• Rahul Pathak
• Mohd. SaquibFaraz
• Mayank Jain

The objective of this work is to ascertain whether reliable prediction of Global Horizontal Irradiance (GHI) is attainable using predictor variables: wind speed, wind direction, temperature, relative humidity, solar zenith angle, date of year and time. Multivariate backward stepwise linear regressions was utilized to determine significant attributes for GHI estimation. The model was then used to predict value of GHI. The performance of models was investigated using model residuals. The resulting model could explain 67% of variation in data. The model was further tested for multicollinearity and heteroscedasticity. The model gives satisfactory VIF and MAPE values and nominal heterosdasticity. R computation platform was used for modeling and computation.

Multicollinearity, Heteroscdasticity, Linear regression, Variable inflation factor

"Irradiance Prediction Model with Step wise Backward Linear Regression", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.15-20, June-2019, Available :http://www.jetir.org/papers/JETIRCO06004.pdf

"Irradiance Prediction Model with Step wise Backward Linear Regression", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp15-20, June-2019, Available at : http://www.jetir.org/papers/JETIRCO06004.pdf