Optimal siting of electric vehicle charging stations: A GIS-based fuzzy Multi-Criteria Decision Analysis

Erbaş, Mehmet; Kabak, Mehmet; Özceylan, Eren; Çetinkaya, Cihan

doi:10.1016/j.energy.2018.08.140

Cited by 203 publications

(92 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Similar results were obtained in their research by Arabameri et al They used multi-criteria decision analysis based on GIS for developing the methodology used by decision-makers and managers to plan preventive measures and reduce damage caused by erosion [26]. An interesting combination of the presented approach was proposed by the Erbaş et al hybrid method supporting the decision making process regarding the location and construction of vehicle charging stations [27]. The methodology of making decisions regarding the determination of optimal locations for wind farms was also presented in [28], in which three location scenarios were analyzed-each contained a different set of restrictions.…”

Section: Introductionsupporting

confidence: 66%

An Innovative Decision Support System to Improve the Energy Efficiency of Buildings in Urban Areas

et al. 2020

View full text Add to dashboard Cite

Improving in the energy efficiency of urban buildings, and maximizing the savings and the resulting benefits require information support from city decision-makers, planners, and designers. The selection of the appropriate analytical methods will allow them to make optimal design and location decisions. Therefore, the research problem of this article is the development of an innovative decision support system using multi-criteria analysis and Geographic Information Systems (decision support system + Geographic Information Systems = DGIS) for planning urban development. The proposed decision support system provides information to energy consumers about the location of energy efficiency improvement potential. This potential has been identified as the possibility of introducing low-energy buildings and the use of renewable energy sources. DGIS was tested in different construction areas (categories: A, B, C, D), Zielona Góra quarters. The results showed which area among the 53 quarters with a separate dominant building category was the most favorable for increasing energy efficiency, and where energy efficiency could be improved by investing in renewable energy sources, taking into account the decision-maker. The proposed DGIS system can be used by local decision-makers, allowing better action to adapt cities to climate change and to protect the environment. This approach is part of new data processing strategies to build the most favorable energy scenarios in urban areas.

show abstract

Section: Introductionsupporting

confidence: 66%

An Innovative Decision Support System to Improve the Energy Efficiency of Buildings in Urban Areas

et al. 2020

View full text Add to dashboard Cite

show abstract

“…The results in this study concur with the existing literature that showed the superiority of GIS-based multicriteria approach for site selection [9,21,22]. This superiority of the approach is not limited to landfill siting alone but also for infrastructure such as electric vehicle charging stations [31], bike-share stations [11] and potential ecotourism sites [32]. The number of criteria included in the study and the use of deterministic parameters that may not necessarily cope with uncertainty are the main limitations of this study.…”

Section: Discussionsupporting

confidence: 90%

Geospatial analysis of landfill site selection perspectives using geographic information systems in Bongo district, Ghana

Amoah

Kursah

2019

SN Appl. Sci.

View full text Add to dashboard Cite

This study applied geospatial tools in geographic information systems (GIS) to produce five different landfill suitability maps using criteria selection and prioritisation from the governmental guideline, the local technocrats, the indigenes and two optimal options, which are made up of the harmonisation of the three perspectives. The results from the five perspectives are compared and analysed using the error index technique. The results showed a low spatial agreement (low degree of matching) between the landfill suitability from the governmental guideline and the rest of the perspectives. It also showed a consistent reduction in the areas classified as suitable landfill sites from the governmental guideline to the indigenous perspective. The governmental guideline, thus, exhibits wider spatial discrepancy from the perspective of the local technocrats, and it is even incongruent with that of the indigenes. This study, therefore, exposed a classical case where proponents of landfill sites could meet the governmental guideline and legally acquire permit, but the site could be socioculturally disruptive to the residents. This is identified as the potential source of residents' opposition to landfill siting. The challenges of the criteria in the guideline are also highlighted. A revision of the guideline is suggested, as it is risk-seeking in its current form. Based on this, the bottom-up approach for designing landfill guidelines is recommended.

show abstract

“…For this reason, holistic approaches that take different aspects into consideration are important to actualize more functional solutions for the dissemination of electric vehicles. Furthermore, the present paper provides a highresolution solution to location selection of electric vehicle charging stations as suggested in the previous study (Dong et al 2019). By applying the higher analysis resolution, more detailed suitability results are obtained.…”

Section: Examination Of Alternative Rankingmentioning

confidence: 84%

“…According to the results of this study, they observed that the driving rages dominantly affect the selection process of appropriate charging station locations. Erbaş et al (2018) proposed an approach that combines GIS techniques and MCDM methods to determine optimal locations of electric vehicle charging stations in Ankara, Turkey. The authors applied different scenarios relating to obtaining weights of criteria, but they did not analyse the intersection of suitable location suitability indexes that are gained from these scenarios.…”

Section: Introductionmentioning

confidence: 99%

Suitable location selection for the electric vehicle fast charging station with AHP and fuzzy AHP methods using GIS

Güler

Yomralıoğlu

2020

Annals of GIS

View full text Add to dashboard Cite

Electric vehicles arouse interest since they not only contribute economies of countries in the context of dependency to oil but also support to more livable and sustainable urban areas. The location selection of electric vehicle charging stations is one of the most vital topics in order to enhance the use of electric vehicles. In this sense, the aim of this paper is to propose an approach that integrates Geographic Information System (GIS) techniques and Multi-Criteria Decision Making (MCDM) methods for finding suitable locations of the electric vehicle charging stations. In this regard, the Analytic Hierarchy Process (AHP) and the Fuzzy Analytic Hierarchy Process (FAHP) methods are used to calculate the weights of criteria. While the two different weights for each criterion are obtained by means of AHP in terms of environmental impact and accessibility, another weight for each criterion is obtained as a means of applying the FAHP. The intersection of three different suitability indexes is determined so as to achieve a holistic, credible result. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the alternative locations. The results show that the proposed approach offers a notable solution to be selected suitable charging station locations. Moreover, policymakers and administrators could benefit from these results in order to make efficient decisions for forward planning and strategies.

show abstract

Optimal siting of electric vehicle charging stations: A GIS-based fuzzy Multi-Criteria Decision Analysis

Cited by 203 publications

References 33 publications

An Innovative Decision Support System to Improve the Energy Efficiency of Buildings in Urban Areas

An Innovative Decision Support System to Improve the Energy Efficiency of Buildings in Urban Areas

Geospatial analysis of landfill site selection perspectives using geographic information systems in Bongo district, Ghana

Suitable location selection for the electric vehicle fast charging station with AHP and fuzzy AHP methods using GIS

Contact Info

Product

Resources

About