INSMART Integrative Energy Planning For Cities Low Carbon Futures: Analytical Framework

Transcription

1 INSMART Integrative Energy Planning For Cities Low Carbon Futures: Analytical Framework Cesena (Italy) Deka Trikala (Greece) Évora (Portugal) Nottingham (U.K.) JoãoPedro Gouveia Luis Dias, JúliaSeixas,Sofia Simões 3 rd Energy for Sustainability Conference, Funchal, 8 th February 2017

2 1. Vision and Purpose VISION: Cities sustainable energy future are achievable by: bringing together cities, scientific and industrial organizations, considering the integration of the components of the city s energy system, selecting cost-effective options from multiple data sources and integrated tools, choosing the best social-accepted technologies and measures. PURPOSE: Design comprehensive data-driven methods for enhancing the city s sustainable planning addressing the current and future city energy needs, Implement an integrative planning tool to identify the optimum mix of short, medium and long term measures for a sustainable energy future for the city, Address the efficiency of energy flows across all city sectors taking spatial patterns and economic, environmental and social criteria Engage city agents to pave the implementation of priority actions.

3 2. Methods & tools for data-driven integrated energy planning 389 DOOR-TO-DOOR SURVEYS SMART METERS DOOR-TO- DOOR SURVEYS 460 SMART METERS Integrated City Energy Planning framework

4 2. Methods & tools for data-driven integrated energy planning Door-to-door Buildings and Transport and Mobility Surveys Comprehensive GIS energy city database (present situation and future scenarios) Cities buildings stock characterized and modeled through a typology approach (using Energy Plus modeling tools) Extensive data from smart meters (relying on a sample of the EDP Distribution S.A., INOVGRID project) Transport based energy and carbon model Integrated modeling with TIMES (The Integrated Markal-Efom System) technoeconomic optimization modeling tool. used to analyse the mix of measures required to meet sustainable energy targets Selected measures assessed with respect to non-technical criteria using a multicriteria decision making method (PROMEΤHEE (Preference Ranking Organization Method for the Enrichment of Evaluations) to address economic, environmental as well as social issues.

5 2. Methods & tools for data-driven integrated energy planning City Energy Planning structure and major outcomes

6 2. Methods & tools for data-driven integrated energy planning è City Analytics Buildings Archetypes and energy simulation modelling Surveys, EnergyPlus, DesignBuilder, Smart meters data [Évora] Representative typologies for the city of Évora

7 3. Selected achievements towards sustainability è City Analytics Buildings Archetypes and energy simulation modelling Surveys, EnergyPlus, DesignBuilder, Smart meters data [Évora] General o Location o Period of construction o Foot print area o Average household area o Frequency Geometry o Type of building o Number of floors o Number of dwellings o Height o Room in the roof Construction o Bearing Structure o Exterior wall type o Roof type o Wall insulation o Glass type o Window framing Occupation o Number of occupants o Average income o Occupation schedule o Type of room heated Annual Energy Demand (kwh) Equipment Ownership o Refrigerators o Coolers o Washing machines (clothes, dishes) o Fireplaces o Solar thermal panels o Air Conditioning o Computers Sub Typologies Heating demand Cooling demand Electricity demand

8 3. Selected achievements towards sustainability

9 3. Selected achievements towards sustainability è Electricity Consumer Groups Unravelling consumers groups in the city policies - Combining electricity smart meters and door-to-door surveys [Évora] for tailor-made U profile (soft): Fuel Poverty Small houses (< 90m 2 ) Single glazing, rented houses 2 pax/house, > 65 years old, low education level Average income < 750 monthly Daily electricity consumption (kwh) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Rural (Total) Urban (Total) W profile: Fat Energy households Rural very recent houses (>160 m 2 ) Double glazing 4 pax/house; 60% with years old 50% with income > 2500 Medium-high class Daily electricity consumption (kwh) Jan FebMar AprMayJun Jul Aug Sep Oct NovDec Month Before 1945 (Total) Between 1946 and 1990 (Total) From 1991 (Total) Gouveia, J.P., Seixas, J. (2016). Unraveling electricity consumption profiles in households through clusters: Combining smart meters and door-to-door surveys. Energy and Buildings. 116,

10 3. Selected achievements towards sustainability è High Resolution data integration

11 3. Selected achievements towards sustainability è High Resolution data integration

12 3. Selected achievements towards sustainability è Transports and Mobility Mobility flows analysis within city sectors (#21) using an energy and emissions model Identification and assessment of energy efficiency measures in transport Door to door surveys and energy and emissions modelling [Évora] Évora city sectors for mobility patterns assessment Total energy demand (MJ) per origin sector

13 3. Selected achievements towards sustainability è Other Energy Consuming Sectors (Public Lighting, Waste, Water and Wastewater, Industries, Services) Types of public light operation control systems and SLP in Évora municipality Street lighting points (SLP) in Évora municipality 13

14 3. Selected achievements towards sustainability èrenewable energy resources potential - Solar PV utility-scale (1MW) [Évora] - near 2500 MW potential capacity - Solar PV rooftop [Évora] a) technical (59MW) and b) auto production potential (12.7MW) Solar PV Potential for by buildings typologies Solar PV Potential for 1MW projects Source: Lourenço, P Produção de eletricidade a partir de energia solar fotovoltaica de larga escala PV e CPV na zona rural do município de Évora: área disponível e potencial técnico. FCT- UNL. Sources: a)moreira, D Solar PV rooftop in households: technical potential for the municipality of Évora. FCT-UNL b) Gouveia, J. P., Seixas, J., Mendes, L., Shiming, L., Looking Deeper into Residential Electricity Consumption Profiles: The Case of Évora. 12th International Conference on the European Energy market, Lisbon, May 2015, Portugal. DOI: /EEM

15 4. Conclusions Comprehensive data gathering and processing steps are key to an integrative energy planning to deliver future sustainable energy pathways. The combination and integration of multi-scale data granularity: 15 minutes electricity consumption data from smart meters, monthly to annual statistical energy production and consumption data, Detailed energy modelling of buildings typologies, City transport characteristics and mobility flows, Door-to-door surveys, GIS tools, Participation of different levels of city stakeholders (municipality, utilities, transport companies, citizen groups, market associations) brings forward the main advantages of this methodology. The stakeholders participation at the different stages of the methodology is essential in assembling an acceptable, realistic and mostly beneficial city action plan. 15

16 Consumers Profiles & Energy Efficiency Energy Transitions New Technologies & Low Carbon Practices Policy Support Integrative Energy City Planning Climate Mitigation/ Adaptation JOÃO PEDRO GOUVEIA ENERGY& CLIMATE CO 2 The InSMARTproject has received funding from the EU 7th FP (ENER/FP7/314164). JoãoPedro Gouveia is funded by the Portuguese Science and Technology Foundation (FCT) through the Scholarship SFRH/BD/70177/2011.