Regression analysis of solar power generation with meteorological variables

Authors

Lea Angela M. Saure ⋅ PH Department of Physical Sciences, Polytechnic University of the Philippines
Rosenel T. Dahipon ⋅ PH Department of Physical Sciences, Polytechnic University of the Philippines
Victor Angelo Asuncion ⋅ PH Ensky Corporation, Philippines
Rhenish C. Simon ⋅ PH Physics Department, De La Salle University

Abstract

We formulated a Principal Correlation Regression model to estimate Solar Energy generation in Quezon City. The variability of the energy generated by the PV modules is associated with the meteorological variables using the model. The meteorological parameters used are daily Temperature (Average, Minimum, and Maximum), Rainfall, and Relative Humidity from June 1, 2017 to December 31, 2019. Our results suggest that the model can explain 15.33% variation of the Actual Value. Generating an effective model can assist in the efficient and economic use of Solar Photovoltaic technology in the Philippines.

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Issue

2022: Proceedings of the 40th Samahang Pisika ng Pilipinas Physics Conference

Physics 2.0.2022: Renormalizing uncertainties with Physics
19-21 October 2022, Legazpi City

Please visit the SPP2022 activity webpage for more information on this year's Physics Congress.

Article ID

SPP-2022-PB-19

Section

Poster Session B (Complex Systems, Simulations, and Theoretical Physics)

Published

2022-10-02

How to Cite

[1]

LAM Saure, RT Dahipon, VA Asuncion, and RC Simon, Regression analysis of solar power generation with meteorological variables, Proceedings of the Samahang Pisika ng Pilipinas 40, SPP-2022-PB-19 (2022). URL: https://proceedings.spp-online.org/article/view/SPP-2022-PB-19.