研究目的
Investigating the parameter estimation of photovoltaic systems under real operating conditions to improve the accuracy of photovoltaic models.
研究成果
The MVMO method effectively estimated photovoltaic system parameters under real operating conditions, showing significant differences in parallel and series resistances compared to standard test conditions. The validation confirmed the accuracy of the estimated parameters, highlighting the method's potential for improving photovoltaic system modeling.
研究不足
The study is limited by the influence of parameter limits on the processing time of MVMO and the need for further research on combining MVMO with non-linear methods to accelerate convergence.
1:Experimental Design and Method Selection:
The improved single diode model was selected to represent the photovoltaic system, and the mean-variance mapping optimization (MVMO) method was used for parameter estimation.
2:Sample Selection and Data Sources:
Real measurements from a photovoltaic system installed at Sao Paulo University were used, including voltage, current, solar irradiance, and cell temperature.
3:List of Experimental Equipment and Materials:
Photovoltaic modules of 265Wp, a power inverter of
4:0kW, and data acquisition systems. Experimental Procedures and Operational Workflow:
Measurements were taken every 5 minutes for voltage and current, and every 5 seconds for solar irradiance and cell temperature, with mean values used for estimation.
5:Data Analysis Methods:
The MVMO method was applied to estimate parameters, with results validated against real measurements.
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