Long-term load forecasting in electricity market

被引：37

作者：

Daneshi, Hossein ^{[1
]}

Shahidehpour, Mohammad ^{[1
]}

Choobbari, Azim Lotfjou ^{[1
]}

机构：

[1] IIT, Elect Power & Power Elect Ctr, Chicago, IL 60616 USA

来源：

2008 IEEE INTERNATIONAL CONFERENCE ON ELECTRO/INFORMATION TECHNOLOGY | 2008年

关键词：

power system planning; long-term load forecasting; regression method; artificial neural network; fuzzy system;

D O I：

10.1109/EIT.2008.4554335

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Long-term load forecasting has a vital role in generation, transmission and distribution network planning. Traditional studies for long-term load forecasting were based on regression method, which could not provide a true representation of power system behavior in a volatile electricity market. The purpose of this paper is to introduce two approaches based regression method and artificial neural network (ANN) for long-term load forecast. We apply fuzzy sets to ANN for modeling long-term uncertainties and compare the enhanced forecasting results with those of traditional methods. The ISO New England market data are used to illustrate the efficiency of each technique.

引用

页码：395 / 400

页数：6

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