| Bidding of hydropower plant is an important part in electricity market competition. Making correct and reasonable bidding strategy is very essential for hydropower plant to obtain expected maximum benefit. It is based on the forecasted price. In order to reduce the error, the bidding model of hydropower plant uses the piecewise bidding strategy. The optimal goal is making hydropower plant obtain maximum income in the way of making good bidding strategy. Its model have three characteristics: complex constraint conditions, several decision variable and nonlinear. So its solution is worth been discussed further.In this paper, firstly, hydropower’s characteristics, formation process and affecting factors of the piecewise bidding strategy are introduced in detail. Secondly, the bidding model of constant water head hydropower plant and its optimal mechanism are introduced. Then its original bidding strategy is improved: the price coefficient is introduced and the golden section method is applied to optimize to get a better output-bidding strategy. Besides, a concrete computing case is presented to test the model, verifying the plausibility of the methodology. Finally, the bidding model of variable head hydropower plant and its optimization mechanism are introduced. After analyzing and comparing the advantages and disadvantages between genetic algorithm and ant algorithm, this paper complemented them each other and introduced the double genetic algorithm-ant algorithm: it made full use of the each algorithm’s features to solve the model. In order to validate the rightness of the proposed hybrid optimization algorithm, the algorithm is programmed by MATLAB software. After quoting the variable head hydropower plant’s data, the results are obtained it proves the betterment of the proposed algorithm.In this paper, the solving method of bidding model of hydropower plant, which provide solution and proposal for its bidding strategy in electricity market, are discussed. |
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