• Energy Research

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.

Abstract A photovoltaic field is classically made of parallel connected strings, each one formed by a number of series connected modules. The total cross tied interconnection, which adds string-to-string wires, allows to increase the harvested energy when non-uniform operating conditions, like partial shadowing, occur. The simulation of mismatched total cross tied photovoltaic fields is mandatory to predict the increase of the power production accurately and for designing the proper power processing stage for the maximum power point tracking function. A fast and accurate simulation is also useful for model-based diagnostic purposes. In this paper an effective simulation model, which profits from a peculiar sparsity pattern of the system of non linear equations for achieving a very short computation time, is presented. It can be implemented in any platform and it has high potentialities also to be ported on embedded systems for real time simulation.

Abstract The power vs. voltage curve of a photovoltaic string operating under mismatched conditions can exhibit more than one maximum power point (MPP). In this paper, a direct method for the estimation of these points using explicit equations is introduced. The method employs a piecewise linear approximation of the current vs. voltage curve of each photovoltaic panel in the string and assumes that the open circuit voltage and the position of the maximum power points of each panel are known. Numerical results comparing the performances of the proposed approach with those offered by the adoption of the accurate single diode model show that the computational burden is reduced by almost four orders of magnitude. The approach is validated by experimental results exhibiting estimation errors lower than 5%. The satisfactory trade-off between accuracy and computation time provided by the proposed method is illustrated using two application examples: reconfiguration and long-term power production of PV strings. Moreover, an in-depth comparison of the existing simplified methods to estimate the MPPs has been performed.

Abstract In this paper a computationally efficient approach to the modeling of a photovoltaic array is presented. It is especially suited for simulating mismatched operating conditions, in which the different modules of the array work at different irradiation levels and temperatures. The model used allows to keep into account parametric tolerances and drifts among the modules. The proposed technique is based on the use of the Lambert W-function, which allows to obtain an explicit relationship between the voltage and the current of any photovoltaic module. The non linear system of equations describing the photovoltaic array is easily solved thanks to the explicit symbolic calculation of the inverse of the Jacobian matrix. The performances of the proposed numerical approach are discussed especially in cases where a deep mismatch affects the photovoltaic array.

This paper proposes an effective algorithm for simulating a large mismatched photovoltaic array. The technique allows to reproduce the array behavior at a cell level, including both the direct and the reverse operating mode, thus making the analysis of the hot-spot phenomenon possible. The algorithm is also able to manage the electrical variables related to the bypass diodes, which are usually connected in anti-parallel with a number of series connected cells. The non-linear system of equations describing the array is solved by using a suitable algorithm, introduced herein, for the inversion of the Jacobian matrix. The proposed procedure guarantees a high accuracy at a low computational burden. Some simulation examples allow to show the features of the technique on practical cases and to confirm its outstanding performances.

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.

The introduction of renewable energy sources in microgrids increases energy reliability, especially in small communities that operate disconnected from the main power grid. A battery energy storage system (BESS) plays an important role in microgrids because it helps mitigate the problems caused by the variability of renewable energy sources, such as unattended demand and voltage instability. However, a BESS increases the cost of a microgrid due to the initial investment and maintenance, requiring a cost–benefit analysis to determine its size for each application. This paper addresses this problem by formulating a method that combines economic and technical approaches to provide favorable relations between costs and performances. Mixed integer linear programming (MILP) is used as optimization algorithm to size BESS, which is applied to an isolated community in Colombia located at Isla Múcura. The results indicate that the optimal BESS requires a maximum power of 17.6 kW and a capacity of 76.61 kWh, which is significantly smaller than the existing 480 kWh system. Thus, a reduction of 83.33% in the number of batteries is obtained. This optimized size reduces operational costs while maintaining technical reliability. The proposed method aims to solve an important problem concerning state policy and the universalization of electrical services, providing more opportunities to decision makers in minimizing the costs and efforts in the implementation of energy storage systems for isolated microgrids.

Parametric identification of the single diode model of a photovoltaic generator is a key element in simulation and diagnosis. Parameters’ values are often determined by using experimental data the modules manufacturers provide in the data sheets. In outdoor applications, the parametric identification is instead performed by starting from the current vs. voltage curve acquired in non-standard operating conditions. This paper refers to this latter case and introduces an approach based on the use of interval arithmetic. Photovoltaic generators based on crystalline silicon cells are considered: they are modeled by using the single diode model, and a divide-and-conquer algorithm is used to contract the initial search space up to a small hyper-rectangle including the identified set of parameters. The proposed approach is validated by using experimental data measured in outdoor conditions. The information provided by the approach, in terms of parametric sensitivity and of correlation between current variations and drifts of the parameters values, is discussed. The results are analyzed in view of the on-site application of the proposed approach for diagnostic purposes.