2016
DOI: 10.1016/j.enconman.2016.01.020
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Study of decision framework of offshore wind power station site selection based on ELECTRE-III under intuitionistic fuzzy environment: A case of China

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Cited by 217 publications
(106 citation statements)
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“…Another study by Wątróbski et al [36] has defined the methodological aspects of a decision support system for localizing offshore wind farms. Wu et al [37] have developed a decision-making framework for the selection of offshore wind sites using Elimination et Choix Traduisant la Realité-III (ELECTRE-III). Sanchez et al [38] combined fuzzy approaches of different Multi-Criteria Decision Making (MCDM) to deal with the current decision problem of onshore wind site selection.…”
Section: Factor Analysis (Fa)mentioning
confidence: 99%
“…Another study by Wątróbski et al [36] has defined the methodological aspects of a decision support system for localizing offshore wind farms. Wu et al [37] have developed a decision-making framework for the selection of offshore wind sites using Elimination et Choix Traduisant la Realité-III (ELECTRE-III). Sanchez et al [38] combined fuzzy approaches of different Multi-Criteria Decision Making (MCDM) to deal with the current decision problem of onshore wind site selection.…”
Section: Factor Analysis (Fa)mentioning
confidence: 99%
“…In this paper, evaluation criteria and their importance were presented in a decision model for the sake of selecting a wind farm location. On the other hand, in [16] selection of an onshore wind farm location is also dealt with in [17], and an offshore one received a similar treatment in [5]. GIS decision systems were suggested, amongst other things in [18], [19], [20], [21].…”
Section: Literature Reviewmentioning
confidence: 99%
“…100m is crucial. [5], [6], [15], [17], [19]- [21], [23], [24], [26] C1.2 Output power of wind turbine [8] C1.3 Power grid voltage on the site of connection [26] C2 Economic C2.1 Yearly amount of energy generated [6], [7], [25] C2.2 Investment cost [5]- [7], [16], [25] C2.3 Operational costs per year [5], [6], [16], [25] C2.4 Incomes from generated energy per year [26] C2.5 Profits from generated energy per year [5], [6], [24] C2.6 Payback period [5]- [7] C3 Social C3.1 Number of generated workplaces [5], [6], [15] C3. C4.3 Location in Natura 2000 protected area [7], [19], [22], [23] C1.2 The maximum output power of a turbine is achieved at a specific wind speed, which is critical.…”
Section: The Proposed Decision Model For Dssmentioning
confidence: 99%
“…Sánchez-Lozano et al [16] utilized CNVs, LVs, and triangular fuzzy numbers (TFNs) to represent the values of criteria involved in onshore wind farm site selection, and then, the CNVs and LVs were both converted into the TIFNs. Wu and Zhang [17] utilized CNVs and LVs to represent the values of criteria involved in offshore wind power station site selection, and transformed both the CNVs and the LVs into intuitionistic fuzzy numbers (IFNs). Also, Wu et al [18] used CNVs and IFNs in the process of wind farm project plan selection, and then, the CNVs were transformed into the IFNs.…”
Section: Literature Reviewmentioning
confidence: 99%