Short-term load forecasting based on weather information

被引：0

作者：

Feng, W ^{[1
]}

Keng, YE ^{[1
]}

Qi, LY ^{[1
]}

Jun, L ^{[1
]}

Shan, YC ^{[1
]}

机构：

[1] Elect Power Res Inst, Beijing 100085, Peoples R China

来源：

POWERCON '98: 1998 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY - PROCEEDINGS, VOLS 1 AND 2 | 1998年

关键词：

short-term load forecasting (STLF); artificial neural network (ANN); weather variable;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper addresses electric power short-term load forecasting(the next day 24 or 96 time point load) based on weather forecasting information. It describes a load forecasting system that is running in North China Electric Power Network. The system can consider the effect of temperature, relative humidity and weather condition on the load. The forecasting result is improved apparently. The ANN's techniques and An simplified pattern recognition are adopt to deal with the complex relation between the load and weather variables.

引用

页码：572 / 575

页数：4

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