Distribution network reconfiguration optimization based on genetic algorithm and its influence on operation and maintenance management
Abstract
As one of the advanced application functions of distribution network automation, distribution network reconfiguration is an important optimization means to ensure the normal operation of the power grid. In order to further improve the power supply quality and operation and maintenance efficiency of the distribution network, this paper proposes a reconfiguration method based on improved genetic algorithm, establishes a network topology reconfiguration computational model, and validates the proposed method for the reconfiguration of the distribution network, and the results show that compared with the reconfiguration model of the distribution network constructed by basic genetic algorithm, the algorithm of this paper shows excellent performance in terms of both the comparison of the node voltages and the evolution of the population. The results show that compared with the basic genetic algorithm constructed distribution network reconfiguration model, this paper's algorithm exhibits excellent performance in both node voltage comparison and population evolution, and is capable of realizing optimal power transmission. Finally, the impact of distribution network reconfiguration on operation and maintenance management is analyzed.
References
1. Taylor L A. Pruning duplicate nodes in depth-first search[M]. University of California, Los Angeles, 1997.
2. GAO Nan. Economic Operation analysis of Distribution Network based on Network reconstruction and Capacitor switching [D]. North China Electric Power University,2010.
3. Mehdi, Semsarzadeh, Mehdi, et al. Tampering Detection in Compressed Digital Video Using Watermarking[J]. IEEE Transactions on Instrumentation & Measurement, 2014.
4. Chen Zheng-peng, Huang Chun, ZHANG Ya-ping, KANG Zhi-hao, Reconfiguration of distribution network with distributed power based on improved double population Genetic Algorithm [J]. Journal of Electric Power Systems and Automation, 2017,29 (4): 78-83.
5. LIANG San, MAO Yi, LIU Xiaoli, PENG Wenqiang, FAN Xing, DANG Haichao. Improved harmonic search algorithm for distribution network reconfiguration[J]. Journal of Power System and its Automation,2017,29(03):90-95.
6. LI Qian-Qian, LI Shao-ming, YAN Cheng-Ren. Research on Distribution network reconstruction based on improved particle swarm optimization and Genetic Algorithm [J]. Journal of Luoyang University of Science and Technology (Natural Science Edition),2018,28(04):46-52.
7. XU Jiabin, ZHANG Xin, ZHANG Yuzhen, Zhang Jing. Mining Distribution Network Reconstruction based on improved Fireworks Algorithm [J]. Automatization of Industry and Mining,2018,44(09):32-36.
8. SONG Ziyang, ZHANG Jing, LIU Xiaokang, LIU Chuanxiu. Multi-target reconfiguration of distribution networks based on improved particle swarm algorithm[J]. Intelligent Computer and Application ,2020,10(05):76-80.
9. Zhang Y, Qian T, Tang W. Buildings-to-distribution-network integration considering power transformer loading capability and distribution network reconfiguration[J]. Energy, 2022, 244: 123104.
10. Mishra S, Das D, Paul S. A comprehensive review on power distribution network reconfiguration[J]. Energy Systems, 2017, 8: 227-284.
11. Mishra A, Tripathy M, Ray P. A survey on different techniques for distribution network reconfiguration[J]. Journal of Engineering Research, 2024, 12(1): 173-181.
12. Asrari A, Ansari M, Khazaei J, et al. The impacts of a decision making framework on distribution network reconfiguration[J]. IEEE Transactions on Sustainable Energy, 2020, 12(1): 634-645.
13. Essallah S, Khedher A. Optimization of distribution system operation by network reconfiguration and DG integration using MPSO algorithm[J]. Renewable Energy Focus, 2020, 34: 37-46.
14. Cikan M, Kekezoglu B. Comparison of metaheuristic optimization techniques including Equilibrium optimizer algorithm in power distribution network reconfiguration[J]. Alexandria Engineering Journal, 2022, 61(2): 991-1031.
15. Naguib M, Omran W A, Talaat H E A. Performance enhancement of distribution systems via distribution network reconfiguration and distributed generator allocation considering uncertain environment[J]. Journal of Modern Power Systems and Clean Energy, 2021, 10(3): 647-655.
16. Parihar S S, Malik N. Network reconfiguration in the presence of optimally integrated multiple distributed generation units in a radial distribution network[J]. Engineering Optimization, 2024, 56(5): 679-699.
17. Ali Z M, Diaaeldin I M, El-Rafei A, et al. A novel distributed generation planning algorithm via graphically-based network reconfiguration and soft open points placement using Archimedes optimization algorithm[J]. Ain Shams Engineering Journal, 2021, 12(2): 1923-1941.
18. Nguyen T T, Nguyen T T, Nguyen N A, et al. A novel method based on coyote algorithm for simultaneous network reconfiguration and distribution generation placement[J]. Ain Shams Engineering Journal, 2021, 12(1): 665-676.
19. Cikan M, Kekezoglu B. Comparison of metaheuristic optimization techniques including Equilibrium optimizer algorithm in power distribution network reconfiguration[J]. Alexandria Engineering Journal, 2022, 61(2): 991-1031.
20. Yang T, Guo Y, Deng L, et al. A linear branch flow model for radial distribution networks and its application to reactive power optimization and network reconfiguration[J]. IEEE Transactions on Smart Grid, 2020, 12(3): 2027-2036.
21. Monteiro R V A, Bonaldo J P, da Silva R F, et al. Electric distribution network reconfiguration optimized for PV distributed generation and energy storage[J]. Electric Power Systems Research, 2020, 184: 106319.
22. Wang C, Lei S, Ju P, et al. MDP-based distribution network reconfiguration with renewable distributed generation: Approximate dynamic programming approach[J]. IEEE Transactions on Smart Grid, 2020, 11(4): 3620-3631.
23. Tran The T, Vo Ngoc D, Tran Anh N. Distribution network reconfiguration for power loss reduction and voltage profile improvement using chaotic stochastic fractal search algorithm[J]. Complexity, 2020, 2020(1): 2353901.
24. Shi Q, Li F, Olama M, et al. Network reconfiguration and distributed energy resource scheduling for improved distribution system resilience[J]. International Journal of Electrical Power & Energy Systems, 2021, 124: 106355.
25. Parihar S S, Malik N. Network reconfiguration in the presence of optimally integrated multiple distributed generation units in a radial distribution network[J]. Engineering Optimization, 2024, 56(5): 679-699.
Copyright (c) 2024 Jun Lin, Chen Liang Zhou
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright on all articles published in this journal is retained by the author(s), while the author(s) grant the publisher as the original publisher to publish the article.
Articles published in this journal are licensed under a Creative Commons Attribution 4.0 International, which means they can be shared, adapted and distributed provided that the original published version is cited.
Submit a Paper
