Offshore wind farm wake modelling using deep feed forward neural networks for active yaw control and layout optimisation
S Anagnostopoulos, MD Piggott - Journal of Physics: Conference …, 2022 - iopscience.iop.org
Offshore wind farm modelling has been an area of rapidly increasing interest over the last
two decades, with numerous analytical as well as computational-based approaches …
two decades, with numerous analytical as well as computational-based approaches …
A data-driven machine learning approach for yaw control applications of wind farms
This study proposes a cost-effective machine-learning based model for predicting velocity
and turbulence kinetic energy fields in the wake of wind turbines for yaw control …
and turbulence kinetic energy fields in the wake of wind turbines for yaw control …
[HTML][HTML] Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models
SJ Anagnostopoulos, J Bauer, MCA Clare… - Renewable Energy, 2023 - Elsevier
Wind farm modelling is an area of rapidly increasing interest with numerous analytical and
computational-based approaches developed to extend the margins of wind farm efficiency …
computational-based approaches developed to extend the margins of wind farm efficiency …
[HTML][HTML] Predicting wind farm wake losses with deep convolutional hierarchical encoder–decoder neural networks
DA Romero, S Hasanpoor, EGA Antonini… - APL Machine …, 2024 - pubs.aip.org
Wind turbine wakes are the most significant factor affecting wind farm performance,
decreasing energy production and increasing fatigue loads in downstream turbines. Wind …
decreasing energy production and increasing fatigue loads in downstream turbines. Wind …
Jensen-ANN: A Machine Learning adaptation of Jensen Wake Model
Wake models play an important role in wind farm layout optimization and control studies and
it is, therefore, important to model wake effects in accurate and efficient ways. The power …
it is, therefore, important to model wake effects in accurate and efficient ways. The power …
Towards multi-fidelity deep learning of wind turbine wakes
Engineering wake models that accurately predict wake in a computationally efficient manner
are very important for tasks such as layout optimization and control of wind farms. In this …
are very important for tasks such as layout optimization and control of wind farms. In this …
A data-driven layout optimization framework of large-scale wind farms based on machine learning
This paper presents a data-driven wind farm layout optimization framework that uses a
machine learning wake model that considers physical control stages. The machine learning …
machine learning wake model that considers physical control stages. The machine learning …
Validation of an analytical optimization framework for wind farm wake steering applications
View Video Presentation: https://doi. org/10.2514/6.2022-1920. vid Large-Eddy Simulations
have been used extensively to develop and test wake steering wind farm control strategies …
have been used extensively to develop and test wake steering wind farm control strategies …
Machine learning-based approach to wind turbine wake prediction under yawed conditions
As wind energy continues to be a crucial part of sustainable power generation, the need for
precise and efficient modeling of wind turbines, especially under yawed conditions …
precise and efficient modeling of wind turbines, especially under yawed conditions …
Data-driven optimisation of wind farm layout and wake steering with large-eddy simulations
Maximising the power production of large wind farms is key to the transition towards net
zero. The overarching goal of this paper is to propose a computational method to maximise …
zero. The overarching goal of this paper is to propose a computational method to maximise …