考虑运行控制策略的广义储能资源与分布式电源联合规划
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摘要
针对广义储能资源和分布式电源的联合规划问题,提出了包含实际储能、可平移负荷、可转移负荷和可削减负荷的响应特性模型。进一步通过双层优化架构求解考虑运行控制策略的广义储能资源和分布式电源的联合规划问题,提出不同可调控资源选址定容的实际意义与方法,上层采用改进多目标粒子群算法搜索两部分资源的选址定容方案,下层采用分支定界法求解广义储能的运行优化策略,通过上下层交替优化实现资源的联合优化配置。以IEEE 33节点配电系统进行多场景的仿真分析,结果验证了所提模型的实用性,并说明了联合规划和虚拟储能参与调控的优势与意义。
Aiming at the joint planning problem of generalized energy storage resources and distributed generator, a response model including fixed energy storage, shiftable load, transferable load and reducible load is proposed. Furthermore, the joint planning problem of generalized energy storage resources and distributed generator considering operation control strategies is solved by a bi-level optimization architecture. The practical significance and methods of siting and locating of different regulatory resources are put forward. The upper layer uses improved multi-objective particle swarm optimization algorithm to search the location and capacity selection scheme. The lower layer uses branch and bound method to solve the operation control strategy of generalized energy storage. The joint optimization configuration of resources is implemented by alternate optimization of upper and lower levels. The simulation results of multi-scenario in IEEE 33-node distribution system verify the practicability of the proposed model and prove the advantages and significance of joint planning and operation control of the virtual energy system.
Aiming at the joint planning problem of generalized energy storage resources and distributed generator, a response model including fixed energy storage, shiftable load, transferable load and reducible load is proposed. Furthermore, the joint planning problem of generalized energy storage resources and distributed generator considering operation control strategies is solved by a bi-level optimization architecture. The practical significance and methods of siting and locating of different regulatory resources are put forward. The upper layer uses improved multi-objective particle swarm optimization algorithm to search the location and capacity selection scheme. The lower layer uses branch and bound method to solve the operation control strategy of generalized energy storage. The joint optimization configuration of resources is implemented by alternate optimization of upper and lower levels. The simulation results of multi-scenario in IEEE 33-node distribution system verify the practicability of the proposed model and prove the advantages and significance of joint planning and operation control of the virtual energy system.
引文
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[16] 高红均,刘俊勇.考虑不同类型DG和负荷建模的主动配电网协同规划[J].中国电机工程学报,2016,36(18):4911-4922.GAO Hongjun,LIU Junyong.Coordinated planning considering different types of DG and load in active distribution network[J].Proceedings of the CSEE,2016,36(18):4911-4922.
[17] 茆美琴,丁勇,王杨洋,等.微网-未来能源互联网系统中的“有机细胞”[J].电力系统自动化,2017,41(19):1-11.DOI:10.7500/AEPS20170417007.MAO Meiqin,DING Yong,WANG Yangyang,et al.Microgrid—an “organic cell” for future energy interconnection system[J].Automation of Electric Power Systems,2017,41(19):1-11.DOI:10.7500/AEPS20170417007.
[18] 孙川,汪隆君,许海林.用户互动负荷模型及其微电网日前经济调度的应用[J].电网技术,2016,40(7):2009-2015.SUN Chuan,WANG Longjun,XU Hailin.An interaction load model and its application in microgrid day-ahead economic scheduling[J].Power System Technology,2016,40(7):2009-2015.
[19] 王蓓蓓,朱峰,嵇文路,等.中央空调降负荷潜力建模及影响因素分析[J].电力系统自动化,2016,40(19):44-52.WANG Beibei,ZHU Feng,JI Wenlu,et al.Load cutting potential modeling of central air-conditioning and analysis on influencing factors[J].Automation of Electric Power Systems,2016,40(19):44-52.
[20] CHEN X,WANG J,XIE J,et al.Demand response potential evaluation for residential air conditioning loads[J].IET Generation,Transmission & Distribution,2018,12(19):4260-4268.
[21] CHENG L,QI N,WEI L,et al.Power and energy balance of active distribution network considering operation-control strategy[C]// 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2),October 20-22,2018,Beijing,China.
[22] 王成山.微电网分析与仿真理论[M].北京:科学出版社,2013.WANG Chengshan.Microgrid analysis and simulation theory[M].Beijing:Science Press,2013.
[23] BRACKEN J,FALK J E,MCGILL J T.The equivalence of two mathematical programs with optimization problems in the constraints[J].Operations Research,1974,22(5):1102-1104.
[24] 王丹,兰宇,贾宏杰,等.基于弹性温度可调裕度的中央空调集群需求响应双层优化[J].电力系统自动化,2018,42(22):118-126.DOI:10.7500/AEPS20180225003.WANG Dan,LAN Yu,JIA Hongjie,et al.Double-layer optimization strategy of cluster central air-conditioner demand response based on elastic temperature adjustable margin[J].Automation of Electric Power Systems,2018,42(22):118-126.DOI:10.7500/AEPS20180225003.
[25] 胡文平,何立夫,陈杰军,等.考虑大规模电动汽车接入电网的双层优化调度策略[J].电力系统保护与控制,2016,44(21):22-28.HU Wenping,HE Lifu,CHEN Jiejun,et al.A bi-layer optimization based schedule considering large-scale electric vehicles[J].Power System Protection and Control,2016,44(21):22-28.
[26] 许志恒,张勇军,陈泽兴,等.考虑运行策略和投资主体利益的电转气容量双层优化配置[J].电力系统自动化,2018,42(13):76-84.DOI:10.7500/AEPS20170713011.XU Zhiheng,ZHANG Yongjun,CHEN Zexing,et al.Bi-level optimal capacity configuration for power to gas facilities considering operation strategy and investment subject benefit[J].Automation of Electric Power Systems,2018,42(13):76-84.DOI:10.7500/AEPS20170713011.
[27] 刘小聪,王蓓蓓,李扬,等.智能电网下计及用户侧互动的发电日前调度计划模型[J].中国电机工程学报,2013,33(1):30-38.LIU Xiaocong,WANG Beibei,LI Yang,et al.Day-ahead generation scheduling model considering demand side interaction under smart grid paradigm[J].Proceedings of the CSEE,2013,33(1):30-38.
[2] 邢海军,程浩忠,张沈习,等.主动配电网规划研究综述[J].电网技术,2015,39(10):2705-2711.XING Haijun,CHENG Haozhong,ZHANG Shenxi,et al.Review of active distribution network planning[J].Power System Technology,2015,39(10):2705-2711.
[3] 张建华,曾博,张玉莹,等.主动配电网规划关键问题与研究展望[J].电工技术学报,2014,29(2):13-23.ZHANG Jianhua,ZENG Bo,ZHANG Yuying,et al.Key issues and research prospects of active distribution network planning[J].Transactions of China Electrotechnical Society,2014,29(2):13-23.
[4] ALHARBI H,BHATTACHARYA K.Stochastic optimal planning of battery energy storage systems for isolated microgrids[J].IEEE Transactions on Sustainable Energy,2018,9(1):211-227.
[5] 吴小刚,刘宗歧,田立亭,等.基于改进多目标粒子群算法的配电网储能选址定容[J].电网技术,2014,38(12):3405-3411.WU Xiaogang,LIU Zongqi,TIAN Liting,et al.Energy storage device locating and sizing for distribution network based on improved multi-objective particle swarm optimizer[J].Power System Technology,2014,38(12):3405-3411.
[6] 孙鸣,桂旭.可向特定负荷定时限独立供电的储能系统优化配置[J].电力系统自动化,2018,42(14):115-122.DOI:10.7500/AEPS20170120004.SUN Ming,GUI Xu.Optimal configuration of battery energy storage system providing independent power supply for specific load during certain time[J].Automation of Electric Power Systems,2018,42(14):115-122.DOI:10.7500/AEPS 20170120004
[7] KAABI S S A,ZEINELDIN H H,KHADKIKAR V.Planning active distribution networks considering multi-DG configurations[J].IEEE Transactions on Power Systems,2014,29(2):785-793.
[8] XIAO J,ZHANG Z,BAI L,et al.Determination of the optimal installation site and capacity of battery energy storage system in distribution network integrated with distributed generation[J].IET Generation,Transmission & Distribution,2016,10(3):601-607.
[9] YANG P,NEHORAI A.Joint optimization of hybrid energy storage and generation capacity with renewable energy[J].IEEE Transactions on Smart Grid,2017,5(4):1566-1574.
[10] 沈欣炜,朱守真,郑竞宏,等.考虑分布式电源及储能配合的主动配电网规划-运行联合优化[J].电网技术,2015,39(7):1913-1920.SHEN Xinwei,ZHU Shouzhen,ZHENG Jinghong,et al.Active distribution network planning-operation co-optimization considering the coordination of ESS and DG[J].Power System Technology,2015,39(7):1913-1920.
[11] 张钦,王锡凡,王建学,等.电力市场下需求响应研究综述[J].电力系统自动化,2008,32(3):97-107.ZHANG Qin,WANG Xifan,WANG Jianxue,et al.Survey of demand response research in deregulated electricity markets[J].Automation of Electric Power Systems,2008,32(3):97-107.
[12] SHOJAABADI S,ABAPOUR S,ABAPOUR M,et al.Optimal planning of plug-in hybrid electric vehicle charging station in distribution network considering demand response programs and uncertainties[J].IET Generation,Transmission & Distribution,2016,10(3):3330-3340.
[13] 刘维康,王丹,余晓丹,等.考虑电气转换储能和可再生能源集成的微能源网多目标规划[J].电力系统自动化,2018,42(16):11-20.DOI:10.7500/AEPS20180228003.LIU Weikang,WANG Dan,YU Xiaodan,et al.Multi-objective planning of micro energy network considering P2G-based storage system and renewable energy integration[J].Automation of Electric Power Systems,2018,42(16):11-20.DOI:10.7500/AEPS20180228003.
[14] 贾龙,胡泽春,宋永华,等.储能和电动汽车充电站与配电网的联合规划研究[J].中国电机工程学报,2017,37(1):73-83.JIA Long,HU Zechun,SONG Yonghua,et al.Joint planning of distribution networks with distributed energy storage systems and electric vehicle charging stations[J].Proceedings of the CSEE,2017,37(1):73-83.
[15] ASENSIO M,QUEVEDO P M D,MUNOZ-DELGADO G,et al.Joint distribution network and renewable energy expansion planning considering demand response and energy storage:Part Ⅰ stochastic programming model[J].IEEE Transactions on Smart Grid,2018,9(2):655-666.
[16] 高红均,刘俊勇.考虑不同类型DG和负荷建模的主动配电网协同规划[J].中国电机工程学报,2016,36(18):4911-4922.GAO Hongjun,LIU Junyong.Coordinated planning considering different types of DG and load in active distribution network[J].Proceedings of the CSEE,2016,36(18):4911-4922.
[17] 茆美琴,丁勇,王杨洋,等.微网-未来能源互联网系统中的“有机细胞”[J].电力系统自动化,2017,41(19):1-11.DOI:10.7500/AEPS20170417007.MAO Meiqin,DING Yong,WANG Yangyang,et al.Microgrid—an “organic cell” for future energy interconnection system[J].Automation of Electric Power Systems,2017,41(19):1-11.DOI:10.7500/AEPS20170417007.
[18] 孙川,汪隆君,许海林.用户互动负荷模型及其微电网日前经济调度的应用[J].电网技术,2016,40(7):2009-2015.SUN Chuan,WANG Longjun,XU Hailin.An interaction load model and its application in microgrid day-ahead economic scheduling[J].Power System Technology,2016,40(7):2009-2015.
[19] 王蓓蓓,朱峰,嵇文路,等.中央空调降负荷潜力建模及影响因素分析[J].电力系统自动化,2016,40(19):44-52.WANG Beibei,ZHU Feng,JI Wenlu,et al.Load cutting potential modeling of central air-conditioning and analysis on influencing factors[J].Automation of Electric Power Systems,2016,40(19):44-52.
[20] CHEN X,WANG J,XIE J,et al.Demand response potential evaluation for residential air conditioning loads[J].IET Generation,Transmission & Distribution,2018,12(19):4260-4268.
[21] CHENG L,QI N,WEI L,et al.Power and energy balance of active distribution network considering operation-control strategy[C]// 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2),October 20-22,2018,Beijing,China.
[22] 王成山.微电网分析与仿真理论[M].北京:科学出版社,2013.WANG Chengshan.Microgrid analysis and simulation theory[M].Beijing:Science Press,2013.
[23] BRACKEN J,FALK J E,MCGILL J T.The equivalence of two mathematical programs with optimization problems in the constraints[J].Operations Research,1974,22(5):1102-1104.
[24] 王丹,兰宇,贾宏杰,等.基于弹性温度可调裕度的中央空调集群需求响应双层优化[J].电力系统自动化,2018,42(22):118-126.DOI:10.7500/AEPS20180225003.WANG Dan,LAN Yu,JIA Hongjie,et al.Double-layer optimization strategy of cluster central air-conditioner demand response based on elastic temperature adjustable margin[J].Automation of Electric Power Systems,2018,42(22):118-126.DOI:10.7500/AEPS20180225003.
[25] 胡文平,何立夫,陈杰军,等.考虑大规模电动汽车接入电网的双层优化调度策略[J].电力系统保护与控制,2016,44(21):22-28.HU Wenping,HE Lifu,CHEN Jiejun,et al.A bi-layer optimization based schedule considering large-scale electric vehicles[J].Power System Protection and Control,2016,44(21):22-28.
[26] 许志恒,张勇军,陈泽兴,等.考虑运行策略和投资主体利益的电转气容量双层优化配置[J].电力系统自动化,2018,42(13):76-84.DOI:10.7500/AEPS20170713011.XU Zhiheng,ZHANG Yongjun,CHEN Zexing,et al.Bi-level optimal capacity configuration for power to gas facilities considering operation strategy and investment subject benefit[J].Automation of Electric Power Systems,2018,42(13):76-84.DOI:10.7500/AEPS20170713011.
[27] 刘小聪,王蓓蓓,李扬,等.智能电网下计及用户侧互动的发电日前调度计划模型[J].中国电机工程学报,2013,33(1):30-38.LIU Xiaocong,WANG Beibei,LI Yang,et al.Day-ahead generation scheduling model considering demand side interaction under smart grid paradigm[J].Proceedings of the CSEE,2013,33(1):30-38.