研究目的
To develop an intelligent control system using fuzzy inference system and energy management algorithm for a Fuel cell assisted PV Battery system to achieve steady process and power balance despite varying environmental conditions.
研究成果
The paper presents a highly practical, precise model of a photovoltaic fuel cell system, demonstrating how hybrid systems behave under various conditions. The developed technique improves battery mean state of charge by 20%, increases PV energy utilization by 20–30%, and reduces fuel usage of Fuel Cell by 25%. The results depict a near optimal solution for managing different power systems and energy devices.
研究不足
The study is based on simulation results, and real-world implementation may face challenges not accounted for in the model. The unpredictability of microgrids due to multiple sources and the absence of specific simulators for alternative sources are also limitations.
1：Experimental Design and Method Selection:
The study involves the simulation of a microgrid system with PV and FC system using MATLAB/Simulink. An intelligent controller based on fuzzy inference system is implemented for supervisory control and battery management system.
2：Sample Selection and Data Sources:
The system is simulated under varying conditions such as irradiance and Hydrogen levels to observe its performance.
3：List of Experimental Equipment and Materials:
The model includes a PEMFC stack with a nominal voltage of 45 Vdc and nominal power of 1.5 kW, a PV array, and a battery bank.
4：5 kW, a PV array, and a battery bank.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The system's performance is evaluated under different operating conditions, including changes in solar radiation, panel temperature, and consumer load profiles.
5：Data Analysis Methods:
The effectiveness of the developed system is confirmed through simulation results, focusing on power balance, efficiency, and energy management.
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