Integrated Information System of Township Power Supply Office and Team Based on Cloud Computing

  • Dapeng ZhouEmail author
  • Jinghong Zhao
  • Ran Ran
  • Ying Liu
  • Dong Liu
  • Jun Qi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1146)


Township is the weak point and weak point in the coordinated development of China’s economy. It is also a link that must be strengthened in the coordinated development of China’s economy. The development of power grid provides a strong guarantee for the development of township economy and related industries. With the smooth progress of “SG – ERP project” of state grid corporation of China, the informatization construction of township power supply units has made remarkable achievements, and the informatization and datamation of daily management have been basically realized. However, there still exists the construction pattern of insufficient intelligence and failure to combine cloud computing technology to support the network of power supply system, which also greatly depresses the ideal implementation effect of information system. In order to fundamentally solve these constraints, it is necessary to carry out a series of power supply team integrated information system construction. In the current power supply system, the team is the direct executor of the daily work of the state grid corporation, as well as the grass-roots organization of the entire power industry. The efficiency of the township power supply station and the team directly affects the reputation of the state grid corporation. This paper will first make a detailed description of the information status of the township power supply station, and then put forward the overall framework of the township power supply station information integration construction system in this study, then the system is deployed and tested, and finally the application value and efficiency of the system are analyzed.


Cloud computing Township power stations Team integration Power supply system 



This work was supported by Research on improving technological innovation ability and mass innovation - State Grid Liaoning Electric Power Co., Ltd. information and communication branch (2019YF-65) fund.


  1. 1.
    NCD Risk Factor Collaboration (NCD-RisC) – Africa Working Group, Kengne, A.P., Bentham, J.: Trends in obesity and diabetes across Africa from 1997 to 2016: an analysis of pooled population-based studies. Int. J. Epidemiol. 46(5), 784–796 (2017).Google Scholar
  2. 2.
    Cai, Y.N., Ma, Y.L., Luo, H.B.: Knowledge, related behavior and on AIDS/HIV infection among rural adults with Derung minority, in Yunnan province, 2016. Zhonghua liu xing bing xue za zhi Zhonghua liuxingbingxue zazhi 39(4), 483–486 (2018)Google Scholar
  3. 3.
    Hosseini, S., Vakili, R.: Game theory approach for detecting vulnerable data centers in cloud computing network. Int. J. Commun. Syst. 32(1), 372–395 (2019)Google Scholar
  4. 4.
    Aodenggaowa, Li, Y., Bayaer, W.: Quantitative analysis on land use structure at village level in farming-pastoral fragile steppe zone. Nongye Gongcheng Xuebao/Trans. Chin. Soc. Agric. Eng. 33(6), 222–231 (2017)Google Scholar
  5. 5.
    Uma Maheswari, S., Vasanthanayaki, C.: Secure medical health care content protection system (SMCPS) with watermark detection for multi cloud computing environment. Multimedia Tools Appl. 63(1), 1–23 (2019)Google Scholar
  6. 6.
    Wang, L., Xue, J., Liao, X.: LCCFS: a lightweight distributed file system for cloud computing without journaling and metadata services. Sci. China Inf. Sci. 62(7), 78–93 (2019)Google Scholar
  7. 7.
    Fujimoto, T., Kagohashi, K.: Community-Led micro-hydropower development and landcare: a case study of networking activities of local residents and farmers in the Gokase Township (Japan). Energies 12(53), 4–7 (2019)Google Scholar
  8. 8.
    Arul Xavier, V.M., Annadurai, S.: Chaotic social spider algorithm for load balance aware task scheduling in cloud computing. Cluster Comput. 22(9), 1–11 (2019)Google Scholar
  9. 9.
    Okawa, S., Win, H.H., Nanishi, K.: Advice on healthy pregnancy, delivery, motherhood and information on non-communicable diseases in the maternal care programme in Myanmar: a cross-sectional study. BMJ Open 9(3), 4–12 (2019)CrossRefGoogle Scholar
  10. 10.
    Yang, J., Xiang, Z., Mou, L.: Multimedia resource allocation strategy of wireless sensor networks using distributed heuristic algorithm in cloud computing environment. Multimedia Tools Appl. 74(62), 87–92 (2019)Google Scholar
  11. 11.
    Mohammadi, A., Rezvani, M.H.: A novel optimized approach for resource reservation in cloud computing using producer–consumer theory of microeconomics. J. Supercomput. 5(6), 3–7 (2019)Google Scholar
  12. 12.
    Cao, L.: Spatial-temporal pattern of land ecological security at a township scale in the Bortala Mongolian autonomous prefecture. Acta Ecol. Sin. 37(19), 1127–1148 (2017)Google Scholar
  13. 13.
    Krishnaswamy, V., Sundarraj, R.P.: Impatience characteristics in cloud-computing-services procurement: effects of delay horizon and situational involvement. Group Decis. Negot. 47(11), 52–61 (2019)Google Scholar
  14. 14.
    Ding, Z., Wu, H., Wu, C.: The epidemiology of imported acute infectious diseases in Zhejiang Province, China, 2011–2016: analysis of surveillance data. Am. J. Trop. Med. Hyg. 98(3), 296–298 (2017)Google Scholar
  15. 15.
    Ma, Z.B., Chen, X.P., Chen, H.: Multi-scale spatial patterns and influencing factors of rural poverty: a case study in the Liupan mountain region, Gansu Province, China. Chin. Geogr. Sci. 28(2), 296–312 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Dapeng Zhou
    • 1
    Email author
  • Jinghong Zhao
    • 1
  • Ran Ran
    • 1
  • Ying Liu
    • 1
  • Dong Liu
    • 1
  • Jun Qi
    • 1
  1. 1.State Grid Liaoning Electric Power Co., Ltd., Information Communication BranchShenyangChina

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