Transients have proven to be a specially demanding operation mode for rotor cages in induction motors. The combination of thermal and mechanical stresses causes damage in weak points of the secondary circuit of these machines. A 3D multiphysics computation may shed some light into the conditions under faults such as broken bars develop whilst taking into account phenomena as interbar currents. With the aim of reducing the computational cost involved, this work carries out a 3D simulation of just the rotor during the first 2.5 cycles after a direct-on-line connection, being the tangential component of the magnetic vector potential mapped on its iron surface from the results obtained by 2D locked rotor FE simulation. The results provide an insight into the skin effect and mechanical loads in the cage, a magnetic coupling between the end ring and the shaft as well as the limitations of the weakly coupled magnetoelastic analysis.
Accurate understanding of losses and frequency‐dependent winding parameters have been an important aspect for selecting the right configuration of stranded conductors in power‐electronic inductors. An approach for modelling frequency‐dependent parameters of a winding with twisted wire bundles in toroidal inductors using a multi‐axial sliced finite element (FE) modelling approach is presented here. A 2D magnetodynamic FE problem is solved in several axial and radial slices of the inductor, accounting for the twisted conductor bundles by varying the conductor positions in the slices. Case studies are presented for different levels and pitch lengths of twisting. The approach is validated against 3D FE simulations in the case of 3–4 parallel strands and against measurements in the case of 75, 105 and 125 strands, which would be impossibly heavy for conventional 3D FE tools. The results provide insight into the effect of strand grouping, twisting levels and twisting pitch on the frequency‐dependent resistance of windings.
The reliability of power system under fault susceptible environment has become major challenge for the power sector units. The injection of renewable power source has increased the complexity for distribution system and to deal with massive network, evolution of smart-grid has been enforced, which works in an automated fashion to improve overall reliability, efficiency and quality of the system. Proactive Self-healing is a critical feature of smart-grid. This paper tries to explain the concept sensing the occurrence of fault beforehand and providing possible solution for self-healing in smart grid. The fundamental base for incorporating afore discussed technology viz. understanding nature of fault, sources of fault and implementation of effective measuring techniques are enumerated in paper briefly. Support required in terms of technology is reviewed towards the end followed by a case study of practical implementation of self-healing control in a distribution system.
Computer simulations are a powerful tool to support the design and development of electrical components and equipment. However, simulations are configured by a user, thus inevitably incorporating the human factor and potentially leading to divergence in results. To assess this degree of variance and thus the role of the user, 10 participants were asked to simulate the same medium voltage porcelain pin insulator using FEM software. Boundary conditions and materials were fixed. However, participants were able to define the geometry and details of the pin insulator by any means at their disposal. The varying skills of the participants resulted in geometries ranging from highly detailed complex models to rougher approximations. A CAD model provided by the pin insulator manufacturer is used as a reference. To quantify the extent of divergence, electric field intensity values in selected critical areas of the geometry are compared. This study presents the influence of the human factor and investigates the requirements for reliable simulation, i.e., how detailed does a model have to be to produce reliable information. The findings of this study can be used to save time and focus efforts on pertinent aspects in simulations.
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