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.
Original language | English |
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Article number | 1069 |
Number of pages | 19 |
Journal | Energies |
Volume | 9 |
Issue number | 12 |
DOIs | |
Publication status | Published - 1 Dec 2016 |
Externally published | Yes |
Keywords
- ARIMA models
- Day-ahead electricity market price
- Forecasting portfolio
- Stochastic programming