This article presents a dataset for thermal characterization of photovoltaic systems to identify snail trails and hot spot failures. This dataset has 277 thermographic aerial images that were acquired by a Zenmuse XT IR camera (7–13 μm wavelength) from a DJI Matrice 100 1drone (quadcopter). Additionally, our dataset includes the next environmental measurements: temperature, wind speed, and irradiance. The experimental set up consisted in a photovoltaic array of 4 serial monocrystalline Si panels (string) and an electronic equipment emulating a real load. The conditions for images acquisition were stablished in a flight protocol in which we defined altitude, attitude, and weather conditions.

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In view of the frequent ventilation network changes during production in underground mining, decreasing sensors and actuators without altering production control and safety is one of the chief engineering challenges. This work is focused on modeling identification and control strategies for underground ventilation networks in small‐scale mines using an experimental benchmark. Guidelines to obtain a discrete state space model are provided, considering the conservation laws in the network to define the structure of the linear model. The main purpose of the paper is to analyze the use of classic controllers in the mine ventilation system when there are limitations on the number of sensors and actuators available to design a feedback control system. A comparison of three classic control strategies is presented considering the a constraint on the available number of sensors. Experimental and simulation results are presented.

The DC-link capacitor is one of the components that are more prone to faults in energy-distributed systems based on voltage source inverters. A predictive maintenance approach should allow to foresee the risk of an unexpected system shutdown. In this study, a two-stage diagnostic approach that is aimed at determining the health status of the DC-link capacitor in a single-phase grid-connected PV system was proposed. The equivalent series resistance (ESR) and the capacitance (C) values were used as indicators in the estimation of the degradation stage. Electrochemical impedance spectroscopy (EIS) was used to estimate the impedance curve of the DC-link capacitor, and a multi-fitting algorithm allowed us to determine the ESR and C parameters. A comparison between the estimated values C and ESR and the nominal values was used to quantify the fault severity. It was demonstrated that the EIS allowed the determination of the capacitor impedance regardless of the actual operating conditions of the photovoltaic generator, such as during irradiance changes and with the maximum power point algorithm turned off. By using the capacitor simplified model and a multi-fitting algorithm, the C and ESR values were estimated with an error that was lower than 1%. An analysis of the hardware required to implement the proposed approach in real applications by achieving the desired accuracy was also proposed.

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Direct current microgrids (DCMGs) are currently presented as an alternative solution for small systems that feed sensitive electrical loads into DC. According to the scientific literature, DCMG maintains good voltage regulation. However, when the system is in islanded mode, very pronounced voltage variations are presented, compromising the system’s ability to achieve reliable and stable energy management. Therefore, the authors propose a solution, connecting the electrical network through a grid-tied voltage source converter (GVSC) in order to reduce voltage variations. A coordinated control strategy between the DCMG and GVSC is proposed to regulate the DC voltage and find a stable power flow between the various active elements, which feed the load. The results show that the control strategy between the GVSC and DCMG, when tested under different disturbances, improves the performance of the system, making it more reliable and stable. Furthermore, the GVSC supports the AC voltage at the point of common coupling (PCC) without reducing the operating capacity of the DCMG and without exceeding even its most restrictive limit. All simulations were carried out in MATLAB 2020.