Power loss minimization for transformers connected in parallel with taps based on power chargeability balance

ABSTRACT: In this paper, a model and solution approach for minimizing internal power losses inTransformers Connected in Parallel (TCP) with tap-changers is proposed. The model is basedon power chargeability balance and seeks to keep the load voltage within an admissible range.For achieving this, tap positions are adjusted in such a way that all TCP are set in similar/same powerchargeability. The main contribution of this paper is the inclusion of several construction features(rated voltage, rated power, voltage ratio, short-circuit impedance and tap steps) in the minimizationof power losses in TCP that are not included in previous works. A Genetic Algorithm (GA) is used forsolving the proposed model that is a system of nonlinear equations with discrete decision variables.The GA scans different sets for tap positions with the aim of balancing the power supplied by eachtransformer to the load. For this purpose, a fitness function is used for minimizing two conditions:The first condition consists on the mismatching between power chargeability for each transformerand a desired chargeability; and the second condition is the mismatching between the nominalload voltage and the load voltage obtained by changing the tap positions. The proposed method isgeneralized for any given number of TCP and was implemented for three TCP, demonstrating thatthe power losses are minimized and the load voltage remains within an admissible range.

• Autores: Jaramillo Duque, Alvaro; Muñoz Galeano, Nicolás; Ortiz Castrillón, José Robinson; López Lezama, Jesús María; Albarracín Sánchez, Ricardo
• Tipo de recurso: Article of investigation
• Fecha de publicación: 2018
• Institución: Universidad de Antioquia
• Repositorio: Repositorio UdeA
• Idioma: eng
• OAI Identifier: oai:bibliotecadigital.udea.edu.co:10495/25082
• Acceso en línea: http://hdl.handle.net/10495/25082
• Palabra clave: Perdidas eléctricas; Electric losses; Sistemas de energía eléctrica; Electric power systems; Algoritmos genéticos; Genetic algorithms; Transformadores; Algoritmos genéticos
• Rights: openAccess
• License: http://creativecommons.org/licenses/by/2.5/co/