说明：  The prediction of short term power load owns a great influence on performance of the whole electric sys- tem. Raising the result of power load forecasting is always a research spot. This paper proposes a method combined Elman neural network (ENN) and the particle swarm optimization (PSO) for the short-term power load forecasting. Firstly, this paper introduces the principle of ENN and PSO algorithm respectively and analyzes performance of network influenced by parameters of ENN. Then the particle swarm opti- mization algorithm is applied to searching the optimal learning rate of ENN