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

Zhaowen Liang (), Yongqiang Liu, Lili Mo and Yan Zhang
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Zhaowen Liang: School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China
Yongqiang Liu: School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China
Lili Mo: School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China
Yan Zhang: School of Digital Economics, Guangdong University of Finance and Economics, Guangzhou 510320, China

Energies, 2024, vol. 17, issue 17, 1-20

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.

Keywords: dynamic load modeling; induction motor; model reduction; grouping and aggregation method; transient voltage stability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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