SCADA data as a powerful tool for early fault detection in wind turbine gearboxes

2020 ◽  
pp. 0309524X2096941
Author(s):  
Khaled Taha Abd-Elwahab ◽  
Ali Ahmed Hassan
Keyword(s):  
Wind Speed ◽  
Fault Detection ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Comparison Method ◽  
Operating Conditions ◽  
Tree Model ◽  
Aggregated Model ◽  
Early Fault Detection ◽  
Abnormal Performance

The different operating conditions of wind turbines pose great challenges for efficient and reliable fault detection. Therefore, a good analysis of wind turbine data is essential in assessing the state of the wind turbines, since the traditional threshold cannot provide a timely warning as it indicates that the malfunction has already occurred. This paper presents a new method for analyzing the actual data of the turbines, using aggregated model consisting of the neighborhood comparison method, K-means clustering and decision tree model to diagnose faults. The wind speed of the adjacent turbines is compared with each other, then other parameters of the same wind speed are also compared with each other. The purpose of comparison is that, the wind turbines which are similar in wind speed are similar in performance as well. This approach helps us to discover the abnormal data for turbine performance with in the normal operating range. The abnormal performance of any turbine destroys the similarity relationship between its data and the neighboring unit’s data. The main advantage of this approach is the possibility to detect the beginning of abnormal performance in real time, a case study using real SCADA data is used to validate this approach, which demonstrates its effectiveness and advantages.

scholarly journals A Fault Detection System for The Yaw Control of A HAWT Based on Neural Networking

2021 ◽  
Vol 85 (1) ◽  
pp. 135-142
Author(s):  
Ahmed R. El-Mallawany ◽  
Sameh Shaaban ◽  
Aida Abdel Hafiz
Keyword(s):  
Fault Detection ◽  
Wind Turbine ◽  
Detection System ◽  
Operating Conditions ◽  
Horizontal Axis Wind Turbine ◽  
Yaw Control ◽  
Detection Approach ◽  
Simulation Results ◽  
Early Fault Detection ◽  
The Time Domain

The objective of the yaw control system in a horizontal axis wind turbine (HAWT) is to follow the wind direction with a minimum error. In this paper, a data driven fault detection approach of a HAWT is applied. Three simulation programs were utilized in order to model a 1.5 MW HAWT. These programs are Fatigue, Aerodynamics, Structures, and Turbulence(FAST), TurbSim, and MATLAB. The approach is implemented under normal operating scenarios while considering different wind velocities. Different kinds of faults were applied to the system for a nacelle-yaw angle error ranging from -10° to +20°. The simulation results of the Tower Top Deflection (TTD) in the time domain were transferred into frequency domain by Fast Fourier Transform (FFT). The output variables were used in order to build a Neural Networking, which will monitor the performance of the wind turbine. The built Neural Networking will also provide an early fault detection to avoid the operating conditions that lead to sudden turbine breakdown. The present work provides initial results that are useful for remote condition monitoring and assessment of a 1.5MW HAWT. The simulation results indicate that the implemented Neural Networking can achieve improvement of the wind turbine operation and maintenance level.

scholarly journals Performance Evaluation of Grid-Connected Wind Turbine Generators

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6807
Author(s):  
Henok Ayele Behabtu ◽  
Thierry Coosemans ◽  
Maitane Berecibar ◽  
Kinde Anlay Fante ◽  
Abraham Alem Kebede ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Generation ◽  
Operating Conditions ◽  
Induction Generator ◽  
Turbine Generators ◽  
Wind Turbine Generators ◽  
Generation Capacity ◽  
Variable Wind

The risk of oscillation of grid-connected wind turbine generators (WTGs) is well known, making it all the more important to understand the characteristics of different WTGs and analyze their performance so that the problems’ causes are identified and resolved. While many studies have evaluated the performance of grid-connected WTGs, most lack clarity and precision in the modeling and simulation techniques used. Moreover, most of the literature focuses on a single mode of operation of WTGs to analyze their performances. Therefore, this paper updates the literature by considering the different operating conditions for WTGs. Using MATLAB/SIMULINK it expands the evaluation to the full range of vulnerabilities of WTGs: from the wind turbine to grid connection. A network representing grid-connected squirrel-cage induction generator (SCIG) and doubly-fed induction generator (DFIG) wind turbines are selected for simulation. The performances of SCIG and DFIG wind turbines are evaluated in terms of their energy generation capacity during constant rated wind speed, variable wind speed, and ability of fault-ride through during dynamic system transient operating conditions. The simulation results show the performance of DFIG is better than SCIG in terms of its energy generation capacity during variable wind speed conditions and active and reactive power control capability during steady-state and transient operating conditions. As a result, DFIG wind turbine is more suitable for large-scale wind power plants connected to weak utility grid applications than SCIG.

scholarly journals Design of a Robust Adaptive Controller for the Pitch and Torque Control of Wind Turbines

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1195 ◽  
Author(s):  
Srikanth Bashetty ◽  
Joaquin I. Guillamon ◽  
Shanmukha S. Mutnuri ◽  
Selahattin Ozcelik
Keyword(s):  
Adaptive Control ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Degrees Of Freedom ◽  
Robust Adaptive Control ◽  
Operating Conditions ◽  
Torque Control ◽  
Rotor Speed ◽  
Robust Adaptive

In this paper, robust adaptive control is designed for pitch and torque control of the wind turbines operating under turbulent wind conditions. The dynamics of the wind turbine are formulated by considering the five degrees of freedom system (rotor angle, gearbox angle, generator angle, flap-wise deflection of the rotor blade, and axial displacement of the nacelle). The controller is designed to maintain the rotor speed, maximize the aerodynamic efficiency of the wind turbine, and reduce the loads due to high wind speeds. Gaussian probability distribution function is used for approximating the wind speed, which is given as the disturbance input to the plant. The adaptive control algorithm is implemented to 2 MW and 5 MW wind turbines to test the robustness of the controller for varying parameters. The simulation is carried out using MATLAB/Simulink for three cases, namely pitch control, torque control, and the combined case. A case study is done to validate the proposed adaptive control using real wind speed data. In all the cases, the results indicate that the rotor speed follows the reference speed and show that the designed controller gives a satisfactory performance under varying operating conditions and parameter variations.

Output wind power curve optimization based on design wind speed concept

2020 ◽  
pp. 0309524X1990100
Author(s):  
Cherif Khelifi ◽  
Fateh Ferroudji
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Power ◽  
Wind Turbines ◽  
Wind Farms ◽  
Operating Conditions ◽  
Speed Ratio ◽  
Power Curve ◽  
Design Wind Speed

The output wind power curve versus wind speed is the most important characterization parameter of wind turbines. It allows quantifying and analyzing the design performances of wind turbines, monitoring its database, and controlling the operation modes and manufacturing products. Wind power curve can be used to select the proper rotor size to estimate the potential of wind energy at candidate wind sites and to assess the control device of the operating conditions. Developing model strategies for wind farms has the basic objectives such as the optimization of wind power produced and the minimization of dynamic loads to provide the best quality of output wind power at reasonable cost. Optimal design of wind turbines requires maximum-closing to the cubical output wind power curve despite technical and economic considerations. This study aims to determine the design wind speed of a wind turbine based on modeling-optimization of the output wind power curve under certain working conditions. The procedure is applied to a unit wind turbine in Gamesa wind farm (G52/850, 10.2 MW, http://www.thewindpower.net ) connected to an electrical grid located in south-west Algeria and extrapolated for other windy sites in Algeria. From simulation results, the design wind speed to inlet wind speed ratio [Formula: see text] increased from 0.35 to 7.68 once [Formula: see text] increased from 0.001 to 2.9999. Consequently, the output wind power predicted an increase of about 17.7% and an annual specific wind energy factor of about 2.55%–4% than nominal value given by the manufacturer, reducing the unit average cost of the electricity, generated by wind farms, by about 18.75%.

scholarly journals Early Fault Detection of Wind Turbines Based on Operational Condition Clustering and Optimized Deep Belief Network Modeling

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 984 ◽  
Author(s):  
Hong Wang ◽  
Hongbin Wang ◽  
Guoqian Jiang ◽  
Jimeng li ◽  
Yueling Wang
Keyword(s):  
Fault Detection ◽  
Wind Turbines ◽  
Health Monitoring ◽  
Deep Belief Network ◽  
Operating Conditions ◽  
Behavior Modeling ◽  
Operation Condition ◽  
Belief Network ◽  
Operation Conditions ◽  
Early Fault Detection

Health monitoring and early fault detection of wind turbines have attracted considerable attention due to the benefits of improving reliability and reducing the operation and maintenance costs of the turbine. However, dynamic and constantly changing operating conditions of wind turbines still pose great challenges to effective and reliable fault detection. Most existing health monitoring approaches mainly focus on one single operating condition, so these methods cannot assess the health status of turbines accurately, leading to unsatisfactory detection performance. To this end, this paper proposes a novel general health monitoring framework for wind turbines based on supervisory control and data acquisition (SCADA) data. A key feature of the proposed framework is that it first partitions the turbine operation into multiple sub-operation conditions by the clustering approach and then builds a normal turbine behavior model for each sub-operation condition. For normal behavior modeling, an optimized deep belief network is proposed. This optimized modeling method can capture the sophisticated nonlinear correlations among different monitoring variables, which is helpful to enhance the prediction performance. A case study of main bearing fault detection using real SCADA data is used to validate the proposed approach, which demonstrates its effectiveness and advantages.

SHAPING OF AN AUTONOMOUS POWER SYSTEM FOR GUARANTEED POWER SUPPLY WITH THE PREDOMINANCE WIND ENERGY

2018 ◽  
pp. 28-50
Author(s):  
S. G. Ignatiev ◽  
S. V. Kiseleva
Keyword(s):  
Energy Storage ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Demand ◽  
Diesel Generator ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind

Optimization of the autonomous wind-diesel plants composition and of their power for guaranteed energy supply, despite the long history of research, the diversity of approaches and methods, is an urgent problem. In this paper, a detailed analysis of the wind energy characteristics is proposed to shape an autonomous power system for a guaranteed power supply with predominance wind energy. The analysis was carried out on the basis of wind speed measurements in the south of the European part of Russia during 8 months at different heights with a discreteness of 10 minutes. As a result, we have obtained a sequence of average daily wind speeds and the sequences constructed by arbitrary variations in the distribution of average daily wind speeds in this interval. These sequences have been used to calculate energy balances in systems (wind turbines + diesel generator + consumer with constant and limited daily energy demand) and (wind turbines + diesel generator + consumer with constant and limited daily energy demand + energy storage). In order to maximize the use of wind energy, the wind turbine integrally for the period in question is assumed to produce the required amount of energy. For the generality of consideration, we have introduced the relative values of the required energy, relative energy produced by the wind turbine and the diesel generator and relative storage capacity by normalizing them to the swept area of the wind wheel. The paper shows the effect of the average wind speed over the period on the energy characteristics of the system (wind turbine + diesel generator + consumer). It was found that the wind turbine energy produced, wind turbine energy used by the consumer, fuel consumption, and fuel economy depend (close to cubic dependence) upon the specified average wind speed. It was found that, for the same system with a limited amount of required energy and high average wind speed over the period, the wind turbines with lower generator power and smaller wind wheel radius use wind energy more efficiently than the wind turbines with higher generator power and larger wind wheel radius at less average wind speed. For the system (wind turbine + diesel generator + energy storage + consumer) with increasing average speed for a given amount of energy required, which in general is covered by the energy production of wind turbines for the period, the maximum size capacity of the storage device decreases. With decreasing the energy storage capacity, the influence of the random nature of the change in wind speed decreases, and at some values of the relative capacity, it can be neglected.

scholarly journals Monitoring Wind Turbine Gearbox with Echo State Network Modeling and Dynamic Threshold Using SCADA Vibration Data

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 982 ◽  
Author(s):  
Xin Wu ◽  
Hong Wang ◽  
Guoqian Jiang ◽  
Ping Xie ◽  
Xiaoli Li
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Operating Conditions ◽  
Dynamic Threshold ◽  
Detection Accuracy ◽  
Echo State Network ◽  
Monitoring Method ◽  
Vibration Data ◽  
Static Monitoring ◽  
Threshold Monitoring

Health monitoring of wind turbine gearboxes has gained considerable attention as wind turbines become larger in size and move to more inaccessible locations. To improve the reliability, extend the lifetime of the turbines, and reduce the operation and maintenance cost caused by the gearbox faults, data-driven condition motoring techniques have been widely investigated, where various sensor monitoring data (such as power, temperature, and pressure, etc.) have been modeled and analyzed. However, wind turbines often work in complex and dynamic operating conditions, such as variable speeds and loads, thus the traditional static monitoring method relying on a certain fixed threshold will lead to unsatisfactory monitoring performance, typically high false alarms and missed detections. To address this issue, this paper proposes a reliable monitoring model for wind turbine gearboxes based on echo state network (ESN) modeling and the dynamic threshold scheme, with a focus on supervisory control and data acquisition (SCADA) vibration data. The aim of the proposed approach is to build the turbine normal behavior model only using normal SCADA vibration data, and then to analyze the unseen SCADA vibration data to detect potential faults based on the model residual evaluation and the dynamic threshold setting. To better capture temporal information inherent in monitored sensor data, the echo state network (ESN) is used to model the complex vibration data due to its simple and fast training ability and powerful learning capability. Additionally, a dynamic threshold monitoring scheme with a sliding window technique is designed to determine dynamic control limits to address the issue of the low detection accuracy and poor adaptability caused by the traditional static monitoring methods. The effectiveness of the proposed monitoring method is verified using the collected SCADA vibration data from a wind farm located at Inner Mongolia in China. The results demonstrated that the proposed method can achieve improved detection accuracy and reliability compared with the traditional static threshold monitoring method.

Evaluation of the Dynamic-Response-Based Intact Stability Criterion for Floating Wind Turbines

2015 ◽  
Author(s):  
Marco Masciola ◽  
Xiaohong Chen ◽  
Qing Yu
Keyword(s):  
Wind Speed ◽  
Dynamic Response ◽  
Wind Turbines ◽  
Stability Criterion ◽  
Area Ratio ◽  
Operating Conditions ◽  
Dynamic Responses ◽  
Stability Criteria ◽  
Intact Stability ◽  
Overturning Moment

As an alternative to the conventional intact stability criterion for floating offshore structures, known as the area-ratio-based criterion, the dynamic-response-based intact stability criteria was initially developed in the 1980s for column-stabilized drilling units and later extended to the design of floating production installations (FPIs). Both the area-ratio-based and dynamic-response-based intact stability criteria have recently been adopted for floating offshore wind turbines (FOWTs). In the traditional area-ratio-based criterion, the stability calculation is quasi-static in nature, with the contribution from external forces other than steady wind loads and FOWT dynamic responses captured through a safety factor. Furthermore, the peak wind overturning moment of FOWTs may not coincide with the extreme storm wind speed normally prescribed in the area-ratio-based criterion, but rather at the much smaller rated wind speed in the power production mode. With these two factors considered, the dynamic-response-based intact stability criterion is desirable for FOWTs to account for their unique dynamic responses and the impact of various operating conditions. This paper demonstrates the implementation of a FOWT intact stability assessment using the dynamic-response-based criterion. Performance-based criteria require observed behavior or quantifiable metrics as input for the method to be applied. This is demonstrated by defining the governing load cases for two conceptual FOWT semisubmersible designs at two sites. This work introduces benchmarks comparing the area-ratio-based and dynamic-response-based criteria, gaps with current methodologies, and frontier areas related to the wind overturning moment definition.

scholarly journals Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4291
Author(s):  
Paxis Marques João Roque ◽  
Shyama Pada Chowdhury ◽  
Zhongjie Huan
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Wind Farms ◽  
Operating Conditions ◽  
Wake Effect ◽  
Wind Generators ◽  
Wind Potential

District of Namaacha in Maputo Province of Mozambique presents a high wind potential, with an average wind speed of around 7.5 m/s and huge open fields that are favourable to the installation of wind farms. However, in order to make better use of the wind potential, it is necessary to evaluate the operating conditions of the turbines and guide the independent power producers (IPPs) on how to efficiently use wind power. The investigation of the wind farm operating conditions is justified by the fact that the implementation of wind power systems is quite expensive, and therefore, it is imperative to find alternatives to reduce power losses and improve energy production. Taking into account the power needs in Mozambique, this project applied hybrid optimisation of multiple energy resources (HOMER) to size the capacity of the wind farm and the number of turbines that guarantee an adequate supply of power. Moreover, considering the topographic conditions of the site and the operational parameters of the turbines, the system advisor model (SAM) was applied to evaluate the performance of the Vestas V82-1.65 horizontal axis turbines and the system’s power output as a result of the wake effect. For any wind farm, it is evident that wind turbines’ wake effects significantly reduce the performance of wind farms. The paper seeks to design and examine the proper layout for practical placements of wind generators. Firstly, a survey on the Namaacha’s electricity demand was carried out in order to obtain the district’s daily load profile required to size the wind farm’s capacity. Secondly, with the previous knowledge that the operation of wind farms is affected by wake losses, different wake effect models applied by SAM were examined and the Eddy–Viscosity model was selected to perform the analysis. Three distinct layouts result from SAM optimisation, and the best one is recommended for wind turbines installation for maximising wind to energy generation. Although it is understood that the wake effect occurs on any wind farm, it is observed that wake losses can be minimised through the proper design of the wind generators’ placement layout. Therefore, any wind farm project should, from its layout, examine the optimal wind farm arrangement, which will depend on the wind speed, wind direction, turbine hub height, and other topographical characteristics of the area. In that context, considering the topographic and climate features of Mozambique, the study brings novelty in the way wind farms should be placed in the district and wake losses minimised. The study is based on a real assumption that the project can be implemented in the district, and thus, considering the wind farm’s capacity, the district’s energy needs could be met. The optimal transversal and longitudinal distances between turbines recommended are 8Do and 10Do, respectively, arranged according to layout 1, with wake losses of about 1.7%, land utilisation of about 6.46 Km2, and power output estimated at 71.844 GWh per year.

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