Improved Wind Turbine Control Strategies for Maximizing Power Output and Minimizing Power Flicker

For reducing the cost of energy (COE) for wind power, controls techniques are important for enhancing energy yield, reducing structural load and improving power quality. This thesis presents the control strategies studies for wind turbine both from the perspectives of both maximizing power output and reducing power flicker and structural load, First, a self-optimizing robust control scheme is developed with the objective of maximizing the power output of a variable speed wind turbine with doubly-fed induction generator (DFIG) operated in Region 2. Wind power generation can be divided into two stages: conversion from aerodynamic power to rotor (mechanical) power and conversion from rotor power to the electrical (grid) power. In this work, the maximization of power generation is achieved by a two-loop control structure in which the power control for each stage has intrinsic synergy. The outer loop is an Extremum Seeking Control (ESC) based generator torque regulation via the rotor power feedback. The ESC can search for the optimal torque constant to maximize the rotor power without wind measurement or accurate knowledge of power map. The inner loop is a vector-control based scheme that can both regulate the generator torque requested by the ESC and also maximize the conversion from the rotor power to grid power. In particular, an ∞ controller is synthesized for maximizing, with performance specifications defined based upon the spectrum of the rotor power obtained by the ESC. Also, the controller is designed to be robust against the variations of some generator parameters. The proposed control strategy is validated via simulation study based on the synergy of several software packages including the TurbSim and FAST developed by NREL, Simulink and SimPowerSystems. Then, a bumpless transfer scheme is proposed for inter-region controller switching scheme in order to reduce the power fluctuation and structural load under fluctuating wind conditions. This study considers the division of Region 2, Region 2.5 and Region 3 in the neighborhood of the rated wind speed. When wind, varies around the rated wind speed, the switching of control can lead to significant fluctuation in power and voltage supply, as well as structural loading. To smooth the switch and improve the tracking, two different bumpless transfer methods, Conditioning and Linear Quadratic techniques, are employed for different inter-region switching situations. The conditioning bumpless transfer approach adopted for switching between Region 2 maximum power capture controls to Region 2.5 rotor speed regulation via generator torque. For the switch between Region 2.5 and Region 3, the generator torque windup at rated value and pitch controller become online to limit the load of wind turbine. LQ technique is posed to reduce the discontinuity at the switch between torque controller and pitch controller by using an extra compensator. The flicker emission of the turbine during the switching is calculated to evaluate power fluctuation. The simulation results demonstrated the effectiveness of the proposed scheme of inter-region switching, with significant reduction of power flicker as well as the damage equivalent load

Wind Turbine Controls for Farm and Offshore Operation

Development of advanced control techniques is a critical measure for reducing the cost of energy for wind power generation, in terms of both enhancing energy capture and reducing fatigue load. There are two remarkable trends for wind energy. First, more and more large wind farms are developed in order to reduce the unit-power cost in installation, operation, maintenance and transmission. Second, offshore wind energy has received significant attention when the scarcity of land resource has appeared to be a major bottleneck for next level of wind penetration, especially for Europe and Asia. This dissertation study investigates on several wind turbine control issues in the context of wind farm and offshore operation scenarios. Traditional wind farm control strategies emphasize the effect of the deficit of average wind speed, i.e. on how to guarantee the power quality from grid integration angle by the control of the electrical systems or maximize the energy capture of the whole wind farm by optimizing the setting points of rotor speed and blade pitch angle, based on the use of simple wake models, such as Jensen wake model. In this study, more complex wake models including detailed wind speed deficit distribution across the rotor plane and wake meandering are used for load reduction control of wind turbine. A periodic control scheme is adopted for individual pitch control including static wake interaction, while for the case with wake meandering considered, both a dual-mode model predictive control and a multiple model predictive control is applied to the corresponding individual pitch control problem, based on the use of the computationally efficient quadratic programming solver qpOASES. Simulation results validated the effectiveness of the proposed control schemes. Besides, as an innovative nearly model-free strategy, the nested-loop extremum seeking control (NLESC) scheme is designed to maximize energy capture of a wind farm under both steady and turbulent wind. The NLESC scheme is evaluated with a simple wind turbine array consisting of three cascaded variable-speed turbines using the SimWindFarm simulation platform. For each turbine, the torque gain is adjusted to vary/control the corresponding axial induction factor. Simulation under smooth and turbulent winds shows the effectiveness of the proposed scheme. Analysis shows that the optimal torque gain of each turbine in a cascade of turbines is invariant with wind speed if the wind direction does not change, which is supported by simulation results for smooth wind inputs. As changes of upstream turbine operation affects the downstream turbines with significant delays due to wind propagation, a cross-covariance based delay estimate is proposed as adaptive phase compensation between the dither and demodulation signals. Another subject of investigation in this research is the evaluation of an innovative scheme of actuation for stabilization of offshore floating wind turbines based on actively controlled aerodynamic vane actuators. For offshore floating wind turbines, underactuation has become a major issue and stabilization of tower/platform adds complexity to the control problem in addition to the general power/speed regulation and rotor load reduction controls. However, due to the design constraints and the significant power involved in the wind turbine structure, a unique challenge is presented to achieve low-cost, high-bandwidth and low power consumption design of actuation schemes. A recently proposed concept of vertical and horizontal vanes is evaluated to increase damping in roll motion and pitch motion, respectively. The simulation platform FAST has been modified including vertical and horizontal vane control. Simulation results validated the effectiveness of the proposed vertical and horizontal active vane actuators

Towards data-driven and data-based control of wave energy systems: Classification, overview, and critical assessment

Currently, a significant effort in the world research panorama is focused on finding efficient solutions to a carbon-free energy supply, wave energy being one of the most promising sources of untapped renewable energy. However, wave energy is not currently economic, though control technology has been shown to significantly increase the energy capture capabilities. Usually, the synthesis of a wave energy control strategy requires the adoption of control-oriented models, which are prone to error, particularly arising from unmodelled hydrodynamics, given the complexity of the hydrodynamic interactions between the device and the ocean. In this context, data-driven and data-based control strategies provide a potential solution to some of these issues, using real-time data to gather information about the system dynamics and performance. Thus motivated, this study provides a detailed analysis of different approaches to the exploitation of data in the design of control philosophies for wave energy systems, establishing clear definitions of data-driven and data-based control in this field, together with a classification highlighting the various roles of data in the control synthesis process. In particular, we investigate intrinsic opportunities and limitations behind the use of data in the process of control synthesis, providing a comprehensive review together with critical considerations aimed at directly contributing towards the development of efficient data-driven and data-based control systems for wave energy devices

A LYAPUNOV BASED APPROACH TO ENERGY MAXIMIZATION IN RENEWABLE ENERGY TECHNOLOGIES

This dissertation describes the design and implementation of Lyapunov-based control strategies for the maximization of the power captured by renewable energy harnessing technologies such as (i) a variable speed, variable pitch wind turbine, (ii) a variable speed wind turbine coupled to a doubly fed induction generator, and (iii) a solar power generating system charging a constant voltage battery. First, a torque control strategy is presented to maximize wind energy captured in variable speed, variable pitch wind turbines at low to medium wind speeds. The proposed strategy applies control torque to the wind turbine pitch and rotor subsystems to simultaneously control the blade pitch and tip speed ratio, via the rotor angular speed, to an optimum point at which the capture efficiency is maximum. The control method allows for aerodynamic rotor power maximization without exact knowledge of the wind turbine model. A series of numerical results show that the wind turbine can be controlled to achieve maximum energy capture. Next, a control strategy is proposed to maximize the wind energy captured in a variable speed wind turbine, with an internal induction generator, at low to medium wind speeds. The proposed strategy controls the tip speed ratio, via the rotor angular speed, to an optimum point at which the efficiency constant (or power coefficient) is maximal for a particular blade pitch angle and wind speed by using the generator rotor voltage as a control input. This control method allows for aerodynamic rotor power maximization without exact wind turbine model knowledge. Representative numerical results demonstrate that the wind turbine can be controlled to achieve near maximum energy capture. Finally, a power system consisting of a photovoltaic (PV) array panel, dc-to-dc switching converter, charging a battery is considered wherein the environmental conditions are time-varying. A backstepping PWM controller is developed to maximize the power of the solar generating system. The controller tracks a desired array voltage, designed online using an incremental conductance extremum-seeking algorithm, by varying the duty cycle of the switching converter. The stability of the control algorithm is demonstrated by means of Lyapunov analysis. Representative numerical results demonstrate that the grid power system can be controlled to track the maximum power point of the photovoltaic array panel in varying atmospheric conditions. Additionally, the performance of the proposed strategy is compared to the typical maximum power point tracking (MPPT) method of perturb and observe (P&O), where the converter dynamics are ignored, and is shown to yield better results

Combining pendulum and gyroscopic effects to step-up wave energy extraction in all degrees of freedom

The fight against the global threat of climate change requires, among other actions, to increase the penetration of renewable energy technologies and diversify the energy mix in order to support a resilient energy system that can reach net-zero greenhouse gas emissions. Offshore energy is expected to drive the energy transition, with wave energy having the major role to provide a reliable baseload and reduce the need for storage; however, its techno-economic feasibility requires reduction of costs and increase of energy conversion efficiency. This paper tackles a fundamental innovation of a device’s working principle which, jointly exploiting pendulum and gyroscopic effects, steps-up the overall conversion efficiency in real operational conditions. A recent patent proposes a technological solution that conveniently combines pendulum and gyroscopic effects in order to effectively exploit motion also outside the plane, namely in the three-dimensional space and from all degrees of freedom (DoFs). This paper tackles the endeavour of the analytical formulation of the electro-mechanical conversion system dynamics, considering at first the fully-nonlinear equation of motion, obtained through a Lagrangian approach. Consequently, incremental simplifications are applied to accommodate practical application, based on the study on the relative importance of each term in the equation of motion. Furthermore, preliminary results are produced and discussed, comparing the behaviour in response to 3-DoF to 6-DoF exploitation

School of water, energy and envitornment energy systems and thermal processes

The fast development of the wind power technology is leading to larger and more expensive wind turbines which require increasingly advance control systems to achieve optimal or near optimal operation. However, the increased optimality of complex operation schemes, like real-time optimization approaches, incur in high implementation and maintenance costs. Furthermore, while the wind speed is a key variable for the wind turbine control, using it as a direct input leads to a poor response of the power control. This makes the industry focus on simpler control structures, considering wind as a disturbance [1]. Nevertheless, baseline control laws, which perform a deterministic control, require that complex aerodynamic properties are well-known to achieve the desired performance. But in practice, variability bounds the efficiency of the energy capture. Thus, a constrained self-optimizing control is proposed to regulate the wind turbine operation coping with wind speed uncertainty. A data-driven self-optimizing control is proposed for the wind turbine control region where power is maximized (region 2). Operational data is extracted from a model off-line to examine the structure of the optimal solution. This insight is then transformed into a simple control structure capable of keeping the wind turbine to an optimal operation, in terms of maximizing power output. However, at high wind speed, wind turbine power output has to be maintained at its nominal rate. Thus, a cascade control structure for self-optimizing and constrained control is incorporated. The control structure is implemented in Simulink using as a model FAST v8 5MW onshore wind turbine model. The proposed self-optimizing control learns the structure of the optimal solution off-line and then performs the optimization strategy, adjusting both torque and pitch to maximize energy capture. This control approach leads to an increase in power output when comparing it with the deterministic baseline control. Moreover, this heuristic control approach has the potential to take into account a higher number of inputs without compromising reliability. This property allows its future application for more advance control strategies

Adaptive control algorithm for improving power capture of wind turbines in turbulent winds

Abstract — The standard wind turbine (WT) control law modifies the torque applied to the generator as a quadratic function of the generator speed (Kω 2) while blades are positioned at some optimal pitch angle (β ∗). The value of K and β ∗ should be properly selected such that energy capture is increased. In practice, the complex and time-varying aerodynamics a WT face due to turbulent winds make their determination a hard task. The selected constant parameters may maximize energy for a particular, but not all, wind regime conditions. Adaptivity can modify the controller to increase power capture under variable wind conditions. This paper present new analysis tools and an adaptive control law to increase the energy captured by a wind turbine. Due to its simplicity, it can be easily added to existing industry-standard controllers. The effectiveness of the proposed algorithm is assessed by simulations on a high-fidelity aeroelastic code. Index Terms — Wind Turbines, Adaptive Control, efficiency. I