考虑电池储能寿命模型的发电计划优化
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摘要
电池储能的寿命将受到其运行方式的影响。对规模化电池储能接入电力系统的发电计划优化问题进行了研究,重点考虑了电池储能的寿命模型及其在不同运行方式下的折损与经济性。文中依据电池寿命的影响机理和半经验模型,针对全系统优化的简化建模的要求,归纳出了基于交换功率和基于放电深度两类电池寿命模型,其中基于放电深度的模型可进一步区分为考虑日循环次数和等效循环次数两种计算方式。接着,将电池寿命模型分别内嵌到电力系统的机组组合问题中进行一体化的优化求解,构建了一个混合整数线性规划的数学模型。最后,通过算例分析比较了不同模型的适用性与建模效果。
The service life of battery storage is influenced by its short-term operation. With special concern about battery degradation and economic values in different operation manners, optimal generation scheduling of power system with large-scale battery storage is studied considering battery life model. Based on battery degradation mechanism and the semi-empirical model and requirement of simplified modelling on system optimization, two types of battery life models based on power exchange and depth of discharge(DOD) are built, respectively. The DOD-based model can be further simplified by the number of cycles per day or the equivalent full cycle in a day. Battery life models are integrated into the unit commitment problem of the power system, then a mixed integer linear programming model is constructed to solve the optimization. Finally, the feasibility and modelling effect of different models are compared by case studies.
The service life of battery storage is influenced by its short-term operation. With special concern about battery degradation and economic values in different operation manners, optimal generation scheduling of power system with large-scale battery storage is studied considering battery life model. Based on battery degradation mechanism and the semi-empirical model and requirement of simplified modelling on system optimization, two types of battery life models based on power exchange and depth of discharge(DOD) are built, respectively. The DOD-based model can be further simplified by the number of cycles per day or the equivalent full cycle in a day. Battery life models are integrated into the unit commitment problem of the power system, then a mixed integer linear programming model is constructed to solve the optimization. Finally, the feasibility and modelling effect of different models are compared by case studies.
引文
[1] 熊雄,叶林,杨仁刚.电力需求侧规模储能容量优化和经济性分析[J].电力系统自动化,2015,39(17):42-48.XIONG Xiong, YE Lin, YANG Rengang. Optimal allocation and economic benefits analysis of energy storage system on power demand side[J]. Automation of Electric Power Systems, 2015, 39(17): 42-48.
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[3] 谢东亮,薛峰,宋晓芳.基于最优价值网络的储能系统调度优化及仿真[J].电力系统自动化,2016,40(24):42-48.XIE Dongliang, XUE Feng, SONG Xiaofang. Optimization and simulation for dispatch of energy storage systems based on optimal value networks[J]. Automation of Electric Power Systems, 2016, 40(24): 42-48.
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[9] 邱海峰,赵波,林达,等.计及储能损耗和换流成本的交直流混合微网区域协调调度[J].电力系统自动化,2017,41(23):29-37.DOI:10.7500/AEPS20161213012.QIU Haifeng, ZHAO Bo, LIN Da, et al. Regional coordinated dispatch in AC/DC hybrid microgrids considering energy storage loss and converter cost[J]. Automation of Electric Power Systems, 2017, 41(23): 29-37. DOI: 10.7500/AEPS20161213012.
[10] XU B, OUDALOV A, ULBIG A, et al. Modeling of lithium-ion battery degradation for cell life assessment[J]. IEEE Transactions on Smart Grid, 2018, 9(2): 1131-1140.
[11] WANG J, PUREWAL J, LIU P, et al. Degradation of lithium ion batteries employing graphite negatives and nickel-cobalt-manganese oxide+spinel manganese oxide positives: Part 1 aging mechanisms and life estimation[J]. Journal of Power Sources, 2014, 269(12): 937-948.
[12] 李逢兵,谢开贵,张雪松,等.基于寿命量化的混合储能系统协调控制参数优化[J].电力系统自动化,2014,38(1):1-5. LI Fengbing, XIE Kaigui, ZHANG Xuesong, et al. Optimization of coordinated control parameters for hybrid energy storage system based on life quantization[J]. Automation of Electric Power Systems, 2014, 38(1): 1-5.
[13] 肖浩,裴玮,孔力.基于模型预测控制的微电网多时间尺度协调优化调度[J].电力系统自动化,2016,40(18):7-14.XIAO Hao, PEI Wei, KONG Li. Multi-time scale coordinated optimal dispatch of microgrid based on model predictive control[J]. Automation of Electric Power Systems, 2016, 40(18): 7-14.
[14] SHI Y, XU B, WANG D, et al. Using battery storage for peak shaving and frequency regulation: joint optimization for superlinear gains[J]. IEEE Transactions on Power Systems, 2018, 33(3): 2882-2894.
[15] SU W, WANG J, ROH J. Stochastic energy scheduling in microgrids with intermittent renewable energy resources[J]. IEEE Transactions on Smart Grid, 2014, 5(4): 1876-1883.
[16] AL-SAADI M K, LUK P C K, FEI W. Impact of unit commitment on the optimal operation of hybrid microgrids[C]//2016 UKACC 11th International Conference on Control, August 31-September 2, 2016, Belfast, UK: 1-6.
[17] 陈健,王成山,赵波,等.考虑储能系统特性的独立微电网系统经济运行优化[J].电力系统自动化,2012,36(20):25-31.CHEN Jian, WANG Chengshan, ZHAO Bo, et al. Economic operation optimization of a stand-alone microgrid system considering characteristics of energy storage system[J]. Automation of Electric Power Systems, 2012, 36(20): 25-31.
[18] TRAN D, KHAMBADKONE A M. Energy management for lifetime extension of energy storage system in micro-grid applications[J]. IEEE Transactions on Smart Grid, 2013, 4(3): 1289-1296.
[19] VETTER J, NOVáK P, WAGNER M R, et al. Ageing mechanisms in lithium-ion batteries[J]. Journal of Power Sources, 2005, 147(1/2): 269-281.
[20] KOLLER M, BORSCHE T, ULBIG A, et al. Defining a degradation cost function for optimal control of a battery energy storage system[C]// 2013 IEEE Grenoble Conference, June 16-20, 2013, Grenoble, France: 1-6.
[21] GOEBEL C, HESSE H, SCHIMPE M, et al. Model-based dispatch strategies for lithium-ion battery energy storage applied to pay-as-bid markets for secondary reserve[J]. IEEE Transactions on Power Systems, 2017, 32(4): 2724-2734.
[22] PJM. PJM metered load data[EB/OL]. [2018-01-01]. http://www.pjm.com/markets-and-operations/ops-analysis/historical-load-data.aspx.
[2] HE G, CHEN Q, KANG C, et al. Optimal bidding strategy of battery storage in power markets considering performance-based regulation and battery cycle life[J]. IEEE Transactions on Smart Grid, 2016, 7(5): 2359-2367.
[3] 谢东亮,薛峰,宋晓芳.基于最优价值网络的储能系统调度优化及仿真[J].电力系统自动化,2016,40(24):42-48.XIE Dongliang, XUE Feng, SONG Xiaofang. Optimization and simulation for dispatch of energy storage systems based on optimal value networks[J]. Automation of Electric Power Systems, 2016, 40(24): 42-48.
[4] LU B, SHAHIDEHPOUR M. Short-term scheduling of battery in a grid-connected PV/battery system[J]. IEEE Transactions on Power Systems, 2005, 20(2): 1053-1061.
[5] POZO D, CONTRERAS J, SAUMA E E. Unit commitment with ideal and generic energy storage units[J]. IEEE Transactions on Power Systems, 2014, 29(6): 2974-2984.
[6] DUGGAL I, VENKATESH B. Short-term scheduling of thermal generators and battery storage with depth of discharge-based cost model[J]. IEEE Transactions on Power Systems, 2015, 30(4): 2110-2118.
[7] 孙浩, 张磊, 许海林,等. 微电网日内调度计划的混合整数规划模型[J]. 电力系统自动化, 2015, 39(19): 21-27.SUN Hao, ZHANG Lei, XU Hailin, et al. Mixed integer programming model for microgrid intra-day scheduling[J]. Automation of Electric Power Systems, 2015, 39(19): 21-27.
[8] 杨艳红, 裴玮, 邓卫,等.计及蓄电池储能寿命影响的微电网日前调度优化[J].电工技术学报,2015,30(22):172-180.YANG Yanhong, PEI Wei, DENG Wei, et al. Day-ahead scheduling optimization for microgrid with battery life model[J]. Transactions of China Electrotechnical Society, 2015, 30(22): 172-180.
[9] 邱海峰,赵波,林达,等.计及储能损耗和换流成本的交直流混合微网区域协调调度[J].电力系统自动化,2017,41(23):29-37.DOI:10.7500/AEPS20161213012.QIU Haifeng, ZHAO Bo, LIN Da, et al. Regional coordinated dispatch in AC/DC hybrid microgrids considering energy storage loss and converter cost[J]. Automation of Electric Power Systems, 2017, 41(23): 29-37. DOI: 10.7500/AEPS20161213012.
[10] XU B, OUDALOV A, ULBIG A, et al. Modeling of lithium-ion battery degradation for cell life assessment[J]. IEEE Transactions on Smart Grid, 2018, 9(2): 1131-1140.
[11] WANG J, PUREWAL J, LIU P, et al. Degradation of lithium ion batteries employing graphite negatives and nickel-cobalt-manganese oxide+spinel manganese oxide positives: Part 1 aging mechanisms and life estimation[J]. Journal of Power Sources, 2014, 269(12): 937-948.
[12] 李逢兵,谢开贵,张雪松,等.基于寿命量化的混合储能系统协调控制参数优化[J].电力系统自动化,2014,38(1):1-5. LI Fengbing, XIE Kaigui, ZHANG Xuesong, et al. Optimization of coordinated control parameters for hybrid energy storage system based on life quantization[J]. Automation of Electric Power Systems, 2014, 38(1): 1-5.
[13] 肖浩,裴玮,孔力.基于模型预测控制的微电网多时间尺度协调优化调度[J].电力系统自动化,2016,40(18):7-14.XIAO Hao, PEI Wei, KONG Li. Multi-time scale coordinated optimal dispatch of microgrid based on model predictive control[J]. Automation of Electric Power Systems, 2016, 40(18): 7-14.
[14] SHI Y, XU B, WANG D, et al. Using battery storage for peak shaving and frequency regulation: joint optimization for superlinear gains[J]. IEEE Transactions on Power Systems, 2018, 33(3): 2882-2894.
[15] SU W, WANG J, ROH J. Stochastic energy scheduling in microgrids with intermittent renewable energy resources[J]. IEEE Transactions on Smart Grid, 2014, 5(4): 1876-1883.
[16] AL-SAADI M K, LUK P C K, FEI W. Impact of unit commitment on the optimal operation of hybrid microgrids[C]//2016 UKACC 11th International Conference on Control, August 31-September 2, 2016, Belfast, UK: 1-6.
[17] 陈健,王成山,赵波,等.考虑储能系统特性的独立微电网系统经济运行优化[J].电力系统自动化,2012,36(20):25-31.CHEN Jian, WANG Chengshan, ZHAO Bo, et al. Economic operation optimization of a stand-alone microgrid system considering characteristics of energy storage system[J]. Automation of Electric Power Systems, 2012, 36(20): 25-31.
[18] TRAN D, KHAMBADKONE A M. Energy management for lifetime extension of energy storage system in micro-grid applications[J]. IEEE Transactions on Smart Grid, 2013, 4(3): 1289-1296.
[19] VETTER J, NOVáK P, WAGNER M R, et al. Ageing mechanisms in lithium-ion batteries[J]. Journal of Power Sources, 2005, 147(1/2): 269-281.
[20] KOLLER M, BORSCHE T, ULBIG A, et al. Defining a degradation cost function for optimal control of a battery energy storage system[C]// 2013 IEEE Grenoble Conference, June 16-20, 2013, Grenoble, France: 1-6.
[21] GOEBEL C, HESSE H, SCHIMPE M, et al. Model-based dispatch strategies for lithium-ion battery energy storage applied to pay-as-bid markets for secondary reserve[J]. IEEE Transactions on Power Systems, 2017, 32(4): 2724-2734.
[22] PJM. PJM metered load data[EB/OL]. [2018-01-01]. http://www.pjm.com/markets-and-operations/ops-analysis/historical-load-data.aspx.