Overview of Solar Photovoltaic MPPT Methods: A State of the Art on Conventional and Artificial Intelligence Control Techniques

International Transactions on Electrical Energy Systems, Journal Year: 2024, Volume and Issue: 2024, P. 1 - 24

Published: April 17, 2024

Due to their inherent ability and environmentally friendly nature, renewable energy sources are the only real option for producing pollution-free in modern era. Solar is one of best possibilities this family supplying civilization with power it needs. Researchers can efficiently boost a PV panel’s efficiency by using maximum point tracking (MPPT) approach extract most from panel send load. The authors study examined surveyed sequential advancement solar cell research decade next, they elaborated on upcoming trends behaviours. Many algorithms (MPPTs) that employed photovoltaic systems (PVSs) function under both uniform partial shade situations structurally summarized work. Well-written descriptions features modules followed variety effective control strategies, including AI-based traditional controllers. In addition, appropriate knowledge various controllers essential when system exposed shade, keeping mind different systems’ classifications situation. A thorough analysis several soft computing-based techniques also included, as well many classical controller-based systems. First, well-developed MPPT methods used, artificial intelligence-based approaches. Later, comparison MPPT-controlling approaches established. For operating conditions (PSCs), advantages disadvantages outlined, contrasted, assessed. Future directions being investigated. collection datasets pertaining processes were gleaned articles has been presented. working PV-based those sectors production sustainable development would be very interested findings review study.

Language: Английский

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Hybrid MPPT control using hybrid pelican optimization algorithm with perturb and observe for PV connected grid

Frontiers in Energy Research, Journal Year: 2025, Volume and Issue: 12

Published: Jan. 3, 2025

Introduction Photovoltaic systems offer immense potential as a future energy source, yet maximizing their efficiency presents challenges, notably in achieving optimal voltage due to nonlinear behavior. Operating current and fluctuations, driven by temperature radiation changes, significantly impact power output. Traditional Maximum Power Point Tracking (MPPT) methods struggle adapt accurately these dynamic environmental conditions. While Artificial Intelligence (AI) optimization techniques show promise, implementation complexity longer attainment times for (MPP) hinder widespread adoption. Method This paper proposes hybrid MPPT technique that integrates the Pelican Optimization algorithm (POA) with Perturb Observe (P&O) grid-connected photovoltaic system (PV). The proposed consists of two loops: PO reference point setting loop (inner loop) POA fine-tuning (outer)loop. combination inner outer loops minimizes oscillations adjusting perturbation direction enhancing convergence speed MPPT. Results Discussion To validate efficacy different conditions, comprehensive comparison is conducted between pelican perturb observe (HPPO) other algorithms. has optimized PV grid outputs an 99%, best tracking speed, total harmonic distortion (THD) all conditions below 5% agree IEEE 519 standards.

Language: Английский

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A Review of Traditional and Advanced MPPT Approaches for PV Systems Under Uniformly Insolation and Partially Shaded Conditions

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(3), P. 1031 - 1031

Published: Jan. 21, 2025

Solar photovoltaic (PV) is a crucial renewable energy source that converts sunlight into electricity using silicon-based semiconductor materials. However, due to the non-linear characteristic behavior of PV module, module’s output power varies according solar radiation and ambient temperature. To address this challenge, maximum point tracking (MPPT) techniques are employed extract amount from modules. This paper offers comprehensive review widely used traditional advanced MPPT approaches in systems, along with current developments future directions field. Under uniform insolation, these methods compared based on their strengths weaknesses, including sensed parameters, circuitry, speed, implementation complexity, true MPPT, accuracy, cost. Additionally, algorithms evaluated terms performance reaching (MPP) under partial shading condition (PSC). Existing research clearly demonstrates exhibit superior efficiency comparison methods, although at cost increased design complexity higher expenses. By presenting detailed providing tables techniques, study aims provide valuable insights for researchers practitioners selecting appropriate applications.

Language: Английский

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Emerging maximum power point control algorithms for PV system: review, challenges and future trends

Electrical Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 18, 2025

Language: Английский

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Hybrid prediction method for solar photovoltaic power generation using normal cloud parrot optimization algorithm integrated with extreme learning machine

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 22, 2025

As the energy crisis environmental concerns rise, harnessing renewable sources like photovoltaics (PV) is critical for sustainable development. However, seasonal variability and random intermittency of solar power pose significant forecasting challenges, threatening grid stability. Therefore, this paper proposes a novel hybrid method, NCPO-ELM, to adequately capture spatial temporal dependencies within meteorological data crucial accurate predictions. To effectively optimize performance Extreme Learning Machine (ELM), Normal Cloud Parrot Optimization (NCPO) algorithm developed, inspired by Pyrrhura Molinae parrots' flock behavior cloud model theory. NCPO integrates five unique search strategies utilizes structure explore exploit. By introducing normal generate samples with specific distributions, enhances solution space coverage. subsequently employed Single-Layer Feedforward Network (SLFN) hidden layer hyperparameters, yielding optimal weights biases output layer, thereby reducing benchmark ELM's sensitivity noise instability from initialization. The actual results PV stations across different regions demonstrate that proposed NCPO-ELM shows superior prediction accuracy compared existing approaches, particularly time series diverse characteristics variations.

Language: Английский

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Direct Current Photovoltaic Solar Energy for Water Heating

Energies, Journal Year: 2025, Volume and Issue: 18(8), P. 2009 - 2009

Published: April 14, 2025

In this study, an experimental device is developed and implemented to evaluate the process of heating water using photovoltaic solar energy in direct current. The prototype consists a 147 L stainless steel tank, 5000 W element, four panels (370 each). Tests were carried out with power supply use maximum point tracking (MPPT) device. Temperature electrical sensors installed connected data acquisition system. results show that produced by PV can be used directly for heating. For supply, average total efficiency 12%; MPPT, value 18.2%. There clear improvement when tracking, improving reducing time needed reach set temperature. This technology applied residences, medical centers, other buildings require it.

Language: Английский

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Experimental analysis and performance evaluation of a solar PV-driven diffusion absorption refrigeration system

Case Studies in Thermal Engineering, Journal Year: 2025, Volume and Issue: 66, P. 105754 - 105754

Published: Jan. 9, 2025

Language: Английский

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Novel optimized closed-loop fuzzy control for maximum power tracking of proton exchange membrane fuel cell

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104303 - 104303

Published: Feb. 1, 2025

Language: Английский

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Experimental Validation of Intelligent MPPT Control for Photovoltaic Energy Chain

Engineering Technology & Applied Science Research, Journal Year: 2025, Volume and Issue: 15(2), P. 21754 - 21761

Published: April 3, 2025

This paper presents a comparative study of two Maximum Power Point Tracking (MPPT) algorithm techniques for Photovoltaic (PV) system, which includes PV generator, DC-DC boost converter, and resistive load. The compares the performance Artificial Neural Networks (ANN) Perturb Observe (P&O) algorithms in extracting maximum power under both stable variable climatic conditions. To this end, simulation tests are performed using MATLAB Simulink, with focus on energy efficiency response time different scenarios. findings validated through hardware setup LAUNCHPAD-XL 28F379D C2000 embedded coder. results demonstrate that ANN-based MPPT technique outperforms traditional P&O method, particularly rapidly changing environmental conditions, highlighting its superior systems. Additionally, ANN has been shown to exhibit enhanced adaptability irradiance temperature, thereby ensuring more consistent output across broad spectrum operating

Language: Английский

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Optimizing solar vehicle performance in urban shading conditions with enhanced control strategies

Ain Shams Engineering Journal, Journal Year: 2024, Volume and Issue: 15(10), P. 102985 - 102985

Published: Aug. 7, 2024

Solar-powered electric vehicles play a pivotal role in the forthcoming era of eco-friendly transportation, offering significant ecological advantages and addressing challenges posed by escalating fuel costs. Despite these advantages, often encounter disparity between available photovoltaic power required load power, necessitating reliance on energy storage systems. This situation gives rise to several challenges, including maximizing lifespan systems, identifying shiftable non-shiftable secondary systems real-time scenarios, ensuring road driver safety, navigating urban environment with obstacles causing shading. In response this paper presents pioneering solutions aimed at pushing boundaries solar-powered vehicle technology. First, novel approach PV converter control is introduced, leveraging an adaptive strategy within maximum point tracking algorithm. innovative technique dynamically adjusts algorithm's step size, particularly crucial when traversing shaded areas during movement, thus capture efficiency. Complementing breakthrough, proposes cutting-edge decentralized management strategy. characterized its versatility autonomy, featuring four parallel functions designed optimize signal frequency allocation each component, determine shedding percentages for based battery availability, identify optimal shedding, manage their activation deactivation seamlessly. To validate performance efficacy groundbreaking methodologies, extensive simulations were conducted using Matlab software, supplemented validation OPAL-RT platform hardware-in-the-loop application. The results obtained from both simulation testing provide compelling empirical evidence superior effectiveness high-performance capabilities proposed solutions.

Language: Английский

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