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Wind power trading in the competitive electricity market
The installed wind power capacity has been increasing rapidly around the world. In the United States, most independent system operators (ISOs) and regional transmission organizations (RTOs) allow wind power to be sold into the competitive electricity market. However, the uncertain characteristic of wind resources has posed a major challenge for wind power producers to survive in such a competitive environment. Moreover, in the presence of a significant wind power penetration, the electricity market equilibria should be evaluated. To solve these problems, two objectives were set in this dissertation research. The first objective is to develop optimization models to generate optimal trading strategies for wind power producers in the electricity market. The second objective is to develop an appropriate approach to find the equilibria of the electricity market with multiple wind power producers. To achieve both objectives, the uncertainties should be considered and modeled appropriately. To achieve the first objective, this research developed three different stochastic optimization models to generate optimal trading strategies for price-taker and price-maker wind power producers, respectively, in the short-term electricity market. In the first model, the optimal bidding strategies of price-taker wind power producers were generated while considering the influence of the conventional power producers who provide bilateral reserves for the wind power producers. The second model maximized the profit of a combined wind and compressed air energy storage (CAES) power producer in both the short-term bilateral and pool electricity market. In both cases, the risk management is also considered to model the tradeoff between risk and profit. For a price-maker wind power producer, its trading behavior will influence the market clearing price. Therefore, a bilevel stochastic optimization model was developed to generate the optimal bidding strategies for the price-maker wind power producer while taking into account the market clearing process. To achieve the second objective, a stochastic equilibrium problem with equilibrium constraints (EPEC) model was built to find all Nash Equilibria of the electricity market, where the wind power producers are either price-takers or price-makers. The impacts of high penetration levels of wind power and transmission constraints were analyzed. Extensive computer simulations were performed to validate the proposed models using real-world data obtained from the U.S. electricity markets.
Dai, Ting, "Wind power trading in the competitive electricity market" (2015). ETD collection for University of Nebraska - Lincoln. AAI3718077.