ACTIVE DISTRIBUTION NETWORK FAULT LOCATION METHOD BASED ON IMPROVED MULTIVERSE ALGORITHM

Wei Du,∗ Guozhu Yang,∗ Maojie Tian,∗ Wei Hu,∗ and Chuntian Ma∗

References

  1. [1] X. Sun and J. Qiu, Two-stage volt/Var control in activedistribution networks with multi-agent deep reinforcementlearning method, IEEE Transactions on Smart Grid, 12(4),2021, 2903–2912.
  2. [2] M. Gholami, A. Abbaspour, S. Fattaheian-Dehkordi, M.Lehtonen, M. Moeini-Aghtaie, and M. Fotuhi, Optimalallocation of PMUs in active distribution network consideringreliability of state estimation results, IET Generation,Transmission & Distribution, 14(18), 2020, 3641–3651.
  3. [3] C. Zhou, G. Zou, L. Zang, and X. Du, Current differentialprotection for active distribution networks based on improvedfault data self-synchronization method, IEEE Transactions onSmart Grid, 13(1), 2022, 166–178.
  4. [4] D. A. Contreras and K. Rudion, Computing the feasibleoperating region of active distribution networks: Comparisonand validation of random sampling and optimal power flowbased methods. IET Generation, Transmission & Distribution,15(10), 2021, 1600–1612.
  5. [5] P. Yu, C. Wan, M. Sun, Y. Zhou, and Y. Song, Distributedvoltage control of active distribution networks with globalsensitivity, IEEE Transactions on Power Systems, 37(6), 2022,4214–4228.
  6. [6] X. Sun, J. Qiu, Y. Yi, and Y. Tao, Cost-effectivecoordinated voltage control in active distribution networkswith photovoltaics and mobile energy storage systems. IEEETransactions on Sustainable Energy, 13(1), 2021, 501–513.
  7. [7] U. Kamnarn, J. Yodwong, P. Piyawongwisal, P. Wutthiwai,A. Namin, P. Thounthong, and N. Takorabet, Design andsimulation of DC distributed power supply with power balance9control technique, International Journal of Power Electronicsand Drive Systems (IJPEDS), 13(1), 2022, 460.
  8. [8] R. Krishnathevar and E. E. Ngu, Generalized impedance-basedfault location for distribution systems, IEEE Transactions onPower Delivery, 27(1), 2012, 449–451.
  9. [9] R. Dashti, M. Daisy, H. R. Shaker, and M. Tahavori, Impedance-based fault location method for four-wire power distributionnetworks, IEEE Access, 6, 2018, 1342–1349.
  10. [10] A. Tashakkori, P. J. Wolfs, S. Islam, and A. Abu-Siada,Fault location on radial distribution networks via distributedsynchronized traveling wave detectors, IEEE Transactions onPower Delivery, 35(3), 2020, 1553–1562.
  11. [11] S. Shi, B. Zhu, A. Lei, and X. Dong, Fault location for radialdistribution network via topology and reclosure-generatingtraveling waves. IEEE Transactions on Smart Grid, 10(6),2019, 6404–6413.
  12. [12] G. G. Soma, Optimal sizing and placement of capacitor banksin distribution networks using a genetic algorithm, Electricity,2(2), 2021, 187–204.
  13. [13] X. Huang, Z. Xie, and X. Huang, Fault location of distributionnetwork base on improved cuckoo search algorithm. IEEEAccess, 8, 2019 ,2272–2283.
  14. [14] Y. Fu, M. Zhou, X. Guo, L. Qi, and K. Sedraoui, Multiverseoptimization algorithm for stochastic biobjective disassemblysequence planning subject to operation failures. IEEETransactions on Systems, Man, and Cybernetics: Systems,52(2), 2021, 1041–1051.
  15. [15] M. Azeroual, Y. Boujoudar, A. Aljarbouh, H. ElMoussaoui, and H. El Markhi, A multi-agent-basedfor fault location in distribution networks with windpower generator, Wind Engineering, 46(3), 2022,700–711.
  16. [16] E. Hosseini, K. Z. Ghafoor, A. Emrouznejad, A. S. Sadiq,and D. B. Rawat, Novel metaheuristic based on multiversetheory for optimization problems in emerging systems, AppliedIntelligence, 51(6), 2021, 3275–3292.
  17. [17] V. S. Murty, S. Jain, and A. Ojha, Application of linearswitched reluctance motor for sustainable electric vehicularsystem, International Journal of Power and Energy Systems,40(1), 2020.
  18. [18] S. Sarvari, N. F. Mohd. Sani, Z. Mohd Hanapi,and M. T. Abdullah, An efficient quantum multiverseoptimization algorithm for solving optimization problems,International Journal of Advances in Applied Sciences,9(1), 2020, 27.
  19. [19] J. Liu, H. Wang, X. Li, K. Chen, and C. Li, Roboticarm trajectory optimization based on multiverse algorithm.Mathematical Biosciences and Engineering, 20(2), 2023,2776–2792.
  20. [20] M. Otair, A. Alhmoud, H. Jia, M. Altalhi, A.MAziz.Hussein, and L. Abualigah, Optimized task scheduling incloud computing using improved multi-verse optimizer, ClusterComputing, 25(6), 2022, 4221–4232.
  21. [21] R. B. Hendi, S. J. Seyed-Sheneva, and M. Gandomkar, Electricaldistribution system reliability improvement by optimal place-ment of fault indicators using immune algorithm. InternationalJournal of Engineering Research and Applications, 2(2), 2012,1383–1390.
  22. [22] O. Kahouli, H. Alsaif, Y. Bouteraa, N. Ben Ali, andM. Chaabene, Power system reconfiguration in distributionnetwork for improving reliability using genetic algorithm andparticle swarm optimization, Applied Sciences, 11(7), 2021,3092.
  23. [23] J. Wen, L. Qu Xing, S. Lin, and X. Qiankang. A novel faultlocation method for the active distribution network based ondynamic quantum genetic algorithm. Electrical Engineering,106, 2024, 4719–4735.
  24. [24] M. N. Azari, H. A. Khazaeli, and M. Samami, Flux-based faultdetection in rotors of induction motors, using finite elementsand neural network, International Journal of Power & EnergySystems, 39(2), 2019, 77–87.
  25. [25] S. Mansouri, S. Tnamo, and O. Bachelier, Integration andcontrol of a multi-task hybrid inverter in renewable energysystems, International Journal of Power & Energy Systems,40(2), 2020, 95–102.

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