2006•Dianli xitong zidonghuaRequires access

Review of the Short-term Electricity Price Forecasting

Jianxue Wang

Open publisher page 15 citations

Abstract

A veracious short-term electricity price forecasting can help a market participant make effective bidding decisions, decrease bidding risk, and bring steady-going incomes in a competitive electricity market. Thus much attention has been focused on electricity price forecasting. In this study the available literatures on electricity price forecasting from 1997 are surveyed firstly. Based on the characteristics and contributing factors of electricity price, this paper reviews two basic methods for electricity price forecasting, viz. the time series model and the neural networks method, and then proposes their possible development. Finally, three key issues in the electricity price forecasting are discussed whilst some hot topics for further work are also presented. This work is supported by Special Fund of the National Basic Research Program of China (No. 2004CB217905).

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What this paper is about

A veracious short-term electricity price forecasting can help a market participant make effective bidding decisions, decrease bidding risk, and bring steady-going incomes in a competitive electricity market. Thus much attention has been focused on electricity price forecasting. In this study the available literatures on electricity price forecasting from 1997 are surveyed firstly. Based on the characteristics and contributing factors of electricity price, this paper reviews two basic methods for electricity price forecasting, viz. the time series model and the neural networks method, and then proposes their possible development. Finally, three key issues in the electricity price forecasting are discussed whilst some hot topics for further work are also presented. This work is supported by Special Fund of the National Basic Research Program of China (No. 2004CB217905).

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Available abstract

A veracious short-term electricity price forecasting can help a market participant make effective bidding decisions, decrease bidding risk, and bring steady-going incomes in a competitive electricity market. Thus much attention has been focused on electricity price forecasting. In this study the available literatures on electricity price forecasting from 1997 are surveyed firstly. Based on the characteristics and contributing factors of electricity price, this paper reviews two basic methods for electricity price forecasting, viz. the time series model and the neural networks method, and then proposes their possible development. Finally, three key issues in the electricity price forecasting are discussed whilst some hot topics for further work are also presented. This work is supported by Special Fund of the National Basic Research Program of China (No. 2004CB217905).

Key concepts: Electricity price forecasting, Bidding, Electricity, Electricity market, Electricity price, Economics, Work (physics), Term (time)

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