Orthogonal Regression Analyses of solar Irradiation and DC Power Data

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Abstract

The rapid deployment of solar photovoltaic cells in recent times is enablingdata analysis of renewable energy solar source and its conversion to electrical energy. The need for estimating the capacityofSolar irradiation and solar DC power in any geographical location is necessary for short-term and long-term forecasting. In this paper a regression-based data analysis is carried out at different locations in India and analyze the residue for better fit. Here solar DC power is a dependent output variable and solar irradiance is an independent predictor. The orthogonal regression is a standard linear regression technique involves in reducing the sum of squared orthogonal projections. The primary goal of this paper is to analyze orthogonal regression technique withthe relationship between response (DC power data) and predictor (solar irradiation) across different diverse locations. The fitted value for the solar irradiance accounts for the uncertainty in the value of the predictor.The study of nonlinear nature of solar irradiation and DC power generated across geographically dispersed sites for a time series data leads to better estimate of solar power.

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H.H.*, Mr. S., D, Mr. S., & K.R., Mr. S. (2020). Orthogonal Regression Analyses of solar Irradiation and DC Power Data. International Journal of Innovative Technology and Exploring Engineering, 9(4), 175–180. https://doi.org/10.35940/ijitee.d1438.029420

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