2024 06 1-7
基于模糊PI控制的飞轮储能分阶段并网启动控制策略分析
基金项目(Foundation):
国家电网公司科技项目“新型储能-发电联合系统主动支撑电网调控技术与低碳决策研究”（5100-202199535A-0-5-ZN）
邮箱(Email):
DOI:
10.19929/j.cnki.nmgdljs.2024.0073
中文作者单位:
国网内蒙古东部电力有限公司电力科学研究院，呼和浩特 010010
摘要(Abstract):
针对飞轮储能传统的永磁同步电机变频调速控制方法启动过程中存在的功率期望值与实际值存在误差、电磁功率升高造成系统内部干扰、控制参数整定难度较大等问题，以经典矢量控制策略为基础，通过分阶段切换控制目标和参考值，将模糊控制技术与PI控制器相结合，提出了基于模糊PID控制的飞轮储能分阶段并网启动控制方法，并基于MATLAB/Simulink建立飞轮储能并网启动仿真模型。仿真结果表明，在飞轮电机启动过程、负载转矩给定过程、转速指令突变过程中，PI控制器参数能够实现自整定，飞轮电机的电磁转矩与转速调节时间明显缩短，调节速度能够提升近50%，各阶段直流母线电压能够保持恒定，波动较小，保证变流器稳定运行，提出的控制方法能够解决由于控制目标切换带来的参数整定困难问题，提升控制系统的动态性能。
关键词(KeyWords):
飞轮储能;并网启动;电磁转矩;分阶段控制;参数自适应;矢量控制
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参考文献
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[13] 范凯伦，张兵，李志俊，等.基于模糊算法的自适应忆阻PI控制系统设计[J].电子测量技术，2023，46（9）：23-29. FAN Kalun, ZHANG Bing, LI Zhijun, et al. Design of adaptive memristive PI control system based on fuzzy algorithm[J]. Electronic Measurement Technology, 2023, 46(9): 23-29.
[14] 吕广强，许文敏，王谱宇.基于变论域模糊PI自适应控制的电力弹簧控制策略[J].电力系统自动化，2020，44（18）：172-178. LYU Guangqiang, XU Wenmin, WANG Puyu. Power spring control strategy based on variable universe fuzzy PI adaptive control[J]. Automation of Electric Power Systems, 2020, 44(18): 172-178.
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[2] 韩如磊，樊子铭，王粟，等.新型电力系统惯量支撑和调频响应特性典型建模综述[J].电工电能新技术，2023，42（11）：67-83. HAN Rulei, FAN Ziming, WANG Su, et al. Review of typical modeling of inertia support and frequency modulation response characteristics for new power systems[J]. Advanced Technology of Electrical Engineering and Energy, 2023, 42(11): 67-83.
[3] 洪烽，贾欣怡，梁璐，等.火-储耦合协同调频策略下飞轮储能容量配置一体化研究[J].热力发电，2023，52（9）：65-75. HONG Feng, JIA Xinyi, LIANG Lu, et al. Research on the integration of flywheel energy storage capacity configuration under the coordinated frequency regulation strategy of fire-storage coupling[J]. Thermal Power Generation, 2023, 52(9): 65-75.
[4] 陈彪，王玮，高嵩，等.基于模糊自适应指令分解的飞轮-火电一次调频控制策略[J].电力系统自动化，2023，47（19）：128-137. CHEN Biao, WANG Wei, GAO Song, et al. Flywheel-thermal power primary frequency regulation control strategy based on fuzzy adaptive instruction decomposition[J]. Automation of Electric Power Systems, 2023, 47(19): 128-137.
[5] 李忠瑞，聂子玲，艾胜，等.一种基于非线性扰动观测器的飞轮储能系统优化充电控制策略[J].电工技术学报，2023，38（6）：1506- 1518. LI Zhongrui, NIE Ziling, AI Sheng, et al. An optimal charging control strategy for flywheel energy storage system based on nonlinear disturbance observer[J]. Transactions of China Electrotechnical Society, 2023, 38(6): 1506-1518.
[6] 赵永明，邱清泉，聂子攀，等.重力/飞轮综合储能电机变流并网系统设计及运行特性[J].储能科学与技术，2022，11（12）：3895- 3905. ZHAO Yongming, QIU Qingquan, NIE Zipan, et al. Design and operation characteristics of converter grid-connected system for gravity/flywheel integrated energy storage motor[J]. Energy Storage Science and Technology, 2022, 11(12): 3895-3905.
[7] 洪烽，梁璐，逄亚蕾，等.基于自适应协同下垂的飞轮储能联合火电机组一次调频控制策略[J].热力发电，2023，52（1）：36-44. HONG Feng, LIANG Lu, PANG Yalei, et al. Primary frequency regulation control strategy of flywheel energy storage combined with thermal power unit based on adaptive cooperative droop[J]. Thermal Power Generation, 2023, 52(1): 36- 44.
[8] 韩健民，薛飞宇，梁双印，等.模糊控制优化下的混合储能系统辅助燃煤机组调频仿真[J].储能科学与技术，2022，11（7）：2188- 2196. HAN Jianmin, XUE Feiyu, LIANG Shuangyin, et al. Simulation of frequency regulation of coal-fired units assisted by hybrid energy storage system under fuzzy control optimization[J]. Energy Storage Science and Technology, 2022, 11(7): 2188-2196.
[9] 武鑫，陈玉龙，柳亦兵.并网型飞轮储能系统金属转子结构优化设计[J].太阳能学报，2021，42（2）：317-321. WU Xin, CHEN Yulong, LIU Yibing. Structural optimization design of metal rotor for grid-connected flywheel energy storage system[J]. Acta Energiae Solaris Sinica, 2021, 42(2): 317-321.
[10] 陈仲伟，李达伟，邹旭东，等.双馈电机驱动的飞轮储能系统稳定运行控制方法[J].电力科学与技术学报，2021，36（1）：177-184. CHEN Zhongwei, LI Dawei, ZOU Xudong, et al. Control method for stable operation of flywheel energy storage system driven by doubly-fed machine[J]. Journal of Electric Power Science and Technology, 2021, 36(1): 177-184.
[11] 龚仁喜，杨元甲，王保平.改进粒子群优化的双向DC/DC变换器模糊PI控制[J].河南科技大学学报（自然科学版)，2022，43（6）： 37-43，7. GONG Renxi, YANG Yuanjia, WANG Baoping. Improved particle swarm optimization of bidirectional DC/DC converter fuzzy PI control[J]. Journal of Henan University of Science & Technology(Natural Science), 2022, 43(6): 37-43, 7.
[12] 宋新甫，于国康，孟高军，等.基于改进重复控制和模糊PI自整定的并网逆变器设计[J].可再生能源，2020，38（2）：245-251. SONG Xinfu, YU Guokang, MENG Gaojun, et al. Design of grid-connected inverter based on improved repetitive control and fuzzy PI self-tuning[J]. Renewable Energy Resources, 2020, 38(2): 245-251.
[13] 范凯伦，张兵，李志俊，等.基于模糊算法的自适应忆阻PI控制系统设计[J].电子测量技术，2023，46（9）：23-29. FAN Kalun, ZHANG Bing, LI Zhijun, et al. Design of adaptive memristive PI control system based on fuzzy algorithm[J]. Electronic Measurement Technology, 2023, 46(9): 23-29.
[14] 吕广强，许文敏，王谱宇.基于变论域模糊PI自适应控制的电力弹簧控制策略[J].电力系统自动化，2020，44（18）：172-178. LYU Guangqiang, XU Wenmin, WANG Puyu. Power spring control strategy based on variable universe fuzzy PI adaptive control[J]. Automation of Electric Power Systems, 2020, 44(18): 172-178.
[15] 樊立萍，冯翔.基于模糊PI的Boost PFC变换器的控制改进[J].电测与仪表，2019，56（22）：121-125，145. FAN Liping, FENG Xiang. Control improvement of Boost PFC converter based on fuzzy PI[J]. Electrical Measurement & Instrumentation, 2019, 56(22): 121-125, 145.
基本信息:
DOI：10.19929/j.cnki.nmgdljs.2024.0073
中图分类号:
引用信息:
[1]郑博文,任正,王新宇等.基于模糊PI控制的飞轮储能分阶段并网启动控制策略分析[J],2024,42(06):1-7.DOI:10.19929/j.cnki.nmgdljs.2024.0073.
基金信息:
国家电网公司科技项目“新型储能-发电联合系统主动支撑电网调控技术与低碳决策研究”（5100-202199535A-0-5-ZN）
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