Piecewise Affine System Identification of a Hydraulic Wind Power Transfer System

Hydraulic wind power transfer systems exhibit a highly nonlinear dynamic influenced by system actuator hysteresis and disturbances from wind speed and load torque. This paper presents a system identification approach to approximate such a nonlinear dynamic. Piecewise affine (PWA) models are obtained utilizing the averaged nonlinear models of hysteresis in a confined space. State-space representation of PWA models is obtained over the allocated operating point clusters. The experimental results demonstrate a close agreement with that of the simulated. The experimental results and simulation show more than 91% match

Hybrid modeling and control of mechatronic systems using a piecewise affine dynamics approach

This thesis investigates the topic of modeling and control of PWA systems based on two experimental cases of an electrical and hydraulic nature with varying complexity that were also built, instrumented and evaluated. A full-order model has been created for both systems, including all dominant system dynamics and non-linearities. The unknown parameters and characteristics have been identi ed via an extensive parameter identi cation. In the following, the non-linear characteristics are linearized at several points, resulting in PWA models for each respective setup. Regarding the closed loop control of the generated models and corresponding experimental setups, a linear control structure comprised of integral error, feed-forward and state-feedback control has been used. Additionally, the hydraulic setup has been controlled in an autonomous hybrid position/force control mode, resulting in a switched system with each mode's dynamics being de ned by the previously derived PWA-based model in combination with the control structure and respective mode-dependent controller gains. The autonomous switch between control modes has been de ned by a switching event capable of consistently switching between modes in a deterministic manner despite the noise-a icted measurements. Several methods were used to obtain suitable controller gains, including optimization routines and pole placement. Validation of the system's fast and accurate response was obtained through simulations and experimental evaluation. The controlled system's local stability was proven for regions in state-space associated with operational points by using pole-zero analysis. The stability of the hybrid control approach was proven by using multiple Lyapunov functions for the investigated test scenarios.publishedVersio

Control of a Hydraulic Wind Power Transfer System under Disturbances

Hydraulic wind power transfer systems deliver the captured energy by the blades to the generators differently and through an intermediate medium i.e. hydraulic fluid. This paper develops a control system for a nonlinear model of hydraulic wind power transfer systems. To maintain a fixed frequency electrical voltage by the system, the generator should remain at a constant rotational speed. The fluctuating wind speed from the upstream applies considerable disturbances on the system. A controller is designed and implemented to regulate the flow in the proportional valve and as a consequence the generator maintains its constant speed compensating for low wind speed and high wind speed disturbances. The controller is applied to the system by utilizing MATLAB/Simulink

Optimum Adaptive Piecewise Linearization: An Estimation Approach in Wind Power

This paper introduces an effective piecewise linearization technique to obtain an estimation of nonlinear models when their input-output domains include multidimensional operating points. The algorithm of a forward adaptive approach is introduced to identify the effective operating points for model linearization and adjust their domains for the maximum coverage and the minimum model linearization error. The technique obtains a minimum number of linearized models and the continuity of their domains. The algorithm also yields global minimum model linearization error. The introduced algorithm is formulated for a wind power transfer system for a 2-D set of input domains. The linearization error can be arbitrarily minimized in exchange for a higher number of models. The results demonstrate a significant improvement in the linearization of nonlinear models

Wind turbine simulator fault diagnosis via fuzzy modelling and identification techniques

For improving the safety and the reliability of wind turbine installations, the earliest and fastest fault detection and isolation are highly required, since it could be used also for accommodation purpose. Modern wind turbines consist of several important subsystems, which can be affected by malfunctions regarding actuators, sensors, and components. From the turbine control point-of-view they are extremely important since provide the actuation signals, the main functions, as well as the measurements. In this paper, a fault diagnosis scheme based on the identification of fuzzy models is described, in order to detect and isolate these faults in the most efficient way, in order also to improve the energy cost, the production rate, and reduce the operation and maintenance operations. Fuzzy systems are proposed here since the model under investigation is nonlinear, whilst the wind speed measurement is uncertain since it depends on the rotor plane wind turbulence effects. These fuzzy models are described as Takagi-Sugeno prototypes, whose parameters are estimated from the wind turbine measurements. The fault diagnosis methodology is thus developed using these fuzzy models, which are exploited as residual generators. The wind turbine simulator is finally employed for the validation of the obtained performances.For improving the safety and the reliability of wind turbine installations, the earliest and fastest fault detection and isolation is highly required, since it could be used also for accommodation purpose. Modern wind turbines consist of several important subsystems, which can be affected by malfunctions regarding actuators, sensors, and components. From the turbine control point–of–view they are extremely important since provide the actuation signals, the main functions, as well as the measurements. In this paper, a fault diagnosis scheme based on the identification of fuzzy models is described, in order to detect and isolated these faults in the most efficient way, in order also to improve the energy cost, the production rate, and reduce the operation and maintenance operations. Fuzzy systems are proposed here since the model under investigation is nonlinear, whilst the wind speed measurement is uncertain since it depends on the rotor plane wind turbulence effects. These fuzzy models are described as Takagi–Sugeno prototypes, whose parameters are estimated from the wind turbine measurements. The fault diagnosis methodology is thus developed using these fuzzy models, which are exploited as residual generators. The wind turbine simulator is finally employed for the validation of the obtained performances

Maximum power generation control of a hybrid wind turbine transmission system based on H∞ loop-shaping approach

The paper presents the design, modelling and optimal power generation control of a large hybrid wind turbine transmission system that seamless integrates planetary/parallel gear sets with a hydraulic transmission to improve the turbine’s reliability and efficiency. The hybrid wind turbine has power splitting flows including both mechanical and hydraulic power transmissions. The turbine transmission ratio can be controlled to continuously vary for the maximum wind power extraction and grid integration. Dynamics of the hybrid wind turbine is modeled as an incremental disturbed state space model based on the dynamic equations of each mechanical/hydraulic element. To achieve good tracking and robustness performance, an optimal H∞ loop-shaping pressure controller is designed, which accurately tracks the optimal load pressure in the hydraulic transmission for maximizing wind power generations. The validations of the proposed hybrid wind turbine and the H∞ loop-shaping pressure controller are performed based on a detailed aero-hydro-servo-elastic hybrid type wind turbine simulation platform with both mechanical geared transmission and hydraulic transmission, which is adapted from the NREL (National Renewable Energy Laboratory) 5 MW monopile wind turbine model within FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code. The validation results demonstrate that the hybrid wind turbine achieves better performance in both the maximum wind power extraction and power quality than the hydrostatic wind turbine. In addition, the proposed H∞ loop-shaping pressure controller has better tracking performance than the traditional proportional integral (PI) controller

Energy Storage Techniques for Hydraulic Wind Power Systems

Hydraulic wind power transfer systems allow collecting of energy from multiple wind turbines into one generation unit. They bring the advantage of eliminating the gearbox as a heavy and costly component. The hydraulically connected wind turbines provide variety of energy storing capabilities to mitigate the intermittent nature of wind power. This paper presents an approach to make wind power become a more reliable source on both energy and capacity by using energy storage devices, and investigates methods for wind energy electrical energy storage. The survey elaborates on three different methods named “Battery-based Energy Storage”, Pumped Storage Method, and “Compressed Air Energy Storage (CAES)”

Abandoned Mine Voids for Pumped Storage Hydro

Pumped Storage Hydro (PSH) is geographically limited but can expand greatly if abandoned subsurface coal mines are leveraged for the lower reservoir. Such lands are already permitted, generally less desirable, and found in regions eager for job creation. Vertical stacking of the upper and lower reservoirs is an efficient use of the land. Water can be raised by electric pumps as part of energy arbitrage; however, water can also be raised with Hydraulic Wind Turbines. HWTs are far less costly than traditional electric turbines, and start-up at lower wind speeds - thereby extending their geographic range. The HWT masts can serve double duty as tent poles to support translucent architectural fabric over the surface lake. This prevents evaporation and ingress of wildlife, and provides an interior space useful for non-electric revenue, such as aquaculture and greenhouses. Water cycled through the system can, in some cases, supplement local sources. Seepage through water tables replenishes clean water. Subsurface water is cool and can be circulated through server farms in data centers which represents a potential revenue source that can be started up well in advance of the primary energy storage operation. Combined, these factors bring an innovative solution to site selection, design, and engineering for PSH which promises accelerated commissioning and permitting, and low-cost operation. The bottom line for communities in Coal Country is more jobs and cheaper power

Data-driven techniques for the fault diagnosis of a wind turbine benchmark

This paper deals with the fault diagnosis of wind turbines and investigates viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator, i.e., the fault estimate, involves data-driven approaches, as they can represent effective tools for coping with poor analytical knowledge of the system dynamics, together with noise and disturbances. In particular, the proposed data-driven solutions rely on fuzzy systems and neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen architectures rely on nonlinear autoregressive models with exogenous input, as they can represent the dynamic evolution of the system along time. The developed fault diagnosis schemes are tested by means of a high-fidelity benchmark model that simulates the normal and the faulty behaviour of a wind turbine. The achieved performances are also compared with those of other model-based strategies from the related literature. Finally, a Monte-Carlo analysis validates the robustness and the reliability of the proposed solutions against typical parameter uncertainties and disturbances.This paper deals with the fault diagnosis of wind turbines and investigates viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator, i.e., the fault estimate, involves data-driven approaches, as they can represent effective tools for coping with poor analytical knowledge of the system dynamics, together with noise and disturbances. In particular, the proposed data-driven solutions rely on fuzzy systems and neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen architectures rely on nonlinear autoregressive models with exogenous input, as they can represent the dynamic evolution of the system along time. The developed fault diagnosis schemes are tested by means of a high-fidelity benchmark model that simulates the normal and the faulty behaviour of a wind turbine. The achieved performances are also compared with those of other model-based strategies from the related literature. Finally, a Monte-Carlo analysis validates the robustness and the reliability of the proposed solutions against typical parameter uncertainties and disturbances

Robust Control Applications to a Wind Turbine-Simulated System

Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modelling and control become challenging problems. On one hand, high-fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behaviour. Therefore, the development of modelling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this chapter is thus to provide two practical examples of development of robust control strategies when applied to a simulated wind turbine plant. Experiments with the wind turbine simulator represent the instruments for assessing the main aspects of the developed control methodologies