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Abstract(s)
Forecasting electricity prices is a fundamental task for all type of markets participants including electricity markets. There are factors that bring unce1tainty to price formation, such as demand forecasting, fuel prices, player's strategies, regulatory changes, weather conditions and technical restrictions and generation availability. In addition, the particular characteristics of electricity (supply must be in balance with demand) make this task more complicated. So, it is necessary to develop accurate and robust techniques on a sho1t-term (days) and long-term basis (months). This work presents two methodologies to be applied to long-term electricity prices forecasting (months) in Spanish electricity market for a glven period. A study case with real data is presented and discussed in detail.
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Keywords
Artificial neural networks Electricity Markets Price Forecasting Regression Models