Service Restoration in Distribution Networks by Optimal Scheduling of Repair Crew and Mobile Power Sources

Document Type : Research Article

Authors

Faculty of Electrical and Computer Engineering, University of Birjand, 97175 Birjand, Iran

Abstract

Power distribution utilities need to have an effective and suitable service restoration (SR) plan to reconnect customers quickly after power outages. This article presents a heuristic bi-stage SR algorithm that first re-energizes some of the loads fast by remote-controlled switches (RCSs) in the first stage and then continues to restore the rest of the network in the second stage with all possible switching actions using RCSs and manual switches (MSs). This study also includes finding the optimal Switching Sequences (SSs) and the estimated energy not supplied  (EENS) as an objective function. Moreover, the proposed method is more attractive and practical because it considers the time of occurrence of the failure and the daily load curve, the location of the load transfer capability, and the traffic conditions of the network. In this method, repair crew (RC) and mobile power sources (MPSs) are also important for the restoration process. The heuristic SR algorithm was tested on a standard IEEE 70-bus system in different scenarios. The results showed a significant difference in the solutions to the problem and the ENS in different scenarios. Lastly, it was concluded that this heuristic method would produce optimal, precise, and feasible solutions for SR in distribution networks.

Keywords

Main Subjects

References

[1] A. Coelho, A. Rodrigues, and M. Da Silva, "Distribution network reconfiguration with reliability constraints," in 2004 International Conference on Power System Technology, 2004. PowerCon 2004., 2004, vol. 2: IEEE, pp. 1600-1606.
[2]  A. Kavousi-Fard and T. Niknam, "Optimal distribution feeder reconfiguration for reliability improvement considering uncertainty," IEEE Transactions on Power Delivery, vol. 29, no. 3, pp. 1344-1353, 2014.
[3]  A. Zidan et al., "Fault detection, isolation, and service restoration in distribution systems: State-of-the-art and future trends," IEEE Transactions on Smart Grid, vol. 8, no. 5, pp. 2170-2185, 2017.
[4]  M. Khederzadeh and S. Zandi, "Enhancement of Distribution System Restoration Capability in Single/Multiple Faults by Using Microgrids as a Resiliency Resource," IEEE Systems Journal, 2019.
[5] S. A. Sedgh, M. Doostizadeh, F. Aminifar, and M. Shahidehpour, "Resilient-enhancing critical load restoration using mobile power sources with incomplete information," Sustainable Energy, Grids and Networks, vol. 26, p. 100418, 2021.
[6]  L. Yang, Y. Xu, H. Sun, M. Chow, and J. Zhou, "A multiagent system based optimal load restoration strategy in distribution systems," International Journal of Electrical Power & Energy Systems, vol. 124, p. 106314, 2021.
[7] K. Aoki, H. Kuwabara, T. Satoh, and M. Kanezashi, "Outage state optimal load allocation by automatic sectionalizing switches operation in distribution systems," IEEE Transactions on Power Delivery, vol. 2, no. 4, pp. 1177-1185, 1987.
[8] K. Aoki, T. Satoh, M. Itoh, H. Kuwabara, and M. Kanezashi, "Voltage crop constrained restoration of supply by switch operation in distribution systems," IEEE Transactions on power delivery, vol. 3, no. 3, pp. 1267-1274, 1988.
[9]  W. Luan, M. R. Irving, and J. S. Daniel, "Genetic algorithm for supply restoration and optimal load shedding in power system distribution networks," IEE Proceedings-Generation, Transmission and Distribution, vol. 149, no. 2, pp. 145-151, 2002.
[10]  S. Mohanram and T. Sudhakar, "Power system restoration using reverse delete algorithm implemented in FPGA," 2011.
[11] H. Xiaoyu, X. Mingchao, and H. Yinghui, "A service restoration method for active distribution network," Energy Procedia, vol. 61, pp. 339-344, 2014.
[12] E. G. Carrano, G. P. da Silva, E. P. Cardoso, and R. H. Takahashi, "Subpermutation-based evolutionary multiobjective algorithm for load restoration in power distribution networks," IEEE Transactions on evolutionary computation, vol. 20, no. 4, pp. 546-562, 2016.
[13] A. A. A. Zidan, "Reconfiguration and self-healing mechanisms in distribution systems with high distributed generation (DG) penetration," 2013.
[14]M. Gholami, J. Moshtagh, and L. Rashidi, "Service restoration for unbalanced distribution networks using a combination two heuristic methods," International Journal of Electrical Power & Energy Systems, vol. 67, pp. 222-229, 2015.
[15] X. Huang, Y. Yang, and G. A. Taylor, "Service restoration of distribution systems under distributed generation scenarios," CSEE Journal of Power and Energy Systems, vol. 2, no. 3, pp. 43-50, 2016.
[16]   C. Shen, P. Kaufmann, C. Hachmann, and M. Braun, "Three-stage power system restoration methodology considering renewable energies," International Journal of Electrical Power & Energy Systems, vol. 94, pp. 287-299, 2018.
[17]  R. Romero, J. F. Franco, F. B. Leão, M. J. Rider, and E. S. De Souza, "A new mathematical model for the restoration problem in balanced radial distribution systems," IEEE Transactions on Power Systems, vol. 31, no. 2, pp. 1259-1268, 2016.
[18]  M. H. Camillo et al., "Determination of switching sequence of service restoration in distribution systems: application and analysis on a real and large-scale radial system," in 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), 2016: IEEE, pp. 1-5.
[19] L. T. Marques, A. C. B. Delbem, and J. B. A. London, "Service restoration with prioritization of customers and switches and determination of switching sequence," IEEE Transactions on Smart Grid, vol. 9, no. 3, pp. 2359-2370, 2018.
[20]   F. Goulart, A. L. Maravilha, E. G. Carrano, and F. Campelo, "Permutation-based optimization for the load restoration problem with improved time estimation of maneuvers," International Journal of Electrical Power & Energy Systems, vol. 101, pp. 339-355, 2018.
[21] E. Shirazi and S. Jadid, "A multiagent design for self-healing in electric power distribution systems," Electric Power Systems Research, vol. 171, pp. 230-239, 2019.
[22] M. Rodríguez-Montañés, J. Rosendo-Macías, and A. Gómez-Expósito, "A systematic approach to service restoration in distribution networks," Electric Power Systems Research, vol. 189, p. 106539, 2020.
[23] T. Ding, Z. Wang, W. Jia, B. Chen, C. Chen, and M. Shahidehpour, "Multiperiod distribution system restoration with routing repair crews, mobile electric vehicles, and soft-open-point networked microgrids," IEEE Transactions on Smart Grid, vol. 11, no. 6, pp. 4795-4808, 2020.
[24] Q. Asadi, A. Amini, H. Falaghi and M. Ramezani, "A Heuristic Algorithm for Effective Service Restoration Toward Distribution Networks Automation," 2020 15th International Conference on Protection and Automation of Power Systems (IPAPS), Shiraz, Iran, 2020, pp. 19-24, doi: 10.1109/IPAPS52181.2020.9375560.
[25]  Q. Asadi, A. Ashoornezhad, H. Falaghi and M. Ramezani, "Optimal Service Restoration with Repair Crew and Mobile Power Source Scheduling: A Step Towards a Smarter Grid," 2023 8th International Conference on Technology and Energy Management (ICTEM), Mazandaran, Babol, Iran, Islamic Republic of, 2023, pp. 1-6, doi: 10.1109/ICTEM56862.2023.10084137.
[26]  Q. Asadi, A. Amini, H. Falaghi and M. Ramezani, "Effective Service Restoration in Electrical Distribution Networks Using a Bi-Stage Algorithm," 2021 29th Iranian Conference on Electrical Engineering (ICEE), Tehran, Iran, Islamic Republic of, 2021, pp. 198-203, doi: 10.1109/ICEE52715.2021.9544452.
[27]  Q. Asadi, A. Ashoornezhad, H. Falaghi and M. Ramezani, "Optimal Repair Crew and Mobile Power Source Scheduling for Load Restoration in Distribution Networks," 2023 International Conference on Protection and Automation of Power Systems (IPAPS), Tehran, Iran, Islamic Republic of, 2023, pp. 1-6, doi: 10.1109/IPAPS58344.2023.10123318.
[28]  D. Das, "A fuzzy multiobjective approach for network reconfiguration of distribution systems," IEEE transactions on power delivery, vol. 21, no. 1, pp. 202-209, 2006.
[29]  Q. Asadi, A. Ashoornezhad, H. Falaghi and M. Ramezani, "Optimal Placement of Maintenance Teams in Distribution Networks to Minimize Energy Not Supplied," 2022 30th International Conference on Electrical Engineering (ICEE), Tehran, Iran, Islamic Republic of, 2022, pp. 941-945, doi: 10.1109/ICEE55646.2022.9827158.
AUT Journal of Electrical Engineering
Volume 56, Issue 2
2024
Pages 269-290

Files

Share

How to cite

Statistics