电网技术2001，Vol.25Issue(1)：49-53,5.
遗传神经网络在电力系统短期负荷预测中的应用
APPLICATION OF GENETIC ALGORITHM NEURAL NETWORK FOR
SHORT TERM LOAD FORECASTING OF POWER SYSTEM
摘要
Abstract
To overcome the defects of BP neural network and to make short term load forecasting more accurate and fast, a kind of genetic algorithm neural network is established to forecast short term load of power system by combining
genetic algorithm and neural network. For establishing this genetic algorithm neural network, a method consisting of three steps is applied. In the first step, the number of hiddennodes of this network is calculated by use of genetic
algorithm. Thus, a more rational neural network structure is determined. In the second step, by use of genetic algorithm a fittest initial weight value is selected from the solution group of initial weight values to avoid the blindness in the selection of initial weight value. In the third step, combining the structure of the obtained neural network and the fittest initial weight value, the short term load forecasting of power system can be performed by use of improved BP algorithm.
Simulation results indicate that this method can meet the need of improving forecast accuracy and enhancing the performance of the network.关键词
遗传神经网络/短期负荷预测/BP神经网络分类
信息技术与安全科学引用本文复制引用
梁海峰,涂光瑜,唐红卫..遗传神经网络在电力系统短期负荷预测中的应用[J].电网技术,2001,25(1):49-53,5.
