Wind Farm Layout Optimization

Wind farm design has long been an application domain for evolutionary learning and optimization due to the complexity of the design space, and the discontinuities in the search space caused by the wake effects that make it hard to optimize analytically. Now, with a need to increase the renewable energy portfolio, existing wind farm layout approaches are being tested under a variety of scenarios. Newer models to evaluate layouts and newer constraints emerge, demanding more sophistication from the algorithms.

This is my master thesis: Surrogate modelling using machine learning for the wind farm layout optimisation problem.

Basically for the project we will be comparing: -- stochastic optimisation method X with no surrogate model vs -- stochastic optimisation method X with a surrogate model M