Optimizing Marx Impulse Generator Settings for Lightning Impulse Testing of Transformers: An Automated Approach for Enhanced Efficiency and Accuracy

Abstract

The insulation strength of electrical equipment is required to be accurately tested to prevent insulation failures caused by abrupt overvoltages due to lightning strikes on power systems. In conventional methods, Marx impulse generators are used to produce impulse waveforms for testing. However, these methods often involve time consuming trial and error procedures and run the risk of damaging transformers during tests. This study proposes an algorithmic method for selecting resistor values in Marx generators to generate lightning impulse test waveforms. The proposed method establishes a circuit model based on the transformer’s frequency response and uses an optimization algorithm that combines a genetic algorithm with simulations of electromagnetic transients. The primary objective of the optimization process is to minimize the difference between the desired and simulated waveforms while obtaining optimum resistor block values. The proposed optimization-enabled method not only enhances accuracy in testing procedures but also reduces testing time and improves protection for test transformers. Consequently, these findings hold practical implications for electrical equipment manufacturers, test engineers, and researchers involved in insulation impulse testing, thereby promoting more reliable and effective testing procedures in the industry.