A site selection framework for urban power substation at micro-scale using spatial optimization strategy and geospatial big data

Yao Yao; Chenqi Feng; Jiteng Xie; Xiaoqin Yan; Qingfeng Guan; Jian Han; Jiaqi Zhang; Shuliang Ren; Yuyun Liang; Peng Luo

doi:10.1111/tgis.13093

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A site selection framework for urban power substation at micro-scale using spatial optimization strategy and geospatial big data

Journal article

Peer reviewed

A site selection framework for urban power substation at micro-scale using spatial optimization strategy and geospatial big data

Yao Yao, Chenqi Feng, Jiteng Xie, Xiaoqin Yan, Qingfeng Guan, Jian Han, Jiaqi Zhang, Shuliang Ren, Yuyun Liang and Peng Luo

Transactions in GIS, Vol.27(6), pp.1662-1679

09/01/2023

DOI: 10.1111/tgis.13093

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Abstract

The world is facing more energy crises due to extreme weather and the rapidly growing demand for electricity. Siting new substations and optimizing the location of existing ones are necessary to address the energy crisis. The current site selection lacks consideration of spatial and temporal heterogeneity in urban power demand, which results in unreasonable energy transfer and waste, leading to power outages in some areas. Aiming to maximize the grid coverage and transformer utilization, we propose a multi-scene micro-scale urban substation siting framework (UrbanPS): (1) The framework uses multi-source big data and the machine learning model to estimate fine-scale power consumption for different scenarios; (2) the region growing algorithm is used to divide the power supply area of substations; and the (3) location set coverage problem and genetic algorithm are introduced to optimize the substation location. The UrbanPS was used to perform siting optimization of 110 kV terminal substations in Pingxiang City, Jiangxi Province. Results show that the coverage and utilization rate of the optimization results under different power consumption scenarios are close to 99%. We also found that the power can be saved by dynamic regulation of substation operation.

Geography

Social Sciences

Details

Title: Subtitle: A site selection framework for urban power substation at micro-scale using spatial optimization strategy and geospatial big data
Creators: Yao Yao - China University of Geosciences
Chenqi Feng - China University of Geosciences
Jiteng Xie - China University of Geosciences
Xiaoqin Yan - China University of Geosciences
Qingfeng Guan - China University of Geosciences
Jian Han - State Grid Corporation of China (China)
Jiaqi Zhang - China University of Geosciences
Shuliang Ren - Peking University
Yuyun Liang - China University of Geosciences
Peng Luo - University of Oxford
Resource Type: Journal article
Publication Details: Transactions in GIS, Vol.27(6), pp.1662-1679
DOI: 10.1111/tgis.13093
ISSN: 1361-1682
eISSN: 1467-9671
Publisher: Wiley
Number of pages: 18
Grant note: National Key Research and Development Program of China; National Key Research & Development Program of China; National Key Technology R&D Program National Natural Science Foundation of China; National Natural Science Foundation of China (NSFC) Alibaba Innovative Resarch Project Scientific Research Program of the Department of Natural Resources of Hubei Province State Key Laboratory of Resources and Environmental Information System
Language: English
Date published: 09/01/2023
Academic Unit: School of Earth, Environment, and Sustainability
Record Identifier: 9985219301602771

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