This study addresses the problem of detection and isolation of open‐switch faults in voltage source inverters by processing the stator current measurements. First, the resulting post‐fault trajectories for the stator currents are analytically derived for single and concurrent faults (21 classes) by using Fourier series. This analysis motivated the proposed approach, which is based on the resulting pattern of the stator currents in the dq ‐frame after a fault, where a histogram of the trajectory is calculated by dividing the plane in 24 equally spaced sectors. From the calculated histogram, a distinctive signature is associated to each fault trajectory in the dq ‐plane. Single and double faults in the power semi‐conductors are analysed that all provide linearly independent signatures for fault isolation. The proposed isolation methodology is independent of the load torque (system disturbance), supply frequency and only requires the information of the stator currents. Furthermore, since the isolation stage is focused on the angle of the current trajectories in the dq ‐plane, open‐ and closed‐loop configurations of a variable speed drive can be simultaneously handled. Experimental results with a test bench of 3/4 HP induction motor under single and concurrent faults validated the proposed methodology.

This study presents a fault detection and isolation (FDI) method for open‐circuit faults (OCFs) in the switching devices of a grid‐connected neutral‐point‐clamped (NPC) inverter for photovoltaic (PV) applications. The proposed methodology addresses the fault diagnosis problem by a combined model‐based and data processing perspective to study single and simultaneous faults in the NPC inverter. For the model‐based scheme, a bank of sliding‐mode proportional–integral observers is suggested to estimate the fault profiles under an additive model. Thus, from the estimated fault profiles, and by performing a directional residual evaluation in a fixed reference frame, single and simultaneous fault scenarios can be isolated in the NPC inverter. However, for some fault classes, there is some ambiguity by just the model‐based approach that is overcome by employing the average line currents to construct extra fault signatures. The proposed FDI scheme only requires the measurements of line currents and grid voltages in the diagnosis media and can isolate single OCFs and simultaneous OCFs in the order or lower than a fundamental period of the grid frequency. Our new FDI methodology is validated through experimental data from a practical PV system in a closed‐loop grid‐connected NPC inverter under single and simultaneous OCF conditions.

Switch semiconductors are essential components in power electronics stages for photovoltaic (PV) systems, which are prone to failures caused mainly by thermal stress, thereby affecting PV energy production. Specifically, dc/dc boost power converters are commonly used as maximum power point tracking (MPPT) systems. Several works have been reported so far in the literature for switch fault detection and isolation (FDI) purposes in boost power converters. However, most of them require additional sensors and circuitry to those included in any PV system, which generate extra costs on the overall system. Hence, this work presents an efficient and low-cost switch fault diagnosis proposal, which requires only the most common measurements in PV systems, namely, PV current and voltage. This work departs from a data-driven FDI methodology for diagnosing switch open- and short-circuit faults in dc/dc boost converters. The experimental results have been evaluated against sudden irradiance changes and switch faults in a test bench of 350 $\text {W}$ operating under a closed-loop nonlinear control action for MPPT purposes by using the dSpace 1104 board.

Distributed maximum power point tracking photovoltaic (PV) systems based on series-connected dc/dc converters are one of the most promising PV configurations for an enhanced security and efficiency in distributed generation systems. Most of the works reported so far in the literature for control and stability analysis of these configurations are based on small-signal ac models. This could be a significant limitation, as this kind of linearization produces a good approximation of the nonlinear model of series-connected dc/dc converters only at the operating point. However, PV systems must be controlled for a large set of operating points with a satisfactory performance and robustness. Moreover, stability analysis of series-connected dc/dc converters has not yet been widely discussed in previous research. Therefore, this article presents a nonlinear model of series-connected boost dc/dc converters and develops control and stability analysis to fill the gap in this emerging topic. A systematic experimental and numerical investigation is performed in order to validate the effectiveness of the proposed control approach in this study.

Here, the authors study open‐circuit faults (OCFs) in the power switches of multilevel converters with a model‐based perspective. In specific, the authors address single‐phase cascaded H‐bridge (CHB) converters with n ‐levels in its output voltage (CHB‐ n L), which are designed as shunt active power filters. In this task, the OCFs are modelled by fault profiles with an additive structure in each subsystem of the CHB‐ n L converter. These additive fault profiles have constant and oscillatory components, where the constant term sign indicates the pair of damaged switches in the H‐bridge. Hence, a sliding‐mode integral observer is proposed to estimate the constant terms of the fault profiles. The complexity of the observer depends on the number of H‐bridges in the CHB‐ n L converter. As a result, the proposed fault detection and isolation (FDI) scheme relies on the estimated constant terms of the additive fault profiles to achieve a robust and fast diagnosis stage. The proposed model‐based FDI scheme is validated experimentally under single and multiple fault scenarios, and model uncertainty. During the evaluation, the derived methodology only requires less than one cycle of the fundamental frequency to isolate the faults, and show robustness to load changes and parametric uncertainty.