计及预测精度及拓扑结构的光伏电站储能经济配置
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摘要
光伏电站并网离不开储能系统的支持,为了提高储能配置的精度并降低储能系统的成本,考虑到现有研究的不足,分析了光伏电站出力预测算法误差、储能拓扑结构对储能配置的影响。提出了一种储能的快速配置方法,分析了预测算法误差对储能定容的影响,完善了储能的收益模型;引入了一种双元互补的储能拓扑结构,并分析了该拓扑结构对电池特性以及储能成本模型的影响;建立了以最大经济效益为目标的总投资收益模型,并基于某光伏电站的实际数据确定其最优配置方案。算例结果表明,预测算法误差会引起储能容量及功率增大,从而导致储能系统的成本增大;引入所提储能拓扑结构能有效地提高电池的使用寿命,降低储能系统的成本。
Energy storage system can well support PV(PhotoVoltaic) power station connecting to power grid. In order to improve the configuration accuracy of energy storage and reduce the cost of energy storage system,conside-ring the shortcomings of existing research,the influences of the error of PV power station output power prediction algorithm and the topological structure of energy storage on energy storage configuration are analyzed. A fast energy storage configuration method is proposed. The influence of prediction algorithm's error on the capacity determination of energy storage is analyzed and the revenue model of energy storage is improved. A topological structure of energy storage system with dual complementary units is introduced,and its influences on the battery characteristics and the cost model of energy storage are analyzed. The investment income model is established with the maximum economic benefit as its objective. The optimal energy storage configuration scheme of a PV power station is determined based on the actual data. The example results show that,the error of prediction algorithm will lead to the increase of energy storage capacity and power,which will lead to the increase of energy storage system cost. The proposed topological structure of energy storage can effectively improve the life of battery and reduce the cost of the energy storage system.
Energy storage system can well support PV(PhotoVoltaic) power station connecting to power grid. In order to improve the configuration accuracy of energy storage and reduce the cost of energy storage system,conside-ring the shortcomings of existing research,the influences of the error of PV power station output power prediction algorithm and the topological structure of energy storage on energy storage configuration are analyzed. A fast energy storage configuration method is proposed. The influence of prediction algorithm's error on the capacity determination of energy storage is analyzed and the revenue model of energy storage is improved. A topological structure of energy storage system with dual complementary units is introduced,and its influences on the battery characteristics and the cost model of energy storage are analyzed. The investment income model is established with the maximum economic benefit as its objective. The optimal energy storage configuration scheme of a PV power station is determined based on the actual data. The example results show that,the error of prediction algorithm will lead to the increase of energy storage capacity and power,which will lead to the increase of energy storage system cost. The proposed topological structure of energy storage can effectively improve the life of battery and reduce the cost of the energy storage system.
引文
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[15]谭兴国,王辉,张黎,等.微电网复合储能多目标优化配置方法及评价指标[J].电力系统自动化,2014,38(8):7-14.TAN Xingguo,WANG Hui,ZHANG Li,et al.Multi-objective optimization of hybrid energy storage and assessment indices in microgrid[J].Automation of Electric Power Systems,2014,38(8):7-14.
[16]LEE T Y,CHEN N M.Optimal capacity of the battery energy storage system in a power system[J].IEEE Transactions on Energy Conversion,1993,8(4):667-673.
[17]JENKINS D P,FLETCHER J,KANE D.Lifetime prediction and sizing of lead-acid batteries for microgeneration storage applications[J].IET Renewable Power Generation,2008,2(3):191-200.
[18]丁明,徐宁舟.基于马尔可夫链的光伏发电系统输出功率短期预测方法[J].电网技术,2011,35(1):152-157.DING Ming,XU Ningzhou.A method to forecast short-term output power of photovoltaic generation system based on Markov chain[J].Power System Technology,2011,35(1):152-157.
[19]ZIADI Z,OSHIRO M,SENJYU T,et al.Optimal voltage control using inverters interfaced with PV systems considering forecast error in a distribution system[J].IEEE Transactions on Sustainable Energy,2014,5(2):682-690.
[20]林少伯,韩民晓,赵国鹏,等.基于随机预测误差的分布式光伏配网储能系统容量配置方法[J].中国电机工程学报,2013,33(4):25-33.LIN Shaobo,HAN Minxiao,ZHAO Guopeng,et al.Capacity allocation of energy storage in distributed photovoltaic power system based on stochastic prediction error[J].Proceedings of the CSEE,2013,33(4):25-33.
[21]陈昌松,段善旭,蔡涛,等.基于模糊识别的光伏发电短期预测系统[J].电工技术学报,2011,26(7):83-89.CHEN Changsong,DUAN Shanxu,CAI Tao,et al.Short-term photovoltaic generation forecasting system based on fuzzy recognition[J].Transactions of China Electrotechnical Society,2011,26(7):83-89.
[22]BAHRAMIRAD S,REDER W,KHODAEI A.Reliability-constrained optimal sizing of energy storage system in a microgrid[J].IEEETransactions on Smart Grid,2012,3(4):2056-2062.
[23]European Commission Joint Research Centre.PVGIS[EB/OL].[2018-04-03].http:∥re.jrc.ec.europa.eu/pvg_tools/en/tools.html.
[2]周任军,黄灵资,王靓,等.基于风险和条件风险方法的光伏电站并网极限容量计算[J].电力自动化设备,2012,32(6):1-5.ZHOU Renjun,HUANG Lingzi,WANG Liang,et al.Capacity limit calculation based on risk and conditional risk method for grid-connected photovoltaic power station[J].Electric Power Automation Equipment,2012,32(6):1-5.
[3]杨清,袁越,王敏,等.独立型水光储微电网系统容量优化配置[J].电力自动化设备,2015,35(10):37-44.YANG Qing,YUAN Yue,WANG Min,et al.Optimal capacity configuration of standalone hydro-photovoltaic-storage microgrid[J].Electric Power Automation Equipment,2015,35(10):37-44.
[4]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.
[5]丁明,王伟胜,王秀丽,等.大规模光伏发电对电力系统影响综述[J].中国电机工程学报,2014,34(1):1-14.DING Ming,WANG Weisheng,WANG Xiuli,et al.A review on the effect of large-scale PV generation on power systems[J].Proceedings of the CSEE,2014,34(1):1-14.
[6]CHENG Feng,WILLARD S,HAWKINS J,et al.Applying battery energy storage to enhance the benefits of photovoltaics[C]∥2012IEEE Energytech.Cleveland,OH,USA:IEEE,2012:1-5.
[7]王成山,于波,肖峻,等.平滑可再生能源发电系统输出波动的储能系统容量优化方法[J].中国电机工程学报,2012,32(16):1-8.WANG Chengshan,YU Bo,XIAO Jun,et al.Sizing of energy storage systems for output smoothing of renewable energy systems[J].Proceedings of the CSEE,2012,32(16):1-8.
[8]张野,郭力,贾宏杰,等.基于平滑控制的混合储能系统能量管理方法[J].电力系统自动化,2012,36(16):36-41.ZHANG Ye,GUO Li,JIA Hongjie,et al.An energy management method of hybrid energy storage system based on smoothing control[J].Automation of Electric Power Systems,2012,36(16):36-41.
[9]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 real-time smoothing control strategy with SOC adjustment function of storage systems[J].Proceedings of the CSEE,2013,33(1):22-29.
[10]ESMAILI A,NOVAKOVIC B,NASIRI A,et al.A hybrid system of Li-ion capacitors and flow battery for dynamic wind energy support[J].IEEE Transactions on Industry Applications,2013,49(4):1649-1657.
[11]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.
[12]CHEN S X,GOOI H B,WANG M Q.Sizing of energy storage for microgrids[J].IEEE Transactions on Smart Grid,2012,3(1):142-151.
[13]田培根,肖曦,丁若星,等.自治型微电网群多元复合储能系统容量配置方法[J].电力系统自动化,2013,37(1):168-173.TIAN Peigen,XIAO Xi,DING Ruoxing,et al.A capacity configuring method of composite energy storage system in autonomous multi-microgrid[J].Automation of Electric Power Systems,2013,37(1):168-173.
[14]何俊,邓长虹,徐秋实,等.基于等可信容量的风光储电源优化配置方法[J].电网技术,2013,37(12):3317-3324.HE Jun,DENG Changhong,XU Qiushi,et al.Optimal configuration of distributed generation system containing wind PV battery power sources based on equivalent credible capacity theory[J].Power System Technology,2013,37(12):3317-3324.
[15]谭兴国,王辉,张黎,等.微电网复合储能多目标优化配置方法及评价指标[J].电力系统自动化,2014,38(8):7-14.TAN Xingguo,WANG Hui,ZHANG Li,et al.Multi-objective optimization of hybrid energy storage and assessment indices in microgrid[J].Automation of Electric Power Systems,2014,38(8):7-14.
[16]LEE T Y,CHEN N M.Optimal capacity of the battery energy storage system in a power system[J].IEEE Transactions on Energy Conversion,1993,8(4):667-673.
[17]JENKINS D P,FLETCHER J,KANE D.Lifetime prediction and sizing of lead-acid batteries for microgeneration storage applications[J].IET Renewable Power Generation,2008,2(3):191-200.
[18]丁明,徐宁舟.基于马尔可夫链的光伏发电系统输出功率短期预测方法[J].电网技术,2011,35(1):152-157.DING Ming,XU Ningzhou.A method to forecast short-term output power of photovoltaic generation system based on Markov chain[J].Power System Technology,2011,35(1):152-157.
[19]ZIADI Z,OSHIRO M,SENJYU T,et al.Optimal voltage control using inverters interfaced with PV systems considering forecast error in a distribution system[J].IEEE Transactions on Sustainable Energy,2014,5(2):682-690.
[20]林少伯,韩民晓,赵国鹏,等.基于随机预测误差的分布式光伏配网储能系统容量配置方法[J].中国电机工程学报,2013,33(4):25-33.LIN Shaobo,HAN Minxiao,ZHAO Guopeng,et al.Capacity allocation of energy storage in distributed photovoltaic power system based on stochastic prediction error[J].Proceedings of the CSEE,2013,33(4):25-33.
[21]陈昌松,段善旭,蔡涛,等.基于模糊识别的光伏发电短期预测系统[J].电工技术学报,2011,26(7):83-89.CHEN Changsong,DUAN Shanxu,CAI Tao,et al.Short-term photovoltaic generation forecasting system based on fuzzy recognition[J].Transactions of China Electrotechnical Society,2011,26(7):83-89.
[22]BAHRAMIRAD S,REDER W,KHODAEI A.Reliability-constrained optimal sizing of energy storage system in a microgrid[J].IEEETransactions on Smart Grid,2012,3(4):2056-2062.
[23]European Commission Joint Research Centre.PVGIS[EB/OL].[2018-04-03].http:∥re.jrc.ec.europa.eu/pvg_tools/en/tools.html.