A framework for GIS-based site selection and technical potential evaluation of PV solar farm using Fuzzy-Boolean logic and AHP multi-criteria decision-making approach

Noorollahi, Younes; Senani, Ali Ghenaatpisheh; Fadaei, Ahmad; Simaee, Mobina; Moltames, Rahim

doi:10.1016/j.renene.2021.12.124

Cited by 129 publications

(38 citation statements)

References 40 publications

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“…Greece AHP, TOPSIS [11] Khuzestan AHP, fuzzy Boolean logic [27] Turkey AHP [22,24,[28][29][30][31][32] Morocco AHP [33][34][35] China AHP [36] Israel AHP [37] Algeria AHP, EQual Weighted (EQW), Best Worst Method (BWM) [15,[38][39][40] Peru AHP [41] Afghanistan AHP, ANP [42] Iraq AHP, Boolean AHP [8,43] Iran AHP, fuzzy logic, weighted linear Combination (WLC) [44] Thailand AHP [45] Ethiopia AHP [46] Egypt AHP [47] Ireland AHP [48] Chile AHP, ordered weighted averaging [10] Philippines AHP [25] Tanzania AHP [49] Saudi Arabia AHP [23] T A B L E 3 Summary of studies on EVCS site selection using GIS and AHP.…”

Section: Study Area Methods Referencesmentioning

confidence: 99%

An approach for selecting optimal locations for electric vehicle solar charging stations

2023

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Electric vehicles (EVs) are seen as a solution to reduce transport-related greenhouse gas emissions. A major obstacle to wider adoption is the insufficient amount of charging stations. Furthermore, supplying charging stations with renewable energy is still in its infancy. The selection of optimal locations for charging stations is important to best serve the users and maximise the possibilities of renewable energy use. Given this background, this study developed an approach for Solar-supplied Electric Vehicle Charging Station (EVCS) location selection by combining EVCS and solar farm site selection studies using Geographical Information System (GIS) and Analytic Hierarchy Process (AHP). The study determined the most important criteria for site selection based on previous solar and EVCS site selection studies and expert opinions. The 10 most important criteria according to the survey results were: availability of power, solar energy potential, solar panel installation cost, number of EVs, operation and management costs, land cost, distance from roads/highways, distance from current EVCSs, industrial capability of installation and distance to high population density centres. The importance weights of these criteria were assigned using AHP method. The findings are expected to benefit urban planners, decision-makers, and researchers designing solar-supplied EV charging infrastructure.

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Section: Study Area Methods Referencesmentioning

confidence: 99%

An approach for selecting optimal locations for electric vehicle solar charging stations

2023

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“…The BWM and WASPAS method are integrated for eliciting the criteria weights during the expert survey and for the multicriteria ranking of the heating technologies. Noorollahi et al 29 aim to assess utilizing PV solar power plant in Khuzestan province in Iran, using Fuzzy‐Boolean logic and AHP decision analysis based on GIS. The climatic, economic, orography, and environment are investigated as the main criteria for optimal location selection.…”

Section: Literature Reviewmentioning

confidence: 99%

A comprehensive framework for solar panel technology selection: A BWM‐ MULTIMOOSRAL approach

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Hafezalkotob

Fardi

et al. 2022

Energy Science & Engineering

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Concerning the overwhelming advantages of solar energy, controlling and exploiting solar energy by using solar panels is one of the main fields of research in the domain of renewable energy. The choice of solar panel technology is highly significant to exploit as much energy as possible. In this paper, the main goal is to select the best technology for solar panels by investigating nine technologies from the first, second, and third generations of solar panels. Moreover, five sustainable criteria of electrical, mechanical, economic, technical, and climate, and 20 subcriteria are given for making decision analysis. Then, the best-worst method is employed according to the experts' opinions for weighting the criteria and for comparing the ranking of the solar energy technologies a framework based on the MULTIMOOSRAL multiple criteria decision-making method is proposed. Finally, sensitivity analysis will be conducted on the ranking of the technologies. By exploiting the proposed methodology, CIS/CIGS and Perovskite Solar cell are ranked 1 and 2 as the best solar panel technologies for the selected locations.

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“…Considering the target background of carbon neutrality, according to the basic theories of sustainability analysis and comprehensive project evaluation of PV power plant projects, combined with the actual situation of PV power plant projects, this paper forms a framework of sustainability evaluation indexes for PV projects in the context of carbon neutrality target. A total of five dimensions (first-level indicators) are considered: geographical resource sustainability, technical sustainability, economic sustainability, social sustainability and environmental sustainability [20][21][22] along with 20 secondary indicators, as shown in Table 1. References [20][21][22] were consulted in designing the index system, and its main findings are shown in Table 2.…”

Section: Construction Of Sustainability Evaluation Index System For P...mentioning

confidence: 99%

“…A total of five dimensions (first-level indicators) are considered: geographical resource sustainability, technical sustainability, economic sustainability, social sustainability and environmental sustainability [20][21][22] along with 20 secondary indicators, as shown in Table 1. References [20][21][22] were consulted in designing the index system, and its main findings are shown in Table 2.…”

Section: Construction Of Sustainability Evaluation Index System For P...mentioning

confidence: 99%

Smart Evaluation of Sustainability of Photovoltaic Projects in the Context of Carbon Neutrality Target

et al. 2022

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To support the sustainable development of photovoltaic (PV) projects in the context of the carbon neutrality aim, a scientific and reliable evaluation technique is crucial. In this research, an AdaBoost-LS-WSVM intelligent evaluation model built on the Spark platform is suggested to increase evaluation accuracy and timeliness. Firstly, the sustainability evaluation index system of PV projects is constructed from five levels: geographic resource sustainability, technical sustainability, economic sustainability, social sustainability, and environmental sustainability in the context of the carbon neutrality target. Then, the AdaBoost-LS-WSVM intelligent evaluation model with Spark as the platform is constructed, and the wavelet kernel function is applied to the LSSVM model to form the LS-WSVM regression model with stronger nonlinear fitting ability. The learning and training of training samples are completed by the AdaBoost model, and multiple weak LS-WSVM regressors are weighted to get a strong LS-WSVM regressor. The regression model is used for assessing the sustainability of PV projects on Spark Big Data runtime platform. Lastly, the scientific accuracy and reliability of the proposed model is confirmed by a case study, which facilitates a timely and effective assessment of the sustainability of PV projects in the context of carbon neutrality target and can provide scientific and reasonable decision support for the construction of a sustainable development model of PV projects.

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A framework for GIS-based site selection and technical potential evaluation of PV solar farm using Fuzzy-Boolean logic and AHP multi-criteria decision-making approach

Cited by 129 publications

References 40 publications

An approach for selecting optimal locations for electric vehicle solar charging stations

An approach for selecting optimal locations for electric vehicle solar charging stations

A comprehensive framework for solar panel technology selection: A BWM‐ MULTIMOOSRAL approach

Smart Evaluation of Sustainability of Photovoltaic Projects in the Context of Carbon Neutrality Target

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