The selection of renewable energy technologies using a hybrid subjective and objective multiple criteria decision making method

Sitorus, Fernando; Brito-Parada, Pablo R.

doi:10.1016/j.eswa.2022.117839

Cited by 29 publications

(9 citation statements)

References 54 publications

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“…In the subjective weighting methods, the criteria weights and the alternatives’ scores mainly depend on the decision makers’ judgements and preferences via pairwise comparisons, the potential uncertainty of which is considered the prime disadvantage of the subjective methods (Sahoo et al 2016 ; Sitorus and Brito-Parada 2022 ). As a subjective weighting method, the ordered binary comparison method combines qualitative ranking and quantitative scaling, aiming to distinguish the importance of factors by repeatedly comparing every two factors to identify the ranks and weights of factors.…”

Section: Methodsmentioning

confidence: 99%

Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China

et al. 2022

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Extremely heavy rainfall has posed a significant hazard to urban growth as the most common and disaster-prone natural calamity. Due to its unique geographical location, the metro system is more vulnerable to waterlogging caused by rainstorm disaster. Research on resilience to natural disasters has attracted extensive attention in recent years. However, few studies have focused on the resilience of the metro system against rainstorms. Therefore, this paper aims to develop an assessment model for evaluating metro stations’ resilience levels. Twenty factors are carried out from dimensions of resistance, recovery and adaptation. The methods of ordered binary comparison, entropy weight and cloud model are proposed to build the assessment model. Then, taking Chongqing metro system in china as a case study, the resilience level of 13 metro stations is calculated. Radar charts from dimensions of resistance, recovery, and adaptation are created to propose recommendations for improving metro stations’ resilience against rainstorms, providing a reference for the sustainable development of the metro system. The case study of the Chongqing metro system in china demonstrates that the assessment model can effectively evaluate the resilience level of metro stations and can be used in other infrastructures under natural disasters for resilience assessment.

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Section: Methodsmentioning

confidence: 99%

Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China

et al. 2022

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“…Çolak and Kaya [46] proposed an integrated MCDM model, which combines the fuzzy analytic hierarchy process (FAHP) and fuzzy TOPSIS method to prioritize the renewable energy alternatives in Turkey. Sitorus and Brito-Parada [47] used the hybrid MCDM method to select renewable energy technologies by considering both subjective and objective multiple criteria. Ullah et al [48] used an integrated model by combining fuzzy AHP, fuzzy TOPSIS, fuzzy EDAS, and fuzzy MOORA to plan the on/off grid hybrid renewable energy supply.…”

Section: Renewable Energy Technology Selection and Mcdmmentioning

confidence: 99%

Alleviating Energy Poverty through Renewable Energy Technology: An Investigation Using a Best-Worst Method-Based Quality Function Deployment Approach with Interval-Valued Intuitionistic Fuzzy Numbers

Zhou

Ren

2023

International Journal of Energy Research

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Renewable energy technology is suitable for reducing energy consumption and emissions, and the corresponding impact on energy poverty has aroused tremendous attention. This paper proposed the best-worst method- (BWM-) based quality function deployment (QFD) approach within interval-valued intuitionistic fuzzy number (IVIFN) to select the appropriate renewable energy technology for energy poverty alleviation. QFD is firstly used to explore the relationship between energy poverty reduction requirements (CRs), renewable energy technology selection criteria (TRs), and correlation among TRs. Interval-valued intuitionistic fuzzy (IVIF) BWM is then applied for obtaining the correlation among CRs. After that, the IVIF-QFD method is used to attain the weight of TRs, which are then used to evaluate the renewable energy technology alternatives through IVIF-VIKOR approach. The six representative renewable energy technologies, including wind energy, solar energy, biomass (direct combustion, combined heat and power, and gasification), and hydropower have been selected in the decision model, and the result shows that the large-scale hydropower could be selected as the best choice to reduce the energy poverty issues, whose interval numbers is [0, 0.2925]. Except for prioritization of the selected technologies, findings of this paper could also contribute to developing sustainable renewable energy policies and energy roadmaps.

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“…Estimating the objective weights of disaster preparedness criteria is beneficial as it can overcome the problem of an exclusive focus on the subjective disaster preparedness criteria. However, in line with Sitorus and Parada (2022), a hybrid subjective and objective disaster preparedness dimension weightage approach is a more effective approach because it allows for gauging both the decision-makers’ preferences and the objective information contained in the disaster dimensional preparedness data. The composite of weight criteria Uji, which presents the combination of subjective weight YjS and objective weight VjO can be obtained from the following mathematical expression:…”

Section: Integrating Statistical Variance and Piv – The Proposed Modelmentioning

confidence: 99%

Disaster readiness assessment model using integrated statistical variance and proximity value index

Sutrisno

Wuisang

Yusupa

2023

IJES

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PurposeThe regular occurrence of natural disasters elevates the need for an effective method to measure organizational preparedness in responding to the adverse impact of disasters. In this context, this paper presents a new decision support model to assess organizational disaster preparedness using both subjective and objective disaster preparedness criteria in a multi-criteria decision-making context.Design/methodology/approachThe statistical variance method is integrated with the proximity value index (PVI) technique to determine priority scores in order to rank organizational disaster readiness.FindingsThe results of applying the integrated model developed herein enable decision-makers to make informed decisions for assigning priority ranking of organizational disaster preparedness in a simpler and more efficient way.Research limitations/implicationsHuman resource is the most impacting criterion affecting hospital preparedness in undertaking action to cure disaster victims.Practical implicationsThis paper offers an exemplar of a simple and efficient decision-making process considering the subjectivity associated with decision-making as well as the objectivity of data used for determining the priority ranking of organizational disaster preparedness.Originality/valueIntegrating statistical variance method with the PVI technique is novel and it has not been presented in previous studies. In fact, this study is the first to integrate both methods for selecting the priority ranking of organizational disaster preparedness.

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The selection of renewable energy technologies using a hybrid subjective and objective multiple criteria decision making method

Cited by 29 publications

References 54 publications

Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China

Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China

Alleviating Energy Poverty through Renewable Energy Technology: An Investigation Using a Best-Worst Method-Based Quality Function Deployment Approach with Interval-Valued Intuitionistic Fuzzy Numbers

Disaster readiness assessment model using integrated statistical variance and proximity value index

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