Abstract：Hybrid energy storage system has the technical characteristics of both energy storage and power storage. It can effectively reduce the photovoltaic power prediction error, hence improve the reliability where PV forecast output is used as the reference of the power dispatch. Therefore, this paper proposes an optimal control strategy for hybrid energy storage system to improve the capacity of photovoltaic output tracking the target output power. This strategy uses the compound control method to control the internal energy coordination control and the multi-objective optimization control. It can reasonably distribute the charge and discharge power of battery and super capacitor, and control the output of the hybrid system to make up for the deviations between the predicted power and the actual power. By analyzing the data of 250 days output power from a domestic 40MW photovoltaic power station, it is shown that this strategy can not only effectively trace the predicted output power of PV, but also make full use of the characteristics of different storage mediums. It reduces the charge and discharge depths of the battery, and consequently the hybrid storage can be better applied.
田春光, 田, 利, 李德鑫, 吕项羽, 常学飞. 基于混合储能系统跟踪光伏发电输出功率的控制策略[J]. 电工技术学报, 2016, 31(14): 75-83.
Tian Chunguang, Tian Li, Li Dexin, Lü Xiangyu, Chang Xuefei. Control Strategy for Tracking the Output Power of Photovoltaic Power Generation Based on Hybrid Energy Storage System. Transactions of China Electrotechnical Society, 2016, 31(14): 75-83.
[1] 戚永志, 刘玉田. 风光储联合系统输出功率滚动优化与实时控制[J]. 电工技术学报, 2014, 29(8): 265-273. Qi Yongzhi, Liu Yutian. Output power rolling opti- mization and real-time control in wind-photovoltaic- storage hybrid system[J]. Transactions of China Electrotechnical Society, 2014, 29(8): 265-273. [2] 刘伟, 彭冬, 卜广全, 等. 光伏发电接入智能配电网后的系统问题综述[J]. 电网技术, 2009, 33(19): 1-6. Liu Wei, Peng Dong, Bu Guangquan, et al. A survey on system problems in smart distribution network with grid-connected photovoltaic generation[J]. Power System Technology, 2009, 33(19): 1-6. [3] 马速良, 蒋小平, 马会萌, 等. 平抑风电波动的混合储能系统的容量配置[J]. 电力系统保护与控制, 2014, 42(8): 108-114. Ma Suliang, Jiang Xiaoping, Ma Huimeng, et al. Capacity configuration of the hybrid energy storage system for wind power smoothing[J]. Power System Protection and Control, 2014, 42(8): 108-114. [4] 郭思琪, 袁越, 张新松, 等. 多时间尺度协调控制的独立微网能量管理策略[J]. 电工技术学报, 2014, 29(2): 122-129. Guo Siqi, Yuan Yue, Zhang Xinsong, et al. Energy management strategy of isolated microgrid based on multi-time scale coordinated control[J]. Transa- ctions of China Electrotechnical Society, 2014, 29(2): 122-129. [5] 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 storagesystems for output smoothing of renewable energy systems[J]. Proceedings of the CSEE, 2012, 32(16): 1-8. [6] 张纯江, 董杰, 刘君, 等. 蓄电池与超级电容混合储能系统的控制策略[J]. 电工技术学报, 2014, 29(4): 334-340. Zhang Chunjiang, Dong Jie, Liu Jun, et al. A control strategy for battery-ultracapacitor hybrid energy storage system[J]. Transactions of China Electro- technical Society, 2014, 29(4): 334-340. [7] Ise T, Kita M, Taguchi A. A hybrid energy storage with a SMES and secondary battery[J]. IEEE Transactions on Sustainable Energy, 2005, 15(2): 1915-1918. [8] 于芃, 赵瑜, 周玮, 等. 基于混合储能系统的平抑风电波动功率方法的研究[J]. 电力系统保护与控制, 2011, 39(24): 35-40. Yu Peng, Zhao Yu, Zhou Wei, et al. Research on the method based on hybrid energy storage system for balancing fluctuant wind power[J]. Power System Protection and Control, 2011, 39(24): 35-40. [9] 丁明, 林根德, 陈自年, 等. 一种适用于混合储能系统的控制策略[J]. 中国电机工程学报, 2012, 32(7): 1-6. Ding Ming, Lin Gende, Chen Zinian, et al. A control strategy for hybrid energy storage systems[J]. Proceedings of the CSEE, 2012, 32(7): 1-6. [10] Brekken T K A, Yokochi A, Von Jouanne A, et al. Optimal energy storage sizing and control for wind power applications[J]. IEEE Transactions on Sustain- able Energy, 2011, 2(1): 69-77. [11] 于芃, 周玮, 孙辉, 等. 用于风电功率平抑的混合储能系统及其控制系统设计[J]. 中国电机工程学报, 2011, 31(17): 127-133. Yu Peng, Zhou Wei, Sun Hui, et al. Hybrid energy storge system and control system design for wind power balancing[J]. Proceedings of the CSEE, 2011, 31(17): 127-133. [12] 姜晓亮, 李巍, 吕项羽, 等. 基于非参数核密度估计法的光储系统容量优化配置[J]. 高电压技术, 2015, 41(7): 2225-2230. Jiang Xiaoliang, Li Wei, Lü Xiangyu, et al. Optimization configuration of photovoltaic-storage system capacity based on non-parametric Kernel density estimation[J]. High Voltage Engineering, 2015, 41(7): 2225-2230. [13] 刘皓明, 陆丹, 杨波, 等. 可平抑高渗透分布式光伏发电功率波动的储能电站调度策略[J]. 高电压技术, 2015, 41(10): 3213-3223. Liu Haoming, Lu Dan, Yang Bo, et al. Dispatch strategy of energy storage station to smooth power fluctuations of high penetration photovoltaic gener- ation[J]. High Voltage Engineering, 2015, 41(10): 3213-3223. [14] 梁亮, 李建林, 惠东. 光伏-储能联合发电系统运行机理及控制策略[J]. 电力自动化设备, 2011, 31(8): 20-23. Liang Liang, Li Jianlin, Hui Dong. Operating modes of photovoltaic/energy-storage hybrid systemand its control strategy[J]. Electric Power Automation Equipment, 2011, 31(8): 20-23. [15] 孔波利, 崔丽艳, 丁钊, 等. 基于风光混合模型的短期功率预测方法研究[J]. 电力系统保护与控制, 2015, 43(18): 62-66. Kong Boli, Cui Liyan, Ding Zhao, et al. Short term power prediction based on hybrid wind-PV forecasting model[J]. Power System Protection and Control, 2015, 43(18): 62-66. [16] 裴胜玉, 周永权. 基于Pareto最优解集的多目标粒子群优化算法[J]. 计算机工程与科学, 2010, 32(11): 85-90. Pei Shengyu, Zhou Yongquan. A multi-objective particle swarm algorithm based on the Praeto optimization solution set[J]. Computer Engineering & Science, 2010, 32(11): 85-90.
2016, Vol. 31 
