遗传算法在电力系统无功优化中的应用

遗传算法根据自然界适者生存的原则进行搜索和优化。将遗传算法应用于电力系统无功优化，不仅能避免一般优化算法的局部最优问题，并能解决无功优化中变量的离散问题，避免维数灾难，提供最优及次优方案，使无功优化更切实际。遗传算法的引入，为电力系统无功优化提供了一种新的计算方法，使无功优化方法更加完善和实用。

THE APPLICATION OF GENETIC ALGORITHMS TO REACTIVE POWER OPTIMIZATION IN ELECTRIC POWER SYSTEMS

This paper proposes a novel approach to reactive power optimization on the basis of genetic algorithms.Genetic algorithms are search and optimization algorithms based on the machanics of natural selection and natural genetics.When genetic algorithms are applied to the reactive power optimization in electric power systems,it not only can avoid optimization problems in general optimization algorithms ,but also can solve the discrete variables in reactive power optimizations.The genetic algorithms can avert a dimension catastrophe,and provide an optimal and some sub-optimal schemes for reactive power optimization.With the application of genetic algorithms in electric power systems,a novel algorithm is supplied for reactive power optimization,the reactive power optimization will become more perfect and more realizable.