An evolutionary computation solution to the governor-turbine parameter estimation problem

Stefopoulos, GK; Georgilakis, PS; Hatziargyriou, ND

dc.contributor.author	Stefopoulos, GK	en
dc.contributor.author	Georgilakis, PS	en
dc.contributor.author	Hatziargyriou, ND	en
dc.date.accessioned	2014-03-01T02:43:06Z
dc.date.available	2014-03-01T02:43:06Z
dc.date.issued	2005	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31235
dc.subject	Evolutionary computation	en
dc.subject	Genetic algorithms	en
dc.subject	Parameter estimation	en
dc.subject	Simulation-based optimization	en
dc.subject.other	Power system transient phenomena	en
dc.subject.other	Simulation based optimization	en
dc.subject.other	Speed governors	en
dc.subject.other	Computation theory	en
dc.subject.other	Electric power systems	en
dc.subject.other	Optimization	en
dc.subject.other	Parameter estimation	en
dc.subject.other	Evolutionary algorithms	en
dc.title	An evolutionary computation solution to the governor-turbine parameter estimation problem	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ISAP.2005.1599276	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ISAP.2005.1599276	en
heal.identifier.secondary	1599276	en
heal.publicationDate	2005	en
heal.abstract	Speed governors are key elements in the dynamic performance of electric power systems. Therefore, accurate governor models are of great importance in simulating and investigating the power system transient phenomena. Model parameters of such devices are, however, usually unavailable or inaccurate, especially when old generators are involved. Most methods for speed governor parameter estimation are based on measurements of frequency and active power variations during transient operation. This paper proposes an evolutionary-computation-based optimization technique for parameter estimation, which makes use of such measurements. The proposed methodology uses a real-coded genetic algorithm. The paper estimates the parameters of all system generators simultaneously, instead of every machine independently, which is fully in line with the interest to treat the electric power system as a whole and study its comprehensive behaviour. Moreover, the methodology is not model-dependent and, therefore, it is readily applicable to a variety of model types and for many different test procedures. The proposed methodology is applied to the electric power system of Crete and the results demonstrate the feasibility and practicality of this approach. © 2005 ISAP.	en
heal.journalName	Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, ISAP'05	en
dc.identifier.doi	10.1109/ISAP.2005.1599276	en
dc.identifier.volume	2005	en
dc.identifier.spage	280	en
dc.identifier.epage	285	en