Short-term forecasting of prices for the Russian wholesale electricity market based on neural networks

被引:0
|
作者
Zolotova I.Y. [1 ]
Dvorkin V.V. [1 ]
机构
[1] Institute for Problems of Pricing and Regulation of Natural Monopolies of the National Research University, Higher School of Economics, Moscow
基金
俄罗斯基础研究基金会;
关键词
D O I
10.1134/S1075700717060144
中图分类号
学科分类号
摘要
The article considers the possibility of using neural networks for the short-term forecasting of electricity prices in the day-ahead market (DAM) based on factors strictly determined for the forecast period. A set of six factors has been determined, which allows an hourly forecast of the DAM price to be constructed for a month in each of the four seasons with a high accuracy. The proposed model shows low average errors in forecasting the price for each hour of the month and in turn allows possible significant price deviations to be anticipated. © 2017, Pleiades Publishing, Ltd.
引用
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页码:608 / 615
页数:7
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