Individual Blade Pitch Control of Floating Offshore Wind Turbines for Load Mitigation and Power Regulation

Abstract

This paper proposes a new strategy for individual blade pitch control to regulate power production while simultaneously alleviating structural loads on spar-type floating offshore wind turbines. Individual blade pitch control types of algorithms for offshore wind turbines are sparse in the literature though there are expected benefits from experience on such types of controllers for onshore wind turbines. Wind turbine blade pitch actuators are primarily used to maintain rated power production at above-rated wind speeds and therefore, control algorithms are usually developed only to regulate power production. The scope of reducing structural loads using individual pitch control has been proved to be very promising over the last decade and numerous individual pitch control algorithms have been proposed by researchers. However, reduction in structural loads often results in a degradation in power production and regulation. Furthermore, improving power regulation often has a detrimental effect on the floating platform motion. In this paper, a new control strategy is proposed to achieve the two competing objectives. The proposed controller combines a low authority Linear Quadratic (LQ) controller with an integral action to reduce the 1P (once per revolution) aerodynamic loads while regulating power production using the same pitch actuators that are traditionally used only to optimize power production. The proposed controller is compared against the baseline controller used by state-of-the-art wind turbine simulator FAST using a high fidelity aeroelastic offshore wind turbine model. Numerical results show that the proposed controller offers improved performance in optimizing power production and reducing wind turbine and platform loads compared to the baseline controller over an envelope of windwave loading environment.Index Terms-Floating offshore wind turbines, individual blade pitch control, regulate power production, alleviate aerodynamic loads.

Recent Control Technologies for Floating Offshore Wind Energy System: A Review

“…As comparison with the previous works, the integration of the SFC and one more component (like integral block in [103] to compensate the accumulated error) can exhibit the best performance in which most remained problems are tackled.…”

“…Taking advantages of state feedback control (SFC), Sarkar et al [103] proposed the idea of integrating a linearquadratic (LQ) control with an integrated controller (LQ-I) to improve the generator output and spar-platform dynamics as shown in Fig. 30.…”

Use of Kane’s Method for Multi-Body Dynamic Modelling and Control of Spar-Type Floating Offshore Wind Turbines

“…FAST [25,26], an open-source wind turbine simulation tool developed by the National Renewable Energy Laboratory (NREL) in the United States, is one of the most popular tools used to simulate the dynamic behaviour of wind turbines. FAST models the wind turbine as a multi-body system using Kane's method [27] similar to the works in [28][29][30][31][32][33]. Similar to FAST, HAWC2 [34] was developed in the Technical University of Denmark, Risø to study the dynamics of horizontal axis wind turbines.…”

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

“…However, MLC learning on a cloud computer takes three days, which is not suitable for practical controller design involving iterative tuning of the cost and specifications. In contrast, Sarkar et al [13] proposed a simple IBP controller by combining a linear quadratic controller with an integral action to reduce the aerodynamic loads. Moreover, Bagherieh et al [14], Navalkar et al [15], Zhao and Nagamune [16], Zhang et al [17], and Yu et al [18] applied sophisticated techniques, such as input/output feedback linearization, H ∞ feedforward-feedback control, switching LPV control, sliding mode Although high-performance controllers are desirable, their implementation is difficult and impractical if they are too complicated and computationally expensive.…”