Author
Listed:
- Elias Ojetunde
(Department of Accountancy, University of Dundee, Dundee DD1 4HN, UK)
- Olubayo Babatunde
(Department of Industrial Engineering, Durban University of Technology, Durban 4000, South Africa
Institute of Systems Science, Durban University of Technology, Durban 4000, South Africa)
- Busola Akintayo
(Department of Industrial Engineering, Durban University of Technology, Durban 4000, South Africa
Institute of Systems Science, Durban University of Technology, Durban 4000, South Africa)
- Adebayo Dosa
(Department of Industrial Engineering, Durban University of Technology, Durban 4000, South Africa
Institute of Systems Science, Durban University of Technology, Durban 4000, South Africa)
- John Ogbemhe
(Department of Systems Engineering, University of Lagos, Akoka 100213, Nigeria)
- Desmond Ighravwe
(Department of Industrial Engineering, Durban University of Technology, Durban 4000, South Africa
Institute of Systems Science, Durban University of Technology, Durban 4000, South Africa
Department of Mechanical Engineering, Bells University of Technology, Ota 112104, Nigeria)
- Olanrewaju Oludolapo
(Institute of Systems Science, Durban University of Technology, Durban 4000, South Africa)
Abstract
The shift towards renewable energy demands decision-making tools that unite economic performance with environmental stewardship and social equity. The conventional evaluation methods fail to consider these interconnected factors, which results in substandard investment results. The paper establishes a sustainability accounting system that uses the Elimination and Choice Expressing Reality (ELECTRE) method to optimize investment distribution between solar power, wind power, and bioenergy systems. The evaluation framework uses six performance indicators, which include cost efficiency and return on investment, together with CO 2 emissions intensity, job creation, energy output, and financial sustainability indicators, like Net Present Value (NPV) and payback period. The barrier optimization algorithm solved the model in 10 iterations, which took 0.10 s to achieve an optimal objective value of 1.6929. The wind energy source demonstrated superior performance in every evaluation criterion because it achieved the highest concordance scores, lowest discordance levels, best payback period, and strongest NPV. The maximum allocation went to wind at 53.3%, while bioenergy received 31.0%, and solar received 16.7%. The optimized portfolio reached a total sustainability index (SI) of 1.70, which validates the method’s strength. The research shows that using ELECTRE with sustainability accounting creates an exact and open system for renewable energy investment planning. The framework reveals wind as the core alternative yet demonstrates how bioenergy and solar work together to support sustainable development across environmental and economic and social dimensions.
Suggested Citation
Elias Ojetunde & Olubayo Babatunde & Busola Akintayo & Adebayo Dosa & John Ogbemhe & Desmond Ighravwe & Olanrewaju Oludolapo, 2025.
"ELECTRE-Based Optimization of Renewable Energy Investments: Evaluating Environmental, Economic, and Social Sustainability Through Sustainability Accounting,"
Sustainability, MDPI, vol. 17(23), pages 1-18, December.
Handle:
RePEc:gam:jsusta:v:17:y:2025:i:23:p:10872-:d:1810694
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