Energies 2013, 6(11), 5897-5920; doi:10.3390/en6115897
Article

Price Forecasting in the Day-Ahead Energy Market by an Iterative Method with Separate Normal Price and Price Spike Frameworks

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Received: 12 September 2013; in revised form: 25 October 2013 / Accepted: 5 November 2013 / Published: 12 November 2013
(This article belongs to the Special Issue Smart Grids: The Electrical Power Network and Communication System)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: A forecasting methodology for prediction of both normal prices and price spikes in the day-ahead energy market is proposed. The method is based on an iterative strategy implemented as a combination of two modules separately applied for normal price and price spike predictions. The normal price module is a mixture of wavelet transform, linear AutoRegressive Integrated Moving Average (ARIMA) and nonlinear neural network models. The probability of a price spike occurrence is produced by a compound classifier in which three single classification techniques are used jointly to make a decision. Combined with the spike value prediction technique, the output from the price spike module aims to provide a comprehensive price spike forecast. The overall electricity price forecast is formed as combined normal price and price spike forecasts. The forecast accuracy of the proposed method is evaluated with real data from the Finnish Nord Pool Spot day-ahead energy market. The proposed method provides significant improvement in both normal price and price spike prediction accuracy compared with some of the most popular forecast techniques applied for case studies of energy markets.
Keywords: electricity price forecasts; price spike forecasts; compound classifier; hybrid methodology; input feature selection
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MDPI and ACS Style

Voronin, S.; Partanen, J. Price Forecasting in the Day-Ahead Energy Market by an Iterative Method with Separate Normal Price and Price Spike Frameworks. Energies 2013, 6, 5897-5920.

AMA Style

Voronin S, Partanen J. Price Forecasting in the Day-Ahead Energy Market by an Iterative Method with Separate Normal Price and Price Spike Frameworks. Energies. 2013; 6(11):5897-5920.

Chicago/Turabian Style

Voronin, Sergey; Partanen, Jarmo. 2013. "Price Forecasting in the Day-Ahead Energy Market by an Iterative Method with Separate Normal Price and Price Spike Frameworks." Energies 6, no. 11: 5897-5920.


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