<p>This paper presents a multi-objective genetic algorithm approach for optimizing voltage and current control in a doubly-fed induction generator wind energy system. A comprehensive MATLAB/Simulink model is developed, and a multi-objective optimization problem is formulated to improve voltage and current regulation under dynamic operating conditions. The proposed method automatically tunes nine gains <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$ (K_{p,v},\ K_{i,v},\ K_{p,id},\ K_{i,id},\ K_{p,idr},\ K_{i,idr},\ K_{p,iqr},\ K_{i,iqr},\ K_{pg}) $</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">(</mo> <msub> <mi>K</mi> <mrow> <mi>p</mi> <mo>,</mo> <mi>v</mi> </mrow> </msub> <mo>,</mo> <mspace width="4pt" /> <msub> <mi>K</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>v</mi> </mrow> </msub> <mo>,</mo> <mspace width="4pt" /> <msub> <mi>K</mi> <mrow> <mi>p</mi> <mo>,</mo> <mi>i</mi> <mi>d</mi> </mrow> </msub> <mo>,</mo> <mspace width="4pt" /> <msub> <mi>K</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>i</mi> <mi>d</mi> </mrow> </msub> <mo>,</mo> <mspace width="4pt" /> <msub> <mi>K</mi> <mrow> <mi>p</mi> <mo>,</mo> <mi>i</mi> <mi>d</mi> <mi>r</mi> </mrow> </msub> <mo>,</mo> <mspace width="4pt" /> <msub> <mi>K</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>i</mi> <mi>d</mi> <mi>r</mi> </mrow> </msub> <mo>,</mo> <mspace width="4pt" /> <msub> <mi>K</mi> <mrow> <mi>p</mi> <mo>,</mo> <mi>i</mi> <mi>q</mi> <mi>r</mi> </mrow> </msub> <mo>,</mo> <mspace width="4pt" /> <msub> <mi>K</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>i</mi> <mi>q</mi> <mi>r</mi> </mrow> </msub> <mo>,</mo> <mspace width="4pt" /> <msub> <mi>K</mi> <mrow> <mi mathvariant="italic">pg</mi> </mrow> </msub> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> by seamlessly integrating MATLAB code with Simulink, enabling automated parameter assignment, simulation execution, and performance evaluation. This flexible framework is compatible with a wide range of controller structures (e.g., PI), making it adaptable to various control strategies. Simulation results under a turbulent wind profile demonstrate significant improvements in both voltage and current regulation, as well as reductions in overshoot and harmonic distortion for the system. Additionally, the proposed approach provides a set of optimal solutions for trade-off analysis, offering a systematic and effective framework for balancing multiple control objectives.</p>

Multi-objective Genetic Algorithm-Based Optimization of DFIG Voltage and Current Control for Wind Energy Systems

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发表日期：

2026年3月25日

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Adel Ilyas Saada,
Oumelkhier Bouchiba,
Mohammed Slimane Moulay Omar,
Zakarya Saada,
Mohammed Chakib Sekkal,
Saliha Chettih

摘要

This paper presents a multi-objective genetic algorithm approach for optimizing voltage and current control in a doubly-fed induction generator wind energy system. A comprehensive MATLAB/Simulink model is developed, and a multi-objective optimization problem is formulated to improve voltage and current regulation under dynamic operating conditions. The proposed method automatically tunes nine gains $ (K_{p,v},\ K_{i,v},\ K_{p,id},\ K_{i,id},\ K_{p,idr},\ K_{i,idr},\ K_{p,iqr},\ K_{i,iqr},\ K_{pg}) $ $(K_{p, v}, K_{i, v}, K_{p, i d}, K_{i, i d}, K_{p, i d r}, K_{i, i d r}, K_{p, i q r}, K_{i, i q r}, K_{pg})$ by seamlessly integrating MATLAB code with Simulink, enabling automated parameter assignment, simulation execution, and performance evaluation. This flexible framework is compatible with a wide range of controller structures (e.g., PI), making it adaptable to various control strategies. Simulation results under a turbulent wind profile demonstrate significant improvements in both voltage and current regulation, as well as reductions in overshoot and harmonic distortion for the system. Additionally, the proposed approach provides a set of optimal solutions for trade-off analysis, offering a systematic and effective framework for balancing multiple control objectives.