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Bidding and Offering Strategy of Hybrid Electric Companies in Day-ahead Energy Market

Kazemi, Mostafa | 2016

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 48915 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Ehsan, Mehdi
  7. Abstract:
  8. This Thesis presents a new approach for determining the day-ahead bidding strategies of a hybrid electric energy company. The company has both energy generation and energy retailing businesses in a competitive electricity market. Demand response programs are also considered in the retail side of the company in order to hedge the risk of participation in wholesale market. Price-taker and price maker companies are considered in this thesis separateky.For the price-taker hybrid structure, the predivtion of day-ahead prices are used to evaluate the optimum bidding and offering strategies. Also, day-ahead market price uncertainty is modeled, using non-probabilistic Information Gap Decision Theory (IGDT) method. The considered GenCo has generation units and a retailer part. In addition, non-decreasing bidding curve is constructed according to the proposed IGDT-based method. The applicability of the proposed method is demonstrated using an illustrative example, with 54 thermal units and the results are verified using after-the-fact actual market data. For the price-maker cases, a max-min bi-level mathematical programming with equilibrium constraint model is introduced for offering a strategy that manages the risk of uncertain forecasted rivals’ bids by robust optimization. The max-min bi-level model is converted to its equivalent single level optimization using Karush-Kuhn-Tucker optimality conditions. The duality theory is utilized to find the equivalent ordinary maximization model of max-min problem. Strong duality theory and big M method are also used to linearize the final model of offering strategy. Applicability of the proposed approach is shown by implementing it on IEEE 118-bus test system
  9. Keywords:
  10. Bidding Strategy ; Duality Theory ; Robust Optimization ; Day-ahead Energy Market ; Hybrid Electric Company

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