风电功率波动平抑下的MPC双储能控制策略研究
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摘要
风电的规模化接入对电力系统造成了较大影响,应用储能进行风电功率波动的平抑可以提高其并网可信度。首先,应用模型预测控制算法平抑风电波动以达到其并网要求;然后,针对单组储能功率频繁充放电的情况,应用两组不同充放电状态的储能平抑风电波动,当一组储能处于充电时,另一组放电,其中任意一组达到SOC约束时,两组储能同时切换充放电状态;最后,从储能的经济性成本方面进行分析,通过与单组储能的对比证明了其优越性。
Large-scale grid-connected wind power brings a greater impact on the power system. The energy storage is used to mitigate wind power fluctuation, so the grid reliability is improved drastically. Firstly, model predictive control algorithm(MPC) is used to mitigate wind power fluctuation within the requirements of the grid. Daul energy storage with different states of charge and discharge are applied to overcome frequent charging and discharging of single energy storage. When one reaches SOC constraints, both of states of charge and discharge are changed. Finally, the superiority of this method is proved by comparing with single energy storage from the economic cost analysis.
Large-scale grid-connected wind power brings a greater impact on the power system. The energy storage is used to mitigate wind power fluctuation, so the grid reliability is improved drastically. Firstly, model predictive control algorithm(MPC) is used to mitigate wind power fluctuation within the requirements of the grid. Daul energy storage with different states of charge and discharge are applied to overcome frequent charging and discharging of single energy storage. When one reaches SOC constraints, both of states of charge and discharge are changed. Finally, the superiority of this method is proved by comparing with single energy storage from the economic cost analysis.
引文
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[18]张新松,顾菊平,袁越,等.基于电池储能系统的风功率波动平抑策略[J].中国电机工程学报,2014,34(28):4752-4760.Zhang Xinsong,Gu Juping,Yuan Yue,et al.Strategy of smoothing wind power fluctuation based on battery energy storage system[J].Proceedings of the CSEE,2014,34(28):4752-4760.
[19]Bindner H,Cronin T,Lundsager P,et al.Lifetime modelling of lead acid batteries[R].Roskilde:Ris?National Laboratory,2005.
[2]Khalid M,Savkin A V.A model predictive control approach to the problem of wind power smoothing with controlled battery storage[J].Renewable Energy,2010,35(7):1520-1526.
[3]Brunety.储能技术[M].唐西胜,译.北京:机械工业出版社,2013:137-183.
[4]Lu Mingshun,Chang C L,Lee W J,et al.Combining the wind power generation system with energy storage equipment[J].IEEE Transactions on Industry Applications,2009,45(6):2109-2115.
[5]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.
[6]颜宁,厉伟,邢作霞,等.复合储能在主动配电网中的容量配置[J].电工技术学报,2017,32(19):180-186.Yan Ning,Li Wei,Xing Zuoxia,et al.Capacity allocation method in active distribution network based on hybrid energy storage[J].Transactions of China Electrotechnical Society,2017,32(19):180-186.
[7]易林,娄素华,吴耀武,等.基于变寿命模型的改善风电可调度性的电池储能容量优化[J].电工技术学报,2015,30(15):54-59.Yi Lin,Lou Suhua,Wu Yaowu,et al.Optimal battery capacity based on lifetime predication for improving the schedulability of the wind power[J].Transactions of China Electrotechnical Society,2015,30(15):54-59.
[8]雷珽,欧阳曾恺,李征,等.平抑风能波动的储能电池SOC与滤波协调控制策略[J].电力自动化设备,2015,35(7):126-131.Lei Ting,Ouyang Zengkai,Li Zheng,et al.Coordinated control of battery SOC maintaining and filtering for wind power fluctuation smoothing[J].Electric Power Automation Equipment,2015,35(7):126-131.
[9]王晓东,张磊,姚兴佳,等.基于模糊自适应卡尔曼滤波的风电场储能系统功率控制[J].电网技术,2014,38(6):1465-1470.Wang Xiaodong,Zhang Lei,Yao Xingjia,et al.Afuzzy adaptive Kalman filter based power control strategy of energy storage system for wind farm[J].Power System Technology,2014,38(6):1465-1470.
[10]刘世林,文劲宇,高文根,等.基于飞轮储能的并网风电功率综合调控策略[J].电力自动化设备.2015,35(12):34-39.Liu Shilin,Wen Jinyu,Gao Wengen,et al.FESS-based comprehensive control of grid-connecting wind power[J].Electric Power Automation Equipment,2015,35(12):34-39.
[11]刘颖明,徐中民,王晓东.基于双模糊算法的风电机组储能系统优化控制[J].高电压技术,2015,41(7):2180-2185.Liu Yingming,Xu Zhongmin,Wang Xiaodong.Optimal control of wind turbine energy storage system based on double fuzzy strategy[J].High Voltage Engineering,2015,41(7):2180-2185.
[12]Zhang Kun,Mao Chengxiong,Lu Jiming,et al.Optimal control of state-of-charge of superconducting magnetic energy storage for wind power system[J].IET Renewable Power Generation,2014,8(1):58-66.
[13]Jiang Quanyuan,Wang Haijiao.Two-time-scale coordination control for a battery energy storage system to mitigate wind power fluctuations[J].IEEETransactions on Energy Conversion,2013,28(1):52-61.
[14]娄素华,吴耀武,崔艳昭,等.电池储能平抑短期风电功率波动运行策略[J].电力系统自动化,2014,38(2):17-22.Lou Suhua,Wu Yaowu,Cui Yanzhao,et al.Operation strategy of battery energy storage system for smoothing short-term wind power fluctuation[J].Automation of Electric Power Systems,2014,38(2):17-22.
[15]丁明,吴建锋,朱承治,等.具备荷电状态调节功能的储能系统实时平滑控制策略[J].中国电机工程学报,2013,33(1):22-29.Ding Ming,Wu Jianfeng,Zhu Chengzhi,et al.A realtime smoothing control strategy with SOC adjustment function of storage systems[J].Proceedings of the CSEE,2013,33(1):22-29.
[16]Li Xiangjun,Hui Dong,Lai Xiaokang.Battery energy storage station(BESS)-based smoothing control of photovoltaic(PV)and wind power generation fluctuations[J].IEEE Transactions on Sustainable Energy,2013,4(2):464-473.
[17]杨裕生,程杰,曹高萍.规模储能装置经济效益的判据[J].电池,2011,41(1):19-21.Yang Yusheng,Cheng Jie,Cao Gaoping.A gauge for direct economic benefits of energy storage devices[J].Battery Bimonthly,2011,41(1):19-21.
[18]张新松,顾菊平,袁越,等.基于电池储能系统的风功率波动平抑策略[J].中国电机工程学报,2014,34(28):4752-4760.Zhang Xinsong,Gu Juping,Yuan Yue,et al.Strategy of smoothing wind power fluctuation based on battery energy storage system[J].Proceedings of the CSEE,2014,34(28):4752-4760.
[19]Bindner H,Cronin T,Lundsager P,et al.Lifetime modelling of lead acid batteries[R].Roskilde:Ris?National Laboratory,2005.