Aspern Smart City Research. Corporate Technology

Transcription

1 Aspern Smart City Research siemens.at/innovationen

2 Future energy infrastructure of Smart Cities requires smart energy distribution and usage concepts Security of supply Energy must always be reliable and affordable. Renewable Energy System integration and intelligent control of renewable to reduce CO 2 and increase energy efficiency. Low voltage grid control In the future, millions of small power producers feed electricity into the grid. The low voltage grid provides stability in the network and balances production and consumption. Consumption Control Demand Side Management; Power consumption in real-time to adapt to price fluctuations. Energy storage Since wind and solar energy supply is irregular, power storage and management are necessary. Efficient use of Energy Intelligent control of distribution networks and buildings will lead to energy savings. Page 2 Source: CC Siemens (Siemens-Welt December 2012)

3 aspern Vienna s Urban Lakeside Facts 2,4 million m² area 2,2 million m² gross floor space workplaces residents high class apartments Offices, production and service business, science, research and education More than m² area for shops, pubs and small business in the whole Urban Lakeside Vienna Urban Lakeside Aspern Page 3

4 ASCR Structure Partner of the ASCR joint venture 44,1 % 29,95 % 20,0 % 4,66 % 1,29 % 38,5 meur Page 4 Planning and construction Operative, maintenance and repair Research ASCR staff Miscellaneous (marketing, office, ) 9,7 meur 6,5 meur 14,1 meur 5,6 meur 2,4 meur

5 ASCR Research Fields Page 5

6 Smart Grid Domain R&D Agenda Step 1 Grid transparency Data provisioning & grid monitoring grid operation determine remaining grid capacity and enable secure operation near the limits Continuous provisioning of grid operation data (sensors, meters, status estimation) Consolidation LV grid topology with measurement values Monitoring of faults and threshold violations Step 2 Data recording and processing Big data & data analytics back office grid optimization passive grid optimization Migration of planning process from worst case assumptions to real requirements based on measured data and prosumer models Grid and process optimization through data analytics Step 3 Active distribution grid Active grid management distributed intelligent devices active grid optimization framework - basis for new services Plug and play environment for distributed field devices minimizing CAPEX and OPEX APP Ecosystem for field devices based on standard Hardware Flexibility management Page 6

7 Smart Building R&D Agenda Predictive optimization Use energy at the right time Model predictive optimization and control Prediction of building generation & consumption Predictive optimization using external information (e.g., weather forecasts) Multi-modal optimization (heat, electricity) Simulation and model based optimization Buildings as part of a higher-level optimization Buildings provide flexibility Standardized interfaces Integration of all stakeholders into the system Standardized communication interfaces Development of an overall system architecture Simplified provisioning, configuration and management over the system s life cycle Data analysis Generate new information from data analytics Context-aware information systems Central or de-central data analytics Data Mining User behavior modeling to increase the accuracy of energy demand forecasting algorithms Data correlation for fault detection and predictive maintenance Page 7

8 Smart Grid Flexibility Operator Energy Pool Manager Smart Market Smart Building overview Smart ICT Smart User Interaction Building Energy Management Desigo TRA S7 Desigo PX Room Automation Building Metering Heating, Ventilation Renewable Energy & Storage Page 8

9 ASCR SIEMENS Wien Energie / Wiener Netze ASCR1.0 Preliminary results (Status 7/17) Example Quick Wins for WE (building domain): Air-heatpump for garages CO 2 comparison for residential (D12) Energy optimization student home (D5b) Soil storage utilization Home Automation App Infrastructure planning Etc. Example Quick Wins for WN (grid domain): Grid map Grid data granularity Smart Metering monitoring Storage strategies Data analytics GMD Cost analysis smart grid Etc. Building energy management system BEMS (building optimization) De-centralized energy management System (DEMS) for energy pooling Installed smart grid framework with prototype applications (Watch Dog, Forecasting, Flex Op, State detection etc.) Installed comprehensive data model acting as the research base Smart Building Testbed: 3 building blocks with thermal and electrical supply infrastructure + Building automation (DESIGO) Smart Grid Testbed: 12 transformer stations with smart metering & grid Monitoring devices Smart ICT Testbed: Teradata Data Warehouse Connectivity to data center Wien Energie und Wiener Netze Page 9

10 Smart ICT R&D Agenda Simulation and Prognosis Digital Twin for estimating potentials Validation and impact assessment Smart Grid Domain Smart ICT in a Smart City Context Information Ecosystem for independent stakeholders Interfaces and Interactions across domains Smart Building Domain Data Integration and Analytics Business Intelligence and Data Discovery Complex Data Analytics and Identification of Correlations Page 10

11 LV-Grid Monitoring with Analytic Web-App Traditional Business Intelligence Structured and repeatable abcdef1 abcdef2 abcdef3 abcdef4 Page 11

12 LV-Grid Connection Evaluation with Analytic Web-App Page 12 Traditional Business Intelligence Structured and repeatable

13 Data Discovery in the Aspern LV-Grid Data Discovery Multi-structured and iterative Page 13

14 Siemens Contact and further information DI Harald Loos Head Research in Digitalization and Automation Austria Siemensstraße Wien Phone: Internet siemens.at/innovationen Page 14

15 I M P R E S S U M Energiekonferenz energy2050: Am Marktplatz Energiezukunft: Was wollen Kunden, was kann die Branche? 27. bis 29. in Hof bei Salzburg Veranstalter und Herausgeber VERBUND AG Am Hof 6a 1010 Wien Copyright: Das Werk einschließlich aller seiner Teile ist urheberrechtlich geschützt. Jede Verwertung außerhalb der engen Grenzen des Urheberrechtsgesetzes ist ohne Zustimmung des Verlages unzulässig und strafbar. Das gilt vor allem für Vervielfältigungen in irgendeiner Form (Fotokopie, Mikrokopie oder ein anderes Verfahren), Übersetzung und die Einspeicherung und Verarbeitung in elektronischen Systemen.