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Optimal energy management system using biogeography based optimization for grid-connected MVDC microgrid with photovoltaic, hydrogen system, electric vehicles and Z-source converters
Energy Conversion and Management ( IF 10.4 ) Pub Date : 2021-10-02 , DOI: 10.1016/j.enconman.2021.114808
Lais de Oliveira-Assis 1 , Pablo García-Triviño 1 , Emanuel P.P. Soares-Ramos 1, 2 , Raúl Sarrias-Mena 3 , Carlos Andrés García-Vázquez 1 , Carlos Ernesto Ugalde-Loo 4 , Luis M. Fernández-Ramírez 1
Affiliation  

Currently, the technology associated with charging stations for electric vehicles (EV) needs to be studied and improved to further encourage its implementation. This paper presents a new energy management system (EMS) based on a Biogeography-Based Optimization (BBO) algorithm for a hybrid EV charging station with a configuration that integrates Z-source converters (ZSC) into medium voltage direct current (MVDC) grids. The EMS uses the evolutionary BBO algorithm to optimize a fitness function defining the equivalent hydrogen consumption/generation. The charging station consists of a photovoltaic (PV) system, a local grid connection, two fast charging units and two energy storage systems (ESS), a battery energy storage (BES) and a complete hydrogen system with fuel cell (FC), electrolyzer (LZ) and hydrogen tank. Through the use of the BBO algorithm, the EMS manages the energy flow among the components to keep the power balance in the system, reducing the equivalent hydrogen consumption and optimizing the equivalent hydrogen generation. The EMS and the configuration of the charging station based on ZSCs are the main contributions of the paper. The behaviour of the EMS is demonstrated with three EV connected to the charging station under different conditions of sun irradiance. In addition, the proposed EMS is compared with a simpler EMS for the optimal management of ESS in hybrid configurations. The simulation results show that the proposed EMS achieves a notable improvement in the equivalent hydrogen consumption/generation with respect to the simpler EMS. Thanks to the proposed configuration, the output voltage of the components can be upgraded to MVDC, while reducing the number of power converters compared with other configurations without ZSC.



中文翻译:

基于生物地理学的优化能源管理系统,用于具有光伏、氢系统、电动汽车和 Z 源转换器的并网 MVDC 微电网

目前,与电动汽车(EV)充电站相关的技术需要研究和改进,以进一步鼓励其实施。本文提出了一种基于生物地理学优化 (BBO) 算法的新能源管理系统 (EMS),用于混合电动汽车充电站,其配置将 Z 源转换器 (ZSC) 集成到中压直流 (MVDC) 电网中。EMS 使用进化 BBO 算法来优化定义等效氢消耗/生成的适应度函数。充电站由一个光伏 (PV) 系统、一个本地电网连接、两个快速充电单元和两个储能系统 (ESS)、一个电池储能 (BES) 和一个带有燃料电池 (FC)、电解槽的完整氢气系统组成(LZ) 和氢气罐。通过使用BBO算法,EMS 管理组件之间的能量流动,以保持系统中的功率平衡,减少等效氢气消耗并优化等效氢气生成。EMS 和基于 ZSC 的充电站配置是本文的主要贡献。EMS 的行为通过三个 EV 连接到充电站在不同的太阳辐照度条件下进行演示。此外,将提议的 EMS 与更简单的 EMS 进行比较,以优化混合配置中的 ESS。模拟结果表明,与更简单的 EMS 相比,所提出的 EMS 在等效氢消耗/生成方面取得了显着改善。由于建议的配置,组件的输出电压可以升级到 MVDC,

更新日期:2021-10-02
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