Nearby allocation of emergency repair resources for multiple faults in distribution networks based on parallel CNN algorithm

被引:0
|
作者
Feng, Bo [1 ,2 ]
Zhang, Wei [1 ,3 ]
Huang, Weixiang [1 ,3 ]
Chen, Qianyi [1 ,3 ]
Li, Shan [1 ,3 ]
机构
[1] Elect Power Res Inst Guangxi Power Grid Co Ltd, Nanning 530023, Peoples R China
[2] Guangxi Key Lab Intelligent Control & Operat & Mai, Nanning 530023, Peoples R China
[3] Guangxi Power Grid Equipment Monitoring & Diag Eng, Nanning 530023, Peoples R China
关键词
Convolutional neural network - Detection methods - Emergency repair - Fault-based - Faults detection - Matrix operations - Multiple faults - Network-based - Neural networks algorithms - Objective functions;
D O I
10.1063/5.0210959
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
In order to improve the efficiency of emergency repair for multiple faults in distribution networks, a method for allocating emergency repair resources for multiple faults in distribution networks based on parallel convolutional neural network (CNN) algorithm is studied. This method uses a matrix operation based multiple fault detection method for distribution networks. After determining the location of multiple faults based on the direction of fault power, the principle is to allocate emergency repair resources nearby for multiple faults, with the goal of minimizing economic losses caused by the fault point and minimizing fault repair time. The objective function for allocating emergency repair resources nearby is constructed, and parallel CNN algorithm is used to solve the problem by classification, to find the feasible solution with the minimum mean square error between the objective function and the feasible solution set for nearby allocation of emergency repair resources, and it is used as the optimal solution for nearby allocation of repair resources. The experimental results show that when the proposed method is used to allocate emergency repair resources for multiple faults in the distribution network, the optimal time for setting the repair plan is 0.53 and 0.96 s, respectively, with an average allocation accuracy of 91%. It has been confirmed that this method can achieve the optimal decision of resource allocation plan in a short period of time, improving the efficiency of emergency repair.
引用
收藏
页数:10
相关论文
共 50 条
  • [31] Optimal allocation model of port emergency resources based on the improved multi-objective particle swarm algorithm and TOPSIS method
    Guo, Jianqun
    Jiang, Zhonglian
    Ying, Jianglong
    Feng, Xuejun
    Zheng, Fengfan
    MARINE POLLUTION BULLETIN, 2024, 209
  • [32] Channel Allocation Based on Genetic Algorithm for Multiple IEEE 802.15.4-compliant Wireless Sensor Networks
    Hu, Xiaoya
    Ge, Sanyou
    Xiao, Jiangwen
    2017 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMMUNICATIONS AND COMPUTING (ICSPCC), 2017,
  • [33] Parallel operated hybrid Arithmetic-Salp swarm optimizer for optimal allocation of multiple distributed generation units in distribution networks
    Anjum, Zeeshan Memon
    Said, Dalila Mat
    Hassan, Mohammad Yusri
    Leghari, Zohaib Hussain
    Sahar, Gul
    PLOS ONE, 2022, 17 (04):
  • [34] A Novel Price-Based Power Allocation Algorithm in Non-Orthogonal Multiple Access Networks
    Wang, Zhengqiang
    Wen, Chenchen
    Fan, Zifu
    Wan, Xiaoyu
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2018, 7 (02) : 230 - 233
  • [35] Resource Allocation Based on Channel Distribution Information for Elastic and Streaming Traffic in OFDMA Networks: A Heuristic Algorithm
    Mokari, Nader
    Javan, Mohammed R.
    Navaie, Keivan
    2009 IEEE 70TH VEHICULAR TECHNOLOGY CONFERENCE FALL, VOLS 1-4, 2009, : 813 - 817
  • [36] Bacterial foraging optimization building block distribution algorithm based dynamic allocation in multiple robotic system
    P. Anand Raj
    S. Palanimurugan
    S. Senthilkumar
    Discover Applied Sciences, 7 (4)
  • [37] Optimal Allocation and Sizing of Multiple Distributed Generators in Distribution Networks Using a Novel Hybrid Particle Swarm Optimization Algorithm
    Tolba, Mohamed A.
    Tulsky, Vladimir N.
    Diab, Ahmed A. Zaki
    PROCEEDINGS OF THE 2017 IEEE RUSSIA SECTION YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING CONFERENCE (2017 ELCONRUS), 2017, : 1606 - 1612
  • [38] An ant-based rate allocation algorithm for media streaming in peer to peer networks: Extension to multiple sessions and dynamic networks
    Goudarzi, Hadi
    Salavati, Amir Hesam
    Pakravan, Mohammad Reza
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2011, 34 (01) : 327 - 340
  • [39] Effects of residential EV charging on power distribution networks and their mitigation by optimal allocation of wind-based DG resources
    Painuli, Shefali
    Khandelwal, Divyanshu
    Bhowmick, Suman
    Saha, Radheshyam
    ELECTRIC POWER SYSTEMS RESEARCH, 2025, 241
  • [40] Adaptive subcarrier-distribution algorithm for routing and spectrum allocation in OFDM-based elastic optical networks
    Zhenrong Zhang
    Mei Xiao
    Minghou Wu
    Feng Xie
    Photonic Network Communications, 2014, 28 : 225 - 231