Generator Torque Control Research Articles

Optimized design of multiple tuned mass dampers for vibration control of offshore wind turbines

Offshore wind turbines (OWTs) are dynamically sensitive structures to low-frequency wind-wave loadings due to their low damping and high flexibility. This makes them vulnerable to unwanted vibrations in ocean environments. Therefore, there is a need to implement innovative vibration control devices to suppress undesired vibration and ensure their structural safety. A tuned mass damper (TMD) has been a promising solution to control excessive vibrations recently in OWTs due to higher efficiency and low installation cost. However, TMD performance in vibration mitigation of OWTs when placed at a nacelle is still challenging to investigate because the generator torque and pitch control may affect the dynamics of the overall system. In this paper, an optimal multiple TMD system is designed by placing TMDs at optimal locations along the tower, which are defined using the maximum amplitude of the displacements for the first three natural frequencies of the tower. In addition, extensive simulations are carried out with integrated OWT-TMD systems to find the optimal mass ratio values and quantity of the TMDs. The TMD system is also tuned for several scenarios, including operating, parked, and idling conditions under the combined wind-wave loadings. A numerical model of the 5 MW NREL OWT developed in OpenFAST is considered as the baseline in this study. The results show a root mean square (RMS) response reduction of 10.2% and 42% in fore-aft (FA) and side-side (SS) tower displacement with optimally designed multiple TMDs. Moreover, improved mitigation effects on tower base moment of RMS 43.6% and 20.8% are observed in orthogonal directions, respectively. The findings of this paper may have the potential for designing passive TMD systems for vibration reductions in OWT.

Catenary Mooring Length Control for Motion Mitigation of Semi-Submersible Floating Wind Turbines

Besides improving the generator torque and blade pitch controller, incorporating additional control actuations, such as a vibration absorber and active ballast, into the floating offshore wind turbine (FOWT) system is also promising for the motion mitigation of FOWTs. This work aims to study the catenary mooring length re-configuration effect on the dynamic behaviours of semi-submersible FOWTs. The mooring length re-configuration mentioned here is achieved by altering the mooring length with winches mounted on the floating platform, which is in a period of minutes to hours, so that the mooring tensions could be adjusted to reduce the aerodynamic load induced platform mean pitch. Control designs for both single mooring line and multiple mooring lines have been described and studied comparatively. In order to assess the motion mitigation performance of the proposed mooring line length re-configuration methods, fully coupled numerical simulations under different environmental cases have been conducted. Results indicate that the catenary mooring length re-configuration is able to reduce the platform pitch motion by up to 15.8% under rated condition, while careful attention must be paid to the scenarios where the catenary moorings become taut, which may lead to large load variations.

Increased power capture efficiency of large-scale wind turbines using model-free coordinated pitch, yaw, and torque control with wind direction estimation in diverse environmental conditions

Offshore large-scale wind turbine systems (LSWTS) face challenges in pitch and yaw management mainly due to unreliable wind direction measurements, delayed responses, and redundant yaw movements, reducing their optimal efficiency under various offshore renewable environmental conditions. To address this problem and increase power capture, this study introduces a model-free coordinated super-twisting pitch, yaw, and generator torque control for LSWTS under various wind speed and direction conditions. To achieve this, a dynamic model of the weather vane is first designed to accurately measure the wind directions under fluctuating wind speed and environmental conditions. At the same time, the onshore/offshore LSWTS weather vane model is formulated to operate under optimal conditions considering air density, temperature, humidity, and external disturbances. Then, super-twisting control based on an enhanced adaptive barrier function is proposed for the coordinated control operation of the pitch, yaw, and generator torque actuators for stable maximum power extraction of the offshore LSWTS. Finally, simulation and comparative studies are presented to signify the increased power capture ability of the proposed scheme for both a 4.8 MW benchmark and a 20 MW PMVG-based offshore LSWTS to verify robustness against wind gusts, direction changes, and model uncertainties.

Experimental investigation of advanced turbine control strategies and load-mitigation measures with a model-scale floating offshore wind turbine system

To advance the control co-design of offshore wind energy systems, the authors perform basin-scale experiments with a fully instrumented and actuated floating offshore wind turbine model. The model consists of a 1:70 scale performance-matched model of the International Energy Agency Wind Technology Collaboration Programme 15-MW reference turbine atop the VolturnUS-S semisubmersible platform. The Reference OpenSource Controller provides real-time blade pitch and generator torque control. We aim to develop an open data set for the validation of numerical models in predicting the influence of turbine control and load-mitigation measures. For this purpose, we measure the effects of advanced turbine control features, including peak shaving and floating feedback as well as hull-based control using tuned mass dampers on the system. Overall, the results demonstrate measurable and consistent influences from the control and load-mitigation measures, thus confirming the usefulness as a validation data set. Peak shaving attenuates the response to wind turbulence at near-rated wind speed. Floating feedback reduces the load and platform pitch motion associated with the negative damping induced by blade pitch control. The tuned mass dampers also attenuate the system response near the targeted frequencies under suitable conditions. We also identify detrimental side effects of each load-mitigation measure.

Power maximization and regulation of the super-large wind turbine system using generalized predictive approach-based torque and pitch control

Power maximization, regulation, and structural load reduction become critical when the wind turbine capacity reaches multi-megawatt levels. Thus a well-designed control system allows for better energy extraction and load alleviation of the large-scale wind energy conversion system (WECS). To do this, a 20MW super-large WECS is first modeled using a permanent magnet synchronous generator (PMSG). Next, the optimal generator torque and rotor pitch angle control are designed based on the generalized predictive control approach. Then, the designed controller predicts the best future control effort by identifying the model using the reaction curve method. Further, the proposed controllers are implemented on the designed super-large PMSG-based WECS to achieve the control objectives from the partial and full-load wind regions. Finally, the suggested controllers are compared with the existing control methods to check their effectiveness using step and unexpectedly varying wind speeds.

Robust Reinforcement Learning-Based Multiple Inputs and Multiple Outputs Controller for Wind Turbines

The control of variable-speed wind turbines that generate electricity from the kinetic energy of the wind involves subsystems that need to be controlled simultaneously, namely, the blade pitch angle controllers and the generator torque controllers. The presented study solves the control problem with multiple inputs and multiple outputs (MIMO), using the method of reinforcement learning–based Trust Region Policy Optimization, through which the control parameters of both subsystems are simultaneously optimized. In this case, the robust control problem is transformed into a constrained optimal control problem with an appropriate choice of value functions for the nominal system. The study aims to synthesize a robust controller, with the aim of maximizing the generated energy (power) and minimizing unwanted forces (thrust). The innovative control architecture uses an extended input space, which allows fine-tuning of parameters for each operating state. Test calculations carried out in simulation experiments using models of the 5 MW NREL wind turbine and the 4 MW Enercon E-126 EP3 wind turbine are presented to illustrate the performance and practicality of the proposed approach.

An adaptive operational strategy for enhanced provision of frequency containment reserve by Wind Turbines: Data-driven based power reserve adjustment

Due to the growing penetration of renewables, Wind Turbines (WT) are becoming increasingly crucial for grid balancing services, such as Frequency Containment Reserve (FCR). This study proposes an adaptive operational strategy that optimally accommodates the power reserve and controls the active power based on grid frequency uncertainties and stochastic wind variations. The proposed approach includes an end-to-end solution, considering fixed and percentage reserve methods, from estimating an appropriate reserve margin to the real-time computation of generator torque and pitch control setpoints in response to grid frequency variations. A real-time look-up table is incorporated to actively adjust the reserve and adapt the deloading rotor speed-power curve based on a short-term estimation of the grid frequency using a deep-learning technique. Applying the proposed strategy improves WTs’ FCR contribution by at least 3.3 times reserve in MW. Moreover, adaptive fuzzy-PI pitch-torque controllers are suggested to enhance the WT dynamic response and ensure smooth provision of FCR. Simulation results of a 5 MW-NREL offshore model show the improvement of the fuzzy-PI in power reference tracking, rotor speed regulation, and average studied mechanical load parameters in the range of 2.14–11.69%, 11.1%, and 8.81%, respectively, for an average of 250 kW reserve, confirming an overall improvement.

The influence of tuned mass dampers on vibration control of monopile offshore wind turbines under wind-wave loadings

The passive tunned mass dampers (TMDs) can effectively mitigate vibrations of offshore wind turbines (OWTs). However, most of the aforementioned literatures only focus on the vibration reduction effect of a TMD without considering vibration mechanism of the OWT with and without the TMD, which is affected by the frequency characteristics of wind-wave loadings, especially the low frequency characteristics of wind loads. Moreover, the baseline control of OWTs including the pitch control and the generator torque control can affect the dynamical responses of the OWT and thus the vibration reduction performance of a TMD. In this paper, an optimal dual TMD is placed at the nacelle for mitigating the vibration of the OWT. The influence of the TMD on dynamical responses of the OWT is fully investigated under the baseline control and the various wind-wave loadings. The research shows that the TMD has an excellent vibration reduction effect when the OWT is parked (at high wind velocities). When the OWT is parked and the wind velocity at the hub is at 25 m/s, the vibration reduction performance of the TMD is the best, and the maximum values of the tower top displacement and acceleration, and the top and the bottom tower moments are reduced by 25.41%, 24.76%, 7.09% and 16.78%, respectively. Moreover, the optimal designs for the TMD are further conducted under the baseline control and the different wind-wave loadings. The research results show that the vibration reduction performance of the TMD is not significantly enhanced when the OWT can work normally, but it is enhanced when the OWT is parked. This work can provide technical support for optimal design of the TMD under the wind-wave environments.

Experimental study of floating wind turbine control on a TetraSub floater with tower velocity feedback gain

We present an experimental study of floating wind turbine control with inclusion of tower motion feedback. The study is conducted for a 1:60 scaled-model of the DTU 10MW reference wind turbine on a design variant of the TetraSub floater. A review of control methods for floating wind turbines is provided, covering both de-tune and tower motion feedback methods. We next detail the implementation in the experimental setup that includes real-time integration and low-pass filtering of the measured tower-top acceleration. We demonstrate how the tower feedback loop is able to stabilize an otherwise unstable land-based controller. The results further show that the stability is maintained for increasing values of the feedback gain until a certain limit. For the chosen control parameters and the lab-generated wind field, which had limited low-frequency energy, we observe that the variations in rotor speed, blade pitch and platform motion are generally larger for the tower loop controller. This finding is not generalizable due to the special inflow conditions and because controller optimization is not performed. For the tower loop controller, a substantial response at the floater roll frequency is identified. This is caused by the influence of blade pitch on the aerodynamic torque in combination with the constant generator torque. Mitigation through generator torque control is proposed.

Efficiency enhancement strategy implementation in hybrid electric vehicles using sliding mode control

Introduction. Hybrid electric vehicles are offering the most economically viable choices in today's automotive industry, providing best solutions for a very high fuel economy and low rate of emissions. The rapid progress and development of this industry has prompted progress of human beings from primitive level to a very high industrial society where mobility used to be a fundamental need. However, the use of large number of automobiles is causing serious damage to our environment and human life. At present most of the vehicles are relying on burning of hydrocarbons in order to achieve power of propulsion to drive wheels. Therefore, there is a need to employ clean and efficient vehicles like hybrid electric vehicles. Unfortunately, earlier control strategies of series hybrid electric vehicle fail to include load disturbances during the vehicle operation and some of the variations of the nonlinear parameters (e.g. stator’s leakage inductance, resistance of winding etc.). The novelty of the proposed work is based on designing and implementing two robust sliding mode controllers (SMCs) on series hybrid electric vehicle to improve efficiency in terms of both speed and torque respectively. The basic idea is to let the engine operate only when necessary keeping in view the state of charge of battery. Purpose. In proposed scheme, both performance of engine and generator is being controlled, one sliding mode controllers is controlling engine speed and the other one is controlling generator torque, and results are then compared using 1-SMC and 2-SMC’s. Method. The series hybrid electric vehicle powertrain considered in this work consists of a battery bank and an engine-generator set which is referred to as the auxiliary power unit, traction motor, and power electronic circuits to drive the generator and traction motor. The general strategy is based on the operation of the engine in its optimal efficiency region by considering the battery state of charge. Results .Mathematical models of engine and generator were taken into consideration in order to design sliding mode controllers both for engine speed and generator torque control. Vehicle was being tested on standard cycle. Results proved that, instead of using only one controller for engine speed, much better results are achieved by simultaneously using two sliding mode controllers, one controlling engine speed and other controlling generator torque.

Adaptive Active Generator Torque Controller Design Using Multi-Objective Optimization for Tower Lateral Load Reduction in Monopile Offshore Wind Turbines

Adaptive Active Generator Torque Controller Design Using Multi-Objective Optimization for Tower Lateral Load Reduction in Monopile Offshore Wind Turbines

Online data‐driven control of variable speed wind turbines using the simultaneous perturbation stochastic approximation approach

AbstractThis article presents a data‐driven control algorithm for a variable‐speed wind turbine in the partial load region. The controller is designed and optimized online to capture maximum energy from the wind. The online optimization is based on the simultaneous perturbation stochastic approximation method (SPSA) that is data‐driven, has a low computational load, and converges rapidly. In the control structure, the generator torque control is activated, and the aerodynamical models and the wind speed value are not required. A suitable cost function is defined, and a time window optimization problem is solved via the SPSA algorithm. The efficiency of the proposed method is evaluated on a 4.8 MW wind turbine benchmark.

Quantifying the effects of high-speed shaft braking on the substructural dynamics of monopile offshore wind turbines

ABSTRACT This paper investigates the effects of high-speed shaft braking (HSB) on the substructural dynamics of monopile-type offshore wind turbines. By incorporating blade aerodynamics, generator-torque control, monopile structural dynamics, and the HSB control, the main dynamics of the offshore wind turbine are analyzed. Dynamic simulations of a monopile 5 MW offshore wind turbine by utilizing a high-fidelity aeroelastic offshore wind turbine model are used to provide detailed results. Orthogonal experiments are also conducted using the Taguchi method for different levels of the HSB control. The results reveal that the roll/sway displacements of the monopile and the side-to-side shear force of the tower-top/yaw bearing experience amplitude vibrations (around 20% of the rated value) due to the HSB control. The HSB control not only changes the instantaneous dynamic loads (more than 25% of the rated values) on the blades but also can interact with the normal wind turbine control. Therefore, the HSB control should be carefully designed and applied when the offshore wind turbine is in normal operation since incorrect HSB control may excite large oscillations.

Study on the Influence of Low-Level Jet on the Aerodynamic Characteristics of Horizontal Axis Wind Turbine Rotor Based on the Aerodynamics–Controller Interaction Method

Accurate prediction of the aerodynamic characteristics of wind rotors subjected to various wind profiles is of considerable importance in the aerodynamics and structural design of wind turbines. As a very complex atmospheric phenomenon, the impact of a low-level jet (LLJ) on the aerodynamic characteristics of wind rotors is becoming more and more significant with the increase in wind turbine height. Additionally, during calculating the aerodynamic characteristics of the wind rotor, the known wind speed, rotor speed, and blade-pitch angle are generally required. However, when the wind profile is in the LLJ condition, it is difficult to determine the blade-pitch angle and rotor speed. Therefore, in this paper, the blade-element-momentum (BEM) method is exploited by considering the coupling with the generator-torque controller and blade-pitch controller. In order to solve the problem of the unknown rotor speed and blade-pitch angle under the LLJ condition, a C++ code is developed. Then, the influence of the LLJ on the aerodynamic characteristics of the wind rotor is exclusively examined. The research results show that the calculation method can precisely evaluate the rotor speed, blade-pitch angle, and aerodynamic characteristics of the wind rotor. The influence of the LLJ on the aerodynamic loads of the wind rotor is greater than that of the wind shear. When the LLJ is placed inside the rotor swept area, the aerodynamic loads of the blade exhibit two local maximums and local minimums with the variation of the azimuth angle in a rotation period. The closer the LLJ height is to the hub height, the greater the average aerodynamic loads of the wind rotor are, and the smaller the amplitude of aerodynamic loads of the blade is relative to the average value. When the LLJ height is positioned outside the rotor swept area, the change law of the aerodynamic loads of the blade would be similar to that of the wind subjected to a very strong wind shear inflow. This study provides a crucial reference for a more rational assessment of the aerodynamic characteristics of wind turbines under the action of complex wind profiles, as well as revealing the influence of the LLJ on the aerodynamic characteristics of wind turbines.

Actor-critic continuous state reinforcement learning for wind-turbine control robust optimization

The control of Variable-Speed Wind-Turbines (VSWT) extracting electrical power from the wind kinetic energy are composed of subsystems that need to be controlled jointly, namely the blade pitch and the generator torque controllers. Previous state of the art approaches decompose the joint control problem into independent control subproblems, each with its own control subgoal, carrying out separately the design and tuning of a parameterized controller for each subproblem. Such approaches neglect interactions among subsystems which can introduce significant effects. This paper applies Actor-Critic Reinforcement Learning (ACRL) for the joint control problem as a whole, carrying out the simultaneous control parameter optimization of both subsystems without neglecting their interactions, aiming for a globally optimal control of the whole system. The innovative control architecture uses an augmented input space so that the parameters can be fine-tuned for each working condition. Validation results conducted on simulation experiments using the state-of-the-art OpenFAST simulator show a significant efficiency improvement relative to the best state of the art controllers used as benchmarks, up to a 22% improvement in the average power error performance after ACRL training.

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

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.

Control Considerations for Very Large Floating Wind Turbines

Increasingly large floating wind turbines (FWTs) are being introduced to access the offshore wind resource over deep water at lower cost. In connection with designing a 25 MW semi-submersible wind turbine, we examine the scaling trends associated with the dynamic performance of the generator torque and blade pitch controllers and highlight the challenges that may be encountered for such devices. The increased rotor inertia, reduced blade pitch rates, longer platform pitch and surge natural periods, and flexible modes of the tower, platform, and rotor all affect the ability of the controller to track the desired rotor speed. The effects of control design and tuning choices on the FWT behavior in representative wind and wave conditions are shown.

Optimization and realization on the coordination control strategy for auxiliary power unit of range-extended electric vehicle

The auxiliary power unit (APU) is a major power source of range-extended electric vehicle (R-EEV). Excellent coordination control strategy of APU has a great significance impact on improving the overall electrical control system performance of R-EEV. A coordination control strategy based on parameters adapt fuzzy-PID is proposed to ensure the dynamic and static response characteristics of the coordination control system. Firstly, the APU high precision simulation control model is built in GT-Power and Matlab-Simulink. Three coordination control strategies based on traditional PID control method are designed, namely, engine speed control model (ESCM), generator torque control model (GTCM), and APU speed-torque control model (AS-TCM). The three coordination control strategies are simulated on working conditions, which include start-up working condition, power raised working condition, and power reduced working condition. Combined with the PID control principle, the control performance and inherent limitations of three traditional PID control strategies (TPCS) are analyzed and compared. Then, according to the above simulation results of analysis and comparation, the parameters adapt fuzzy-PID control strategy (PAF-PCS) is designed and simulated. The results show that three control parameters ( kp, ki, kd) are changed in real time to ensure the flexibility and adaptability of the control system and improve the stability and robustness of control system. Finally, the results of bench test show that power responds quickly and no oscillation and fixed-point power generation works smoothly, which are basically consistent with the simulation results. Therefore, the PAF-PCS proposed in this paper has good feasibility and effectiveness.

Exploring the application of reinforcement learning to wind farm control

Optimal control of wind farms to maximize power is a challenging task since the wake interaction between the turbines is a highly nonlinear phenomenon. In recent years the field of Reinforcement Learning has made great contributions to nonlinear control problems and has been successfully applied to control and optimization in 2D laminar flows. In this work, Reinforcement Learning is applied to wind farm control for the first time to the authors’ best knowledge. To demonstrate the optimization abilities of the newly developed framework, parameters of an already existing control strategy, the helix approach, are tuned to optimize the total power production of a small wind farm. This also includes an extension of the helix approach to multiple turbines. Furthermore, it is attempted to develop novel control strategies based on the control of the generator torque. The results are analysed and difficulties in the setup in regards to Reinforcement Learning are discussed. The tuned helix approach yields a total power increase of 6.8% on average for the investigated case, while the generator torque controller does not yield an increase in total power. Finally, an alternative setup is proposed to improve the design of the problem.

Numerical design of a wind observer and feedforward control of wind turbines

Wind speed is an unknown variable that is very difficult to measure relying on instruments that are commonly present on-board the wind turbine nacelle. The alternative to this approach is to extract a wind speed estimate from other measured quantities. The so-obtained wind speed could then be integrated in common power control algorithms as an additional scheduling variable or it can be exploited to realize feedforward actions to enhance the machine power capture and fatigue life. This work deals with the design of an observer to estimate the spatially-averaged wind speed on the rotor swept area. A linear model of the wind turbine drivetrain based on steady aerodynamics is introduced and used as the base for the wind speed observer. The observer is implemented on the DTU 10MW RWT and a feedforward action based on the estimated effective wind speed is added to the standard feedback controller. FAST co-simulations are performed to evaluate the performances of the implemented system in several wind turbine operating conditions. Its responsiveness is shown to be greater when operating in presence of above-rated winds due to the higher rotor aerodynamic sensitivity. The observer response is instead slower in below-rated winds, where its capability of predicting high-frequency wind gusts is limited by the combination of rotor inertia and generator torque control.