Building a Unified Spatio-Temporal Data Model for Grid Resources Based on Microservice Architecture
Author(s): |
Haoqi Dai
Yuxu Chen Haowen Ren Xiaolu Li Zhiqi Ao |
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Medium: | journal article |
Language(s): | English |
Published in: | Journal of Physics: Conference Series, 1 December 2022, 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. |
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data sheet - Reference-ID
10777666 - Published on:
12/05/2024 - Last updated on:
12/05/2024