电网技术2018，Vol.42Issue(2)：598-606,9.DOI:10.13335/j.1000-3673.pst.2017.0937
基于VMD与PSO优化深度信念网络的短期负荷预测
Short-Term Load Forecasting Based on VMD and PSO Optimized Deep Belief Network
摘要
Abstract
In order to improve accuracy of short-term load forecasting,original historical load sequence is decomposed into several characteristic model functions with variational mode decomposition (VMD).Load forecasting models are developed after analyzing characteristics of each model function.Selecting effective input variables is technical measures to improve load forecasting accuracy.In this paper,mutual information is adopted to calculate correlation between influence factors and output variables,and then an input variable set is selected.It is difficult for traditional load forecasting model based on neural network to train multi-layer network,thus affecting its prediction accuracy.Deep belief network (DBN) uses a non-supervised greedy layer-by-layer training algorithm to construct a multi-hidden layer sensor structure with excellent performance in regression and forecasting analysis,and becomes a research hotspot in deep learning field.This paper uses DBN algorithm to establish a forecasting model for each model function to improve prediction accuracy.DBN connection weight is optimized with particle swarm optimization algorithm to avoid local optimal solution due to random initialization,thus enhancing DBN forecasting performance.Finally,case test shows effectiveness of the proposed model.关键词
短期负荷预测/变分模态分解/输入变量选择/互信息/粒子群算法/优化深度信念网络Key words
short-term load forecasting/variational mode decomposition/input variables selection/mutual information/particle swarm optimization algorithm/optimized deep belief network分类
信息技术与安全科学引用本文复制引用
梁智,孙国强,李虎成,卫志农,臧海祥,周亦洲,陈霜..基于VMD与PSO优化深度信念网络的短期负荷预测[J].电网技术,2018,42(2):598-606,9.基金项目
国家自然科学基金项目(51507052) （51507052）
江苏省电力公司科技项目《大规模用户与主动配电网的双向友好互动技术研究》资助项目(J2016015) （J2016015）
江苏省智能电网技术与装备重点实验室课题资助.Project Supported by National Natural Science Foundation of China(51507052) （51507052）
Science and Technology Project of Jiangsu Electric Power Company (Research on Two-way Friendly Interaction Technology Between Large Scale Users and Active Distribution Networks,J2016015) （Research on Two-way Friendly Interaction Technology Between Large Scale Users and Active Distribution Networks,J2016015）
Jiangsu Key Laboratory of Smart Grid Technology and Equipment. （）
