人工鱼群神经网络在电力系统短期负荷预测中的应用APPLICATION OF ARTIFICIAL FISH-SWARM NEURAL NETWORK IN SHORT-TERM LOAD FORECASTING OF POWER SYSTEM
马建伟,张国立
摘要(Abstract):
短期负荷预测结果对电力系统的经济效益具有重要影响。人工鱼群算法是最新提出的新型寻优策略,具有良好的克服局部极值、获得全局极值的能力。文章建立了一种新的人工鱼群神经网络预测模型,利用人工鱼群算法训练神经网络的权值,再将该神经网络用于短期负荷预测。对某电力系统进行的负荷预测结果表明,该方法与传统的BP神经网络预测方法相比具有较强的自适应能力和较好的预测效果。
关键词(KeyWords): 人工鱼群算法;神经网络;短期负荷预测;电力系统
基金项目(Foundation):
作者(Author): 马建伟,张国立
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参考文献(References):
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