Advanced lead-acid battery models for the state-of-charge estimation in an isolated microgrid

T. Roje, A. Navas, M. Urrutia, P. Mendoza-Araya, G. Jiménez‐Estévez
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Abstract

In order to compare and improve battery energy storage system (BESS) models, this work exhibits a comparative study of the Coppeti, the Coulomb counting, and the Thevenin based models of the State of Charge (SoC) for lead-acid batteries. Additionally, a multi-model estimator that merges and exploits the benefits of aforementioned models is proposed by using an extended Kalman filter (EKF). The performance of the different SoC models are evaluated by means of simulations in a economic dispatch problem of an isolated microgrid with an Energy Management System (EMS). The Comparative study of the SoC models is done using real operation data from the Huatacondo's microgrid with an EMS based on a rolling horizon strategy. As shown in the results, the operating costs of the microgrid are considerably reduced when the multi-model estimator is used, showing a direct impact in the economical costs of the system.
用于隔离微电网状态估计的先进铅酸电池模型
为了比较和改进电池储能系统(BESS)模型,本研究对基于Coppeti、库仑计数和Thevenin的铅酸电池荷电状态(SoC)模型进行了比较研究。此外,利用扩展卡尔曼滤波(EKF),提出了一种融合并利用上述模型优点的多模型估计器。通过对具有能源管理系统(EMS)的孤立微电网经济调度问题的仿真,评估了不同SoC模型的性能。利用Huatacondo微电网与基于滚动地平线策略的EMS的实际运行数据,对SoC模型进行了比较研究。结果表明,采用多模型估计器后,微电网的运行成本显著降低,对系统的经济成本有直接影响。
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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