以净效益最大为目标的储能电池参与二次调频的容量配置方法
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摘要
针对储能电源参与电网辅助调频问题,提出一种以净效益最大为目标的储能电池参与二次调频的容量配置方法。综合考虑实时电量、备用功率和环境效益,构建储能电池全寿命周期的成本-效益计算模型;进而建立以净效益最大为目标,以容量及功率为决策变量,综合考虑实时出力、调频需求约束和荷电状态(SOC)约束的储能电池优化配置模型;基于经验模态分解(EMD)原理,设计一种考虑常规机组爬坡率限制的储能参与二次调频的初始功率指令分配方法;并给出了利用遗传算法辅助求解该优化模型的容量配置方法流程。仿真结果表明,所提出的容量配置方法不仅可以得到能够较好地协调经济效益和调频效果的容量配置方案,同时可得到储能出力功率,该功率可作为储能电池的运行调度参考方案,提高了配置方法的工程实用性。
Energy storage power has brought some problems involved in the auxiliary frequency regulation, aiming at the problems, a capacity allocation method of BESS in secondary frequency regulation with the goal of maximum net benefit is proposed. Considering the real-time electricity, reserve power and environmental benefit, the cost-benefit calculation model of full life cycle of BESS is constructed. Then taking the maximum net benefit as the goal, the capacity and the power as the decision variables, and considering the real-time output, the frequency regulation demand constraint and the SOC boundary, the optimization configuration model of BESS is established; Based on the principle of empirical mode decomposition(EMD) and considering the limitation of ramp rate of conventional units, this paper designs an initial power instruction allocation method for BESS in secondary frequency regulation; Also this paper gives the flow chart of capacity allocation method assisted by genetic algorithm. The simulation results show that the proposed capacity allocation method can not only obtain the capacity allocation scheme that can coordinate the economic benefit and frequency regulation effect, but also obtain the energy storage output power. The output power can be used as a reference scheme of BESS, which improves the engineering practicability of the configuration method.
Energy storage power has brought some problems involved in the auxiliary frequency regulation, aiming at the problems, a capacity allocation method of BESS in secondary frequency regulation with the goal of maximum net benefit is proposed. Considering the real-time electricity, reserve power and environmental benefit, the cost-benefit calculation model of full life cycle of BESS is constructed. Then taking the maximum net benefit as the goal, the capacity and the power as the decision variables, and considering the real-time output, the frequency regulation demand constraint and the SOC boundary, the optimization configuration model of BESS is established; Based on the principle of empirical mode decomposition(EMD) and considering the limitation of ramp rate of conventional units, this paper designs an initial power instruction allocation method for BESS in secondary frequency regulation; Also this paper gives the flow chart of capacity allocation method assisted by genetic algorithm. The simulation results show that the proposed capacity allocation method can not only obtain the capacity allocation scheme that can coordinate the economic benefit and frequency regulation effect, but also obtain the energy storage output power. The output power can be used as a reference scheme of BESS, which improves the engineering practicability of the configuration method.
引文
[1]李建林,马会萌,惠东.储能技术融合分布式可再生能源的现状及发展趋势[J].电工技术学报,2016,31(14):1-10.Li Jianlin,Ma Huimeng,Hui Dong.Present development condition and trends of energy storage technology in the integration of distributed renewable energy[J].Transactions of China Electrotechnical Society,2016,31(14):1-10.
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[7]李建林,郭斌琪,牛萌,等.风光储系统储能容量优化配置策略[J].电工技术学报,2018,33(6):1189-1196.Li Jianlin,Guo Binqi,Niu Meng,et al.Optimal configuration strategy of energy storage capacity in wind/PV/Storage hybrid system[J].Transactions of China Electrotechnical Society,2018,33(6):1189-1196.
[8]赵晶晶,徐传琳,吕雪,等.微电网一次调频备用容量与储能优化配置方法[J].中国电机工程学报,2017,37(15):4324-4332,4572.Zhao Jingjing,Xu Chuanlin,LüXue.Optimization of micro-grid primary frequency regulation reserve capacity and energy storage system[J].Proceedings of the CSEE,2017,37(15):4324-4332,4572.
[9]黄际元,李欣然,常敏,等.考虑储能电池参与一次调频技术经济模型的容量配置方法[J].电工技术学报,2017,32(21):112-121.Huang Jiyuan,Li Xinran,Chang Min,et al.Capacity allocation of BESS in primary frequency regulation considering its technical-economic model[J].Transactions of China Electrotechnical Society,2017,32(21):112-121.
[10]Leou R C.An economic analysis model for the energy storage system applied to a distribution substation[J].Electrical Power and Energy Systems,2012,34:132-137.
[11]马美婷,袁铁江,陈广宇,等.储能参与风电辅助服务综合经济效益分析[J].电网技术,2016,40(11):3362-3367.Ma Meiting,Yuan Tiejiang,Chen Guangyu,et al.Analysis on economic benefit of energy storage in auxiliary service of wind power[J].Power System Technology,2016,40(11):3362-3367.
[12]?wierczyński M,Stroe D,Stan A,et al.Lifetime and economic analyses of lithium-ion batteries for balancing wind power forecast error[J].International Journal of Energy Research,2015,39(6):760-770.
[13]刘秋华,吴玲.电力技术经济分析[M].北京:中国电力出版社,2012.
[14]Fares R L,Meyers J P,Webber M E.A dynamic model-based estimate of the value of a vanadium redox flow battery for frequency regulation in Texas[J].Applied Energy,2014,113:189-198.
[15]王菲菲.火力发电企业环境成本核算方法研究[D].济南:山东财经大学,2015.
[16]王丽梅,孙璐,初升.基于经验模态分解算法的永磁直线同步电机迭代学习控制[J].电工技术学报,2017,32(6):164-171.Wang Limei,Sun Lu,Chu Sheng.Iterative learning control of permanent magnet linear synchronous motor based on empirical mode decomposition algorithm[J].Transactions of China Electrotechnical Society,2017,32(6):164-171.
[17]徐青山,娄藕蝶,郑爱霞,等.基于近邻传播聚类和遗传优化的非侵入式负荷分解方法[J].电工技术学报,2018,33(16):3868-3878.Xu Qingshan,Lou Oudie,Zheng Aixia,et al.A nonintrusive load decomposition method based on affinity propagation and genetic algorithm optimization[J].Transactions of China Electrotechnical Society,2018,33(16):3868-3878.
[18]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.
[19]北极星储能网.投资单价下降至1.12元/Wh储能电池类项目的全投资收益率或可达9%以上[EB/OL].http://shupeidian.bjx.com.cn/news/20180323/887242.shtml,2018-03-23.
[20]华北区域并网发电厂辅助服务管理实施细则(修订版)[S].北京:原华北电监局,2012.
[2]胡泽春,罗浩成.大规模可再生能源接入背景下自动发电控制研究现状与展望[J].电力系统自动化,2018,42(8):2-15.Hu Zechun,Luo Haocheng.Research status and prospect of automatic generation control with integration of large-scale renewable energey[J].Automation of Electric Power Systems,2018,42(8):2-15.
[3]孙冰莹,杨水丽,刘宗歧,等.国内外兆瓦级储能调频示范应用现状分析与启示[J].电力系统自动化,2017,41(11):8-16,38.Sun Bingying,Yang Shuili,Liu Zongqi,et al.Analysis on present application of megawatt-scale energy storage in frequency regulation and its enlightenment[J].Automation of Electric Power Systems,2017,41(11):8-16,38.
[4]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):38-45,83.Niu Yang,Zhang Feng,Zhang Hui,et al.Optimal control strategy and capacity planning of hybrid energy storge system for improving AGC performace of thermal power units[J].Automation of Electric Power Systems,2016,40(10):38-45,83.
[5]苏小林,李丹丹,阎晓霞,等.储能技术在电力系统中的应用分析[J].电力建设,2016,37(8):24-32.Su Xiaolin,Li Dandan,Yan Xiaoxia,et al.Application analysis of energy storage technology in power system[J].Electric Power Construction,2016,37(8):24-32.
[6]沈子奇,裴玮,邓卫,等.考虑电池寿命和运行控制策略影响的风电场储能容量优化配置[J].高电压技术,2015,41(7):2236-2244.Shen Ziqi,Pei Wei,Deng Wei,et al.Storage capacity optimization for wind farm considering the impact of battery lifetime and control strategy[J].High Voltage Engineering,2015,41(7):2236-2244.
[7]李建林,郭斌琪,牛萌,等.风光储系统储能容量优化配置策略[J].电工技术学报,2018,33(6):1189-1196.Li Jianlin,Guo Binqi,Niu Meng,et al.Optimal configuration strategy of energy storage capacity in wind/PV/Storage hybrid system[J].Transactions of China Electrotechnical Society,2018,33(6):1189-1196.
[8]赵晶晶,徐传琳,吕雪,等.微电网一次调频备用容量与储能优化配置方法[J].中国电机工程学报,2017,37(15):4324-4332,4572.Zhao Jingjing,Xu Chuanlin,LüXue.Optimization of micro-grid primary frequency regulation reserve capacity and energy storage system[J].Proceedings of the CSEE,2017,37(15):4324-4332,4572.
[9]黄际元,李欣然,常敏,等.考虑储能电池参与一次调频技术经济模型的容量配置方法[J].电工技术学报,2017,32(21):112-121.Huang Jiyuan,Li Xinran,Chang Min,et al.Capacity allocation of BESS in primary frequency regulation considering its technical-economic model[J].Transactions of China Electrotechnical Society,2017,32(21):112-121.
[10]Leou R C.An economic analysis model for the energy storage system applied to a distribution substation[J].Electrical Power and Energy Systems,2012,34:132-137.
[11]马美婷,袁铁江,陈广宇,等.储能参与风电辅助服务综合经济效益分析[J].电网技术,2016,40(11):3362-3367.Ma Meiting,Yuan Tiejiang,Chen Guangyu,et al.Analysis on economic benefit of energy storage in auxiliary service of wind power[J].Power System Technology,2016,40(11):3362-3367.
[12]?wierczyński M,Stroe D,Stan A,et al.Lifetime and economic analyses of lithium-ion batteries for balancing wind power forecast error[J].International Journal of Energy Research,2015,39(6):760-770.
[13]刘秋华,吴玲.电力技术经济分析[M].北京:中国电力出版社,2012.
[14]Fares R L,Meyers J P,Webber M E.A dynamic model-based estimate of the value of a vanadium redox flow battery for frequency regulation in Texas[J].Applied Energy,2014,113:189-198.
[15]王菲菲.火力发电企业环境成本核算方法研究[D].济南:山东财经大学,2015.
[16]王丽梅,孙璐,初升.基于经验模态分解算法的永磁直线同步电机迭代学习控制[J].电工技术学报,2017,32(6):164-171.Wang Limei,Sun Lu,Chu Sheng.Iterative learning control of permanent magnet linear synchronous motor based on empirical mode decomposition algorithm[J].Transactions of China Electrotechnical Society,2017,32(6):164-171.
[17]徐青山,娄藕蝶,郑爱霞,等.基于近邻传播聚类和遗传优化的非侵入式负荷分解方法[J].电工技术学报,2018,33(16):3868-3878.Xu Qingshan,Lou Oudie,Zheng Aixia,et al.A nonintrusive load decomposition method based on affinity propagation and genetic algorithm optimization[J].Transactions of China Electrotechnical Society,2018,33(16):3868-3878.
[18]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.
[19]北极星储能网.投资单价下降至1.12元/Wh储能电池类项目的全投资收益率或可达9%以上[EB/OL].http://shupeidian.bjx.com.cn/news/20180323/887242.shtml,2018-03-23.
[20]华北区域并网发电厂辅助服务管理实施细则(修订版)[S].北京:原华北电监局,2012.
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