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短期电价预测综述
引用本文:张显,王锡凡.短期电价预测综述[J].电力系统自动化,2006,30(3):92-101.
作者姓名:张显  王锡凡
作者单位:西安交通大学电气工程学院,陕西省西安市,710049
基金项目:国家重点基础研究发展计划(973计划)资助项目(2004CB217905).
摘    要:准确的短期电价预测可为市场参与者的竞价策略提供指导,从而减少参与者的竞价风险,为其带来稳定的收益,因此短期电价预测已成为电力市场中的研究热点。结合1997年以来的相关文献对短期电价预测进行了综述。在分析电价基本特点和电价影响因素的基础上,重点对时间序列法和神经网络法这2种常用的电价预测方法进行了评述,探讨了各方法可能的进一步研究方向。最后对电价影响因素选择、数据预处理和电价预测工具的选择这3个电价预测中的重要问题进行了讨论,并对短期电价预测的研究工作提出了一些建议。

关 键 词:电力市场  电价  短期电价预测  时间序列法  神经网络
收稿时间:2005-06-20
修稿时间:2005-06-202005-08-01

Review of the Short-term Electricity Price Forecasting
ZHANG Xian,WANG Xi-fan.Review of the Short-term Electricity Price Forecasting[J].Automation of Electric Power Systems,2006,30(3):92-101.
Authors:ZHANG Xian  WANG Xi-fan
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).
Keywords:electricity market  electricity price  short-term electricity price forecasting  time series model  neural network
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