Robust power optimization strategy for wind-driven induction machines using type-2 and type-1 fuzzy logic controllers
タイプ2およびタイプ1ファジィ論理コントローラを用いた風力駆動誘導機のロバスト電力最適化戦略 (AI 翻訳)
Belkhiri, Driss, Nassiri, Boujemaa, Ajaamoum, Mohamed
🤖 gxceed AI 要約
日本語
本論文は、風力駆動誘導機の出力電力を最大化するロバストな最適化戦略を提案する。タイプ2およびタイプ1ファジィ論理コントローラを用いて、変動する風況や不確かなパラメータに対処し、最大電力点追従（MPPT）を実現する。実データによる検証の結果、提案手法は定常偏差や追従誤差が小さく、エネルギー収量が高いことが示された。センサレスでコスト増加も少ない。
English
This paper proposes a robust power optimization strategy for wind-driven induction machines using type-2 and type-1 fuzzy logic controllers. It maximizes harvested power under variable wind turbulence and uncertain parameters via MPPT based on rotor speed control. Validated with real data, the scheme shows superior tracking performance, lower errors (RMSE/MAE), and higher energy yield, while being independent of wind speed sensors and adding minimal cost.
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
日本は再生可能エネルギー、特に洋上風力の拡大を推進している。本論文の提案するロバスト制御手法は、風況変動が大きい日本海域でも高効率運転を可能にし、保守コスト低減や設備利用率向上に貢献する可能性がある。また、センサレス設計は既設風車への後付け適用も期待される。
In the global GX context
Globally, wind energy is a cornerstone of the energy transition. This work enhances turbine efficiency and reliability through advanced fuzzy logic control, reducing dependency on costly sensors. The results directly support better LCOE and grid integration, relevant for both onshore and offshore wind projects under variable conditions.
👥 読者別の含意
🔬研究者:Provides a comparative study of type-2 vs type-1 fuzzy logic for wind turbine MPPT, with robust performance analysis.
🏢実務担当者:Offers a sensorless control strategy that improves energy yield and reduces maintenance, applicable to wind farm operators and turbine manufacturers.
📄 Abstract（原文）
This paper proposes a reliable power optimization strategy that maximizes the harvested power of induction machines driven by wind, taking into account variable wind turbulence and uncertain machine parameters. This work explores the challenging task of designing type-2 fuzzy logic (T2FL) and conventional type-1 fuzzy logic (T1FL) controllers for wind energy conversion systems that exhibit multiple non-linearities. T2FL controllers are proficient in tackling uncertainties and offer quicker and more precise decision-making capabilities. The proposed approach is beneficial as it is independent of accurate wind turbine parameters, wind speed data, or additional sensors. Rather, it utilizes the mechanical rotor speed and the wind turbine power as input, which corresponds to maximum power point tracking (MPPT) through the management of the rotor speed via the machine-side converter. Real data validates the scheme against classical controllers, and via a set of simulations and statistical analyses, performance metrics like steady-state error, overshoot, tracking speed, and efficiency are widely assessed. The results show that the proposed scheme, which is independent of a dedicated wind speed sensor, demonstrates superior tracking performance, lower tracking errors, such as lower RMSE/MAE, and higher energy yield, although the wind speed and the system parameters change rapidly. Overall, this design provides more robust performance to random wind speed variations, increases operational efficiency and wind turbines' service life, and is low in adding mass and cost.
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/20636336first seen 2026-06-11 04:28:20 · last seen 2026-06-12 04:21:30
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