Energies 2014, 7(5), 3304-3318; doi:10.3390/en7053304

Dynamic Hybrid Model for Short-Term Electricity Price Forecasting

1,* email, 2email and 3email
Received: 14 April 2014; in revised form: 8 May 2014 / Accepted: 12 May 2014 / Published: 20 May 2014
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: Accurate forecasting tools are essential in the operation of electric power systems, especially in deregulated electricity markets. Electricity price forecasting is necessary for all market participants to optimize their portfolios. In this paper we propose a hybrid method approach for short-term hourly electricity price forecasting. The paper combines statistical techniques for pre-processing of data and a multi-layer (MLP) neural network for forecasting electricity price and price spike detection. Based on statistical analysis, days are arranged into several categories. Similar days are examined by correlation significance of the historical data. Factors impacting the electricity price forecasting, including historical price factors, load factors and wind production factors are discussed. A price spike index (CWI) is defined for spike detection and forecasting. Using proposed approach we created several forecasting models of diverse model complexity. The method is validated using the European Energy Exchange (EEX) electricity price data records. Finally, results are discussed with respect to price volatility, with emphasis on the price forecasting accuracy.
Keywords: data mining; neural network; price volatility; short term electricity price forecasting; forecasting techniques; spot market; electricity price
PDF Full-text Download PDF Full-Text [1198 KB, uploaded 20 May 2014 11:49 CEST]

Export to BibTeX |

MDPI and ACS Style

Cerjan, M.; Matijaš, M.; Delimar, M. Dynamic Hybrid Model for Short-Term Electricity Price Forecasting. Energies 2014, 7, 3304-3318.

AMA Style

Cerjan M, Matijaš M, Delimar M. Dynamic Hybrid Model for Short-Term Electricity Price Forecasting. Energies. 2014; 7(5):3304-3318.

Chicago/Turabian Style

Cerjan, Marin; Matijaš, Marin; Delimar, Marko. 2014. "Dynamic Hybrid Model for Short-Term Electricity Price Forecasting." Energies 7, no. 5: 3304-3318.

Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert