A reference open-source controller for fixed and floating offshore wind turbines

Abstract

Abstract. This paper describes the development of a new reference controller framework for fixed and floating offshore wind turbines that greatly facilitates controller tuning and represents standard industry practices. The reference wind turbine controllers that are most commonly cited in the literature have been developed to work with specific reference wind turbines. Although these controllers have provided standard control functionalities, they are often not easy to modify for use on other turbines, so it has been challenging for researchers to run representative, fully dynamic simulations of other wind turbine designs. The Reference Open-Source Controller (ROSCO) has been developed to provide a modular reference wind turbine controller that represents industry standards and performs comparably to or better than existing reference controllers. The formulation of the ROSCO controller logic and tuning processes is presented in this paper. Control capabilities such as tip speed ratio tracking generator torque control, minimum pitch saturation, wind speed estimation, and a smoothing algorithm at near-rated operation are included to provide modern controller features. A floating offshore wind turbine feedback module is also included to facilitate growing research in the floating offshore arena. All of the standard controller implementations and control modules are automatically tuned such that a non-controls engineer or automated optimization routine can easily improve the controller performance. This article provides the framework and theoretical basis for the ROSCO controller modules and generic tuning processes. Simulations of the National Renewable Energy Laboratory (NREL) 5 MW reference wind turbine and International Energy Agency 15 MW reference turbine on the University of Maine semisubmersible platform are analyzed to demonstrate the controller's performance in both fixed and floating configurations, respectively. The simulation results demonstrate ROSCO's peak shaving routine to reduce maximum rotor thrusts by over 10 % compared to the NREL 5 MW reference wind turbine controller on the land-based turbine and to reduce maximum platform pitch angles by nearly 30 % when using the platform feedback routine instead of a more traditional low-bandwidth controller.

Lidar-assisted model predictive control of wind turbine fatigue via online rainflow counting considering stress history

“…-Instead of the NREL baseline controller (Jonkman et al, 2009), the MPCs could be compared to a more modern reference controller, as for example the one of Abbas et al (2022).…”

Effectively using multifidelity optimization for wind turbine design

“…where k P and k I are the PI gains of the pitch controller, and k float = −9.49 s is the floating feedback gain. The PI gains are a function of the bandwidth, ω PC , and turbine parameters (Abbas et al, 2022). Generally, as the design variable ω PC increases, the PI gains also increase.…”

Challenges and Possible Solutions in Aeroelastic Modeling for the Distributed Wind Industry

“…Furthermore, there is a widespread sense that the current development of AM codes is focusing solely on utility-scale wind turbines and the renewed challenges and idiosyncrasies that giantscale rotors may bring forth. As an example, recent efforts [14] in the development of automatic control tuning for OpenFAST 1 , the most widely used AM code in the DWT industry, have neglected fixed-speed generators that are still being used by several SWTs. Analogously, the tail and passive-yaw aero-servo-elastic dynamics are no longer supported by OpenFAST.…”