Enhanced Forecasting Approach for Electricity Market Prices and Wind Power Data Series in the Short-Term

Gerardo J. Osório, Jorge N. D. L. Gonçalves, Juan M. Lujano-Rojas and João P. S. Catalão
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Gerardo J. Osório: C-MAST, University of Beira Interior, Covilhã 6201-001, Portugal
Jorge N. D. L. Gonçalves: INESC TEC and the Faculty of Engineering of the University of Porto, Porto 4200-465, Portugal
Juan M. Lujano-Rojas: C-MAST, University of Beira Interior, Covilhã 6201-001, Portugal
João P. S. Catalão: C-MAST, University of Beira Interior, Covilhã 6201-001, Portugal

Energies, 2016, vol. 9, issue 9, 1-19

Abstract: The uncertainty and variability in electricity market price (EMP) signals and players’ behavior, as well as in renewable power generation, especially wind power, pose considerable challenges. Hence, enhancement of forecasting approaches is required for all electricity market players to deal with the non-stationary and stochastic nature of such time series, making it possible to accurately support their decisions in a competitive environment with lower forecasting error and with an acceptable computational time. As previously published methodologies have shown, hybrid approaches are good candidates to overcome most of the previous concerns about time-series forecasting. In this sense, this paper proposes an enhanced hybrid approach composed of an innovative combination of wavelet transform (WT), differential evolutionary particle swarm optimization (DEEPSO), and an adaptive neuro-fuzzy inference system (ANFIS) to forecast EMP signals in different electricity markets and wind power in Portugal, in the short-term, considering only historical data. Test results are provided by comparing with other reported studies, demonstrating the proficiency of the proposed hybrid approach in a real environment.

Keywords: adaptive neuro-fuzzy inference system (ANFIS); differential evolutionary particle swarm optimization (DEEPSO); electricity market prices (EMP); forecasting; short-term; time series; wavelet transform (WT); wind power (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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