Optimal Scheduling and Sizing of Energy Storage System using Hybrid Algorithm for Electric Vehicles

2022 International Virtual Conference on Power Engineering Computing and Control: Developments in Electric Vehicles and Energy Sector for Sustainable Future (PECCON) Pub Date : 2022-05-05 DOI:10.1109/PECCON55017.2022.9851152

S. Dhivya, R. Arul, S. Maheswari, R. Kanimozhi, N. Karthik

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引用次数: 1

Abstract

The rapid exhaustion of fossils shaded concern about environmental problems which enforce researchers to embed this renewable distribution generation into power system networks. Electric vehicles are increasing threat to reliability of power grid by overloaded equipment and disturbed stability in voltage. However, it is important that electric vehicles must provide support to grids through vehicle to grid optimized V2G scheduling to minimize load variances. The purpose of this study is to employ a hybrid approach to improve energy storage system scheduling and sizing for electric vehicles. The hybrid version of Flower Pollination and golden section search is used. This research considers peak shaving, valley filling and priority charging mode of Energy Storage System for effective load management. Results indicated that optimized and scheduled energy storage system can fulfill the proper load allocation at grid.

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基于混合算法的电动汽车储能系统优化调度与规模研究

化石资源的迅速枯竭掩盖了人们对环境问题的担忧，迫使研究人员将这种可再生配电发电嵌入电力系统网络。电动汽车的超载和电压稳定性受到干扰，对电网的可靠性构成越来越大的威胁。然而，重要的是，电动汽车必须通过车辆到电网优化的V2G调度来为电网提供支持，以最小化负载差异。本研究的目的是采用一种混合方法来改善电动汽车储能系统的调度和规模。混合版本的花授粉和黄金分割搜索是使用。本文考虑了储能系统的调峰、填谷和优先充电模式，以实现有效的负荷管理。结果表明，优化调度的储能系统能够实现合理的电网负荷分配。

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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2022 International Virtual Conference on Power Engineering Computing and Control: Developments in Electric Vehicles and Energy Sector for Sustainable Future (PECCON)

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