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Recursive genetic algorithm-finite element method technique for the solution of transformer manufacturing cost minimisation problem

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1 Author(s)
Georgilakis, P.S. ; Dept. of Production Eng. & Manage., Tech. Univ. of Crete, Chania, Greece

The transformer manufacturing cost minimisation (TMCM), also known as transformer design optimisation, is a complex constrained mixed-integer non-linear programming problem with discontinuous objective function. This paper proposes an innovative method combining genetic algorithm (GA) and finite element method (FEM) for the solution of TMCM problem. The main contributions of the proposed method are: (a) introduction of an innovative recursive GA with a novel external elitism strategy associated with variable crossover and mutation rates resulting in an improved GA, (b) adoption of two particular finite element models of increased accuracy and high computational speed for the validation of the optimal design by computing the no-load loss and impedance and (c) combination of the innovative recursive GA with the two particular finite element models resulting in a proposed GA-FEM model that finds the global optimum, as concluded after several tests on actual transformer designs, while other existing methods provided suboptimal solutions that are 3.1-5.8% more expensive than the optimal solution.

Published in:

Electric Power Applications, IET  (Volume:3 ,  Issue: 6 )