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Wind Farms Site Selection and Allocation In Power Distribution Network Using Environmental, Economic and Technical Factors
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Mina Sadedghi *   , Mohammad Karimi |
| k.n.toosi university |
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Abstract: (2611 Views) |
| Increasing demand for electricity and consequently running out of fossil fuel resources and negative impact of fossil fuels on the environment has led to the need for finding renewable energy sources. Iran has high potentiality in exploiting wind energy because of its topology and various climatic conditions. For this purpose, optimal places for installing these facilities should be determined. The purpose of this research is to evaluate land suitability for constructing wind farms using Geographic information system (GIS) and Multi-criteria decision-making method (MCDM) and to find optimal sites for wind farm development using Genetic Algorithm and to add it to the medium voltage power network. In the first step, we determine the effective environmental factors, criteria and constraints. The factors that we considered in this research sort into two categories: environmental and economic. Then, the criteria and factors were weighted using the AHP method, the factor maps were made and then combined in GIS environment using land suitability index, and finally thirty suitable sites were selected for installing the facilities. In the next step, these candidates were allocated to power system using genetic algorithm in 13 cases with the goal of minimizing power loss, maximizing the suitability of the candidates and maximizing the load supply. For instance, in each case, the allocation of one more Dg will be added in order to eliminate the power plant totally. Based on the suitability maps, northwestern and western parts of the region are suitable for wind farm development. The allocation of the candidate sites will be done using genetic algorithm. The output of the algorithm will be the DG ID and the substation ID to which the Dg will be connected. |
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| Keywords: Wind turbin, AHP, GIS, Site selection, Genetic algorithm. |
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Full-Text [PDF 2511 kb]
(822 Downloads)
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Type of Study: Research |
Subject:
GIS
Received: 2019/04/24 | Accepted: 2019/12/10 | Published: 2021/07/22
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