GRNN Short-term Load Forecasting Model and Virtual Instrument Design

摘要：

This paper presents a short-term load forecasting model using a General Regression Neural Network (GRNN) based on actual historical load data and weather data of Yichang, Hubei, China. The forecasting accuracy shows that the model is valid and feasible which could be put into practical use. The utilization of the neural network toolbox in MATLAB has simplified the whole modeling process. In addition, in order to increase the inniitiveness of forecasting results, this paper attempts to combine neural network technique with virtual instrument technology and use LabVIEW to build a GRNN virtual instrument for short-term load forecasting.

关键词： generalregression neuralnetwork load forecasting MATLAB virtualInstrument LabVIEW

作者: Changhao Xia Bangjun Lei Hongping Wang Jiangnan Li

作者单位: Institute of Intelligent Vision and Image Information Electrical Engineering and Renewable Energy School China Three Gorges University, Yichang Hubei 443002 China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer Engineering and Applications(2011第三届计算机工程与应用国际会议 ICCEA2011)

会议地点: 海口

会议语种:英文

页码: 141-145

在线出版日期: 2011-07-15（万方平台首次上网日期，不代表论文的发表时间）