考虑需量管理的用户侧储能优化配置
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摘要
随着能源互联网的不断发展,分布式储能使用需求日益增长。基于用户侧电能管理,提出一种考虑优化负荷特性的储能系统规划和调度综合优化模型。在两部制分时电价的背景下,以用户侧储能系统全寿命周期内总的净收益为外层目标函数,综合考虑了储能削峰收益、峰谷套利收益、全寿命周期成本等因素;以储能系统日调度周期内收益为内层目标函数,研究用户侧储能系统各时段充/放电值的优化。结合工程实际,通过遗传算法和混合整数线性规划求解双层优化配置模型,算例测试比较了锂离子和铅炭两种电池的额定容量/功率配置、削峰率和净收益,分析了负荷曲线特性、储能单位成本和能量转换效率储能成本对于经济效益的影响,为用户侧储能系统的优化配置提供建议。
With continuous development of energy internet, the demand for distributed energy storage increases.This paper proposes a planning and scheduling model for battery energy storage system(BESS) considering load characteristics optimization based on user-side power management. Under two-part time-sharing electricity price mechanism, the model takes total net proceeds of user-side BESS within its life cycle as the outer level objective function,considering income of peak load shaving, arbitrage income and life cycle cost. The model takes net daily income of BESS as the inner level objective function to optimize the charge-discharge curve of BESS. The genetic algorithm combined with mixed integer linear programming(MILP) is adopted to solve the bi-level optimization model based on a practical project. The configurations, peak shaving rates and net proceeds of lithium ion(Li-ion) battery and lead carbon(Pb-C)battery are compared through case studies, and the effects of load curve characteristics, cost of unit energy storage and energy conversion efficiency on economic benefit are analyzed,and some suggestions on configuration plan of the battery are provided.
With continuous development of energy internet, the demand for distributed energy storage increases.This paper proposes a planning and scheduling model for battery energy storage system(BESS) considering load characteristics optimization based on user-side power management. Under two-part time-sharing electricity price mechanism, the model takes total net proceeds of user-side BESS within its life cycle as the outer level objective function,considering income of peak load shaving, arbitrage income and life cycle cost. The model takes net daily income of BESS as the inner level objective function to optimize the charge-discharge curve of BESS. The genetic algorithm combined with mixed integer linear programming(MILP) is adopted to solve the bi-level optimization model based on a practical project. The configurations, peak shaving rates and net proceeds of lithium ion(Li-ion) battery and lead carbon(Pb-C)battery are compared through case studies, and the effects of load curve characteristics, cost of unit energy storage and energy conversion efficiency on economic benefit are analyzed,and some suggestions on configuration plan of the battery are provided.
引文
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[14]向育鹏,卫志农,孙国强,等.基于全寿命周期成本的配电网蓄电池储能系统的优化配置[J].电网技术,2015,39(1):264-270.Xiang Yupeng,Wei Zhinong,Sun Guoqiang,et al.Life cycle cost basedoptimalconfigurationofbatteryenergystoragesystemindistribution network[J].Power System Technology,2015,39(1):264-270(in Chinese).
[15]韩晓娟,王丽娜,高僮,等.基于成本和效益分析的并网光储微网系统电源规划[J].电工技术学报,2016,31(14):31-39.Han Xiaojuan,Wang Lina,Gao Tong,et al.Generation planning of grid-connectedmicro-gridsystemwithPVandbatteriesstorage systembasedoncostandbenefitanalysis[J].TransactionsofChina Electrotechnical Society,2016,31(14):31-39(in Chinese).
[16]孙波,廖强强,陆宇东,等.钠硫电池储能系统的电价机制研究[J].电网技术,2014,38(8):2108-2113.Sun Bo,Liao Qiangqiang,Lu Yudong,et al.Research on electricity pricingmechanismofNaSbatterybasedenergystoragesystem[J].Power System Technology,2014,38(8):2108-2113(in Chinese).
[17]Oudalov A,Cherkaoui R,Beguin A.Sizing and optimal operation of battery energy storage system for peak shaving application[C]//Power Tech,2007 IEEE Lausanne.IEEE,2008:621-625.
[18]Wang Z,LüG X,Wei L,et al.Study on optimization of hybrid energy storageconfiguration[C]//IEEEConferenceonEnergyInternetand Energy System Integration.IEEE,2017:1-6.
[19]邹波,文福拴,周盈,等.不完全信息情形下确定两部制输电价格的风险谈判模型[J].电力系统自动化,2015,39(22):59-67.Zou Bo,Wen Fushuan,Zhou Ying,et al.A CvaR-based Negotiation model for determining two-part transmission prices under incomplete information[J].Automation Electric Power Systems,2015,39(22):59-67(in Chinese).
[2]Huang AQ,Crow ML,HeydtGT,etal.The futurer enewable electricenergy delivery and management(FREEDM)system:the energy internet[J].Proceedings of the IEEE,2011,99(1):133-148.
[3]李建林,田立亭,来小康.能源互联网背景下的电力储能技术展望[J].电力系统自动化,2015,39(23):15-25.Li Jianlin,Tian Liting,Lai Xiaokang.Outlook of electrical energy storagetechnologiesunderenergyinternetbackground[J].AutomationElectricPowerSystems,2015,39(23):15-25(in Chinese).
[4]徐国栋,程浩忠,马紫峰,等.用于缓解电网调峰压力的储能系统规划方法综述[J].电力自动化设备,2017,37(8):3-11.Xu Guodong,Cheng Haozhong,Ma Zifeng,et al.Overview of ESS planningmethodsforalleviatingpeak-shavingpressureofgrid[J].ElectricPowerAutomationEquipment,2017,37(8):3-11(in Chinese).
[5]刘静琨,张宁,康重庆.电力系统云储能研究框架与基础模型[J].中国电机工程学报,2017,37(12):3361-3371.Liu Jingkun,Zhang Ning,Kang Chongqing.Research framework and basicmodelsforcloudenergystorageinpowersystem[J].Proceedings of the CSEE,2017,37(12):3361-3371(in Chinese).
[6]修晓青,唐巍,李建林,等.基于层次分析法的储能配置综合评估技术[J].电力系统自动化,2018,42(11):72-78.Xiu Xiaoqing,Tang Wei,Li Jianlin,et al.Comprehensive evaluation technologyofenergystorageconfigurationbasedonanalytic hierarchyprocess[J].AutomationElectricPowerSystems,2018,42(11):72-78(in Chinese).
[7]赵波,包侃侃,徐志成,等.考虑需求侧响应的光储并网型微电网优化配置[J].中国电机工程学报,2015,35(21):5465-5474.Zhao Bo,Bao Kankan,Xu Zhicheng,et al.Optimal sizing for gridconnectedPV-and-storagemicrogridconsideringdemandresponse[J].Proceedings of the CSEE,2015,35(21):5465-5474(in Chinese).
[8]周楠,樊伟,刘念,等.基于需求响应的光伏微网储能系统多目标容量优化配置[J].电网技术,2016,40(6):1709-1716.Zhou Nan,Fan Wei,Liu Nian,et al.Battery storage multi-objective optimizationforcapacityconfigurationofPV-basedmicrogridconsidering demand response[J].Power System Technology,2016,40(6):1709-1716(in Chinese).
[9]Cao M,Xu Q,Bian H,et al.Research on configuration strategy for regional energy storage system based on three typical filtering methods[J].IET Generation Transmission&Distribution,2016,10(10):2360-2366.
[10]Zhang X,Yuan Y,Hua L,et al.On generation schedule tracking of wind farms with battery energy storage systems[J].IEEE Transactions on Sustainable Energy,2017,8(1):341-353.
[11]DvorkinY,Fernández-BlancoR,KirschenDS,etal.Ensuring profitabilityofenergystorage[J]. IEEETransactionsonPower Systems,2016,32(1):611-623.
[12]郑乐,胡伟,陆秋瑜,等.储能系统用于提高风电接入的规划和运行综合优化模型[J].中国电机工程学报,2014,34(16):2533-2543.ZhengLe,HuWei,LuQiuyu,etal.Researchonplanningand operationmodelforenergystoragesystemtooptimizewindpower integration[J].Proceedings of the CSEE,2014,34(16):2533-2543(in Chinese).
[13]薛金花,叶季蕾,陶琼,等.采用全寿命周期成本模型的用户侧电池储能经济可行性研究[J].电网技术,2016,40(8):2741-2746.XueJinhua,YeJilei,TaoQiong,etal.Economicfeasibilityof user-side battery energy storage based on whole-life-cycle cost model[J].Power System Technology,2016,40(8):2741-2746(in Chinese).
[14]向育鹏,卫志农,孙国强,等.基于全寿命周期成本的配电网蓄电池储能系统的优化配置[J].电网技术,2015,39(1):264-270.Xiang Yupeng,Wei Zhinong,Sun Guoqiang,et al.Life cycle cost basedoptimalconfigurationofbatteryenergystoragesystemindistribution network[J].Power System Technology,2015,39(1):264-270(in Chinese).
[15]韩晓娟,王丽娜,高僮,等.基于成本和效益分析的并网光储微网系统电源规划[J].电工技术学报,2016,31(14):31-39.Han Xiaojuan,Wang Lina,Gao Tong,et al.Generation planning of grid-connectedmicro-gridsystemwithPVandbatteriesstorage systembasedoncostandbenefitanalysis[J].TransactionsofChina Electrotechnical Society,2016,31(14):31-39(in Chinese).
[16]孙波,廖强强,陆宇东,等.钠硫电池储能系统的电价机制研究[J].电网技术,2014,38(8):2108-2113.Sun Bo,Liao Qiangqiang,Lu Yudong,et al.Research on electricity pricingmechanismofNaSbatterybasedenergystoragesystem[J].Power System Technology,2014,38(8):2108-2113(in Chinese).
[17]Oudalov A,Cherkaoui R,Beguin A.Sizing and optimal operation of battery energy storage system for peak shaving application[C]//Power Tech,2007 IEEE Lausanne.IEEE,2008:621-625.
[18]Wang Z,LüG X,Wei L,et al.Study on optimization of hybrid energy storageconfiguration[C]//IEEEConferenceonEnergyInternetand Energy System Integration.IEEE,2017:1-6.
[19]邹波,文福拴,周盈,等.不完全信息情形下确定两部制输电价格的风险谈判模型[J].电力系统自动化,2015,39(22):59-67.Zou Bo,Wen Fushuan,Zhou Ying,et al.A CvaR-based Negotiation model for determining two-part transmission prices under incomplete information[J].Automation Electric Power Systems,2015,39(22):59-67(in Chinese).