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

Published: 15 November 2022 Publication History

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Highlights

A new decision making method for selection problems under uncertainty is proposed.
The method considers both the objective weights and the subjective preferences.
The method is applied to the selection of renewable energy technologies.
The best option varies depending on the coefficient factor of the subjective weight.
The method is applicable to other selection problems in different areas.

Abstract

The use of renewable energy technologies is a key factor for sustainable development but their selection from several alternatives is a difficult task that relies on the careful assessment of relevant criteria. While Multiple Criteria Decision Making (MCDM) methods have been used successfully in various renewable energy technology selection problems, the decision process becomes more challenging when preferential judgements are made on the basis of non-homogenous and imprecise input data, and when there is uncertainty due to disparities among decision makers. This paper presents a hybrid MCDM method capable of overcoming these problems by taking into account quantitative and qualitative data under a probabilistic environment in the context of group decision making. In this method, qualitative data is fuzzified and used along with quantitative data to develop a hybrid model. A coefficient factor allows decision makers to vary the weight of each quantitative model so that the resultant criteria weights and overall alternatives’ scores consider both subjective considerations and objective information. An example is presented to showcase the usability of the method developed for ranking and evaluating renewable energy technologies in the mining industry. In addition, the impact of different coefficient factors on the final results was assessed by means of sensitivity analysis. The results indicate that the method developed is able to minimise the loss of valuable objective information, caused by the subjective bias of qualitative weights during the evaluations, by adjusting the coefficient factors of the hybrid model during the calculations.

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            Published In

            cover image Expert Systems with Applications: An International Journal
            Expert Systems with Applications: An International Journal  Volume 206, Issue C
            Nov 2022
            1603 pages

            Publisher

            Pergamon Press, Inc.

            United States

            Publication History

            Published: 15 November 2022

            Author Tags

            1. AHP
            2. CSP
            3. FAHP
            4. GHG
            5. IC-FSAHP
            6. LEC
            7. MCDM
            8. NV
            9. OW
            10. PV
            11. SE
            12. TFN
            13. WSM
            14. gCO2eq/kWh
            15. m2/kW
            16. $/MWh
            17. Jobs/annual GWh

            Author Tags

            1. Renewable energy technologies
            2. Multiple criteria decision making (MCDM)
            3. Uncertainty
            4. Mining industry

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            • (2024)A novel evaluation method for renewable energy development based on improved sparrow search algorithm and projection pursuit modelExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.122991244:COnline publication date: 15-Jun-2024
            • (2024)Classification-based consensus model considering quantum interference in linguistic distribution environmentComputers and Industrial Engineering10.1016/j.cie.2024.110658198:COnline publication date: 1-Dec-2024
            • (2023)An integrated simulation and AHP-entropy-based NR-TOPSIS method for automated container terminal layout planningExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.120197225:COnline publication date: 1-Sep-2023

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