Advanced Control Strategies for Wind Turbine Blade Angle Systems: A Comparative Study of Optimization Algorithms and Controllers
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| Publicado en: | International Journal of Energy Research vol. 2025 (2025) |
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| Autor principal: | |
| Otros Autores: | , , , , , |
| Publicado: |
John Wiley & Sons, Inc.
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| 024 | 7 | |a 10.1155/er/5550970 |2 doi | |
| 035 | |a 3227459779 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 163842 |2 nlm | ||
| 100 | 1 | |a Aya Hamdy Ramadan |u Department of Electrical Power and Machines Faculty of Engineering Ain Shams University Cairo Egypt | |
| 245 | 1 | |a Advanced Control Strategies for Wind Turbine Blade Angle Systems: A Comparative Study of Optimization Algorithms and Controllers | |
| 260 | |b John Wiley & Sons, Inc. |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Wind energy is a critical component of renewable energy systems, but the stochastic nature of wind speed poses significant challenges for consistent power generation. This paper addresses these challenges by proposing advanced control strategies to enhance the performance of wind turbine blade angle systems. We compare two optimization algorithms: harmony search algorithm (HSA) and exponential distribution optimizer (EDO) for tuning proportional-integral-derivative (PID) controllers under various operating conditions, including normal operation and fault scenarios. The EDO algorithm demonstrates superior performance in optimizing blade angle control, leading to improved system stability and faster response times. Building on this, we further evaluate three controllers: PID, proportional-derivative-derivative, and adaptive proportional-integral (API) using the EDO algorithm. The API controller, with its adaptive gains, outperforms both PID and proportional double derivative (PD2) controllers, achieving smoother pitch angle adjustments and more stable active power output under varying wind conditions. The results highlight the API controller’s ability to maintain rated power levels with minimal oscillations, even during rapid wind speed changes and fault conditions. This study provides valuable insights into the optimization of wind turbine blade angle systems, offering a robust framework for improving power extraction efficiency and system reliability. The findings suggest that the combination of EDO optimization and API control represents a promising approach for enhancing wind turbine performance in dynamic environments. | |
| 653 | |a Wind power | ||
| 653 | |a Oscillations | ||
| 653 | |a Proportional integral derivative | ||
| 653 | |a System reliability | ||
| 653 | |a Algorithms | ||
| 653 | |a Optimization techniques | ||
| 653 | |a Wind speed | ||
| 653 | |a Systems stability | ||
| 653 | |a Proportional derivative | ||
| 653 | |a Critical components | ||
| 653 | |a Efficiency | ||
| 653 | |a Comparative analysis | ||
| 653 | |a Renewable energy | ||
| 653 | |a Turbines | ||
| 653 | |a Comparative studies | ||
| 653 | |a Performance enhancement | ||
| 653 | |a Pitch (inclination) | ||
| 653 | |a Renewable resources | ||
| 653 | |a Optimization | ||
| 653 | |a Controllers | ||
| 653 | |a Design | ||
| 653 | |a Search algorithms | ||
| 653 | |a Cost analysis | ||
| 653 | |a Wind turbines | ||
| 653 | |a Turbine blades | ||
| 653 | |a Alternative energy sources | ||
| 653 | |a Probability distribution functions | ||
| 653 | |a Optimization algorithms | ||
| 653 | |a Turbine engines | ||
| 653 | |a Economic | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Attia, Mahmoud A |u Department of Electrical Power and Machines Faculty of Engineering Ain Shams University Cairo Egypt | |
| 700 | 1 | |a Mekhamer, S F |u Electrical Engineering Department at Future University New Cairo Egypt | |
| 700 | 1 | |a Badr, Ahmed O |u Department of Electrical Power and Machines Faculty of Engineering Ain Shams University Cairo Egypt | |
| 700 | 1 | |a Moustafa Ahmed Ibrahim |u Electrical Engineering Department University of Business and Technology Jeddah 23435 Saudi Arabia | |
| 700 | 1 | |a Alruwaili, Mohammed |u Department of Electrical Engineering College of Engineering Northern Border University Arar Saudi Arabia | |
| 700 | 1 | |a AboRas, Kareem M |u Department of Electrical Power and Machines Faculty of Engineering Alexandria University Alexandria 21544 Egypt | |
| 773 | 0 | |t International Journal of Energy Research |g vol. 2025 (2025) | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3227459779/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3227459779/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3227459779/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |