High-Voltage Outdoor Insulators' Performance Analysis: Bridging Real-world and Simulation Studies for Machine Learning Model Training

High-voltage insulators used in transmission lines provide electrical and mechanical support for power line conductors. These insulators are subjected to severe weather conditions and are susceptible to external factors. Consequently, monitoring contaminated insulators is paramount to guarantee the efficient operation of transmission lines. This study investigates and analyzes the influence of contaminated insulator performance on the dielectric dissipation factor. To analyze the effect of pollution on the glass insulator surface, real practical measurements are conducted along with a simulation study and insulators' contamination is examined. Three contamination levels (light, medium, and heavy) and different pollutants including iron (Fe), calcium (Ca), aluminium (Al), and kaolin with distinct relative permittivity and bulk conductivity measurements are discussed. The dielectric dissipation factors are calculated and measured using capacitance C and resistance R values obtained from the simulation and practical work. The results show a tendency for the dielectric dissipation factor to increase as the pollution on the insulator surface thickens and support us in training our models in machine learning for insulators' contamination model training and labelling later.