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Power Loss Minimization for Transformers Connected in Parallel with Taps Based on Power Chargeability Balance

Author

Listed:
  • Álvaro Jaramillo-Duque

    (Research Group in Efficient Energy Management (GIMEL), Universidad de Antioquia, Calle 67 No. 53-108, 050010 Medellín, Colombia)

  • Nicolás Muñoz-Galeano

    (Research Group in Efficient Energy Management (GIMEL), Universidad de Antioquia, Calle 67 No. 53-108, 050010 Medellín, Colombia)

  • José R. Ortiz-Castrillón

    (Research Group in Efficient Energy Management (GIMEL), Universidad de Antioquia, Calle 67 No. 53-108, 050010 Medellín, Colombia)

  • Jesús M. López-Lezama

    (Research Group in Efficient Energy Management (GIMEL), Universidad de Antioquia, Calle 67 No. 53-108, 050010 Medellín, Colombia)

  • Ricardo Albarracín-Sánchez

    (Departamento de Ingeniería Eléctrica, Electrónica, Automática y Física Aplicada, Escuela Técnica Superior de Ingeniería y Diseño Industrial, Universidad Politécnica de Madrid, Ronda de Valencia 3, 28012 Madrid, Spain)

Abstract

In this paper, a model and solution approach for minimizing internal power losses in Transformers Connected in Parallel (TCP) with tap-changers is proposed. The model is based on 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 power chargeability. 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 minimization of power losses in TCP that are not included in previous works. A Genetic Algorithm (GA) is used for solving 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 each transformer 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 transformer and a desired chargeability; and the second condition is the mismatching between the nominal load voltage and the load voltage obtained by changing the tap positions. The proposed method is generalized for any given number of TCP and was implemented for three TCP, demonstrating that the power losses are minimized and the load voltage remains within an admissible range.

Suggested Citation

  • Álvaro Jaramillo-Duque & Nicolás Muñoz-Galeano & José R. Ortiz-Castrillón & Jesús M. López-Lezama & Ricardo Albarracín-Sánchez, 2018. "Power Loss Minimization for Transformers Connected in Parallel with Taps Based on Power Chargeability Balance," Energies, MDPI, vol. 11(2), pages 1-12, February.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:2:p:439-:d:132089
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    References listed on IDEAS

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    1. Stefan Tenbohlen & Sebastian Coenen & Mohammad Djamali & Andreas Müller & Mohammad Hamed Samimi & Martin Siegel, 2016. "Diagnostic Measurements for Power Transformers," Energies, MDPI, vol. 9(5), pages 1-25, May.
    2. Byung Eun Lee & Jung-Wook Park & Peter A. Crossley & Yong Cheol Kang, 2014. "Induced Voltages Ratio-Based Algorithm for Fault Detection, and Faulted Phase and Winding Identification of a Three-Winding Power Transformer," Energies, MDPI, vol. 7(9), pages 1-19, September.
    3. Radu Godina & Eduardo M. G. Rodrigues & João C. O. Matias & João P. S. Catalão, 2015. "Effect of Loads and Other Key Factors on Oil-Transformer Ageing: Sustainability Benefits and Challenges," Energies, MDPI, vol. 8(10), pages 1-40, October.
    4. Yiyi Zhang & Jiefeng Liu & Hanbo Zheng & Hua Wei & Ruijin Liao, 2017. "Study on Quantitative Correlations between the Ageing Condition of Transformer Cellulose Insulation and the Large Time Constant Obtained from the Extended Debye Model," Energies, MDPI, vol. 10(11), pages 1-17, November.
    5. Huan Xia & Huaixin Chen & Zhongping Yang & Fei Lin & Bin Wang, 2015. "Optimal Energy Management, Location and Size for Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm," Energies, MDPI, vol. 8(10), pages 1-23, October.
    6. Chen Wang & Jie Wu & Jianzhou Wang & Weigang Zhao, 2016. "Reliability Analysis and Overload Capability Assessment of Oil-Immersed Power Transformers," Energies, MDPI, vol. 9(1), pages 1-19, January.
    7. Sarimuthu, Charles R. & Ramachandaramurthy, Vigna K. & Agileswari, K.R. & Mokhlis, Hazlie, 2016. "A review on voltage control methods using on-load tap changer transformers for networks with renewable energy sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 1154-1161.
    8. Ehsan Gholamalizadeh & Man-Hoe Kim, 2016. "Multi-Objective Optimization of a Solar Chimney Power Plant with Inclined Collector Roof Using Genetic Algorithm," Energies, MDPI, vol. 9(11), pages 1-14, November.
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