Research on Fault Location of Distribution Network with DG Based on HHO

Yan Xin; Liu Ruichen; Tu Naiwei; Xing Jiaqi

doi:doi:10.11648/j.sd.20221005.19

| Peer-Reviewed

Research on Fault Location of Distribution Network with DG Based on HHO

Yan Xin, Liu Ruichen, Tu Naiwei, Xing Jiaqi

Published in Science Discovery (Volume 10, Issue 5)

Received: 20 September 2022 Accepted: 18 October 2022 Published: 24 October 2022

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Power generation, transmission, transformation, distribution and use are several important links in the power system, of which the distribution link is the most important. Since the 18th National Congress of the CPC, with the acceleration of carbon peaking and carbon neutrality process, clean energy such as solar power generation, wind power generation and fuel cells has developed rapidly, and the energy utilization mode has become complex and diversified. The access of these distributed power sources has put forward higher requirements for the safe and stable operation of the power system. Therefore, the research on fault location has become an indispensable part of the research on the stability of distribution network. In order to enhance the accuracy and speed of fault location, a distributed power distribution network fault location method based on Harris Eagle algorithm was proposed. The specific process is: when a fault occurs in the power grid, FA (feeder automation) will first monitor the error message and upload it to FTU (feeder terminal unit), and FTU will interpret the error message according to HHO algorithm and accurately locate it to the fault section. However, the traditional HHO is not suitable for the discreteness problem, so it is first converted into a binary BHHO, based on this, new fault location coding mode, switching function and evaluation function suitable for binary system are constructed. BHHO is applied to the IEEE33 bus distribution network model with DG, and compared with GA and PSO under the conditions of single point fault, multi-point fault and information distortion fault The simulation results show that the accuracy and speed of BHHO are better than those of GA and PSO under various fault conditions. The results prove that HHO can better enhance the accuracy and stability of fault location in distribution network.

Published in	Science Discovery (Volume 10, Issue 5)
DOI	10.11648/j.sd.20221005.19
Page(s)	332-339
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Harris Eagle Algorithm, Power Distribution Network, Fault Location, Distributed Generation

References

[1]	张朝平. 馈线自动化模式的研究与实现 [D]. 湖南大学. 2005. (Zhang Chaoping. Research and implementation of feeder automation mode [D] Hunan University, 2005.)
[2]	刘健，林涛，赵江河，等. 面向供电可靠性的配电自动化系统规划研究 [J]. 电力系统保护与控制. 2014. 42 (11): 52-60. (Liu Jian, Lin Tao, Zhao Jianghe, et al. Research on distribution automation system planning for power supply reliability [J] Power system protection and control 2014. 42 (11): 52-60.)
[3]	Hart DG, et al. Automated Solutions for Distribution Feeders [J]. IEEE Computer Applications in Power. 200 0. 13 (4): 25-30.
[4]	杜红卫, 孙雅明, 刘弘靖, 等. 基于遗传算法的配电网故障定位和隔离 [J]. 电网技术, 2000 (05): 52-55. (Du Hongwei, Sun Yaming, Liu Hongjing, et al. Distribution network fault location and isolation based on genetic algorithm [J] Power grid technology, 2000 (05): 52-55.)
[5]	卫志农, 何桦, 郑玉平. 配电网故障区间定位的高级遗传算法 [J]. 中国电机工程学报, 2002 (04): 128-131. (Wei Zhinong, He Hua, Zheng Yuping. Advanced genetic algorithm for fault location in distribution network [J] Chinese Journal of electrical engineering, 2002 (04): 128-131.)
[6]	张钊. 配网故障诊断及供电恢复算法研究 [D]. 东南大学, 2005. (Zhang Zhao. Research on distribution network fault diagnosis and power supply restoration algorithm [D] Southeast University, 2005.)
[7]	李超文, 何正友, 张海平, 等. 基于二进制粒子群算法的辐射状配电网故障定位 [J]. 电力系统保护与控制, 2009, 37 (07): 35-39. (Li Chaowen, He Zhengyou, Zhang Haiping, et al. Fault location of radial distribution network based on binary particle swarm optimization [J] Power system protection and control, 2009, 37 (07): 35-39.)
[8]	裘德玺, 宋哲, 冷磊磊, 等. 基于改进烟花算法的配电网集中式馈线自动化故障定位研究 [J]. 浙江电力, 2021, 40 (0 9): 99-104. (Qiu Dexi, Song Zhe, Leng Leilei, et al. Research on centralized feeder automation fault location of distribution network based on improved fireworks algorithm [J] Zhejiang electric power, 2021, 40 (09): 99-104.)
[9]	张荣升, 刘丽桑, 宋天文, 等. 基于鲸鱼优化算法的配电网故障区段定位 [J]. 福建工程学院学报, 2021, 19 (04): 37 8-384. (Zhang Rongsheng, liu Lisang, Song Tianwen, et al. Distribution network fault section location based on whale optimization algorithm [J] Journal of Fujian Institute of engineering, 2021, 19 (04): 378-384.)
[10]	陈磊, 詹跃东, 田庆生. 基于人工鱼群算法的配电网故障定位 [J]. 电子测量技术, 2018, 41 (23): 1-5. (Chen Lei, Zhan Yuedong, Tian Qingsheng. Distribution network fault location based on artificial fish swarm algorithm [J] Electronic measurement technology, 2018, 41 (23): 1-5.)
[11]	梁有伟，胡志坚，陈允平. 分布式发电及其在电力系统中的应用研宄综述 [J]. 电网技术，2003, 27 (12): 71-75. (Liang Youwei, Hu Zhijian, Chen Yunping. Overview of research on distributed generation and its applicati on in power system [J]. power grid technology, 2003, 27 (12): 71-75.)
[12]	Ali Asghar Heidari, Seyedali Mirjalili, Hossam Faris, Ib rahim Aljarah, et al. Harris hawks optimization: Algor ithm and applications [J]. Future Generation Computer Systems, 2019, 97.
[13]	Bednarz J C. Cooperative hunting in harris’hawks (p arabuteo unicinctus) [J]. Science, 1998, 239 (4847): 1525-1 527.
[14]	刘骏鹏. 哈里斯鹰算法的改进及应用研究 [D]. 浙江大学, 2021. (Liu Junpeng. Research on improvement and application of Harris Eagle algorithm [D]. Zhejiang University, 2021.)
[15]	郭雨鑫, 刘升, 高文欣, 等. 多策略改进哈里斯鹰优化算法 [J]. 微电子学与计算机, 2021, 38 (07): 18-24. (Guo Yuxin, Liu Sheng, Gao Wenxin, et al. Multi strategy improved Harris Eagle optimization algorithm [J]. Microelectronics and computer, 2021, 38 (07): 18-24.)
[16]	王归新, 田中天. 基于分层混合灰狼-哈里斯鹰算法的水火电调度优化 [J]. 电工材料, 2021 (03): 58-62. (Wang Guixin, Tian Zhongtian. Hydro thermal power dispatching optimization based on hierarchical hybrid gray wolf Harris Eagle algorithm [J] Electrical materials, 2021 (03): 58-62.)
[17]	贾鹤鸣, 康立飞, 孙康健, 等. 哈里斯鹰算法优化脉冲耦合神经网络的图像自动分割 [J]. 应用科技, 2019, 46 (04): 16-20. (Jia Heming, Kang Lifei, Sun Kangjian, et al. Harris Eagle algorithm optimizes pulse coupled neural network for automatic image segmentation [J] Applied science and technology, 2019, 46 (04): 16-20.)
[18]	吴丁杰, 温立书. 一种基于哈里斯鹰算法改进的BP神经网络 [J]. 网络安全技术与应用, 2022 (01): 38-40. (Wu Dingjie, Wen Lishu. An improved BP neural network based on Harris Eagle algorithm [J] Network security technology and application, 2022 (01): 38-40.)
[19]	刘迎. 含分布式电源的配电网故障定位研究 [D]. 中国矿业大学, 2017. (Liu Ying. Research on fault location of distribution network with distributed generation [D] China University of mining and technology, 2017.)
[20]	孙飞洋, 龚涛. 改进免疫网络及其算法在配电网故障定位中的应用 [J]. 现代计算机, 2021, 27 (23): 67-72. (Sun Feiyang, Gong Tao. Application of improved immune network and its algorithm in distribution network fault location [J] Modern computer, 2021, 27 (23): 67-72.)

Cite This Article

Plain Text BibTeX RIS

APA Style

Yan Xin, Liu Ruichen, Tu Naiwei, Xing Jiaqi. (2022). Research on Fault Location of Distribution Network with DG Based on HHO. Science Discovery, 10(5), 332-339. https://doi.org/10.11648/j.sd.20221005.19

Copy | Download

ACS Style

Yan Xin; Liu Ruichen; Tu Naiwei; Xing Jiaqi. Research on Fault Location of Distribution Network with DG Based on HHO. Sci. Discov. 2022, 10(5), 332-339. doi: 10.11648/j.sd.20221005.19

Copy | Download

AMA Style

Yan Xin, Liu Ruichen, Tu Naiwei, Xing Jiaqi. Research on Fault Location of Distribution Network with DG Based on HHO. Sci Discov. 2022;10(5):332-339. doi: 10.11648/j.sd.20221005.19

Copy | Download

@article{10.11648/j.sd.20221005.19,
  author = {Yan Xin and Liu Ruichen and Tu Naiwei and Xing Jiaqi},
  title = {Research on Fault Location of Distribution Network with DG Based on HHO},
  journal = {Science Discovery},
  volume = {10},
  number = {5},
  pages = {332-339},
  doi = {10.11648/j.sd.20221005.19},
  url = {https://doi.org/10.11648/j.sd.20221005.19},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20221005.19},
  abstract = {Power generation, transmission, transformation, distribution and use are several important links in the power system, of which the distribution link is the most important. Since the 18th National Congress of the CPC, with the acceleration of carbon peaking and carbon neutrality process, clean energy such as solar power generation, wind power generation and fuel cells has developed rapidly, and the energy utilization mode has become complex and diversified. The access of these distributed power sources has put forward higher requirements for the safe and stable operation of the power system. Therefore, the research on fault location has become an indispensable part of the research on the stability of distribution network. In order to enhance the accuracy and speed of fault location, a distributed power distribution network fault location method based on Harris Eagle algorithm was proposed. The specific process is: when a fault occurs in the power grid, FA (feeder automation) will first monitor the error message and upload it to FTU (feeder terminal unit), and FTU will interpret the error message according to HHO algorithm and accurately locate it to the fault section. However, the traditional HHO is not suitable for the discreteness problem, so it is first converted into a binary BHHO, based on this, new fault location coding mode, switching function and evaluation function suitable for binary system are constructed. BHHO is applied to the IEEE33 bus distribution network model with DG, and compared with GA and PSO under the conditions of single point fault, multi-point fault and information distortion fault The simulation results show that the accuracy and speed of BHHO are better than those of GA and PSO under various fault conditions. The results prove that HHO can better enhance the accuracy and stability of fault location in distribution network.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Research on Fault Location of Distribution Network with DG Based on HHO
AU  - Yan Xin
AU  - Liu Ruichen
AU  - Tu Naiwei
AU  - Xing Jiaqi
Y1  - 2022/10/24
PY  - 2022
N1  - https://doi.org/10.11648/j.sd.20221005.19
DO  - 10.11648/j.sd.20221005.19
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 332
EP  - 339
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20221005.19
AB  - Power generation, transmission, transformation, distribution and use are several important links in the power system, of which the distribution link is the most important. Since the 18th National Congress of the CPC, with the acceleration of carbon peaking and carbon neutrality process, clean energy such as solar power generation, wind power generation and fuel cells has developed rapidly, and the energy utilization mode has become complex and diversified. The access of these distributed power sources has put forward higher requirements for the safe and stable operation of the power system. Therefore, the research on fault location has become an indispensable part of the research on the stability of distribution network. In order to enhance the accuracy and speed of fault location, a distributed power distribution network fault location method based on Harris Eagle algorithm was proposed. The specific process is: when a fault occurs in the power grid, FA (feeder automation) will first monitor the error message and upload it to FTU (feeder terminal unit), and FTU will interpret the error message according to HHO algorithm and accurately locate it to the fault section. However, the traditional HHO is not suitable for the discreteness problem, so it is first converted into a binary BHHO, based on this, new fault location coding mode, switching function and evaluation function suitable for binary system are constructed. BHHO is applied to the IEEE33 bus distribution network model with DG, and compared with GA and PSO under the conditions of single point fault, multi-point fault and information distortion fault The simulation results show that the accuracy and speed of BHHO are better than those of GA and PSO under various fault conditions. The results prove that HHO can better enhance the accuracy and stability of fault location in distribution network.
VL  - 10
IS  - 5
ER  -

Copy | Download

Author Information

Yan Xin

School of Electrical and Control Engineering, Liaoning University of Engineering and Technology, Huludao, China
Liu Ruichen

School of Electrical and Control Engineering, Liaoning University of Engineering and Technology, Huludao, China
Tu Naiwei

School of Electrical and Control Engineering, Liaoning University of Engineering and Technology, Huludao, China
Xing Jiaqi

School of Electrical and Control Engineering, Liaoning University of Engineering and Technology, Huludao, China

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Yan Xin, Liu Ruichen, Tu Naiwei, Xing Jiaqi. (2022). Research on Fault Location of Distribution Network with DG Based on HHO. Science Discovery, 10(5), 332-339. https://doi.org/10.11648/j.sd.20221005.19

Copy | Download

ACS Style

Yan Xin; Liu Ruichen; Tu Naiwei; Xing Jiaqi. Research on Fault Location of Distribution Network with DG Based on HHO. Sci. Discov. 2022, 10(5), 332-339. doi: 10.11648/j.sd.20221005.19

Copy | Download

AMA Style

Yan Xin, Liu Ruichen, Tu Naiwei, Xing Jiaqi. Research on Fault Location of Distribution Network with DG Based on HHO. Sci Discov. 2022;10(5):332-339. doi: 10.11648/j.sd.20221005.19

Copy | Download

@article{10.11648/j.sd.20221005.19,
  author = {Yan Xin and Liu Ruichen and Tu Naiwei and Xing Jiaqi},
  title = {Research on Fault Location of Distribution Network with DG Based on HHO},
  journal = {Science Discovery},
  volume = {10},
  number = {5},
  pages = {332-339},
  doi = {10.11648/j.sd.20221005.19},
  url = {https://doi.org/10.11648/j.sd.20221005.19},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20221005.19},
  abstract = {Power generation, transmission, transformation, distribution and use are several important links in the power system, of which the distribution link is the most important. Since the 18th National Congress of the CPC, with the acceleration of carbon peaking and carbon neutrality process, clean energy such as solar power generation, wind power generation and fuel cells has developed rapidly, and the energy utilization mode has become complex and diversified. The access of these distributed power sources has put forward higher requirements for the safe and stable operation of the power system. Therefore, the research on fault location has become an indispensable part of the research on the stability of distribution network. In order to enhance the accuracy and speed of fault location, a distributed power distribution network fault location method based on Harris Eagle algorithm was proposed. The specific process is: when a fault occurs in the power grid, FA (feeder automation) will first monitor the error message and upload it to FTU (feeder terminal unit), and FTU will interpret the error message according to HHO algorithm and accurately locate it to the fault section. However, the traditional HHO is not suitable for the discreteness problem, so it is first converted into a binary BHHO, based on this, new fault location coding mode, switching function and evaluation function suitable for binary system are constructed. BHHO is applied to the IEEE33 bus distribution network model with DG, and compared with GA and PSO under the conditions of single point fault, multi-point fault and information distortion fault The simulation results show that the accuracy and speed of BHHO are better than those of GA and PSO under various fault conditions. The results prove that HHO can better enhance the accuracy and stability of fault location in distribution network.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Research on Fault Location of Distribution Network with DG Based on HHO
AU  - Yan Xin
AU  - Liu Ruichen
AU  - Tu Naiwei
AU  - Xing Jiaqi
Y1  - 2022/10/24
PY  - 2022
N1  - https://doi.org/10.11648/j.sd.20221005.19
DO  - 10.11648/j.sd.20221005.19
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 332
EP  - 339
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20221005.19
AB  - Power generation, transmission, transformation, distribution and use are several important links in the power system, of which the distribution link is the most important. Since the 18th National Congress of the CPC, with the acceleration of carbon peaking and carbon neutrality process, clean energy such as solar power generation, wind power generation and fuel cells has developed rapidly, and the energy utilization mode has become complex and diversified. The access of these distributed power sources has put forward higher requirements for the safe and stable operation of the power system. Therefore, the research on fault location has become an indispensable part of the research on the stability of distribution network. In order to enhance the accuracy and speed of fault location, a distributed power distribution network fault location method based on Harris Eagle algorithm was proposed. The specific process is: when a fault occurs in the power grid, FA (feeder automation) will first monitor the error message and upload it to FTU (feeder terminal unit), and FTU will interpret the error message according to HHO algorithm and accurately locate it to the fault section. However, the traditional HHO is not suitable for the discreteness problem, so it is first converted into a binary BHHO, based on this, new fault location coding mode, switching function and evaluation function suitable for binary system are constructed. BHHO is applied to the IEEE33 bus distribution network model with DG, and compared with GA and PSO under the conditions of single point fault, multi-point fault and information distortion fault The simulation results show that the accuracy and speed of BHHO are better than those of GA and PSO under various fault conditions. The results prove that HHO can better enhance the accuracy and stability of fault location in distribution network.
VL  - 10
IS  - 5
ER  -

Copy | Download