Automatic and Self Adaptive P&amp;O MPPT Based PID Controller and PSO Algorithm

Aoughlis, Celia; Belkaid, Abdelhakim; Çolak, İlhami; Guenounou, Ouahib; Kacimi, Mohand Akli

doi:10.1109/icrera52334.2021.9598489

Cited by 10 publications

(3 citation statements)

References 21 publications

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“…The nonlinear multiplicity of the base system's less precise equivalent modeling can be handled by the SI with ease. For PSO and for MPPT in TEG systems, [4] found that the PSO algorithm was able to significantly improve the efficiency of the TEG system, compared to other MPPT techniques, such as P&O. In this class, particle swarm optimization (PSO) [5,6], grey wolf optimization (GWO) [7], Harris hawk optimization (HHO) [8], grasshopper optimization (GHO) [9], and ant colony optimization (ACO) [10,11] are most implemented techniques.…”

Section: Literaturementioning

confidence: 99%

A Novel MPPT Controller Based on Mud Ring Optimization Algorithm for Centralized Thermoelectric Generator under Dynamic Thermal Gradients

et al. 2023

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Most industrial processes generate raw heat. To enhance the efficiency of industrial operations, this raw heat is recovered. Thermoelectric generators (TEG), as solid state devices, provide an excellent application of heat recovery in the form of most manageable electrical power. This work presents a novel MPPT controller based on the Mud Ring Optimization algorithm for a centralized Thermoelectric Generator (TEG) under dynamic thermal gradients. The existing stochastic optimization algorithm for Maximum Power Point Tracking (MPPT) control in renewable energy systems exhibits several limitations that affect its performance in MPPT control. The convergence speed, local minima trap, hyper parameters’ sensitivity toward the population size, acceleration coefficients, and the stopping criterion all impact the convergence stability. In addition to these limitations, sensor noise sensitivity in measurement fluctuates the control system leading to reduced performance. Therefore, the careful design and implementation of the MRO algorithm is crucial to overcome these limitations and achieve a satisfactory performance in MPPT control. The results of this study contribute to developing more efficient MPPT control of TEG systems and implementing renewable energy technologies. The algorithm effectively tracks the maximum power point in dynamic thermal environments and increases the power output compared to conventional MPPT methods. The findings illustrate the efficacy of the proposed controller providing a higher power output (Avg. 99.95%) and faster response time (220 ms) under dynamic thermal conditions achieving 38–70% faster tracking of the GM in dynamic operating conditions.

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Section: Literaturementioning

confidence: 99%

A Novel MPPT Controller Based on Mud Ring Optimization Algorithm for Centralized Thermoelectric Generator under Dynamic Thermal Gradients

et al. 2023

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“…Several research algorithms have been reported to extract the maximum power from solar panels under stochastic environmental conditions. A number of techniques have been presented in recent years as examples, including perturb and observe (P&O) [4], incremental conductance (INC) [5], and fuzzy logic controller (FLC) [6].…”

Section: Introductionmentioning

confidence: 99%

An Experimental Testing of Optimized Fuzzy Logic‐Based MPPT for a Standalone PV System Using Genetic Algorithms

Yahiaoui

Chabour

Guenounou

et al. 2023

Mathematical Problems in Engineering

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The choice and the dimensioning of the controller for the maximum power point tracking (MPPT) are determined for the ideal energy efficiency of the photovoltaic (PV) systems. Many works have been developed in the field of MPPT methods, especially fuzzy logic controllers. However, these are robust if the parameters of the membership functions have been well designed. In this paper, the performances of an intelligent fuzzy logic controller (FLC)-based MPPT method have been optimized by an evolutionary genetic algorithm (GA). The works presented in the literature have shown the efficiency of the proposed method compared to classical methods. In our paper, the validation of the experimental results obtained is given with respect to a reference signal. The control of the simulated PV source and the proposed method are built using the Simulink/Matlab environment and implemented on the dSPACE DS1104 controller to validate the practical execution of the suggested method. The standalone PV system has been tested in an emulated test bench experimentation. Experimental results confirm the efficiency of the proposed method and its high accuracy in handling fast varying load conditions.

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“…In this context, reconfiguration, floating photovoltaic plants, global maximum power point tracking, solar trackers, cooling systems, and cleaning techniques are the foremost methodologies applied to enhance the output efficiency of PV systems [2]. This investigation aims to provide substantial contributions to the advancement of photovoltaic systems by shifting its focus towards the rigorous exploration and implementation of GMPPT in the presence of anomalies, mainly under partial shading conditions, which may significantly exert a profound influence on the electricity output [3]. Consequently, the power-voltage (P-V) characteristic curve demonstrates a distinct profile, marked by the emergence of multiple peaks, thereby rendering the extraction of GMPP more challenging.…”

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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Automatic and Self Adaptive P&O MPPT Based PID Controller and PSO Algorithm

Cited by 10 publications

References 21 publications

A Novel MPPT Controller Based on Mud Ring Optimization Algorithm for Centralized Thermoelectric Generator under Dynamic Thermal Gradients

A Novel MPPT Controller Based on Mud Ring Optimization Algorithm for Centralized Thermoelectric Generator under Dynamic Thermal Gradients

An Experimental Testing of Optimized Fuzzy Logic‐Based MPPT for a Standalone PV System Using Genetic Algorithms

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

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