Engineering topics

Henry, Aoife

Publications and source records attributed to Henry, Aoife.

3 records

DOE OSTI2024

A Tutorial on the Control of Floating Offshore Wind Turbines: Stability Challenges and Opportunities for Power Capture

Climate change is a serious threat facing humanity. The United States (U.S.) and many other countries are increasing the amount of electrical power generated from renewable energy sources in an effort to combat climate change and ensure energy independence. The U.S. has set goals to achieve a 100% decarbonized electric grid by 2035 and a net-zero emissions economy by no later than 2050. Renewable energy currently accounts for about 20% of the U.S. power grid. According to the U.S. Department of Energy and the National Renewable Energy Laboratory (NREL), in the U.S. in 2021, wind and solar photovoltaic generation supplied 9.1% and 4% of total electricity generation, respectively, and the latest publicly available data show that hydropower represented 6.6% of all electricity generated in the U.S. in 2019. As wind farms have been built in many of the best wind resource areas on land, the U.S. and many other countries are turning to offshore wind for further growth of wind power capacity. Further, the U.S. has committed to deploy 30 GW of offshore wind by 2030, a significant increase from the 0.04 GW of installed offshore wind in the country as of the end of 2023. Many other countries have also established ambitious goals or plans to increase the amount of installed offshore wind power.

17 WIND ENERGY↗

DOE OSTI2024

Online Learning of Effective Turbine Wind Speed in Wind Farms

To develop better wind farm controllers that can meet more complex objectives, methods of modeling the wind turbine wakes at low computational expense are needed. Gaussian process (GP) regression offers a computationally inexpensive framework for learning complex functions from noisy measurements with very few datapoints. In this work, an online learning approach is presented to learn the rotor-averaged wind velocity at downstream wind turbines with GPs, using the available datastream of wind field measurements and wind turbine control set-points. This framework can readily be integrated into model-based controls methods because the model a) is updated online at low computational expense, b) assumes a mathematically favorable Gaussian form, and c) explicitly quantifies the stochastic nature of the wake field so that the trade-off between exploration and exploitation, and the uncertainty in the prediction, can be utilized. We show that a GP-learned model can match true values with errors within 0.5% on average, with as few as 5 training data points.

Gaussian process↗

DOE OSTI2023

Sink or Swim: A Tutorial on the Control of Floating Wind Turbines: Preprint

Within the rapidly growing wind energy sector, floating offshore wind turbines are expected to be the fastest growing portion. This is largely driven by the immense offshore wind resources that are mostly over deep water, where fixed-bottom concepts become cost prohibitive. However, compared to fixed-bottom wind turbines, floating wind turbines are more dynamic and exhibit potential instabilities, which requires advanced control technologies to ensure a safe and efficient operation. Beyond their existing objectives of maximizing power production while minimizing structural loads, floating wind turbine controllers must also avoid large platform oscillations and accommodate wave disturbances. This paper provides an overview of the challenges and opportunities in the control of floating offshore wind energy systems.

control↗