Abstract
With the increasing penetration of wind power, output fluctuations and fatigue damage of wind turbines pose greater challenges to wind farm operational control. This paper proposes a fatigue-aware optimal active power dispatch method for wind farms. First, a low-complexity cumulative fatigue damage calculation model is developed, and estimation models for tower thrust and main shaft torque are established based on wind speed and power data. Then, a multi-objective active power allocation model aiming at minimizing cumulative fatigue damage is formulated. Finally, the resulting multi-constrained optimization problem is solved using a Grey Wolf Optimizer with an improved convergence factor. Simulation results on a wind farm with 80 turbines demonstrate that the proposed method can effectively reduce turbine fatigue damage while satisfying grid dispatch requirements, with computational efficiency suitable for real-time operation and good engineering applicability.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2026 IEEE 9th International Electrical and Energy Conference, CIEEC 2026 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2267-2272 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798331549558 |
| DOIs | |
| State | Published - 2026 |
| Externally published | Yes |
| Event | 9th International Electrical and Energy Conference, CIEEC 2026 - Tianjin, China Duration: 15 May 2026 → 17 May 2026 |
Publication series
| Name | Proceedings of 2026 IEEE 9th International Electrical and Energy Conference, CIEEC 2026 |
|---|
Conference
| Conference | 9th International Electrical and Energy Conference, CIEEC 2026 |
|---|---|
| Country/Territory | China |
| City | Tianjin |
| Period | 15/05/26 → 17/05/26 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- active power dispatch
- fatigue damage
- grey wolf optimization algorithm
- rainflow counting method
- wind farm
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