1. Savona, 10th April 2014 OPTIMUS Linking Smart Cities with Energy Optimisation

2. Overview  OPTIMUS: A multidimensional pioneer  OPTIMUS DSS Data Input  Weather Forecasting  Energy Profiles  Social Media  Energy Prices  Energy Production  The OPTIMUS DSS architectural concept

3. OPTIMUS: A multidimensional pioneer  Multidisciplinary Data Sources  Semantic Modeling of Data  Integration of Data for Energy Optimisation Adopts state-of-the-art technologies and develops appropriate intelligent tools, leading to City-level energy optimization.

4. OPTIMUS DSS Data Input  Weather Forecasting  Energy Profiles of municipal buildings  Data and Social Mining concerning scheduled major city events  Energy Prices available from the city energy providers  Energy Production from any facility available to the city

5. Weather Forecasting: Now-casting and short-term forecasting  Capturing of data concerning the upcoming weather conditions (reliable short-term and free online sources for relevant weather variables)  Combination with the energy profiles of the municipal buildings (energy uses-production)  Normalization according to fixed information (time schedules & holidays)  Energy demand forecasting and definition of the consequent behaviors

6. Energy Profiles: Short and long term decision making and optimization  Capture data through a network of sensors Advantage: Real time functioning information  Categories of collected data: Building parameters, energy variables & indoor environmental variables  Aggregation/scale: time-stamp & spatial scale  Determination way: calculated & measured

7. Social Media: Capturing information through keywords and events  Contain information about special events  Illustrate the behavior of people and furthermore the energy profile of buildings  Are exploited for a lasting energy behavioral change  “Trend Analysis” and “Sentiment Analysis” modules Retrospectively and on-line detection of events REAL TIME

8. Energy Prices: Taking advantage of flexible markets Dealing with  Day-ahead & Intra-day market  Actors in the electricity market & Electricity exchanges in Europe Approaches based on  Historical data (ARX models)  Self-learning machines (ELM machines)

9. Energy Production: Monitoring the energy production facilities of the pilot cities Urban scale production or gained indirectly through the grid Data collection from:  Tools intended for the management, maintenance and optimization of RE facilities  External data acquisition systems

10. The OPTIMUS DSS architectural concept

11. Ms. Stella Androulaki: standrul@epu.ntua.gr Dr. Haris Doukas: h_doukas@epu.ntua.gr Mr. Vangelis Spiliotis: spiliotis@fsu.gr Mr. Vangelis Marinakis: vmarinakis@epu.ntua.gr Mr. Manos Ergazakis: mergaz@epu.ntua.grstandrul@epu.ntua.grh_doukas@epu.ntua.grspiliotis@fsu.grvmarinakis@epu.ntua.grmergaz@epu.ntua.gr Thank you for your Attention!