A novel mppt technique based on mutual coordination between two pv modules/arrays

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

Neighboring-Pixel-Based Maximum Power Point Tracking Algorithm for Partially Shaded Photovoltaic (PV) Systems

In this paper, a neighboring-pixel-based virtual imaging (NPBVI) technique is developed to comprehensively detect the shading conditions on PV arrays. The proposed VI technique is then merged with a probabilistic mechanism of shaded module currents. Finally, a mathematical model is presented, which predicts the current voltage (I-V) region corresponding to the global maximum (GM) of the shaded PV array. The effectiveness of the proposed NPBVI MPPT is validated through numerous experiments that were carried out using a hardware prototype with a 150 W power rating. For the experiments, a PV array consisting of 3 × 2 (Np× Ns ) 20 W PV modules was utilized. The experiments showcase agreement that the proposed method successfully identified the GM region of a partially shaded PV array

Coot bird algorithms based tuning PI controller for optimal microgrid autonomous operation

This paper develops a novel methodology for optimal control of islanded microgrids (MGs) based on the coot bird metaheuristic optimizer (CBMO). To this end, the optimum gains for the PI controller are found using the CBMO under a multi-objective optimization framework. The Response Surface Methodology (RSM) is incorporated into the developed procedure to achieve a compromise solution among the different objectives. To prove the effectiveness of the new proposal, a benchmark MG is tested under various scenarios, 1) isolate the system from the grid (autonomous mode), 2) islanded system exposure to load changes, and 3) islanded system exposure to a 3 phase fault. Extensive simulations are performed to validate the new method taking conventional data from PSCAD/EMTDC software. The validity of the suggested optimizer is proved by comparing its results with that achieved using the LMSRE-based adaptive control, sunflower optimization algorithm (SFO), Ziegler-Nichols method and the particle swarm optimization (PSO) techniques. The article shows the superiority of the suggested CBMO over the LMSRE-based adaptive control, SFO, Ziegler-Nichols and the PSO techniques in the transient responses of the system.The Researchers Supporting Project, King Saud University, Riyadh, Saudi Arabia.https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639Electrical, Electronic and Computer Engineerin

Hybrid cascaded MLI development for PV‐grid connection applications

Abstract For grid‐connected solar photovoltaic (PV) applications, a hybrid cascaded MLI (H‐CMLI) topology based on cascaded H‐bridge MLI is proposed in this study. The proposed configuration is a hybrid of two common MLIs: Cascaded H‐bridge and three‐phase cascaded voltage source inverter (VSI). For the same voltage level, the proposed topology enhances the number of the generated voltage levels while employing fewer components, relative to other traditional MLI topologies. Furthermore, the voltage stresses on switches in the proposed topology are decreased, compared to when each part operates independently. The proposed topology could be utilized for many applications, such as PV‐grid connection, active power filters, and STATCOM. To verify the effectiveness of the proposed topology, the model is developed in MATLAB/Simulink environment, in which a closed‐loop control scheme based on the traditional one is used to achieve the PV‐grid connection. Alongside the simulation results, the proposed topology and its control scheme are experimentally implemented in the laboratory. Two cases were experimentally applied to validate the successful performance of the proposed H‐CMLI: Open‐loop control and closed‐loop control for PV‐grid integration. The proposed control scheme effectively maintains the DC link voltage at its reference voltages. Also, the closed‐loop control scheme is capable of providing the power factor at unity and maintaining the total harmonic distortion (THD) of grid current within the acceptable limit. To demonstrate the proposed topology's functionality and viability, experimental results are provided

Hybrid MLI Topology Using Open-End Windings for Active Power Filter Applications

Different multilevel converter topologies have been presented for achieving more output voltage steps, hence improving system performance and lowering costs. In this paper, a hybrid multilevel inverter (MLI) topology is proposed for active-power-filter applications. The proposed MLI is a combination of two standard topologies: the cascaded H-bridge and the three-phase cascaded voltage source inverter. This configuration enhances the voltage levels of the proposed MLI while using fewer switches than typical MLI topologies. The proposed MLI was developed in the MATLAB/Simulink environment, and a closed-loop control technique was used to achieve a unity power factor connection of the PV modules to the grid, as well as to compensate for harmonics caused by nonlinear loads. To demonstrate that the configuration was working correctly and that the control was precise, the proposed MLI was constructed in a laboratory. A MicroLabBox real-time controller handled data acquisition and switch gating. The proposed topology was experimentally connected to the grid and the MLI was experimentally used as an active power filter to compensate for the harmonics generated due to nonlinear loads. This control technique was able to generating a sinusoidal grid current that was in phase with the grid voltage, and the grid current’s total harmonic distortion was within acceptable limits. To validate the practicability of the proposed MLI, both simulation and experimental results are presented

Technical and economic evaluation for off-grid hybrid renewable energy system using novel bonobo optimizer

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RST Digital Robust Control for DC/DC Buck Converter Feeding Constant Power Load

The instability of DC microgrids is the most prominent problem that limits the expansion of their use, and one of the most important causes of instability is constant power load CPLs. In this paper, a robust RST digital feedback controller is proposed to overcome the instability issues caused by the negative-resistance effect of CPLs and to improve robustness against the perturbations of power load and input voltage fluctuations, as well as to achieve a good tracking performance. To develop the proposed controller, it is necessary to first identify the dynamic model of the DC/DC buck converter with CPL. Second, based on the pole placement and sensitivity function shaping technique, a controller is designed and applied to the buck converter system. Then, validation of the proposed controller using Matlab/Simulink was achieved. Finally, the experimental validation of the RST controller was performed on a DC/DC buck converter with CPL using a real-time Hardware-in-the-loop (HIL). The OPAL-RT OP4510 RCP/HIL and dSPACE DS1104 controller board are used to model the DC/DC buck converter and to implement the suggested RST controller, respectively. The simulation and HIL experimental results indicate that the suggested RST controller has high efficiency

Manta Ray Foraging Optimization for the Virtual Inertia Control of Islanded Microgrids Including Renewable Energy Sources

Nowadays, the penetration level of renewable energy sources (RESs) has increased dramatically in electrical networks, especially in microgrids. Due to the replacement of conventional synchronous generators by RESs, the inertia of the microgrid is significantly reduced. This has a negative impact on the dynamics and performance of the microgrid in the face of uncertainties, resulting in a weakening of microgrid stability, especially in an islanded operation. Hence, this paper focuses on enhancing the dynamic security of an islanded microgrid using a frequency control concept based on virtual inertia control. The control in the virtual inertia control loop was based on a proportional-integral (PI) controller optimally designed by the Manta Ray Foraging Optimization (MRFO) algorithm. The performance of the MRFO-based PI controller was investigated considering various operating conditions and compared with that of other evolutionary optimization algorithm-based PI controllers. To achieve realistic simulations conditions, actual wind data and solar power data were used, and random load fluctuations were implemented. The results show that the MRFO-based PI controller has a superior performance in frequency disturbance alleviation and reference frequency tracking compared with the other considered optimization techniques

Hardware-In-the-Loop Validation of Direct MPPT Based Cuckoo Search Optimization for Partially Shaded Photovoltaic System

During partial shading conditions (PSCs), the power-voltage curve becomes more complex, having one global maximum power (GMP) and many local peaks. Traditional maximum power point tracking (MPPT) algorithms are unable to track the GMP under PSCs. Therefore, several optimization tactics based on metaheuristics or artificial intelligence have been applied to deal with GMP tracking effectively. This paper details how a direct control cuckoo search optimizer (CSO) is used to track the GMP for a photovoltaic (PV) system. The proposed CSO addresses the limitations of traditional MPPT algorithms to deal with the PSCs and the shortcomings of the particle swarm optimization (PSO) algorithm, such as low tracking efficiency, steady-state fluctuations, and tracking time. The CSO was implemented using MATLAB/Simulink for a PV array operating under PSCs and its tracking performance was compared to that of the PSO-MPPT. Experimental validation of the CSO-MPPT was performed on a boost DC/DC converter using a real-time Hardware-In-the-Loop (HIL) simulator (OPAL-RT OP4510) and dSPACE 1104. The results show that CSO is capable of tracking GMP within 0.99–1.32 s under various shading patterns. Both the simulation and experimental findings revealed that the CSO outperformed the PSO in terms of steady-state fluctuations and tracking time

Neighboring-Pixel-Based Maximum Power Point Tracking Algorithm for Partially Shaded Photovoltaic (PV) Systems

In this paper, a neighboring-pixel-based virtual imaging (NPBVI) technique is developed to comprehensively detect the shading conditions on PV arrays. The proposed VI technique is then merged with a probabilistic mechanism of shaded module currents. Finally, a mathematical model is presented, which predicts the current voltage (I-V) region corresponding to the global maximum (GM) of the shaded PV array. The effectiveness of the proposed NPBVI MPPT is validated through numerous experiments that were carried out using a hardware prototype with a 150 W power rating. For the experiments, a PV array consisting of 3 × 2 (Np × Ns) 20 W PV modules was utilized. The experiments showcase agreement that the proposed method successfully identified the GM region of a partially shaded PV array