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.

Hybrid energy storage systems (HESSs) are essential for adopting sustainable energy sources. HESSs combine complementary storage technologies, such as batteries and supercapacitors, to optimize efficiency, grid stability, and demand management. This work proposes a semi-active HESS formed by a battery connected to the DC bus and a supercapacitor managed by a Sepic/Zeta converter, which has the aim of avoiding high-frequency variations in the battery current on any operation condition. The converter control structure is formed by an LQG controller, an optimal state observer, and an adaptive strategy to ensure the correct controller operation in any condition: step-up, step-down, and unitary gain. This adaptive LQG controller consists of two control loops, an internal current loop and an external voltage loop, which use only two sensors. Compared with classical PI and LQG controllers, the adaptive LQG solution exhibits a better performance in all operation modes, up to 68% better than the LQG controller and up to 84% better than the PI controller. Therefore, the control strategy proposed for this HESS provides a fast-tracking of DC-bus current, driving the high-frequency component to the supercapacitor and the low-frequency component to the battery. Thus, fast changes in the battery power are avoided, reducing the degradation. Finally, the system adaptability to changes up to 67% in the operation range are experimentally tested, and the implementation of the control system using commercial hardware is verified.

In a DC microgrid that involves a battery storage system, the primary energy management is performed by a battery charger/discharger based on a dc/dc power converter. Moreover, the battery charger/discharger is also used to regulate the voltage of the dc bus. One of the challenges at the control level is to regulate the DC bus voltage under battery charge and discharge conditions but also under different relations between the battery and bus voltages. For this reason, this paper proposes a battery charger/discharger based on the Sepic/Zeta converter and an adaptive controller, which provides bidirectional current flow, stable bus voltage, and satisfactory electrical characteristics. The main advantage of the proposed control system is the capability to adapt the controller parameters to any operation condition, which provides a general solution to interface any battery to any bus voltage. This study is focused on the design procedure of both the power converter and the controller, where a detailed mathematical analysis is performed to ensure the system performance and stability. Finally, the proposed solution is validated using an experimental prototype and a practical application case.

Se presenta una metodología de diseño e implementación de un sistema para generación de campos magnéticos uniformes de baja magnitud y frecuencia, sobre un volumen específico utilizando una bobina Helmholtz cuadrada tri-axial. El procedimiento de diseño se basa en conceptos teóricos y simulaciones a partir de expresiones matemáticas simples que relacionan el área, con campo magnético uniforme, con la longitud de las bobinas. Además, se conotruye el modelo computacional y se simula usando software de elementos finitos. Se observa que los resultados teóricos son consistentes con los resultados del modelo de simulación y las pruebas mediante medición de campo magnético. Se concluye que la metodología de diseño permite establecer un procedimiento simplificado y repetible, para obtener campo magnético uniforme en un volumen de trabajo adecuado para realizar estudios in-vitro o in-vivo.

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.