1. ICT Smartcities 2013 FP7-SMARTCITIES-2013 Kick Off Meeting Athens October 23,24 2013 OPTIMising the energy USe in cities with smart decision support system (OPTIMUS) Objective ICT-2013.6.4 Optimising Energy Systems in Smart Cities Small or medium scale focused research project (STREP) “FUNITEC- Engineering and Architecture La Salle Ramon Llull University, Barcelona, Spain” Dr. Leandro Madrazo, Álvaro Sicilia, Gonçal Costa

2. Index -Scope -Objectives -Tasks -Deliverables -TimeLine -Milestones -Actions -Requirements capture -Risks

3. Scope The semantic framework will gather and integrate the data coming from the various data sources. Then, data mining process will be carried out to add metadata to data (patterns, clusters, etc). The inference engine will receive as input the data and metadata, and based on the rules included in it, it will suggest the best alternatives for the short-term energy planning. The front-end environment will show the data, criteria and suggested alternatives in the right form to the end user (city authorities).

4. Objectives These different types of data will be treated by the corresponding DSS modules. They will also inform the OPTIMUS DSS requirements and objectives. The data which will be modelled using semantic technologies and provided to different stakeholders to develop and apply advanced analysis procedures. The semantic data integration will be implemented with the participation of domain experts and data owners so as to integrate the data sources into a global data space for a city. This integration processes encompass data cleaning, data linking, data enrichment, data publishing and testing, as depicted in the following figure. Semantic integration process

5. Objectives This work package will focus on the construction of the OPTIMUS DSS architecture according to the requirements and objectives set in the WP1. The main objectives are: 1.To make use of the data captured in WP2 which will be transformed into meaningful information for different stakeholders applying advanced analysis procedures.  Tasks: T3.1, T3.2 and T3.4. 2. The information and recommendations provided by the DSS will be facilitated to stakeholders through open environments which will foster the interaction between data and users with the purpose of achieving the energy optimization objectives. 3. To meet all the necessary requirements and expectations of the end-users and will act as decision support tool for energy optimization in a rapid and sustainable way for different stakeholders involved. The DSS front-end will be user-friendly and it will be generic and adaptable enough to be applied in different cities.

6. Tasks Task 3.1: Semantic Framework For Data Integration (FUNITEC)  Implementation of methods and tools to provide an integrated access to the data captured and modelled in WP2 using semantic technologies. Task 3.2 Data Mining Analysis (FUNITEC)  Receives the semantic data from the semantic framework (T3.1) and applies data mining analysis generating a metadata layer which enhances the source data. Task 3.3 Inference Rules (POLITO)  Develop/Implement all the knowledge and intelligent rules for the energy optimization, based on the data that the DSS will receive as input (Inference Engine) Task 3.4: Front-End Environments (FUNITEC)  Create web-based environments which will provide access to different types of stakeholders in diverse forms suited to their requirements and knowledge. Task 3.5: Integration and Development of OPTIMUS DSS (FUNITEC)  Integration of the semantic data, analysis tools, inference engine and web environments (developed in T3.1, T3.2, T3.3 and T3.4) in a common architecture.

7. Deliverables D3.1. Published data in an open data portal M15  The data semantically integrated will be published in a data portal providing both HTML and RDF interface D3.2. Analysis tools to process data and inference rules M17  Tools identified and implemented as part of the DSS, including the customization of the data mining methods selected. D3.3. Inference engine integrated in the management environment M19  To create an inference from the semantic data D3.4. Functional end-user environment M17  The end-user environment implemented as part of the DSS validated and tested by the final user. D3.5 Integrated DSS system M21  Semantic framework, data portal, analysis tools, inference engine, management and end-user environments completely integrated D3.6 Integrated DSS system, fine-tuned version M34  Semantic framework, data portal, analysis tools, inference engine, management and end-user environments completely integrated

8. TimeLine Requirements (e.g. use cases, indicators, users, tools) are required to model the data based on the outputs provided by T2.1. Creation of links between data elements of different sources is required (e.g. the energy consumption data monitored in T2.3 to link them to the energy prices data captured in T2.5.) Development of the environments will be based on the user requirements gathered in T1.3. Pilot phase requires the implementation of the DSS to test it in different environments

9. Timeline WP3 -Data integration -Data mining -Inference rules -Front-end WP4 -DSS customization -Feedback from SCEAF implementation WP1 -SCEAF -User requirements WP2 -DSS Architecture -Data capture modules Requirements (e.g. use cases, indicators, users, tools, data, needs) are required to implement the DSS based on the outputs provided by -T1.3 User requirements -T2.1 DSS architecture -T4.1 Application of SCEAF in cities The feedback gathered in the Pilot implementation will retrofit the DSS implementation Requirements (e.g. use cases, indicators, users, tools, data, needs) are required to implement the DSS based on the outputs provided by -T1.3 User requirements -T2.1 DSS architecture -T4.1 Application of SCEAF in cities The feedback gathered in the Pilot implementation will retrofit the DSS implementation DSS to test it in different environments.. DSS to test it in different environments.. WP3 receives from other WPS WP3 provides to other WPS

10. Milestones Milestone 3 (month 34) - Design, Architecture and development of OPTIMUS DSS (WP2, WP3) - Fine-tuned version of OPTIMUS DSS fully operational.

11. Requirements capture process A first contact has been established with P-11 Sant Cugat to know the data, users and services which would be needed. A survey has been sent to Sant Cugat. This can be a starting point of the requirement capture process to carried out in the three pilot cities (SCEAF, Task 1.2, Task 4.1).

12. Requirements capture process: survey 1. ABOUT DATA SOURCES - Energy consumption data (monitoring) - List buildings you have energy consumption data of (monitoring, bills,…). - Describe each of them: Building dimensions, Building materials, Building destination, Occupancy, Appliances, consuming electricity, or other energy sources, Instrumentations (HVAC…)… - Energy prices - Which kind of energy prices do you have (tariffs, contractual options, special offers)? - How are you managing the energy prices? - Do you have real time access to energy prices from the energy providers? (PDF, Excel, web page…) - Energy production -Which energy production facilities do you have in your buildings/districts? - Describe each of them: Energy source (solar, wind, waterpower, renewed biomass…), energy produced, operation schedule, monitoring sensors and counters… - Which energy production management solutions are you deploying? This survey could be a starting point for Task 1.2

13. Requirements capture process: survey 1.ABOUT DATA SOURCES 2.ABOUT END-USERS 3.ABOUT NEW SERVICES This survey could be a starting point for Task 1.2

14. Requirements capture process: survey 1. ABOUT DATA SOURCES - Weather conditions Do you have/use any weather forecast system? - Upcoming events Do you have any system to capture data about citizens’ activities/events carried out in your buildings? Describe them: channels (web page, forums, social networks…),. This survey could be a starting point for Task 1.2

15. Requirements capture process: survey 2. ABOUT END-USERS - Who are the decision-makers who will use the data facilitated by the Decision Support System (DSS)? - Describe each of them: role, activities carried out by them, external company/administration… - Who are the users who will implement the actions to optimize existing conditions (facility managers, energy prices manager…)? - Describe each of them: role, tasks carried out by them, external company/administration… 3. ABOUT NEW SERVICES - Regarding energy prices which actions can you carry out/improve (changing a tariff, contractual options, special offers…)? - Regarding facilities management, which actions can you carry out/improve (operating procedures…)? This survey could be a starting point for Task 1.2

16. Risks. Risk DescriptionProbabilityImpactMitigation Plan OPTIMUS DSS requirements not adequate for development. LowHighThe OPTIMUS DSS architecture will be designed by the WP2. However, these will not be created in a vacuum. Initial design activities will be already underway giving the opportunity to technical personnel to articulate their need for specific and useful requirements during the implementation of the particular WP. OPTIMUS DSS is off-spec relative to the initial design of the prototype or fails performance and functionality testing MediumHighDevelopment will have constant oversight and quality controls. A rigorous testing and software/hardware quality control framework will be designed as a separate task and used for continuous testing and adaptations of the prototype platform. OPTIMUS DSS Pilot application is hampered due to technical problems with the prototype platform MediumHighThe testing and quality procedures will ensure software/hardware quality before the OPTIMUS DSS application. Continuous upgrades of the System mean that resources will be on hand to ensure quick responses to bugs and technical problems The reduction of energy consumption and CO2 emissions in the pilot cities is lower than anticipated due to insufficient consideration of OPTIMUS DSS suggestions from pilot cities’ decision makers. MediumHighThe pilot cities’ decision makers will be strongly involved in the project since its first phases. This reassures that their needs and expectations from the system and its envisaged functionalities will be taken into consideration in its design and development, thus increasing the OPTIMUS DSS level of acceptance. In addition during the pilot operation period, there will be strong collaboration among all consortium partners and city authorities so as to reassure that decision makers will remain highly committed to project objectives.