摘要
短期负荷预测是一项重要的工作。分析了BP神经网络的基本原理,并基于BP神经网络建立了短期负荷预测模型,设计了模型的输入层、输出层和隐层。通过分析结果可以看出,该方法可以准确地对未来24小时的负荷波动进行预测。
Short-term load forecasting is an important task.In this paper,we analyze the basic principles of the BP neural network,and establish a short-term load prediction model based on the BP neural network,and design the input layer,output layer and hidden layer of the model.According to the example analysis results,the current method can accurately predict the load fluctuations in the next 24 hours.
作者
马隽遥
MA Juan-yao(Luoyang Power Supply Company,State Grid Henan Electric Power Company,Luoyang 471000,China)
出处
《电气开关》
2024年第4期49-51,55,共4页
Electric Switchgear
关键词
负荷预测
BP神经网络
温度
湿度
降雨量
load forecasting
BP neural network
temperature
humidity
rainfall