基于模糊神经网络的短期负荷预测

Cuiru Wang, Zhikun Cui, Qi Chen
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引用次数: 23

摘要

短期负荷预测方法是电力系统优化运行的基础。准确的负荷预测有助于提高电力系统的安全性和经济性,降低发电成本。因此,寻找合适的负荷预测方法,提高预测精度具有重要的应用价值。在分析了电力系统负荷预测的意义和方法的基础上,阐述了人工神经网络(ANN)和模糊推理系统(FIS)的一般理论,建立了基于模糊神经网络的负荷预测方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-term Load Forecasting Based on Fuzzy Neural Network
Short-term load forecasting method is the basis of optimizing the operation for power systems. Accurate load forecasting is helpful to improve the security and economic effect of power systems and can reduce the cost of generating electricity. Therefore, finding an appropriate load forecasting method to improve accuracy of forecasting has important application value. After analyzing the meaning and methods of power system load forecasting, this paper explains the general theory of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS), and builds a load forecasting method based on Fuzzy Neural Network.
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