| The economic operation in hydropower station is an important part of the operation in power system. Many documents have made an intensive study on it. Most of these studies are based on monopolistic market. In the new market, The management of hydropower station transforms into bidding in competitive environment form planned generation. So economic operation has been becoming the conscious behavior of the electric corporations. The goal of hydropower station is to maximize the profits, which to some extent is determined by the information taken form electricity market and the operation strategy.Aim at the character of electricity market in competitive environment, two UC models were constructed in this paper. The first one is based on forecasted marginal price and takes profit as optimizing goal, this model can give hydropower station a valuable reference when they are making their bidding strategy ;The latter is a cost minimization model intending to help hydropower station lower their operation cost.Based on comprehensively comparing some sorts of algorithm available for solving UC and combining the characters of the models being proposed in this paper, genetic algorithm was chosen as numerical computing method. Some improvements concerning coding ,operator designing, constrain handling etc were made so as to make the algorithm more suitable for the models constructed in the paper. Numerical analysis illustrates that the improved genetic algorithm (IGA) designing is successful in solving high-dimension, multi-constrains, and nonlinear UC problem. The designing method is also helpful for solving other complex system optimization problems.Two illustrative examples are given in this paper. We expound that how to use the modified genetic algorithm to solve this new UC Problem with the first example. Comparing results of the second example with two other methods the algorithm's practicability is proved. Finally, a summary is given and some problems to be further studied are discussed.
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