This paper proposes evolutionary particle swarm optimization (EPSO) combined with an adaptive-network-based fuzzy inference system (ANFIS) for short-term electricity prices forecasting. In a deregulated framework, producers and consumers require short-term price forecasting to derive their bidding strategies to the electricity market. Accurate forecasting tools are required for producers to maximize their profits and for consumers to maximize their utilities. The accuracy of the price forecasting attained with the proposed intelligent system is thoroughly evaluated, reporting the numerical results from a real-world case study.