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The Sensitivity Analysis Using Adjoint Method In Numerical Modeling of Electric Potential Distribution of the Transmission Lines
  • +2
  • Andre Paganotti,
  • Rodney Saldanha,
  • Adriano Chaves Lisboa,
  • Márcio Matias Afonso,
  • B. A. M. DUANE
Andre Paganotti
Centro Federal de Educacao Tecnologica de Minas Gerais

Corresponding Author:paganotti@cefetmg.br

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Rodney Saldanha
Universidade Federal de Minas Gerais
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Adriano Chaves Lisboa
Universidade Federal de Minas Gerais
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Márcio Matias Afonso
Centro Federal de Educacao Tecnologica de Minas Gerais
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B. A. M. DUANE
Centro Federal de Educacao Tecnologica de Minas Gerais
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Abstract

This paper proposes a new methodology for sensitivity analysis evaluation, fast and with high precision of the electric potential distribution near the transmission lines (TL’s). The TL is modeled by the finite element method and the sensitivity of the cable positions is obtained using the adjoint method. The sensitivity of the objective function during the optimization process by using methods based on gradient information is obtained by using the adjoint method. The exact sensitivity obtained by the adjoint method concerning the numeric model of the TL’s results in new geometries of the bundles conductors with high surge impedance loading. These geometries are not possible to get using analytic models. The sensitivities of a large number of conductors by phase are obtained with high precision and very low computational cost using adjoint sensitivities, which are independent of the number of design variables. The central finite difference (CFD) method is used to calculate the sensitivities and to validate the adjoint method. With this methodology, the FEM model of the TL can be used during the optimization process without compromising the required computational processing time.
Submitted to International Journal of Numerical Modelling: Electronic Networks, Devices and Fields
04 Apr 2024Review(s) Completed, Editorial Evaluation Pending
04 Apr 2024Editorial Decision: Revise Minor
18 Jun 2024Editorial Decision: Accept