Massive simplification of the wind farm layout optimization problem

Abstract

Abstract. The wind farm layout optimization problem is notoriously difficult to solve because of the large number of design variables and extreme multimodality of the design space. Because of the multimodality of the space and the often discontinuous models used in wind farm modeling, the wind industry is heavily dependent on gradient-free techniques for wind farm layout optimization. Unfortunately, the computational expense required with these methods scales poorly with increasing numbers of variables. Thus, many companies and researchers have been limited in the size of wind farms they can optimize. To solve these issues, we present the boundary-grid parameterization. This parameterization uses only five variables to define the layout of a wind farm with any number of turbines. For a 100-turbine wind farm, we show that optimizing the five variables of the boundary-grid method produces wind farms that perform just as well as farms where the location of each turbine is optimized individually, which requires 200 design variables. Our presented method facilitates the study and both gradient-free and gradient-based optimization of large wind farms, something that has traditionally been less scalable with increasing numbers of design variables.

Control-oriented model for secondary effects of wake steering

“…In particular, u is determined by converting the ambient turbulence intensity into TKE by (Stull, 2012)…”

Realistic Optimization of Parallelogram-Shaped Offshore Wind Farms Considering Continuously Distributed Wind Resources

“…Despite this, little work has been done to limit solutions to OWFs with evenly distributed turbines [15][16][17][18], which is a solution that is increasingly being adopted by designers of real OWFs. Among them, parallelogram-shaped wind farms are a particular and frequent case.…”

“…Feng in [17] uses a parallelogram shape solution in a first stage of the WFOP to deduce the best orientation and shape of the OWF, before performing the complete layout optimization. Finally, Stanley in [18] uses five parameters to define the solutions bounded in a concession area with the benefit of reducing the computational expense. For other renewable sources, a continuous exploration of the position and orientation of a solar array is presented in [19].…”

Objective and algorithm considerations when optimizing the number and placement of turbines in a wind power plant

“…The balance of station (BOS) cost model (per kilowatt of installed wind power plant capacity) as a function of the total power plant capacity (Key et al, 2020). cost, which we assumed is USD 829 kW −1 of plant capacity (Wiser et al, 2020); O&M is the operation and maintenance cost, which we assumed is USD 44 kW −1 of plant capacity per year (Stehly and Beiter, 2020); and BOS is the balance of station cost. For this paper, we created a simple relation of BOS costs as a function of the installed wind power plant capacity from a set of higher fidelity BOS cost data (Key et al, 2020).…”