An extension of best-worst method with D numbers: Application in evaluation of renewable energy resources

Mousavi-Nasab, Seyed Hadi; Sotoudeh-Anvari, Alireza

doi:10.1016/j.seta.2020.100771

Cited by 25 publications

(9 citation statements)

References 108 publications

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“…WPM was created to prevent options with low attribute values. It computes the score of each choice as a product of the scale rating of each attribute's strengths multiplied by the importance weight of that attribute [27].…”

Section: Waspas Methodsmentioning

confidence: 99%

Spherical Fuzzy Multicriteria Decision-Making Model for Wind Turbine Supplier Selection in a Renewable Energy Project

2022

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The Vietnamese government has decided to use and promote the development of more renewable energy sources, particularly wind energy. When implementing a wind energy project, choosing a wind turbine supplier is an important decision and investors must find the optimal supplier through evaluating many qualitative and quantitative criteria that affect each other symmetrically. Therefore, the process used for selecting a wind turbine supplier in wind power projects is a multi-criteria decision-making process. Many approaches have been applied for this decision process, some of which are based on multicriteria decision-making (MCDM) methods, whether applied individually or in combination with other MCDM models. In this study, the researchers proposed a decision-making model based on spherical fuzzy sets for wind turbine supplier selection in wind power energy projects. In this paper, Vietnam is used as a case study. The recommended turbine suppliers for installations can finally be generated after the calculations in the final stage of this research. The contribution of this research is developing a fuzzy MCDM model for suitable turbine suppliers in wind power energy projects. The results of this study can be used as references for experts in deciding on a suitable wind turbine supplier in other countries as well as in other renewable energy projects.

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Section: Waspas Methodsmentioning

confidence: 99%

Spherical Fuzzy Multicriteria Decision-Making Model for Wind Turbine Supplier Selection in a Renewable Energy Project

2022

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“…This is because the entire degree of influence between indicators is determined by a mixed relationship rather than simply sum of the intensity of influence ( Michnik, 2013 ). So far, it has been utilized in green building development( Wang et al, 2021 ), automotive industry( Kaviani et al, 2020 ), technology projects( Hadi Mousavi-Nasab & Sotoudeh-Anvari, 2020 ).…”

Section: Literature Reviewsmentioning

confidence: 99%

An integrated rough-fuzzy WINGS-ISM method with an application in ASSCM

Wang

Zhang²,

Tian³

et al. 2023

Expert Systems with Applications

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“…However, according to the Renewable Energy and Energy Efficiency Organization (SATBA)'s report in October 2020, 838.18 MW of renewable energy had been installed [27]. Despites this, Iran possesses favorable geography for RESs and a high potential from them due to the country's location in the solar belt [28]. Therefore, North Khorasan province, one of the youngest provinces in Iran, was selected as a study area [29].…”

Section: Introductionmentioning

confidence: 99%

Implementing MCDM Techniques for Ranking Renewable Energy Projects under Fuzzy Environment: A Case Study

et al. 2021

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Energy requirements have increased dramatically due to industrialization, economic, and population growth. To meet this demand, and solve its challenges, such as climate change, renewable energies do play an important role. This research work aims at selecting the best renewable energy projects using a hybrid decision-making framework from environmental, economic, technical, and social aspects at a sub-national level. In this regard, a new hybrid fuzzy multi-criteria decision-making model is deployed in which Vise Kriterijumska Optimizacija I Kompromisno Resenje, distance from average solution, and additive ratio assessment methods are used. In addition, for the weighing of criteria, Fuzzy Shannon’s entropy is used. Furthermore, the North Khorasan province is nominated as a sub-national study area. The results show that among 30 sub-criteria, social acceptance, net-presented cost, and noise were the top three with weights of 0.1105, 0.1003, and 0.0988, respectively. Solar energy projects also accomplished high ranks with an overall score of roughly 0.22. After that, small hydropower got second place with a score of 0.187. Moreover, the ranking of cities indicates that Jajarm was the most suitable location for implementing renewable energy development with a score of 0.14. Finally, sensitivity analysis was carried out to show that the mathematical model possessed good robustness.

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An extension of best-worst method with D numbers: Application in evaluation of renewable energy resources

Cited by 25 publications

References 108 publications

Spherical Fuzzy Multicriteria Decision-Making Model for Wind Turbine Supplier Selection in a Renewable Energy Project

Spherical Fuzzy Multicriteria Decision-Making Model for Wind Turbine Supplier Selection in a Renewable Energy Project

An integrated rough-fuzzy WINGS-ISM method with an application in ASSCM

Implementing MCDM Techniques for Ranking Renewable Energy Projects under Fuzzy Environment: A Case Study

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