Grid connected photovoltaic system efficiency and quality improvement using fuzzy-incond MPPT

Amara, Yasmine; Bradai, Rafik; Boukenoui, R.; Mellit, A.

doi:10.11591/ijpeds.v11.i3.pp1536-1546

Cited by 6 publications

(3 citation statements)

References 18 publications

(24 reference statements)

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“…The instantaneous conductance is equal to the negative of the incremental conductance at the MPP (Eq.9). This value is higher at the MPP left side and lower at the MPP right side as in Eq.10 and Eq.11 ,respectively [9] [14].…”

Section: A Incremental Conductance With Fixed Setep Sizementioning

confidence: 86%

“…However, this method is not validated for a large input signal and variable weather conditions. Others improved are report to the existing In-Cond by introducing intelligent controller in hybrid controllers, such as Fuzzy-incremental conductance proposed in [14] which uses a fuzzy control to adjust the step size of the incremental conductance and estimate the duty cycle variations. High performance and stability of the system under standard and variable weather conditions are obtained for a grid connected system.…”

Section: Introductionmentioning

confidence: 99%

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A Comparison Analysis between a Fixed and Multi-Step Size MPPTs for PV System under Variable Irradiance and Real Solar Curve

AMARA¹

2022

int. j. eng. mgmt. res.

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The control of the power electronic interfaces is essential to ensure the high efficiency of the photovoltaic system. In a DC stand-alone photovoltaic system, the boost converter is the most used. A regulator named maximum Power Point Tracking (MPPT) is inserted to control the ON/OFF states. Incremental conductance (In-Cond) is widely used to extract the maximum power point (MPP) from the Photovoltaic panel. It presents more efficiency and reliability compared to the conventional perturb and observes (P&O) technique. However, it presents power loss during the variations appearing during changes in weather conditions, due to the use of fixed step size. Accordingly, the present paper proposes a Multi-step size In-Cond to adapt the PV system to any change of the applied irradiance and to overcome the drawbacks of the existing In-Cond. Indeed, the present contributions introduced two-steps sizes instead of one. The principle is to design a step size value when approaching the MPP and a large value when the operating point is far from the MPP. Simulations and comparisons through MATLAB/Simulink under various applied conditions show that the proposed technique outperforms the conventional Inc-Cond in terms of convergence speed, response time, stability, and performance.

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Section: A Incremental Conductance With Fixed Setep Sizementioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

A Comparison Analysis between a Fixed and Multi-Step Size MPPTs for PV System under Variable Irradiance and Real Solar Curve

AMARA¹

2022

int. j. eng. mgmt. res.

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show abstract

“…The steady state oscillations at MPP under dynamic irradiation settings are reduced using ANN technique [19]. A novel fuzzy logic-IncCond based MPPT controller is implemented to reduce the step size and convergence time [20]. However, ANN requires more data with multiple layers.…”

Section: Introductionmentioning

confidence: 99%

Machine learning based cascaded ANN MPPT controller for erratic PV shading circumstances

Sreedhar,

Karunanithi,

Ramesh

2023

IJPEDS

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Power generation is challenged to meet energy demand during peak hours. As a result of limited non-renewable energy resources, power utilities heavily rely on fossil fuels. Therefore, scientists and researchers are looking for some distributed generators to provide additional power during peak hours. During such period, load demand is solved using solar power. As a consequence, grid-connected solar Photovoltaic (PV) systems are catching the attention owing to their ability to significantly reduce the use of fossil fuels. Under Partial Shading Condition (PSC), this paper utilizes Luo Converter along with Cascaded Artificial Neural Network (ANN), which is a Machine Learning Based Maximum Power Point Tracking (ML-MPPT) approach for tracking optimal power from PV system. The gained DC supply is converted into AC voltage using VSI attached to the system. In addition, PI controller engaged controls the voltage at grid side and results in effective grid synchronization. Furthermore, MATLAB Simulink analysis is carried out and the outcomes reveal the effectiveness of proposed system with 98% efficiency under different PV circumstances.

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Comparative Analysis between Proportional-Integral and Artificial Neural Network Control of a Grid-Connected PV System

Gouaamar,

Bri,

Mekrini

2023

E3S Web of Conf.

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This article presents a comprehensive analysis of the modeling and control techniques applied to a photovoltaic (PV) system that is connected to a three-phase grid. To successfully integrate the PV system with the electrical grid, an innovative and reliable controller has been designed and put into practice. The utilization of an artificial neural network (ANN) enables the system to optimize power extraction from the PV panels, benefiting from the ANN's resilience and swift response to varying conditions. Moreover, a robust proportional-integral (PI) control strategy is introduced to govern the grid-side operations. This strategy of action focuses on managing the injection of both active and reactive electricity into the grid as well as controlling the voltage of the DC bus. A series of detailed simulations were carried out evaluating the efficiency of the suggested control strategy in the MATLAB/SIMULINK. The results obtained from these simulations share insightful information on the effectiveness and efficiency of the control system in ensuring optimal operation and power management of the PV system within the grid-connected setup.

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Grid connected photovoltaic system efficiency and quality improvement using fuzzy-incond MPPT

Cited by 6 publications

References 18 publications

A Comparison Analysis between a Fixed and Multi-Step Size MPPTs for PV System under Variable Irradiance and Real Solar Curve

A Comparison Analysis between a Fixed and Multi-Step Size MPPTs for PV System under Variable Irradiance and Real Solar Curve

Machine learning based cascaded ANN MPPT controller for erratic PV shading circumstances

Comparative Analysis between Proportional-Integral and Artificial Neural Network Control of a Grid-Connected PV System

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