Enabling Real-Time Charging for Smart Grid Infrastructures using In-Memory Databases

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  • Motivation: “Was nichtgemessenwerdenkann, kannnichtverbessertwerden!”DaheristZiel des BachelorprojektsdurchMessen von EnergiewertenInformationenabzuleiten
  • Enabling Real-Time Charging for Smart Grid Infrastructures using In-Memory Databases

    1. 1. Enabling Real-Time Charging for Smart Grid Infrastructures using In-Memory Databases<br />1st LCN Workshop on Smart Grid Networking InfrastructureOct 14, 2010 - Denver, CO, USA<br />Matthieu-P. Schapranow<br />Hasso Plattner Institute<br />
    2. 2. Agenda<br />Key Facts about the Hasso Plattner Institute<br />Motivation<br />Proposed Architecture<br />Simulation Details<br />Benchmarking<br />Business Impacts<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />2<br />
    3. 3. Key Facts about the Hasso Plattner InstituteInternals<br />Founded as a public-private partnershipin 1998 in Potsdam near Berlin, Germany<br />Institute belongs to theUniversity of Potsdam<br />Ranked 1st in CHE 2009<br />500 B.Sc. and M.Sc. students<br />10 professors, 92 PhD students<br />Course of study: IT Systems Engineering <br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />3<br />
    4. 4. Key Facts about the Hasso Plattner Institute Research Group Hasso Plattner / Alexander Zeier<br />Research focus: real customer data for enterprisesoftware and design of complex applications<br />In-Memory Data Management for Enterprise Applications <br />Human-Centered Software Design and Engineering <br />Maintenance and Evolution of SOA Systems <br />Integration of RFID Technology in Enterprise Platforms <br />Cooperations<br />Academic: Stanford, MIT, etc.<br />Industry: SAP, Siemens, Audi, etc.<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />4<br />
    5. 5. MotivationHow to measure?<br />“If you cannot measure it,you cannot improve it!”<br />(William Thomson, 1st Lord Kelvin)<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />5<br />
    6. 6. MotivationState-of-the-art<br />Interval: Mainly annual meter readings<br />Type: Mainly manual or small range wireless readings<br />What is missing?<br />Direct feedback for customers<br />Convenient tracking methods<br />Real-time billing details for cost control<br />How much personnel involvement is required?<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />6<br />
    7. 7. Proposed Architecture<br />*Advanced Metering Infrastructure was simulated<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />7<br />
    8. 8. Simulation DetailsMaster Energy Profile<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />8<br />
    9. 9. Simulation DetailsRealistic Test Data<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />9<br /><ul><li>Basis: Consumption profile of singlehousehold in Germany in 2009
    10. 10. Variance: +/- 5 percent per profile
    11. 11. 8-digit unique profile number
    12. 12. Each profile stored in an approx. 1.6 MB CSV file</li></li></ul><li>BenchmarkingSetup<br />Intra-day Billing with Time-of-Use Buckets<br />Pro: Prices depend on real energy demand <br />Cons: Billing requires assignment of power consumption time<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />10<br />
    13. 13. SAP’s Columnar In-Memory DB distributed across 3 blades, each<br />2 x Intel Xeon E5450 CPUs@3GHz, 4 cores, 32 kB L1, 12 MB L2,<br />64 GB DIMM DDR <br />Data compression ratio about 8:1 in-memory<br />BenchmarkingIn-Memory Prototype<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />11<br />
    14. 14. BenchmarkingQuery Results for 100k households<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />12<br />
    15. 15. Business ImpactsCurrent State: Post-payment Schema<br />Fix contracts, e.g. for the period of 12 months<br />Annual metering of power consumption<br />Fixed down payments per month or quarter<br />Pros: Not a single huge payment<br />Cons:<br />Over payment, when using less energy (bound money)<br />No convenient way to measure saving impacts<br />Provider changes are only rare<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />13<br />
    16. 16. Business ImpactsFuture Outlook of Real-Time Charging<br />Tracking of consumption on live data<br />Instant feedback for customers<br />Payments can be accurately adapted each month<br />Basis for alternative payment methods, e.g. pre-paid<br />Switching between energy providers instantly<br />Select a certain provider for a certain time span or device<br />Full cost control possible<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />14<br />
    17. 17. Thank you for your interest!Keep in contact with us.<br />Ralph Kühne, M.Sc.<br />ralph.kuehne@hpi.uni-potsdam.de<br />Matthieu-P. Schapranow, M.Sc.<br />matthieu.schapranow@hpi.uni-potsdam.de<br />Hasso Plattner InstituteEnterprise Platform & Integration ConceptsMatthieu-P. SchapranowAugust-Bebel-Str. 8814482 Potsdam, Germany<br />Responsible: Deputy Prof. of Prof. Hasso PlattnerDr. Alexander Zeierzeier@hpi.uni-potsdam.de<br />SGNI/LCN2010, Enabling Real-Time Charging for Smart Grid Infrastructures, Schapranow, Oct 14, 2010<br />15<br />

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