Mitigating Turbine Mechanical Loads Using Engineering Model Predictive Wind Farm Controller

Jonas Kazda*, K. Merz, Nicolaos Antonio Cutululis, John Olav Tande

*Corresponding author for this work

Research output: Contribution to journalConference articleResearchpeer-review

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Cumulative O&M costs of offshore wind farms can amount to 38% of lifetime costs. In wind farms, upstream turbine wakes can result in up to 80% higher fatigue loads at downstream wind turbines. The present work therefore investigates to reduce wind turbine fatigue loads during the provision of grid balancing services using model predictive wind farm control. The main objective of the developed controller is to follow a total wind farm power reference and to reduce the damage equivalent tower bending moments of the turbines in the wind farm. The novelty in the control approach is the use of an engineering model-based, linear wind farm operation model and a newly developed wind farm-scale wind turbine fatigue load model. The model predictive controller is compared with commonly used wind farm control approaches in two wind farm case studies using a dynamic wind farm simulation tool. The simulation results suggest that the proposed model predictive controller can reduce the sum of the equivalent tower bending moments of wind turbines in a wind farm during provision of ancillary services. Simulations of an eight turbine array show up to 28% lower sum equivalent tower moments as compared to commonly used wind farm controllers. The observed reduction in turbine fatigue loads is attributed to the use of adequate wind farm-scale wind turbine fatigue load models.
Original languageEnglish
Article number012036
Book seriesJournal of Physics: Conference Series
Publication statusPublished - 2018
Event15th Deep Sea Offshore Wind R&D Conference - Trondheim, Norway
Duration: 17 Jan 201819 Jan 2018
Conference number: 15


Conference15th Deep Sea Offshore Wind R&D Conference

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