Study On AGC And AVC Of Hydropower Station Based On Improved Genetic Algorithm

The AGC and AVC of hydropower station are very important and complex softwares that control hydropower station in providing power to electric system, and play an important role in ensuring the quality of electric energy. The traditional control algorithm in AGC and AVC of hydropower station is not as competent as it appears; however, the developing Intelligent Control (IC) theory provides some new solutions to this problem.At the beginning of this paper, the traditional control algorithm in AGC and AVC of hydropower station and the IC theory, especially the genetic algorithm (GA) theory, are stated. A better method based on GA, which is used to solve nonlinear function optimization under the multi-restrictive conditions, is introduced, and the float encoded genetic algorithm (FGA) based on direct comparison-proportional method (DCPM) is detailed here. The method can deal with multi-restrictive conditions of the optimal problem effectively. It ameliorates searching efficiency of GA, and has strong robustness. With characteristic of a turbine generator, the alterable intercross probability and mutation probability, and with intercross operator and mutation operator that suit the float encoded genetic algorithm, the AGC and AVC software of hydropower station has been designed based on DCPM-FGA.At the end of the dissertation, example calculation is given under multi-loading cases using the AGC software of hydropower station based on DCPM-FGA. The example indicates that the results of DCPM-FGA are small. Comparing with the method of equal differential increment rate, DCPM-FGA has better optimization quality. The AGC software of hydropower station based on DCPM-FGA can reduce water consume, and enhance the economic performance of hydropower stations.