Reactive Power Optimization of Wind Farm based on Improved Genetic Algorithm

Reactive power optimization plays a significant role in the operation of wind farm grid intern connection to maintaining voltage stability and system reliability. Genetic algorithm (GA) is an efficient method which can be applied in reactive power optimization to reduce power loss and improve power quality. However, traditional GA has some defects, such as slow convergence and prematurity. For improvement, the paper modified decoding method, genetic operators, crossover and mutation probability, iteration stopping criterion based on the theory of Catastrophism. A reactive power optimization techniques based on improved genetic algorithm (IGA) of wind farm is such presented. Simulation results for Chinese Mongolia Huitengliang Power Plant show that the proposed method has satisfied global performance, high convergence speed and stable convergence performance, so it is suitable to solve the optimal reactive power planning. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the organizing committee of 2nd International Conference on Advances in Energy Engineering (ICAEE).