This article presents a novel method for identification of synchronous generator parameters that is based on sudden short-circuit test data and a novel metaheuristic algorithm, called the adaptive black widow optimization algorithm. Unlike traditional methods defined by IEEE and International Electrotechnical Commission (IEC) standards, which rely on the armature current oscillogram, the method proposed in this article uses the field current waveform during the short-circuit test. Moreover, the standard graphical method for extraction of the generator parameters is replaced by an effective metaheuristic algorithm. The proposed algorithm tends to minimize the normalized sum of squared errors (NSSE) between simulation and experimental results. The applicability and accuracy of the proposed optimization technique are verified using experimentally obtained results from a 100-MVA synchronous generator at the Bajina Basta hydropower plant.

中文翻译：

---

基于场电流波形的同步发电机参数估计方法使用自适应黑寡妇优化算法

本文提出了一种基于突发短路测试数据的同步发电机参数识别新方法和一种新的元启发式算法，称为自适应黑寡妇优化算法。与 IEEE 和国际电工委员会 (IEC) 标准定义的传统方法依赖电枢电流波形图不同，本文提出的方法使用短路测试期间的励磁电流波形。此外，用于提取生成器参数的标准图形方法被有效的元启发式算法所取代。所提出的算法倾向于最小化模拟和实验结果之间的归一化平方和（NSSE）。