
The operational usage from metered data;
The overall performance gap in terms of a
percentage;
Observations from this initial data are:
The performance gap was confirmed as real and
in the range 208 to 490 per cent;
The values observed were similar to that observed
by previous studies which were between 200 and
450 per cent (see Figure 1);
There was no relationship between the perceived
operational status (see Figure 3) and that
observed:
o Exemplar E was perceived to have good
operational status; has one of the best asset
ratings (65 C) and the lowest metered
usage. However, it has a performance gap
of 276 per cent which is around the
average of 288 per cent for the five
buildings;
o Exemplar C on the other hand was
perceived to have averaged operational
status; has the best asset rating (58 C); the
highest metered usage; which results in the
highest value for the performance gap at
490 per cent;
o Exemplar B was perceived to have poor
operational status; has the lowest asset
rating (110 E); the lowest metered usage;
which results in the lowest value for the
performance gap at 151 per cent;
An asset rating was then modelled using data collected
on site including hours of occupancy, HVAC set points
and energy data. This was done in an attempt to
granulate the performance gap into the contributions
made by modelling for compliance and those due to poor
operation.
The initial results indicated that the major effect was the
contribution was by modelling for compliance and not
operational issues. However, there were a pair of
negative results which indicted the modelling of the
real operational parameter was overestimating the
energy usage. As a result, further auditing will be
undertaken when the survey is undertaken to investigate
the operation of the assets.
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Table 1. Exemplar building energy performance
* After Data Entry of Occupancy, HVAC set points & Energy Data
4 CONCLUSIONS
The initial data collection was difficult and time-
consuming where the remaining data required for the
first phase (see Appendix 1) is currently being collected
or measured on-site. The current data collection and
storage processes for these buildings are ineffective due
to the lack of management and a dedicated resource.
The management structures for the five buildings are
shown in Appendices 2 and 3. The issues with the first
structure shown in Appendix 2 are that no-one is directly
responsible for the building; there is no on-site presence
or contact point; and the criss-crossing of
communication routes where responsibilities and roles
are unclear. The outcome is no focal point for the
management and operation of the building, where all
managerial actions are reactive.
The issues with the second structure are not so obvious
but the building still has no better than an average
performance gap. Therefore, more in-depth
investigations are required, and these are part of the on-
going research.
Currently, the team is investigating both the asset and
operational features of the five exemplar buildings in
more depth, in order to obtain more granularity in terms
of key performance aspects/indicators and the
underpinning reasons/drivers for the poor performance.
One thing is clear the management of data is a real issue
both in terms of its existence, quantity, quality, and
consistency. In the end if you cannot measure it you
cannot manage it which leads into the next part of this
projects investigation.
References
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Appendix 1: Initial operational data
1. Occupancy hours and density for each property
(P/M2)
2. Small Power Gains (W/M2)
3. HVAC Set Points (heating & cooling) (DegC)
4. Hot Water Usage (where known) (L/M2/Day)
5. Fresh Air Exchange rate (where applicable)
(L/S/M2)
6. Lighting Lux Levels (Lux)
7. Lighting times (on/off including holidays &
weekends) (Hour)
8. Display Lighting (W/M2)
9. There are 18 Management Questions (there will be
more in the 3rd phase):
a. Do you have a programme of regular inspection
and remedial measures for air tightness?
b. Do you have a programme of regular inspection
and remedial measures for fixed shading?
c. How are staff/users trained on how to use the
systems within the building?
d. Is managing energy part of somebodys job
description?
e. Are suitable qualified/trained staff running the
system?
f. Do you have a programme of monitoring &
targeting your energy consumption?
g. What level of understanding/training do
staff/users have in relation to lighting?
h. How Often are your luminaires cleaned?
i. Do you know where your HVAC system
controls are and how do you manage them?
j. How are the operating times of your HVAC
system managed?
k. How does timing of your HVAC system
respond to daily changes?
l. Do you adjust your HVAC set point
temperatures (heating and cooling) based on
external weather conditions on an on-going
basis?
m. What levels of checking of your HVAC
system does/will your energy manager carry
out?
n. How frequently is your HVAC plant serviced?
o. How frequently do you/will you undertake air
handling filter cleaning on your HVAC system?
p. How frequently are the air handling components
of your HVAC system cleaned/will be cleaned?
q. Do you have comfort controls sub-divided
within the zone and use/manage them on that
basis?
r. do you have lighting controls sub-divided
within the zone and use/manage them on
that basis?
10. MPAN & Electricity Meter Serial Numbers
11. months utility usage data for all fuel types (if
estimated please indicate)
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Appendix 2: Management structure for
exemplars A to D
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Appendix 3: Management structure for
exemplar E
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We have the ability to design good buildings and the knowledge to operate them in an effective and efficient manner – so why doesn’t it happen? The construction industry has in general been “designing for compliance” using software with “standardised driving conditions” – see below. We know how to build good performance buildings but the issue seems to be having the design feed through to performance-in-use1. This has led to what has been termed the performance gap. In reality this has two components): • The compliance gap; and • Actual performance gap.
Book
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Operators of commercial and public (ie non-domestic) buildings need clear and realistic guidance on targeting energy running costs for their properties and on the potential savings available. At their disposal are two seemingly irreconcilable indicators of performance: the asset rating (eg energy performance certificate or EPC), which provides a theoretical assessment of the asset under standard ‘driving conditions’ typical of that type of building in that location; and the operational rating (eg display energy certificate or DEC), which is based on energy bills so gives no indication of how much lower running costs could be. To truly understand how a building uses energy, it is necessary to know how the building has been designed and how it is used; this requires both an asset rating and an operational rating. The difference between these ratings – or between the predicted and actual performance of buildings – is known as the ‘performance gap’. This Information Paper looks at a way to bridge this gap and bring together these two assessments using the Green Deal assessment tool for non-domestic buildings, which allows the input of non-standard operating conditions, hours of operation and occupancy patterns. By defining these aspects of the building ‘in use’, the predicted energy performance of the asset can be brought closer to the in-use reality.
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The objective of this Information Paper is to bring together BRE’s wide-ranging knowledge and experience in energy surveys and auditing into a single publication. This is not a comprehensive technical guide, but highlights the important issues that need to be considered and directs the reader to more detailed technical information where appropriate. Guidance contained herein is applicable to: energy and facility managers looking to employ energy consultants to complete energy audits and surveys – to understand the scope and context of the works energy consultants and advisers looking to maintain their professional expertise and to update their knowledge of the approach and techniques needed to comply with recent and imminent legislation and standards system and equipment suppliers looking to assess how their particular technology or service will support clients in meeting recent and imminent legislation and standards. This publication follows the structure of BS EN 16247-1 and reviews its content. It is intended to put sufficient flesh on the bones of the standard to enable good-quality audits to be specified.
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A publication devised jointly by Building Research Establishment and ESTA to provide practical measures and advice to energy, facility and maintenance managers on how to manage energy. A step-by-step approach to energy management is explained, together with the use of a matrix tool for implementing energy management initiatives within an organisation. The tool can help identify areas for improvement, prioritise energy management activities and maximise benefits. Most of the examples are from the built environment but the principles can be employed in any organisation or industry sector. The guidance is applicable by anyone responsible for energy management in an organisation, from board level to operational staff.
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One of the biggest obstacles to the uptake of low carbon technologies is the production of a poor business case. Unless the business case stacks up and can survive close scrutiny, the idea will be thrown out, no matter how good it is. One of the major disjoints that exist in organisations is that between the technical departments and the management board. Rarely do the benefits of energy savings alone justify investment in energy efficient technologies and energy management initiatives. However, this is starting to change due to 10 per cent year-on-year increases in energy prices. Energy is now a significant cost even in an office-based environment, especially with the ever-expanding use of IT and office equipment. However, reduced maintenance and increased productivity need to be factored in if the business case is to stack up.
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Buildings rarely perform as well as their designers predicted – energy consumption can be as much as double what was expected, so annual energy costs can also be doubled. This difference has become known as the performance gap – in some cases it is due to more intensive or extended occupancy, but often the major cause is that the building services are operated inefficiently and not as intended by the designers. The performance gap is difficult to quantify because the performance ratings obtained from energy certificates at design and in use are, amazingly, not directly comparable. The two seemingly irreconcilable indicators of performance available are energy performance certificates (EPCs) which provide a theoretical assessment of their asset but under standardised 'driving conditions'; while operational ratings based on energy bills give no indication of how much lower those bills could be. The operational rating is nearly always higher due to non-standard hours of operation, occupancy patterns and unregulated loads, such as IT and office equipment. To truly understand how a building uses energy it is necessary to know something about the building itself and about how it is used; this requires both an asset rating and an operational energy rating. Dr Andy Lewry has just published a booklet [1], with ESTA (the Energy Services and Technology Association) looking at a way to bring the two assessments together. The UK Government’s Green Deal assessment process (GD-SBEM) provides, for the first time, a tool to reconcile these pieces of information, which ties in with the requirements of the UK government’s ‘Energy Savings Opportunity Scheme’ (ESOS). The Green Deal Tool can be used to understand the energy use in a building, highlighting where improvements can be made, and can also be used to produce the data to underpin any business case for investment in energy efficiency measures.
Conference Paper
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To truly understand how a building uses energy you require both an Asset and an Operational energy rating. An asset rating models the theoretical, as designed, energy efficiency of a particular building. However, the asset rating provides no information about how the building is operated in practice. The operational rating records the actual energy use from a building over the course of a year, and benchmarks it against buildings of similar type. There is significant confusion in the UK non-domestic property market between the two different building energy ratings currently in use. This paper discussed the underlying principles of how the UK Green Deal tool was designed, using the Interface to the Simple Building Energy Modeling (iSBEM), and how it has bridged the gap between the two ratings to provide a more complete picture of how energy is used in a building
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Current methods for calculating elevator energy consumption rely on rules of thumb, the accuracy of which is very limited. In this paper a new general energy modeling approach is proposed. The resulting energy model can be used to calculate the energy consumption of any individual elevator trip. The energy model is linked to an elevator traffic simulation program, which enables the energy consumption of an elevator installation to be calculated in any building, and for any passenger traffic scenario.
IES Faculty: Intelligent Big Data in Building Services
  • N Khan
N. Khan, N., 'IES Faculty: Intelligent Big Data in Building Services', CIBSE Building Simulation Group event, (2016). IES, London.
Building 4 People: Quantifying the benefits of energy renovation investments in schools, offices and hospitals
  • J Kockat
  • P V Dorizas
  • J Volt
  • J Staniaszek
J. Kockat, P. V.Dorizas, J. Volt, J. and J. Staniaszek, Building 4 People: Quantifying the benefits of energy renovation investments in schools, offices and hospitals, Buildings 2030/BPIE report, (2018), available at https://www.buildings2030.com/spotlight/study/ (accessed 30th Nov. 2018).