Optimal Design of Winding Transposition of Power Transformer Using Adaptive Co-Kriging Surrogate Model

초록

An adaptive co-Kriging surrogate model, which is numerically more efficient and accurate than a conventional co-Kriging model, is developed, and incorporated into a heuristic optimization algorithm to be applied to the optimal design of transposition of power transformer windings. The sampling data of the proposed adaptive co-Kriging consist of a few expensive and many cheap data to save the computational efforts while increasing modeling accuracy. A criterion on the minimum number of expensive sampling data is investigated to achieve a desired fitting accuracy.

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