研究目的
To feed domestic load with solar energy in order to ensure the continuity of supply to the load, also using grid power.
研究成果
The maximum power point technique with the Neuro-fuzzy algorithm in a solar photovoltaic system has been presented. It gave a better performance under various environmental changes like solar irradiation and temperature. The overall system has been analyzed and studied with Matlab/Simulink. The performance results were validated with the hardware result, with the benefits of FPGA.
研究不足
The dynamic nature of solar irradiance and temperature poses challenges in efficient energy conversion.
1：Experimental Design and Method Selection:
The system is modeled using Matlab/Simulink with the Anfis algorithm for MPPT.
2：Sample Selection and Data Sources:
Solar irradiance and temperature data are used to train the Anfis controller.
3：List of Experimental Equipment and Materials:
PV module, boost converter, inverter, FPGA, and programmable relay.
4：Experimental Procedures and Operational Workflow:
The system tracks the maximum power point by changing the duty ratio of the boost converter. The hardware results are validated using FPGA.
5：Data Analysis Methods:
The performance is analyzed under various environmental changes like solar irradiation and temperature.
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