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A Decision-Making Tool for Electric Distribution Network Planning Based on Heuristics and Georeferenced Data

Author

Listed:
  • Alex Valenzuela

    (Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170146, Ecuador
    These authors contributed equally to this work.)

  • Iván Montalvo

    (Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170146, Ecuador
    These authors contributed equally to this work.)

  • Esteban Inga

    (Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170146, Ecuador
    These authors contributed equally to this work.)

Abstract

Designing and planning of electrical distribution systems is a task that design engineers perform during their daily activities. These designs, which are completed manually, are made according to the expertise of the designer; as a consequence, the obtained product varies depending on the person in charge of executing the layout, highlighting the fact that those designs are susceptible to involuntary human mistakes resulting in no optimal solutions and high cost consequences. The work presented below explains the implementation of an intelligent decision tool that allows the design of network distribution system planning considering the current electrical company standards, in order to have a clear and quick initial overview of the configuration that an electricity network should have in response to an increasing demand, considering not only the coverage and capacity of the transformers but also voltage drop along the conductors, which must not exceed 3% of the nominal value. The objective of this design tool is that it can be applicable in real scenarios; for this reason, the routing of the conductors and the location of the transformers are based on a georeferenced map. It is important to mention that the optimization problem is focused on minimizing the amount of transformers and at the same time ensuring a total coverge of 100% end users connected to the grid. This tool would be very useful in the educational and practical fields, since private and public electricity companies could use it to obtain a quick and efficient base product on which they could start to develop expansion and planning of distribution networks. The concept and development of such a tool is the subject of this paper.

Suggested Citation

  • Alex Valenzuela & Iván Montalvo & Esteban Inga, 2019. "A Decision-Making Tool for Electric Distribution Network Planning Based on Heuristics and Georeferenced Data," Energies, MDPI, vol. 12(21), pages 1-18, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:21:p:4065-:d:280117
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    References listed on IDEAS

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    Cited by:

    1. Edy Quintana & Esteban Inga, 2022. "Optimal Reconfiguration of Electrical Distribution System Using Heuristic Methods with Geopositioning Constraints," Energies, MDPI, vol. 15(15), pages 1-20, July.
    2. Ameling, Justus & Gust, Gunther, 2024. "Automated feeder routing for underground electricity distribution networks based on aerial images," European Journal of Operational Research, Elsevier, vol. 318(2), pages 629-641.
    3. Alex Valenzuela & Silvio Simani & Esteban Inga, 2021. "Automatic Overcurrent Protection Coordination after Distribution Network Reconfiguration Based on Peer-To-Peer Communication," Energies, MDPI, vol. 14(11), pages 1-22, June.
    4. Alex Guamán & Alex Valenzuela, 2021. "Distribution Network Reconfiguration Applied to Multiple Faulty Branches Based on Spanning Tree and Genetic Algorithms," Energies, MDPI, vol. 14(20), pages 1-16, October.

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