Show simple item record

dc.contributor.advisorZivanovic, R.
dc.contributor.authorEls, Stephanus Lourens
dc.date.accessioned2023-05-04T11:59:46Z
dc.date.available2023-05-04T11:59:46Z
dc.date.issued2000
dc.identifier.urihttp://hdl.handle.net/10394/41239
dc.descriptionMEng, North-West University, Potchefstroom Campusen_US
dc.description.abstractState estimation is the process to calculate estimates for unknown state variables of a power network by minimising an objective function. Classical state estimators take into account that network parameters e.g. impedances and ad­mittances, and topology of the power network are accurately known for state estimation. This assumption can cause state variables to be incorrectly estimated. Network impedances can be in­correct or even unknown when a state estimation process needs to be done. The topology of the power network can also be incorrect or even unknown. A solution for these problems is to use a gen­eralised state estimator. A generalised state estimator uses advanced network modelling techniques. These techniques can be used to give estimates for network parameters and topology. The following advanced network modelling techniques are introduced: • Modelling of circuit breakers • Modelling of zero impedance branches • Modelling of network parameters • Modelling of transformer parameters These advanced modelling techniques are used in a state estimation process which minimised a Weighted Least Squares objective function. These advanced modelling techniques are also used in a state estimation process which minimised a Quadratic-Tangent objective function. Measurements obtained from a network are fraught with errors/bad data. Bad data is used in a state estimation process which minimised a Weighted Least Squares objective function. Bad data is also used in a state estimation process which minimised a Quadratic-Tangent objective function. Advanced network modelling techniques are used in both these estimation processes. From the results obtained, it is shown that in the presence of bad data, advanced network modelling techniques can be used in a state estimation process which minimises a Quadratic-Tangent objective function.en_US
dc.language.isoenen_US
dc.publisherNorth-West University (South Africa).en_US
dc.subjectPower systemsen_US
dc.subjectState estimationen_US
dc.subjectLoad flowen_US
dc.subjectMeasurementsen_US
dc.subjectState variablesen_US
dc.subjectTopologyen_US
dc.subjectObservabilityen_US
dc.subjectPseudo-measurementsen_US
dc.subjectQuadratic-Tangent Objective functionen_US
dc.titleAdvanced network modelling techniques for power system state estimationen_US
dc.typeThesisen_US
dc.description.thesistypeMastersen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record