Optimization of the Black-Box Arc Models for DC Current Limiting Circuit Breakers Using Levenberg-Marquardt Algorithm

Abstract

The black-box arc model is a tool that facilitates efficient research based on empirical studies in breaker design and analysis. However, its application has primarily focused on the design of ACCBs, with only a few instances of its implementation in the design of low-voltage (LV) DC circuit breakers (DCCBs) using mechanical methods. In DCCBs with non-zero crossing characteristics, several factors need to be considered in the design process. Therefore, it is crucial to have a reliable and accurate DC arc model to effectively apply black-box arc model studies to actual DCCB designs. Especially, DC Current limiting circuit breaker (CLCB), which has fast operation characteristics through its own over current relays (OCR), requires reliable and accurate modeling because minor factors in the topology can contribute significantly to the interrupting performance. This paper presents a study on the characterization and modeling approach for the DC CLCB, which exhibits somewhat different arc voltage characteristics compared to the general Air Circuit Breaker (ACB). The black-box arc model incorporates existing schwarz and kema arc models, and the Levenberg-Marquardt Algorithm (LMA) is employed to optimize the parameters of each model. An efficient parameter optimization method for the CLCB model is proposed, and the characteristics of factors that should be considered in the design are identified. Consequently, the applicability and reliability of the model are verified through a comparative study with the short-circuit test results of the actual DC CLCB.

Keywords

• LVDC CLCB
• dc arc modeling
• black-box arc model
• Levenberg-Marquardt algorithm (LMA)
• parameter optimization