Optimising Energy Use in Cities through Smart Decision Support Systems

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1 Optimising Energy Use in Cities through Smart Decision Support Systems Energy Management for Sustainable Action Plans, Brussels, 18 June 2015 Siegfried Zoellner, Coordinator, ICLEI European Secretariat This project is co-funded by the European Union

2 The challenge: cities are increasingly hungry for energy Cities consume over 2/3rds of the world s energy; they are the largest emitters of greenhouse gases; and can influence over 70 % of the total ecological footprint. And with 6 out of 10 people expected to live in cities by 2030, urban energy demands are continuously growing (WHO).

3 Using city data to make smart energy decisions Local authorities are uniquely placed to play a key role in the European and national goals of developing a low-carbon economy: have a huge sphere of influence and a duty to promote the social, economic and environmental well-being of their community. as permanent bodies that plan for the long term a number of data sets available portfolios include many types of building, each which use significant amounts of energy

4 Energy is one of the largest controllable overheads in many local authority buildings

5 The OPTIMUS approach. using city data to make smart energy-saving decisions in public buildings The OPTIMUS project aims to design, develop and deliver an integrated ICT platform that will collect & structure open data sets to recommend the best energy-saving opportunities available in public buildings Developing the Training sessions The city assessment Piloting the DSS Decision Support for other cities to framework three cities System (DSS) implement the DSS DSS Savona, Sant Cugat, Zaanstad

6 The SCEAF Model Smart City Energy Assessment Framework General characteristics Political Field of Action Energy & Environmental Profile Related Infrastructure Energy & ICT 1.1 Degree of ambition 1.2 Efficiency at fulfilling targets 2.1 Energy Consumption Intensity 2.2 Energy production via Renewable Technology 2.3 Energy Conservation Issues 2.4 Network Efficiency 3.1 Monitoring Systems BEMS 3.2 Levels of integration of automations, Mart meters & ICT solutions 3.3 Forecasting systems 1.3 Asset Management 2.5 Ambient Air Pollution 3.4 Exploitation of Social Media

7 OPTIMUS Rating Chart Calculated score per axis OPTIMUS City City under Evaluation Highest score in every indicator Specific score in each indicator Scaling Political Field of Action Energy & Environmental Profile Related Infrastructures & ICT

8 Developing the DSS (1/8) an overview of the architecture OPTIMUS DSS will be fed with data sources from multiple domains and it will support the short-term energy action plans of municipal buildings. OPTIMUS Decision Support System (DSS) Weather forecasting De-centralized data Social Feedback Energy pricing Renewable energy sources

9 Developing the DSS (2/8) Module 1: Weather Forecasting DSS Weather can heavily affect energy consumption in a city (e.g. heating/cooling in public buildings, energy use in public venues and stadiums, etc.). By collecting data from weather forecasting we can develop accurate energy-demand models and map consumer behaviour related to the selected public buildings, which in turn can be used to help plan and optimise the energy use in the future. Some of the most relevant parameters that will be taken into account include: Temperature Wind speed & direction Period of irradiation Humidity Solar irradiation Sky coverage

10 Developing the DSS (3/8) Module 2: De-centralized Data DSS Energy monitoring requires a clear definition of the boundaries of the considered systems and a proper classification of the captured energy data. Data considered within this module can be distinguished in two main categories: Static data Building dimensions; Building materials; Building destination; Occupancy; Appliances consuming electricity; Instrumentations (e.g. light sensors); Dynamic data Indoor temperature from thermostats; Indoor humidity from psychrometers; Electricity consumption from counters; Natural Gas consumption from counters; Thermal flows from calorimeters or other flow meters; Occupancy from presence detectors.

11 Developing the DSS (4/8) Module 3: Social Feedback DSS Information provided by building occupants can assist the energy managers in adjusting thermal comfort parameters, in order to optimize energy use and maintaining comfort levels in accepted ranges. The idea is to use input from occupants of the building, reflecting their opinion about comfort levels in the buildings to help decide what action needs to be taken. Thermal Comfort Validator, a tool that evaluates thermal comfort at a 7-level scale.

12 Developing the DSS (5/8) Module 4: Energy Prices DSS This data- capturing module extracts real-time data on energy prices available from energy providers within the local markets. Prices will be evaluated for the following energy types: Thermal energy (Solar Thermal Energy, District Heating, Natural Gas, Biomass, LPG, others); Electricity (PV Energy Production, Wind Energy Production, National Grid Electricity, others).

13 Developing the DSS (6/8) Module 5: Energy Production DSS This module will collect data on the production of energy from renewable energy facilities available in the city and will match them with the energy demand profiles in order to propose the optimal energy management solution. The energy production is classified according to the kind of source (solar, wind, water power, renewed biomass, etc.) and the kind of energy produced (electricity, heat).

14 Developing the DSS (7/8) The user interface OPTIMUS DSS Sant Cugat Logged as: David Hernández Log out Sant Cugat > List of buildings Sant Cugat Buildings: 2 Total surface: m2 Renewable generation: PV plant (23 MWh) Thermal power: 850 kw Electrical power: 440 kw Total energy consumption: 2157kWh/m 2 CO 2 emissions: 86kgCO 2 /m 2 User requirements methods: User/group interviews Prototyping Use cases Brainstorming Town hall Status: No action required Last action: 15 / 04 / :00 Building description Building use: Office Address: Plaça de la Vila, 1 Year of construction: 2007 Surface: 8.593m2 Floors: 6 Occupation: 350 employees, 400 visitors Building description Building use: Cultural Address: Plaça de la Vila, 1 Year of construction: 2010 Surface: 9.593m2 Floors: 6 Occupation: 35 employees, 800 visitors Configuration Configuration Partitions 23 Partitions 8 Sensors 23 Sensors 11 Action plans 3 Theatre Status: Action required Last action: 15 / 03 / :00 Action plans 2

15 Developing the DSS (8/8) The user interface OPTIMUS DSS Sant Cugat Logged as: David Hernández Log out Sant Cugat > Town Hall > Action Plan: Optimum start/stop of the heating/cooling system Town Hall Action Plan: Optimum start/stop of the heating/cooling system Description: Control of pre-heating/cooling of the rooms based on schedules and weather forecasts Last forecast calculated: 9 / 11 / :00 Building use: Office Address: Plaça de la Vila, 1 Year of construction: 2007 Surface: 8.593m2 Floors: 6 Occupation: 350 employees, 400 visitors Energy rating: D Renewable generation: PV plant (23 MWh) Thermal power: 850 kw Electrical power: 440 kw Total energy consumption: 357kWh/m 2 CO 2 emissions: 86kgCO 2 /m 2

16 Piloting the DSS (1/2) Meet the three pilot cities This web-based decision support system (DSS) will be tested and validated through pilot applications in three different cities: Savona (Italy), Sant Cugat del Vallès (Spain) and Zaanstad (The Netherlands). Zaanstad (Netherlands) OPTIMUS will have, by design, the necessary degree of generalisation so as to be easily adapted to cities with different characteristics. Sant Cugat del Vallès (Spain) Savona (Italy)

17 Piloting the DSS (2/2) The process Baseline review using SCEAF Savona Campus Sant Cugat Zaanstad Proposed actions for energy optimisation

18 Task 4.1 Application of Smart City ex-ante Assessment Framework on the cities Meetings with: The Energy Manager of Savona Municipality ARE Project Manager in charge of Savona SEAP School Director School Thermal Plant Manager Information Collection: Pilot site visits Savona (1/2) Municipality s energy profile & targets set Technical characteristics of installed equipment School s operating schedule Checklist of documents: Colombo-Pertini school energy profile summary A version of Savona s SEAP Energy bills and records, thermal and electricity, past 3 years Energy Certificate and building plans of school Operating schedule of school and gym Technical datasheets of boilers, heating pump, A/C, PV plant Participation from: NTUA, D APPOLONIA, POLITO, IPS

19 Task 4.1 Application of Smart City ex-ante Assessment Framework on the cities Pilot site visits Savona (2/2) Detected possibilities to improve energy efficiency Space heating Lighting system Domestic Hot Water (DHW) Production PV system maintenance Indicative possible DSS action plans Action Plan Idea Involved equipment Output of the system Programming of the space heating system according to the real energy needs, to propose an operational schedule Optimal management of DHW Production according to the real use of the school Optimally maintaining the PV of the school, by comparing the observed energy production with the expected Sectioning the 4 main heat distribution lines, installation of thermostatic valves and variable flow rate distribution pumps. Use of the main gas boiler, instead of electricity, installation of timer-driven switches on remaining electric boilers to operate only during low tariff times. Exploitation of the Savona Campus DEMS that predicts PV energy production Schedule for switching on and off the boilers, definition of duration and distribution lines to be switched on and off. A weekly schedule of switching on/off the boilers Weekly indication of expected production

20 Task 4.1 Application of Smart City ex-ante Assessment Framework on the cities Pilot site visits Zaanstad (1/2) Meetings with: Key staff members of the Zaanstad municipality BMS company representatives Town Hall Thermal Plant Manager Information Collection: Building s energy profile Technical characteristics of installed equipment Town Hall s operating schedule Occupancy levels Checklist of documents: Electricity and gas records for 2013 and previous years Energy Certificate and building schematics Operating schedule of the Town Hall Technical data sheets of heating pump, ventilation system, cassette units Participation from: NTUA, D APPOLONIA, POLITO

21 Task 4.1 Application of Smart City ex-ante Assessment Framework on the cities Pilot site visits Zaanstad (2/2) Detected possibilities to improve energy efficiency Space heating Occupancy Domestic Hot Water (DHW) Production Indicative possible DSS action plans Action Plan Idea Involved equipment Output of the system Programming of the space heating system according to humidity and temperature levels Change of staff s working places according to the cool and the hot areas of the building Change of the base temperature, which is set at 22 o Celsius throughout the whole year Adjustment of the BEMS accepted levels of relative humidity and temperature Passage to a HVAC regulation system allowing variable flow rate in ventilation Tracking of employees working positions via the Flexwhere system Adjustment of the BEMS temperature setpoint Weekly indication of accepted levels of relative humidity and temperature Weekly suggestions of working places Suggestion for setting higher or lower base temperature

22 Task 4.1 Application of Smart City ex-ante Assessment Framework on the cities Meetings with: Pilot site visits Sant Cugat (1/2) The Environmental Manager of Sant Cugat s Municipality Building Maintenance Technicians Energy, Land and Urban Quality Managers Technical personnel of the Town Hall and Theatre Information Collection Municipality s energy profile and targets set Technical characteristics of equipment Checklist of documents: Electricity and gas records and bills of previous years Operating schedule and building schematics Technical data sheets of equipment Samples files of the database from the Flexwhere system Energy production records of the Town Hall s PV system Funds spent on purchasing EnEf and RES equipment Participation from: NTUA, FUNITEC, D APPOLONIA, POLITO

23 Task 4.1 Application of Smart City ex-ante Assessment Framework on the cities Town Hall Theatre Pilot site visits Sant Cugat (2/2) Detected possibilities to improve energy efficiency Space heating and cooling PV system (Town Hall) Lighting system Occupancy Indicative possible DSS action plans Action Plan Idea Involved equipment Output of the system Optimization of air-conditioning profiles using free cooling instead of the heat pump Scheduling of pre-heating and cooling of the rooms, according to occupancy Optimal use of electrical equipment according to measured and forecast occupancy (which is highly variable) Change of staff s working places according to the colder and hotter areas of the building Update of the BMS (Desigo system) Adaptation of air-conditioning electric load to the present and foreseen production of the PV plant Adaptation of the BMS Operating Schedules Installation of BEMS Operating Schedules Weekly schedule of switching on/off the air-conditioning system Weekly schedule of switching on/off the respective systems A weekly schedule based on upcoming scheduled rehearsals, past occupancy data, approximate durations, employees habits A weekly schedule of working places based on temperature, humidity and lighting conditions

24 Stay in touch For the latest news and updates you can join us online Website: YouTube: Optimus-Smarcity.eu Facebook: OPTIMUS LinkedIN: OPTIMUS Newsletter: sign up by visiting our website

25 OPTIMUS Web-based Tools OPTIMUS SCEAF Tool Assess the performance of a building in terms of energy optimization, CO 2 emissions reduction and energy cost minimization. Thermal Comfort Validator Declare your thermal sensation inside a building

26 Thank you for your attention! Contact: Siegfried Zoellner Coordinator, Sustainable Resources, Climate & Resilience ICLEI European Secretariat GmbH (ICLEI Europe) Leopoldring 3 D Freiburg Germany Tel.: This project has received funding from the European Union s Seventh Programme for Research, Technological Development and Demonstration under Grant Agreement No

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