研究目的
Evaluating the Maximum Power Point Tracking in the grid integrated Photovoltaic (PV) power generation system using a novel Grasshopper Optimization (GOA) based Xilinx System Generator (XSG) controller.
研究成果
The Xilinx-based GOA MPPT algorithm effectively maximizes power extraction from the PV array under varying environmental conditions. The controller's performance, validated through simulation, shows superior efficiency compared to conventional methods like PSO and ABC. Future work includes hardware implementation to validate the simulation results under real-world conditions.
研究不足
The study is simulation-based, and real-world implementation challenges such as environmental variability and hardware constraints are not fully explored. The comparison is limited to existing algorithms like PSO and ABC, potentially overlooking other advanced techniques.
1：Experimental Design and Method Selection:
The study employs a GOA algorithm for MPPT in a PV system, integrated with an XSG controller for switching signal generation. The methodology involves simulation in MATLAB/Simulink and hardware implementation via XSG.
2：Sample Selection and Data Sources:
The PV system's performance is analyzed under varying solar irradiance and temperature conditions to evaluate the controller's effectiveness.
3：List of Experimental Equipment and Materials:
PV array, DC-DC boost converter, Voltage Source Inverter (VSI), Xilinx FPGA for XSG controller implementation.
4：Experimental Procedures and Operational Workflow:
The PV system's output is monitored under two cases: constant irradiance with variable temperature and constant temperature with variable irradiance. The GOA algorithm adjusts the switching signals to the DC-DC converter to maximize power extraction.
5：Data Analysis Methods:
The output power parameters (voltage, current, and power) are measured and compared with conventional techniques like PSO and ABC algorithms.
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