article · Journal Européen des Systèmes Automatisés
Wind turbines encounter unpredictable wind patterns and external disruptions that challenge standard operational control. This study addresses these issues by designing an approach to optimise the energy extracted by a wind energy conversion system featuring a permanent magnet synchronous generator. The method uses a maximum power point tracking strategy paired with a novel nonlinear proportional-integral controller. To calibrate the controller, three metaheuristic algorithms were tested: Particle Swarm Optimisation, Harris Hawks Optimisation, and Golden Jackal Optimisation. Based on simulation outcomes, the controller tuned using Golden Jackal Optimisation delivered the best overall results. It achieved precise and rapid mechanical speed regulation while minimising overshoot, which boosted energy extraction efficiency and improved overall dynamic performance.
Wind turbines face constant shifts in wind speed and environmental disturbances, which make harvesting steady energy difficult. Applying smarter, algorithm-tuned control systems helps turbine components react more swiftly to changing conditions. This enhances overall power output and reduces mechanical stress, helping renewable energy installations operate more effectively.
This work could be used by wind turbine manufacturers and energy system operators to improve turbine speed control and power extraction efficiency. The findings are currently based on simulation results, indicating that the technology is at an early, applied stage of development and requires hardware-in-the-loop testing or physical prototyping before field deployment.
AI-generated from the published abstract. Always read the original work before citing.
Wind turbines operate under highly dynamic conditions influenced by unpredictable wind profiles and external disturbances.The nonlinear characteristics of their dynamic models further complicate their modeling and control.This research focuses on optimizing the power output of a Wind Energy Conversion System (WECS) equipped with a Permanent Magnet Synchronous Generator (PMSG).To achieve this, a Maximum Power Point Tracking (MPPT) strategy is developed, integrating an innovative nonlinear PI controller.The parameters of this controller are fine-tuned using advanced meta-heuristic optimization techniques, including Particle Swarm Optimization (PSO), Harris Hawks Optimization (HHO), and Golden Jackal Optimization (GJO).Simulation results highlight the superior performance of the GJO-NLPI controller, demonstrating exceptional accuracy and rapid response in regulating mechanical rotation speed, while effectively reducing overshoot.The proposed control architecture showcases significant advancements in power extraction efficiency and dynamic performance.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.18280/jesa.580805
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
