Contribution of Nanotechnology in Optimization of Thermal and Dielectric Properties for Improving Insulating Performance of Natural Ester Oils

Emara, Manal M.

dc.contributor.author	Emara, Manal M.
dc.date.accessioned	2022-01-18T06:28:28Z
dc.date.available	2022-01-18T06:28:28Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/54343
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.22041
dc.rights	Default License
dc.subject	Lightning impulse voltage	en
dc.subject	Nanofluid	en
dc.subject	Power transformer	en
dc.subject	Dissolved gas analysis (DGA)	en
dc.subject	Thermal conductivity	en
dc.title	Contribution of Nanotechnology in Optimization of Thermal and Dielectric Properties for Improving Insulating Performance of Natural Ester Oils	en
dc.contributor.department	High Voltage and Electrical Measurements Laboratory	el
heal.type	doctoralThesis
heal.classification	High voltage engineering	en
heal.classification	Nanotechnology	en
heal.classification	Electrical Engineering	en
heal.language	en
heal.access	campus
heal.recordProvider	ntua	el
heal.publicationDate	2021-10-26
heal.abstract	The infrastructure of every power system includes a large number of transformers. Therefore, the reliability of the entire system depends heavily on the well operation of each transformer and, more specifically, on its dielectric insulation capabilities which rely mainly on its high thermal and dielectric properties. Another parameter, contributing significantly to system reliability by preventing unwanted power loss and transformer failure events, is the detection and diagnosis of their initial fault. The recent focus of the international industry in environment friendly solutions has also affected, as part of a stricter environmental framework, the construction and insulation material technologies. Towards this effort, the substitution of mineral oils with natural, “green”, insulating oils can potentially be a step of significant importance, drawing therefore the attention of the relevant research community. Another main field of interests for researches of the field is the utilization of nanoparticles, dispersed in insulating oil, forming nanofluids for improving its insulation performance. In this thesis, nanofluids were prepared using the prepared pentyl‑graphene nanosheets with different concentrations mainly to investigate the thermal properties of nanofluids compared to pure oils. These properties were examined based on the measured thermal diffusivity and specific heat values by LFA (Laser Flash analysis) and DSC (Differential Scanning Calorimetry), respectively, for a range of temperature values. Most importantly, the hybrid nanofluid maintains its dielectric properties, such as relative permittivity and electrical conductivity measured by means of broadband dielectric spectroscopy for a range of frequencies through heating and cooling processes. The optimal concentration value regarding the performance in terms of thermal and dielectric properties is obtained. Additionally, UV-Visible absorbance is used for the properties’ behavior for different graphene concentration values. Furthermore, another type of natural ester oil based nanofluids was prepared by employing magnesium oxide nanoparticles with different concentrations to investigate their electrical properties under the effect of lightning impulse voltage of 1.2/50μs by utilizing a one-stage impulse generator. The impulse voltage and the transient current were measured, while the breakdown time was recorded, in order to investigate the nanofluid performance for various concentration values under these effects. The prepared natural ester oil based nanofluids displayed better performance, by means of increased U50% than the base oil. For fault diagnosis and monitoring of dielectric liquid filled transformers, different graphical diagnostic methods, which are based on dissolved gas analysis (DGA) are widely used. The aforementioned graphical diagnostic methods mainly focus on three, four, five or seven gases. In this thesis, an alternative approach is proposed by means of a two-shapes graphical method in order to discriminate between different fault types guided from the acetylene percentage derived from the DGA analysis. Low thermal faults are studied through the first shape (square), while electrical discharge faults are depicted in the second shape (pentagon). The accuracy of the proposed method is calculated based on 375 DGA data; the overall obtained accuracy is 78.93%.	en
heal.advisorName	Gonos, Ioannis
heal.committeeMemberName	Kyritsis, Apostolos
heal.committeeMemberName	Christoforou, Evangelos
heal.committeeMemberName	Gonos, Ioannis
heal.committeeMemberName	PYRGIOTI, ELEFTHERIA
heal.committeeMemberName	TOPALIS, FRANGISKOS
heal.committeeMemberName	Mikropoulos, Pantelis
heal.committeeMemberName	Tsovilis, Thomas
heal.academicPublisher	Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών	el
heal.academicPublisherID	ntua
heal.numberOfPages	152
heal.fullTextAvailability	false