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Reliable energy prediction method for grid connected photovoltaic power plants situated in hot and dry climatic condition
Published in Springer Nature
Volume: 2
Issue: 3
This paper presents a mathematical model to predict the energy generation of photovoltaic power plant in hot and humid climatic condition. This model is based on meteorological data and laboratory tested solar module parameters with twenty-four inputs and one output. In addition the twenty-four inputs drive an equation to calculate final energy generation from photovoltaic power plant. Validation of the proposed model was done by comparing the results of predicted energy generation using proposed model and PVWATT software model for two existing PV power plants of India. Monthly and annual energy production and errors will be the main criteria for the selection of batter model. The result shows that in comparison with PVWATT software proposed model was found to be more efficient and accurate to predict energy generation and proposed model also reduces mean absolute percentage error and root mean square error significantly compared to PVWATT software for hot and humid climatic condition. © 2020, Springer Nature Switzerland AG.
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JournalData powered by TypesetSN Applied Sciences
PublisherData powered by TypesetSpringer Nature