Optimization Method for the Internal Distribution Network of a Photovoltaic Plant Using Genetic Algorithm

Eluan Oliveira Nascimento, Paulo Roberto Monteiro Duailibe, Thiago Borges Trezza
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Abstract

Solar energy has grown exponentially around the world because it is clean and renewable, with this, photovoltaic plants are installed for its consumers as well as to relieve the electrical system of the country and guarantee the reliability. In this way, carrying out a correct dimensioning and finding a layout for the execution of a solar plant is important because it can increase or minimize the electrical losses as well as the investment. This study uses the genetic algorithm in order to find better layout to optimize the energy loss on an implanted solar power plant and resize the conductors by current capacity and voltage drop, the study shows how to program Excel to solve the multi-positioning problem through the genetic algorithm in a solar power plant. The results show that the optimization proposed by the genetic algorithm was able to reduce electrical losses by 75% and the net present value over a period of 25 years was reduced by 25%. Future research will be carried out considering 3D plans covering solar plants that are installed on the roof.
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基于遗传算法的光伏电站内部配电网优化方法
太阳能因其清洁和可再生而在世界范围内呈指数级增长,因此,为消费者安装光伏电站以及减轻国家电力系统的负担并保证可靠性。通过这种方式,执行正确的尺寸并为太阳能发电厂的执行找到一个布局是很重要的,因为它可以增加或减少电力损失以及投资。本研究利用遗传算法寻找更好的布局,以优化植入式太阳能电站的能量损失,并通过电流容量和电压降调整导体的尺寸,研究如何通过遗传算法编程Excel来解决太阳能电站中的多定位问题。结果表明,采用遗传算法优化后,电力损耗降低75%,25年净现值降低25%。未来的研究将考虑安装在屋顶上的太阳能发电厂的3D计划。
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