Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea

Ali, Sajid; Lee, Sang Moon; Jang, Choon‐Man

doi:10.3390/en10122072

Cited by 45 publications

(36 citation statements)

References 40 publications

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“…With regard to the evaluation methods of the onshore optimal locations, and according to the specific literature, 70.6% of contributions included a combination of geospatial tools and multicriteria decision methods,-accounting for 24 works in total-. The most commonly used combination was GIS and MCDM methods, or several of them: AHP (Analytic Hierarchy Process), FAHP (Fuzzy Analytic Hierarchy Process), OWA (Ordered Weighted Average), TOPSIS, WLC (Weighted Liner Composition) [15,17,27,28,30,31,[34][35][36][39][40][41][42]44,45]. The combination of GIS and SMCA (Spatial Multicriteria Analysis), DSS (Decision Support System), SDSS (Spatial Decision Support Systems) and MCE (Multicriteria Evaluation) can be identified in seven contributions [16,18,19,21,29,32,37].…”

Section: Methodologies: Comparison and Statisticsmentioning

confidence: 99%

Categorization and Analysis of Relevant Factors for Optimal Locations in Onshore and Offshore Wind Power Plants: A Taxonomic Review

Gil-García

García-Cáscales

Fernández‐Guillamón

et al. 2019

JMSE

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Wind power is widely considered to be a qualified renewable, clean, ecological and inexhaustible resource that is becoming a leader in the current energy transition process. It is a mature technology solution that was quickly developed and has been massively integrated into power systems in recent years. Indeed, a remarkable number of renewable integration policies have been promoted by different governments and countries. With the aim of maximizing the power given by wind resources, the locations of both onshore and offshore wind power plants must be optimized following a sort of different criteria. Under this scenario, a number of factors and decision criteria in the evaluation and selection of locations can be identified. Moreover, the relevant wind power increasing in the power generation mix is addressed, along with a standardization of factors and decision criteria in the optimization and selection of such optimal locations. In this context, this paper describes a systematic review and meta-analysis combining most of the contributions and studies proposed during the last decade. Thus, our aim is focused on reviewing and categorizing all factors to be considered for optimal location estimation, pointing out the differences among the selected factors and the decision criteria for onshore and offshore wind power plants. In addition, our review also includes an analysis of the representative key indicators for the contributions, such as the annual frequency of publications, geographical classification, analysis by category, evaluation method and determining factors.

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Section: Methodologies: Comparison and Statisticsmentioning

confidence: 99%

Categorization and Analysis of Relevant Factors for Optimal Locations in Onshore and Offshore Wind Power Plants: A Taxonomic Review

Gil-García

García-Cáscales

Fernández‐Guillamón

et al. 2019

JMSE

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“…In terms of location optimisation, the authors of [32] proposed an optimisation approach that relies on integrating geographic information systems (GIS) with a fuzzy-analytical hierarchy process (FAHP) for choosing suitable wind farm sites. Impacts of location choices made on wind turbine operations were discussed in [33].…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainable Zoning, Land-Use Allocation and Facility Location Optimisation in Smart Cities

et al. 2019

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Many cities around the world are facing immense pressure due to the expediting growth rates in urban population levels. The notion of 'smart cities' has been proposed as a solution to enhance the sustainability of cities through effective urban management of governance, energy and transportation. The research presented herein examines the applicability of a mathematical framework to enhance the sustainability of decisions involved in zoning, land-use allocation and facility location within smart cities. In particular, a mathematical optimisation framework is proposed, which links through with other platforms in city settings, for optimising the zoning, land-use allocation, location of new buildings and the investment decisions made regarding infrastructure works in smart cities. Multiple objective functions are formulated to optimise social, economic and environmental considerations in the urban space. The impact on underlying traffic of location choices made for the newly introduced buildings is accounted for through optimised assignment of traffic to the underlying network. A case example on urban planning and infrastructure development within a smart city is used to demonstrate the applicability of the proposed method.Energies 2019, 12, 1318 2 of 23 increasingly reflected in the operations of existing cities, resulting in an interrelated platform between large numbers of citizens, transport networks, services and urban assets and facilities [9].Decision-making in planning and operations of smart cities needs to be structured around two main considerations, namely strategic and tactical decisions [10]. Yet, current emphasis in the literature is on the technical interfaces making up the various data-exchange enabling platforms placed within the cities, with little emphasis on the strategic and tactical urban planning aspects of smart cities. Within the area of strategic decision-making in city planning, zoning of the city and the location of its operating facilities, including schools, hospitals and so forth, are both of significant relevance [11]. An appropriate selection of zone clusters and the subsequent selection of locations to place buildings in form the main components that are involved in city design. In cities, the positioning of new buildings leads to the generation of traffic demand in the existing network structure [12]. This causes additional traffic loadings on the existing network, and if not well planned for, can result in major transportation delays to network users. Traffic congestion is thought to result in over $121 billion in losses [13] and can increase the amount of carbon emissions from traffic by more than 53% [14]. Another important strategic consideration is the development of the underlying travel network of the region. Specifically, the development of the transport network will be based on the capacities required to handle the initiated travel on the transport networks, while the operations of the network will in turn be associated with the established capacity of the network, along...

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“…It is a flexible and powerful tool for both qualitative and quantitative investigation of multi-criteria problems [40]. AHP is characterized based on paired comparisons as it is helpful in breaking down complicated problems with multiple criteria into number of matched comparisons [41].…”

Section: Application Of Ahp In Siting Solid Waste Landfillmentioning

confidence: 99%

A GIS–AHP-based approach in siting MSW landfills in Lokoja, Nigeria

et al. 2019

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The acute shortage and scarcity of lands for suitable waste disposal is rapidly becoming a critical growing potential problem in most urban cities in developing countries of the world, and several fast-growing cities in Nigeria are not exempted from this menace. In this study, geographic information system (GIS) and analytic hierarchy process (AHP) are combined to select the most suitable landfill location in Lokoja, Nigeria. The landfill site selection criteria considered include proximity to major road, powerline, water body, landfill areas and built-up area. GIS was used to digitize spatial features related to unsuitable landfill site. A total of 19 candidate landfill sites were identified from GIS analysis. AHP model was developed from the GIS result as multi-criteria decision tool in evaluating each candidate site so as to choose the best appropriate landfill site. AHP model rated candidate site 11 located along Jimgbe road has the most preferable site to locate a landfill in Lokoja with an approximate area of 3.4204 km 2 ; the distance from the minor road, nearest water body, powerline and built-up areas to the location is 210.50 m, 1408.20 m, 1810.80 m and 205.61 m, respectively. Also, the model rated candidate site 16 located along 500 housing units as the least preferable site to locate a landfill in Lokoja. The characteristic features of the site location as obtained from GIS analysis include an approximate area of 2.5680 km 2 at an approximate distance of 2430.75 m, 594.04 m, 1980 m and 200.68 m from the major road, water body, powerline and built-up areas, respectively. This result will greatly serve as guide in landfill site selection in major urban states of other developing countries.

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Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea

Cited by 45 publications

References 40 publications

Categorization and Analysis of Relevant Factors for Optimal Locations in Onshore and Offshore Wind Power Plants: A Taxonomic Review

Categorization and Analysis of Relevant Factors for Optimal Locations in Onshore and Offshore Wind Power Plants: A Taxonomic Review

Sustainable Zoning, Land-Use Allocation and Facility Location Optimisation in Smart Cities

A GIS–AHP-based approach in siting MSW landfills in Lokoja, Nigeria

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