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Performance Evaluation of Hydro Power Projects in India Using Multi Criteria Decision Making Methods

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Języki publikacji
EN
Abstrakty
EN
In the contemporary period of the green economy, energy planning has grown more complicated due to the inclusion of numerous standards, including technical, social, economic, and environmental. This, in turn, restricts the ability of decision-makers to make the most efficient use of energy resources. In addition, the difficulty of energy planning is exacerbated by topographical restrictions on renewable energy systems, the majority of which are found in nature. Based on factors such as total installed capacity, total reservoir capacity, total surface capacity, the height, length, number of units, and the cost of the dam were used to determine the finest hydro power project in India, according to this study. For performance evaluation, multi criteria decision making (MCDM) techniques like analytic hierarchy process (AHP) and TOPSIS (technique for order reference by similarity to ideal solution) are used in conjunction with VIKOR (vlekriterijumsko kompromisno rangiranje) for performance evaluation. AHP is used to calculate the weights of each criteria. The TOPSIS and VIKOR methods will utilise these weights to choose the optimal option. For the purpose of demonstrating the approaches’ applicability, an in-depth case study of various hydropower facilities in India was carried out.
Twórcy
  • Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam 532127, Srikakulam, Andhra Pradesh, India
  • Department of Electrical Electronics and Communication Engineering, GITAM, Rushikonda 530045, Visakhapatnam, Andhra Pradesh, India
  • Department of Electrical Electronics and Communication Engineering, GITAM, Rushikonda 530045, Visakhapatnam, Andhra Pradesh, India
  • Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam 532127, Srikakulam, Andhra Pradesh, India
  • Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam 532127, Srikakulam, Andhra Pradesh, India
Bibliografia
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  • 4. Fei, L., Deng, Y. 2020. Multi-criteria decision making in Pythagorean fuzzy environment. Applied Intelligence, 50(2), 537–561.
  • 5. Youssef, A.E. 2020. An integrated MCDM approach for cloud service selection based on TOPSIS and BWM. IEEE Access, 8, 71851–71865.
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  • 7. Bączkiewicz, A., Kizielewicz, B., Shekhovtsov, A., Yelmikheiev, M., Kozlov, V., Sałabun, W. 2021. Comparative analysis of solar panels with determination of local significance levels of criteria using the MCDM methods resistant to the rank reversal phenomenon. Energies, 14(18), 5727.
  • 8. Sasikumar, G., Ayyappan, S. 2019. Multi-criteria decision making for solar panel selection using fuzzy analytical hierarchy process and technique for order preference by similarity to ideal solution (TOPSIS): an empirical study. Journal of The Institution of Engineers (India): Series C, 100(4), 707–715.
  • 9. Asadi, M., Pourhossein, K. 2019, June. Wind and solar farms site selection using geographical information system (GIS), based on multi criteria decision making (MCDM) methods: A case study for East-Azerbaijan. In: Iranian Conference on Renewable Energy & Distributed Generation (ICREDG '2019), 1–6
  • 10. Wiguna, K.A., Sarno, R., Ariyani, N.F. 2016, October. Optimization solar farm site selection using multi-criteria decision making fuzzy AHP and PROMETHEE: Case study in Bali. In: International Conference on Information & Communication Technology and Systems (ICTS '2016), 237–243.
  • 11. Goh, H.H., Li, C., Zhang, D., Dai, W., Lim, C.S., Kurniawan, T.A., Goh, K.C. 2021. Using multi-criteria decision making (MCDM) and choosing by advantages (CBA) to determine the optimal location for solar photovoltaic (PV) farms. https://doi.org/10.21203/rs.3.rs-1108987/v1
  • 12. Ruiz, H.S., Sunarso, A., Ibrahim-Bathis, K., Murti, S.A., Budiarto, I. 2020. GIS-AHP Multi Criteria Decision Analysis for the optimal location of solar energy plants at Indonesia. Energy Reports, 6, 3249–3263.
  • 13. Vishnupriyan, J., Manoharan, P.S. 2018. Multicriteria decision analysis for renewable energy integration: A southern India focus. Renewable Energy, 121, 474–488.
  • 14. Štreimikienė, D., Šliogerienė, J., Turskis, Z. 2016. Multi-criteria analysis of electricity generation technologies in Lithuania. Renewable Energy, 85, 148–156.
  • 15. Ozdemir, S., Sahin, G. 2018. Multi-criteria decision-making in the location selection for a solar PV power plant using AHP. Measurement, 129, 218–226.
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  • 20. Zlaugotne, B., Zihare, L., Balode, L., Kalnbalkite, A., Khabdullin, A. and Blumberga, D. 2020. Multi-criteria decision analysis methods comparison. Rigas Tehniskas Universitates Zinatniskie Raksti, 24(1), 454–471.
  • 21. Vinchurkar, S.H., Samtani, B.K. 2019. Performance evaluation of the hydropower plants using various multi-criteria decision-making techniques. International Journal of Engineering and Advanced Technology, 8, 2031–2038.
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Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2ece59e8-1d29-432c-a6d2-47cbdcd9f28c
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