Renewable energy optimization for sustainable power generation
Abstract
To improve sustainability in power generation, this study presents a thorough data-driven method for maximizing renewable energy sources. It employs measures like capacity utilization factor (CUF) and efficiency to evaluate the performance of solar and wind energy using historical weather and energy-generating data. The study offers practical suggestions for improving renewable energy systems, such as weather-energy correlation analysis and machine learning-based forecasting models. In addition, a comparative analysis is carried out to ascertain which energy source is better, and useful real-world data is provided, including a summary of all India’s total renewable energy generation (excluding large hydro) for June 2023 and a performance comparison year over year. A useful, data-driven approach for enhancing renewable energy is provided by this work, which advances the topic of sustainable energy.
Keywords
Capacity utilization factor; Machine learning; Optimization; Power generation; Renewable energy; Sustainability; Weather-energy correlation
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PDFDOI: http://doi.org/10.11591/ijict.v15i1.pp365-373
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Copyright (c) 2026 Debani Prasad Mishra, Sarita Samal, Rohit Kumar, Arun Kumar Sahoo, Surender Reddy Salkuti
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The International Journal of Informatics and Communication Technology (IJ-ICT)
p-ISSN 2252-8776, e-ISSN 2722-2616
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).