Forecasting of Solar Irradiance using Probability Distributions for a PV System: A Case Study

RAMI REDDY CH, Dukkipati Sudha, P Srinivasa Varma, V Sankar

Abstract


Photo Voltaic (PV) generation is intermittent which cannot carry out the constant electric power. The amount of solar irradiance received for a particular area is one of the most important climatic conditions for forecasting PV generation. The solar irradiance data used for analysis is collected from Koneru Lakshmaiah Education Foundation (KLEF) and the data is collected for the year (2017-18). In this paper, four Probability Distribution Functions (PDFs) such as Normal, Weibull, Rayleigh, Log normal are used to investigate the best fit probability distribution of the collected solar irradiance data. Root Mean Square Error (RMSE) method is used as a goodness of fit test for identifying the best suited probability distribution function for the collected solar irradiance data. With this analysis, solar irradiance and PV power generation can be predicted for the next year. The efficacy of the proposed method is validated using MATLAB.


Keywords


Probability Distribution Function, Solar irradiance, Monte Carlo Simulation, Root Mean Square Error (RMSE).

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DOI (PDF): https://doi.org/10.20508/ijrer.v9i2.9216.g7643

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