Please use this identifier to cite or link to this item: https://rfos.fon.bg.ac.rs/handle/123456789/2330
Title: Hybrid q-Rung Orthopair Fuzzy Sets Based CoCoSo Model for Floating Offshore Wind Farm Site Selection in Norway
Authors: Deveci, Muhammet
Pamučar, Dragan 
Cali, Umit
Kantar, Emre
Kolle, Konstanze
Tande, John O.
Keywords: Wind turbines;Wind farms;Wind energy;site selection;q-rung orthopair fuzzy sets;offshore wind farm;Investment;Fuzzy sets;Fuzzy hamacher;FUCOM;Europe;Decision-making;Decision making
Issue Date: 2022
Publisher: China Electric Power Research Inst, Beijing
Abstract: Unlocking offshore wind farms' high energy generation potential requires a comprehensive multi-disciplinary analysis that consists of intensive technical, economic, logistical, and environmental investigations. Offshore wind energy projects have high investment volumes that make it essential to conduct extensive site selection to ensure feasible investment decisions that reduce the potential financial risks. Depending on the scenario and circumstances, a ranking of alternative offshore wind energy projects helps to prioritise the investment decisions. Decision-making algorithms based on expert knowledge can support the prioritisation and thus alleviate the work load for investment decisions in the future. The case study considered here is to find the best site for a floating offshore wind farm in Norway from four pre-selected alternatives: Utsira Nord, Stadthavet, Froyabanken, and Tr AE na Vest. We propose a hybrid decision-making model as a combined compromised solution (CoCoSo) based on the q-rung orthopair fuzzy sets (q-ROFSs) including the weighted q-rung orthopair fuzzy Hamacher average (Wq-ROFHA) and the weighted q-rung orthopair fuzzy Hamacher geometric mean (Wq-ROFHGM) operators. In this model, the q-ROFSs based full consistency method (FUCOM) is introduced as a new methodology to determine the weights of the decision criteria. The results of the proposed model show that the best site among the investigated four alternatives is A1: Utsira Nord. A sensitivity analysis has verified the stability of the proposed decision-making model.
URI: https://rfos.fon.bg.ac.rs/handle/123456789/2330
ISSN: 2096-0042
Appears in Collections:Radovi istraživača / Researchers’ publications

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