基于多目标网格自适应搜索算法的储能系统参与AGC优化控制策略
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摘要
为使储能系统(energy storage system,ESS)更好地辅助传统调频机组参与电网的自动发电控制(automatic generation control,AGC),提出了一种基于动态仿真滚动优化和多目标网格自适应搜索(multi-objective mesh adaptive direct search,MOMADS)算法的优化控制策略。该策略基于对系统功率扰动的预测数据,并结合动态仿真结果和MOMADS算法对未来1min时间段内AGC指令的最优分配比例进行滚动优化计算,使系统AGC性能达到最优。算例分析表明,该策略能够有效提高系统的AGC性能,稳定系统频率,维持ESS的SOC在较为理想的区间,并且具有较强的鲁棒性。
In order to make energy storage system(ESS) participate in system automatic generation control(AGC), this paper presents an optimal control strategy based on dynamic simulation rolling calculation and multi-objective mesh adaptive direct search(MOMADS) algorithm. According to predicted power disturbance data, this strategy combines rolling calculation for the optimal distribution ratio of AGC instruction with the results of dynamic simulations and MOMADS algorithm. It could achieve the goal of ESS assisting traditional units to improve frequency control capacity of system. Simulations demonstrate that this strategy could improve AGC performance, stabilize system frequency, and maintain the SOC of ESS within an ideal range. In addition, the strategy has a strong robustness.
In order to make energy storage system(ESS) participate in system automatic generation control(AGC), this paper presents an optimal control strategy based on dynamic simulation rolling calculation and multi-objective mesh adaptive direct search(MOMADS) algorithm. According to predicted power disturbance data, this strategy combines rolling calculation for the optimal distribution ratio of AGC instruction with the results of dynamic simulations and MOMADS algorithm. It could achieve the goal of ESS assisting traditional units to improve frequency control capacity of system. Simulations demonstrate that this strategy could improve AGC performance, stabilize system frequency, and maintain the SOC of ESS within an ideal range. In addition, the strategy has a strong robustness.
引文
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[14]孙冰莹,刘宗歧,杨水丽,等.补偿度实时优化的储能-火电联合AGC策略[J].电网技术,2018,42(2):426-433.Sun Bingying,Liu Zongqi,Yang Shuili,et al.A real-time optimization method of compensation degree for storage coordinated with thermal power unit in AGC[J].Power System Technology,2018,42(2):426-433(in Chinese).
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[17]黄际元,李欣然,曹一家,等.面向电网调频应用的电池储能电源仿真模型[J].电力系统自动化,2015,39(18):20-24,74.Huang Jiyuan,Li Xinran,Cao Yijia,et al.Battery energy storage power supply simulation model for power grid frequency regulation[J],Automation of Electric Power Systems,2015,39(18):20-24,74(in Chinese).
[18]程瑜,张粒子,李渝.考虑需求价格弹性的销售电价帕累托优化折扣[J].电力系统自动化,2003,27(24):10-13.Cheng Yu,Zhang Lizi,Li Yu.Pareto optimization on electricity price discount considering demand price elasticity[J].Automation of Electric Power Systems,2003,27(24):10-13(in Chinese).
[19]葛炬,张粒子.可中断负荷参与的备用市场帕累托优化模型[J].电力系统自动化,2006,30(9):34-37.Ge Ju,Zhang Lizi.Pareto optimality model of reserve market including interruptible load as participants[J].Automation of Electric Power Systems,2006,30(9):34-37(in Chinese).
[20]盛四清,范林涛,李兴,等.基于帕累托最优的配电网多目标规划[J].电力系统自动化,2014,38(15):51-57.Sheng Siqing,Fan Lintao,Li Xing,et al.Multi-objective planning of distribution network based on pareto optimality[J]Automation of Electric Power Systems,2014,38(15):51-57(in Chinese).
[21]刘乐.自动发电控制中频率偏差系数研究[D].大连:大连理工大学,2008.
[22]张新松,袁越,曹阳.考虑损耗成本的电池储能电站建模及优化调度[J].电网技术,2017,41(5):1541-1547.Zhang Xinsong,Yuan Yue,Cao Yang.Modeling and scheduling for battery energy storage station with consideration of wearing costs[J].Power System Technology,2017,41(5):1541-1547(in Chinese).
[23]彭春华,孙惠娟.基于非劣排序微分进化的多目标优化发电调[J].中国电机工程学报,2009,29(34):71-76.Peng Chunhua,Sun Huijuan.Multi-objective optimization power dispatch based on non-dominated sorting differential evolution[J].Proceedings of the CSEE,2009,29(34):71-76(in Chinese).
[24]王焱,汪震,黄民翔,等.基于OS-ELM和Bootstrap方法的超短期风电功率预测[J].电力系统自动化,2014,38(6):14-19.Wang Yan,Wang Zhen,Huang Minxiang,et al.Ultra-short-term wind power prediction based on OS-ELN and bootstrap method[J].Automation of Elevtric Power Systems,2014,38(6):14-19(in Chinese).
[25]王新,孟玲玲.基于EEMD-LSSVM的超短期负荷预测[J].电力系统保护与控制,2015,39(1):61-66.Wang Xin,Meng Lingling.Ultra-short-term load forecasting based on EEMD-LSSVM[J].Power System Protection and Control,2015,39(1):61-66(in Chinese).
[26]肖浩,裴玮,杨艳红,等.计及电池寿命和经济运行的微电网储能容量优化[J].高电压技术,2015,41(10):3256-3265.Xiao Hao,Pei Wei,Yang Yanhong,et al.Energy storage capacity optimization for microgrid considering battery life and economic operation[J].High Voltage Engineering,2015,41(10):3256-3265(in Chinese).
[27]黄亚唯,李欣然,黄际元,等.电池储能电源参与AGC的控制方式分析[J].电力系统及其自动化学报,2017,29(3):83-89.Huang Yawei,Li Xinran,Huang Jiyuan,et al.Analysis of ol methods for AGC with battery energy storage system[J].Proceedings of the CSU-EPSA,2017,29(3):83-89(in Chinese).
[28]Kundur P.Power system stability and control[M].New York:McGraw-Hill Professional,2005.
[29]李欣然,黄际元,陈远扬,等.大规模储能电源参与电网调频研究综述[J].电力系统保护与控制,2016,44(7):145-153.Li Xinran,Huang Jiyuan,Chen Yuanyang,et al.Review on large-scale involvement of energy storage in power grid fast frequency regulation[J].Power System Protection and Control,2016,44(7):145-153(in Chinese).
[2]高宗和,滕贤亮,涂力群.互联电网AGC分层控制与CPS控制策略[J].电力系统自动化,2004,28(1):78-81.Gao Zonghe,Teng Xianliang,Tu Liqun.Hierarchical AGC mode and CPS control strategy for interconnected power systems[J].Automation of Electric Power Systems,2004,28(1):78-81(in Chinese).
[3]谷俊和,刘建平,江浩.风电接入对系统频率影响及风电调频技术综述[J].现代电力,2015,32(1):46-51.Gu Junhe,Liu Jianping,Jiang Hao.Literature review on the influence of wind power on system frequency and frequency regulation technologies of wind power[J].Modern Electric Power,2015,32(1):46-51(in Chinese).
[4]陈大宇,张粒子,马历.储能参与的AGC市场出清优化建模新方法[J].电力系统自动化,2014,38(13):79-84.Chen Dayu,Zhang Lizi,Ma Li.A new optimization method for AGCmarket clearing considering energy storage systems[J].Automation of Electric Power Systems,2014,38(13):79-84(in Chinese).
[5]邓霞,孙威,肖海伟.储能电池参与一次调频的综合控制方法[J].高电压技术,2018,44(4):1157-1165.Deng Xia,Sun Wei,Xiao Haiwei.Integrated control strategy of battery energy storage system in primary frequency regulation[J].High Voltage Engineering,2018,44(4):1157-1165(in Chinese).
[6]牛阳,张峰,张辉,等.提升火电机组AGC性能的混合储能优化控制与容量规划[J].电力系统自动化,2016,40(10):38-45.Niu Yang,Zhang Feng,Zhang Hui,et al.Optimal contyral strategy and capacity planning of hybrid energy storage system for improving AGC performance of thermal power units[J].Automation of Electric Power Systems,2016,40(10):38-45(in Chinese).
[7]杨水丽,李建林,李蓓,等.电池储能系统参与电网调频的优势分析[J].电网与清洁能源,2013,29(2):43-47.Yang Shuili,Li Jianlin,Li Bei,et al.Advantages of battery energy storage system for frequency regulation[J].Power System and Clean Energy,2013,29(2):43-47(in Chinese).
[8]丁冬,刘宗歧,杨水丽,等.基于模糊控制的电池储能系统辅助AGC调频方法[J].电力系统保护与控制,2015,43(8):81-87.Ding Dong,Liu Zongqi,Yang Shuili,et al.Battery energy storage aid automatic generation control for load frequency control based on fuzzy control[J].Power System Protection and Control,2015,43(8):81-87(in Chinese).
[9]Dang J,Seuss J,Suneja L,et al.SoC feedback control for wind and ESS hybrid power system frequency regulation[J].IEEE Journal of Emerging and Selected Topics in Power Electronics,2014,2(1):79-86.
[10]Cheng Y,Tabrizi M,Sahni M,et al.Dynamic available AGC based approach for enhancing utility scale energy storage performance[J].IEEE Transactions on Smart Grid,2014,5(2):1070-1078.
[11]李欣然,邓涛,黄际元,等.储能电池参与电网快速调频的自适应控制策略[J].高电压技术,2017,43(7):2362-2369.Li Xinran,Deng Tao,Huang Jiyuan,et al.Battery energy storage system self-adaptation control strategy in fast frequency regulation[J].High Voltage Engineering,2017,43(7):2362-2369(in Chinese).
[12]李欣然,黄际元,陈远扬,等.基于灵敏度分析的储能电池参与二次调频控制策略[J].电工技术学报,2017,32(12):224-233.Li Xinran,Huang Jiyuan,Chen Yuanyang,et al.Battery energy storage control strategy in secondary frequency regulation considering its action moment and depth[J].Transactions of China Electrotechnical Society,2017,32(12):224-233(in Chinese).
[13]胡泽春,夏睿,吴林林,等.考虑储能参与调频的风储联合运行优化策略[J].电网技术,2016,40(8):2251-2257.Hu Zechun,Xia Rui,Wu Linlin,et al.Joint operation optimization of wind-storage union with energy storage participating frequency regulation[J].Power System Technology,2016,40(8):2251-2257(in Chinese).
[14]孙冰莹,刘宗歧,杨水丽,等.补偿度实时优化的储能-火电联合AGC策略[J].电网技术,2018,42(2):426-433.Sun Bingying,Liu Zongqi,Yang Shuili,et al.A real-time optimization method of compensation degree for storage coordinated with thermal power unit in AGC[J].Power System Technology,2018,42(2):426-433(in Chinese).
[15]李飞.储能系统辅助火电机组调频的建模及控制策略研究[D].北京:华北电力大学,2017.
[16]黄际元,李欣然,黄继军,等.不同类型储能电源参与电网调频的效果比较研究[J].电工电能新技术,2015(3):49-53.Huang Jiyuan,Li Xinran,Huang Jijun,et al.Comparison of application of different energy storages in power system frequency regulation[J].Advanced Technology of Electrical Engineering and Energy,2015(3):49-53(in Chinese).
[17]黄际元,李欣然,曹一家,等.面向电网调频应用的电池储能电源仿真模型[J].电力系统自动化,2015,39(18):20-24,74.Huang Jiyuan,Li Xinran,Cao Yijia,et al.Battery energy storage power supply simulation model for power grid frequency regulation[J],Automation of Electric Power Systems,2015,39(18):20-24,74(in Chinese).
[18]程瑜,张粒子,李渝.考虑需求价格弹性的销售电价帕累托优化折扣[J].电力系统自动化,2003,27(24):10-13.Cheng Yu,Zhang Lizi,Li Yu.Pareto optimization on electricity price discount considering demand price elasticity[J].Automation of Electric Power Systems,2003,27(24):10-13(in Chinese).
[19]葛炬,张粒子.可中断负荷参与的备用市场帕累托优化模型[J].电力系统自动化,2006,30(9):34-37.Ge Ju,Zhang Lizi.Pareto optimality model of reserve market including interruptible load as participants[J].Automation of Electric Power Systems,2006,30(9):34-37(in Chinese).
[20]盛四清,范林涛,李兴,等.基于帕累托最优的配电网多目标规划[J].电力系统自动化,2014,38(15):51-57.Sheng Siqing,Fan Lintao,Li Xing,et al.Multi-objective planning of distribution network based on pareto optimality[J]Automation of Electric Power Systems,2014,38(15):51-57(in Chinese).
[21]刘乐.自动发电控制中频率偏差系数研究[D].大连:大连理工大学,2008.
[22]张新松,袁越,曹阳.考虑损耗成本的电池储能电站建模及优化调度[J].电网技术,2017,41(5):1541-1547.Zhang Xinsong,Yuan Yue,Cao Yang.Modeling and scheduling for battery energy storage station with consideration of wearing costs[J].Power System Technology,2017,41(5):1541-1547(in Chinese).
[23]彭春华,孙惠娟.基于非劣排序微分进化的多目标优化发电调[J].中国电机工程学报,2009,29(34):71-76.Peng Chunhua,Sun Huijuan.Multi-objective optimization power dispatch based on non-dominated sorting differential evolution[J].Proceedings of the CSEE,2009,29(34):71-76(in Chinese).
[24]王焱,汪震,黄民翔,等.基于OS-ELM和Bootstrap方法的超短期风电功率预测[J].电力系统自动化,2014,38(6):14-19.Wang Yan,Wang Zhen,Huang Minxiang,et al.Ultra-short-term wind power prediction based on OS-ELN and bootstrap method[J].Automation of Elevtric Power Systems,2014,38(6):14-19(in Chinese).
[25]王新,孟玲玲.基于EEMD-LSSVM的超短期负荷预测[J].电力系统保护与控制,2015,39(1):61-66.Wang Xin,Meng Lingling.Ultra-short-term load forecasting based on EEMD-LSSVM[J].Power System Protection and Control,2015,39(1):61-66(in Chinese).
[26]肖浩,裴玮,杨艳红,等.计及电池寿命和经济运行的微电网储能容量优化[J].高电压技术,2015,41(10):3256-3265.Xiao Hao,Pei Wei,Yang Yanhong,et al.Energy storage capacity optimization for microgrid considering battery life and economic operation[J].High Voltage Engineering,2015,41(10):3256-3265(in Chinese).
[27]黄亚唯,李欣然,黄际元,等.电池储能电源参与AGC的控制方式分析[J].电力系统及其自动化学报,2017,29(3):83-89.Huang Yawei,Li Xinran,Huang Jiyuan,et al.Analysis of ol methods for AGC with battery energy storage system[J].Proceedings of the CSU-EPSA,2017,29(3):83-89(in Chinese).
[28]Kundur P.Power system stability and control[M].New York:McGraw-Hill Professional,2005.
[29]李欣然,黄际元,陈远扬,等.大规模储能电源参与电网调频研究综述[J].电力系统保护与控制,2016,44(7):145-153.Li Xinran,Huang Jiyuan,Chen Yuanyang,et al.Review on large-scale involvement of energy storage in power grid fast frequency regulation[J].Power System Protection and Control,2016,44(7):145-153(in Chinese).