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The presence and evolution of static power converters in electric grids are growing on a daily basis. Starting from the most used voltage source converter (VSC), passing through the use of multilevel converters, the most recent configuration is the so-called modular multilevel converter (MMC). Because of its intrinsic advantages, it is used not only in high-voltage systems but also in low- and medium-voltage ones to interface renewable energy sources such as photovoltaic (PV) panels. Several configurations and maximum power point tracker (MPPT) algorithms have been proposed and analyzed for MMC-PV-based systems. However, when using distributed MPPTs, partial shading conditions cause a problem. The PV panel can be directly connected to the MMC using its dc link or submodule. Based on this configuration, this paper proposes a novel control strategy that tracks both the ac grid current and ac circulating current for a single-phase low-voltage system to obtain the maximum power under any irradiance condition. The effectiveness of the proposed control strategy is demonstrated through time-domain simulation results.

The integration of photovoltaic (PV) modules with a modular multilevel converter (MMC) is very interesting because it allows us to exploit the intrinsic advantages of that converter, such as modularity and high voltage quality, and to implement distributed maximum power point tracking algorithms. The latter can appropriately be performed through controlling the circulating currents. In the literature, some control strategies for both the AC and DC circulating currents were proposed to manage the power mismatch among the legs and between the arms of the MMC. In a previous work, the authors proposed a novel control strategy for the circulating current components and inserted a capacitor on the DC side of a three-phase MMC with integrated PV panels. In the present work, it is shown how the correct sizing of this capacitor is essential to optimize the AC circulating voltages and minimize converter losses. A sizing procedure is proposed, deeply analyzed, and validated through numerical simulations.

When solar irradiation is uniform along with the array, the P–V curve represents a unique maximum power point (MPP). If the cells undergo shade conditions in the presence of bypass diodes, the solar array’s power is decreased, and the P–V curve of the array represents multiple local MPPs (LMPP) and a global MPP (GMPP). LMPPs might mislead the maximum power point tracking (MPPT) algorithms because their characteristics are identical to the MPP. Various studies have been conducted on partial shading conditions. This study uses parallel distributed maximum power point tracking (DMPPT) due to the advantages of this structure. A high-gain converter is presented to resolve the high conversion gain required by the DC/DC converter in this structure. This study also presents MLP and RBF networks for MPP tracking and compares their efficiencies under the same irradiation and partial shading conditions. Since determining optimal weight coefficients in MLP neural networks and variances, means, and weights in RBF networks play an essential role in their performance, this study uses four optimization algorithms of particle swarm optimization (PSO), gray wolf optimization (GWO), grasshopper optimization algorithm (GOA), and Harris Hawks optimization (HHO). Finally, an adaptive fuzzy-PID controller controls the three-phase grid-connected inverter. A comparison of the results shows that the efficiency of MLP and RBFII is almost the same, about 98–99%. Moreover, the accuracy of MLP networks is higher than RBF, and RBF networks’ only advantage is shorter training time. In addition, RBF networks require much more activation functions for proper performance. The simulation outcomes confirm the superior efficacy of the HHO algorithm in training neural networks when compared to alternative algorithms.

Maximum power point tracking (MPPT) is an essential part of a photovoltaic (PV) power generation systems to obtain the possible biggest efficiency. In partial shading conditions (PSCs), distributed MPPT strategy is used to eliminate mismatching cases between PV modules and load. In this study, forward converter-based distributed MPPT approach is presented for small power module-level and submodule-level MPPT applications. First, operation principles of a forward converter are explained for an MPPT application. Then, performance of a forward converter is evaluated by perturb and observe (P&O) algorithm for module-level and submodule-level MPPT systems in MATLAB/Simulink. Simulation results show that in module-level MPPT technique, forward converter cannot track global maximum power point (MPP) in some PSCs. On the other hand, submodule-level MPPT guarantees global MPPT (GMPPT). Average tracking efficiencies are calculated as 71.24% and 95.34% for module-level and submodule-level MPPT, respectively. That is, submodule-level MPPT outperforms module-level MPPT. On the other hand, submodule-level MPPT is more expensive solution since hardware requirements are very high compared with the module-level MPPT strategy.

The integration of photovoltaic (PV) systems with three-phase four-wire (3P4W) distribution networks has imposed several challenges related to existing unbalanced loads, reactive power generation and harmonics content. In this paper, a multifunctional distributed maximum power point (MPPT) controller for grid integration of PV systems is proposed. The proposed distributed MPPT controller is developed based on employing a four-leg three-level T-type multilevel inverter. The proposed inverter performs multifunctionalities, including distributed MPPT, neutral current compensation for the unbalanced loads, supplying reactive power into the grid and the grid integration. Moreover, the proposed inverter overcomes the stochastic behavior of both the PV generation with partial shading problems and its operation with unbalanced loads as well. Furthermore, the new proposed controller injects sinusoidal output currents with decreased levels of total harmonic distortion (THD) into the grid. The tested case study is investigated for the various operating scenarios of PV generation and load demands. The results and tabulated performance comparisons have proven the superior performance of the proposed multifunctional PV generation system. The results show the ability of the proposed controller to efficiently extract distributed MPPT for all PV modules at all the tested scenarios. Additional improvement of the energy efficiency is achieved through the elimination of the neutral current due to existing unbalanced loads.

Partial shading poses a significant challenge to photovoltaic (PV) systems by degrading power output and overall efficiency, especially under non-uniform irradiance conditions. This paper proposes an advanced time-sharing maximum power point tracking (MPPT) control strategy implemented through a non-isolated single-phase multi-input microinverter architecture. The system enables individual power regulation for multiple PV modules while preserving their voltage–current (V–I) characteristics and eliminating the need for additional active switches. Building on the concept of distributed MPPT (DMPPT), a flexible full power processing (FPP) framework is introduced, wherein a single MPPT controller sequentially optimizes each module’s output. By leveraging the slow-varying nature of PV characteristics, the proposed algorithm updates control parameters every half-cycle of the AC output, significantly enhancing controller utilization and reducing system complexity and cost. The control strategy is validated through detailed simulations and experimental testing under dynamic partial shading scenarios. Results confirm that the proposed system maximizes power extraction, maintains voltage stability, and offers improved thermal performance, particularly through the integration of GaN power devices. Overall, the method presents a robust, cost-effective, and scalable solution for next-generation PV systems operating in variable environmental conditions.

Renewable energy resources such as offshore wind and wave energy are environmentally friendly and omnipresent. A hybrid offshore wind-wave energy system produces a more sustainable form of energy that is not only eco-friendly but also economical and efficient as compared to use of individual resources. The objective of this paper is to give a detailed review of co-generation technologies for hybrid offshore wind and wave energy. The proposed area of this review paper is based on the power conversions techniques, response coupling, control schemes for co-generation and complimentary generation, and colocation and integrated conversion systems. This paper aims to offer a systematic review to cover recent research and development of novel hybrid offshore wind-wave energy (HOWWE) systems. The current hybrid wind-wave energy structures lack efficiency due to their design and AC-DC-AC power conversion that need to be improved by applying an advanced control strategy. Thus, using different power conversion techniques and control system methodologies, the HOWWE structure can be improved and will be transferrable to the other hybrid models such as hybrid solar and wind energy. The state-of-the-art HOWWE systems are reviewed. Critical analysis of each method is performed to evaluate the best possible combination for development of a HOWWE system.

The integration of large-scale photovoltaic (PV) systems requires advanced converter architectures capable of ensuring both high efficiency and fast dynamic response. Leveraging the inherent modularity and low harmonic distortion of Modular Multilevel Converters (MMCs), this paper presents a novel control and modulation framework for grid-connected PV applications. The key innovation lies in the implementation of distributed, string-level Maximum Power Point Tracking (MPPT), enabling optimal energy extraction even under non-uniform (shaded) irradiance conditions. The proposed method operates within a dual time-scale control architecture: an outer Perturb and Observe (P&O) loop assigns independent power references, while the inner modulation stage employs an innovative switching strategy that activates only one module per sampling period. Unlike conventional MPPT-based schemes, where submodules are driven by voltage references, the proposed approach directly regulates the power of each MMC submodule, eliminating the need for PV-side current measurement.

A novel maximum power point tracking (MPPT) technique based on mutual coordination of two photovoltaic (PV) modules/arrays has been proposed for distributed PV (DPV) systems. The proposed technique works in two stages. Under non-mismatch conditions between PV modules/arrays, superior performance stage 1 is active, which rectifies the issues inherited by the perturb and observe (P&O) MPPT. In this stage, the technique revolves around the perturb and observe (P&O) algorithm containing an intelligent mechanism of leader and follower between two arrays. In shading conditions, stage 2 is on, and it works like conventional P&O. Graphical analysis of the proposed technique has been presented under different weather conditions. Simulations of different algorithms have been performed in Matlab/Simulink. Simulation results of the proposed technique compliment the graphical analysis and show a superior performance and a fast response as compared to others, thus increasing the efficiency of distributed PV systems.

Recently direct current (DC) microgrids have drawn more consideration because of the expanding use of direct current (DC) energy sources, energy storages, and loads in power systems. Design and analysis of a standalone solar photovoltaic (PV) system with DC microgrid has been proposed to supply power for both DC and alternating current (AC) loads. The proposed system comprises of a solar PV system with boost DC/DC converter, Incremental conductance (IncCond) maximum power point tracking (MPPT), bi-directional DC/DC converter (BDC), DC-AC inverter and batteries. The proposed bi-directional DC/DC converter (BDC) lessens the component losses and upsurges the efficiency of the complete system after many trials for its components’ selection. Additionally, the IncCond MPPT is replaced by Perturb & Observe (P&O) MPPT, and a particle swarm optimization (PSO) one. The three proposed techniques’ comparison shows the ranking of the best choice in terms of the achieved maximum power and fast—dynamic response. Furthermore, a stability analysis of the DC microgrid system is investigated with a boost converter and a bidirectional DC-DC converter with the Lyapunov function for the system has been proposed. The complete system is designed and executed in a MATLAB/SIMULINK environment and validated utilizing an OPAL real-time simulator.