Improved Adaptive Genetic Algorithm and Its Application in Short-Term Optimal Operation of Cascade Hydropower Stations

The improved Adaptive Genetic Algorithm (AGA) and its application in short-term joint optimal operation of Qing River cascade hydropower stations are presented in this paper. In the improved method, a new selection operator is adopted to keep the diversity of population in the selection process by making non-line conversion to fitness function. The results of simulative optimal operation based on several representative hydrographs show that the improved AGA can find a more excellent solution in the same algebra. And the results also show that power generation benefit has a certain correlation with power generation amount, but maximum power generation amount is not equal to maximum power generation benefit. The research achievements also have an important reference for the compilation of daily generation scheduling of Qing River cascade hydropower stations system.