Estimating primary substation boundaries and the value of mapping Great Britain's electrical network infrastructure

Localised data aggregation in many countries including Great Britain (GB) is typically performed at a geographical level with polygon boundaries that have a robust and trusted governance system in place. This means there is confidence in a process to create a set of polygons that have unique identifiers coupled to geographical areas, and the ability to have these updated through a defined code of practice. Examples found across many countries are in the delivery of post, such as post codes and zip codes, and of the definition of census areas and municipal boundaries. The confidence in these boundaries allows different data to be aggregated by third parties, which itself provides greater amounts of data over comparable geographical areas to enhance wider analysis and decision making. As helpful as these polygons are for certain types of analyses, they are not specifically defined for energy systems analysis. Here we combine publicly available datasets published from the six regional electricity Distribution Network Operators of GB to produce a new geospatial dataset with 4436 unique polygons defining the areas served by electrical primary substations. An example demonstrating the value of these polygons is given to link these polygons with postcode level open government datasets on domestic energy consumption (2015–2020) from the Department of Energy Security and Net Zero (DESNZ). The resulting new data reflects energy statistics aggregated to the geographical areas served by each primary electrical substation across Great Britain. The significant value of the generated data is demonstrated by the quantification of the domestic annual heating demand presently met by natural gas across different primary substation areas which varies from an average of 5100 kWh to 28,900 kWh per property. This highlights how the rate of electrical capacity expansion will have to differ by geography under an electrified heating scenario. Therefore, we believe there is a compelling argument for all countries to set up processes to create and update polygons that have a meaningful relationship to energy systems. This would allow more accurate energy systems analysis to be performed, ultimately leading to an accelerated or potentially lower cost transition to a net zero world. • Creation of valuable open dataset mapping Great Britain's primary substation areas. • Aggregation of domestic energy consumption to all primary substation boundaries. • Insights for industry that can improve consistency of geospatial electrical data. • Extending approach to all energy networks with monitoring enables digital twins. • This technique evaluates decarbonisation strategies at high spatial resolution.

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Publication Details

Journal
Applied Energy
Published
2024-08-31
DOI
https://doi.org/10.1016/j.apenergy.2024.124242
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Estimating primary substation boundaries and the value of mapping Great Britain's electrical network infrastructure

Edward Barbour, Bruno Cárdenas, Joseph Day, Seamus D. Garvey et al.
1 links
Applied Energy
Geographic Information Systems Studies
article

Estimating primary substation boundaries and the value of mapping Great Britain's electrical network infrastructure

Edward Barbour, Bruno Cárdenas, Joseph Day, Seamus D. Garvey, Grant Wilson, Andrew J. Urquhart, Daniel L. Donaldson, C. R. Jones
article en

Abstract

Localised data aggregation in many countries including Great Britain (GB) is typically performed at a geographical level with polygon boundaries that have a robust and trusted governance system in place. This means there is confidence in a process to create a set of polygons that have unique identifiers coupled to geographical areas, and the ability to have these updated through a defined code of practice. Examples found across many countries are in the delivery of post, such as post codes and zip codes, and of the definition of census areas and municipal boundaries. The confidence in these boundaries allows different data to be aggregated by third parties, which itself provides greater amounts of data over comparable geographical areas to enhance wider analysis and decision making. As helpful as these polygons are for certain types of analyses, they are not specifically defined for energy systems analysis. Here we combine publicly available datasets published from the six regional electricity Distribution Network Operators of GB to produce a new geospatial dataset with 4436 unique polygons defining the areas served by electrical primary substations. An example demonstrating the value of these polygons is given to link these polygons with postcode level open government datasets on domestic energy consumption (2015–2020) from the Department of Energy Security and Net Zero (DESNZ). The resulting new data reflects energy statistics aggregated to the geographical areas served by each primary electrical substation across Great Britain. The significant value of the generated data is demonstrated by the quantification of the domestic annual heating demand presently met by natural gas across different primary substation areas which varies from an average of 5100 kWh to 28,900 kWh per property. This highlights how the rate of electrical capacity expansion will have to differ by geography under an electrified heating scenario. Therefore, we believe there is a compelling argument for all countries to set up processes to create and update polygons that have a meaningful relationship to energy systems. This would allow more accurate energy systems analysis to be performed, ultimately leading to an accelerated or potentially lower cost transition to a net zero world. • Creation of valuable open dataset mapping Great Britain's primary substation areas. • Aggregation of domestic energy consumption to all primary substation boundaries. • Insights for industry that can improve consistency of geospatial electrical data. • Extending approach to all energy networks with monitoring enables digital twins. • This technique evaluates decarbonisation strategies at high spatial resolution.

Applied EnergyVol. 376
University of Nottingham (GB), Loughborough University (GB), University of Portsmouth (GB), University of Birmingham (GB)
Alan Turing Institute, Engineering and Physical Sciences Research Council
Industry, innovation and infrastructure
Openalex Percentile: Top 77%
Geographic Information Systems Studies
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