Fuzzy DEA Model with Exogenously Fixed Variables for Ranking of Renewable Energy Sources

Jyoti Luhaniwal (), Shivi Agarwal () and Trilok Mathur ()
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Jyoti Luhaniwal: Birla Institute of Technology and Science, Pilani
Shivi Agarwal: Birla Institute of Technology and Science, Pilani
Trilok Mathur: Birla Institute of Technology and Science, Pilani

A chapter in Advances in the Theory and Practice of Data Envelopment Analysis, 2025, pp 251-266 from Springer

Abstract: Abstract As the global population grows, so does the demand for energy. India, with its fast growth, industrialization, and urbanization, is struggling to meet energy needs using traditional sources. To tackle energy shortages, pollution, and climate change, it’s important to find cost-effective and environment friendly alternatives. Renewable energy sources (RESs) offer a promising solution, making it important to prioritize them. India has strong potential in technologies like solar, geothermal, hydro, biomass, wave energy, and onshore and offshore wind energy. However, prioritizing these energy options involves considering many factors, often with conflicting priorities. This study proposed a fuzzy Data Envelopment Analysis (DEA) method to prioritize renewable energy sources in India, considering exogenously fixed variables that can’t be controlled, and handling undesirable variables. The proposed model ranks RESs effectively. It is revealed from results that Offshore wind energy is found to be the most efficient, followed by onshore wind and hydro energy, while geothermal energy ranks the lowest. The proposed methodology and findings can help developing nations and policymakers make better decisions when adopting renewable energy sources.

Keywords: Sustainable development; Renewable energy sources; Fuzzy Data envelopment analysis (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-98177-7_17

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