Parameter-varying modeling and nonlinear model predictive control with disturbance prediction for spar-type floating offshore wind turbines

Author(s):  
Yuga Okada ◽  
Ken Haneda ◽  
Toshiki Chujo ◽  
Toshiyuki Ohtsuka
Author(s):  
Zhongyou Wu ◽  
Yaoyu Li

Abstract Floating offshore wind turbines (FOWTs) are subject to undesirable platform motion and significant increase in fatigue loads compared to their onshore counterparts. We have recently proposed using the Fishing Line Artificial Muscle (FLAM) actuators to realize active mooring line force control (AMLFC) for platform stabilization and thus load reduction, which features compact design and no need for turbine redesign. However, as for the thermally activated FLAM actuators, a major control challenge lies in the asymmetric dynamics for the heating and the cooling half cycle of operation. In this paper, for a tension-leg platform (TLP) based FOWT with FLAM actuator based AMLFC, a hybrid dynamic model is obtained with platform pitch and roll degrees of freedom included. Then a hybrid model predictive control (HMPC) strategy is proposed for platform motion stabilization, with preview information on incoming wind and wave. A move blocking scheme is used to achieve reasonable computational efficiency. FAST based simulation study is performed using the NREL 5 MW wind turbine model. Under different combinations of wind speed, wave height and wind directions, simulation results show that the proposed control strategy can significantly reduce the platform roll and tower-base side-to-side bending moment, with mild level of actuator power consumption.


2021 ◽  
Author(s):  
Athul K. Sundarrajan ◽  
Yong Hoon Lee ◽  
James T. Allison ◽  
Daniel R. Herber

Abstract This paper discusses a framework to design elements of the plant and control systems for floating offshore wind turbines (FOWTs) in an integrated manner using linear parameter-varying models. Multiple linearized models derived from high-fidelity software are used to model the system in different operating regions characterized by the incoming wind speed. The combined model is then used to generate open-loop optimal control trajectories as part of a nested control co-design strategy that explores the system’s stability and power production in the context of crucial plant and control design decisions. A cost model is developed for the FOWT system, and the effect of plant decisions and subsequent power and stability response of the FOWT is quantified in terms of the levelized cost of energy (LCOE) for that system. The results show that the stability constraints and the plant design decisions affect the turbine’s power and, subsequently, LCOE of the system. The results indicate that a lighter plant in terms of mass can produce the same power for a lower LCOE while still satisfying the constraints.


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