Current collector optimizer topology to extract maximum power from non-uniform aged PV array

Refaat, Ahmed; Osman, Mohamed H.; Korovkin, Nikolay

doi:10.1016/j.energy.2020.116995

Cited by 24 publications

(4 citation statements)

References 33 publications

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“…In order to improve the student's knowledge, a good teacher allocation method is crucial, and which is defined by the fourth rule. Inspired by the hunting behavior of grey wolves, the top three best students are selected, as presented in Equation (13).…”

Section: Teacher Allocation Phasementioning

confidence: 99%

“…Step 4: Teacher Allocation Phase: Select top three best particles and calculate the Teacher T using Equation (13).…”

Section: Fundingmentioning

confidence: 99%

“…Work done to improve the step size of the aforementioned techniques, improved the performance and efficiency but increased the complexity, and required accurate sensors. A comprehensive mathematical model integration with operating PV conditions is cumbersome, moreover, a partial shading scenario, and intrinsic oscillations could not be minimized significantly [13].…”

Section: Introductionmentioning

confidence: 99%

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Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

et al. 2020

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The most cost-effective electrical energy is produced by photovoltaic (PV) systems, and with the smallest carbon footprint, making it a sustainable renewable energy. They provide an excellent alternative to the existing fossil fuel-based energy systems, while providing 4% of global electricity demand. PV system efficiency is significantly reduced by the intrinsic non-linear model, maximum power point (MPP), and partial shading (PS) effects. These two problems cause major power loss. To devise the maximum power point tracking (MPPT) control of the PV system, a novel group teaching optimization algorithm (GTOA) based controller is presented, which effectively deals with the PS and complex partial shading (CPS) conditions. Four case studies were employed that included fast-changing irradiance, PS, and CPS to test the robustness of the proposed MPPT technique. The performance of the GTOA was compared with the latest bio-inspired techniques, i.e., dragon fly optimization (DFO), cuckoo search (CS), particle swarm optimization (PSO), particle swarm optimization gravitational search (PSOGS), and conventional perturb and observe (P&O). The GTOA tracked global MPP with the highest 99.9% efficiency, while maintaining the magnitude of the oscillation <0.5 W at global maxima (GM). Moreover, 13–35% faster tracking times, and 54% settling times were achieved, compared to existing techniques. Statistical analysis was carried out to validate the robustness and effectiveness of the GTOA. Comprehensive analytical and statistical analysis solidified the superior performance of the proposed GTOA based MPPT technique.

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Section: Teacher Allocation Phasementioning

confidence: 99%

“…Step 4: Teacher Allocation Phase: Select top three best particles and calculate the Teacher T using Equation (13).…”

Section: Fundingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

et al. 2020

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“…Due to these changes, PV systems cannot offer maximum power to the load indefinitely. As a result, algorithm like maximum power point tracking (MPPT) is required to quickly adjust the PV system for changing climate conditions and supply optimal power to the load [3]. The main goals of MPPT are to ensure fast, precise maximum power tracking and reduce oscillations.…”

Section: Introductionmentioning

confidence: 99%

A novel robust model reference adaptive MPPT controller for Photovoltaic systems

Manna¹,

Singh²,

Akella³

et al. 2022

Scientia Iranica

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Solar photovoltaic (SPV) power generation has been more popular throughout the world in recent years due to its recyclable and eco-friendly nature. As a result, extracting the maximum power from SPV systems is important. Our contribution to this problem is to harvest maximum power under changes in ambient conditions and parametric variations. This paper presents a novel robust model reference adaptive maximum power point tracking controller (RMRAC-MPPT) for PV systems under five different cases including temperature, load, irradiance, boost converter capacitance, and inductance variations. To assess the robustness of the proposed method, MATLAB/Simulink software is used to compare it to the state-of-the-art techniques such as INC, P&O, FLC, Adaptive FLC, SMC, back stepping-SMC, PI, iRCS-MPC, P&O-MPC, ANFIS, BAT-FLC, and IPID. The verification of the proposed method is also tested in a laboratory-based OPAL-RT real-time simulator. It is evident that the proposed MPPT technique improves maximum power point (MPP) tracking capabilities while reducing steady-state oscillations. Furthermore, with five different parameter variations, the time duration to capture MPP is 1.5ms, which is significantly faster than other state-of-the-art 2 techniques. In addition, the proposed technique has a tracking efficiency of 99.75% and an overall system efficiency of 96%.

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An Efficient MPP Tracker Based on Flower Pollination Algorithm to Capture Maximum Power from PEM Fuel Cell

Elbaz,

Refaat,

Korovkin

et al. 2024

Earth and Environmental Sciences Library

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Current collector optimizer topology to extract maximum power from non-uniform aged PV array

Cited by 24 publications

References 33 publications

Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

A novel robust model reference adaptive MPPT controller for Photovoltaic systems

An Efficient MPP Tracker Based on Flower Pollination Algorithm to Capture Maximum Power from PEM Fuel Cell

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