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Grounding System Cost Analysis Using Optimization Algorithms

Author

Listed:
  • Jau-Woei Perng

    (Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan)

  • Yi-Chang Kuo

    (Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan
    Taiwan Power Company Southern Region Construction Office, Kaohsiung 81166, Taiwan)

  • Shih-Pin Lu

    (Taiwan Power Company Southern Region Construction Office, Kaohsiung 81166, Taiwan)

Abstract

In this study, the concept of grounding systems is related to the voltage tolerance of the human body (human body voltage tolerance safety value). The maximum touch voltage target and grounding resistance values are calculated in order to compute the grounding resistance on the basis of system data. Typically, the grounding resistance value is inversely proportional to the laying depth of the grounding grid and the number of grounded copper rods. In other words, to improve the performance of the grounding system, either the layering depth of the grounding grid or the number of grounded copper rods should be increased, or both of them should be simultaneously increased. Better grounding resistance values result in increased engineering costs. There are numerous solutions for the grounding target value. Grounding systems are designed to find the combination of the layering depth of the grounding grid and the number of grounded copper rods by considering both cost and performance. In this study, we used a fuzzy algorithm on the genetic algorithm (GA), multi-objective particle swarm optimization (MOPSO) algorithm, Bees, IEEE Std. 80-2000, and Schwarz’s equation based on a power company’s substation grounding system data to optimize the grounding resistance performance and reduce system costs. The MOPSO algorithm returned optimal results. The radial basis function (RBF) neural network curve is obtained by the MOPSO algorithm with three variables (i.e., number of grounded copper rods, grounding resistance value, and grounding grid laying depth), and the simulation results of the electrical transient analysis program (ETAP) system are verified. This could be a future reference for substation designers and architects.

Suggested Citation

  • Jau-Woei Perng & Yi-Chang Kuo & Shih-Pin Lu, 2018. "Grounding System Cost Analysis Using Optimization Algorithms," Energies, MDPI, vol. 11(12), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3484-:d:190384
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    Citations

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    Cited by:

    1. Krzysztof Lowczowski & Jozef Lorenc & Andrzej Tomczewski & Zbigniew Nadolny & Jozef Zawodniak, 2020. "Monitoring of MV Cable Screens, Cable Joints and Earthing Systems Using Cable Screen Current Measurements," Energies, MDPI, vol. 13(13), pages 1-28, July.
    2. Navinesshani Permal & Miszaina Osman & Azrul Mohd Ariffin & Navaamsini Boopalan & Mohd Zainal Abidin Ab Kadir, 2021. "Optimization of substation grounding grid design for horizontal and vertical multilayer and uniform soil condition using Simulated Annealing method," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-16, September.
    3. Vaclav Vycital & Michal Ptacek & David Topolanek & Petr Toman, 2019. "On Minimisation of Earthing System Touch Voltages," Energies, MDPI, vol. 12(20), pages 1-15, October.
    4. Francisco G. Montoya & Raúl Baños & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Optimization Methods Applied to Power Systems," Energies, MDPI, vol. 12(12), pages 1-8, June.
    5. Jau-Woei Perng & Yi-Chang Kuo & Yao-Tsung Chang & Hsi-Hsiang Chang, 2020. "Power Substation Construction and Ventilation System Co-Designed Using Particle Swarm Optimization," Energies, MDPI, vol. 13(9), pages 1-27, May.

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