The main objective of this work is to provide an overview and evaluation of discrete model predictive controlbased maximum power point tracking (MPPT) for PV systems. A large number of MPC based MPPT methods have been recently introduced in the literature with very promising performance, however, an in-depth investigation and comparison of these methods have not been carried out yet. Therefore, this paper has set out to provide an in-depth analysis and evaluation of MPC based MPPT methods applied to various common power converter topologies. The performance of MPC based MPPT is directly linked with the converter topology, and it is also affected by the accurate determination of the converter parameters, sensitivity to converter parameter variations is also investigated. The static and dynamic performance of the trackers are assessed according to the EN 50530 standard, using detailed simulation models and validated by experimental tests. The analysis in this work aims to present a useful insight for practicing engineers and academic researchers when selecting the MPP tracker for their application.

The high variability of solar irradiance, originated by moving clouds, causes fluctuations in Photovoltaic (PV) power generation, and can negatively impact the grid stability. For this reason, grid codes have incorporated ramp-rate limitations for the injected PV power. Energy Storage Systems (ESS) coordinated by ramp-rate (RR) control algorithms are often applied for mitigating these power fluctuations to the grid. These algorithms generate a power reference to the ESS that opposes the PV fluctuations, reducing them to an acceptable value. Despite their common use, few performance comparisons between the different methods have been presented, especially from a battery status perspective. This is highly important, as different smoothing methods may require the battery to operate at different regimes (i.e., number of cycles and cycles deepness), which directly relates to the battery lifetime performance. This paper intends to fill this gap by analyzing the different methods under the same irradiance profile, and evaluating their capability to limit the RR and maintain the battery State of Charge (SOC) at the end of the day. Moreover, an analysis into the ESS capacity requirements for each of the methods is quantified. Finally, an analysis of the battery cycles and its deepness is performed based on the well-established rainflow cycle counting method.

Solar panels have a nonlinear voltage-current characteristic, with a distinct maximum power point (MPP), which depends on the environmental factors, such as solar irradiance and ambient temperature. In order to increase the power extracted from the solar panel, it is necessary to operate the photovoltaic (PV) system at the maximum power point (MPP). In this paper a novel maximum-power-point tracking (MPPT) method based on current perturbation algorithm (CPA) with a variable perturbation step and fractional short circuit current algorithm (FSCC) to determine an optimum operating current. An experimental comparative study of these maximum power point tracking methods using dSPACE is presented in this article. The effectiveness of proposed algorithm in terms of dynamic performance and improved stability is validated by detailed simulation and experimental studies.

This paper presents a method that overcomes the problem of the confusion during fast irradiance change in the classical MPPTs as well as in model predictive control (MPC)based MPPTs available in the literature. The previously introduced MPC-based MPPTs take into account the model of the converter only, which make them prone to the drift during fast environmental conditions. Therefore, the model of the PV array is also considered in the proposed algorithm, which allows it to be prompt during rapid environmental condition changes. It takes into account multiple previous samples of power, and based on that is able to take the correct tracking decision when the predicted and measured power differ (in case of drift issue). After the tracking decision is taken, it will be sent to a second part of the algorithm as a reference. The second part is used for following the reference provided by the first part, where the pulses are sent directly to the converter, without a modulator or a linear controller. The proposed technique is validated experimentally by using a buck converter, fed by a PV simulator. The tracking efficiency is evaluated according to EN50530 standard in static and dynamic conditions. The experimental results show that the proposed MPC-MPPT is a quick and accurate tracker under very fast changing irradiance, while maintaining high tracking efficiency even under very low irradiance.