Comprehensive Fault Location on Transmission Lines Considering Variation in Line Parameters and Saturation in Current Transformers

Precise and rapid fault location on transmission lines is a cornerstone for enhancing the reliability and cost-efficiency of power systems. This paper proposes an innovative approach to a fault location by solving an optimization problem. The process relies on transmission line parameters, which can vary significantly under various operating conditions. Inaccurate parameters can severely affect fault location results. To address this issue, the paper proposes a parameter estimation process. Additionally, when faults occur near transmission line terminals, high fault currents can cause current transformer (CT) saturation and secondary current distortion, further impacting fault location accuracy. Instead of using currents distorted by CT saturation, this paper proposes to estimate the currents for inputting into the fault location procedure. To achieve accurate parameter and current estimation at both terminals of the transmission line, advanced artificial bee colony (ABC) algorithms such as Chaos ABC algorithm and Chaos particle swarm optimization (PSO)-ABC algorithm are employed. These are enhanced variants designed to improve exploitation ability, leading to better convergence values and reduced iteration requirements. The proposal is applied for locating three-line (L-L-L), three-line to-ground (L-L-L-G), two-line (L-L), two-line to-ground (L-L-G), and line-to-ground (L-G) faults on the transmission line with various locations. More specifically, the transmission line parameter variations and the CT saturation are considered to enhance the practicality of the fault location problem. Numerical results and comparisons confirm the proposal’s effectiveness, being better than the previous traditional fault location technique such as the impedance-based (IB) technique, as well as other meta-heuristic algorithms such as a grey wolf optimization (GWO) algorithm, a gravitational search (GS) algorithm, and an inclined planes optimization (IPO) algorithm. The error percentages of the fault location results are always less than 1.16%, 1.19%, 1.18%, 1.16%, and 1.04% in the L-L-L, L-L-L-G, L-L, L-L-G, and L-G fault location problems, respectively by using the Chaos PSO-ABC algorithm.