基于NSGA-Ⅱ风蓄协调的多目标优化调度研究
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摘要
针对风电并网带来弃风与常规机组污染排放问题,在考虑经济效益、提高风电利用率的同时,建立一种多目标风电-抽水蓄能联合优化日运行模型,采用带精英策略的快速非支配排序遗传算法(non-dominated sorting genetic algorithm-Ⅱ,NSGA-Ⅱ)进行机组特性分层对比,确定抽蓄机组与常规机组工况,以最大化抽蓄机组削峰填谷的效益和最小化常规机组耗煤与排放量为目标,寻求最优运行方式。通过算例对比3种不同的运行方式,证明该模型能够有效地减少弃风功率,煤耗量和排放量,同时与多目标粒子群算法(multi-objectiveparticle swarm optimization,MOPSO)对比显示出NSGA-Ⅱ求解的优越性。
Aiming at the problems of wind power curtailment and pollutant emission of conventional units,and considering the economic benefits and improvement of wind energy utilization,a multi-objective combined operation model of wind power and pumped, storage is established.Non-dominated sorting genetic algorithm-II(NSGA-II)is used to compare unit characteristics and determine the working conditions of the storage unit and the conventional unit.In order to maximize the benefit of peak shaving and valley filling of pumped storage units and minimize coal consumption and emission of conventional units,the optimum running mode is studied.Comparing three different running modes,the example proves that the model can effectively reduce the wind power curtailment,coal consumption and emissions.Meanwhile,comparing with multiobjective particle swarm optimization,the superiority of NSGA-II is shown.
Aiming at the problems of wind power curtailment and pollutant emission of conventional units,and considering the economic benefits and improvement of wind energy utilization,a multi-objective combined operation model of wind power and pumped, storage is established.Non-dominated sorting genetic algorithm-II(NSGA-II)is used to compare unit characteristics and determine the working conditions of the storage unit and the conventional unit.In order to maximize the benefit of peak shaving and valley filling of pumped storage units and minimize coal consumption and emission of conventional units,the optimum running mode is studied.Comparing three different running modes,the example proves that the model can effectively reduce the wind power curtailment,coal consumption and emissions.Meanwhile,comparing with multiobjective particle swarm optimization,the superiority of NSGA-II is shown.
引文
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[10]董振斌,李义容,李海思.考虑风电功率与需求响应不确定性的备用容量配置[J].电力需求侧管理,2017,19(1):29-34.DONG Zhenbin,LI Yirong,LI Haisi.Reserve capactity configuration considering uncertainty of wind power and demand response[J].Power Demand Side Management,2017,19(1):29-34.
[2]张鹏,刘继春,吕林,等.基于风蓄协调的节能调度方法[J].电力系统保护与控制,2011,39(2):29-34.ZHANG Peng,LIU Jichun,LU Lin,et al.The energysaving dispatch based on the coordination between pumped storage hydro and wind energy[J].Power System Protection and Control,2011,39(2):29-34.
[3]胡泽春,丁华杰,孔涛.风电-抽水蓄能联合日运行优化调度模型[J].电力系统自动化,2012,36(2):36-41.HU Zechun,DING Huajie,KONG Tao.A novel control strategy based on phase adjustment for microgrid parallel inverters without interconnection[J].Automation of Electric Power Systems,2012,36(2):36-41.
[4]邹金,赖旭,汪宁渤.以减少电网弃风为目标的风电与抽水蓄能协调运行[J].电网技术,2015,39(9):2472-2 477.ZOU Jin,LAI Xu,WANG Ningbo.Mitigation of wind curtailment by coordinating with pumped storage[J].Power System Technology,2015,39(9):2 472-2 477.
[5]肖白,丛晶,高晓峰,等.风电-抽水蓄能联合系统综合效益评价方法[J].电网技术,2014,38(2):400-404.XIAO Bai,CONG Jing,GAO Xiaofeng,et al.A method to evaluate comprehensive benefits of hybrid wind powerpumped storage system[J].Power System Technology,2014,38(2):400-404.
[6]罗斌.基于NSGA-Ⅱ的含风电场电力系统多目标调度计划研究[D].长沙:长沙理工大学,2013.LUO Bin.NSGA-II based multi-objective dispatch scheduling of wind power integrated system[D].Changsha:Changsha University of Science and Technology,2013.
[7]HOZOURI M A,ABBASPOUR A,FOTUHI-FIRUZABADM,et al.On the use of pumped storage for wind energy maximization in transmission-constrained power systems[J].IEEE Transactions on Power Systems,2015,30(2):1 017-1 025.
[8]杨柳青,林舜江,刘明波,等.考虑风电接入的大型电力系统多目标动态优化调度[J].电工技术学报,2014,29(10):286-295.YANG Liuqing,LIN Shunjiang,LIU Mingbo,et al.Multiobjective dynamic optimal dispatch for large-scale power systems considering wind power penetration[J].Electrical Technology of Large Power System Wind Power,2014,29(10):286-295.
[9]杨丽君,杨丽君,李健强,等.计及供需侧备用协调优化的含风电场电力系统经济调度[J].电力需求侧管理,2015(4):7-12.YANG Lijun,YANG Lijun,LI Jianqiang,et al.A wind integrated power system economic dispatch based on supplydemand coordinated optimization method[J].Power Demand Side Management,2015(4):7-12.
[10]董振斌,李义容,李海思.考虑风电功率与需求响应不确定性的备用容量配置[J].电力需求侧管理,2017,19(1):29-34.DONG Zhenbin,LI Yirong,LI Haisi.Reserve capactity configuration considering uncertainty of wind power and demand response[J].Power Demand Side Management,2017,19(1):29-34.