Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids

Juan Ignacio Guerrero Alonso, Enrique Personal, Antonio Parejo, S. García, Antonio García, C. León
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引用次数: 1

Abstract

Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization methodology is proposed in this paper. The solution is based on the concept of virtual power plants and the usage of evolutionary computation algorithms. Additionally, the comparison of several evolutionary algorithms, genetic algorithm, genetic algorithm with evolution control, particle swarm optimization, and hybrid solution are shown in order to evaluate the proposed architecture. The proposed solution is presented to prevent the overload of the power grid.
预测充电需求以整合智能电网中的电动汽车车队
电动车队和智能电网是两项正在发展的技术。这些技术为减少污染和提高能源效率提供了新的可能性。从这个意义上说,电动汽车在电网中被用作移动负载。提出了一种分布式收费优先排序方法。该解决方案基于虚拟电厂的概念和进化计算算法的使用。此外,还比较了几种进化算法、遗传算法、进化控制遗传算法、粒子群优化和混合解决方案,以评估所提出的体系结构。提出了防止电网过载的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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