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Short-term Load Forecasting Based on Fuzzy Neural Network

机译:基于模糊神经网络的短期负荷预测

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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.
机译:短期负荷预测方法是优化电力系统操作的基础。准确的负载预测有助于提高电力系统的安全性和经济效益,并可降低发电的成本。因此,找到适当的负载预测方法,以提高预测的准确性具有重要的应用价值。分析电力系统负荷预测的含义和方法后,本文解释了人工神经网络(ANN)和模糊推理系统(FIS)的一般理论,并建立了基于模糊神经网络的负载预测方法。

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