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Hybrid Multi-Criteria Decision Making approach for the evaluation of sustainable photovoltaic farms locations
Faculty
Computer Science
Year:
2021
Type of Publication:
ZU Hosted
Pages:
Authors:
Osama Mohamed Abdelsalam Ahmed Elkomy
Staff Zu Site
Abstract In Staff Site
Journal:
Journal of Cleaner Production ELSEVIER
Volume:
Keywords :
Hybrid Multi-Criteria Decision Making approach , , evaluation
Abstract:
As a result of the increased demand for energy combined with the limitations of traditional energy sources, it is necessary to turn to renewable energy sources such as solar energy, which is one of the most promising technologies to assist the transition towards sustainable development. With the increasing interest in renewable energies in general and solar energy in particular, attempts have been made to ensure that solar energy technologies provide an amount of energy equal to or close to the amount of energy currently consumed. Solar photovoltaic farm applications have become so widespread that they are now relied upon to produce massive amounts of energy for use in factories and homes. In this regard, identifying and prioritizing convenient areas for the construction of expensive solar photovoltaic farms is an important issue. Additionally, determining the suitable geographical locations for photovoltaic farms is not only related to the amount of solar radiation received, but many dimensions must be taken into accounts such as technical, economic, environmental, sociopolitical dimensions, risks, and their sub-indicators. To overcome the problem of prioritizing and selecting the best location for solar photovoltaic farms to achieve sustainability factors resulting from the presence of many different indicators, this paper applies a hybrid multi-criteria decision-making approach under a neutrosophic environment. Initially, the Delphi method is employed to capture preference and to determine the dimensions and their indicators in addition to provide preference among sub-indicators and available alternatives. The proportional importance of the designated dimensions and their sub-indicators was evaluated by the Decision Making Trial and Evaluation Laboratory. Then, Vlse Kriterijumska Optimizacija Kompromisno Resenje is adopted to rank seven solar photovoltaic farm locations in Egypt. The Benban solar photovoltaic farm is shown to be the most sustainable alternative among the solar photovoltaic farm locations followed by Darb Al Arbaeen solar photovoltaic farm and so has priority for increased installation investments in solar energy production. To validate the proposed approach, results comparisons were implemented to indicate the advantages of the hybrid multi-criteria decision-making methods. Sensitivity analysis reveals that changing criteria weightings does not affect the ranking order.
Author Related Publications
Osama Mohamed Abdelsalam Ahmed Elkomy, "MT-nCov-Net: A Multitask Deep-Learning Framework for Efficient Diagnosis of COVID-19 Using Tomography Scans", IEEE, 2021
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Osama Mohamed Abdelsalam Ahmed Elkomy, "Two-Stage Deep Learning Framework for Discrimination between COVID-19 and Community-Acquired Pneumonia from Chest CT scans.", ELSEVIER, 2021
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Osama Mohamed Abdelsalam Ahmed Elkomy, "Efficient model for emergency departments: Real case study", Computers, Materials and ContinuaComputers, Materials and Continua, 2022
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Osama Mohamed Abdelsalam Ahmed Elkomy, "Recognition of phonetic Arabic figures via wavelet based Mel Frequency Cepstrum using HMMs", HBRC Journal, 2014
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Osama Mohamed Abdelsalam Ahmed Elkomy, "Multi-Objective Task Scheduling Approach for Fog Computing.", IEEE Access, 2021
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Department Related Publications
Walid Ibrahim Ibrahim Khedr, "Enhanced inter-ASN handover authentication scheme for IEEE 802.16m network", Institution of Engineering and Technology United Kingdom, 2015
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Walid Ibrahim Ibrahim Khedr, "Improved Lightweight Authentication Scheme For Ieee 802.11P Vehicle-to-Infrastructure Communications", Old City Publishing, Inc., USA, 2015
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Walid Ibrahim Ibrahim Khedr, "Cryptographic Accumulator-Based Scheme for Critical Data Integrity Verification in Cloud Storage", IEEE, 2019
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