能源研究与管理2025，Vol.17Issue(4)：64-76,13.DOI:10.16056/j.2096-7705.2025.04.009
基于风光储的光伏MPPT和并网协同控制策略对比
Comparative Study of Coordinated Photovoltaic MPPT and Grid Control Strategies in Wind-Solar-Storage Systems
摘要
Abstract
The fluctuating and uncertain output of renewable energy sources poses challenges to power system stability.To address this issue,aims to identify combinations of photovoltaic(PV)control and grid-connected control strategies that achieve superior system operating performance.A wind-PV-storage multi-energy complementary grid-connected system model is developed in Simulink,integrating four MPPT algorithms-perturb and observe(P&O),incremental conductance(INC),fuzzy logic control(FLC),and particle swarm optimization(PSO)—which are respectively combined with two grid-connected control strategies,active and reactive power(PQ)control and droop control,to form eight coordinated control schemes.Under typical irradiance step changes and load fluctuation conditions,these schemes are systematically compared in terms of PV maximum power point tracking speed,dynamic response rate of the energy storage system,and DC-bus voltage fluctuation.The results show that,for the PV subsystem,the FLC algorithm combined with droop control reaches the maximum power point within 0.004 s,followed by the FLC algorithm combined with PQ control at 0.008 s,both significantly faster than the other algorithms.For the energy storage system,the P&O algorithm combined with droop control achieves the fastest dynamic response.In terms of overall system response and stability,PQ control yields a grid-connected response time of about 0.003 s and a DC-bus voltage fluctuation of approximately 18 V,with no obvious oscillations in the output waveforms,and thus outperforms droop control.Considering PV tracking performance,power quality,and system regulation capability comprehensively,the combination of FLC and PQ control exhibits the best overall performance.The proposed analysis provides theoretical support and engineering references for coordinated control optimization of wind-PV-storage systems and their applications in distributed microgrids and integrated generation-grid-load-storage scenarios.关键词
光伏/最大功率点跟踪/储能/PQ控制/下垂控制Key words
photovoltaic(PV)/maximum power point tracking(MPPT)/energy storage/active and reactive power(PQ)con-trol/droop control分类
信息技术与安全科学引用本文复制引用
LI Yu,SHEN Haotian,XU Yujie,XI Jianfei..基于风光储的光伏MPPT和并网协同控制策略对比[J].能源研究与管理,2025,17(4):64-76,13.基金项目
中国科学院洁净能源先导科技专项资助项目(XDA0400100) （XDA0400100）
中国科学院国际合作局对外合作重点项目资助项目(117GJHZ2023009MI) （117GJHZ2023009MI）
中国科学院国际合作局国际伙伴计划项目计划资助项目(117GJHZ2023093MI) （117GJHZ2023093MI）
中国科学院战略性先导科技专项资助项目(XDC0190000) （XDC0190000）
