A novel meta-heuristic optimization algorithm based MPPT control technique for PV systems under complex partial shading condition

Sustainable Energy Technologies and Assessments, Journal Year: 2021, Volume and Issue: 47, P. 101367 - 101367

Published: June 11, 2021

Language: Английский

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A Novel Improved Grey Wolf Algorithm Based Global Maximum Power Point Tracker Method Considering Partial Shading

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 6148 - 6159

Published: Jan. 1, 2024

Considering photovoltaic systems' sustainability and environmental friendliness, they have been widely used due to ease of installation as their cost reduces efficiency is improved. Analytical maximum power point tracking methods for system work effectively under uniform weather conditions. However, may fall into local points partial shading Although numerous meta-heuristic can overcome these challenges, still be improved regarding the convergence time global point. This paper suggests an grey wolf optimization method track points, enhancing process various The proposed has verified experimentally dynamic real conditions, consisting non-uniform provides better speed up 82% 1.4% compared basic optimization. According daily performance evaluation, IGWO runtime by 76% improves energy harvesting 2.3% obtained results validate superiority conditions in terms accuracy.

Language: Английский

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Intelligent adaptive PSO and linear active disturbance rejection control: A novel reinitialization strategy for partially shaded photovoltaic-powered battery charging

Computers & Electrical Engineering, Journal Year: 2025, Volume and Issue: 123, P. 110037 - 110037

Published: Jan. 4, 2025

Language: Английский

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High-efficiency hybrid PV-TEG system with intelligent control to harvest maximum energy under various non-static operating conditions

Journal of Cleaner Production, Journal Year: 2021, Volume and Issue: 320, P. 128643 - 128643

Published: Aug. 13, 2021

Language: Английский

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Adaptive ML-based technique for renewable energy system power forecasting in hybrid PV-Wind farms power conversion systems

Energy Conversion and Management, Journal Year: 2022, Volume and Issue: 258, P. 115564 - 115564

Published: April 1, 2022

Large scale integration of renewable energy system with classical electrical power generation requires a precise balance to maintain and optimize the supply–demand limitations in grids operations. For this purpose, accurate forecasting is needed from wind conversion systems (WECS) solar plants (SPPs). This daunting task has limits long-short term due highly random nature environmental conditions. paper offers hybrid variational decomposition model (HVDM) as revolutionary composite deep learning-based evolutionary technique for production microgrid farms. The objective obtain short-term five steps development. An improvised dynamic group-based cooperative search (IDGC) mechanism IDGC-Radial Basis Function Neural Network (IDGC-RBFNN) proposed enhanced forecasting. meteorological data time series utilized. SCADA provide values system. improvisation been made metaheuristic algorithm an training designed short (STWF) problem. results are compared two different topologies three heuristic algorithms: particle swarm intelligence (PSO), IDGC, group cooperation optimization (DGCO). 24 h ahead studied experimental simulations. analysis using seasonal behavior year-round performance analysis. prediction accuracy achieved by shows greater results. comparison statistically existing works literature showing effective at lower computational burden. Three graphically statistically.

Language: Английский

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Marine Predator Algorithm (MPA)-Based MPPT Technique for Solar PV Systems under Partial Shading Conditions

Energies, Journal Year: 2022, Volume and Issue: 15(17), P. 6172 - 6172

Published: Aug. 25, 2022

To satisfy global electrical energy requirements, photovoltaic (PV) is a promising source that can be obtained from the available alternative sources, but partial shading conditions (PSCs), which trap local maxima power point instead of peak (GMPP), are major problem needs to addressed in PV systems achieve uninterruptable continuous supply desired by consumers. avoid these difficulties, marine predator algorithm (MPA), bio-inspired meta-heuristic algorithm, applied this work. The work validated and executed using MATLAB/Simulink software along with hardware experimentation. superiority proposed MPA method four different PSCs on system, their characteristics compared those existing algorithms. PSC outcomes terms GMPP case 1 at 0.07 s 995.0 Watts; 2 0.06 674.5 3 0.04 654.1 4 364.2 Watts. software- hardware-validated results show its supremacy convergence time, efficiency, accuracy, extracted power.

Language: Английский

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Towards green energy for sustainable development: Machine learning based MPPT approach for thermoelectric generator

Journal of Cleaner Production, Journal Year: 2022, Volume and Issue: 351, P. 131591 - 131591

Published: March 30, 2022

Language: Английский

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Data-driven green energy extraction: Machine learning-based MPPT control with efficient fault detection method for the hybrid PV-TEG system

Energy Reports, Journal Year: 2023, Volume and Issue: 9, P. 3604 - 3623

Published: Feb. 27, 2023

The hybrid photovoltaic-thermoelectric generation system (PVTEG) gives two-fold benefits; firstly, it efficiently utilizes the available solar energy as converts both irradiance and thermal into electricity, secondly, enhances PV efficiency by reducing module surface temperature. However, of PVTEG is usually low because TEG are not highly efficient devices. Under changing environmental conditions, a well-designed maximum power point tracking (MPPT) controller can enhance 10%–15%. Therefore, this research explores evolutionary Neural Network based MPPT control technique for systems. snake optimizer optimally tuned weight biases Multilayer perceptron neural network (MLPNN), which provides fast real-time global maxima (GM) tracking. Furthermore, to robustness control, PID gains using SO algorithm. Use (SOPID) with (SOANN) results in stable, accurate under varying conditions. effectiveness proposed SOANN validated comparing PSOANN, RSANN GWOANN. very negligible oscillations. extract optimal an average 99.928% time less than 5ms. intelligent data driven fault detection algorithm proposed, do require any temperature or sensors cost system. Comparative, simulation, quantitative, statistical second superior performance terms efficiency, time, stability capability various practical condition.

Language: Английский

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Novel initialization strategy: Optimizing conventional algorithms for global maximum power point tracking

Results in Engineering, Journal Year: 2024, Volume and Issue: 22, P. 102067 - 102067

Published: March 31, 2024

In this research, a novel initialization strategy for conventional MPPT algorithms is proposed to define the best position tracking process start over P–V curve. Consequently, global maximum power point (GMPP) becomes nearest or first among existing multiple MPPs under partial shading condition (PSC). addition, step size of applied algorithm minimized based on its proximity actual GMPP. Therefore, speed improved, and loss can be reduced by approach. The major advantages approach are eliminating need modify original algorithm, hybridizing with other algorithms, employing any complex procedures, as in metaheuristic optimization algorithms. Hence, it overcoming main drawbacks MPPT. work, simplest technique, which perturbation observation (P&O) show enhancement performance without introduce processes. MATLAB/Simulink simulation model hardware implementation digital signal processing (DSP) controller TMS320F28335 two distinct methodologies used validate outperformance when applying technique PSC various weather fluctuations. outcomes that was successful extracting peak while also improving time response, accuracy, generating oscillations.

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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