Se ha denunciado esta presentación.
Se está descargando tu SlideShare. ×

CARE4CLIMATE_Leandro_Madrazo_published.pdf

Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Próximo SlideShare
Group 6 Final Presentation
Group 6 Final Presentation
Cargando en…3
×

Eche un vistazo a continuación

1 de 99 Anuncio

CARE4CLIMATE_Leandro_Madrazo_published.pdf

Descargar para leer sin conexión

Presentation by Leandro Madrazo, ARC Engineering and Architecture La Salle, at the CARE4CLIMATE conference held in Ljubljana, Slovenia, on 8 June 2022. Research work in the field of energy efficiency in buildings and cities using digital technologies, carried out by the ARC research group from 2008 to the present.

You can see a recording of the presentation in this link
https://www.youtube.com/watch?v=c36Z_blspiU

Presentation by Leandro Madrazo, ARC Engineering and Architecture La Salle, at the CARE4CLIMATE conference held in Ljubljana, Slovenia, on 8 June 2022. Research work in the field of energy efficiency in buildings and cities using digital technologies, carried out by the ARC research group from 2008 to the present.

You can see a recording of the presentation in this link
https://www.youtube.com/watch?v=c36Z_blspiU

Anuncio
Anuncio

Más Contenido Relacionado

Más de ARC research group (20)

Anuncio

CARE4CLIMATE_Leandro_Madrazo_published.pdf

  1. 1. 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
  2. 2. - 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
  3. 3. 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
  4. 4. 2008-2011 IntUBE: Intelligent Use of Building’s Energy Information
  5. 5. 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
  6. 6. 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
  7. 7. 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.
  8. 8. 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.
  9. 9. 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):
  10. 10. 2009-2012 RÉPENER: Control and Improvement of Energy Efficiency In Buildings through the Use of Repositories
  11. 11. 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)
  12. 12. User Facilities Manager: - Examples of energy efficient buildings to learn from best practices
  13. 13. User Facilities Manager: - Examples of energy efficient buildings to learn from best practices - Reference values: confort, energy demand, energy consumption, primary energy
  14. 14. User Facilities Manager: - Examples of energy efficient buildings to learn from best practices - Reference values: confort, energy demand, energy consumption, primary energy - Location of the reference buildings
  15. 15. Glossary: - Ontology to interlink data from different sources and domains
  16. 16. 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):
  17. 17. 2011-2014 SEMANCO: Semantic Tools for Carbon Reduction in Urban Planning
  18. 18. 2011-2014 SEMANCO: Semantic Tools for Carbon Reduction in Urban Planning www.semanco-project.eu
  19. 19. 2011-2014 SEMANCO: Semantic Tools for Carbon Reduction in Urban Planning
  20. 20. 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
  21. 21. 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 Modelling data with ontologies
  22. 22. 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 Modelling data with ontologies Providing tools and services to interoperate with data
  23. 23. 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 Modelling data with ontologies Providing tools and services to interoperate with data Using tools at different decision making realms
  24. 24. 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 Modelling data with ontologies Providing tools and services to interoperate with data Using tools at different decision making realms Reducing carbon emissions
  25. 25. Data connected through the Semantic Energy Information Framework OPEN SEMANTIC DATA MODELS DATA TOOLS
  26. 26. 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)
  27. 27. 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.
  28. 28. 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.
  29. 29. INTEGRATED PLATFORM : URBAN ENERGY MODEL: BASELINE Visualizing the energy information at the neighborhood level
  30. 30. Smart City Expo World Congress, Barcelona, 18-20 November 2014 Visualization of energy information at the building level INTEGRATED PLATFORM : URBAN ENERGY MODEL: BASELINE
  31. 31. Smart City Expo World Congress, Barcelona, 18-20 November 2014 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
  32. 32. Smart City Expo World Congress, Barcelona, 18-20 November 2014 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.
  33. 33. 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
  34. 34. Results of the energy simulation carried out by URSOS
  35. 35. Current status of the buildings before applying measures
  36. 36. Creating plans to improve energy efficiency of buildings
  37. 37. Smart City Expo World Congress, Barcelona, 18-20 November 2014 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.
  38. 38. 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.
  39. 39. www.eecities.com
  40. 40. www.semanco-tools.eu
  41. 41. 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):
  42. 42. 2014-2017 ENERSI: Energy Service Platform Based on the Integration of Data from Multiple Sources
  43. 43. 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
  44. 44. 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
  45. 45. Insert address of building / apartment
  46. 46. Select an apartment
  47. 47. Technical inspections Cadastre EPC label
  48. 48. Comparison with similar buildings (year of construction, surface, climate zone)
  49. 49. Rehabilitation measures applicable to the building (on walls, roofs, windows, equipment, energy sources) Energy savings, costs, return on investment, maintenance
  50. 50. Renovation options for each building component or system
  51. 51. Access to public grants to finance the renovation
  52. 52. Downloadable summary
  53. 53. Energy performance certificates in a province
  54. 54. Energy performance certificates in a county
  55. 55. Energy performance certificates in a municipality
  56. 56. Energy performance certificates in a building
  57. 57. Certified dwellings are classified into 9 clusters, according to building type and year of construction. *Classification based on ERESEE
  58. 58. 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 €
  59. 59. 50% buildings Energy reduction Emission reduction Cost 15,2m € Improvement measures can be applied to a percentage of buildings in each cluster and the energy improvements and cost of retrofitting can be assessed.
  60. 60. 25% buildings Energy reduction Emission reduction Cost 15,2m € Improvement measures can be applied to a percentage of buildings in each cluster and the energy improvements and cost of retrofitting can be assessed.
  61. 61. The rehabilitation measures to be applied to the buildings of the selected groups are propsed **Simulation based on ICAEN tool
  62. 62. The buildings to be rehabilitated are identified on the map.
  63. 63. The list of addresses and characteristics of the buildings to be refurbished in the groups considered is provided.
  64. 64. When selecting a property, ENERHAT provides a summary of its characteristics (energy efficiency level, plot, technical building report).
  65. 65. ENERHAT suggests rehabilitation measures according to the characteristics of the dwelling. **Simulation based on ICAEN tool
  66. 66. 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
  67. 67. 2013-2016 OPTIMUS: Optimising the Energy Use in Cities with Smart Decision Support Systems
  68. 68. 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.
  69. 69. 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
  70. 70. OPTIMUS Decision Support System Performance indicators: - Energy cost - CO2 production - Energy consumption - RES production
  71. 71. OPTIMUS DSS Building dashboard Daily monitoring of performance indicators Action plans based on predictive models
  72. 72. Optimization of the boost time of the heating/cooling system Action plan: - Scheduling on/off heating system in specific areas of the building
  73. 73. OPTIMUS DSS Monitored data Monitoring the action plan: - Comparing the historic data with the forecasted data
  74. 74. • 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):
  75. 75. 2021-2024 TIMEPAC: Towards Innovative Methods for Energy Performance Assessment and Certification
  76. 76. timepac.eu
  77. 77. • 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/
  78. 78. A holistic approach to EPC TIMEPAC: Towards Innovative Methods for Energy Performance Assessment and Certification of Buildings
  79. 79. 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 TIMEPAC: Towards Innovative Methods for Energy Performance Assessment and Certification of Buildings EPBD recast – December 2021 Green Deal / Fit for 55 / Renovation Wave
  80. 80. Enhanced EPC TIMEPAC: Towards Innovative Methods for Energy Performance Assessment and Certification of Buildings Envisioning future scenarios to exploit EPCs enhanced with interlinked data
  81. 81. EPC work and data flow TIMEPAC: Towards Innovative Methods for Energy Performance Assessment and Certification of Buildings
  82. 82. Methodology TIMEPAC: Towards Innovative Methods for Energy Performance Assessment and Certification of Buildings 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
  83. 83. 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
  84. 84. 2021-2024 RETABIT: Multi-dimensional Data Driven Services to Foster Residential Building Retrofitting Programmes in the Implementation of SECAPs
  85. 85. 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)
  86. 86. 4 Impact assessment and monitoring of rehabilitation measures
  87. 87. RETABIT PLATFORM
  88. 88. RETABIT PLATFORM
  89. 89. 2017-2019 OpenSantCugat
  90. 90. 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
  91. 91. 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
  92. 92. 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 OpenSant Cugat – Data access
  93. 93. 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 to the data from the municipality and from external sources EPC Cadastre Other Citizen/business Departments Collaboration with third parties OpenDataSantCugat Departments data OpenSant Cugat – Data access
  94. 94. 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 to the data from the municipality and from external sources EPC Cadastre Other Citizens/companies Departments Collaboration with third parties OpenDataSantCugat Departments data
  95. 95. OpenSant Cugat – Data access
  96. 96. 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.
  97. 97. 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.
  98. 98. 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/
  99. 99. 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

×