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Dive into the research topics where Peter Fogh Odgaard is active.

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Featured researches published by Peter Fogh Odgaard.


IFAC Proceedings Volumes | 2009

Fault tolerant control of wind turbines: a benchmark model

Peter Fogh Odgaard; Jakob Stoustrup; Michel Kinnaert

Abstract The installed energy generation capacity of wind turbines is increasing dramatically on a global scale; this means that reliability of wind turbines is of higher importance. A part of this task is to improve fault detection and accommodation schemes of the wind turbine. This paper presents a benchmark model for simulation of fault detection and accommodation schemes. This benchmark model deals with the wind turbine on a system level containing sensors, actuators and systems faults in the pitch system, drive train, generator and converter system.


IEEE Transactions on Control Systems and Technology | 2013

Fault-Tolerant Control of Wind Turbines: A Benchmark Model

Peter Fogh Odgaard; Jakob Stoustrup; Michel Kinnaert

This paper presents a test benchmark model for the evaluation of fault detection and accommodation schemes. This benchmark model deals with the wind turbine on a system level, and it includes sensor, actuator, and system faults, namely faults in the pitch system, the drive train, the generator, and the converter system. Since it is a system-level model, converter and pitch system models are simplified because these are controlled by internal controllers working at higher frequencies than the system model. The model represents a three-bladed pitch-controlled variable-speed wind turbine with a nominal power of 4.8 MW. The fault detection and isolation (FDI) problem was addressed by several teams, and five of the solutions are compared in the second part of this paper. This comparison relies on additional test data in which the faults occur in different operating conditions than in the test data used for the FDI design.


american control conference | 2013

Wind turbine fault detection and fault tolerant control - An enhanced benchmark challenge

Peter Fogh Odgaard; Kathryn E. Johnson

Wind turbines are increasingly growing larger, becoming more complex, and being located in more remote locations, especially offshore. Interest in advanced controllers for normal operation has expanded in recent years, but fault detection and fault tolerant control for wind turbines is a less well-developed area of interest. In this benchmark challenge, we have reworked a previous challenge paper to present a more sophisticated wind turbine model - a modern 5 MW turbine implemented in the FAST software - and updated fault scenarios. These updates enhance the realism of the challenge and will therefore lead to solutions that are significantly more useful to the wind industry. This paper presents the challenge model and the requirements for challenge participants. In addition, it provides additional information about the faults selected for the challenge and their basis in field data.


IFAC Proceedings Volumes | 2009

Unknown Input Observer Based Scheme for Detecting Faults in a Wind Turbine Converter

Peter Fogh Odgaard; Jakob Stoustrup

Abstract In order to improve reliability of wind turbines, it is important to detect faults in the turbine as fast as possible to handle them in an optimal way. An important component in modern wind turbines is the converter, which for a wind turbine control point-of-view normally provides the torque acting on the wind turbine generator, as well as measurement of this torque. In this paper an unknown input observer is presented to estimate these faults in the converter and isolate them either to be an actuator fault or a sensor fault. The unknown input observer is used since the speed of wind acting on the wind turbine is assumed unknown, since measurement of it is influenced by the turbulence around the rotor plane. A detection scheme is formed based on these fault estimates. A detail simulation model is used to simulate a wind turbine in which both types of faults are present during the simulation. The detection scheme detects and isolates both faults with in 2 samples of its beginning.


IFAC Proceedings Volumes | 2008

On-Line Estimation of Wind Turbine Power Coefficients Using Unknown Input Observers

Peter Fogh Odgaard; Chris Damgaard; Rasmus Nielsen

Abstract As installed wind turbine energy generation capacity increases, the interest in optimizing these wind turbines increases as well. The optimal operating points for the power and speed control of the turbines depends on a mapping to the power conversion ratio (C p ) from tip speed ratio and blade pitch angles. This mapping changes slowly with time, which can lead to a non-optimal operation of the turbine with time. Another issue is quality of the initial mapping. It might be correct but it can be uncertain. This paper introduces a scheme to estimate this power conversion ratio. The estimated values can subsequently be used to calculate a new operating point. The estimation is based on an optimal unknown input observer.


IFAC Proceedings Volumes | 2012

Results of a wind turbine FDI competition

Peter Fogh Odgaard; Jakob Stoustrup

Abstract In this paper some newly published methods for fault detection and isolation developed for a wind turbine benchmark model are tested, compared and evaluated. These methods have been presented as a part of an international competition. The tested methods cover different types of fault detection and isolation methods, which include support vector machines, observer based methods, and auto generated methods. All of these methods show interesting potentials for usage in the wind turbine application, but all with different strong and weak sides in relation to the requirements specified in the proposed benchmark model.


international conference on control applications | 2010

Unknown input observer based detection of sensor faults in a wind turbine

Peter Fogh Odgaard; Jakob Stoustrup

in this paper an unknown input observer is designed to detect three different sensor fault scenarios in a specified bench mark model for fault detection and accommodation of wind turbines. A subset of faults is dealt with, which are faults in the rotor and generator speed sensors as well as a converter sensor fault. The proposed scheme detects the speed sensor faults in question within the specified requirements given in the bench mark model, while the converter fault is detected but not within the required time to detect.


IEEE Transactions on Energy Conversion | 2008

Observer and Data-Driven-Model-Based Fault Detection in Power Plant Coal Mills

Peter Fogh Odgaard; Bao Lin; Sten Bay Jørgensen

This paper presents and compares model-based and data-driven fault detection approaches for coal mill systems. The first approach detects faults with an optimal unknown input observer developed from a simplified energy balance model. Due to the time-consuming effort in developing a first principles model with motor power as the controlled variable, data-driven methods for fault detection are also investigated. Regression models that represent normal operating conditions (NOCs) are developed with both static and dynamic principal component analysis and partial least squares methods. The residual between process measurement and the NOC model prediction is used for fault detection. A hybrid approach, where a data-driven model is employed to derive an optimal unknown input observer, is also implemented. The three methods are evaluated with case studies on coal mill data, which includes a fault caused by a blocked inlet pipe. All three approaches detect the fault as it emerges. The optimal unknown input observer approach is most robust, in that, it has no false positives. On the other hand, the data-driven approaches are more straightforward to implement, since they just require the selection of appropriate confidence limit to avoid false detection. The proposed hybrid approach is promising for systems where a first principles model is cumbersome to obtain.


IEEE Transactions on Control Systems and Technology | 2015

A benchmark evaluation of fault tolerant wind turbine control concepts

Peter Fogh Odgaard; Jakob Stoustrup

As the worlds power supply to a larger and larger degree depends on wind turbines, it is consequently and increasingly important that these are as reliable and available as possible. Modern fault tolerant control (FTC) could play a substantial part in increasing reliability of modern wind turbines. A benchmark model for wind turbine fault detection and isolation, and FTC has previously been proposed. Based on this benchmark, an international competition on wind turbine FTC was announced. In this brief, the top three solutions from that competition are presented and evaluated. The analysis shows that all three methods and, in particular, the winner of the competition shows potential for wind turbine FTC. In addition to showing good performance, the approach is based on a method, which is relevant for industrial usage. It is based on a virtual sensor and actuator strategy, in which the fault accommodation is handled in software sensor and actuator blocks. This means that the wind turbine controller can continue operation as in the fault free case. The other two evaluated solutions show some potential but probably need improvements before industrial applications.


international conference on control applications | 2009

Robust LMI-based control of wind turbines with parametric uncertainties

Christoffer Sloth; Thomas Esbensen; Michael Odgaard Kuch Niss; Jakob Stoustrup; Peter Fogh Odgaard

This paper considers the design of robust LMIbased controllers for a wind turbine along its entire nominal operating trajectory. The proposed robust controller design takes into account parametric uncertainties in the model using a structured uncertainty description, which makes the controllers less conservative than controllers designed using unstructured uncertainty descriptions. The LMI-based approach enables additional constraints to be included in the design, which is exploited to include requirements for minimizing fatigue loads and actuator usage.

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Vicenç Puig

Spanish National Research Council

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Michel Kinnaert

Université libre de Bruxelles

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Teresa Escobet

Polytechnic University of Catalonia

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Bao Lin

Technical University of Denmark

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