This project has received funding from the European Union s FP7 research and innovation programme under grant agreement No

Transcription

1 This project has received funding from the European Union s FP7

2 Partners This project has received funding from the European Union s FP7

3 Our vision Our vision is to design, develop and deliver a smart Decision Support System (DSS) as an integrated web-platform which helps local authorities to show the best energy saving opportunities available in public buildings. As permanent bodies that plan for the long term, local authorities are uniquely placed to play a significant role in achieving the EU 2020 targets and enabling a shift towards a low carbon economy and a cleaner, more sustainable environment. The DSS will work by collecting and structuring real- time open data sets from five domains, namely: weather conditions, social mining, buildings energy profiles, energy prices, energy production. At the same time, the system will take into account de-centralised renewable energy production, connection with the smart electricity grid and integration with smart district heating and cooling grids and other renewable energy sources. By combing real-time data with this integrated information on energy sources and systems the OPTIMUS DSS, will enable local authorities to produce short-term energy plans and implement an overall more responsive sustainable action plan to energy use for their buildings, venues and stadiums. This project has received funding from the European Union s FP7

4 Work structure OPTIMUS will follow four broad stages over the three years that it is taking place. This includes the development of a framework used to carry out a baseline assessment of the city s current energy situation; the system development of the DSS; the pilot scheme which is to take place in three cities across Europe and finally the dissemination of how to use the DSS in your cities through a series of local workshops. This project has received funding from the European Union s FP7

5 User Requirements definition methodology DATA COLLECTION PHASES Municipality & pilot buildings description questionnaire Questionnaire refining telephone calls DSS expected fucntionalities questionnaire Functionalities refining calls DSS MockUp Questionnairetodefine requeriments for each OPTIMUS s data gathering subsystem This project has received funding from the European Union s FP7

6 MOCK-UP RESULTS DSS Visual Layout: Sant Cugat Units Weather conditions Temperature (max/min)( o C) Occupancy average level (occupants) Energy cost ( ) Energy building consumption ( ) Renewable energy production (KW/h) CO2 Emissions (TNCO2) KW/h TNC today Energy monetization in comparison with weather conditions Energy monitorization table view This project has received funding from the European Union s FP7

7 Task 4.1 Application of Smart City ex-ante Assessment Framework on the cities Pilot site visits Sant Cugat Meetings with: Key staff members of the Sant Cugat 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

8 Task 4.1 Application of Smart City ex-ante Assessment Framework on the cities Comparative Analysis (3/5) Zaanstad Pilot Has an adequate level of target for The efforts made so far are not sufficient. The energy mix used leads to high CO 2 emissions and energy cost. RES (Geothermal) have been introduced but the system does not work properly. The adoption of ICT and automations is unbalanced towards comfort rather not energy efficiency. The existing systems are not exploited adequately.

9 Overview

10 Task 4.1 Application of Smart City ex-ante Assessment Framework on the cities OPTIMUS SCEAF Tool (1/4) Fill SCEAF questionnaire Evaluation Visualization Data Collection SCEAF methodology

11 Task 4.1 Application of Smart City ex-ante Assessment Framework on the cities Possible Action Plans Sant Cugat Detected possibilities to improve energy efficiency Space heating and cooling PV system (Town Hall) Lighting system Occupancy Indicative possible action plans ActionPlan Idea Involved equipment ActionPlan Description Town Hall 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 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 Weekly schedule of switching on/off the air-conditioning system Weekly schedule of switching on/off the respective systems Theatre 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 Operating Schedules Installation of BEMS Operating Schedules 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 This project has received funding from the European Union s FP7

12