New control strategy for multifunctional grid-connected photovoltaic systems

Soumana, Ricsa Alhassane; Saulo, Michael Juma; Muriithi, Christopher Maina

doi:10.1016/j.rineng.2022.100422

Cited by 26 publications

(10 citation statements)

References 27 publications

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“…The choice of an MPPT control technique depends on specific application requirements and the operating conditions of the PV system. P&O and IC are reliable for simpler setups, while ANN offers a cutting-edge solution for systems demanding adaptability and enhanced performance in dynamic environments (Soumana, Saulo, & Muriithi, 2022). Researchers and practitioners should carefully consider these tradeoffs when selecting the most appropriate MPPT technique for their particular use case (Lazarov, Zarkov, Stoyanov, & Kanchev, 2012).…”

Section: Description Of Pv Conversion Chainmentioning

confidence: 99%

Optimizing Photovoltaic System Performance through the Design and Development of an Artificial Neural Network MPPT Control

Meddah,

Belarbi,

Negadi

et al. 2024

Preprint

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This article conducts a thorough comparison of three Maximum Power Point Tracking control techniques for photovoltaic systems: Perturb and Observe, Incremental Conductance, and Artificial Neural Network. The study aims to identify the most effective MPPT method by subjecting each technique to numerical simulations. The article explores the performance, efficiency, and robustness of Perturb and Observe, Incremental Conductance and Artificial Neural Network in capturing the maximum power output from photovoltaic panels under varying environmental conditions. Following rigorous testing through numerical simulations, the superior technique is selected for implementation in a grid-connected photovoltaic power conversion chain. This research contributes valuable insights into the optimization of photovoltaic system performance through advanced MPPT control strategies, facilitating informed decisions for practical applications in renewable energy systems.

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Section: Description Of Pv Conversion Chainmentioning

confidence: 99%

Optimizing Photovoltaic System Performance through the Design and Development of an Artificial Neural Network MPPT Control

Meddah,

Belarbi,

Negadi

et al. 2024

Preprint

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“…Second stage power density, grid filter reduction, and reliability are achieved by high switching frequency interactions between a rectifier-inverter system and the utility grid. In 81 , a new control technique for multifunctional grid-connected photovoltaic systems (GCPVSs). While considering inverter capacity, it prioritizes PCC power quality enhancement.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis and mitigation of PQ disturbances in grid connected system using fuzzy logic based IUPQC

Ravi,

Kumar,

Dhanamjayulu

et al. 2023

Sci Rep

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Renewable energy integration introduces grid instability due to variable and intermittent sources like solar and wind, impacting reliability. This paper provides a thorough discussion of recent advancements and emerging trends in grid-integrated wind energy systems (GIWES) and grid-integrated solar energy systems (GISES). More than 70 research articles have been rigorously assessed and listed the technological and economic challenges. The increase in installations of grid-Integrating systems gives rise to challenges like as grid strain, peak shaving impacts, unpredictability of renewable energy sources (RES), and power quality disturbances. A variety of custom power devices, such as dynamic voltage restorers (DVR), static synchronous compensators (STATCOM), active power filters (APF), and unified power quality conditioners (UPQC), have gained popularity in response to these challenges. Among the various challenges, power quality disturbances, including voltage sag, swell, current and harmonics pose significant issues. To address these disturbances this work present a novel approach utilizing fuzzy logic (FL) to develop multi-feeder interline unified power-quality conditioners (MF-IUPQCs). The MF-IUPQC has three legs and three levels, each of which has four diode-clamped inverters. Switching is carried out through the use of space vector pulse width/duration modulation (SVPWM). Total harmonic distortion (THD) induced by nonlinear loads is reduced by the FLC-based MF-IUPQC, which also improves dynamic performance and offers a smooth DC-link voltage. The proposed control mechanism is implemented using MATLAB/Simulink. The fuzzy-based controller is compared to the industry-standard proportional-integral (PI) controller to determine its efficacy. Among them, the MF-IUPQC based on FLC delivers the smoothest voltage profile and the lowest THD.

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“…Auxiliary regulation involves the adjustment of power system parameters to counteract fluctuations, imbalances, and disturbances that impact grid stability. But the grid operates within acceptable limits and responds effectively to changes in demand and generation [10]. It involves adjusting power generation or consumption to maintain the grid frequency within specified limits.…”

Section: Introductionmentioning

confidence: 99%

Research on intelligent auxiliary regulation technology of large power grid section based on artificial intelligence

Kun Zhang

2024

jes

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In the modern era, large-scale renewable energy systems are integrated with advanced power systems and provide efficient operations. Also, optimized power systems require accurate energy generation and effective control systems to manage and ensure a stable power supply. Nevertheless, uncertainties are the intermittent balance of supply and high electricity demand. In addition, conventional power sources are not applicable for this challenging task and increase electricity costs. Therefore, an efficient Neuro Fuzzy Single phase Unified Power Quality Conditioner with Maximum Power Point Tracking (NF-SP UPQC -MPPT) strategy is developed for enhancing the grid-connected power systems. Here, Neuro-fuzzy logic is used as dynamic reactive power compensation in the grid. Also, this logic can efficiently handle the Energy storage system (ESS). Then SP UPQC was used to enhance power quality in electrical distribution systems. It combines both series and shunt compensators to mitigate various power quality issues such as voltage sags, harmonics, and unbalance. After that MPPT was utilized to extract the maximum power from the grid system. Model Predictive Control (MPC) controller to determine the overall stability and performance of the system. Moreover, the developed model was implemented on the MATLAB platform and performance is analyzed in terms of voltage deviation, grid current, reactive power fluctuations and Total Harmonic Distortion (THD).

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New control strategy for multifunctional grid-connected photovoltaic systems

Cited by 26 publications

References 27 publications

Optimizing Photovoltaic System Performance through the Design and Development of an Artificial Neural Network MPPT Control

Optimizing Photovoltaic System Performance through the Design and Development of an Artificial Neural Network MPPT Control

Analysis and mitigation of PQ disturbances in grid connected system using fuzzy logic based IUPQC

Research on intelligent auxiliary regulation technology of large power grid section based on artificial intelligence

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