Harnessing Solar Power at peak efficiency through Prediction Modeling

Anant Aggarwal

Abstract


This research paper aims to address the need for optimizing solar power production by developing prediction models for three important solar irradiance parameters: Clearsky DHI (Diffuse Horizontal Irradiance), Clearsky DNI (Direct Normal Irradiance), and Clearsky GHI (Global Horizontal Irradiance). The dataset used in this study spans a period of ten years, collected at a 30-minute interval, and includes various meteorological and environmental parameters. By accurately predicting these solar irradiance components, a solar power generation company can enhance the efficiency and effectiveness of their operations, leading to improved energy yield and cost savings. This paper explores the development and evaluation of prediction models using the dataset, focusing on machine learning techniques and statistical analysis.


Keywords


solar power production, optimization, prediction model, Clearsky DHI, Clearsky DNI, Clearsky GHI, solar irradiance, machine learning, statistical analysis.

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