|Full text PDF:||https://spectrum.library.concordia.ca/982361/1/Akiror_PhD_S2017.pdf;Akiror,JemimahConnie
Accurate estimation of core losses in hydro generators is invaluable as it has implications of monetary value to both machine designers and utilities. For machine designers to meet the maximum acceptable total loss design targets, accurate loss estimation techniques are important to avoid the penalty of the extra losses generated. On the other hand, increase in the demand for electricity requires utilities to increase the output of their hydro generators as an alternative to building new stations, which is a more cost efficient option. Therefore, accurate prediction of core losses and their distribution, as part of the uprate studies, is key for any proposed uprate to determine the machines hot spots and core capability. This will permit the increase in machine rating without compromising its life time.This study is towards an accurate quantification of core losses and their distribution in hydro generators stators for uprate studies. The emphasis is on understanding the distribution of rotational flux in the generator stator core, rotational core loss measurements in lamination steel, and core loss estimation including both the rotational and non-sinusoidal flux density components. This entails 2D electromagnetic finite element modelling, validation and simulation of hydro generators, which are subsequently used for the analysis.The distribution of rotational flux was found to be dependent on the stator dimensions and material BH curve operating point. Moreover, the associated rotational core losses resulted in a non-uniform distribution of losses in the stator, with higher localized losses at the back of the tooth. This new distribution of core losses is important in the thermal modelling to determine the distribution of hotspots in the machine.In this work, the numerical analysis provides an understanding of what is happening in the machine beyond the current measurement capability in the real machine. The experimental measurements performed also support the numerical results in the loss estimation.