基于蜻蜓算法的微电网多目标优化调度  

Multi-objective Optimal Scheduling of Microgrid Based on Dragonfly Algorithm

作　　者：王蒙[1] 汪峰坤[1] 李宁 Wang Meng;Wang Fengkun;Li Ning(School of Internet and Communication,Anhui Electromechanical Vocational and Technical College,Wuhu,Anhui 241000,China;School of Electrical Engineering,Anhui University of Engineering,Wuhu,Anhui 241000,China)

机构地区：[1]安徽机电职业技术学院互联网与通信学院,安徽芜湖241000 [2]安徽工程大学电气工程学院,安徽芜湖241000

出　　处：《黑龙江工业学院学报（综合版）》2020年第5期80-85,共6页Journal of Heilongjiang University of Technology(Comprehensive Edition)

基　　金：安徽省高校自然科学研究重点项目(编号:KJ2019A1159);2018年安徽省省级质量工程项目“安徽机电职业技术学院南京第五十五所技术开发有限公司实践教育基地”(编号:2018sjjd120)。

摘　　要：可再生清洁型新能源能量的随机波动会影响主电网的稳定性,然而有效的能量优化管理能提高供电的可靠性和经济性。文章主要对含有风、光、蓄、柴和微电网并网模式下的典型日优化调度。利用蜻蜓算法从发电成本和环境污染角度对模型进行优化,并将粒子群算法得到的典型日各个时段出力构成图和发电成本进行比较。对比结果表明证明了所建立的模型的切实性和蜻蜓算法相对粒子群算法应用在微电网优化方面的优越性。The randomness and intermittency of renewable energy will have a certain impact on the large power grid,and effective energy optimization management of micro-grid can improve the reliability and economy of power supply. This paper mainly deals with the typical daily optimal scheduling in the grid connection mode of micro-grid with wind-scenery storage and firewood. Dragonfly algorithm was used to optimize the model from the perspective of power generation cost and environmental pollution,and compared with the output maps and power generation costs of typical days at various periods obtained by the particle swarm algorithm. The comparison results show the validity of the model and the dragonfly algorithm and the superiority of relative particle swarm in microgrid optimization.

关 键 词：微电网 蜻蜓算法 经济调度 多目标优化 

分 类 号：TM73[电气工程—电力系统及自动化]