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Building a Unified Spatio-Temporal Data Model for Grid Resources Based on Microservice Architecture

Author(s):




Medium: journal article
Language(s): English
Published in: Journal of Physics: Conference Series, , n. 1, v. 2404
Page(s): 012037
DOI: 10.1088/1742-6596/2404/1/012037
Abstract:

Under the background of accelerating the process of power grid construction, the unified spatial-temporal data model of power grid resources has become a necessary means to describe the relationship between spatial objects and power grid data. Affected by the defect of the information island, some unified spatiotemporal data models of power grid resources have poor updating performance. Therefore, a unified spatiotemporal data model of power grid resources based on microservice architecture is designed. The architecture can obtain the spatial structure elements of the power grid area, identify the spatial correlation characteristics of the modeling object through the distribution of power energy supply lines, eliminate the dimension of meteorological data variables, design a unified resource scheduling scheme based on the microservice architecture, calculate the space-time weight matrix, and build a space-time data model. Test results are that under the two update task scenarios, the average update performance of the unified spatiotemporal data model of power grid resources based on the Internet of things is 11363 times/second. The average update performance of the unified spatiotemporal data model of power grid resources based on the Internet of things is 9958 times/second). And the average update performance of the unified spatiotemporal data model of power grid resources based on the genetic algorithm is 9771 times/second. It shows that the designed unified spatiotemporal data model of power grid resources is perfect after combining the microservice architecture.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1088/1742-6596/2404/1/012037.
  • About this
    data sheet
  • Reference-ID
    10777666
  • Published on:
    12/05/2024
  • Last updated on:
    12/05/2024
 
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