Physics-based data-driven modeling method for power generation degradation of photovoltaic power plants
In order to improve the accuracy and reliability of evaluating the on-site degradation of outdoor photovoltaic power plants,a physics-and data-driven performance degradation model for photo-voltaic modules is proposed in this paper.By studying the characteristics of outdoor photovoltaic modules affected by static temperature,cycle temperature,relative humidity and ultraviolet rays,we synthesized the dynamic stress function and used the cumulative loss model to model the performance degradation of photovoltaic power plants under multiple stresses,and used the genetic algorithm to extract unknown parameters of the model.The model has been trained and tested using long-term data from the US National Solar Radiation Database.The comparison results between the actual performance degradation and the calculated value of the model show that the model proposed in this paper has a lower relative error,which proves the feasibility of the proposed method.
photovoltaic power stationphotovoltaic degradationdata drivenoptimization algorithm
万方数据
维普
