Power electronics converters for an electric vehicle fast charging station based energy storage system and renewable energy sources: Hybird approach

Gopal Soundra Devi, Jawahar Rahila, Athmanathan Radhika, Pandi Meenalochini
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Abstract

Abstract A hybrid method is proposed for electric‐vehicle (EV) fast charging station (FCS)‐based power electronics converters with energy‐storage‐systems (ESS) and renewable‐energy‐sources (RESs). The proposed approach is the combination of the fire hawk optimizer (FHO) and gradient boost decision tree (GBDT) algorithms; hence called as FHO‐GBDT approach. The key objective of the FHO‐GBDT approach is to lessen the peak power demand on the grid. The proposed method is incorporated into EV‐FCS with the capability of a mixture of RESs and energy‐storage‐systems. The capacities of energy‐storage aid in improving power‐demand by lessening the demand for peak power. The structure of the energy storage system minimizes the net cost of the DC micro‐grid (MG). The ESS is mostly composed of batteries, which are reused by EVs. The proposed approach and the ESS enable a decrease in obtaining the greatest amount of power possible from the power‐grid (PG). By then, the performance of the proposed approach is simulated in MATLAB, and it is compared to various existing methods. The simulation result shows that the proposed method offers more power than the existing methods.

Abstract Image

基于储能系统和可再生能源的电动汽车快速充电站的电力电子转换器:混合方法
摘要提出了一种基于储能系统(ESS)和可再生能源(RESs)的电动汽车(EV)快速充电站(FCS)电力电子转换器的混合方法。该方法结合了火鹰优化器(FHO)和梯度增强决策树(GBDT)算法;因此称为FHO - GBDT方法。FHO - GBDT方法的关键目标是降低电网的峰值电力需求。所提出的方法被整合到EV - FCS中,具有RESs和储能系统的混合能力。储能容量通过减少对峰值功率的需求来帮助改善电力需求。储能系统的结构使直流微电网(MG)的净成本最小化。ESS主要由电池组成,电动汽车可以重复使用电池。所提出的方法和ESS能够减少从电网(PG)获得最大电量的可能性。然后,在MATLAB中对所提方法的性能进行了仿真,并与现有的各种方法进行了比较。仿真结果表明,该方法比现有方法具有更高的功率。
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