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山东大学学报 (工学版) ›› 2025, Vol. 55 ›› Issue (2): 37-44.doi: 10.6040/j.issn.1672-3961.0.2023.308

• 电气工程——智慧能源专题(张恒旭教授主持) • 上一篇    下一篇

计及SOC安全边界的光储联合系统协同控制策略

王士柏1,孙树敏1,程艳1,周光奇1,关逸飞1,刘奕元1,张志谦2,张祯滨2*   

  1. 1.国网山东省电力公司电力科学研究院, 山东 济南 250003;2.山东大学电气工程学院, 山东 济南 250061
  • 发布日期:2025-04-15
  • 作者简介:王士柏(1987— ),男,山东烟台人,高级工程师,博士,主要研究方向为大规模新能源与储能并网运行、分布式电源及微电网运行控制、新能源发电并网安全评价. E-mail: 15666968066@126.com. *通信作者简介:张祯滨(1984— ),男,山东济南人,教授,博士生导师,博士,主要研究方向为预测控制在多能源系统与新能源电力变流器集群中的应用等. E-mail: zbz@sdu.edu.cn
  • 基金资助:
    国网山东省电力公司科技资助项目(520626230031)

A cooperative control strategy of integrated photovoltaic-energy storage system considering SOC security boundary

WANG Shibo1, SUN Shumin1, CHENG Yan1, ZHOU Guangqi1, GUAN Yifei1, LIU Yiyuan1, ZHANG Zhiqian2, ZHANG Zhenbin2*   

  1. WANG Shibo1, SUN Shumin1, CHENG Yan1, ZHOU Guangqi1, GUAN Yifei1, LIU Yiyuan1, ZHANG Zhiqian2, ZHANG Zhenbin2*(1. State Grid Shandong Electric Power Research Institute, Jinan 250003, Shandong, China;
    2. School of Electrical Engineering, Shandong University, Jinan 250061, Shandong, China
  • Published:2025-04-15

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摘要： 为解决光储联合系统储能电池荷电状态(state of charge, SOC)超出安全边界时电池加速老化,系统运行经济性差,且系统功率动态响应速度慢的问题,依据光储联合系统的运行特性,提出一种计及SOC安全边界的光储联合系统协同控制策略,当SOC达预设边界时自动切换变流器工作模式,保证系统健康运行的同时使系统具备频率支撑能力。设计一种基于模型预测控制的虚拟同步发电机(virtual synchronous generator, VSG)策略,实现对电网的惯量支撑和负荷功率需求的快速响应。通过搭建MATLAB/Simulink光储联合系统仿真模型,对储能电池SOC越限时的功频响应特性进行对比和分析,结果表明,模型预测控制相比传统双闭环控制具有更好的动态调节性能,且电池SOC始终处于预设的安全边界内。所提方法可以有效加快光储联合系统功率响应速度,提升对电网的主动支撑能力。

关键词: 光储联合系统, 虚拟同步发电机, 模型预测控制, 荷电状态, 协同控制

Abstract: To solve the problems of accelerated battery aging, poor economic performance, and slow dynamic response speed of the integrated photovoltaic-energy storage system, when the state of charge(SOC)of battery exceeded safety boundary, a cooperative control strategy for integrated photovoltaic-energy storage system considering SOC security boundary was proposed, which was based on the operation characteristics of the integrated photovoltaic-energy storage system. When the SOC reached the preset boundary, the working mode of converter was automatically switched to ensure healthy operation of system and endow the system with frequency support capability. A virtual synchronous generator(VSG)strategy based on model predictive control was designed to achieve inertia support for grid and fast response to the load power demand. By constructing a MATLAB/Simulink simulation model of integrated photovoltaic-energy storage converter system, the power-frequency response characteristics of storage batteries at SOC exceeding the boundary were compared and analyzed. The results indicated that compared to traditional dual-loop control, model predictive control provided faster dynamic adjustment performance, and SOC remained within the safety boundary. The proposed method accelerated the power response speed of the integrated photovoltaic-energy storage system, and effectively improved the active support capability to the power grid.

Key words: integrated photovoltaic-energy storage system, virtual synchronous generator, model predictive control, state of charge, cooperative control

中图分类号: 

  • TM615
[1] 康重庆, 姚良忠. 高比例可再生能源电力系统的关键科学问题与理论研究框架[J]. 电力系统自动化, 2017, 41(9): 2-11. KANG Chongqing, YAO Liangzhong. Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2017, 41(9): 2-11.
[2] 张恒旭, 高志民, 曹永吉, 等. 高比例可再生能源接入下电力系统惯量研究综述及展望[J]. 山东大学学报(工学版), 2022, 52(5): 1-13. ZHANG Hengxu, GAO Zhimin, CAO Yongji, et al. Review and prospect of research on power system inertia with high penetration of renewable energy source[J]. Journal of Shandong University(Engineering Science), 2022, 52(5): 1-13.
[3] NGUYENH T, YANG G, NIELSEN A H, et al. Combination of synchronous condenser and synthetic inertia for frequency stability enhancement in low-inertia systems[J]. IEEE Transactions on Sustainable Energy, 2019, 10(3): 997-1005.
[4] 曹炜, 钦焕乘, 陆建忠, 等. 新型电力系统下虚拟同步机的定位和应用前景展望[J]. 电力系统自动化, 2023, 47(4): 190-207. CAO Wei, QIN Huancheng, LU Jianzhong, et al. Orientation and application prospect of virtual synchronous generator in new power system[J]. Automation of Electric Power Systems, 2023, 47(4): 190-207.
[5] 陈文倩, 辛小南, 程志平. 基于虚拟同步发电机的光储并网发电控制技术[J]. 电工技术学报, 2018, 33(增刊2): 538-545. CHEN Wenqian, XIN Xiaonan, CHENG Zhiping. Control of grid-connected of photovoltaic system with storage based on virtual synchronous generator[J]. Tran-sactions of China Electrotechnical Society, 2018, 33(Suppl.2): 538-545.
[6] SHI M, CHEN H, ZHANG C, et al. A virtual synchronous generator system control method with battery SOC feedback[C] // 2018 2nd IEEE Conference on Energy Internet and Energy System Integration(EI2). Beijing, China: IEEE, 2018: 8582563.
[7] 孙东磊, 赵龙, 秦敬涛, 等. 基于学习理论的含光储联合系统的输电网双层规划[J]. 山东大学学报(工学版), 2020, 50(4): 90-97. SUN Donglei, ZHAO Long, QIN Jingtao, et al. Bi-level planning of transmission network with solar-storage combination system based on learning theory[J]. Journal of Shandong University(Engineering Science), 2020, 50(4): 90-97.
[8] 邢东峰, 田铭兴. 虚拟同步发电机频率特性与储能设备容量及充放电特性的关系[J]. 电网技术, 2021, 45(9): 3582-3590. XING Dongfeng, TIAN Mingxing. Relationship between frequency characteristics of virtual synchronous generator and parameters of energy storage equipment[J]. Power System Technology, 2021, 45(9): 3582-3590.
[9] WANG F, ZHANG L, FENG X, et al. An adaptive control strategy for virtual synchronous generator[J]. IEEE Transactions on Industry Applications, 2018, 54(5): 5124-5133.
[10] YANG Y, ZHI P, ZHU W. A photovoltaic power fluctuation design based on moving average algorithm and supercapacitor coordinated control strategy[C] // 2022 41st Chinese Control Conference(CCC). Hefei, China: IEEE, 2022: 5159-5164.
[11] 温烨婷, 戴瑜兴, 毕大强, 等. 一种电网友好型光储分布式电源控制策略[J]. 中国电机工程学报, 2017, 37(2): 464-476. WEN Yeting, DAI Yuxing, BI Daqiang, et al. A grid friendly PV/BESS distributed generation control strategy[J]. Proceedings of the CSEE, 2017, 37(2): 464-476.
[12] GOLSORKHIM S, SHAFIEE Q, LU D D C, et al. A distributed control framework for integrated photovoltaic-battery based islanded microgrids[J]. IEEE Transactions on Smart Grid, 2017, 8(6): 2837-2848.
[13] FU Y, CHEN Y, XIE Z, et al. Coordinated power control of photovoltaic-battery generation system based on self-synchronizing voltage source inverter[C] // IECON 2023-49th Annual Conference of the IEEE Industrial Electronics Society. Singapore: IEEE, 2023: 1-6.
[14] 殷勤. 基于VSG技术的光储微网控制策略研究[D].上海: 东华大学, 2023. YIN Qin. Research on control strategy of photovoltaic/battery microgrid based on VSG technology[D]. Shanghai: Donghua University, 2023.
[15] 高建瑞, 李国杰, 汪可友, 等. 考虑储能充放电功率限制的并网光储虚拟同步机控制[J]. 电力系统自动化, 2020, 44(4): 134-141. GAO Jianrui, LI Guojie, WANG Keyou, et al. Control of grid-connected PV-battery virtual synchronous machine considering battery charging/discharging power limit[J]. Automation of Electric Power Systems, 2020, 44(4): 134-141.
[16] 蒋林, 秦建茹, 韩璐, 等. 基于滑模变功率跟踪的PV-VSG控制技术[J]. 太阳能学报, 2022, 43(5): 193-199. JIANG Lin, QIN Jianru, HAN Lu, et al. Control technology of PV-VSG based on sliding mode variable power tracking[J]. Acta Energiae Solaris Sinica, 2022, 43(5): 193-199.
[17] 倪泽龙, 林钰钧, 王治涛, 等. 基于模型预测的虚拟同步机控制储能调频研究[J]. 电力系统保护与控制, 2022, 50(14): 85-93. NI Zelong, LIN Yujun, WANG Zhitao, et al. Research on frequency regulation of VSG controlled energy storages based on model predictive control[J]. Power System Protection and Control, 2022, 50(14): 85-93.
[18] 朱作滨, 孙树敏, 丁月明, 等. 基于储能协调自适应VSG控制策略研究[J]. 太阳能学报, 2023, 44(12): 410-419. ZHU Zuobin, SUN Shumin, DING Yueming, et al. Research on adaptive VSG control strategy based on energy storage coordination[J]. Acta Energiae Solaris Sinica, 2023, 44(12): 410-419.
[19] CHEN S, SUN Y, HOU X, et al. Quantitative parameters design of VSG oriented to transient synchronization stability[J]. IEEE Transactions on Power Systems, 2023, 38(5): 4978-4981.
[20] LIU T, CHEN A, GAO F, et al. Double-loop control strategy with cascaded model predictive control to improve frequency regulation for islanded microgrids[J]. IEEE Transactions on Smart Grid, 2022, 13(5): 3954-3967.
[21] ZHENG C, DRAGICEVIC T, BLAABJERG F. Model predictive control-based virtual inertia emulator for an islanded alternating current microgrid[J]. IEEE Tran-sactions on Industrial Electronics, 2021, 68(8): 7167-7177.
[22] 王松. 一种基于神经网络的光伏电源最大功率控制系统[J]. 山东大学学报(工学版), 2004, 34(4): 45-48. WANG Song. A maximum power control system of photovoltaic cells based on neural network[J]. Journal of Shandong University(Engineering Science), 2004, 34(4): 45-48.
[23] 张博, 唐巍, 蔡永翔, 等. 基于一致性算法的户用光伏逆变器和储能分布式控制策略[J]. 电力系统自动化, 2020, 44(2): 86-94. ZHANG Bo, TANG Wei, CAI Yongxiang, et al. Distributed control strategy of residential photovoltaic inverter and energy storage based on consensus algorithm[J]. Automation of Electric Power Systems, 2020, 44(2): 86-94.
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