VICTOR I. SERNA FUNDACIÓN CARTIF GIULIA MASSA FUNDACIÓN CARTIF

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2 DEMAND CHARACTERSATION BY INSPIRE BASED EPC GENERATION FOR ENERGY URBAN PLANNING TOWARDS THE DECARBONISATION OF BUILDINGS AND DISTRICTS GEMA HERNÁNDEZ MORAL FUNDACIÓN CARTIF CÉSAR VALMASEDA TRANQUE FUNDACIÓN CARTIF GIACOMO MARTIRANO EPSILON ITALIA VICTOR I. SERNA FUNDACIÓN CARTIF GIULIA MASSA FUNDACIÓN CARTIF

3 Research Centre Generate technological knowledge to be transferred to companies / businesses to improve their competitiveness Foundation Non profit private organisation with a final goal: innovation Centro Tecnológico CARTIF Parque Tecnológico de Boecillo, Boecillo, Valladolid SPAIN

4 Digital and industrial systems Energy Division Energy Policies Smart Cities Energy Efficiency Renewable energy Agroalimentation and processes Smart Grids

5 : legislative aspects to bear in mind 2. ELISE (Energy Pilot) / project 3. Use Case 1: INSPIRE Harmonisation of EPC datasets 4. Spanish Case study: replication of the results 5. Conclusions

6 Before delving into the topic ENERGY PILOT (ELISE Action) PROJECT (Internal Project)

7 : Legislative aspects to bear in mind (EPBD, CoM, EED) - EPBD: Energy Performance of Buldings Directive - CoM: Covenant of Mayors - EED: Energy Efficiency Directive - INSPIRE Directive: location data Image source: y/handle/jrc104587

8 2. ELISE (Energy Pilot) vs Demand characterisation by INSPIRE based EPC generation for energy urban Energy Pilot (JRC) (internal CARTIF project) MAIN FOCUS UC1: INSPIRE Harmonization of existing Energy Performance Certificate datasets and creation of a web application UC2: Benchmark of different Energy Performance Labelling of buildings UC1 Input data (EPCs) MAPPING geo-r EPCs UC3 UC4 UC3: Assessing the Energy Performance of buildings with dynamic measured data UC4: Supporting Energy Efficiency driven renovation planning of the building stock at local level Input data (cadastre) UC2 EPCs calculation MAPPING Output (energy demand ) VALIDATION PLANNING UC5: Supporting integrated energy planning and monitoring at urban/local level (SEAP BEI/MEI) UC6: Supporting the design and implementation of a regional energy strategy Source: project, CARTIF, 2017

9 3. Use Case 1: INSPIRE Harmonisation of EPC datasets Objectives To establish an accessible and interoperable common knowledge base for EPC datasets to support local government and private sector involved in energy efficiency policies. Achievements - Study of Trento s EPC dataset structure (based on real EPCs) - Target data model proposal following INSPIRE - Creation of a web app to access EPCs following INSPIRE specifications Replication of results Spanish case study: EPC harmonisation based on the target model

10 3. Use Case 1: INSPIRE Harmonisation of EPC datasets Image source:

11 4. Spanish Case study: replication of the results Methodology followed data model 1 EPC submission context in Spain 2 Datasets contained in an EPC 3 Comparison with target data model Cadaster energy demand data EPC national data model (national xml)

12 4. Spanish Case study: replication of the results 1: EPC submission context in Spain EUROPE EPBD (Energy Performance of Buildings Directive) Need to generate EPCs Establish Common general framework for the calculation of energy performance of buildings Need a calculation methodology Base it on standard: CEN EN (more standards CENSE) SPAIN MEMBER STATES (SPAIN) transpose the need to generate certificates and general framework FOUR VALIDATED EPC TOOLS ALTERNATIVE PROCEDURES HULC CERMA CEX CE3X Justification required ISSUE EPC + energy label PDF format XML format At national level! REGIONS REGIONS (e.g.cyl) monitor and validate results of certificates + show to public EPC REGISTER Different amount of information provided 4. ES case study PUBLICLY AVAILABLE DATA Maintained by each region depending on the region In each region (in Spain) 5. Conclusions

13 4. Spanish Case study: replication of the results 2: Datasets contained in a Spanish EPC PDF format XML format Semantic richness of Spanish PDF / XML EPC version EPC PDF format - Spain Sample of document XML EPC content

14 4. Spanish Case study: replication of the results 3: Comparison with target data model SPANISH EPC MODEL (XML) TARGET MODEL TRENTO EPC MODEL 1. Main category analysis Datos del certificador Identificación edificio Datos generales y geometría Datos envolvente térmica Building Abstract Construction Abstract Building Certificate Edificio Certificato Generatori Impianti 2. Attribute per attribute comparison (considering multiplicity) Instalaciones térmicas Professional Certificatore 3. Conclusions /quantification Instalaciones iluminación Energy Conversion System Condiciones generales funcionamiento y ocupación Energías renovables Energy System Certifier Demanda Consumo Emisiones CO2 Calificación Medidas de mejora Pruebas, comprobaciones e inspecciones Datos personalizados Main categories in each data model

15 4. Spanish Case study: replication of the results 3: Comparison with target data model STEP 1 1. Main category analysis 2. Attribute per attribute comparison (considering multiplicity) 3. Conclusions /quantification Trento Target data model tables (UC1 work) Target data model analysis tables Target data model UML version (UC1 work)

16 4. Spanish Case study: replication of the results 3: Comparison with target data model STEP 2 1. Main category analysis 2. Attribute per attribute comparison (considering multiplicity) 3. Conclusions /quantification Spanish XML official version Spanish data model analysis tables

17 4. Spanish Case study: replication of the results 3: Comparison with target data model STEP 3 1. Main category analysis 2. Attribute per attribute comparison (considering multiplicity) 3. Conclusions /quantification Target data model analysis tables Spanish data model analysis tables CONCLUSIONS / QUANTIFICATION

18 4. Spanish Case study: replication of the results 3: Comparison with target data model Concept Number of elements (Target model) Number of elements (Spanish XML model) Total number of attributes Main categories (feature types) Main category analysis 2. Attribute per attribute comparison (considering multiplicity) 3. Conclusions /quantification Sub-categories (data types) Mandatory attributes 2 24 (21.23%) 67 (26.38%) Optional attributes 2 89 (78.76%) 187 (73.62%) Codelists General quantification of the data models

19 4. Spanish Case study: replication of the results 3: Comparison with target data model Concept Number of elements (Target model) Number of elements (Spanish XML model) Matching attributes 13 One to more relationships (+7) 1. Main category analysis 2. Attribute per attribute comparison (considering multiplicity) 3. Conclusions /quantification Similar attributes 9 Other sources 43 - Non-matching attributes Total number of attributes Differences found in the comparison

20 4. Spanish Case study: replication of the results 3: Comparison with target data model Perfect matching was difficult to obtain: different definitions and some attributes sometimes corresponded to more than one attribute in the opposite data model Mismatches in terminology: same concepts were treated differently in both data models Non-matching attributes: in Spanish data model are related mainly to building envelope data, improvement measures and energy labelling data (demand, consumption, emissions ) 1. Main category analysis 2. Attribute per attribute comparison (considering multiplicity) 3. Conclusions /quantification It is important to highlight: Input and Output data: while the target data model deals with mainly output data and some necessary input data to calculate the EPC, the Spanish data model is semantically rich enough to hold all necessary input data.

21 5. Conclusions EPC role not to be sub-estimated (not to be an administrative burden) INSPIRE role is highly relevant - in supporting, harmonising, providing the attributes across all member states and making them accessible through catalogues. In addition, location information allows to analyse patterns by location, be able to implement action plans / policies Replication possibilities: While the replication possibilities are necessary and possible, there are many differences related to the way EPCs are defined /conceived in each Member State and how the EPCs are managed (registers etc). Different conceptualisation of EPCs resides in calculation methodology adopted / interpretation of EPBD. Common calculation methodology in member states and registers at national level following the same data model would be highly beneficial to support energy action plans etc. Assuring that the same input data (harmonised across Europe and terminology) is deployed combined with the same calculation methodology will ensure reliable and comparable results across member states. Moreover, assuring an adequate methodology and making these data available to the public might also contribute for a better uptake of the EPCs.

22 Any questions?

23 THANKS FOR YOUR ATTENTION! Gema Hernández Moral - Fundación CARTIF gemher@cartif.es César Valmaseda F. CARTIF cesval@cartif.es Víctor Iván Serna F. CARTIF vicser@cartif.es Giacomo Martirano Epsilon Italia g.martirano@epsilon-italia.it Giulia Massa F. CARTIF giumas@cartif.es

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