Mathematical optimization of renewable energy systems for sustainable development
Volume 3, Issue 1, Article Number: 261006 (2026)
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Garima Singh1,* 
1Department of Science and Humanities, Poornima University, Jaipur – 303905 (India)
*Corresponding Author: garu.bittu@gmail.com
Received: 04 May 2026 | Revised: 20 May 2026
Accepted: 29 May 2026 | Published Online: 22 June 2026
DOI: https://doi.org/10.5281/zenodo.20551819
© 2026 The Authors, under a Creative Commons license, Published by Scholarly Publication
Abstract
Due to the growing worldwide need for renewable energy sources, Renewable Energy Systems (RES) have been rapidly developed and deployed in response to global needs for cleaner energy and environmental damage from the use of fossil fuels. However, the inherent variability and uncertainty associated with renewable energy resources create significant challenges to RES planning, integration of RES into the overall energy system, and management of the RES. This overview examines the various types of mathematical optimization methodologies that have been applied to RES; it examines deterministic classical methods, stochastic approaches to optimizing RES, heuristics and metaheuristic algorithms, and artificial intelligence (AI) solutions through a systematic examination according to a structured taxonomy. The overall critical review describes the strength and weakness of optimization methodologies and provides an assessment of the computing resources available for each type of optimization method, describes the techniques for quantifying uncertainty, explains the principles and techniques used in probabilistic forecasting, and addresses the real-world deployment challenges associated with RES including regulatory, economic, financial, and infrastructure barriers. The overview also describes in detail hybrid renewable energy systems (HRES), multi-objective optimization methods, integration of energy storage systems, and smart grid optimization processes utilizing supporting comparison tables and illustrative examples. The review outlines areas for future research by suggesting using innovations such as Digital Twins, Explainable AI, Federated Learning, and Blockchain technologies for enhancing energy systems management. This review distinguishes itself from previous literature in that it synthesizes findings from multiple optimization paradigms and bridges the gap between theoretical modeling and practical implementation challenges.
Keywords
Renewable Energy Systems, Mathematical Optimization, Sustainable Development, Linear Programming, Stochastic Optimization, Hybrid Energy Systems
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Cite This Article
G. Singh, “Mathematical optimization of renewable energy systems for sustainable development,” Radius: Journal of Science and Technology 3(1) (2026) 261006. https://doi.org/10.5281/zenodo.20551819
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