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Integrated System Modeling for Handling Big Data in Electric Utility Systems

Integrated System Modeling for Handling Big Data in Electric Utility Systems. Stephanie Hamilton Robert Broadwater Brookhaven National Laboratory EDD dew@edd-us.com. Finding Good Solutions for the Hard Problems.

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Integrated System Modeling for Handling Big Data in Electric Utility Systems

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  1. Integrated System Modeling for Handling Big Data in Electric Utility Systems Stephanie Hamilton Robert Broadwater Brookhaven National Laboratory EDD dew@edd-us.com

  2. Finding Good Solutions for the Hard Problems Physical System Model Big Data Big Model Big Analysis

  3. Questions • How can we determine if investments in smart grid were (are) worthwhile? • Why are we just storing all of this data? • How can we determine the effects of renewable generation at the distribution level on the transmission system? • How can we find bad model data and failed measurement devices? • How can we move from a manually operated system to an automatically operated system, a self-healing system? • How can we better manage power restoration for major storms?

  4. Model-Centric Smart Grid • Terabyte sized data sets are being generated by the smart grid • A few utilities are using a new approach to the analysis of smart grid - “model-centric smart grid” • The model-centric approach employs a holistic, construction detail, model of the physical system – “Integrated System Model (ISM)” • All measurement data, including weather data, is related to the ISM • Changes paradigm of “pushing data to algorithms” to “pushing algorithms to data”

  5. Model-Centric Smart Grid Equation Reliability, Efficiency, Capacity, Protection, Controllability Performance Analysis + Economic Analysis + Lab Testing + Field Validation = Model-Centric Smart Grid

  6. Silo’edOrganizations with Many, Disjoint Models Suppose data sets contain terabytes?

  7. Model-Based Decisions Our ability to solve a problem depends upon the model we have to solve the problem ProblemDomain SolutionDomain Model Point solutions or scenario based solutions Can make it easy or difficult to find a good solution to the problem

  8. Measurements, Models, Algorithms, Information Measurements Components, Topology, System constraints Physical Model Understanding, Knowledge, Information Algorithms Only way to achieve certain

  9. Graph Trace Analysis for the Big Model Graph Trace Analysis with Edge-Edge Graph Matrix Analysis with Edge-Node Graph  2 1 2 Topology Iterators 3 1 2  1 3  3 5 4  Transform 4 5 4 Computer Processing Global View Local View • Edge knows neighbors • Topology continuously maintained • Algorithms with topology iterators

  10. Generic Programming Roots for GTA Algorithms that process objects in container, independent of object type Container with Iterators CS Algorithms Generic Programming Algorithms that process edges or components of graph Graph Trace Analysis Engineering Algorithms ISM with Topology Iterators Generic analysis independent of system type - electric, gas, fluid, etc.

  11. The Best Equivalent Is No Equivalent Every model simplification leads to elimination of scenarios

  12. Integrated System Model Merge different construction models together, relating all measurements “Aha” understanding Model for holistic solutions, not point or scenario based solutions

  13. ISM “Living Model” Organization Eyes of all experts on the same model Moves modeling from “age of modeling craftsman” to “manufactured models” used by many Push algorithms to data

  14. Analysis Collaboration to Build Intelligence Security Analysis Reliability Analysis Protection / Coordination Restoration Analysis Contingency Analysis Fault Analysis Power Flow Load Estimation Model Validation SCADA Measurements Load Research Statistics

  15. Commonly Used Analysis Architecture Point Solution App 1 Creation of simplified models App 1 Model Core Models Interfaces? Topology Management SCADA Data App 2 Customer Load Data App 2 Model Pushing measurement data

  16. ISM Analysis Architecture Mass Storage Memory App 1 ISM edge-edge topology Topology iterators, sharing of results, measurements Customer Loads ISM SCADA Measurements Weather Measurements App 2 Interface provided by ISM to applications

  17. ISM Model Management for Distributed Computation Environment Client: Fault Location Supports distributed computations ISM Model Server Model Queue Analysis Processes Client: Reconfiguration

  18. Wrap Up • One model of the entire physical plant that is reused provides • Foundation for solving hard problems • Organizational efficiencies and analysis collaborations • Automated analysis • All measurements are related to ISM • Building ISM requires significant effort to correct mistakes in existing model data and measurements – “Living Model” • Graph Trace Analysis is a new approach to topology management and analysis that can be used for algorithms that run on the ISM

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