Use this URL to cite or link to this record in EThOS: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556126 |
![]() |
|||||||
Title: | Non invasive parameter identification of power plant characteristics based on recorded network transient data | ||||||
Author: | Hutchison, Graeme |
ISNI:
0000 0004 2720 3799
|
|||||
Awarding Body: | Newcastle University | ||||||
Current Institution: | University of Newcastle upon Tyne | ||||||
Date of Award: | 2011 | ||||||
Availability of Full Text: |
|
||||||
Abstract: | |||||||
Synchronous generators are the most widely used machines in power generation. Identifying their parameters in a non invasive way is very challenging due to the inherent nonlinearity of power plant performance. This thesis proposes a parameter identification method using particle swarm optimisation (PSO) for the identification of synchronous machine, excitation system and turbine parameters. The PSO allows a generator model output to be used as the objective function to give a new, more efficient method of parameter identification. This thesis highlights the effectiveness of the proposed method for the identification of power plant parameters, using both simulation and real recorded transient data. The thesis also considers the effectiveness of the method as the number of parameters to be identified is increased, and the effect of using differing forms of disturbances on parameter identification.
|
|||||||
Supervisor: | Not available | Sponsor: | Engineering and Physical Sciences Research Council ; Parsons Brinckerhoff ; Newcastle University | ||||
Qualification Name: | Thesis (D.Eng.) | Qualification Level: | Doctoral | ||||
EThOS ID: | uk.bl.ethos.556126 | DOI: | Not available | ||||
Share: |