本文已被：浏览 1630次 下载 812次
Received:January 16, 2016
Received:January 16, 2016
中文摘要: 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.
中文关键词: 中长期负荷预测 宏观影响因素 粒子群与循环寻优 改进型PSOSVM算法 支持向量机
Abstract: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.
keywords: medium and long-term load forecasting macro factors PSO and cross validation optimization modified PSOSVM algorithm support vector machine
文章编号：201600621 中图分类号： 文献标志码：
基金项目:
Reference text: