11:00
Session 1: Rotary Machine Optimization
Chair: Guillaume Crevecoeur
11:00
20 mins
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MODELING AND SIZING BY OPTIMIZATION OF A BRUSHLESS DOUBLY-FED RELUCTANCE MACHINE
Tiago Staudt, Laurent Gerbaud, Frédéric Wurtz, Nelson Jhoe Batistela, Patrick Kuo Peng
Abstract: The paper proposes an optimization approach to address the modeling and sizing complexities of Brushless Doubly-Fed Reluctances Machines. A semi-analytical model and a reluctance network model are coupled to a deterministic optimization algorithm where several inputs and outputs parameters can be constrained to solve sizing equations iteratively by maximizing or minimizing an objective function. A Pareto Front strategy is used to illustrate the models capabilities, highlighting the trade-offs on the design of this kind of electrical machines. The optimization model provides fast results to define a first design, reducing the number of unknown parameters of early development stages. This saves computation time and computer resources in the design process compared to Finite Element Analysis.
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11:20
20 mins
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OPTIMIZATION AND COMPARISON OF SUPERCONDUCTING GENERATOR TOPOLOGIES FOR A 10 MW WIND TURBINE APPLICATION
Dong Liu, Henk Polinder, Asger B. Abrahamsen, Ewoud Stehouwer, Ben Hendriks, Niklas Magnusson
Abstract: A direct-drive superconducting generator (DDSCG) is proposed for 10 MW wind turbines in the INNWIND.EU project. To fit the generator into the "king-pin" conceptual nacelle design, the generator structure with inner stationary superconducting (SC) field winding and outer rotating copper armature winding is investigated in the first research phase. This paper presents a method using 2D finite element (FE) methods to minimize the active material cost of the "king-pin" fitted DDSCG by optimizing the geometrical variables. By implementing this method, three typical superconducting generator topologies are compared in terms of the active material cost and mass, the synchronous reactance and the phase resistance. The optimization method and the comparison results provide the DDSCG designers with a guideline for selecting a suitable machine topology.
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