A brief review on offshore wind turbine fault detection and recent development in condition monitoring based maintenance system

Offshore wind turbine requires more systematized operation and maintenance strategies to ensure systems are harmless, profitable and cost-effective. Condition monitoring and fault diagnostic systems ominously plays an important role in offshore wind turbine in order to cut down maintenance and operational costs. Condition monitoring techniques which describing complex faults and failure mode types and their generated traceable signs to provide cost-effective condition monitoring and predictive maintenance and their diagnostic schemes. Continuously monitor the condition of critical parts are the most efficient way to improve reliability of wind turbine. Implementation of Condition Based Maintenance (CBM) strategy provides right time maintenance decisions and Predictive Health Monitoring (PHM) data to overcome breakdown and machine downtime. Fault detection and CBM implementation is challenging for off shore wind farm due to the complexity of remote sensing, components health and predictive assessment, data collection, data analysis, data handling, state recognition, and advisory decision. The rapid expansion of wind farms, advanced technological development and harsh installation sites needs a successful CM approach. This paper aims to review brief status of recent development of CM techniques and focusing with major faults takes place in gear box and bearing, rotor and blade, pitch, yaw and tower system and generator and control system.

ADVANCED COMPUTATIONAL MODELING OF THE INTERNAL STRUCTURE OF SMART WIND-TURBINE BLADES

Implementation of stable aeroelastic models with the ability to capture the complex features of Multi concept smartblades is a prime step in reducing the uncertainties that come along with blade dynamics. The numerical simulations of fluid structure interaction can thus be used to test a realistic scenarios comprising of full-scale blades at a reasonably low computational cost. A code which was a combination of two advanced numerical models was designed and was run with the help of paralell HPC supercomputer platform. The first model was based on a variation of dimensional reduction technique proposed by Hodges and Yu. This model was the one to record the structural response of heterogenous composite blades. This technique reduces the geometrical complexities of the heterogenous blade section into a stiffness matrix for an equivalent beam. This derived equivalent 1-D strain energy matrix is similar to the actual 3-D strain energy matrix in an asymptotic sense. As this 1-D matrix helps in accurately modeling the blade structure as a 1-D finite element problem, this substantially redues the computational effort and subsequently the computational cost that are required to model the structural dynamics at each step. Second model comprises of implementation of the Blade Element Momentum Theory. In this approach we map all the velocities and the forces with the help of orthogonal matrices that help in capturing the large deformations and the effects of rotations in calculating the aerodynamic forces. This ultimately helps us to take into account the complex flexo torsional deformations. In this thesis we have succesfully tested these computayinal tools developed by MTU’s research team lead by for the aero elastic analysis of wind-turbine blades. The validation in this thesis is majorly based on several experiments done on NREL-5MW blade, as this is widely accepted as a benchmark blade in the wind industry. Along with the use of this innovative model the internal blade structure was also changed to add up to the existing benefits of the already advanced numerical models.

Stability enhancement of DFIG wind turbine using LQR pitch control over rated wind speed

A novel pitch control design method is proposed for the doubly fed induction generator (DFIG) wind turbine (WT) using linear quadratic regulator (LQR). A seven-order model represents the DFIG WT which is linearized by truncated Taylor series expansion. A systematic approach is adopted to determine the weighting matrices in LQR design for the optimal solution. Simulations have been carried out to compare the performance of the proposed LQR pitch control method against a PI pitch control for small and large disturbances. It is shown that the proposed control method enhances low-voltage ride-through capability and improves system damping under large disturbances.

Rapid displacement of dengue virus type 1 by type 4, Pacific region, 2007-2009

Since 2000-2001, dengue virus type 1 has circulated in the Pacific region. However, in 2007, type 4 reemerged and has almost completely displaced the strains of type 1. If only 1 serotype circulates at any time and is replaced approximately every 5 years, DENV-3 may reappear in 2012.

Fault detection in wind turbine : a systematic literature review

Wind power has become one of the popular renewable resources all over the world and is anticipated to occupy 12% of the total global electricity generation capacity by 2020. For the harsh environment that the wind turbine operates, fault diagnostic and condition monitoring are important for wind turbine safety and reliability. This paper employs a systematic literature review to report the most recent promotions in the wind turbine fault diagnostic, from 2005 to 2012. The frequent faults and failures in wind turbines are considered and different techniques which have been used by researchers are introduced, classified and discussed.

Acoustic emission condition monitoring : an application for wind turbine fault detection

Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.

Application of machine learning technique in wind turbine fault diagnosis

In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). The latter data set was used to compare anomaly detection with SVM, a previously well-known applied method, in rapidly finding the incipient faults.

Direct integration of battery energy storage systems in distributed power generation

In this paper, a wind energy conversion system interfaced to the grid using a dual inverter is proposed. One of the two inverters in the dual inverter is connected to the rectified output of the wind generator while the other is directly connected to a battery energy storage system (BESS). This approach eliminates the need for an additional dc-dc converter and thus reduces power losses, cost, and complexity. The main issue with this scheme is uncorrelated dynamic changes in dc-link voltages that results in unevenly distributed space vectors. A detailed analysis on the effects of these variations is presented in this paper. Furthermore, a modified modulation technique is proposed to produce undistorted currents even in the presence of unevenly distributed and dynamically changing space vectors. An analysis on the battery charging/discharging process and maximum power point tracking of the wind turbine generator is also presented. Simulation and experimental results are presented to verify the efficacy of the proposed modulation technique and battery charging/discharging process.

Design of a wind turbine - battery energy storage scheme to achieve power dispatchability

Battery energy storage system (BESS) is to be incorporated in a wind farm to achieve constant power dispatch. The design of the BESS is based on the forecasted wind speed, and the technique assumes the distribution of the error between the forecasted and actual wind speeds is Gaussian. It is then shown that although the error between the predicted and actual wind powers can be evaluated, it is non-Gaussian. With the known distribution in the error of the predicted wind power, the capacity of the BESS can be determined in terms of the confident level in meeting specified constant power dispatch commitment. Furthermore, a short-term power dispatch strategy is also developed which takes into account the state of charge (SOC) of the BESS. The proposed approach is useful in the planning of the wind farm-BESS scheme and in the operational planning of the wind power generating station.

Connecting two wind turbine generators to the grid using only one three level NPC inverter

This paper explores the possibility of connecting two Wind Turbine Generators (WTG) to the grid using a single three level inverter. In the proposed system the rectified output of one WTG is connected across the upper dc-link capacitor of a standard diode clamped three level inverter. Similarly the rectified output of the other WTG is connected across the lower capacitor. This particular combination has several advantages such as, direct connection to the grid, reduced parts count, improved reliability and high power capacity. However, the major problem in the proposed system is the imminent imbalance of dc-link voltages. Under such conditions conventional modulation methods fail to produce desired voltage and current waveforms. A detailed analysis on this issue and a novel space vector modulation method, as the solution, are proposed in this paper. To track the Maximum power point of each WTG a power sharing algorithm is proposed. Simulation results are presented to attest the efficacy of the proposed system.

Controller design for variable-speed permanent magnet wind turbine generators interfaced with Z-source inverter

Increased awareness of environmental concerns has caused greater interest in developing power sources based on renewable technologies, such as wind. Due to the intermittent nature of the wind speed, output voltage and frequency of the direct driven permanent magnet synchronous generators (PMSG) are normally unsteady. Recently proposed Z-source inverter has been considered as a potential solution for grid interfacing wind power generators, thanks to buck-boost function that the single stage Z-source inverter can offer. Two control methodologies, namely unified controller for isolated operation and a multi-loop controller for grid interfaced operation are investigated in this paper. Theoretical analysis of these two control schemes is presented and experimental results to verify the effectiveness of the control method are also included.

Application of anomaly technique in wind turbine bearing fault detection

Bearing faults are the most common cause of wind turbine failures. Unavailability and maintenance cost of wind turbines are becoming critically important, with their fast growing in electric networks. Early fault detection can reduce outage time and costs. This paper proposes Anomaly Detection (AD) machine learning algorithms for fault diagnosis of wind turbine bearings. The application of this method on a real data set was conducted and is presented in this paper. For validation and comparison purposes, a set of baseline results are produced using the popular one-class SVM methods to examine the ability of the proposed technique in detecting incipient faults.

Fault detection of wind turbine drivetrain utilizing power-speed characteristics

Wind energy, being the fastest growing renewable energy source in the present world, requires a large number of wind turbines to transform wind energy into electricity. One factor driving the cost of this energy is the reliable operation of these turbines. Therefore, it is a growing requirement within the wind farm community, to monitor the operation of the wind turbines on a continuous basis so that a possible fault can be detected ahead of time. As the wind turbine operates in an environment of constantly changing wind speed, it is a challenging task to design a fault detection technique which can accommodate the stochastic operational behavior of the turbines. Addressing this issue, this paper proposes a novel fault detection criterion which is robust against operational uncertainty, as well as having the ability to quantify severity level specifically of the drivetrain abnormality within an operating wind turbine. A benchmark model of wind turbine has been utilized to simulate drivetrain fault condition and effectiveness of the proposed technique has been tested accordingly. From the simulation result it can be concluded that the proposed criterion exhibits consistent performance for drivetrain faults for varying wind speed and has linear relationship with the fault severity level.