Ultra-High Frequency Localization Method for Transformer Partial Discharge based on TDOA and WLS-FA

Partial discharge is one of the main features of internal insulation defects in transformers and other high-voltage electrical equipment, and ultra-high frequency detection methods have been widely used in PD monitoring by virtue of their high sensitivity and strong anti-interference capability. To achieve 3D accurate localization of transformer partial discharge sources, this paper proposes an improved localization strategy based on the arrival time difference model and the weighted least squares-firefly algorithm. First, the WLS method is used to linearize the measured TDOA data to obtain the initial solution, and then the Firefly algorithm is used to optimize the search in the region near the initial solution to correct the possible deviation of WLS in noisy environments or when the initial value is poor. Simulation example is provided to verify the significant improvement in localization accuracy and stability of the proposed WLS-FA localization method. This brings theoretical significance and practical application for transformer partial discharge monitoring and equipment condition maintenance.