Application of statistical and neural approaches to the daily load profiles modelling in power distribution systems

被引：36

作者：

Nazarko, J ^{[1
]}

Styczynski, ZA ^{[1
]}

机构：

[1] Bialystok Tech Univ, Inst Management & Mkt, Bialystok, Poland

来源：

1999 IEEE TRANSMISSION AND DISTRIBUTION CONFERENCE, VOLS 1 & 2 | 1999年

关键词：

load modelling; load forecasting; clustering; statistical method; neural network; network planning;

D O I：

10.1109/TDC.1999.755372

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：

Load modelling is an essential task in economic analysis, operation and planning of distribution systems. Particularly, when a Demand Side Management system is taken into account on a deregulated energy market the knowledge of load profiles is of the greatest importance. Forecasting of daily demand, based upon load models, uses comparable load research data for a different customer mix. For the given season and day of the week the shape of a daily load curve depends mainly on the customer composition. Difficulties in defining objective customer classes significantly complicate the forecasting process. Usage of statistical clustering and neural network approach makes possible to improve the load modelling accuracy. This paper presents load modelling methods useful for the long term planning of power distribution systems. Theoretical statement is illustrated by examples which correspond to Polish and German distribution systems.

引用

页码：320 / 325

页数：6

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