The operation and maintenance costs of wind parks make up a major fraction of a park's overall lifetime costs. They also include opportunity costs of lost revenue from avoidable power generation underperformance. We present a machine-learning based decision support method that minimizes these opportunity costs. By analyzing the stream of telemetry sensor data from the turbine operation, estimating highly accurate power reference relations and benchmarking, we can detect performance-related operational faults in a turbine- and site-specific manner. The most accurate power reference model is selected based on combinations of machine learning algorithms and regressor sets. Operating personal can be alerted if a normal operating state boundary is exceeded. We demonstrate the performance fault detection method in a case study for a commercial grid-connected onshore wind turbine. Diagnosing a detected underperformance event, we find that the observed power generation deficiencies coincide with rotor blade misalignment related to low hydraulic pressure of the turbine's blade actuators.
This paper addresses the problem of control of a twin wind turbine which is subject to an electrical fault affecting only one stator phase of one turbine. An active fault tolerant control is proposed. The performance and robustness of the proposed control, comparing to a passive fault tolerant one developed in the literature, are shown through numerical simulations.
Floating Offshore Wind Turbines (FOWTs) operate in the harsh marine environment with limited accessibility and maintainability. Not only failures are more likely to occur than in land-based turbines, but also corrective maintenance is more expensive. In the present study, a mixed model and signal-based Fault Diagnosis (FD) architecture is developed to detect and isolate critical faults in FOWTs. More specifically, a model-based scheme is developed to detect and isolate the faults associated with the turbine system. It is based on a fault detection and approximation estimator and fault isolatio…
Individual Pitch Control (IPC) is an effective and widely-used strategy to mitigate blade loads in wind turbines. However, conventional IPC fails to cope with blade and actuator faults, and this situation may lead to an emergency shutdown and increased maintenance costs. In this paper, a Fault-Tolerant Individual Pitch Control (FTIPC) scheme is developed to accommodate these faults in Floating Offshore Wind Turbines (FOWTs), based on a Subspace Predictive Repetitive Control (SPRC) approach. To fulfill this goal, an online subspace identification paradigm is implemented to derive a linear appro…
With steadily increasing wind turbine penetration, regulatory standards for grid interconnection are evolving to require that wind generation systems ride-through disturbances such as faults and support the grid during such events. Conventional modifications to the doubly fed induction generation (DFIG) architecture for providing ride-through result in limited control of the turbine shaft and grid current during fault events. A DFIG architecture in which the grid side converter is connected in series as opposed to parallel with the grid connection has shown improved low voltage ride through bu…
As Floating Offshore Wind Turbines (FOWTs) operate in deep waters and are subjected to stressful wind and wave induced loads, they are more prone than onshore counterparts to experience faults and failure. In particular, the pitch system may experience Pitch Actuator Stuck (PAS) type of faults, which will result in a complete loss of control authority. In this paper, a novel fast and adaptive solution is developed by integrating a model-based Fault Diagnosis (FD) scheme and the Subspace Predictive Repetitive Control (SPRC). The FD role is to quickly detect and isolate the failed pitch actuator…
Floating Offshore Wind Turbines (FOWTs) are more prone to suffer from faults and failures than bottom-fixed counterparts due to the severe wind and wave loads typical of deep water sites. In particular, mooring line faults may lead to unacceptably high operation and maintenance costs due to the limited accessibility of FOWTs. Detecting the mooring line faults is therefore critical, but the application of Fault Detection (FD) techniques has not been investigated yet. In this paper, an FD scheme based on a wave-excited linear model is developed to detect in a reliable way critical mooring line f…
Inspired by recent progress in machine learning, a data-driven fault diagnosis and isolation (FDI) scheme is explicitly developed for failure in the fuel supply system and sensor measurements of the laboratory gas turbine system. A passive approach of fault diagnosis is implemented where a model is trained using machine learning classifiers to detect a given set of fault scenarios in real-time on which it is trained. Towards the end, a comparative study is presented for well-known classification techniques, namely Support vector classifier, linear discriminant analysis, K-neighbor, and decisio…
The wind energy industry has been experiencing tremendous growth and confronting the failures of wind turbine components. Wind turbine gearbox malfunctions are particularly prevalent and lead to the most prolonged downtime and highest cost. This paper presents a data-driven gearbox fault detection algorithm base on high frequency vibration data using graph neural network (GNN) models and sparse filtering (SF). The approach can take advantage of the comprehensive data sources and the complicated sensing networks. The GNN models, including basic graph neural networks, gated graph neural networks…
This paper presents developed real-time simulation models for offshore wind turbine generators in compliance with industry standards. The critical control functions such as negative sequence injection, sequence current limit, voltage ride through, and power curtailments are designed to meet the industry requirements for future electromagnetic transient (EMT) testing and controls of offshore wind farms. Average-value and switching detailed models are developed in the Opal-RT real-time simulator. Real-time capabilities of these models are compared to show the effectiveness of the average-value m…
Active power control regulates the total power generated by wind farms with the power consumed on the electricity grid. Due to wake effects, the available power is reduced and turbulence is increased at downstream wind turbines. Such effects lead to a design challenge for wind farm control, where the delicate balance between supply and demand should be maintained, while considering the load balancing in the wind turbine structures. We propose a control architecture based on simple feedback controllers that adjusts the demanded power set points of individual wind turbines to compensate for turb…
Based on a series of two experimental campaigns testing advanced controllers on a scaled wind turbine operating in a wind tunnel, this contribution describes the overall experimental method, challenges faced, lessons learned, and opportunities for future work. The two campaigns, run in Fall 2018 and Fall 2019, tested unconstrained and constrained optimal blade pitch controllers, respectively, using preview disturbance measurements of the oncoming wind. Specifically, the first study considered an extension to the linear-quadratic regulator to include feedforward action, while the second deploye…
Wind turbines may experience local weather perturbation, which is not taken into account by the commonly-used wind turbine simulation packages. Without this information, it is extremely challenging to evaluate the controller performance with regard to the effect of the variation of local atmospheric conditions. On the other side, it is too late and costly to wait until field test time. To fill this gap, in this paper, we develop a control-oriented turbine dynamic simulation framework to evaluate the controller performance considering the perturbation of local atmospheric conditions. This goal …
The use of state estimation technique offers a means of inferring the rotor-effective wind speed based upon solely standard measurements of the turbine. For the ease of design and computational concerns, such estimators are typically built based upon simplified turbine models that characterise the turbine with rigid blades. Large model mismatch, particularly in the power coefficient, could lead to degradation in estimation performance. Therefore, in order to effectively reduce the adverse impact of parameter uncertainties in the estimator model, this paper develops a wind sped estimator based …
There is growing importance to detecting faults and implementing the best methods in industrial and real-world systems. We are searching for the most trustworthy and practical data-based fault detection methods proposed by artificial intelligence applications. In this paper, we propose a framework for fault detection based on reinforcement learning and a policy known as proximal policy optimization. As a result of the lack of fault data, one of the significant problems with the traditional policy is its weakness in detecting fault classes, which was addressed by changing the cost function. Usi…
Fault Detection in New Wind Turbines with Limited Data by Generative Transfer Learning
School of Engineering and Computer Science, Bern University of Applied Sciences, Biel, Switzerland（工程与计算机科学学院，伯恩应用科学大学，瑞士比尔）；Faculty of Informatics, Università della Svizzera italiana, Lugano, Switzerland（信息学院，瑞士意大利大学，瑞士卢加诺）；Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, The Netherlands（地质与遥感系，代尔夫特理工大学，荷兰代尔夫特）
In this paper, the highly acknowledged advantages of the Model Predictive Control (MPC) approach are utilized to regulate the wind turbines' output power in the partial load region. In this region, the purpose of the designed controller is to capture maximum power from the wind. When the wind speed is above rated wind speed (full load region), control strategy is to keep output power and generator speed at their rated value. Because of the wind turbine's nonlinearities and constraints of the variables this is a challenging problem and two MPC-based methods are proposed, i.e. online and offline…
This paper solves the problem of regulating the rotor speed tracking error for wind turbines in the full-load region by an effective robust-adaptive control strategy. The developed controller compensates for the uncertainty in the control input effectiveness caused by a pitch actuator fault, unmeasurable wind disturbance, and nonlinearity in the model. Wind turbines have multi-layer structures such that the high-level structure is nonlinearly coupled through an aggregation of the low-level control authorities. Hence, the control design is divided into two stages. First, an $\mathcal{L}_2$ cont…
With the exploitation of wind power, more turbines will be deployed at remote areas possibly with harsh working conditions (e.g., offshore wind farm). The adverse working environment may lead to massive operating and maintenance costs of turbines. Deploying unmanned aerial vehicles (UAVs) for turbine inspection is considered as a viable alternative to manual inspections. An important objective of automated UAV inspection is to minimize the flight time of the UAVs to inspect all the turbines. A first contribution of this paper is thus formulating an optimization problem to compute the optimal r…
This paper presents a novel feature fusion-based deep learning model (called CASU2Net) for fault detection in offshore wind turbines. The proposed CASU2Net model benefits of a two-step early fusion to enrich features in the final stage. Moreover, since previous studies did not consider uncertainty while model developing and also predictions, we take advantage of Monte Carlo dropout (MC dropout) to enhance the certainty of the results. To design fault detection model, we use five sensors and a sliding window to exploit the inherent temporal information contained in the raw time-series data obta…
Recent years have seen an unprecedented growth in the use of sensor data to guide wind farm operations and maintenance. Emerging sensor-driven approaches typically focus on optimal maintenance procedures for single turbine systems, or model multiple turbines in wind farms as single component entities. In reality, turbines are composed of multiple components that dynamically interact throughout their lifetime. These interactions are central for realistic assessment and control of turbine failure risks. In this paper, an integrated framework that combines i) real-time degradation models used for…
Wind power is seeing a strong growth around the world. At the same time, shrinking profit margins in the energy markets let wind farm managers explore options for cost reductions in the turbine operation and maintenance. Sensor-based condition monitoring facilitates remote diagnostics of turbine subsystems, enabling faster responses when unforeseen maintenance is required. Condition monitoring with data from the turbines' supervisory control and data acquisition (SCADA) systems was proposed and SCADA-based fault detection and diagnosis approaches introduced based on single-task normal operatio…
Floating offshore wind turbines allow wind energy to be harvested in deep waters. However, additional dynamics and structural loads may result when the floating platform is being excited by wind and waves. In this work, the conventional wind turbine controller is complemented with a novel linear feedforward controller based on wave measurements. The objective of the feedforward controller is to attenuate rotor speed variations caused by wave forcing. To design this controller, a linear model is developed that describes the system response to incident waves. The performance of the feedback-feed…
WAKE-NET: A 3D-Wake-Aware Economic Turbine Layout and Cabling Optimization Framework for Multi-Capacity Multi-Hub-Height Wind Farms Serving Grid-Scale and Industrial Power Systems
The extreme loads experienced by the wind turbine in the extreme wind events are critical for the evaluation of structural reliability. Hence, the load alleviation control methods need to be designed and deployed to reduce the adverse effects of extreme wind events. This work demonstrates that the extreme loads are highly correlated to wind conditions such as turbulence-induced wind shears. Based on this insight, this work proposes a turbulence-based load alleviation control strategy for adapting the controller to changes in wind condition. The estimation of the rotor averaged wind shear based…
The thrust for increased rating capacity of wind turbines has resulted into larger generators, longer blades, and taller towers. Presently, up to 16 MW wind turbines are being offered by wind turbines manufacturers which is nearly a 60 percent increase in the design capacity over the last five years. Manufacturing of these turbines involves assembling of gigantic sized components. Due to the frequent design changes and the variety of tasks involved, conventional automation is not possible making it a labor-intensive activity. However the handling and assembling of large components are challeng…
This paper proposes a novel integrated multiport bidirectional back-to-back power converter for a type-4 wind turbine that accommodates a battery and supercapacitor for energy storage. The circuit topology reduces 4 switches compared to the traditional configuration. Moreover, owing to the dual-buck structure embedded in the phase leg, the circuitry has no short-circuit path, therefore it withstands short-circuited events for a much longer time than the normal phase-leg and prevents the reverse current in turn-off recovery. The use of a hybrid energy storage system with battery and supercapaci…
Wind turbine (WT) controllers are often geared towards maximum power extraction, while suitable operating constraints should be guaranteed such that WT components are protected from failures. Control strategies can be also devised to reduce the generated power, for instance to track a power reference provided by the grid operator. They are called down-regulation strategies and allow to balance power generation and grid loads, as well as to provide ancillary grid services, such as frequency regulation. Although this balance is limited by the wind availability and grid demand, the quality of win…
Optimising wind turbine performance involves maximising energy harvesting while seeking to minimise load fatigues on the tower structure, blades and rotor. To improve turbine control performance, wind preview measurement technologies such as Light Detection And Ranging (LIDAR) have been a point of interest for researchers in recent years. In this paper, we explore the application of a classical control methodology known as Exact Output Regulation (EOR) for improving the control performance of a LIDAR-enhanced wind turbine. The EOR controller is designed to achieve the rejection of known input …
Wind turbine condition monitoring based on intra- and inter-farm federated learning
Bern University of Applied Sciences, School of Engineering（伯恩应用科学大学工程学院）；Università della Svizzera italiana, Faculty of Informatics（瑞士联合大学信息学院）；Delft University of Technology, Department of Geoscience（代尔夫特理工大学地质学院）；Remote Sensing, Stevinweg 1, 2628 Delft, The Netherlands（遥感学院，Stevinweg 1，2628 Delft，荷兰）
With increased wind power penetration in modern power systems, wind plants are required to provide frequency support similar to conventional plants. However, for the existing frequency regulation scheme of wind turbines, the control gains in the auxiliary frequency controller are difficult to set because of the compromise of the frequency regulation performance and the stable operation of wind turbines, especially when the wind speed remains variable. This paper proposes a novel frequency regulation scheme (FRS) for de-loaded wind turbines. Instead of an auxiliary frequency controller, frequen…
Improving wind turbine efficiency is essential for reducing the costs of energy production. The highly nonlinear dynamics of the wind turbines and their uncertain operating conditions have posed many challenges for their control methods. In this work, a robust control strategy based on sliding mode and adaptive fuzzy disturbance observer is proposed for speed tracking in a variable speed wind turbine. First, the nonlinear mathematical model that describes the dynamics of the variable speed wind turbine is derived. This nonlinear model is then used to derive the control methodology and to find …
Although variable-speed three-blade wind turbines are nowadays quite popular, their control remains a challenging task. We propose a new easily implementable model-free control approach with the corresponding intelligent controllers. Several convincing computer simulations, including some fault accommodations, shows that model-free controllers are more efficient and robust than classic proportional-integral controllers.
This letter proposes a new control strategy for wind turbine generators to decide the necessity of switches between the normal operation and frequency support modes. The idea is to accurately predict an unsafe frequency response using a differential transformation method right after power imbalance is detected so as to adaptively activate a frequency support mode only when necessary. This control strategy can effectively avoid unnecessary switches with a conventional use of deadband but still ensure adequate frequency response.
In this manuscript, an image analytics based deep learning framework for wind turbine blade surface damage detection is proposed. Turbine blade(s) which carry approximately one-third of a turbine weight are susceptible to damage and can cause sudden malfunction of a grid-connected wind energy conversion system. The surface damage detection of wind turbine blade requires a large dataset so as to detect a type of damage at an early stage. Turbine blade images are captured via aerial imagery. Upon inspection, it is found that the image dataset was limited and hence image augmentation is applied t…
Dynamic induction control is a wind farm flow control strategy that utilises wind turbine thrust variations to accelerate breakdown of the aerodynamic wake and improve downstream turbine performance. However, when floating wind turbines are considered, additional dynamics and challenges appear that make optimal control difficult. In this work, we propose an adjoint optimisation framework for non-linear economic model-predictive control, which utilises a novel coupling of an existing aerodynamic wake model to floating platform hydrodynamics. Analysis of the frequency response for the coupled mo…
