Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545336
Title: Intelligent autoreclosing for systems of high penetration of wind generation with real time modelling, development and deployment
Author: Le Blond, Simon
Awarding Body: University of Bath
Current Institution: University of Bath
Date of Award: 2011
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Abstract:
This thesis presents investigations into the effect of modern wind farms on grid side short circuits using extensive real time digital simulation. Particular reference is made to adaptive autoreclosing algorithms using artificial neural networks. A section of 132kV transmission grid in Scotland, including DFIG wind farms, is modelled on a real time digital simulator. An algorithm is then developed and tested using this model to show that this autoreclosing technique is feasible in systems with high penetration of wind generation. Although based on an existing technique, an important innovation is the use of two neural networks for the separate tasks of arc presence and extinction. The thesis also describes a low-cost, real time, relay development platform.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.545336  DOI: Not available
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