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

I. Yu. Zolotova () and V. V. Dvorkin
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I. Yu. Zolotova: Higher School of Economics
V. V. Dvorkin: Higher School of Economics

Studies on Russian Economic Development, 2017, vol. 28, issue 6, 608-615

Abstract: Abstract 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.

Date: 2017
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DOI: 10.1134/S1075700717060144

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