Open AccessDesign of intelligent distribution network based on Geographic Information Technology
Author(s) -
Linyao Zhang,
Zhenda Hu,
Xiaojie Fang,
Xu Ye,
Xiuwen Cai,
Shu Chen
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1748/4/042009
Subject(s) - computer science , geographic information system , grid , data mining , dimension (graph theory) , spatial analysis , function (biology) , am/fm/gis , representation (politics) , distribution management system , gis applications , engineering , remote sensing , geography , electrical engineering , mathematics , geodesy , evolutionary biology , pure mathematics , biology , politics , political science , law
According to the business requirements of distribution network planning, this paper deeply studies the existing simplified display algorithm of distribution network in GIS, constructs the distribution network model based on geographic information technology, develops the functions of supporting storage, display and display, and the function module of professional map editing for distribution network planning. The concept of spatiotemporal data and its application in GIS are innovatively put forward. The display research based on the status quo and the analysis and management technology of distribution network structure under planning state are carried out. The spatiotemporal representation, spatiotemporal evolution, and comparison of power grid are realized. The geographic image elements are matched and associated with equipment parameters to realize the integrated modeling of map and power grid, realize the penetration function from the map to equipment parameters and power grid indicators, and support the diagnosis and analysis of power grid-related indicators. Finally, a three-dimensional power map with time dimension, space dimension, and attribute dimension is constructed to provide geographic environment and equipment parameter data for power grid planning, site selection, and line selection.