First Ideas on the Methodological Approach OPTIMising the energy USe in cities with smart decision support system (OPTIMUS) Presentation by Stella Androulaki Kick-Off Meeting October, 23 rd -24 th 2013, Athens

Introduction  Energy efficiency in a Smart City Better quality of life Achieving sustainable growth with existing resources  Control energy intensive systems with the use of ICT DSS to support actions improving energy use in a short-term horizon Considering common types of data: weather forecasts, de-centralized measurements, energy prices, renewable energy production data, social media data

Important elements of the DSS  Input Data  Short-term Actions Per sector Stakeholder involved  Measurement Indicators  Other Constraints  Potential Targets for Monitoring  Reduction = F(short-term actions, indicators) ??

Input Data Social Events City authorities planned End-users planned Emergencies Energy- related Prices Tariffs of national energy supply Electricity and fuels costs Renewables Production Production Storage Distribution Demand Environmental Impact Building Indoor conditions Final energy use per sector Real-time energy profiles Transportation Real-time monitoring of free parking places Fuel consumption and amount of emissions per vehicle type Urban Facilities Data of municipal road lighting system … Weather Weather Forecasts Temperature for next week Humidity for next week Other types of data Demographic Geographical Urban Planning: Energy Action Plans Commitments of the city and other legislative constraints Other types of data Demographic Geographical Urban Planning: Energy Action Plans Commitments of the city and other legislative constraints Determination of specific data indicators Identification of reliable & accessible data sources

Sectors & Stakeholders  Sectors Buildings Transportation Urban Facilities  Stakeholders City Authorities: Municipal building, Urban facilities, Municipal lighting, Public transport, Municipal staff, … Energy Companies Citizens Industries Other Stakeholders Decision Maker

Short-Term Actions  Short-term actions will be grouped by sector  According to the stakeholder involved Directly manageable Indirectly manageable WeatherSocialEnergy StakeholderActionTemperature…EventsEmergenciesPrices Building DataTransportation Data Indoor Conditions …Consumption per Vehicle Type … A: Building Sector Actions City AuthorityA1   B: Transportation Sector Actions City Authority, Staff B1  C: Urban Facilities Actions City AuthorityC1  A1: Identification of the most energy efficient plan for heating and cooling a building B1: Carpooling services C1: Manage Stadiums/Facilities lighting

Indicators & Monitoring  Indicators derive from: Metering Calculations Estimations Statistical analysis …  Potential Targets for Monitoring Energy Consumption Reduction Linking with the targets Energy Costs Reduction … Identification of organizations responsible for each type of data collection and statistical analysis

The OPTIMUS DSS Architecture OPTIMUS DSS IndicatorsFormulae Weather Social Prices Sensor- based RE Production Datasources Legislative Constraints Actions/sector Monitoring Suggested actions/ sector Achieved reduction

Thank you for your attention! Prof. John Psarras Dr Haris Doukas Mr Manos Ergazakis Ms Stella Androulaki Mr Vangelis Marinakis OPTIMising the energy USe in cities with smart decision support system (OPTIMUS)