A Fuzzy Multi-Criteria Approach for Selecting Sustainable Power Systems Simulation Software in Undergraduate Education

Olubayo Babatunde (), Michael Emezirinwune, John Adebisi, Khadeejah A. Abdulsalam, Busola Akintayo and Oludolapo Olanrewaju
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Olubayo Babatunde: Department of Industrial Engineering, Durban University of Technology, Durban 4001, South Africa
Michael Emezirinwune: Department of Electrical Electronics Engineering, University of Lagos, Nigeria 100213, South Africa
John Adebisi: Division of Engineering & Technology, The University of West Alabama, Livingston, AL 35470, USA
Khadeejah A. Abdulsalam: Department of Electrical Electronics Engineering, University of Lagos, Nigeria 100213, South Africa
Busola Akintayo: Department of Industrial Engineering, Durban University of Technology, Durban 4001, South Africa
Oludolapo Olanrewaju: Department of Industrial Engineering, Durban University of Technology, Durban 4001, South Africa

Sustainability, 2024, vol. 16, issue 20, 1-22

Abstract: Selecting the most preferred software for teaching power systems engineering at the undergraduate level is a complex problem in developing countries, and it requires making an informed decision by compromising on various criteria. This study proposes a multi-criteria framework to determine the most preferred software solution for instructing undergraduate power system modules using the Fuzzy-ARAS (additive ratio assessment) method and expert opinions. Twelve evaluation criteria were used to evaluate eight widely used software packages. A questionnaire was designed to capture views from professionals in academia and industry on the criteria weights and ranking of software options. Linguistic terms were used to represent the experts’ judgment, and weights were assigned to each criterion. The Fuzzy-ARAS multi-criteria decision approach was applied to obtain ratings for each software alternative. Based on the result, MATLAB emerged as the most preferred software for instructing power systems analysis, whereas MATPOWER (V 8.0) was rated as the least preferred choice. In addition, the Fuzzy-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach was used, producing a separate ranking; the most preferred software was MATPOWER, while the least preferred software was NEPLAN (V 360 10.5.1). A new coefficient that combines the findings of the two approaches was suggested to reconcile the ranks. The combined ranking aligns with the result of the Fuzzy-TOPSIS method by returning MATLAB as the most preferred, while the least preferred software was NEPLAN. This study significantly contributes to the choice of software for undergraduate power systems analysis instruction by providing direction to educators and institutions looking for software solutions to improve undergraduate power systems analysis education.

Keywords: multi-criteria decision-making (MCDM); Fuzzy-ARAS; Fuzzy-TOPSIS; power systems; software selection; MATLAB (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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