dc.contributor |
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.contributor |
Puig, Vicen ç |
dc.contributor.author |
Negre Carrasco, Pep Llu ís |
dc.date |
2010-09 |
dc.identifier.uri |
http://hdl.handle.net/2099.1/16300 |
dc.language.iso |
eng |
dc.publisher |
Universitat Politècnica de Catalunya |
dc.rights |
Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.rights |
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject |
Àrees temàtiques de la UPC::Energies::Energia eòlica::Aerogeneradors |
dc.subject |
Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
dc.subject |
Wind turbines -- Automatic control |
dc.subject |
System failures (Engineering) -- Mathematical models |
dc.subject |
Aerogeneradors -- Control automàtic |
dc.subject |
Errors de sistemes (Enginyeria) -- Models matemàtics |
dc.title |
Fault Detection and Isolation of Wind Turbines - A Real Field Data Approach |
dc.type |
info:eu-repo/semantics/masterThesis |
dc.description.abstract |
The future of wind energy passes through the
installation of o shore wind farms. In such
locations a non-planned maintenance is highly
costly, therefore, a fault-tolerant control system
that is able to maintain the wind turbine connected after the occurrence of certain faults can
avoid major economic losses. The purpose of
this Master's thesis is to design a Fault Detection and Isolation (FDI) system, which is responsible of detecting the wind turbine faults
and identify their origin. In this sense, a robust
fault detection based on system identi fication
and adaptive threshold generation is proposed.
Real fi eld data is used to identify the nominal
model that produces the estimated output for
residual generation. To avoid long term deviations, this estimated output is computed from
the nominal model and an observer that follows
the so-called Luenberger scheme. Moreover, an
adaptive threshold based on model error modelling that take into account the nominal model
uncertainty i.e. makes the FDI system robust is
presented.
Since the wind turbine is a highly non-linear system with a complex operating range, all these
techniques are extrapolated to the entire wind
turbine range using Linear Parameter Varying
(LPV) models.
Finally, an analysis based on residual sensitivity is developed with the aim of making the FDI
system able to isolate the faults. |