A hybrid method for observability analysis using a reduced network graph theory

Korres, GN; Katsikas, PJ

dc.contributor.author	Korres, GN	en
dc.contributor.author	Katsikas, PJ	en
dc.date.accessioned	2014-03-01T01:18:32Z
dc.date.available	2014-03-01T01:18:32Z
dc.date.issued	2003	en
dc.identifier.issn	0885-8950	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15066
dc.subject	Graph theory	en
dc.subject	Observability analysis	en
dc.subject	Observable islands	en
dc.subject	Rank deficiency	en
dc.subject	Reduced model	en
dc.subject	Supernodes	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Electric power systems	en
dc.subject.other	Errors	en
dc.subject.other	Graph theory	en
dc.subject.other	Numerical methods	en
dc.subject.other	Network gain matrix	en
dc.subject.other	Circuit theory	en
dc.title	A hybrid method for observability analysis using a reduced network graph theory	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TPWRS.2002.807072	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TPWRS.2002.807072	en
heal.language	English	en
heal.publicationDate	2003	en
heal.abstract	This paper presents a hybrid topological-numerical approach for observability analysis in power system state estimation. By partitioning the network in observable areas, a reduced network is formed, where each area is represented by a supernode and each line between areas as a branch. We select as areas the flow islands, being the maximal connected components of flow-measured branches. Only boundary nodes and injections at flow islands are retained for numerical processing. Observability testing and identification of maximal observable islands are accomplished by numerical processing on the echelon form of a rectangular test matrix, which is based on the reduced network graph properties. The method uses a noniterative scheme to select a minimal set of nonredundant pseudo measurements which make an unobservable network barely observable. The existing numerical methods are based on the number of zero pivots obtained during the triangular factorization of the gain matrix. Due to round-off errors, the zero pivots may be misclassified. In the proposed method, the nonzero values of the processed test matrix are + 1 or - 1, resulting in better numerical conditioning and accurate detection of zero pivots. The test matrix is generally sparser than the reduced network gain matrix. As a consequence, the proposed method is faster either for observability testing or multiple measurement placement. Several test results are presented.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Power Systems	en
dc.identifier.doi	10.1109/TPWRS.2002.807072	en
dc.identifier.isi	ISI:000180981100040	en
dc.identifier.volume	18	en
dc.identifier.issue	1	en
dc.identifier.spage	295	en
dc.identifier.epage	304	en