A study on neural networks for short-term load forecasting

Proceedings of the First International Forum on Applications of Neural Networks to Power Systems Pub Date : 1991-07-23 DOI:10.1109/ANN.1991.213492

K.Y. Lee, Y. T. Cha, C. Ku

引用次数: 39

Abstract

A study is made on the application of the artificial neural network (ANN) method to forecast the short-term load for a large power system. The load has two distinct patterns: weekday and weekend-day patterns. The weekend-day pattern include Saturday, Sunday, and Monday loads. Three different ANN models are proposed, including two feedforward neural networks and one recurrent neural network. Inputs to the ANN are past loads and the output is the predicted load for a given day. The standard deviation and percent error of each model are compared.<>

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

神经网络短期负荷预测研究

研究了人工神经网络(ANN)方法在大型电力系统短期负荷预测中的应用。负载有两种不同的模式:工作日模式和周末模式。周末模式包括周六、周日和周一的负载。提出了三种不同的神经网络模型，包括两种前馈神经网络和一种递归神经网络。人工神经网络的输入是过去的负荷，输出是给定一天的预测负荷。比较了各模型的标准差和误差百分比。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Proceedings of the First International Forum on Applications of Neural Networks to Power Systems

自引率

0.00%

发文量

期刊最新文献

Finite precision error analysis for neural network learning Hybrid expert system neural network hierarchical architecture for classifying power system contingencies Neural network application to state estimation computation Short term electric load forecasting using an adaptively trained layered perceptron Neural networks for topology determination of power systems