基于混合型粒子群算法的智能家庭能量管理策略  

Home Energy Management Based on Hybrid Particle Swarm Optimization

作　　者：尹忠东[1] 林挚 李德智[2,3] 董明宇 YIN Zhongdong;LIN Zhi;LI Dezhi;DONG Mingyu(State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electrical Power University,Beijing 102206,China;China Electric Power Research Institute,Beijing 100192,China)

机构地区：[1]华北电力大学新能源电力系统国家重点实验室,北京102206 [2]中国电力科学研究院,北京100192 [3]需求侧多能互补优化与供需互动技术北京市重点实验室,北京100192

出　　处：《华北电力大学学报（自然科学版）》2018年第4期25-33,共9页Journal of North China Electric Power University：Natural Science Edition

基　　金：国家重点研发计划重点专项(2016YFB0101900);中国电力科学院研究院创新基金项目(YD83-17-002)

摘　　要：随着全球能源和环境问题的日益严峻,基于可再生能源的分布式电源已成为目前各国的发展重点。在分布式电源日益增长和智能电网的大前提下,智能家庭能量管理系统得到了更多的关注。介绍了目前存在的智能家庭能量管理策略与智能家庭能量管理系统的系统结构,并提出了采用智能式最优化算法来解决这类优化问题。在多种约束条件下,以家庭运行成本以及负荷平滑程度为目标,采用混合型粒子群算法来求解家庭能量管理问题,并用仿真验证了家庭环境下算法的有效性与经济性。As the problem concerning global energy and environment becomes increasingly serious,distributed generation,based on renewable energy,has become the focus of many countries for future development. Under the background of the smart grid and growing number of distributed generation,home energy management system（ HEMS） is getting more and more attention. Firstly,this paper introduced some existing home energy management strategies and the system structure of HEMS. Secondly,an intelligent optimization algorithm was proposed to solve the problem of optimization. Under a variety of constraints,this paper adopted hybrid particle swarm optimization to solve the home energy management problem aiming at minimizing operation cost and the degree of load smoothing. Finally,this paper established a simulation to prove the effectiveness and economy of this method.

关 键 词：家庭能量管理系统 混合型粒子群算法 约束条件 

分 类 号：TM73[电气工程—电力系统及自动化]