A Novel MPPT Algorithm based on Aquila Optimizer under PSC and Implementation using Raspberry

Karmouni, Hicham; Chouiekh, Mohamed; Motahhir, Saad; Dagal, Idriss; Oufettoul, Hicham; Qjidaa, Hassan; Sayyouri, Mhamed

doi:10.1109/icrera55966.2022.9922834

Cited by 8 publications

(3 citation statements)

References 12 publications

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“…Several suspension system design proposals have been introduced to increase the vehicle suspension system performance and sophistication by redefining the element boundaries [45]. A large number of simulation experiments have been executed in the Simulink 2021a environment in order to investigate the performance of the suggested MPPT control [46].…”

Section: Introductionmentioning

confidence: 99%

Maximizing Electric Power Recovery through Advanced Compensation with MPPT Algorithms

Touairi,

Zekraoui,

Mabrouki

2024

Modelling and Simulation in Engineering

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The present investigation introduces an advanced methodology for maximum power point tracking (MPPT) applied to a piezo harvester scheme. A comprehensive rectifier circuit, equipped with an embedded MPPT component, is established to optimize energy production by monitoring a DC-DC inverter connected to the rectifier. Furthermore, the system’s sensitivity error has been finely tuned to dynamically adjust its impedance unit in real time, thereby optimizing load acquisition. This innovative approach seamlessly integrates the MPPT algorithm into the piezo harvester circuit. Moreover, the vehicle’s road handling is significantly augmented through the incorporation of a robust steering front and an active differential control system. Leveraging the MPPT module, the rectifier consistently achieves a power recovery efficiency exceeding 85%, independent of varying load conditions. Additionally, a DC-DC converter circuit has been seamlessly integrated to finely adjust the output voltage to meet specified levels. Numerical simulations demonstrate the effectiveness of the harvesting scheme, extracting a substantial output power of 90 W with an overall efficiency of 70%. The improved MPPT approach, employing angles of arrival (AoA) DV-Hop control strategies, minimizes the system’s power consumption based on the Global Positioning System (GPS). The utilization of Harris Hawks optimization (HHO) and the generation of quadrants in the four-quadrant operation mode of DC motors in the wireless sensor network (RCSFs) have been significantly enhanced in this study. Simulations reveal that, at a velocity of 50 km/h, shock absorbers utilizing the received signal strength indication (RSSI) can harvest between 60 and 90 W on a class C road, based on the time of arrival (TOA). Striking a balance in ride comfort using the time difference of arrival (TDOA) as a trade-off constitutes approximately 30% of the piezoelectric harvester (PEH) system’s power consumption when operating in active suspension mode, optimized by particle swarm optimization (PSO).

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Section: Introductionmentioning

confidence: 99%

Maximizing Electric Power Recovery through Advanced Compensation with MPPT Algorithms

Touairi,

Zekraoui,

Mabrouki

2024

Modelling and Simulation in Engineering

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“…In addition, the multiple peaks in the power-voltage (P-V) curve make maximum power point tracking (MPPT) challenging. Therefore, although a strategy based on I-V characteristics may adequately explore PV array performance, it must typically explain the MPPT process [31], [32], [33]. Thus, the PS restriction distorts the related maximum power point (MPP) voltage using global maximum power point tracking methods [34], [35].…”

Section: Introductionmentioning

confidence: 99%

Comparative Performance Analysis of PV Module Positions in a Solar PV Array Under Partial Shading Conditions

et al. 2023

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The irradiation intensity is the primary catalyst for energy production in photovoltaic (PV) systems. Nevertheless, it alleviates partial shading (PS) by inhibiting power production, primarily in habitable metropolitan areas, owing to surrounding objects or high soiling rates, particularly in dry and semi-arid climates. Hence, the PV module's location, orientation, and tilt angle significantly affect its performance and shorten its durability. Thus, this study undertakes a benchmark analysis of the two distinct panel positions' performance using PSIM and MATLAB software simulations and an actual practical test. A visual inspection of a solar power plant in Morocco's Green Energy Park is the origin of the survey concept; it observes that the soil density consistently covers certain PV panel spots. In this context, the solar energy data of an intelligent home deployed in the earlier-mentioned research platform has been deployed to emulate the performance of future buildings challenged with various obstacles. Therefore, the roof-mounted PV system satisfied the home's energy demands. In the first scenario, the PV module is in portrait mode. In the second case, they are in landscape orientation. The findings of this investigation demonstrate that standard PV panels produce more power when arranged in a landscape configuration than in a portrait configuration, exhibiting a discrepancy of up to 1010 Wh for a modest PV system. Finally, this study suggests appropriate orientation and design recommendations for standard and advanced solar modules, mainly those deployed in arid and heavily populated urban regions featuring severe shading constraints.

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“…Although several GMPPT techniques have been developed to overcome the limitations of conventional MPPT by accurately identifying the true maximum power point among multiple peaks [4]. Through a rigorous literature review encompassing GMPPT techniques, a meticulous examination revealed the ubiquitous recognition that accuracy, stability, and convergence speed remain persistent issues across all methodologies [5]. The classification of GMPPT methods encompasses optimizationbased algorithms, hybrid methodologies combining several optimization algorithms, and alternative approaches, such as curve fitting and fuzzy controllers [6]- [8].…”

Section: Introductionmentioning

confidence: 99%

Optimum MPPT Technique for Reconfiguring the Photovoltaic Array Under Partial Shading Failure

Oufettoul,

Motahhir,

Abdelmoula

et al. 2023

2023 12th International Conference on Renewable Energy Research and Applications (ICRERA)

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Partial shading (PS) considerably restricts photovoltaic (PV) systems, requiring extraction of the global maximum power point (GMPP). This persistent challenge engenders continuous fluctuations in the maximum power point (MPP) and demands utmost attention. In this regard, this paper presents a novel hybrid scanning technique and a Perturb and Observe (P&O) algorithm meticulously designed to accurately track the PV array's GMPP encountering PS, non-uniform dust deposition, or any common failures. Furthermore, it serves as an efficient tool that operates in tandem with the dynamic reconfiguration approaches. Extensive simulation tests were carried out using MATLAB Simulink software, while the validation and verification processes were conducted using an integrated Arduino board. Consequently, the simulation results exhibit outstanding accuracy and stability.

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A Novel MPPT Algorithm based on Aquila Optimizer under PSC and Implementation using Raspberry

Cited by 8 publications

References 12 publications

Maximizing Electric Power Recovery through Advanced Compensation with MPPT Algorithms

Maximizing Electric Power Recovery through Advanced Compensation with MPPT Algorithms

Comparative Performance Analysis of PV Module Positions in a Solar PV Array Under Partial Shading Conditions

Optimum MPPT Technique for Reconfiguring the Photovoltaic Array Under Partial Shading Failure

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