Prediction of Solar Energy Production Quantity Using AR GES Enerji retim Miktarinin AR ile Kestirimi


Alici O., Agi T., ATASOY A.

2023 Innovations in Intelligent Systems and Applications Conference, ASYU 2023, Sivas, Turkey, 11 - 13 October 2023 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/asyu58738.2023.10296719
  • City: Sivas
  • Country: Turkey
  • Keywords: solar energy, statistics and machine learning, stepwise regression
  • Karadeniz Technical University Affiliated: Yes

Abstract

Studies related to energy efficiency in solar power plants generally focus on strategies to enhance the performance of solar energy systems, factors influencing the efficiency of solar panels, and various methods for optimizing energy production. In this study, a stepwise regression analysis was employed to predict the amount of energy generated in solar power plants. Independent variables such as weather conditions, ambient temperature, and panel efficiency were examined for their impact on energy production. Stepwise regression was used to model this relationship in a step-by-step manner. The purpose of the study is to analyze the impact of relevant independent variables on energy production and to present the estimation of the most optimal prediction model based on these analysis results.