Applied Energy - Wind Farm Layout Optimization using Self-Informed Genetic Algorithm with Information Guided Exploitation

Rotor modelling using novel physics-based momentum models across operating regimes

Adaptive PSO After DOA-MUSIC

A Python Library for Global Adaptive Learning

A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, …

A TUDelft-compatible SOWFA with many exampleCases and the ZeroMQ supercontroller

Closed-loop wind farm controller (active power tracking / thrust balancing / load-limiting) object for SOWFA simulations

A MATLAB-based implementation of the zeroMQ closed-loop wind farm controller for SOWFA relying on the FLORISSE_M model

A collection of SOWFA pre- and post-processing tools for internal use at the Data-Driven Controls Research group at TU Delft

Postprocess of SOWFA results

Machine learning of wind farm turbulence features

自修复若干bug

Post procesing utility for NREL SOWFA and OpenFAST

Python and Matlab scripts for the postprocessing of SOWFA data

Code repository for "Modern Statistics: A Computer Based Approach with Python" and "Industrial Statistics: A Computer Based Approach with Python"

Python platform for parallel Surrogate-Based Optimization

Polynomial chaos expansions for wind energy

A Multi-objective Multi-fidelity acquisition function for Bayesian optimization based on EHVI method.

Tutorial on Gaussian Processes

Workflow for Energy with Integrated Servo-controls Toolset

Code to perform case studies for Jasa et al's 2022 Wind Energy Science paper on multifidelity optimization

Welcome to the User Friendly Python Kriging Toolbox!

Gaussian processes framework in python

GPSS 2019, Sheffield University

A highly efficient implementation of Gaussian Processes in PyTorch

A highly efficient and modular implementation of Gaussian Processes in PyTorch

An Intuitive Tutorial to Gaussian Processes Regression