The research will focus on two types of buildings: residential buildings and public buildings. The research plan covers the aspects of defining the ICT based energy management services to be offered, the architecture definition of the systems, definition of the methodology to evaluate energy savings and user behaviour changes and the analysis of the achieved outputs of pilot buildings in real operation conditions.

1. ENERGY OPTIMIZATION OF PUBLIC AND SOCIAL HOUSING
BUILDINGS USING ICT BASED- SERVICES
J. Cipriano
a, S. Danov
a
aCIMNE, Building Energy and Environment Group, UPC Campus Terrassa Edici GAIA (TR14) C/ Rambla
Sant Nebridi 22 08222 Terrassa, Spain
Abstract
Occupants' behavior, building control and energy optimization are strongly correlated and need a
holistic scientic approach to study them. Answering this question is the main focus of this work.
Some experiences in public buildings and social housing will also be presented and some indications
on how these drawbacks can be overcome will be proposed. Energy optimization strategies are
analyzed. These are mainly based on providing useful Energy Awareness Services and Energy
Management Services supported by monitoring and, in some cases with automation, which may
reduce the random behavior of occupant to manageable levels. The research will focus on two types
of buildings: residential buildings and public buildings. The research plan covers the aspects of
dening the ICT based energy management services to be oered, the architecture denition of the
systems, denition of the methodology to evaluate energy savings and user behaviour changes and
the analysis of the achieved outputs of pilot buildings in real operation conditions.
Keywords: Optimization in buildings energy eciency,
1. Introduction
Energy optimization of existing buildings requires a combination of several technologies, analysis
techniques, and holistic consultancy approaches which can be enhanced and strengthened with the
existing wide variety of ICT based technologies. However, once they are implemented in building
operation, many doubts about the level of automation, the end users interaction and how the
energy performance characterization and simulation models can be integrated appear and remain
still unsolved. There are three main approaches to set up optimization strategies based on ICT:
occupant-centered user awareness and management strategy; fully automated strategy with minimal
occupant interaction; automatic control with improved logic through simulation and user modeling.
The rst approach has been put in practice in recent year through many European innovative
projects, funded by the ICT-PSP innovation program. These projects have been facing the rolling
out of ICT based services for improving energy awareness and management in public and social
housing buildings. Some of the achieved energy savings outputs are summarized in the eeMeasure
web portal
1. In the majority of these projects, the energy optimization strategy is performed based
exclusively on user interaction. The deployed services are usually made up of a combination of
web or smart phone visual interfaces and personalized advice services (energy coach,telephone call,
alarms, personalized tips...). They are classied as Energy Awareness Services (EAS) for those
services oered to tenants or sta personnel, and as Energy Management Services (EMS), for those
Email addresses: cipriano@cimne.upc.edu (J. Cipriano), sdanov@cimne.upc.edu (S. Danov)
1http://eemeasure.smartspaces.eu/eemeasure/.
Preprint submitted to Elsevier June 13, 2013

2. services oered to technical sta or energy managers. In these service process models, integration of
predictive energy modeling as well as building energy performance modeling is possible. However,
at present, very few pilot sites implemented them as a support for their ICT based services. In
Catalonia, the company INERGY
2 performed a program of energy consumption reduction based on
low cost measures in 24 public schools of the City of Girona. This program allowed a comparison
between energy management models based exclusively on user awareness models (through monthly
energy billing information) and automated control models based on remote control of the heating
boilers. Large data scattering was detected in the comparative results and the conclusions were that
this is probably related to occupants' behaviour. These projects do not represent a comprehensive
inventory of actions across Europe, instead, they collectively represent a range of strategies aiming
at demonstrating that occupant-centred control systems, based on advanced ICT components and
systems, can contribute directly to reducing both the peak-consumption and energy demand.
The second approach focuses more on exploiting the degrees of freedom of fully automated
control systems for the sake of optimizing energy eciency. In [1], for instance, three dierent
approaches of combination of simulation and automated controls without human interaction are
examined and their advantages and disadvantages are analysed. More recently, in the project
SEEMPubs
3 monitoring and energy management systems for buildings are developed and applied
[2]. They are made up of a combination of automated control with dynamic building simulations to
optimize the control logic. In this research, a control strategy was implemented in pilot buildings
and, once it was under operation, some dierences between the achieved energy savings and the
expected ones were observed and some conclusion about the impact of the occupants' behaviour in
these discrepancies were highlighted.
The third approach combines energy performance building simulation with ICT based systems.
In this approach it is important to consider that many previous studies demonstrated a large gap
between simulated and measured building energy use. Signicant discrepancies between simulated
and measured building energy use were found in several studies [3, 4, 5, 6, 7]. One of the main
reasons, identied in Annex 53
4, for the dierence is neglecting or over-simplifying the inuence
of occupants' behaviour (OB). Meanwhile OB acts in a stochastic way, and varies by time and
occupant. There are signicant interactions between the occupant the buildings and the ICT
based control systems. The occupants' expectation of comfort or satisfaction with the building
environment drives the occupant to perform dierent controls, such as adjusting the thermostat in
spaces, opening windows for ventilation, turning on lights, pulling down the window blinds, and
consuming domestic hot water. Dierent occupants' behaviors have dierent eects on building
performance and energy use. The building performance, on the other hand, will have economic,
physiological and psychological impacts on occupants' expectations.
From these projects and studies, some evidence showed that building energy consumption is not
only be aected by technology employed in buildings, but also by many other factors. Among these
factors, occupants' behavior and interaction with the ICT based control systems takes an extremely
important role. Measured building energy use data [8, 9]demonstrated that some buildings with
advanced building control technology (based on automated ICT services) consumed more energy
than others with conventional or low-cost technology. One of the most important reasons is
the dierence in occupants' behavior and how they inuence energy consumption through their
use of dierent equipment in the building, as stated by [10, 11]. Correctly understanding the
interactions between OB and building controls is critical to optimize energy eciency in buildings.
Dierent customers need dierent ICT based solutions, and dierent ICT based solutions may aect
2www.inergybcn.com
3http://seempubs.polito.it/
4http://www.ecbcsa53.org/
2

3. or change customers' behavior in buildings. The eciency level of building control technologies
is important, but what is more important is the eective interaction between occupant and the
building equipment to meet occupants' comfort and health needs and to avoid continuing complains.
This last aspect is many times underestimated and, as demonstrated by [12], there is a high potential
of integrating within ICT based control systems, some methods to properly collect and answer
occupants' complaints and to use them as a tool for permanent diagnosing of what goes wrong in
buildings.
Therefore, occupants' behavior, building control and energy optimization are strongly correlated
and need a holistic scientic approach to study them. Answering this question is the main focus
of this work. Some experiences in public buildings and social housing will also be presented and
some indications on how these drawbacks can be overcome will be proposed. Energy optimization
strategies are analyzed. These are mainly based on providing useful EAS and EMS supported by
monitoring and, in some cases with automation, which may reduce the random behavior of occupant
to manageable levels. The research will focus on two types of buildings: residential buildings and
public buildings. The research plan covers the aspects of dening the ICT based energy management
services to be oered, the architecture denition of the systems, the integration of intelligence
in the services (mainly through smart alarms and simplied building energy performance models
), denition of the methodology to evaluate energy savings and user behaviour changes and the
analysis of the achieved outputs of pilot buildings in real operation conditions.
2. Geographical coverage and pilot projects
This research is based on the results of the following projects: eSESH
5; BECA
6; and Girona
7.
In the case of public buildings, the ICT based services are evaluated in 24 public schools of the
City of Girona (Spain).
Pilot site Total number of public
buildings included in
the analysis
Automated ICT based
energy management
services
EAS/EMS
Girona 24 schools 16 schools 8 schools
Table 1: Number of pilot public buildings
In Table 1, a summary with the number of analyzed public buildings is shown. As it can be
observed, some of the schools complement EAS and EMS services with a low-level of automation
applied in the heating boilers.
In the case of social housing, the ICT based services are evaluated in 10 pilots in 6 countries
across Europe as summarized in Table 2. More than 5,000 social housing tenants were given access
to Energy Awareness and/or Energy Management As it can be observed in Table 2, from the overall
number of dwellings available, only those with reliable data were selected for the analysis.
5www.eSESH.eu
6www.beca-project.eu
7www.inergybcn.com
3

4. Pilot site Total number of
dwellings involved
Number of
dwellings included
in the analysis
(EAS)
Country
Angers 993 DHW: 404
Electricity: 426
France
Catalonia 77 Electricity: 44
Gas: 38
Spain
Extremadura 116 Electricity: 78 Spain
Frankfurt 358 Heating/DHW: 149 Germany
Karlsruhe 533 Heating: 323
DHW: 260
Germany
Linz 361 Electricity: 166
Heating: 159
Austria
Moulins 399 DHW: 342 France
Solingen 296 Heating: 166 Germany
North Italy 468 Electricity: 253
Gas: 480
District heating: 95
Italy
Westerlo 121 Electricity: 30
Heating: 44
Belgium
In total 3722 1,800-2,200 6
Table 2: Number of pilot dwellings and number after lttering
3. ICT architecture
3.1. ICT architecture for EAS/EMS in social housing
Within eSESH and BECA projects, an eort to dene a common ICT architecture for all
the pilot sites was carried out. The ICT architecture is designed adopting a top-down approach.
General top-level architecture, conceptual diagrams and logical layered architecture description
using a standard Unied Modelling Language (UML) provide link between hardware solutions and
service functionality. In order to build a complex and eective ICT system for providing information
about own energy consumption (tenants and operating sta), various types of requirements have
to be taken into account.
4

5. (a) Energy Awareness Services process models for so-
cial housing (eSEH project)
(b) Energy Management Services process models for
social housing (eSEH project
Figure 1: Role interface diagrams for EAS and EMS in social housing
(a) Top level architecture (b) Conceptual application architecture
Figure 2: Integrated ICT architecture for social housing EAS/EMS
In Figure 1 the role-interface diagrams of the User Awareness Services and of the Energy Man-
agement Services are showed respectively. The Role-Interface diagram is suggested in order to
provide quick view to the developed systems from point of view of the main participants' roles,
technical infrastructures and interfaces through which each role will participate in the RUAS and
RMS.
In Figure 2 the integrated ICT architecture for oering EAS/EMS in social housing is presented.
This architecture is the generalization of the principal characteristics of all pilot-site systems. It is
5

6. representative for the whole family of systems used in the social housing pilot sites. Some of the
pilot-site systems have implemented only part of the features of this general architecture, which is
relevant to their pilot-site situation.
The concept diagram shown in Figure 2 is represented in layers grouping dierent functionalities.
Each layer is composed by functional and logical components that communicate through well-dened
interfaces. In this architectural view the layers may be located on the same physical hardware, or
may be on separate hardware components.
3.2. ICT architecture for EAS/EMS in public buildings
In the case of public buildings, the same UML standard was used. However, in public build-
ings there many stakeholders involved in energy managament issues. More specically, four main
stakeholder areas, with their own specic requirements, need to be addressed:
1. Energy expert, that needs a useful tool to analyse the energy results (Product Management).
2. Sta or end users, that need useful visualization of results capable of inuencing their be-
haviour
3. Software Application IT specialist, the one who is in charge of developing the Software Ap-
plication.
4. IT infrastructure and data Collecting System (System and Hardware Engineer) and the com-
munication of the meter data to the central system
In order to eventually address these specic requirements, the proposed model is made up of ve
main views: a) the logical view, which shows the functional requirements related to the nal user.;
b) the process view, which captures the concurrency aspects between the stakeholders and the
logical elements of the architecture; c) the deployment view, which describes the mapping(s) of
the software onto the hardware; d) the development view, which describes the static organization
of the software; e) the scenarios, which are made up of the the selected use cases. Figure 3 and
Figure 4show schemes of the ve main views followed to describe the ICT architecture for oering
EAS and EMS services in public buildings.
(a) Model 4+1 for public buildings (b) Bussiness process model
Figure 3: Description of the overall architecture view in public buildings
6

7. (a) Model 4+1 for public buildings (b) Bussiness process model
Figure 4: Description of the overall architecture view in public buildings
4. Results in social housing pilot sites
4.1. Methodology used in the social housing pilot sites
The energy consumption measurement and evaluation approach followed internationally ac-
cepted standards (e.g. the International Performance Measurement and Verication Protocol (IP-
MVP)
81). In IPMVP, four options (A-D) are given for measurement and verication, but in the
context of the analyzed social housing pilot buildings, only option C is applicable. Principally,
that is a before-after comparison (before and after an intervention, e.g. the implementation of
an ICT-based consumption feedback solution) using prior consumption for an estimation of non-
intervention consumption. An additional source of estimation is a control building approach, based
on dening a control group of tenants, which are excluded from the ICT based services, and an
experimental group which is receiving the ICT based services for the pilot operation period. A
combination of both estimation methodologies is used to evaluate the achieved energy savings of
the pilot site buildings. At most of the pilot sites the reporting period ended with the year 2012
so that the latest data update has been carried out in January 2013. For calculating the energy
savings, the following parameters has been taken into account: dwelling sizes, household sizes as
well as temperature adjustments where appropriate.The analysis shown always provides:
ˆ Percentages of global energy savings related to the whole cleansed consumption datasets and
related to all available energy types
ˆ Global gures of total consumption in relevant units (kWh, m3
) before and after the imple-
mentation of the ICT based services
ˆ Global values of savings in kWh/a (if applicable HDD corrected) or m3
/a as basis for
Carbon dioxide reduction in kgCO2/a
Savings in ¿/a
8http://www.evo-world.org/index.php?option=com_contenttask=viewid=272Itemid=60lang=en
7

8. ˆ Average consumption per dwelling and year compared to the annual national average
ˆ Savings, CO2 reductions and monetary savings per pilot dwelling.
The basic tenant-related evaluation approach followed a quasi-experimental design including a three-
stage data collection. A quasi-experimental design describes the availability of a control group, but
means in contrast to a real experimental design - that both groups will not be selected randomly.
Instead of that, the housing providers by themselves decide on the assignment of tenants to one or
another group. Generally, in the analyzed pilot sites, there were three tenant groups available:
Experimental or treatment group with:
1. Active users with full access and a regular use of the service
2. Passive users with possible (theoretical) access to the service but without (practical) willing-
ness to use
Control-group without theoretical and practical access to the service.
Often a real control group approach is not appropriate because of the absence of comparable build-
ings/dwellings, too small sample sizes or a combination of both. The comparison of active users
and passive users in fact has some diculties due to a systematic bias because passive users are not
very interested in the services at all, which may be caused by several reasons. Notwithstanding,
under certain conditions by taking into account that bias, for example by including this group in
tenant surveys too, passive users can serve as an adequate comparison group. All pilot sites realised
tenant surveys. 7 out of 10 pilot sites carried out a longitudinal study with baseline and nal tenant
survey. In Figure 5, the survey sample sizes for each pilot site are shown.
Figure 5: Tenant survey sample sizes
The data provision has been realised by the pilot site managers using a standardised evaluation
template which included: an INFO sheet collecting dwelling numbers/tenant IDs, dwelling and
household size, number of rooms , change of tenancy/move-in date and the results of the tenant
surveys following a standardised code plan a Consumption data sheet separately for all measured
energy types related to the eSESH service (separately for EAS and EMS if applicable) a Service
8

9. use sheet which collected the measured web portal log-ins.All consumption data sets have been put
through a data cleansing procedure. That means dwellings with change of tenancy in the project
duration were excluded from the data analysis. The same applies to (temporarily) unoccupied
dwellings or long periods of absence of the tenant (zero values) and to cases with obvious inconsis-
tencies in the measurements (e.g. implausible or extreme values due to malfunctions of the metering
devices).
4.2. Achieved global energy savings
All ten pilots achieved savings. The majority of pilot sites achieved the saving targets dened
in evaluation planning, some at least partly. In most cases (much) more than 50% of the involved
pilot tenants achieved measurable savings. In Figure 6the achieved energy savings per pilot site are
shown.
Figure 6: Achieved global energy savings per pilot site
In Figure 7, the achieved global energy savings per energy type is shown.
9

10. Figure 7: Achieved global energy savings per erngy type
With an overall saving of heat energy consumption of 9% across all pilot sites met a reasonable
target. This presents a signicant achievement considering the outstanding importance of reducing
energy use for domestic heating, which accounts for more than two thirds of energy consumption
in the residential sector.
4.3. Increased user awareness
To evaluate the he increase in user awareness a quantication of the number of tenant accessing
the EAS is necesssary. In Figure 8 the obtained data of interested tenants in EAS, as well as
the percentage of active users is shown. It can be observed that 2,666 tenant households over
5,865 individuals (average household size 2.2) have been enabled to make use of EAS. One third of
the total number of potential users became actual users of the tenant web portal (gathered from
measured portal log-ins).
Figure 8: Achieved number of EAS users
Figure 9 shows the level of raised user awareness ant the number of pilot sites which reported
behaviour changes. Some conclusions can be obtained:
High level = 9 pilots: More than 50% of survey respondents/EAS users described their interest
in consumption and/or have a high energy saving norm` and/or keep now an eye on their
consumption.
Medium level = 1 pilot: More than 50% of survey respondents/EAS users reported on an increased
knowledge about energy consumption.
10

11. Furthermore, in 7 pilot sites the respondents reported on optimized energy consumption behaviour.
Figure 9: Achieved user awareness increase
4.4. Set up of smart alarms system
In order to provide a rst level of intelligence in the energy optimization strategy, 49 combined
alarms were programmed and implemented in some pilot sites. These alarms gave detailed infor-
mation of anomalies in space heating, DHW and electric energy consumption so that the tenant
can take decisions to reduce its energy consumption. The control levels of the alarms were obtained
based on data series analysis methods and some basic linear energy performance characterization
methods.
Figure 10 shows an example of the implemented alarms in the social housing pilots.
Figure 10: Example of smar alarms implemented in the pilot sites
5. Results in public buildings
5.1. Methodology used in public buildings sites
The IPMVP oers several options for calculating energy savings. This project is dealing with
public buildings and is gathering half-hourly data from the pilot sites. To ensure a simple direct
comparison is possible between sites, the project will be following an approach equivalent to IPMVP
option C where possible. For this, data for the whole building are separated into periods before
the intervention (the `baseline') and after the inadmvotervention (the `reporting period' or `test
period'). A statistical model is tted to the baseline data and is used to forecast forwards into the
test period. Savings are estimated as the dierence between measured values in the test period
and the consumption forecast. Simple statistical models are commonly used to model energy
11

12. consumption. In particular the Variable Base Degree Day (VBDD) model and its variants allow
for the inuence of outside air temperature to be modelled fairly simply.
Regarding the change in occupants' behaviour, the evaluation approach followed the same proce-
dure than the social housing pilot sites. In this case, the concept of tenant was substituted by sta
personnel. The EMS were evaluated with the technical personnel and with the energy manager.
5.2. Energy savings achieved
In the pilot site of Girona, there were two dierent ICT based services implemented:
1. ICT Energy Management Service based on monthly monitored data which can allow detecting
some deviations in energy consumption and setting up an alarm system based on seasonal
control
2. ICT Energy Management Services and Energy Awareness Services combined with automation
of the heating boilers.
In order to perform a cross comparison, a normalized indicator of energy consumption was calculated
for each public school (Kwhyear/HDD15).
(a) Achieved energy savings in the schools with basic EMS
(b) Achieved energy savings in the schools with automation
in the heating boilers
Figure 11: Global energy savings of the schools in Girona
12

13. In Figure 11the evolution of the normalized energy indicator is shown for the schools which were
receiving the rst level of ICT based services (a), and for the schools with automated systems in
the heating boilers (b). The red line is the average indicator of all the schools.The baseline was
dened in 2009 while 2010 was the year when the ICT based services start operating. As it can
be appreciated, in both cases energy savings are achieved. However, the schools with automated
systems achieve higher energy savings than the other ones.
The accumulative energy saving achieved in the 16 schools with automation systems, from 2009
to 2012 was of 26 % of the baseline. From an economical point of view, global energy savings of 28
% were achieved.
6. Conclusions
The operation of the EAS and EMS services in public buildings and social housing, based on
a common reference architecture, use cases and process models in several European pilot sites
provided rich experience. The ICT based services at each pilot site were adapted to the local
situation, the specic typology of building energy supply systems and taking into account the user
group requirements in the design phase. This approach makes the pilot operation one of the most
comprehensive activities, to our knowledge, for testing energy awareness and management services
for nal user of social housing and public buildings.
The pilot operation activity permitted to extract useful lessons for replication by others, out-
lining important aspects to be addressed and improved in the future. The lessons learned comprise
three main aspects aecting the service success:
1. Eectiveness of the user interfaces and information content
2. Pilot organisation
3. Appropriateness of the technical means
With regard to the service eectiveness for energy saving, it should be clearly distinguished between
EMS and EAS. Professional EMS are directed to maintenance sta, which provide monitoring and
optimisation of central building energy systems, unconditionally proved to be very eective for
achieving energy savings. The situation is much more complex analysing the results of EAS directed
to tenants or occupants (sta of public buildings), as there is a wide spectrum of factors inuencing
their behaviour and attitudes. The resulting eectiveness of the services depends on the particular
combination of these factors. Motivation of occupant to save energy is the dominant factor for
service success.
Among social housing tenants the interest in services is driven more by economic reasons than
by environmental consciousness, although the latter aspect is growing in interest, especially among
young tenants. On the other hand, in public buildings this is not dominant factor, while improve-
ment of building management and projected image to the citizens seems a stronger factor. For this
reason it is important to establish a clear link between energy saving behaviour and economical
savings.
Social policies in some European countries where unemployed tenants do not pay, or pay very
low rates for energy, or major parts of energy costs of tenants living on social benets are paid by
the state (through social benet payments) (e.g. Germany) is strongly de-motivating particularly
social housing tenants in the use of EAS, and generally in energy saving. Another economically
de-motivating factor for energy saving attitudes is the relatively high xed part in the energy bills
paid to the energy supply companies in concept of power / supply service contracting fee. With low
energy consumption rate, typical for social housing tenants, energy saving aects only the variable
part of the bill, while the xed remains unchanged. In this sense, interesting services are those
orientated to reducing the peak demand (peak shedding) (e.g. Angers), that may lead to reduction
of the contracted power, and respectively to economic saving for tenants.
13

14. Age, educational background, knowledge and habits for using new ICT technologies are other
powerful factors for more active use of the ICT based services. Dierent groups of tenants showed
also dierent interest in the services and, in general, dierent preferences to the interfaces through
which the EAS are communicated. The majority of elderly tenants and those with poor prociency
in ICT have a preference for regular reports on paper.
As a conclusion, in order to communicate eectively the EAS and EMS, it seems important to
oer to the tenants, sta personnel and technical sta, various interface options in order to match
better their preferences and lifestyles. Some technological prospecting is necessary for the lifecycle
of the project to avoid selection of interface options that might become obsolete soon. It must be
taken into account that, due to more demanding economic necessities, a lot of social housing tenants
already apply energy saving practices in their homes. Probably, the margin for savings from that
kind of advices is already exhausted, so EAS have to emphasise above other, more interesting and
unique features that might be provided by analysing the specic measured data and oering the
information in personalised way.
Buildings incorporating energy eciency features (low energy buildings, passive solar buildings)
represent a special case that require tenant interaction, like opening or closing registers, etc., in
order to produce savings. The construction of this kind of buildings has been growing all over
Europe in the last years. In such cases tenants should have good knowledge in order to use the
building properly to save energy. Incorporating instructions to tenants how to properly use these
building features in the EAS could be very eective. A good example for this is the Catalonia pilot
site, where this sort of information given to tenants contributed to the achievement of considerable
energy savings. EAS and EMS in some cases compete for the same savings. As e.g. in the case of
optimisation of the operation of central heating systems, the EMS limiting the internal temperature,
or reducing or stopping heating during the night diminishes or cancels the possibility of saving from
similar functionalities and recommendations in EAS. For this reason some of the pilots applying
such EMS services will not achieve the full expected savings from the EAS but these are reected
in those of the EMS (e.g. Solingen, Frankfurt).
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