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Genetic Algorithm–Optimized Active Disturbance Rejection Control for Robust Voltage Regulation in Standalone DFIG-Based Wind Energy Systems with Battery Storage: Real-Time Experimental Implementation

遺伝的アルゴリズム最適化アクティブ外乱抑制制御による独立型DFIG風力エネルギーシステムのロバスト電圧調整：バッテリ貯蔵を用いたリアルタイム実験実装 (AI 翻訳)

Mrabet N, Chakib M, Benzazah C, Ahmed E

Research Squareプレプリント2026-07-27#再生可能エネルギー対象セクター: power
DOI: 10.20944/preprints202607.1888.v1
原典: https://doi.org/10.20944/preprints202607.1888.v1

🤖 gxceed AI 要約

日本語

本論文は、独立型DFIG風力エネルギーシステムにおいて、遺伝的アルゴリズムで最適化したアクティブ外乱抑制制御(ADRC)を提案し、電圧調整性能を向上させる。バッテリエネルギー貯蔵システムをロータ側に接続し、充電状態を管理するアルゴリズムも実装。MATLAB/SimulinkシミュレーションとdSPACE1104による実時間実験で、従来のPI制御より優れた過渡応答と外乱抑制を確認した。

English

This paper proposes a genetic algorithm-optimized active disturbance rejection controller for voltage regulation in standalone DFIG wind energy systems with battery storage. A battery management algorithm maintains state of charge. Simulations and real-time experiments on dSPACE 1104 demonstrate superior transient response and disturbance rejection over conventional PI controllers.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本では離島や山間部での独立型再エネシステムの需要が高く、本制御手法は系統接続が困難な地域での風力発電の安定運用に貢献しうる。SSBJや有報との直接的な関連は薄いが、技術基盤として再エネ普及を支える。

In the global GX context

For global GX context, standalone renewable systems are crucial for rural electrification and resilience. This control approach improves voltage stability in off-grid wind-battery systems, supporting the broader energy transition. While not directly tied to disclosure frameworks, it addresses technical barriers to renewable integration.

👥 読者別の含意

🔬研究者:Presents a GA-optimized ADRC with experimental validation, offering a reference for advanced control in standalone wind-battery systems.

🏢実務担当者:The battery management algorithm and experimental results can guide design of reliable off-grid wind systems for remote applications.

📄 Abstract（原文）

This paper presents the design, simulation, and experimental validation of a Genetic Algorithm (GA)-optimized Active Disturbance Rejection Controller (ADRC) for voltage regulation in a standalone Doubly Fed Induction Generator (DFIG)-based Wind Energy Conversion System (WECS). The proposed system is designed to operate under variable wind conditions and nonlinear load profiles, with a battery energy storage system (BESS) connected to the rotor side to enhance performance and stability. A battery management algorithm is incorporated to ensure safe operation and maintain the state of charge (SOC) within optimal limits. The control strategy is evaluated through detailed simulations in MATLAB/Simulink and validated experimentally using a real-time dSPACE 1104 platform. Results show that the GA-tuned ADRC offers superior voltage regulation, fast transient response, and strong disturbance rejection compared to conventional PI controllers. Moreover, the integration of the battery management algorithm ensures reliable energy flow and SOC control, confirming the practical feasibility of the proposed method for isolated renewable energy applications.

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