Enhanced Wind Energy Integration and Grid Stability via Adaptive Nonlinear Control with Advanced Energy Management

This paper proposes an advanced wind energy conversion and management framework for improving grid integration and mitigating frequency and power fluctuations caused by wind intermittency. The studied system combines a permanent magnet synchronous generator (PMSG), a unidirectional Vienna rectifier on the machine side, a Li-ion battery energy storage system, and a bidirectional Vienna rectifier on the grid side. The main scientific challenge addressed in this work is to ensure efficient wind power extraction, secure battery charging/discharging operation, and stable power exchange with the grid under variable operating conditions. To this end, a comprehensive nonlinear state-space model of the overall system is first established. Then, nonlinear controllers based on integral sliding mode principles are developed to guarantee rotor-speed tracking, DC-bus voltage regulation, battery charging current limitation, and active/reactive power control. In addition, an adaptive observer is designed to estimate the battery open-circuit voltage and support the supervision of the state of charge. An energy management strategy is further proposed to coordinate the operating modes according to grid conditions and battery constraints. Simulation results demonstrate that the proposed approach effectively smooths wind power fluctuations, improves grid support capability, and enhances the overall dynamic performance of the wind energy conversion system.

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Publication Details

Journal
Energies
Published
2026-04-17
DOI
https://doi.org/10.3390/en19081941
Primary Topic
Wind Turbine Control Systems
Type
article
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article

Enhanced Wind Energy Integration and Grid Stability via Adaptive Nonlinear Control with Advanced Energy Management

Abdelmounime El Magri, Rachid Lajouad, Karim El Mezdi, Ilyass El Myasse et al.
Energies
Wind Turbine Control Systems
article

Enhanced Wind Energy Integration and Grid Stability via Adaptive Nonlinear Control with Advanced Energy Management

Abdelmounime El Magri, Rachid Lajouad, Karim El Mezdi, Ilyass El Myasse, Adil Mansouri, Nabil Elaadouli
article en

Abstract

This paper proposes an advanced wind energy conversion and management framework for improving grid integration and mitigating frequency and power fluctuations caused by wind intermittency. The studied system combines a permanent magnet synchronous generator (PMSG), a unidirectional Vienna rectifier on the machine side, a Li-ion battery energy storage system, and a bidirectional Vienna rectifier on the grid side. The main scientific challenge addressed in this work is to ensure efficient wind power extraction, secure battery charging/discharging operation, and stable power exchange with the grid under variable operating conditions. To this end, a comprehensive nonlinear state-space model of the overall system is first established. Then, nonlinear controllers based on integral sliding mode principles are developed to guarantee rotor-speed tracking, DC-bus voltage regulation, battery charging current limitation, and active/reactive power control. In addition, an adaptive observer is designed to estimate the battery open-circuit voltage and support the supervision of the state of charge. An energy management strategy is further proposed to coordinate the operating modes according to grid conditions and battery constraints. Simulation results demonstrate that the proposed approach effectively smooths wind power fluctuations, improves grid support capability, and enhances the overall dynamic performance of the wind energy conversion system.

EnergiesVol. 19(8)
National School of Business and Management in Settat (MA), Université Hassan 1er (MA), Université Hassan II Mohammedia (MA), University of Hassan II Casablanca (MA)
Affordable and clean energy
Openalex Percentile: Top 22%
Wind Turbine Control Systems
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Enhanced Wind Energy Integration and Grid Stability via Adaptive Nonlinear Control with Advanced Energy Management — Abdelmounime El Magri, Rachid Lajouad, et al. · Energies (2026) | TGRS Research Map | TGRS