中文摘要：

提出一种基于粒子群优化一最小二乘支持向量机（particle swarm optimization -least squares support vector ma-chine, PSO - LSSVM）的短期负荷预测的方法。采用PSO算法对LSSVM的模型参数进行寻优，实现LSSVM参数的自动优化选取，进而得到比单一LSSVM更准确的短期负荷预测模型。实际算例结果验证了所提预测方法可行性，与其他方法预测结果的对比进一步突出了所提方法的有效性。

英文摘要：

A short- term load forecasting method based on particle swarm optimization -least squares support vector machine （ PSO - LSSVM） is proposed. In this method, PSO is adopted to optimize the parameters of LSSVM model, thus to achieve automatic optimization of the parameters of LSSVM and further to obtain the more accurate short - term load forecasting model than a single LSSVM model. The simulation results show the feasibility of the proposed method, and the comparative results with other methods verify the effectiveness of the proposed method.