Construction of a Power Communication Supervision System Based on WOA Fusion Fault Detection from the Perspective of Sustainable Development

Authors

  • Yang Li State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China
  • Jianliang Zhang State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China
  • Meiru Huo State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China
  • Chunshan Zhu State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China
  • Xiaowei Hao State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China
  • Yinghao Gao State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China
  • Leifang Yan State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China
  • Jian Wu State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.4026

Keywords:

WOA, fault detection, distribution network, supervision, sustainable development

Abstract

This paper focuses on the problems of poor fault localization and easy leakage and false alarms of power communication monitoring system for distribution network segments. A new improved method based on whale optimization algorithm (WOA) is proposed to counter poor fault localization. The new method uses a feeder unit system for power grid data feedback, and enhance the adaptability of the model. The study also conducts iterative performance tests of the model in several distribution network segments. It also compares the performance of the improved WOA model with traditional genetic algorithm (GA), particle swarm optimization (PSO) and other algorithms, and conducts simulation analyses of voltage deviation and fault location time, as well as evaluation of fault location accuracy at different grid nodes. The results show that the improved WOA model is significantly better than the traditional algorithms in terms of iteration speed, and its longest time to reach the optimal solution is 3.12 ms after 6 iterations; this is 3.73 ms less than when compared to the GA. In the comparison test of different sections of the grid, the new proposed model is able to achieve a better objective function value in fewer iterations, and the smallest deviation value in grid Node 3 is only 0.05 pu, the localization time is shortened by 0.10 s compared with the GA, and the localization accuracy is improved by 7.9%. The new proposed algorithm offers better advantages in fault localization, communication monitoring and provides effective technical support for fault monitoring in a power communication monitoring system.

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Author Biographies

Yang Li, State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China

Yang Li, born in April 1978, male, from Laizhou City, Shandong Province, China. He obtained his PhD in Mechanical Design and Theory from Harbin Institute of Technology in November 2008. In March 2011, postdoctoral fellow at Inspur Group and Shandong University, with a research focus on data mining.

Work experience: From 2011 to 2012, worked as a pre planning specialist in the System Management Department of Shanxi Electric Power Communication Center. From 2012 to this year, worked as a fourth level employee in the Technical Development Department of the Information and Communication Branch of State Grid Shanxi Electric Power Company.

Academic situation: Published more than 10 articles indexed in EI and SCI, authorized more than 20 patents, completed more than 10 scientific and technological projects, and won two Shanxi Provincial Science and Technology Progress Awards.

Jianliang Zhang, State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China

Jianliang Zhang, born in June 1981, male, from Wutai, Shanxi, Han ethnicity. He obtained a Bachelor’s degree in Electronic Science and Technology from Jilin University in 2004 and a Master’s degree in Electronic and Communication Engineering from Taiyuan University of Technology in 2013, with a research focus on power communication.

Work experience: From 2006 to 2012, worked as a communication operation and maintenance specialist at Shanxi Electric Power Communication Center. From 2013 to 2022, worked as a technology management specialist at the Information and Communication Branch of State Grid Shanxi Electric Power Company. From 2023 to present, worked as a material management specialist at the Information and Communication Branch of State Grid Shanxi Electric Power Company.

Academic situation: Led or participated in 14 scientific and technological projects undertaken by Shanxi Province, State Grid Corporation of China, and provincial companies; Published 1 book, 6 papers in Chinese core journals, 9 papers indexed by EI, and 8 authorized invention patents; Received one second prize for scientific and technological progress in Shanxi Province and six other provincial and ministerial level innovative achievements.

Meiru Huo, State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China

Meiru Huo, born in October 1987, female, from Fenyang, Shanxi, Han ethnicity. She obtained a Bachelor’s degree in Physics from Shanxi University (National Base) in 2012 and a PhD in Optics from Shanxi University in 2018 (combined master’s and doctoral studies). Her research interests include quantum optics, quantum communication, blockchain, and artificial intelligence technology research and applications.

Work experience: From 2018 to 2020, worked as a communication operation and maintenance specialist at the Information and Communication Branch of State Grid Shanxi Electric Power Company. From 2020 to 2022, worked as a communication dispatch team leader at the Information and Communication Branch of State Grid Shanxi Electric Power Company. From 2022 to present, worked as a digital pre management specialist at the Information and Communication Branch of State Grid Shanxi Electric Power Company.

Academic situation: Accumulated publications in SCI EI. There are a total of 12 papers published in Chinese core journals, 3 authorized invention patents, and nearly 20 awards for various scientific and technological innovation achievements. We have mainly participated in 3 science and technology projects of the State Grid Corporation of China headquarters and 5 science and technology projects of provincial companies.

Chunshan Zhu, State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China

Chunshan Zhu, born in February 1973, male, from Wuqing, Tianjin, Han ethnicity, obtained a Bachelor’s degree in Communication Engineering from North China Electric Power University in 1995, with a focus on power communication.

Work experience: From 2019 to 2022, served as the Party Secretary of the Information and Communication Branch of State Grid Shanxi Electric Power Company; From 2022 to present, General Manager of Information and Communication Branch of State Grid Shanxi Electric Power Company.

Academic situation: Published 2 papers in Chinese core journals; Authorized 3 invention patents.

Xiaowei Hao, State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China

Xiaowei Hao, born in September 1982, male, from Yuncheng, Shanxi, Han ethnicity. He obtained a Bachelor’s degree in Electronic Information Engineering from North China Electric Power University in 2004 and a Master’s degree in Electronic and Communication Engineering from Taiyuan University of Technology in 2008, with a focus on power communication.

Work experience: Since 2017, I have been working as a team leader at the Information and Communication Branch of State Grid Shanxi Electric Power Company.

Academic situation: Published 3 papers including Chinese core papers; Authorized 3 invention patents.

Yinghao Gao, State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China

Yinghao Gao, July 1990, male, Lvliang City, Shanxi Province, Han ethnicity, obtained a PhD in Optics from Shanxi University in 2019, with a research focus on Communication

Work experience: Since 2019, I have been the team leader of the Communication Center at the Information and Communication Branch of State Grid Shanxi Electric Power Company.

Academic situation: Published 3 SCI papers, 1 patent, researched maintenance ticket reporting tools based on RPA technology, and researched and applied key technologies for power emergency communication based on satellite communication and Beidou positioning.

Leifang Yan, State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China

Leifang Yan, born in November 1990, female, from Shuozhou, Shanxi, Han ethnicity. She obtained a Bachelor’s degree in Communication Engineering from Shandong University in June 2014 and a Master’s degree in Communication and Information Systems from Shandong University in June 2017, with a focus on machine learning.

Work experience: Since 2017, I have been working as a team leader at the Information and Communication Branch of State Grid Shanxi Electric Power Company.

Academic situation: Published 3 SCI papers and 3 core Chinese papers; Authorized 3 invention patents and accepted 5 invention patents; Received 4 excellent paper awards from the Chinese Society of Electrical Engineering and other organizations.

Jian Wu, State Grid Information & Telecommunication CO. Of Shanxi Electric Power Company, Taiyuan 030021, China

Jian Wu, born in February 1990, male, from Xiangfen, Shanxi, Han ethnicity. He obtained a Bachelor’s degree in Communication Engineering from the University of Electronic Science and Technology of China in 2012 and a Master’s degree in Communication and Information Systems from the same university in 2015. His main research focus is on technologies related to the planning and construction of power communication systems.

Work experience: From 2015 to 2018, worked as a specialist in the Operations and Inspection Center of the Information and Communication Branch of State Grid Shanxi Electric Power Company. From 2018 to 2019, served as the team leader of the Operations and Inspection Center of the Information and Communication Branch of State Grid Shanxi Electric Power Company. From 2019 to present, worked in the Communication Planning and Management Department of the Technology Development Department of the Information and Communication Branch of State Grid Shanxi Electric Power Company.

Academic situation: Published 4 core Chinese papers such as “Intelligent Recognition of Fiber Optic Links Based on Physical Address Encoding”, authorized 6 invention patents, undertaken key research projects of State Grid Shanxi Electric Power Company multiple times, won multiple awards such as the first prize for scientific and technological progress of the provincial company, and was awarded as an excellent engineer in Shanxi’s power industry during the 13th Five Year Plan period.

References

He Y. Multi-modal information analysis for fault diagnosis with time-series data from power transformer. International Journal of Electrical Power & Energy Systems. 2023, 144(1):108567–108568.

Souza BJ, Stefenon SF, Singh G, Freire RZ. Hybrid-YOLO for classification of insulators defects in transmission lines based on UAV. International Journal of Electrical Power & Energy Systems. 2023, 148(2):108982–108983.

Kumar K, Pande SV, Kumar TC, Saini P, Chaturvedi A, Reddy PC, Shah KB. Intelligent controller design and fault prediction using machine learning model. International Transactions on Electrical Energy Systems. 2023, 2023(1):1056387–1056388.

Borousan F, Hamidan MA. Distributed power generation planning for distribution network using chimp optimization algorithm in order to reliability improvement. Electric Power Systems Research. 2023, 217(1):109–110.

Sun Y, Zhu D, Li Y, Wang R, Ma R. Spatial modelling the location choice of large-scale solar photovoltaic power plants: Application of interpretable machine learning techniques and the national inventory. Energy Conversion and Management. 2023, 289(1):117198–117199.

Wu Z, Lu X. Microgrid Fault Diagnosis Based on Whale Algorithm Optimizing Extreme Learning Machine. Journal of Electrical Engineering & Technology. 2024, 19(3):1827–1836.

Yang P, Wang T, Yang H, Meng C, Zhang H, Cheng L. The performance of electronic current transformer fault diagnosis model: Using an improved whale optimization algorithm and RBF neural network. Electronics. 2023, 12(4):1066–1067.

Nayak PC, Mishra S, Prusty RC, Panda S. Hybrid whale optimization algorithm with simulated annealing for load frequency controller design of hybrid power system. Soft Computing. 2023, 16(6):1–24.

Men Z, Hu C, Li YH, Bai X. A hybrid intelligent gearbox fault diagnosis method based on EWCEEMD and whale optimization algorithm-optimized SVM. International Journal of Structural Integrity. 2023, 14(2):322–36.

Chen X, Cheng L, Liu C, Liu Q, Liu J, Mao Y, Murphy J. A WOA-based optimization approach for task scheduling in cloud computing systems. IEEE Systems journal. 2020, 14(3):3117–3128.

Presekal A, Ştefanov A, Rajkumar VS, Palensky P. Attack graph model for cyber-physical power systems using hybrid deep learning. IEEE Transactions on Smart Grid. 2023, 14(5):4007–4020.

Hasan MK, Habib AA, Shukur Z, Ibrahim F, Islam S, Razzaque MA. Review on cyber-physical and cyber-security system in smart grid: Standards, protocols, constraints, and recommendations. Journal of Network and Computer Applications. 2023, 209(1):103540–103541.

Wagle R, Sharma P, Sharma C, Amin M, Rueda JL, Gonzalez-Longatt F. Optimal power flow-based reactive power control in smart distribution network using real-time cyber-physical co-simulation framework. IET Generation, Transmission & Distribution. 2023, 17(20):4489–4502.

Fernandez JH, Omri A, Di Pietro R. Power grid surveillance: Topology change detection system using power line communications. International Journal of Electrical Power & Energy Systems. 2023, 145(10):108634–108635.

Chakraborty S, Saha AK, Chhabra A. Improving whale optimization algorithm with elite strategy and its application to engineering-design and cloud task scheduling problems. Cognitive Computation. 2023 Sep;15(5):1497–1525.

Singh H, Rai V, Kumar N, Dadheech P, Kotecha K, Selvachandran G, Abraham A. An enhanced whale optimization algorithm for clustering. Multimedia tools and applications. 2023, 82(3):4599–4618.

Yu H, Sun L, Wu B. Microgrid fault diagnosis based on whale optimization algorithm optimizing BP neural network. In Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023) 2024, 13159(5):2130–2135.

Nayak PC, Mishra S, Prusty RC, Panda S. Hybrid whale optimization algorithm with simulated annealing for load frequency controller design of hybrid power system. Soft Computing. 2023, 16(6):1–24.

Hocine T, Saliha C. Hybrid improved whales and sine cosine optimization algorithms for the optimal configuration of distribution networks in the presence of dispersed generation systems before, during, and after short circuit current propagation case study: overhead and underground networks in the laghouat region of Algeria. Electrical Engineering. 2024, 106(1):755–771.

Mahmoud MM, Atia BS, Esmail YM, Ardjoun SA, Anwer N, Omar AI, Alsaif F, Alsulamy S, Mohamed SA. Application of whale optimization algorithm based FOPI controllers for STATCOM and UPQC to mitigate harmonics and voltage instability in modern distribution power grids. Axioms. 2023, 12(5):420–421.

J. Morales Pedraza. The Role of Renewable Energy in the Transition to Green, Low-Carbon Power Generation in Asia, GLCE, 2023,1(2):68–84.

Rana AS, Jnaneswar K, Gadhiraju MK, Kumar N, Wani SA, Thomas MS. Design and Implementation of Low-Cost PMU for Off-Nominal Frequency and DDC in Compliance with IEEE C37. 118 Standard. Distributed Generation & Alternative Energy Journal. 2023, 3(1):519–546.

Nethravathi S, Murali V. A Novel Knapsack Algorithm-Based Energy Routing in a Microgrid. Distributed Generation & Alternative Energy Journal. 2023, 3(1):641–668.

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Published

2025-05-19

How to Cite

Li, Y. ., Zhang, J. ., Huo, M. ., Zhu, C. ., Hao, X. ., Gao, Y. ., Yan, L. ., & Wu, J. . (2025). Construction of a Power Communication Supervision System Based on WOA Fusion Fault Detection from the Perspective of Sustainable Development. Distributed Generation &Amp; Alternative Energy Journal, 40(02), 333–360. https://doi.org/10.13052/dgaej2156-3306.4026

Issue

Section

Renewable Power & Energy Systems