光伏微网混合储能系统的研究

摘要/Abstract

摘要： 针对光伏直流微网中混合储能系统（HESS）的能量损耗和充电状态的调度问题，本文设计了一种基于多目标优化算法的能量管理策略。首先，对储能型光伏直流微网的拓扑结构进行分析。其次，将HESS的控制目标设为被优化的目标，提出了一种改进型多目标粒子群优化算法(MOPSO)。基于此算法构建了HESS的能量管理策略。最后，通过仿真验证了所提出算法及能量管理策略的正确性，该方式能够有效减少光伏微网系统的能量损失。

关键词: 混合储能系统, 粒子群算法, 多目标优化, 能量管理

Abstract: An energy management strategy based on multi-objective optimization algorithm is designed to solve the energy loss and charging state scheduling problems of hybrid energy storage system (Hess) in photovoltaic DC microgrid. Firstly, the topology of energy storage photovoltaic DC microgrid is analyzed. Secondly, an improved multi-objective particle swarm optimization (MOPSO) algorithm is proposed by setting the control objective of Hess as the optimized one. Based on this algorithm, the energy management strategy of Hess is constructed. Finally, the correctness of the proposed algorithm and energy management strategy is verified by simulation, which can effectively reduce the energy loss of photovoltaic microgrid system.

Key words: Hybrid energy storage system, particle swarm optimization algorithm, multi-objective optimization, energy management

成杰刘金豆梁安江. 光伏微网混合储能系统的研究[J]. 华电技术.

Jie CHENG. Research On Hybrid Energy Storage System Of Photovoltaic (PV) Microgrid[J]. Huadian Technology.

参考文献

[1]李霞林, 郭力, 王成山,等. 直流微电网关键技术研究综述[J]. 中国电机工程学报, 2016, 36(1):2-16. LI Xialin, Guo Li, Wang Chengshan, et al. Review on Key Technologies of DC microgrid [J]. Chinese Journal of electrical engineering, 2016, 36 (1): 2-16 [2] Soltani, Jafar, Rezaei, et al. A robust control strategy for a grid-connected multi-bus microgrid under unbalanced load conditions[J]. International journal of electrical power and energy systems, 2015. [3] Cingoz F , Elrayyah A , Sozer Y . Optimized Droop Control Parameters for Effective Load Sharing and Voltage Regulation in DC Microgrids[J]. Electric Power Components and Systems, 2015, 43(8-10):879-889. [4] Prasad V. Joshi, Yogesh S. Bhavsar, Sharad S. Dhamal,etc. Grid interconnection of DC microgrid at distribution level using power electronic converter system-MATLAB/Simulink modeling and analysis[C]// 2016 International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT). IEEE, 2017. [5] 闫林芳, 刘巨, 石梦璇,等. 基于模糊逻辑算法的直流微电网复合储能系统功率自适应分配策略[J]. 中国电机工程学报, 2019, 039(009):2658-2669. YAN Linfang, Liu Ju, Shi Mengxuan, et al. Adaptive power allocation strategy for DC microgrid composite energy storage system based on fuzzy logic algorithm [J]. Acta electrical engineering Sinica, 2019, 039 (009): 2658-2669 [6] 王松岑, 来小康, 程时杰. 大规模储能技术在电力系统中的应用前景分析[J]. 电力系统自动化, 2013, 37(1):3-8. WANG Songcen, Lai Xiaokang, Cheng Shijie. Analysis of application prospect of energy storage technology in power system [J]. Power system automation, 2013, 37 (1): 3-8 [7] 马泽宇, 姜久春, 文锋, et al. 用于储能系统的梯次利用锂电池组均衡策略设计[J]. 电力系统自动化, 2014(3). MA Zeyu, Jiang Jiuchun, Wen Feng, et al. Design of lithium battery equalization strategy for echelon utilization of energy storage system [J]. Power system automation, 2014 (3) [8] 熊兰, 桂园, 柳慧梅,等. 带超级电容的级联型光伏并网逆变器控制策略[J]. 电力系统保护与控制, 2019, 047(002):108-114. XIONG Lan, Gui Yuan, Liu Huimei, et al. Control strategy of cascaded photovoltaic grid connected inverter with super capacitor [J]. Power system protection and control, 2019, 047 (002): 108-114 [9] 滕云, 孙鹏, 罗桓桓,等. 计及电热混合储能的多源微网自治优化运行模型[J]. 中国电机工程学报, 2019, 39(18). TENG Yun, Sun Peng, Luo Huanhuan, et al. Autonomous optimal operation model of multi-source microgrid considering electric thermal hybrid energy storage [J]. Chinese Journal of electrical engineering, 2019, 39 (18). [10] 陈强. 基于锂电池充放电状态的混合储能系统控制策略设计[J]. 中国科技投资, 2016(27). CHEN Qiang. Control strategy design of hybrid energy storage system based on lithium battery charging and discharging state [J]. China Science and technology investment, 2016 (27) [11] 周林, 黄勇, 郭珂,等. 微电网储能技术研究综述[J]. 电力系统保护与控制, 2011(07):154-159. ZHOU Lin, Huang Yong, Guo Ke, et al. Review of energy storage technology in microgrid [J]. Power system protection and control, 2011 (07): 154-159 [12] Jia K , Chen Y , Bi T , et al. Historical-Data-Based Energy Management in a Microgrid With a Hybrid Energy Storage System[J]. IEEE Transactions on Industrial Informatics, 2017, 13(5):2597-2605. [13] 周烨, 汪可友, 李国杰,等.基于多智能体一致性算法的微电网分布式分层控制策略[J]. 电力系统自动化, 2017, 041(011):142-149. ZHOU ye, Wang Keyou, Li Guojie, et al. Distributed hierarchical control strategy for microgrid based on multi-agent consensus algorithm [J]. Power system automation, 2017, 041 (011): 142-149 [14] Shucheng T , Ge D , Hui Z , et al. Virtual DC machine control strategy of energy storage converter in DC microgrid[C]// 2016 IEEE Electrical Power and Energy Conference (EPEC). IEEE, 2016. [15] 王德顺, 薛金花, 叶季蕾,等. 基于粒子群算法的储能电站经济优化调度策略[J]. 可再生能源, 2019, 37(05):86-91. WANG Deshun, Xue Jinhua, ye Jilei, et al. Economic optimal scheduling strategy of energy storage power station based on particle swarm optimization algorithm [J]. Renewable energy, 2019, 37 (05): 86-91 [16] 李盟盟, 王育飞, 薛花. 基于改进粒子群算法的削峰填谷用储能系统经济运行策略[J]. 软件工程, 2017(11):36-40. LI Lianmeng, Wang Yufei, Xue Hua. Economic operation strategy of energy storage system for peak shaving and valley filling based on improved particle swarm optimization algorithm [J]. Software engineering, 2017 (11): 36-40 [17] Silva P , Javier Mu?oz, Hernandez R A , et al. On the DC/DC Converters for Cascaded Asymmetric Multilevel Inverters Aimed to Inject Photovoltaic Energy into Microgrids[C]// IEEE SPEC 2016 Auckland. IEEE, 2016.