研究目的
To extract the maximum power from the photovoltaic panel using artificial neural network (ANN) and compare its performance with the conventional P&O method.
研究成果
The ANN-based MPPT algorithm significantly improves the PV system's performance, with faster response times and zero oscillations during steady state, increasing power output by approximately 20% compared to the P&O method.
研究不足
The study is based on simulation results using MATLAB/Simulink. Experimental validation is suggested for future work.
1：Experimental Design and Method Selection:
The study uses ANN for MPPT in PV systems, comparing it with the P&O method.
2：Sample Selection and Data Sources:
Input data for training the ANN are obtained from real weather conditions in Algeria.
3：List of Experimental Equipment and Materials:
PV system, boost converter, MATLAB software.
4：Experimental Procedures and Operational Workflow:
The ANN is trained using data from real weather conditions and the P&O method. The system's performance is simulated in MATLAB/Simulink.
5：Data Analysis Methods:
The performance of the ANN and P&O methods is compared in terms of response time, stability, and power output.
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