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Intelligent Energy Allocation Strategy for PHEV Charging Station Using Gravitational Search Algorithm

机译:使用引力搜索算法的PHEV充电站智能能量分配策略

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Recent researches towards the use of green technologies to reduce pollution and increase penetration of renewable energy sources in the transportation sector are gaining popularity. The development of the smart grid environment focusing on PHEVs may also heal some of the prevailing grid problems by enabling the implementation of Vehicle-to-Grid (V2G) concept. Intelligent energy management is an important issue which has already drawn much attention to researchers. Most of these works require formulation of mathematical models which extensively use computational intelligence-based optimization techniques to solve many technical problems. Higher penetration of PHEVs require adequate charging infrastructure as well as smart charging strategies. We used Gravitational Search Algorithm (GSA) to intelligently allocate energy to the PHEVs considering constraints such as energy price, remaining battery capacity, and remaining charging time.
机译:最近对利用绿色技术来减少污染和增加交通能源的渗透性的研究正在受到普及。专注于PHEV的智能电网环境的开发也可以通过实现车辆到网格(V2G)概念来治愈一些主要的网格问题。智能能源管理是一个重要的问题,已经引起了研究人员的关注。这些作品中的大多数都需要制定数学模型,这些模型广泛使用基于计算智能的优化技术来解决许多技术问题。 PHEV的更高渗透需要足够的充电基础设施以及智能充电策略。我们使用引力搜索算法(GSA)智能地将能量分配给PHEV,考虑到诸如能源价格,剩余电池容量和剩余充电时间的限制。

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