In a deregulated profit-based environment, consumers and producers need short-term intelligent prediction tools to predict their bid strategies in the energy market. Also, all markets players need accurate forecasting tools with lower uncertainty, allowing to maximizing their profits. Hence, this manuscript presents a new intelligent approach based on a combination of Wavelet Transform (WT), Evolutionary Particle Swarm Optimization (EPSO) and Adaptive Network and Fuzzy Inference System (ANFIS) for forecasting in power engineering systems. The results of two real-world case studies are shown, regarding energy prices and wind power, which show the proficiency of the proposed intelligent approach.