基于多因素改进型PSOSVM算法的中长期负荷预测

Medium and Long-term Load Forecasting Based on Multi-factors Modified Psosvm Algorithm

中长期负荷预测作为电力规划与调度中的重要一环,其影响因素有着多样性和不确定性等特点.选取支持向量机作为中长期负荷预测的核心算法,筛选多种区域宏观经济因素,利用粒子群(PSO)寻优与循环寻优的改进型算法对支持向量机(SVM)的参数进行优化及负荷预测.仿真结果显示,改进型PSOSVM算法有着较高的预测精度.

Medium and long-term load forecasting as an important part of the electric power planning and scheduling, its influence factors have diversity, uncertainty, etc. Article selection of support vector machine （SVM） is the core of the medium and long-term load forecasting algorithm, screening of a variety of regional macroeconomic factors uses particle swarm optimization （PSO） and the improved algorithm of loop optimization of support vector machine （SVM） parameters optimization, load forecasting. The simulation results show that the modified PSOSVM algorithm has a high prediction precision.