New Solar MPPT Control Technique Based on Incremental Conductance and Multi-Objective Genetic Algorithm Optimization

Rerhrhaye, Fathallah; Lahlouh, Ilyas; Ennaciri, Yassine; Benzazah, Chirine; Akkary, Ahmed El; Sefiani, Nacer

doi:10.15866/irecon.v10i3.22156

Cited by 2 publications

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“…At each stage, the genetic algorithm chooses individuals of the present population to serve as parents and to bear the future generation's offspring. The selection process is based on the individual's adaptability and scores to produce “the most suitable” individual who will pass on their traits and enable the population to evolve into a successful generation [ 36 , 37 ]. Two main rules are applied to produce the next generation from the current one.…”

Section: Algorithm's Optimizationmentioning

confidence: 99%

Multi-loop active disturbance rejection control and PID control strategy for poultry house based on GA, PSO and GWO algorithms

Elghardouf,

Ennaciri,

Elakkary

et al. 2024

Heliyon

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Section: Algorithm's Optimizationmentioning

confidence: 99%

Multi-loop active disturbance rejection control and PID control strategy for poultry house based on GA, PSO and GWO algorithms

Elghardouf,

Ennaciri,

Elakkary

et al. 2024

Heliyon

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“…Numerous MPPT approaches have been used to (WECS) in earlier literature. DC/DC converters function as MPP monitor and link wind energy conversion systems [11] to diverse load needs. Buck-boost and buck-boost converters most used.…”

Section: The Proposed Systemmentioning

confidence: 99%

Maximum power optimization of a direct-drive wind turbine connected to PMSG using multi-objective genetic algorithm

Mrabet,

Benzazah,

El Akkary

et al. 2024

IJAPE

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This work aimed to develop and evaluate a maximum power point tracking (MPPT) control system for a wind energy conversion system (WECS) based on a permanent magnet synchronous generator (PMSG). PMSG is commonly used to generate direct-drive and variable-speed wind energy. Initially, the generator and converter on the DC load side are controlled to follow the wind speed reference set by the MPPT algorithm. The paper presents the optimization problem formulation, including the optimization space, constraints, and objectives. The genetic algorithm (GA) is used to extract the maximum power from the WECS in this design improvement. In this study, to control and stabilize the maximum power point (MPP) of the wind turbine, a proportional integral (PI) controller and a GA heuristic approach were utilized. The GA approach was employed to determine the best settings (Kp, Ki) using MATLAB/Simulink with a 12.3 kW PMSG to model and simulate the proposed system. Based on four performance indicators-integrated squared error (ISE), integrated absolute error (IAE), integrated time absolute error (ITAE), and integrated time squared error (ITSE), the GA approach was used to optimize the controller settings. The results of the simulation show that the wind turbine (WT) can effectively track the necessary MPP. The simulation's output also includes generated power, DC bus voltage, electromagnetic torque, and currents.

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New Solar MPPT Control Technique Based on Incremental Conductance and Multi-Objective Genetic Algorithm Optimization

Cited by 2 publications

References 0 publications

Multi-loop active disturbance rejection control and PID control strategy for poultry house based on GA, PSO and GWO algorithms

Multi-loop active disturbance rejection control and PID control strategy for poultry house based on GA, PSO and GWO algorithms

Maximum power optimization of a direct-drive wind turbine connected to PMSG using multi-objective genetic algorithm

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