CARE4CLIMATE_Leandro_Madrazo_published.pdf

With successful practices to climate neutrality
Conference LIFE IP CARE4CLIMATE 2022:
8 June 2022, Ljubljana, Slovenia
Energy information systems to improve energy
performance of buildings
Leandro Madrazo
ARC Engineering and Architecture La Salle
Ramon Llull University
Barcelona, Spain

- ARC Engineering and
Architecture La Salle, Ramon Llull
University, Barcelona, is a
multidisciplinary research group
dedicated to the design,
development and application of
information and communication
technologies (ICT) in the
Architecture, Engineering and
Construction (AEC) sector.
- It started in 1999. Members are
architects, computer scientists,
designers.
- Three main lines of research:
- Smart cities
- ICT for Architecture,
Engineering and
Construction
- Technology-enhanced
learning
www.salle.url.edu/arc

2008-2011 IntUBE: Intelligent Use of Building’s Energy Information
7th Framework Programme / Coordinator: VTT, Finland
2009-2012 RÉPENER: Control and Improvement of Energy Efficiency In Buildings through the Use of Repositories
Spanish National RDI Plan / Coordinator: ARC Engineering and Architecture La Salle, Spain
2011-2014 SEMANCO: Semantic Tools for Carbon Reduction in Urban Planning
7th Framework Programme / Coordinator: ARC Engineering and Architecture La Salle, Spain
2013-2016 OPTIMUS: Optimising the Energy Use in Cities with Smart Decision Support Systems
7th Framework Programme / Coordinator: National Technical University of Athens, Greece
2015-2019 OPTEEMAL: Optimised Energy Efficient Design Platform for Refurbishment at District Level
Horizon 2020 Programme / Coordinator: CARTIF, Spain
2014-2017 ENERSI: Energy Service Platform Based on the Integration of Data from Multiple Sources
Spanish National RDI Plan / Coordinator: Innovati Networks, Spain
Research projects on energy information systems carried out by ARC since 2008
2021-2024 TIMEPAC: Towards Innovative Methods for Energy Performance Assessment and Certification.
Horizon 2020 Programme / Coordinator: ARC Engineering and Architecture La Salle, Spain
2021-2024 RETABIT: Multi-dimensional Data Driven Services to Foster Residential Building Retrofitting Programmes in
the Implementation of SECAPs National Research Plan / Coordinator: ARC Engineering and Architecture La Salle, Spain
Lines of work:
• Data
integration
(semantic
technologies)
• Building
energy
performance
at multiple
scales
• Development
of new tools
for energy
related data
integration,
analysis and
visualization

2008-2011
IntUBE: Intelligent Use of Building’s Energy Information

Energy Information Integration
Platform EIIP
PIM server
SIM server
BIM server
RD server
Distributed repositories
s
e
r
v
i
c
e
s
Climate
Monitoring
data
Building
data
Simulation
data
ENERGY INFORMATION CYCLE
DATA
s
e
r
v
i
c
e
s
USERS
Energy
companies
Building
Owner
Building
Designer
Occupants
…
IntUBE – Energy Information Integration Platform (2008-2011)
Extract
benchmark
Monitoring
data
Performance
indicators

EIIP – Energy Information Integration Platform
BIM server SIM server RD server
PIM server
Concept
Design
develop.
Simulation tool
Building lifecycle
Control
/
maintenance
Retrofit
design
KNOWLEDGE
e.g. benchmark
Monitoring/BMS
INFORMATION
Capturing the energy information flow throughout the different stages of the whole building lifecycle
BIM
Static data
(geometry, spaces,
building systems)
Simulated energy
performance
data
Real monitored
data (climate,
occupancy)
Metadata to
interlink
repositories

Demonstration scenario
Publicly subsidised apartment
building in Cerdanyola del
Vallès, Barcelona.
Contact sensors for opening status windows and doors
Temperature and relative humidity, inside, outside, air collector
Illuminance sensor for blind position detection
Touch Panel Screen
Hub connected to Internet
Boiler and heat exchanger SHW
Apartment 2.1
Apartment 2.2
S8
S8
S7
S7
S4
S4
S6
S6
S10
S10
S1
S1
S5
S5
S17
S17 S15
S15 S13
S13
S14
S14
S18
S18
S11
S11
S12
S12
FUNITEC (24 sensors)
•Temperature: 7
•Humidity: 7
•State
•Blinds: 5
•Windows: 5
CIMNE (32 sensors)
•Temperature: 16
•Pulse: 4
•Energy Rate: 12
A demonstration scenario was implemented in a building where several
sensors were installed and a screen to advise dwellers.

kg
0.15
0.15
kg
User interface installed in a social housing building to advise dwellers to reduce
their energy consumption. Also, it shows current consumption of each apartment.

An operative EIIP (Energy Information Integration Platform)
interlinking energy data throughout all stages of the building
lifecycle:
1. Storing BIM models in a server (volumes/spaces in
Revit)
2. Enriching BIM models with energy attributes
3. Storing outputs generated with simulation software
4. Integrating monitoring data (OPC server) in the EIIP
What was achieved in IntUBE (2008-2011):

2009-2012
RÉPENER: Control and Improvement of Energy Efficiency In Buildings
through the Use of Repositories

www.seis-system.org
2009-2012 RÉPENER: Control and Improvement of Energy Efficiency In Buildings through the Use of Repositories
Interlinked data sources:
- Cadastre (open data)
- EPCs (ICAEN)
- Monitoring data (especific buildings)
- Climate data (open data)

User Facilities Manager:
- Examples of energy
efficient buildings to learn
from best practices

from best practices
- Reference values: confort,
energy demand, energy
consumption, primary
energy

from best practices
- Reference values: confort,
energy demand, energy
consumption, primary
energy
- Location of the reference
buildings

Glossary:
- Ontology to interlink data
from different sources and
domains

Integration of data from multiple sources using Semantic
Web technologies
• Taxonomy of energy related data
• Ontology representing a building energy model
• On-line application focused on specific user profiles
What was achieved in RÉPENER (2009-12):

2011-2014
SEMANCO: Semantic Tools for Carbon Reduction in Urban Planning

www.semanco-project.eu

Building
repositories
Energy
data
Environmental
data
Economic
data
Enabling scenarios for stakeholders
Building stock
energy modelling
tool
Advanced energy
information
analysis tools
Interactive
design tool
Energy simulation
and trade-off tool
Policy Makers Citizens
Designers/Engineers Building Managers
Planners
Regulations Urban Developments Building Operations
Planning strategies
WP2
WP6
WP8
Technological
Platform
SEMANTIC ENERGY INFORMATION FRAMEWORK (SEIF)
CO2 emissions
reduction!
Application
domains
Stakeholders
WP3
WP5
WP4
Getting heterogeneous, distributed energy related data

Building
repositories
Energy
data
Environmental
data
Economic
data
Building stock
energy modelling
tool
Advanced energy
information
analysis tools
Interactive
design tool
Energy simulation
and trade-off tool
Planners
Planning strategies
WP2
WP6
WP8
Technological
Platform
CO2 emissions
reduction!
Application
domains
Stakeholders
WP3
WP5
WP4
Modelling data with ontologies

Building
repositories
Energy
data
Environmental
data
Economic
data
Building stock
energy modelling
tool
Advanced energy
information
analysis tools
Interactive
design tool
Energy simulation
and trade-off tool
Planners
Planning strategies
WP2
WP6
WP8
Technological
Platform
CO2 emissions
reduction!
Application
domains
Stakeholders
WP3
WP5
WP4
Providing tools and services to interoperate with data

Building
repositories
Energy
data
Environmental
data
Economic
data
Building stock
energy modelling
tool
Advanced energy
information
analysis tools
Interactive
design tool
Energy simulation
and trade-off tool
Planners
Planning strategies
WP2
WP6
WP8
Technological
Platform
CO2 emissions
reduction!
Application
domains
Stakeholders
WP3
WP5
WP4
Using tools at different decision making realms

Building
repositories
Energy
data
Environmental
data
Economic
data
Building stock
energy modelling
tool
Advanced energy
information
analysis tools
Interactive
design tool
Energy simulation
and trade-off tool
Planners
Planning strategies
WP2
WP6
WP8
Technological
Platform
CO2 emissions
reduction!
Application
domains
Stakeholders
WP3
WP5
WP4
Using tools at different decision making realms
Reducing carbon emissions

Data connected through the
Semantic Energy Information
Framework
OPEN SEMANTIC DATA MODELS
DATA TOOLS

Home Case Studies Analyses Data Services About
Newcastle United Kingdom
Legend
Source:
Indicator:
Units:
- m2 year
- year
Scale:
- District
- Building
Filters
54000
CO2 Emissions (tCO2 year)
213
F
SAP Rate (u.)
G
Tenure
Private owner
1234567
Energy demand (kj. year)
2342
10
Index of multipledeprivation(u)
3
Apply filters
Reset filters
Number of buildings: 15322 / 50200
Total surface built: 9023/ 34342m2
Urban indicators
Age average of building stock: 77 / 42 years
Index of multipledeprivation: 4 / 15
Income score: 53/ 52
District indicators
Fuel poverty: 90/ 20%
CO2 Emissions (tCO2 year): 234/ 3243.
Energy Consumption: 34342 / 23423
Performance indicators
Energy demand: 2343/ 234
SAP rate: 24 / 54
….
…..
Table
3D Map
Projection
Current status
Relationship
Building 1
Building use: Single-family house
Surface: 4234
Height: 23
Floors: 5
CO2 emissions: 23523
Energyconsumption: 4234
Energy demand: 32423
SAP: 2345
IMD: 12
Fuel poverty: 42%
Income index: 32
Link
Export
intervention
SEIF +
Semantic
energy
model
SEMANCO INTEGRATED
PLATFORM
Urban Energy Model A
- Data: Consumption
- Tools: Simulation (Ursos)
- Users: Energy consultants
- Plans: Projects
- Data: Building properties
- Tools: Assessment (SAP)
- Users: Planners, City
- Plans: Projects
Experts’
knowledge
captured in the
ontologies
RDF data
(semantic data)
Urban energy model
(GIS enriched with
semantic data)
Experts’s
knowledge
describe in
Use Case
and
Activities
templates
Repositories
(linked data or
non-structured
data) of energy
related data
Urban Energy Model B
Urban Energy System
Integration of multiple data and knowledge in a platform which
enables the creation of energy models of an urban energy system
(multiple actors from diverse fields interacting to achieve the
objective of reducing energy consumptions)

To determine the baseline (energy
performance based on the available
data and tools) of an urban area
1
To create plans and projects to
improve the existing conditions
2
To evaluate projects
3
For a given urban
energy model,
the SEMANCO
platform could be
used:
Models are created to assess the performance of an
urban system based on the available data, actors and
tools.

C L U S T E R V I E W
TA B L E V I E W
P E R F O R M A N C E I N D I C AT O R S
F I LT E R I N G
M U LT I P L E S C A L E
V I S U A L I Z AT I O N
Once a baseline reflecting the current state of the urban energy model has been
created, different visualization tools can be used to identify problem areas.

INTEGRATED PLATFORM : URBAN ENERGY MODEL: BASELINE
Visualizing the energy information at the neighborhood level

Smart City Expo World Congress, Barcelona, 18-20 November 2014
Visualization of energy information at the building level
INTEGRATED PLATFORM : URBAN ENERGY MODEL: BASELINE

information concerning the selected building derived from the integrated semantic model
Building geometry obtained from the
3D model
Street address obtained from
Google Geolocation services
Performance values to be
calculated with energy
assessment tool
Year of construction obtained from
the cadastre

Interface of the URSOS tool. The input data is automatically filled thanks to the semantic
integration of different data sources. Users can modify the input data in case there are errors.

Interface of the URSOS tool. The input data is automatically filled thanks to the semantic
integration of different data sources. Users can modify the input data in case there are errors.
Wall, ground and roof
properties from the building
typologies database
Year of construction
from the Cadastre
Geometry obtained from the 3D model
Street address name
and Street view from
Google Geolocation
services
Ventilation from the building
typologies database

Results of the energy simulation carried out by URSOS

Current status of the buildings before applying
measures

Creating plans to improve energy efficiency of buildings

Projects can be compared with a multi-criteria decision tool included in the platform. Users can
select the weight (importance) of the performance indicators. Besides, other indicators defined by
users can be included in the analysis, for example: foreseen funding.

SERVICE PLATFORM TO SUPPORT PLANNING OF ENERGY EFFICIENT CITIES
An energy service platform that supports planners, energy consultants, policy makers and
other stakeholders in the process of taking decisions aimed at improving the energy
efficiency of urban areas.
The services provided are based on the integration of available energy related data from
multiple sources such as geographic information, cadastre, economic indicators, and
consumption, among others.
The integrated data is analysed using assessment and simulation tools that are
specifically adapted to the needs of each case.

A platform which enables expert users to create energy
models of urban areas to assess the current performance of
buildings and to develop plans and projects to improve the
current conditions, including:
• An ontology for energy modeling in urban areas
• A methodology to integrate data from multiple
domains and disciplines
• A set of tools to support ontology design (Click-On,
Map-On)
• An operative platform which can be implemented in
other cities
What was achieved in SEMANCO (2011-2014):

2014-2017
ENERSI: Energy Service Platform Based on the Integration of Data from
Multiple Sources

ENERHAT / ENERPAT
Carbon emission
reduction
Energy reduction
Promoting building
retrofitting
- Energy simulation
- Cost simulation
- Planners
- Architects
- Owners
- Administration
- Businesses
- EPCs
- Building inspections
- Census
- Cadastre
APPLICATIONS
USERS
DATA
OBJECTIVES ACTIONS

ENERHAT enable tenants, owners and real
estate agents:
• To know the energy rating of the property
and the condition of the building
• To compare the energy efficiency with
similar properties
• To assess the investment needed to
improve efficiency
ENERPAT enable professionals (architects,
urban planners, builders, technicians and
municipal managers):
• To assess the state of the residential
building stock
• To define refurbishment scenarios to
improve the energy efficiency of the entire
building stock
ENERHAT / ENERPAT
enersi.es/en/enerhat
enersi.es/en/enerpat

Insert address of building / apartment

Technical inspections
Cadastre
EPC label

Comparison with similar buildings (year of
construction, surface, climate zone)

Rehabilitation measures
applicable to the building
(on walls, roofs, windows,
equipment, energy
sources)
Energy savings, costs, return on
investment, maintenance

Renovation options for each building component or system

Access to public grants to finance the renovation

Energy performance certificates in a
province

county

municipality

building

Certified dwellings are classified
into 9 clusters, according to
building type and year of
construction.
*Classification based on ERESEE

Improvement measures can be applied to a percentage
of buildings in each cluster and the energy
improvements and cost of retrofitting can be assessed.
100% buildings
Energy reduction
Emission reduction
Cost 15,2m €

50% buildings
Energy reduction
Emission reduction
Cost 15,2m €

25% buildings
Energy reduction
Emission reduction
Cost 15,2m €

The rehabilitation measures to be applied to the
buildings of the selected groups are propsed
**Simulation based on ICAEN tool

The buildings to be rehabilitated are identified on the
map.

The list of addresses and characteristics of the
buildings to be refurbished in the groups considered
is provided.

When selecting a property,
ENERHAT provides a summary of
its characteristics (energy
efficiency level, plot, technical
building report).

ENERHAT suggests
rehabilitation measures
according to the
characteristics of the
dwelling.
**Simulation based on ICAEN tool

What was achieved in ENERSI (2014-2017):
• Services oriented to specific users: ENERHAT (owners,
tenants) and ENERPAT (planners, businesses)
• Simplifying the complexity of data integration to make it
easier and intuitive to the end-user
• Validity of results depends on the available data and the
simulation tools
• Applications are being used by administrators and private
users

2013-2016
OPTIMUS: Optimising the Energy Use in Cities with Smart Decision
Support Systems

Enhancing building’s energy management systems to make
cities smart
The OPTIMUS DSS was tested in three
municipalities across Europe:
• Savona, Italy
• Sant Cugat del Vallès, Spain
• Zaanstad, Netherlands
To develop a semantic-based decision
support system which integrates data
from five different types / sources:
• climate
• building operation
• energy production costs
• energy consumption
• user’s feedback.

Semantic framework
Weather
forecasting
De-centralized
sensor-based
Feedback from
occupants
Energy
prices
RES
production
DSS INTERFACE
Sant Cugat
Savona
Zaanstad
The results of the
implementation of the actions in
each pilot city will modify the
data sources.
IMPLEMENTATION
PREDICTION
MODELS
DSS ENGINE
INFERENCE RULES
The inference rules and
prediction models are
implemented in the DSS engine
Historical data
Predicted data
Monitored data
Relations between input
data (real time and
predicted data, and
static user inputs) for
suggesting an action
plan
ACTION PLANS

OPTIMUS Decision Support System
Performance indicators:
- Energy cost
- CO2 production
- Energy consumption
- RES production

OPTIMUS DSS
Building dashboard
Daily monitoring of
performance indicators
Action plans based on
predictive models

Optimization of the boost time of the heating/cooling system
Action plan:
- Scheduling on/off heating
system in specific areas of the
building

OPTIMUS DSS
Monitored data
Monitoring the action plan:
- Comparing the historic data
with the forecasted data

• The SEMANCO ontology was expanded with
dynamic data: energy consumption and CO2
emissions, climate and socio-economic factors
influencing consumption.
• A front-end application to know the building
performance based on the prediction models was
implemented in three cities (Zaanstad, Savona, Sant
Cugat)
What was achieved in OPTIMUS (2013-2016):

2021-2024
TIMEPAC: Towards Innovative Methods for Energy Performance
Assessment and Certification

• La Salle – FUNITEC (Coordinator), Spain
• Jožef Stefan Institute, Slovenia
• Politecnico di Torino, Italy
• Institut Català d’Energia, Spain
• CYPE Soft S.L., Spain
• Ministrstvo za infrastrukturo, Slovenia
• Goriška Lokalna Energetska Agencija, Slovenia
• European Science Communication Institute, Germany
• Edilclima, S.r.l., Italy
• Regione Piemonte, Italy
• Institute for Sustainable Energy and Resources Availability, Austria
• Energy Institute Hrvoje Požar, Croatia
• Cyprus Energy Agency, Cyprus
• Cyprus University of Technology, Cyprus
14 partners from 7 EU countries (Austria, Croatia, Cyprus, Germany, Italy, Slovenia, and Spain)
certification public bodies - local energy agencies and
consultancies - software developers - research groups –
communication agency
TIMEPAC: Towards Innovative Methods for Energy Performance Assessment and Certification of Buildings
https://timepac.eu/

A holistic approach to EPC

A new ecosytem for certification Challenges:
• innovative approaches
to building energy
performance
assessment ->
integrating the different
methods and tools
• shared language to
access information ->
policies adapted to
national contexts
• involvement of multiple
stakeholders -> training
in new methods
EPBD recast – December 2021
Green Deal / Fit for 55 / Renovation Wave

Enhanced EPC
Envisioning future scenarios to exploit EPCs enhanced with interlinked data

EPC work and data flow

Methodology
Training on enhanced
certification, at the EU level
– TIMEPAC Academy
Proposals for enhanced
certification procedures and
tools (residential, non-
residential buildings)
Analysis of current
certification procedures
and tools in six partner
countries

What we aim to achieve in TIMEPAC (2021-2024):
To devise future scenarios for improving certification,
contributing:
• To increase the quality and reliability of EPC schemas
• To implement EPC schemas with sustainability and SRIs
• To integrate EPC databases with other data sources in order
to improve the efficiency and reliability of EPCs
• To increase awareness of the need to have EPC enhanced
with other data sources to foster the exploitation of EPC data
• To provide training materials including the new methods
developed in TIMEPAC

2021-2024
RETABIT: Multi-dimensional Data Driven Services to Foster Residential
Building Retrofitting Programmes in the Implementation of SECAPs

Many municipalities have signed up to the
Covenant of Mayors and have an action plan. The
plan includes diagnostics and measures to mitigate
climate change affecting residential buildings.
To make the SECAPs an effective instrument, tools
are needed to make diagnoses, propose measures
and monitor their impact.
Creating these tools requires integrating data from
multiple sectors, making them accessible to
administrations, businesses and citizens.
Green Deal
Fit for 55
Renovation Wave
Zero emissions in Europe by
2050
~75% of buildings in Europe
are not energy efficient.
Only 1% of the building stock
is renewed each year.
Sustainable Energy and Climate Action Plans
(SECAPs)

4 Impact assessment and monitoring of
rehabilitation measures

OpenSant Cugat – Use cases
Departament A
Technicians access the
data from their
department, and from
external sources
EPC Cadastre Other
Access to data from
a department
Department A
Technicians from diferent
departaments access to their
interconnected data, and to data
from external sources
EPC Cadastre Other
Department B
Collaboration between
departments
Citizens and businesses have access
to the data from the municipality
and from external sources
EPC Cadastre Other
Citizen/business
Departments
Collaboration with
third parties
OpenDataSantCugat
Department A data
OpenDataSantCugat
Department A data Department B data
OpenDataSantCugat
Departments data

In which buildings do inspections need
to be carried out?
Filters:
• Multifamily buildings
• Construction year < 2012
• Non-inspected buildings
OpenSant Cugat – Data access
Departament A
Technicians access the
data from their
department, and from
external sources
EPC Cadastre Other
Access to data from
a department
OpenDataSantCugat
Department A data

Filters:
• Residential buildings
• With water consumption
• Without first occupancy licence
Which buildings are in an irregular situation (e.g.
there is water consumption despite not having a first
occupancy licence)?
Department A
Technicians from diferent
departaments access to their
interconnected data, and to data
from external sources
EPC Cadastre Other
Department B
Collaboration between
departments
OpenDataSantCugat
Department A data Department B data

Businesses ask the city how many building permissions
have been granted in a neighbourhood over the last
two years
Filters:
• Licence year> 2020
• Neighbourood: Centre
Citizens and businesses have access
EPC Cadastre Other
Citizen/business
Departments
Collaboration with
third parties
OpenDataSantCugat
Departments data

A citizen wants to know the information the
municipality has about a house/building in which he
lives.
A building report contains all the data
available to the municipality: EPC, building
permits, water consumption….
OpenData Sant Cugat – Data access
Citizens and companies have access
EPC Cadastre Other
Citizens/companies
Departments
Collaboration with
third parties
OpenDataSantCugat
Departments data

Conclusions
- Data is the fundamental basis for the development of
energy information systems: data availability, data
reliability and data maintenance over time are key
issues.
- We need to establish a solid basis for the development
of these systems so that they can be operational over
time, at different levels: local, regional, national, EU.
- This foundation relies on data (formats, standards)
and data interoperability. Ontologies, protocols,
standards are essential to lay out a sound basis.

Conclusions
- Two ongoing trends: bottom-up, citizen
participation (e.g. energy communities); top-down,
EU directives (Renovation Wave, EPBD, EEB recasts).
In the middle there is a space for developing service
platforms that interconnect both levels.
- Data-driven services must take into account the
needs of end-users. We need interfaces in a
language understandable to specific users and
functionalities relevant to each target group.

SEMANCO http://www.semanco-project.eu/
EECITIES http://www.eecities.com/
ENERHAT http://enersi.es/en/enerhat
ENERPAT http://enersi.es/en/enerpat
TIMEPAC https://timepac.eu/
RETABIT https://retabit.es/

With successful practices to climate neutrality
Conference LIFE IP CARE4CLIMATE 2022:
8 June 2022, Ljubljana, Slovenia
Thanks for you attention!
leandro.madrazo@salle.url.edu

CARE4CLIMATE_Leandro_Madrazo_published.pdf

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