Multi-Objective Performance Enhancement of Offshore Wind Turbines Through Planning Controller Parameter: A ‘Plan-Control’ Hierarchical Controller

Abstract

Large-scale offshore wind turbines (OWTs) are manufactured with pronounced flexible structures and operated in complex wind-wave coupled environment, thereby imposing high demands on the controller performance. Existing advanced control strategies have altered the architecture of industry-standard controller, hindering their application in industrial projects. This study aims to propose a novel ‘Plan-Control’ Hierarchical Controller (PCHC) for OWTs, with the inner ‘Control’ loop utilizing an industry-standard controller and the outer ‘Plan’ loop integrating a nonlinear model predictive control (NMPC)-based planner. For the inner loop, the controller provides reference signals of generator torque and blade pitch to actuators of OWTs, with controller parameters, optimal constant in torque control and proportional-integral (PI) gains in pitch control, being transferred from the planner. For the outer loop, an NMPC-based planner determines controller parameters by solving multi-objective optimization formulations with variable prediction horizons. Interestingly, NMPC-based planner does not operate as often as controller in PCHC, but compensates for the residual error, arising from the mismatch of state-space model in the multi-step prediction process, by Gaussian Process regression. A cost function is jointly formulated to suppress mechanical power and rotor speed fluctuations, reduce structural loads, and restrict actuators' actions, with weighting factors tuned online and robustly. Finally, the multi-objective performance enhancement of the PCHC in power and speed stability, and structural load mitigations is demonstrated utilizing aero-hydro-servo-elasto-soil simulations with actual wind-wave environmental conditions. The PCHC maintains the architecture of the industrial-standard controller, thus smoothing the way for its implementation in industrial projects of OWTs.