Multicriteria Decision-Making for Evaluating Solar Energy Source of Saudi Arabia
Abdulaziz Alanazi and
Mohana Alanazi ()
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Abdulaziz Alanazi: Department of Electrical Engineering, College of Engineering, Northern Border University, Arar 73222, Saudi Arabia
Mohana Alanazi: Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia
Sustainability, 2023, vol. 15, issue 13, 1-37
Abstract:
Saudi Arabia generates more than 98% of its electricity through hydrocarbon resources. To reduce the consumption of fossil fuel resources and protect the environment, the government of Saudi Arabia is planning to make renewable energy an essential part of its energy mix. In this study, due to the country’s abundant solar potential, solar energy has been selected as the energy source to generate renewable energy in Saudi Arabia. The two solar energy technologies, photovoltaic (PV) and solar thermal, have been analyzed in three different locations within the country. Multi-criteria decision-making (MCDM) techniques were used to rank the cities for each of the technologies. The SAW(Simple Additive Weighting)-AHP(Analytic Hierarchy Process) MCDM method based on climate, environmental, technical, economic, and social has been adopted to analyze the suitability of each technology for all locations. To assign weights to the criteria AHP method was used, while to rank the technologies, SAW was used. The results show that for the PV technology, Abha ranked 1st with a performance score of 91%, making it the most suitable location, followed by Jeddah with 83%. While for solar thermal technologies, Jeddah is the most suitable location, with a performance score of 96%, followed by Abha with 91%. The PV systems generated a maximum of 11,019 MWh in Abha, while the solar thermal produced maximum of 14,000 MWh in Jeddah. Overall, solar thermal technology outperformed PV technology in Saudi Arabia due to the country’s higher temperature. The analysis of photovoltaic and solar thermal technologies in this study provides valuable insight for the government of Saudi Arabia in identifying the best site for solar energy technologies in the country.
Keywords: distribution network; multi-objective and coordinated framework; reconfiguration; photovoltaic allocation; adaptive inertia weight; improved clouded leopard optimization algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:13:p:10228-:d:1181277
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