Multi-Objective Control of Utility-scale Variable-Speed Wind Turbines for Drive-train Load Reduction in Low Wind Speed Regime

Wind turbines are important in capturing power from varying wind speed. For maximum energy capture in low wind speed regime, a standard generator torque controller is normally used to track the incoming wind speed in order to maximize power production. In low wind speed regime, the rotor blade pitch angles are held constant at an optimum value that ensures maximum lift. This control strategy has some limitations, especially in large wind turbines due to induced structural loads. Though aerodynamic loads are not high in the low wind speed regime, maximum power point tracking can cause high torque variations in the drive-train which can lead to early fatigue failure of the wind turbine. Most studies done in this regime focuses on maximum energy capture, without considering structural loads, which are critical in large wind turbines that have large inertial loads. In this paper, a multi-objective control strategy that ensures utility scale wind turbines capture maximum power in low wind speed regime, while minimizing drive-train vibrations is proposed. An optimal generator torque controller is designed to achieve maximum energy capture, while an independent blade pitch controller is designed to reduce drivetrain vibrational loads in the wind turbine. The two controllers are designed in MATLAB and simulated in Fatigue, Aerodynamics, Structural and Turbulence (FAST) software. TurbSim full-field turbulent wind simulator is used to generate varying wind profiles for simulation purposes. A fictitious 1.5 MW WindPACT wind turbine model is used to evaluate the proposed control strategy. When evaluated against a baseline controller for the low wind speed regime under stochastic wind excitation, the multi-objective control strategy improves drivetrain torsional damping by 2.69%, with standard deviation decreasing by 3.28%, without compromising on power capture. Index Term-Horizontal axis wind turbine (HAWT), linear quadratic gaussian (LQG), maximum power point tracking (MPPT), variable-speed wind turbine (VSWT), independent pitch control (IPC), optimal tracking rotor (OTR). INTRODUCTION WIND turbines are used to capture power from varying wind speed. Being a renewable source of energy, it reduces reliance on fossil fuel-based energy sources that are harmful to the environment. With time, as the world population grows and economies expand, there is increasingly high demand for energy from renewable sources. Wind is most competitive and preferred renewable energy source due to its minimal negative impact on the environment [1]. This has led to rapid growth in demand for wind energy generation, necessitating wind turbine manufacturers to produce larger wind turbines. There are increased structural loads with increase in wind turbine size, which is attributed to gravitational loads, inertial, centrifugal, and gyroscopic loads which occur during operation. These structural loads can drastically reduce the lifetime of a wind turbine. Therefore, there is need to design control strategies to reduce structural loads in wind turbines. In a variable speed wind turbine, power production occurs in the low wind speed regime (below the rated wind speed region), and the high wind speed regime (above the rated wind speed region). Most wind turbines operate in the low wind speed regime, whose main objective is to maximize the amount of power extracted by the wind turbine. Therefore, the rotational speed of the generator should be adjusted in real time in relation to the incoming wind speed [2]. The main objective in the high wind speed regime is to regulate the rotor speed and power so as to avoid exceeding mechanical and electrical limits of the wind turbine. To lower the cost of energy production, there is a growing need for energy efficiency for wind turbines operating in the low wind speed regime. This is attained by operating the wind turbine at optimum power efficiency as much as possible. Proper design of controllers for Wind Energy Conversion Systems (WECS), ensures efficient energy generation, good power quality, and reduced mechanical and aerodynamic loads resulting in increased turbine life [3]. Utility-scale wind turbines normally have Horizontal Axis Wind Turbine (HAWT) configuration due to its advantages over Vertical Axis Wind Turbine (VAWT) configuration. One advantage is being able to mount the entire rotor on top of a tall tower in order to take advantage of higher wind speeds. Variable pitch and speed operation, improved structural performance, and elimination of guy wires used to add structural stability are the other advantages of HAWTs [4]. Wind turbines rotor blades can be fixed pitch or pitch-able. Though fixed pitch blades are cheap to manufacture, variablepitch blades are preferred for large wind turbines since it reduces induction of structural loads during operation. Most modern utility scale wind turbines are designed to have variable pitch and speed in order to capture as much energy as possible by the rotor speed tracking the incoming wind speed [5]. In contrast to constant speed wind turbines, Variable International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:19 No:04 19 191204-5858-IJMME-IJENS © August 2019 IJENS I J E N S Speed Wind Turbines (VSWTs) track wind speed variations in order to maximize aerodynamic efficiency in the low wind speed regime. From control perspective, this requires knowledge of complex aerodynamic properties to ensure maximum energy is captured [6]. Given that variable speed wind turbines are able to change their rotational speed to follow instantaneous changes in wind speed, they are able to maintain an optimal Tip Speed Ratio (TSR) at all times [7]. Therefore, VSWTs are able to operate at maximum aerodynamic efficiency for more fraction of time than fixed speed wind turbines, hence are cost-effective in utility scale applications [8]. Modern utility scale wind turbines are installed with individual blade pitch actuation mechanisms, where control of pitch angle for each blade is done independently to ensure symmetrical loading of the rotor disc. Several sensors are also installed in the blades, tower and nacelle of these wind turbines. According to [9], accelerometers are usually installed in the nacelle to measure tower fore-aft and side-side motion, torque transducers are installed in the Low Speed Shaft (LSS) and High Speed Shaft (HSS), absolute position encoders give information on pitch, yaw, LSS, and HSS positions, and strain gauges are installed in blade roots and towers. In low wind speed regime, Maximum Power Point Tracking (MPPT) can induce mechanical stress on the drive-train system, especially in utility-scale wind turbines. Drive-train vibrations can lead to excitation of poorly damped modes in the turbine which can reduce the service life of a wind turbine [10]. According to a survey done in [11], the main causes of downtime in wind turbines are: Power module, drive-train module, and rotor module. The drivetrain carries some the most critical and expensive components of the wind turbine. Therefore structural load reduction in the drive-train is critical. In [12], a Sliding Mode-Extremum Seeking Controller (SMESC) was proposed. In the study, the control strategy was implemented using PI-based controllers hence, did not account for wind disturbances. Therefore, the MPPT controller performance was degraded under stochastic wind profile. A multi-variable extremum seeking control for maximizing energy capture in VSWTs was implemented in [13], where the optimal control torque and pitch angle are searched by ESC based on the measurement of the rotor power. As opposed to [12] that used only simulated wind profiles, [13] utilized both simulated and field-recorded winds for simulations carried out in FAST software. The developed multi-variable ESC improved turbine operation in fluctuating wind and with actuator saturation, and given addition of anti-windup and input resetting to deal with the integral wind-up, transient performance was improved under sudden changes in wind profile. However, independent pitch control was not implemented. In the study in [3], a multi-variable controller based on Multiple Model Predictive Control (MMPC) technique for the control of variable speed, variable pitch wind turbines operating low and high wind speed regimes. However, the pitch angle was held constant in the low wind speed regime and only generator torque was controlled. The study in [14] proposed a multivariable control strategy for VSWTs operating in both low and high wind speed regimes. The developed torque controller was based on achievement of zero speed-tracking error to allow maximum energy capture in the low wind speed regime. However, the study did not incorporate structural load reduction in the control strategy, which is important if multi-objective control is to be implemented. In [4], a multi-variable control strategy for regulating generator power while minimizing rotor blade loads using a 1.5 MW wind turbine used in this paper, operating in the high wind speed regime was implemented. Contrary to [14], the study in [4] incorporated structural load reduction. A baseline PI controller was used to generate collective pitch angle control for generator speed regulation, and an independent pitch controller, which is designed in this paper, was used for structural load reduction in the high wind speed regime. Performance comparison was done between the multivariable control scheme, and the baseline PI control. The PI controller achieved speed and power regulation, and dampening of tower fore-aft deflection, while the independent pitch controller realized load reduction. However, structural load reduction in low wind speed regime was not explicitly studied. Most of the studies in the low wind speed regime are focused on maximizing power output by manipulating the rotor blade pitch to an optimum pitching angle to achieve highest possible lift, or generator torqu