Offshore wind farm layout optimization using ensemble methods

Abstract

When planning wind farms it is important to optimize the layout to increase production and reduce costs. In this paper we minimize the levelized cost of energy (LCOE) for a floating wind farm using wind data in an area around Porto Santo in Portugal. We use ensemble based optimization (EnOpt), which is frequently applied in the geophysical community to find optimal controls of oil reservoirs. EnOpt is usually used for unconstrained optimization problems or for problems with simple constraints, for example upper and lower bounds on the optimization variables. Here we consider a layout problem with many constraints on the distances between turbines. To handle the constraints, we use an extension of EnOpt called EPF-EnOpt, in which the constrained problem is replaced by a series of unconstrained problems with increasing penalty terms. We compare the performance of this method with EnOpt with a fixed penalty term, and with a deterministic gradient method. All the tested methods reduce the LCOE, but EPF-EnOpt gives better results than both a single run of EnOpt with a fixed penalty term and the deterministic gradient method, and at a lower computational cost than using the gradient method. We also consider the problem of maximizing the annual energy production without taking into account any costs. EPF-EnOpt performs the best also for this problem.