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Reliability Based Genetic Algorithm Applied to Allocation of Fiber Optics Links for Power Grid Automation

Author

Listed:
  • Henrique Pires Corrêa

    (Information and Communication Engineering Group—INCOMM, School of Electrical, Mechanical and Computer Engineering, Federal University of Goiás, Goiânia 74605-010, Brazil)

  • Rafael Ribeiro de Carvalho Vaz

    (Information and Communication Engineering Group—INCOMM, School of Electrical, Mechanical and Computer Engineering, Federal University of Goiás, Goiânia 74605-010, Brazil)

  • Flávio Henrique Teles Vieira

    (Information and Communication Engineering Group—INCOMM, School of Electrical, Mechanical and Computer Engineering, Federal University of Goiás, Goiânia 74605-010, Brazil)

  • Sérgio Granato de Araújo

    (Information and Communication Engineering Group—INCOMM, School of Electrical, Mechanical and Computer Engineering, Federal University of Goiás, Goiânia 74605-010, Brazil)

Abstract

In this work, we address the problem of allocating optical links for connecting automatic circuit breakers in a utility power grid. We consider the application of multi-objective optimization for improving costs and power network reliability. To this end, we propose a novel heuristic for attributing reliability values to the optical links, which makes the optimization converge to network topologies in which nodes with higher power outage indexes receive greater communication resources. We combine our heuristic with a genetic algorithm in order to solve the optimization problem. In order to validate the proposed method, simulations are carried out with real data from the local utility. The obtained results validate the allocation heuristic and show that the proposed algorithm outperforms gradient descent optimization in terms of the provided Pareto front.

Suggested Citation

  • Henrique Pires Corrêa & Rafael Ribeiro de Carvalho Vaz & Flávio Henrique Teles Vieira & Sérgio Granato de Araújo, 2019. "Reliability Based Genetic Algorithm Applied to Allocation of Fiber Optics Links for Power Grid Automation," Energies, MDPI, vol. 12(11), pages 1-26, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2039-:d:234900
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    References listed on IDEAS

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    1. Xuebing Chen & Lu Sun & Tengpeng Chen & Yuhao Sun & Rusli & King Jet Tseng & Keck Voon Ling & Weng Khuen Ho & Gehan A. J. Amaratunga, 2019. "Full Coverage of Optimal Phasor Measurement Unit Placement Solutions in Distribution Systems Using Integer Linear Programming," Energies, MDPI, vol. 12(8), pages 1-19, April.
    2. Zhi Wu & Xiao Du & Wei Gu & Ping Ling & Jinsong Liu & Chen Fang, 2018. "Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks," Energies, MDPI, vol. 11(7), pages 1-19, July.
    3. Li, Yang & Li, Yahui & Li, Guoqing & Zhao, Dongbo & Chen, Chen, 2018. "Two-stage multi-objective OPF for AC/DC grids with VSC-HVDC: Incorporating decisions analysis into optimization process," Energy, Elsevier, vol. 147(C), pages 286-296.
    4. Li, Yang & Feng, Bo & Li, Guoqing & Qi, Junjian & Zhao, Dongbo & Mu, Yunfei, 2018. "Optimal distributed generation planning in active distribution networks considering integration of energy storage," Applied Energy, Elsevier, vol. 210(C), pages 1073-1081.
    5. Md Shafiullah & M. A. Abido & Md Ismail Hossain & A. H. Mantawy, 2018. "An Improved OPP Problem Formulation for Distribution Grid Observability," Energies, MDPI, vol. 11(11), pages 1-16, November.
    6. Li, Yang & Wang, Jinlong & Zhao, Dongbo & Li, Guoqing & Chen, Chen, 2018. "A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making," Energy, Elsevier, vol. 162(C), pages 237-254.
    7. Dariush Khezrimotlagh & Yao Chen, 2018. "The Optimization Approach," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 107-134, Springer.
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