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Multi-objective optimization of location allocation for the construction of solar power plants to meet electricity demand
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Hamidreza Sarchahi   , Rohollah Bagheri * , Alireza Pooya |
| Ferdowsi University of Mashhad |
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Abstract: (1580 Views) |
| Due to the trend of increasing demand for electricity consumption, the use of current fossil fuel-based electricity production technologies has led to frequent blackouts in the summer and fuel burning in the winter. Therefore, the use of renewable energy sources and especially the construction of solar power plants can be a solution to end the blackout and fuel burning crises. The purpose of this research is the multi-objective optimization of the allocation of solar power plant construction to meet the electricity demand. In the objective functions of the problem of system costs, the amount of disturbances in the lines and the amount of greenhouse gases were minimized, as well as the amount of covered areas was maximized. In this research, the LP metric method has been used to solve the problem of multi-objective optimization in GAMS software. In order to validate the presented mathematical model, the correctness of the presented model was checked by GAMS software.Then, by presenting a numerical example, the complexity of the problem, the effectiveness of the multi-objective genetic algorithm in small and large dimensions were investigated. Finally, a case study regarding the construction of a solar power plant in Kashan, Aran and Bidgol region was investigated and According to the given information and the input data of the problem, the situation of the candidate areas for the construction of solar power plants was determined and Also, different areas of demand were assigned to the built solar power plants. |
Article number: 5 |
| Keywords: genetic algorithm, Location allocation, Multi-objective optimization, solar power plant |
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Full-Text [PDF 1800 kb]
(340 Downloads)
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Type of Study: Research |
Subject:
General
Received: 2023/04/1 | Accepted: 2023/06/21 | Published: 2023/06/21
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