Abstract Microgrids, consisting of distributed generators (DGs), loads, and energy storage systems, play an important role in future smart grids. In order to evaluate microgrid operations and their dynamic response, it is necessary to develop accurate dynamic models of DGs in microgrids. This paper presents a systematic method to calibrate the model of a synchronous-generator-interfaced DG. Underlying parameters are categorized into two groups, namely, steady-state parameters and time constants, which are estimated in two successive stages using multiple event data. This methodology ensures that the validated model with the estimated parameters are applicable for a set of events. Moreover, assuming that power angle measurements of a synchronous-generator-interfaced DG are unavailable, a modified unscented Kalman filter (UKF) is proposed to facilitate parameter estimation. The effectiveness of the proposed method is validated using field test data of a 2600 kVA diesel generator which is part of an operational microgrid.

中文翻译：

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使用多事件数据校准微电网中的同步发电机接口 DG 模型

摘要 由分布式发电机（DG）、负载和储能系统组成的微电网在未来的智能电网中发挥着重要作用。为了评估微电网运行及其动态响应，有必要开发微电网中 DG 的准确动态模型。本文提出了一种校准同步发电机接口 DG 模型的系统方法。基础参数分为两组，即稳态参数和时间常数，它们使用多个事件数据在两个连续阶段进行估计。这种方法确保具有估计参数的验证模型适用于一组事件。此外，假设同步发电机接口 DG 的功率角测量不可用，提出了一种改进的无迹卡尔曼滤波器（UKF）来促进参数估计。使用 2600 kVA 柴油发电机的现场测试数据验证了所提出方法的有效性，该柴油发电机是运行微电网的一部分。