A Grouping and Aggregation Modeling Method of Induction Motors for Transient Voltage Stability Analysis

Author:

Liang Zhaowen1ORCID,Liu Yongqiang1,Mo Lili12,Zhang Yan34

Affiliation:

1. School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China

2. Institute of Architectural Design and Research, South China University of Technology, Guangzhou 510641, China

3. School of Digital Economics, Guangdong University of Finance and Economics, Guangzhou 510320, China

4. Research Center of Intelligent Computing and Big Data Technology, Guangdong University of Finance and Economics, Guangzhou 510320, China

Abstract

Induction motors are the most common type of motor in power systems, constituting approximately 70–90% of the dynamic loads, making them significant contributors to system dynamics. In transient voltage stability analysis, dynamic equivalent models are commonly used to simplify the representation of a group of induction motors. This paper presents a method for the grouping and aggregation of induction motors at a common bus. Firstly, grouping rules are provided for clustering induction motors into several subgroups based on the mechanical principles of rotor force and motion, and aggregation rules are provided for aggregating a motor subgroup into a single-unit model based on the relationship between voltage drop and power transmission in distribution networks. Secondly, guided by the grouping rules, high-speed remaining electromagnetic torque and low-speed remaining electromagnetic torque are defined as new clustering indicators, and an adaptive K-means clustering method using silhouette coefficient verification is introduced to obtain the optimal motor subgroups. Thirdly, guided by the aggregation rules, a dynamic equivalent method is further introduced to obtain the equivalent single-unit model from a motor subgroup. Lastly, a transient voltage stability simulation in a typical distribution network is presented to illustrate that the proposed clustering and equivalent methods are more reasonable, accurate, and effective than traditional methods, as the obtained model has better dynamic characteristics and can more accurately reproduce the process of voltage collapse.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Reference47 articles.

1. Load Modeling—A Review;Arif;IEEE Trans. Smart Grid,2018

2. Li, H., Chen, Q., Fu, C., Yu, Z., Shi, D., and Wang, Z. (2019). Bayesian Estimation on Load Model Coefficients of ZIP and Induction Motor Model. Energies, 12.

3. Model Validation for the August 10, 1996 WSCC System Outage;Kosterev;IEEE Trans. Power Syst.,1999

4. An Interim Dynamic Induction Motor Model for Stability Studies in the WSCC;Pereira;IEEE Trans. Power Syst.,2002

5. IEEE Standards Association (2022). IEEE Guide for Load Modeling and Simulations for Power Systems, The Institute of Electrical and Electronics Engineers, Inc.

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