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Enhanced Artificial Immune Systems and Fuzzy Logic for Active Distribution Systems Reconfiguration

Author

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  • Guillermo Alonso

    (Facultad de Ingeniería, Universidad Nacional de Itapúa, Encarnación 070102, Paraguay
    Institute of Electrical Systems and Energy, Universidade Federal de Itajubá, Itajubá 37500-903, Brazil)

  • Ricardo F. Alonso

    (Facultad de Ingeniería, Universidad Nacional de Itapúa, Encarnación 070102, Paraguay
    Institute of Electrical Systems and Energy, Universidade Federal de Itajubá, Itajubá 37500-903, Brazil)

  • Antonio Carlos Zambroni Zambroni De Souza

    (Institute of Electrical Systems and Energy, Universidade Federal de Itajubá, Itajubá 37500-903, Brazil)

  • Walmir Freitas

    (Department of Systems and Energy, UNICAMP—University of Campinas, Campinas 13100-484, Brazil)

Abstract

Nowadays, the high penetration of automation on smart grids challenges electricity companies in providing an efficient distribution networks operation. In this sense, distribution system reconfiguration (DSR) plays an important role since it may help solve real-time problems. This paper proposes a methodology to solve the DSR problem using artificial immune systems (AIS) based on a new, efficient, and robust approach. This new methodology, called Enhanced Artificial Immune Systems (EAIS), uses the values of the currents in wires for intelligent mutations. The problem is accomplished by a multi-objective optimization with fuzzy variables, minimizing power losses, voltage deviation, and feeders load balancing. A comparison with other DSR solution methods is presented. The method is compared with two other previously proposed methods with the help of the 33-bus, 84-bus, and 136-bus distribution systems. Different scenarios are analyzed, including the optimal location of the Distributed Generation (DG). The results show the applicability of the proposed algorithm for the simultaneous solution of DSR and location or dispatch of DGs.

Suggested Citation

  • Guillermo Alonso & Ricardo F. Alonso & Antonio Carlos Zambroni Zambroni De Souza & Walmir Freitas, 2022. "Enhanced Artificial Immune Systems and Fuzzy Logic for Active Distribution Systems Reconfiguration," Energies, MDPI, vol. 15(24), pages 1-18, December.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9419-:d:1001837
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    References listed on IDEAS

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    1. Despoina Kothona & Aggelos S. Bouhouras, 2022. "A Two-Stage EV Charging Planning and Network Reconfiguration Methodology towards Power Loss Minimization in Low and Medium Voltage Distribution Networks," Energies, MDPI, vol. 15(10), pages 1-17, May.
    2. Luis A. Gallego Pareja & Jesús M. López-Lezama & Oscar Gómez Carmona, 2022. "A Mixed-Integer Linear Programming Model for the Simultaneous Optimal Distribution Network Reconfiguration and Optimal Placement of Distributed Generation," Energies, MDPI, vol. 15(9), pages 1-26, April.
    3. Yang, Bo & Zeng, Chunyuan & Li, Danyang & Guo, Zhengxun & Chen, Yijun & Shu, Hongchun & Cao, Pulin & Li, Zilin, 2022. "Improved immune genetic algorithm based TEG system reconfiguration under non-uniform temperature distribution," Applied Energy, Elsevier, vol. 325(C).
    4. Liudmyla Davydenko & Nina Davydenko & Andrii Bosak & Alla Bosak & Agnieszka Deja & Tygran Dzhuguryan, 2022. "Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging," Energies, MDPI, vol. 15(10), pages 1-27, May.
    5. Mariana Durango-Flórez & Daniel González-Montoya & Luz Adriana Trejos-Grisales & Carlos Andres Ramos-Paja, 2022. "PV Array Reconfiguration Based on Genetic Algorithm for Maximum Power Extraction and Energy Impact Analysis," Sustainability, MDPI, vol. 14(7), pages 1-14, March.
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    Cited by:

    1. Matheus Diniz Gonçalves-Leite & Edgar Manuel Carreño-Franco & Jesús M. López-Lezama, 2023. "Impact of Distributed Generation on the Effectiveness of Electric Distribution System Reconfiguration," Energies, MDPI, vol. 16(17), pages 1-20, August.
    2. Elham Mahdavi & Seifollah Asadpour & Leonardo H. Macedo & Rubén Romero, 2023. "Reconfiguration of Distribution Networks with Simultaneous Allocation of Distributed Generation Using the Whale Optimization Algorithm," Energies, MDPI, vol. 16(12), pages 1-19, June.
    3. Ezequiel C. Pereira & Carlos H. N. R. Barbosa & João A. Vasconcelos, 2023. "Distribution Network Reconfiguration Using Iterative Branch Exchange and Clustering Technique," Energies, MDPI, vol. 16(5), pages 1-20, March.

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