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Energies 2016, 9(12), 1069; doi:10.3390/en9121069

Portfolio Decision of Short-Term Electricity Forecasted Prices through Stochastic Programming

E. T. S. de Ingenieros Industriales, University of Castilla-La Mancha, UCLM, 13071 Ciudad Real, Spain
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Academic Editor: Tapas Mallick
Received: 29 August 2016 / Revised: 12 November 2016 / Accepted: 11 December 2016 / Published: 16 December 2016
(This article belongs to the Special Issue Forecasting Models of Electricity Prices)
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Abstract

Deregulated electricity markets encourage firms to compete, making the development of renewable energy easier. An ordinary parameter of electricity markets is the electricity market price, mainly the day-ahead electricity market price. This paper describes a new approach to forecast day-ahead electricity market prices, whose methodology is divided into two parts as: (i) forecasting of the electricity price through autoregressive integrated moving average (ARIMA) models; and (ii) construction of a portfolio of ARIMA models per hour using stochastic programming. A stochastic programming model is used to forecast, allowing many input data, where filtering is needed. A case study to evaluate forecasts for the next 24 h and the portfolio generated by way of stochastic programming are presented for a specific day-ahead electricity market. The case study spans four weeks of each one of the years 2014, 2015 and 2016 using a specific pre-treatment of input data of the stochastic programming (SP) model. In addition, the results are discussed, and the conclusions are drawn. View Full-Text
Keywords: ARIMA models; day-ahead electricity market price; forecasting portfolio; stochastic programming ARIMA models; day-ahead electricity market price; forecasting portfolio; stochastic programming
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Sánchez de la Nieta, A.A.; González, V.; Contreras, J. Portfolio Decision of Short-Term Electricity Forecasted Prices through Stochastic Programming. Energies 2016, 9, 1069.

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