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MASTER THESIS Nr. 315 A SIMULATION PLATFORM FOR POWER TRADING

MASTER THESIS Nr. 315 A SIMULATION PLATFORM FOR POWER TRADING. Jurica Babić. Zagreb, July 2012. Outline. Background and motivation Power Trading Agent Competition (Power TAC) CrocodileAgent 2012. Background and Motivation Transition from traditional to smart grids.

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MASTER THESIS Nr. 315 A SIMULATION PLATFORM FOR POWER TRADING

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  1. MASTER THESIS Nr. 315A SIMULATION PLATFORM FOR POWER TRADING Jurica Babić Zagreb, July 2012

  2. Outline Background and motivation Power Trading Agent Competition (Power TAC) CrocodileAgent 2012

  3. Background and MotivationTransition from traditional to smart grids Some limitations of traditional power grids: centralized production energy losses not able to cope with intermittent and decentralizedrenewables (e.g., wind turbines and solar panels) Smart grids: ICT layer - advanced grid management new market opportunities

  4. Motivation and background (2)Smart grid as an enabler of market applications 2. risk-free environment for testing needed 1. market design needed Smart grids Traditional grids

  5. Power Trading Agent Competition (Power TAC)Introduction Power market simulator International project (6 universities) Purpose – test market designs for smart grids Combines market agents and the element of competition Software agent in a role of self-interested broker: buys and sells energy for customers intention of earning a profit minimizes energy imbalance

  6. Power TACGame scenario CrocodileAgent 2012 Visualizer

  7. CrocodileAgent 2012Overview A software agent for power trading inPower TAC Emphasis was placed on: customer market (i.e., tariff market) activities wholesale market activities forecasting using Holt-Winters method Modular design Main advantageis its active tariff offering adjustments

  8. CrocodileAgent 2012Tracks customers energy usage patterns Daily periodicity – CentervilleHomes Weeklyperiodicity – OfficeComplex No periodicity –WindmillCoOp

  9. CrocodileAgent 2012Holt-Winters: customers energy usage forecasting = Holt-Winters (trained by minimizing NRMSE) = energy usage values = periodicity = number of forecasted values OfficeComplex: actual vs predicted values

  10. CrocodileAgent 2012Activities in the customer market Chooses and applies an appropriate tariff model: fixed price multi-rate flate rate (with periodic payment*) special tariffs Evaluates existing tariffs: deriving tariff utility replacing low-rated tariffs with new ones * amount of money each of the subscribed customers pay in each TAC hour to the broker

  11. CrocodileAgent 2012Wholesale market in Power TAC: day-ahead market Hour-ahead display of market clearings

  12. CrocodileAgent 2012Activities in the wholesale market (2) = past wholesale clearing prices bidding strategy: higher prices for closing markets Energy usage forecast + wholesale price forecast + bidding strategy = wholesale order Wholesale prices: actual vs predicted values

  13. CrocodileAgent 2012Improving competition design CrocodileAgent 2012 has identified two main drawbacks in the current game design: infinite periodic payment customers are ignorant toperiodic payment PAC-MAN syndrome frequent spawn of similartariffs yields to a highermarket share more rounds in a yearly cycle of Power TAC needed

  14. Conclusion and Future Work Power TAC is a promising simulator for the evaluation of market design ideas CrocodileAgent design focus: customer and wholesale market activities Holt-Winters method for forecasting Proposal: more rounds of Power TAC Future Work: more sophisticated portfolio and wholesale m. management

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