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In electricity industry, accurate load forecasting plays a key role in assuring the stability of power network and society. By far, there are many methods and models proposed to enhance the accuracy of forecasting results. On the basis of analyzing the performance of particle swarm algorithm (PSA) and SVM, the paper proposed a new forecasting model which is proved to be able to enhance the accuracy, improve the convergence ability and reduce operation time by numerical experiment. The proposed model is expected to offer a valid alternative for application in the load forecasting field.

Short-term electricity load forecasting based on particle swarm algorithm and SVM