New Solar MPPT Control Technique Based on Incremental Conductance and Multi-Objective Ant Colony Optimization

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

doi:10.15866/ireaco.v15i3.22076

Cited by 2 publications

(2 citation statements)

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“…Proton exchange membrane fuel cells (PEMFCs) function at a low-temperature range (<80°C) and are helpful for many applications. Electric vehicles (EVs) are our case study [24]. Indeed, the FCEV powertrain can be separated into three categories: fuel cell (FC) and battery (B); Fuel Cell and Ultracapacitor (UC); Fuel Cell, Battery, and Ultracapacitor.…”

Section: Hydrogen Application: Fuel Cellsmentioning

confidence: 99%

Hydrogen Production and Applications: A review

Marghani,

Chater,

Bouganssa

et al. 2023

E3S Web of Conf.

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A hydrogen fuel cell car, known as a Fuel Cell Electric Vehicle (FCEV), is essentially an electric vehicle that primarily relies on a fuel cell to generate energy. It also includes a secondary role for a battery within the powertrain. This technological configuration operates through four main scenarios, with the primary energy source being Hydrogen from onboard tanks, which powers the vehicle through the fuel cell and its associated components. Here's a breakdown of how it functions: Hydrogen enters the anode and interacts with a catalyst that separates hydrogen atoms, releasing electrons and protons. A conductive current collector connected to the vehicle's high-voltage circuitry collects these electrons. This electricity can charge the battery and/or drive the motors responsible for propelling the wheels. Fuel cells come in various types, characterized by the type of electrolyte they use, such as the Proton Exchange Membrane Fuel Cell (PEMFC), Solid Oxide Fuel Cell (SOFC), and Molten Carbonate Fuel Cell (MCFC). While all these fuel cell types can generate electricity, their efficiency can range from 30% to 60%. Although hydrogen fuel cell vehicles have shown promise, their adoption is still in its early stages due to challenges related to infrastructure, costs, and ongoing technological advancements. Our current research focuses on hydrogen production from renewable sources and its application in fuel cells to provide the required electrical power for electric vehicle propulsion. We aim to improve energy efficiency over a specified cycle and present a comprehensive analysis of our findings.

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Section: Hydrogen Application: Fuel Cellsmentioning

confidence: 99%

Hydrogen Production and Applications: A review

Marghani,

Chater,

Bouganssa

et al. 2023

E3S Web of Conf.

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“…Existing MPPT methods, including the INC approach, can be affected by the nonlinear interaction between environmental variables and the maximum power point. To address these issues, several MPPT techniques have been developed [8]. The INC strategy, although straightforward, relies on adjusting the duty cycle using the proportional-integral (PI) controller to achieve the maximum power point.…”

Section: Introductionmentioning

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 Ant Colony Optimization

Cited by 2 publications

References 0 publications

Hydrogen Production and Applications: A review

Hydrogen Production and Applications: A review

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

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