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.

This paper proposes a fault identification system for short and open-circuit switch faults (SOCSF) for a dc/dc converter acting as a Maximum Power Point Tracker (MPPT) in Photovoltaic (PV) systems. A closed-loop operation is assumed for the boost dc/dc converter. A linearizing control plus a Proportional-Derivative (PD) controller is suggested for PV voltage regulation at the maximum power point (MPP). In this study, the SOCSF are modeled by using an additive fault representation and the fault identification (FI) system is synthesized departing from a Luenberger observer. Hence, an FI signal is obtained, which is insensitive to irradiance and load current changes, but affected by the SOCSF. For FI purposes, only the sensors used in the control system are needed. Finally, an experimental evaluation is presented by using a solar array simulator dc power supply and a boost dc/dc converter of 175 $\mathrm{W}$ in order to validate the ideas this study exposes.

This paper proposes a light, flexible, and yet reliable multi-parametric estimation algorithm for grid-connected VSC-based systems. This approach combines the nonlinear least squares (NLSQ) fitting algorithm and the steady-state extended harmonic domain (EHD) model to take into account the harmonic effects. The EHD model is used to take advantage of the harmonic content of the electrical signals to provide robustness and improved performance to the NLSQ estimation methodology. In addition, this harmonic formulation reduces the necessity of synchronized measurements. Details of the implementation are provided by an experimental case study in which the grid equivalent (Thevenin voltage, inductance, and resistance), the AC-side filter (inductance and resistance), and the converter switching and conduction loss resistance are accurately estimated for three different operating conditions.

This paper provides the comprehensive development procedures and mathematical model of an adjustable speed drive (ASD) for steady-state solutions, transient trajectories, and local stability based on a Floquet multiplier theory. A complete representation of the ASD is employed, which includes the dynamic equation of the dc link capacitor and the detailed models of the diode rectifier and of the pulse width modulated inverter. The power electronic switches are efficiently represented through smooth functions that allow a larger integration step to be used without the loss of precision in the solution. An efficient technique in the time domain for the computation of the periodic steady-state solution of electric systems, including ASDs based on a discrete-exponential-expansion matrix and the Poincaré map, is used. The obtained results are validated against the solutions obtained with an implementation using the Power System Blockset of Simulink and against the response obtained by the measurements from a 1.5-kVA ASD experimental setup system.

This paper presents an analytical solution to the maximum power point tracking (MPPT) problem for photovoltaic (PV) applications in the form of an improved fractional method. The proposal makes use of a mathematical function that describes the relationship between power and voltage in a PV module in a neighborhood including the maximum power point (MPP). The function is generated by using only three points of the P–V curve. Next, by using geometrical relationships, an analytical value for the MPP can be obtained. The advantage of the proposed technique is that it provides an explicit mathematical expression for calculation of the voltage at the maximum power point ($v_{MPP}$) with high accuracy. Even more, complex calculations, manufacturer data, the measurements of short circuit current ($i_{SC}$) and open-circuit voltage ($v_{OC}$) are not required, making the proposal less invasive than other solutions. The proposed method is validated using the P–V curve of one PV module. Experimental work demonstrates the speed in the calculation of $v_{MPP}$ and the feasibility of the proposed solution. In addition, this MPPT proposal requires only the typical and available measurements, namely, PV voltage and current. Consequently, the proposed method could be implemented in most PV applications.