Adaptive Piecewise Linearization-Based Fault Characteristic Analysis Method for Distribution Networks

With the widespread application of Distributed Generation (DG) in modern distribution networks, the operational and fault characteristics of distribution networks have become increasingly complex. Traditional fault diagnosis methods are difficult to meet real-time diagnostic needs due to high computational complexity. This paper proposes a fault characteristic linearization calculation model based on Taylor expansion, combined with an adaptive piecewise linearization method, to address the uncertainty challenges brought by DG output power fluctuations. Firstly, a linear relationship between DG output power and system fault characteristics is established using Taylor expansion around the operating point, simplifying complex calculations to reduce model complexity. Secondly, the adaptive piecewise linearization method dynamically adjusts the operating point and optimizes the partitioning to reduce linearization errors, ensuring high accuracy even when there are significant fluctuations in DG output. Simulation results show that the proposed method can effectively track nonlinear fault characteristic changes, significantly reducing computational errors and providing reliable theoretical support for real-time fault diagnosis in distribution networks.