Wind Energy Science 

Wind farms are becoming larger and larger and they are shaping up as one of the main drivers towards full green energy transition. Because of their massive proliferation, more and more attention is nowadays focused on optimally design these power plants. We propose an optimization framework in order to contribute for further cost reductions, by simultaneoysly desining the wind turbines and cable layout. We show the capability of the framework to improve designs compared to the classic approach.

Hybrid solar and wind plant layout optimization is a difficult, complex problem. In this paper, we propose a parameterized approach to wind and solar hybrid power plant layout optimization that greatly reduces problem dimensionality while guaranteeing that the generated layouts have a desirable regular structure. We demonstrate that this layout method that generates high-performance, regular layouts which respect hard constraints (e.g. placement restrictions).

Using highly accurate simulations within a design cycle is prohibitively computationally expensive. We implement and present a multifidelity optimization method and showcase its efficacy using three different case studies. We examine aerodynamic blade design, turbine controls tuning, and a wind plant layout problem. In each case, the multifidelity method finds an optimal design that performs better than those obtained using simplified models, but with less cost than high-fidelity optimization.

In controls co-design, whose methods often rely on linearized models of the physics, the physical structure and controller are designed and optimized concurrently, so, it is important to understand how changes to the physical design affect the linearized system. This work summarizes efforts done to understand the impact of design parameter variations in the physical system (mass, stiffness, geometry, etc.) on the linearized system.