Hybrid salp swarm maximum power point tracking algorithm for photovoltaic systems in highly fluctuating environmental conditions

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 3, 2025

The maximum power delivered by a photovoltaic system is greatly influenced atmospheric conditions such as irradiation and temperature surrounding objects like trees, raindrops, tall buildings, animal droppings, clouds. partial shading caused these the rapidly changing parameters make point tracking (MPPT) challenging. This paper proposes hybrid MPPT algorithm that combines benefits of salp swarm (SSA) hill climbing (HC) techniques. As long rate change irradiance does not exceed specific limit, HC mode applied to track global (GMPP). Once high in detected, SSA activated. Moreover, proposed employs concept boundary handle fast slow fluctuating patterns. A comprehensive comparative evaluation SSA-HC with state-of-the-art algorithms has been undertaken. Four distinct cases have examined, including varying rates conditions. validated tested using developed hardware setup, simulated MATLAB for solar (PV) systems, compared standard HC. performance capability this technique at both steady-state dynamic under rapid gradual changes demonstrates its superiority over recent algorithms.

Язык: Английский

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Experimental validation of a low-cost maximum power point tracking technique based on artificial neural network for photovoltaic systems

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Авг. 7, 2024

Maximum power point tracking (MPPT) is a technique involved in photovoltaic (PV) systems for optimizing the output of solar panels. Traditional solutions like perturb and observe (P&O) Incremental Conductance (IC) are commonly utilized to follow MPP under various environmental circumstances. However, these algorithms suffer from slow speed low dynamics fast-changing environment conditions. To cope with demerits, data-driven artificial neural network (ANN) algorithm MPPT proposed this paper. By leveraging learning capabilities ANN, PV operating can be adapted dynamic changes irradiation temperature. Consequently, it offers promising environments as well overcoming limitations traditional techniques. In paper, simulations verification experimental validation ANN-MPPT presented. Additionally, analyzed compared methods. The numerical findings indicate that, examined methods, approach achieves highest efficiency at 98.16% shortest time 1.3 s.

Язык: Английский

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Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Июнь 17, 2024

Abstract This study looks into how to make proton exchange membrane (PEM) fuel cells work more efficiently in environments that change over time using new Maximum Power Point Tracking (MPPT) methods. We evaluate the efficacy of Flying Squirrel Search Optimization (FSSO) and Cuckoo (CS) algorithms adapting varying conditions, including fluctuations pressure temperature. Through meticulous simulations analyses, explores collaborative integration these techniques with boost converters enhance reliability productivity. It was found FSSO consistently works better than CS, achieving an average increase 12.5% power extraction from PEM a variety operational situations. Additionally, exhibits superior adaptability convergence speed, maximum point (MPP) 25% faster CS. These findings underscore substantial potential as robust efficient MPPT method for optimizing cell systems. The contributes quantitative insights advancing green energy solutions suggests avenues future exploration hybrid optimization

Язык: Английский

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Construction of Orchard Agricultural Machinery Dispatching Model Based on Improved Beetle Optimization Algorithm

Agronomy, Год журнала: 2025, Номер 15(2), С. 323 - 323

Опубликована: Янв. 27, 2025

In order to enhance orchard agricultural efficiency and lower fruit production expenses, we propose a BL-DBO (Beetle Optimization Algorithm introducing Bernoulli mapping Lévy flights) solve the machinery dispatching model within area. First, analyze problem in area establish its mathematical with objective of minimizing costs as constraint. To tackle problems uneven individual position distribution risk becoming stuck local optimal solutions traditional DBO algorithm, introduce during initialization phase DBO. This method ensures uniform initialized population. Furthermore, iterative process incorporated flight approach into positional update equations for beetles involved breeding, foraging, theft activities helps escape from solutions. Finally, conduct experiments based on location information Shunping Shunnong Orchard trees Shijiazhuang. The results indicate that, compared using human experience generated by not only reduce number purchases but also decrease energy loss non-working distances machinery, effectively saving costs.

Язык: Английский

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Research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithm

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 1, 2025

Due to environmental factors' influence, the power–voltage (P–V) curve of a photovoltaic array typically presents multiple peaks. The traditional gravitational search algorithm is inclined fall into local optimal solutions and demonstrates poor performance in maximum power point tracking. Consequently, this paper proposes applying PSO for optimizing GSA parameters. Meanwhile, introducing constant accomplishes dynamic adjustment three key parameters PSO. Furthermore, Levy flight step incorporated enhance global capability. improved can improve speed accuracy by adding memory group interaction particle update formula alleviate oscillation. Simulink modeling simulation analysis reveals that, compared with algorithms, identify more rapidly stably under static shading conditions.

Язык: Английский

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Global peak operation of solar photovoltaic and wind energy systems: Current trends and innovations in enhanced optimization control techniques

IFAC Journal of Systems and Control, Год журнала: 2025, Номер unknown, С. 100304 - 100304

Опубликована: Март 1, 2025

Язык: Английский

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A Novel Improved Gradient‐Based Optimizer for Single‐Sensor Global MPPT of PV System

Journal of Mathematics, Год журнала: 2025, Номер 2025(1)

Опубликована: Янв. 1, 2025

Gradient‐Based Optimizer (GBO) is a highly mathematics‐based metaheuristic algorithm that has garnered significant attention since its introduction. It offers several inherent advantages, such as low computational complexity, rapid convergence, and easy implementation. However, GBO some drawbacks, including lack of population diversity tendency to get trapped in local optima. To address these shortcomings, this research introduces an improved version (iGBO). In iGBO, introducing the Sobol sequence strategy ensures higher‐quality initial enhances convergence speed. Additionally, new modified Local Escaping Operator (LEO) proposed, which incorporates sine‐cosine operator DCS/Xbest/Current‐to‐2rand strategy. This LEO improves optimization efficiency boosts search capability, helping avoid The superiority iGBO thoroughly verified through comparisons with original well‐known newly developed algorithms on IEEE CEC’2022 benchmark suite. Furthermore, proposed approach applied extract photovoltaic system’s global maximum power point (MPP) under shading conditions. Three different patterns are considered assess reliability iGBO. performance compared leading algorithms, Particle Swarm Optimization (PSO), Reptile Search Algorithm (RSA), Black Widow (BWOA), Pelican OA (POA), Chimp (ChOA), Osprey (OOA), GBO. results reveal iGBO‐based MPPT consistently outperforms competitors identifying MPP various conditions followed by PSO, while RSA performs least effectively.

Язык: Английский

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Comparative Study of White Shark Optimization and Combined Meta-Heuristic Algorithm for Enhanced MPPT in Photovoltaic Systems

Energies, Год журнала: 2025, Номер 18(8), С. 2110 - 2110

Опубликована: Апрель 19, 2025

This paper proposes a novel hybrid metaheuristic algorithm (MHA) for maximum power point tracking (MPPT), integrating particle swarm optimization (PSO), the differential evolution (DEA), and grey wolf optimizer (GWO). The proposed method is inspired by structural phases of white shark (WSO), recently introduced MHA. study evaluates MPPT performance WSO compares it with approach to provide insights into optimal selection. key contributions include an in-depth analysis framework, benchmarking its against model. Both algorithms are implemented in system assessed based on speed, accuracy, adaptability. results indicate that achieves faster convergence due biologically design, whereas model, despite requiring additional coordination time, ensures comprehensive search space exploration. Notably, excels dynamic efficiency, which crucial accurately following time-varying P-V curves. underscores trade-off between speed demonstrating while advantageous rapid tracking, enhances overall under conditions. These findings offer valuable optimizing strategies renewable energy systems.

Язык: Английский

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Data-driven online prediction and control method for injection molding product quality

Journal of Manufacturing Processes, Год журнала: 2025, Номер 145, С. 252 - 273

Опубликована: Апрель 26, 2025

Язык: Английский

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Feasibility Analysis of an Electric Vehicle Charging Station with Solar Energy and Battery Storage

Energies, Год журнала: 2024, Номер 17(15), С. 3818 - 3818

Опубликована: Авг. 2, 2024

Ecuador, like every country in the world, urgently requires a conversion of transportation to electric power, both for economic and environmental reasons. This paper focuses on technical feasibility solar-powered charging station equipped with battery storage Cuenca, Ecuador. By reviewing current literature, we assess impact mobility its potential reduce fossil fuel dependence generate energy savings. The analysis encompasses various factors, including EV consumption, solar system sizing, production, capacity. Key findings indicate that integrating PV systems stations efficiently supports reliable sustainable supply. Simulation results reveal seasonal variations generation, highlighting importance proper sizing maintain supply reliability manage surplus generation. three scenarios underscores financial viability implementing without storage, yielding positive Internal Rate Return (IRR) Net Present Value (NPV). However, present negative NPV long investment return periods, impacting negatively. These insights underscore need balanced design ensure sustainability transition mobility.

Язык: Английский

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