Keywordselectricity markets; medium-term electricity price forecasting; probabilistic forecasting; extremely low prices; spikes; hybrid approach; market equilibrium; electricity price; Cournot model; market mechanism parameter; selection rule (SR); reducing volatility; self-organizing-map; fuzzy logic; particle swarm optimization (PSO); forecasting; electricity price forecasting; day-ahead market; autoregression; variable selection; stepwise regression; ridge regression; lasso; elastic net; 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; short-term forecasting; electricity market prices; Iberian electricity market (MIBEL); daily session prices; intraday session prices; market clearing price (MCP); mid-term; grey prediction model; sparse data; particle swarm optimization (PSO); electricity; prices; forecasting; fundamentals; hybrid; densities; short-term load forecasting; radial basis function neural network; support vector regression; particle swarm optimization; adaptive annealing learning algorithm; ARIMA models; day-ahead electricity market price; forecasting portfolio; stochastic programming; electricity price forecasting; ensemble model; expert selection; n/a
