Abstract
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.
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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.
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Zhou, D., Zhao, J., Ran, R., Liu, Y., Liu, D., Qi, J. (2020). Integrated Information System of Township Power Supply Office and Team Based on Cloud Computing. In: Xu, Z., Parizi, R., Hammoudeh, M., Loyola-González, O. (eds) Cyber Security Intelligence and Analytics. CSIA 2020. Advances in Intelligent Systems and Computing, vol 1146. Springer, Cham. https://doi.org/10.1007/978-3-030-43306-2_76
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