In order to solve the problems of slow dynamic response and difficult multi-source coordination of solar electric vehicle charging stations under intermittent renewable energy,this paper proposes a hardware-algorithm ...In order to solve the problems of slow dynamic response and difficult multi-source coordination of solar electric vehicle charging stations under intermittent renewable energy,this paper proposes a hardware-algorithm co-design framework:the T-type three-level bidirectional converter(100 kHz switching frequency)based on silicon carbide(SiC)MOSFET is deeply integrated with fuzzy model predictive control(Fuzzy-MPC).At the hardware level,the switching trajectory and resonance suppression circuit(attenuation resonance peak 18 dB)are optimized,and the total loss is reduced by 23%compared with the traditional silicon-based IGBT.At the algorithm level,the adaptive parameter update mechanism and multi-objective rolling optimization are adopted,and the 5 ms level dynamic power allocation is realized by relying on edge computing.Experiments on 800 V DC microgrid(including 600 kW photovoltaic and 150 A·h energy storage)built based on MATLAB/Simulink hardware-in-the-loop(HIL)platform show that the system shortens the battery charging time from 42 to 28 min(the charging speed is increased by 33%).Through the 78%valley power utilization rate,the power purchase cost of high-priced power grids was significantly reduced,and the levelized electricity price decreased by 10.3%;Under the irradiation fluctuation,the renewable energy consumption rate increases by 10.1%,and the DC bus voltage fluctuation is stable within±10 V when the load step is±30%.The co-design provides an economically feasible and dynamically robust solution for the efficient integration of PV-ESG-EV in the smart grid.展开更多
基金Jiangsu Provincial College Student Innovation and Entrepreneurship Program(Grant No.SJCX25_2184)—“Multi-energy Complementary Optimization and Vehicle-Storage Bidirectional Interaction Technology Driven by Novel 5E Framework”(Principal Investigator:Yuan-Yuan ShiFunding Agency:Jiangsu Provincial Education Department)+3 种基金Huaian Natural Science Research Project(Grant No.HAB2024046)—“Optimal Control of Flexible Cold-Heat-Power Integrated System with Source-Grid-Load-Storage Coordination”(Principal Investigator:Jie JiFunding Agency:Huaian Science and Technology Bureau)Huaiyin Institute of TechnologyUniversity-funded Project(GrantNo.HGYK202511)—“Data-driven CooperativeOptimization Dispatch for Source-Grid-Load Systems”(Principal Investigator:Chu-Tong ZhangFunding Agency:Huaiyin Institute of Technology).
文摘In order to solve the problems of slow dynamic response and difficult multi-source coordination of solar electric vehicle charging stations under intermittent renewable energy,this paper proposes a hardware-algorithm co-design framework:the T-type three-level bidirectional converter(100 kHz switching frequency)based on silicon carbide(SiC)MOSFET is deeply integrated with fuzzy model predictive control(Fuzzy-MPC).At the hardware level,the switching trajectory and resonance suppression circuit(attenuation resonance peak 18 dB)are optimized,and the total loss is reduced by 23%compared with the traditional silicon-based IGBT.At the algorithm level,the adaptive parameter update mechanism and multi-objective rolling optimization are adopted,and the 5 ms level dynamic power allocation is realized by relying on edge computing.Experiments on 800 V DC microgrid(including 600 kW photovoltaic and 150 A·h energy storage)built based on MATLAB/Simulink hardware-in-the-loop(HIL)platform show that the system shortens the battery charging time from 42 to 28 min(the charging speed is increased by 33%).Through the 78%valley power utilization rate,the power purchase cost of high-priced power grids was significantly reduced,and the levelized electricity price decreased by 10.3%;Under the irradiation fluctuation,the renewable energy consumption rate increases by 10.1%,and the DC bus voltage fluctuation is stable within±10 V when the load step is±30%.The co-design provides an economically feasible and dynamically robust solution for the efficient integration of PV-ESG-EV in the smart grid.
