IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i6p1607-d214572.html
   My bibliography  Save this article

Optimal Routing an Ungrounded Electrical Distribution System Based on Heuristic Method with Micro Grids Integration

Author

Listed:
  • Wilson Pavón

    (Department of Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170146, Ecuador)

  • Esteban Inga

    (Department of Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170146, Ecuador)

  • Silvio Simani

    (Department of Telecommunications, Università degli Studi di Ferrara, 050031 Ferrara, Italy)

Abstract

This paper proposes a three-layer model to find the optimal routing of an underground electrical distribution system, employing the PRIM algorithm as a graph search heuristic. In the algorithm, the first layer handles transformer allocation and medium voltage network routing, the second layer deploys the low voltage network routing and transformer sizing, while the third presents a method to allocate distributed energy resources in an electric distribution system. The proposed algorithm routes an electrical distribution network in a georeferenced area, taking into account the characteristics of the terrain, such as streets or intersections, and scenarios without squared streets. Moreover, the algorithm copes with scalability characteristics, allowing the addition of loads with time. The model analysis discovers that the algorithm reaches a node connectivity of 100%, satisfies the planned distance constraints, and accomplishes the optimal solution of underground routing in a distribution electrical network applied in a georeferenced area. Simulating the electrical distribution network tests that the voltage drop is less than 2% in the farthest node.

Suggested Citation

  • Wilson Pavón & Esteban Inga & Silvio Simani, 2019. "Optimal Routing an Ungrounded Electrical Distribution System Based on Heuristic Method with Micro Grids Integration," Sustainability, MDPI, vol. 11(6), pages 1-18, March.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:6:p:1607-:d:214572
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/6/1607/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/6/1607/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Abeysinghe, Sathsara & Wu, Jianzhong & Sooriyabandara, Mahesh & Abeysekera, Muditha & Xu, Tao & Wang, Chengshan, 2018. "Topological properties of medium voltage electricity distribution networks," Applied Energy, Elsevier, vol. 210(C), pages 1101-1112.
    2. Freitas, Sara & Santos, Teresa & Brito, Miguel C., 2018. "Impact of large scale PV deployment in the sizing of urban distribution transformers," Renewable Energy, Elsevier, vol. 119(C), pages 767-776.
    3. Zubo, Rana.H.A. & Mokryani, Geev & Rajamani, Haile-Selassie & Aghaei, Jamshid & Niknam, Taher & Pillai, Prashant, 2017. "Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1177-1198.
    4. Alhamwi, Alaa & Medjroubi, Wided & Vogt, Thomas & Agert, Carsten, 2017. "GIS-based urban energy systems models and tools: Introducing a model for the optimisation of flexibilisation technologies in urban areas," Applied Energy, Elsevier, vol. 191(C), pages 1-9.
    5. Aghaei, Jamshid & Muttaqi, Kashem M. & Azizivahed, Ali & Gitizadeh, Mohsen, 2014. "Distribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm," Energy, Elsevier, vol. 65(C), pages 398-411.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    3. Marvin Lema & Wilson Pavon & Leony Ortiz & Ama Baduba Asiedu-Asante & Silvio Simani, 2022. "Controller Coordination Strategy for DC Microgrid Using Distributed Predictive Control Improving Voltage Stability," Energies, MDPI, vol. 15(15), pages 1-15, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Lixiao & Jing, Z.X. & Zheng, J.H. & Wu, Q.H. & Wei, Feng, 2018. "Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals," Energy, Elsevier, vol. 158(C), pages 607-622.
    2. Nutkiewicz, Alex & Yang, Zheng & Jain, Rishee K., 2018. "Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow," Applied Energy, Elsevier, vol. 225(C), pages 1176-1189.
    3. Michiel Fremouw & Annamaria Bagaini & Paolo De Pascali, 2020. "Energy Potential Mapping: Open Data in Support of Urban Transition Planning," Energies, MDPI, vol. 13(5), pages 1-15, March.
    4. Luigi Bottecchia & Pietro Lubello & Pietro Zambelli & Carlo Carcasci & Lukas Kranzl, 2021. "The Potential of Simulating Energy Systems: The Multi Energy Systems Simulator Model," Energies, MDPI, vol. 14(18), pages 1-27, September.
    5. Alhamwi, Alaa & Medjroubi, Wided & Vogt, Thomas & Agert, Carsten, 2018. "Modelling urban energy requirements using open source data and models," Applied Energy, Elsevier, vol. 231(C), pages 1100-1108.
    6. Esmaeeli, M. & Kazemi, A. & Shayanfar, H.A. & Haghifam, M.-R., 2015. "Multistage distribution substations planning considering reliability and growth of energy demand," Energy, Elsevier, vol. 84(C), pages 357-364.
    7. Vaccariello, Enrico & Leone, Pierluigi & Canavero, Flavio G. & Stievano, Igor S., 2021. "Topological modelling of gas networks for co-simulation applications in multi-energy systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 183(C), pages 244-253.
    8. Patrick Sunday Onen & Geev Mokryani & Rana H. A. Zubo, 2022. "Planning of Multi-Vector Energy Systems with High Penetration of Renewable Energy Source: A Comprehensive Review," Energies, MDPI, vol. 15(15), pages 1-25, August.
    9. Guglielmina Mutani & Valeria Todeschi & Simone Beltramino, 2020. "Energy Consumption Models at Urban Scale to Measure Energy Resilience," Sustainability, MDPI, vol. 12(14), pages 1-31, July.
    10. Nikolas Schöne & Boris Heinz, 2023. "Semi-Systematic Literature Review on the Contribution of Hydrogen to Universal Access to Energy in the Rationale of Sustainable Development Goal Target 7.1," Energies, MDPI, vol. 16(4), pages 1-42, February.
    11. Jolando M. Kisse & Martin Braun & Simon Letzgus & Tanja M. Kneiske, 2020. "A GIS-Based Planning Approach for Urban Power and Natural Gas Distribution Grids with Different Heat Pump Scenarios," Energies, MDPI, vol. 13(16), pages 1-31, August.
    12. Mastrucci, Alessio & Marvuglia, Antonino & Benetto, Enrico & Leopold, Ulrich, 2020. "A spatio-temporal life cycle assessment framework for building renovation scenarios at the urban scale," Renewable and Sustainable Energy Reviews, Elsevier, vol. 126(C).
    13. Alhamwi, Alaa & Medjroubi, Wided & Vogt, Thomas & Agert, Carsten, 2019. "Development of a GIS-based platform for the allocation and optimisation of distributed storage in urban energy systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    14. Retière, N. & Sidqi, Y. & Frankhauser, P., 2022. "A steady-state analysis of distribution networks by diffusion-limited-aggregation and multifractal geometry," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    15. Michele Pezzagno & Anna Richiedei & Maurizio Tira, 2020. "Spatial Planning Policy for Sustainability: Analysis Connecting Land Use and GHG Emission in Rural Areas," Sustainability, MDPI, vol. 12(3), pages 1-15, January.
    16. Prades-Gil, C. & Viana-Fons, J.D. & Masip, X. & Cazorla-Marín, A. & Gómez-Navarro, T., 2023. "An agile heating and cooling energy demand model for residential buildings. Case study in a mediterranean city residential sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    17. Gianpiero Colangelo & Gianluigi Spirto & Marco Milanese & Arturo de Risi, 2021. "Progresses in Analytical Design of Distribution Grids and Energy Storage," Energies, MDPI, vol. 14(14), pages 1-43, July.
    18. Feng, Li & Liu, Jiajun & Lu, Haitao & Liu, Bingzhi & Chen, Yuning & Wu, Shenyu, 2022. "Robust operation of distribution network based on photovoltaic/wind energy resources in condition of COVID-19 pandemic considering deterministic and probabilistic approaches," Energy, Elsevier, vol. 261(PB).
    19. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    20. Gust, Gunther & Schlüter, Alexander & Feuerriegel, Stefan & Úbeda, Ignacio & Lee, Jonathan T. & Neumann, Dirk, 2024. "Designing electricity distribution networks: The impact of demand coincidence," European Journal of Operational Research, Elsevier, vol. 315(1), pages 271-288.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:6:p:1607-:d:214572. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.