Prioritizing the existing power generation technologies in Bangladesh’s clean energy scheme using a hybrid multi-criteria decision making model

Ali, Tausif; Chiu, Yie-Ru; Aghaloo, Kamaleddin; Nahian, Ahmed Jaudat; Ma, Hongzhong

doi:10.1016/j.jclepro.2020.121901

Cited by 43 publications

(22 citation statements)

References 30 publications

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“…They found that hydro was the best option for Taiwan, followed by solar, wind, biomass and geothermal. Ali et al ( 2020 ) used a subjective weighting method (BWM) and objective method (integrated determination of objective criteria weights (IDOCRIW)) and an evaluation based on distance from average solution (EDAS) to rank power generation technologies in Bangladesh. Additionally, a comparative analysis was conducted through three MADM methods, namely combinative distance-based assessment (CODAS), weighted aggregated sum product assessment (WASPAS), and multiobjective optimization based on simple ratio analysis (MOOSRA).…”

Section: Resultsmentioning

confidence: 99%

A comprehensive analysis of weighting and multicriteria methods in the context of sustainable energy

Şahin

2020

Int. J. Environ. Sci. Technol.

115

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This study presents a comprehensive and comparative analysis of weighting and multiple attribute decision-making (MADM) methods in the context of sustainable energy. As the selection problems of energy involve various conflicting attributes, MADM methods have been widely applied in addressing these issues. In this study, six weighting and seven MADM methods that constitute a total of 42 models are implemented to evaluate different weighting and multicriteria decision-making methods and determine the most efficient and sustainable energy option. To determine the weights of economic, environmental, socioeconomic, and technical attributes, two subjective methods-the analytic hierarchy process and best-worst method-and four objective methods-the criteria importance through intercriteria correlation, Shannon's entropy, standard deviation, and mean weight-are used. Thus, both expert evaluations and data-based assessments are considered. Using each attribute weight provided by the six methods, the ranking of electricity generation options for Turkey is obtained through seven MADM methods: the elimination and choice expressing the reality method, the weighted sum method, the weighted product method, the organization, rangement et synthese de donnes relationnelles (ORESTE) method, the technique for order performance by similarity to the ideal solution, the preference ranking organization method for the enrichment of evaluations, and the multiple criteria optimization compromise solution. Rankings obtained from all models are integrated through the Borda, Copeland, and grade average methods. The results indicate that hydro is the optimal electricity generation option, followed by onshore wind, solar PV, geothermal, natural gas, and coal.

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Section: Resultsmentioning

confidence: 99%

A comprehensive analysis of weighting and multicriteria methods in the context of sustainable energy

Şahin

2020

Int. J. Environ. Sci. Technol.

115

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“…Zavadskas et al (2017) introduced the IDOCRIW method which brings the complementarity of entropy and CILOS methods into play and aggregates their weights to offset the shortcomings of one method by the advantages of the other one (Zavadskas et al , 2017; Čereška et al , 2016). Since the IDOCRIW method is recently introduced and applied (Zavadskas et al , 2017; Trinkūnienė et al , 2017; Podvezko et al , 2017; Čereška et al , 2018; Ali et al , 2020), there is no study in the literature addressing the applying of fuzzy set theory to the IDOCRIW method to handle the vagueness and uncertainty resulted from the linguistic terms of expressing experts' opinion and knowledge. Thus, this paper updates the IDOCRIW method with the fuzzy set theory for the first time as follows: in the proposed fuzzy IDOCRIW, the first five steps represent the fuzzy Shannon's entropy (Lotfi and Fallahnejad, 2010) and the second five steps calculate the weights from the fuzzy CILOS method and finally, in the last step, the outputs of these two techniques are combined.…”

Section: Proposed Methodologymentioning

confidence: 99%

Prioritizing the effective strategies for construction and demolition waste management using fuzzy IDOCRIW and WASPAS methods

Eghbali-Zarch

Tavakkoli–Moghaddam

Dehghan-Sanej

et al. 2021

ECAM

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PurposeThe construction industry is a key driver of economic growth. However, the adverse impacts of construction and demolition waste (CDW) resulted from the active construction projects on the economy, environment, public health and social life necessitates an appropriate control and management of this waste stream. Developing and promoting the construction and demolition waste management (CDWM) hierarchy program at the strategic level is essential.Design/methodology/approachThis study aims to propose a hybrid decision model that hybridizes the Integrated Determination of Objective Criteria Weights (IDOCRIW) and weighted aggregated sum product assessment (WASPAS) under a fuzzy environment.FindingsThe proposed method ranks the potential strategic alternatives by the sustainable development criteria to improve the performance of CDWM. As indicated in the results, the fuzzy approach in the decision-making process enables the transformation of linguistic variables into fuzzy numbers that show uncertainty and ambiguity in real-world systems. Moreover, the close correlation between the final ranking of the proposed methodology and the average priority order of the strategic alternatives obtained by five different multi-criteria decision-making (MCDM) methods implies the validity of the model performance.Practical implicationsThis proposed model is an appropriate tool to effectively decide on the development of CDWM from a strategic point of view. It aims to establish an MCDM framework for the evaluation of effective strategies for CDWM according to the indices of sustainable development. Implementing proper operational plans and conducting research in CDWM has the highest priority, and enacting new and more stringent laws, rules and regulations against the production of CDW has secondary priority. This study contributes to the field by optimizing the CDWM by applying the top-priority strategies resulted from the proposed fuzzy hybrid MCDM methodology by the decision-makers or policy-makers to reach the best managerial strategic plan.Originality/valueIn the proposed methodology, the IDOCRIW technique is utilized and updated with the triangular fuzzy numbers for the first time in the literature to derive the weights of sustainable development criteria. The fuzzy WASPAS method is utilized for evaluation and providing a final ranking of the strategic alternatives.

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“…This parameter has a range for different technologies and in this study the average value of the reported values is used. The energy efficiencies of solar photovoltaic, wind energy, nuclear energy, and biomass have been extracted from [65,66].…”

Section: Efficiencymentioning

confidence: 99%

“…Each power generation system, due to its nature, can provide service over a certain period of time and it is clear that over time the probability of failure of a system increases. The average lifetime data for solar photovoltaic and wind technologies are derived from [65] and for nuclear and biomass technologies from [26].…”

Section: Lifetimementioning

confidence: 99%

Comparative Analysis of Five Widely-Used Multi-Criteria Decision-Making Methods to Evaluate Clean Energy Technologies: A Case Study

et al. 2022

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Over the last decade, the total primary energy consumption has increased from 479 × 1015 BTU in 2010 to 528 × 1015 BTU in 2020. To address this ever-increasing energy demand, as well as prevent environmental pollution, clean energies are presented as a potential solution. In this regard, evaluating and selecting the most appropriate clean energy solution for a specific area is of particular importance. Therefore, in this study, a comparative analysis in Jiangsu province in China was performed by describing and implementing five prominent multi-criteria decision-making methods in the field of energy technology selection, including SAW, TOPSIS, ELECTRE, VIKOR, and COPRAS. The decision problem here consists of four clean energy options, including solar photovoltaic, wind, nuclear, and biomass, which have been evaluated by twelve basic and important criteria for ranking clean energy options. The obtained results, according to all five MCDM methods, indicate that solar photovoltaic was the optimal option in this study, followed by wind energy. The nuclear and biomass options placed third and fourth, respectively, except in the ELECTRE method ranking, in which both options scored the same and thus neither was superior. Finally, by conducting a comprehensive two-stage sensitivity analysis, in the first stage, it was found that changes in the weights of land use and water consumption criteria had the greatest impact on the performance of options, among which biomass and nuclear showed high sensitivity to variations in criteria weights. In the second stage, by defining five scenarios, the ranking of options was evaluated from different aspects so that the decision maker/organization would be able to make appropriate decisions in different situations.

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Prioritizing the existing power generation technologies in Bangladesh’s clean energy scheme using a hybrid multi-criteria decision making model

Cited by 43 publications

References 30 publications

A comprehensive analysis of weighting and multicriteria methods in the context of sustainable energy

A comprehensive analysis of weighting and multicriteria methods in the context of sustainable energy

Prioritizing the effective strategies for construction and demolition waste management using fuzzy IDOCRIW and WASPAS methods

Comparative Analysis of Five Widely-Used Multi-Criteria Decision-Making Methods to Evaluate Clean Energy Technologies: A Case Study

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