Use this URL to cite or link to this record in EThOS: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545336 |
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Title: | Intelligent autoreclosing for systems of high penetration of wind generation with real time modelling, development and deployment | ||||||
Author: | Le Blond, Simon |
ISNI:
0000 0004 2711 8930
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Awarding Body: | University of Bath | ||||||
Current Institution: | University of Bath | ||||||
Date of Award: | 2011 | ||||||
Availability of Full Text: |
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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.
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Supervisor: | Aggarwal, Raj | Sponsor: | Not available | ||||
Qualification Name: | Thesis (Ph.D.) | Qualification Level: | Doctoral | ||||
EThOS ID: | uk.bl.ethos.545336 | DOI: | Not available | ||||
Keywords: | wind ; protection and control ; Real time simulation of power systems | ||||||
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