The momentous need for optimal operational and maintenance costs of wind energy drives can be accomplished by efficient monitoring of these systems. This allows us to detect the deterioration of the wind energy conversion system's health in early stage. As the frequent inaccessibility of the wind generators due to their positioning heights and as well as the rapid development in offshore wind farms triggering the importance of condition supervision and diagnosis of faults in wind energy conversion systems (WECS). To handle any fault occurred in the current sensor of doubly fed induction generator, a commonly used generator in wind turbines kalman filter is used to detect the sensor fault. Using the generalized observer scheme and dedicated observer scheme the detection and isolation of multiple sensor faults was explained. © 2013 IEEE.

Saravanakumar R

Department of Control and Automation

School of Electrical Engineering

Vellore Campus

Manimozhi M

Enosh M.T.

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

A survey of fault detection and isolation in wind turbine drives

2013 International Conference on Power, Energy and Control (ICPEC)

The fault detection and isolation of generators used in wind turbines gathering interest as to maximize the reliability and avail of distributed energy systems with recent unmatched growth in construction of offshore wind farms. In particular it is interested in performing fault detection and isolation (FDI) of incipient faults affecting the measurements of the three-phase signals (currents) in a controlled DFIG and PMSG. Although different authors have dealt with FDI for sensors in induction machines and in DFIGs, most of them rely on the machine model with constant parameters. However, the parameter uncertainties due to changes in the operating conditions will produce degradation in the performance of such FDI systems. The robust techniques to detect faults are exist but there is a need of extra sensor. This paper proposed a systematic methodology for the design of sensor FDI systems with the following characteristics: i) capable of detecting and isolating incipient additive (bias) faults, ii) robust against changes in the references/ disturbances affecting the controlled DFIG and PMSG as well as modeling/parametric uncertainties, iii) residual generation system based on a multi-observer strategy to enhance the isolation process, The designed sensor FDI systems have been validated using measured voltages, as well as simulated data from a controlled DFIG. First the state space models of DFIG and PMSM explained followed by kalman filter introduction and current sensor fault detection using a bank of kalman filter named dedicated Observer Scheme and generalized Observer scheme to detect simultaneous and multiple faults was theorized and simulated using MATLAB simulation tool .The simulation results were summarized with and without Sensor fault.

Fulltext

Energy Procedia

Simulation of Sensor Fault Diagnosis for Wind Turbine Generators DFIG and PMSM Using Kalman Filter

Wind Power for the World

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2011 International Conference on Communications, Computing and Control Applications (CCCA)

Current sensor FDI by Generalized Observer Scheme for a generator in wind turbine

IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society

Power smoothing of doubly fed induction generator for wind turbine using ultracapacitors

IEEE Transactions on Industrial Electronics

Doubly Fed Induction Generator Model-Based Sensor Fault Detection and Control Loop Reconfiguration

Journal of Aerospace Engineering

Soft Computing Algorithm to Data Validation in Aerospace Systems Using Parity Space Approach

Journal	Data powered by Typeset2013 International Conference on Power, Energy and Control (ICPEC)
Publisher	Data powered by TypesetIEEE
Open Access	0