A novel hybrid MCDM approach for offshore wind farm site selection: A case study of Iran

Fetanat, Abdolvahhab; Khorasaninejad, Ehsan

doi:10.1016/j.ocecoaman.2015.02.005

Cited by 190 publications

(92 citation statements)

References 52 publications

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“…Therefore, an essential factor is a proper selection of an MCDA method [48], [31] which would make it possible to build a complex decision-making model for DSS, while taking into consideration mutual dependencies between criteria. The methods which allow the observation of the influence of individual criteria on other ones in the model are ANP [49], [30] and DEMATEL [50], [24].…”

Section: Discussionmentioning

confidence: 99%

“…In [23], a GISbased DSS system analyzing the potential of onshore wind farm locations was discussed. The problem of the construction of a DSS for selecting an offshore wind location was attempted in [24], [7]. As far as decision problems relating to the project design of a wind farms are concerned, these were discussed in [6], [25].…”

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%

See 2 more Smart Citations

MCDA-based Decision Support System for Sustainable Management – RES Case Study

Wątróbski¹,

Ziemba²,

Wolski³

2016

Annals of Computer Science and Information Systems

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Abstract-The MCDA methods are used in order to solve complex decision-making problems which require considering many interrelated criteria. They are also the basis of DSS. Nevertheless, these dependencies between criteria can have an influence on the obtained solution. A class of decision-making problems, in which there are intercriteria dependencies, are decisions in the sustainability area, e.g. selection of a location and a design of an RES-based power station. The article presents a complex model, taking into consideration dependencies between criteria.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: The Proposed Decision Model For Dssmentioning

confidence: 99%

See 1 more Smart Citation

MCDA-based Decision Support System for Sustainable Management – RES Case Study

Wątróbski¹,

Ziemba²,

Wolski³

2016

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

show abstract

“…In this study, the review of existing literature (25 current authoritative studies [1][2][3][4][5]29,[38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56]) was first carried out. From the analysis of the literature, it can be observed that the current indicators for wind and solar power generation sites can be mainly divided into seven aspects: natural resources, economic factors, technical factors, traffic conditions, geographical factors, social factors and environmental factors.…”

Section: Location Index Of Wind-solar Power Generationmentioning

confidence: 99%

Optimal Site Selection of Wind-Solar Complementary Power Generation Project for a Large-Scale Plug-In Charging Station

2017

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Abstract:The wind-solar hybrid power generation project combined with electric vehicle charging stations can effectively reduce the impact on the power system caused by the random charging of electric cars, contribute to the in-situ wind-solar complementary system and reduce the harm arising from its output volatility. In this paper, the site selection index system of a landscape complementary power generation project is established by using the statistical methods and statistical analysis in the literature. Subsequently, using the Analytic Network Process to calculate the index weight, a cloud model was used in combination with preference ranking organization method for enrichment evaluations to transform and sort uncertain language information. Finally, using the results of the decision-making for the location of the Shanghai wind-solar complementary project and by carrying out contrast analysis and sensitivity analysis, the superiority and stability of the decision model constructed in this study was demonstrated.

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“…On the other hand, the ANP is the most appropriate tool for solving problems that are complicated with inherent relationships among the evaluation criteria [65]. The ANP method is widely employed in research and development for optimal site selection, such as the case of offshore wind farms [66], landfills [67,68], as well as wind power plants [69]. In short, the PROMETHEE method integrated with the cloud model and the ANP method is a suitable and reasonable approach, which should be conducive to exercisable and scientific EVCS site selection decisions.…”

Section: Relevant Studies Descriptionsmentioning

confidence: 99%

Optimal Site Selection of Electric Vehicle Charging Stations Based on a Cloud Model and the PROMETHEE Method

et al. 2016

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Abstract:The task of site selection for electric vehicle charging stations (EVCS) is hugely important from the perspective of harmonious and sustainable development. However, flaws and inadequacies in the currently used multi-criteria decision making methods could result in inaccurate and irrational decision results. First of all, the uncertainty of the information cannot be described integrally in the evaluation of the EVCS site selection. Secondly, rigorous consideration of the mutual influence between the various criteria is lacking, which is mainly evidenced in two aspects: one is ignoring the correlation, and the other is the unconscionable measurements. Last but not least, the ranking method adopted in previous studies is not very appropriate for evaluating the EVCS site selection problem. As a result of the above analysis, a Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) method-based decision system combined with the cloud model is proposed in this paper for EVCS site selection. Firstly, the use of the PROMETHEE method can bolster the confidence and visibility for decision makers. Secondly, the cloud model is recommended to describe the fuzziness and randomness of linguistic terms integrally and accurately. Finally, the Analytical Network Process (ANP) method is adopted to measure the correlation of the indicators with a greatly simplified calculation of the parameters and the steps required.

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A novel hybrid MCDM approach for offshore wind farm site selection: A case study of Iran

Cited by 190 publications

References 52 publications

MCDA-based Decision Support System for Sustainable Management – RES Case Study

MCDA-based Decision Support System for Sustainable Management – RES Case Study

Optimal Site Selection of Wind-Solar Complementary Power Generation Project for a Large-Scale Plug-In Charging Station

Optimal Site Selection of Electric Vehicle Charging Stations Based on a Cloud Model and the PROMETHEE Method

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