Distributed Multiple Fault Detection and Estimation in DC Microgrids with Unknown Power Loads

TL;DR

This paper introduces a distributed fault detection and estimation method for DC microgrids with unknown loads, using a novel approach to distinguish between load changes and line faults.

Contribution

It presents the first solution addressing the challenge of separating load variations from line faults in microgrids with unknown power loads.

Findings

The proposed scheme accurately detects and estimates faults under noise and disturbances.

A differentiate-before-estimate strategy effectively distinguishes load changes from line faults.

Simulations demonstrate robustness and high estimation accuracy in various fault scenarios.

Abstract

This paper proposes a distributed diagnosis scheme to detect and estimate actuator and power line faults in DC microgrids (e.g., electric-vehicle charging microgrids) subject to unknown power loads and stochastic noise. To address actuator faults, we develop an optimization-based filter design approach within the differential-algebraic equation (DAE) framework, which achieves fault estimation, decoupling from power line faults, and robustness against noise. In contrast, the estimation of power line faults poses greater challenges due to the inherent coupling between fault currents and unknown power loads, especially under insufficient system excitation, where their effects become difficult to distinguish from measurements. To the best of our knowledge, this is the first study to address this critical yet underexplored issue. Our solution introduces a novel differentiate-before-estimate strategy. A set of diagnosis rules based on the temporal characteristics (i.e., duration of threshold violation) of a constructed residual is developed to distinguish step load changes from line faults. Once a power line fault is detected, a regularized least-squares (LS) method is activated to estimate the fault currents, for which we further derive an upper bound on the estimation error. Finally, comprehensive simulations validate the effectiveness of the proposed scheme in terms of estimation accuracy and robustness against disturbances and noise under different fault scenarios.