How important is fast-charging station modelling in distribution grid planning? Global sensitivity analysis of grid investment model output

In this article, we address the problem of how to consider load demand from fast-charging stations (FCS) of electric vehicles in distribution grid planning. As the electrification of the transport sector proceeds, connection of charging stations becomes relevant in an increasing number of grid planning cases. However, as many of the inputs and assumptions to distribution grid planning studies are associated with uncertainty, it is not clear how important the modelling of FCSs is for the estimated grid investment costs and the risk of over- and underinvestment in grid capacity. To address this, we apply global sensitivity analysis (GSA) to a grid investment optimization model, which allows us to rank the input factors according to their contribution to the output uncertainty. A voltage-constrained 22 kV distribution grid with expected connection of a FCS is used as case study. The results of the sensitivity analysis show that the uncertainty of the voltage limit planning criterion and the placement of the FCS in the grid, are responsible for most of the output variance of the calculated present value costs of grid investments. This indicates that, to improve grid investment decisions, it is more important to select an appropriate voltage limit and have knowledge about the location of new FCSs, than to improve the estimates of other FCS-related input parameters. In the paper we discuss the use of GSA for guiding data gathering and modelling efforts, leading to improved models and analyses for electric vehicle integration and distribution grid planning. • Global Sensitivity Analysis is used on an investment planning case for a distribution grid with connection of a Fast-Charging Station. • Two variance-based and one moment-independent sensitivity analysis methods are used to validate the results. • The results show that the FCS location is the most important input factor, followed by the planning criterion (voltage planning limit) set by the planner. • The most important FCS-related input factors besides the FCS location, are the responsibility factor and installed capacity. • The results are useful for prioritization of modelling and data gathering efforts.

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Publication Details

Journal
Sustainable Energy Grids and Networks
Published
2025-05-09
DOI
https://doi.org/10.1016/j.segan.2025.101721
Citations
2
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
1.46
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article

How important is fast-charging station modelling in distribution grid planning? Global sensitivity analysis of grid investment model output

Aurora Fosli Flataker, Iver Bakken Sperstad, Magnus Korpås, Rubi Rana
2 citations
Sustainable Energy Grids and Networks
Integrated Energy Systems Optimization
1.46
article

How important is fast-charging station modelling in distribution grid planning? Global sensitivity analysis of grid investment model output

Aurora Fosli Flataker, Iver Bakken Sperstad, Magnus Korpås, Rubi Rana
article en
2 citations

Abstract

In this article, we address the problem of how to consider load demand from fast-charging stations (FCS) of electric vehicles in distribution grid planning. As the electrification of the transport sector proceeds, connection of charging stations becomes relevant in an increasing number of grid planning cases. However, as many of the inputs and assumptions to distribution grid planning studies are associated with uncertainty, it is not clear how important the modelling of FCSs is for the estimated grid investment costs and the risk of over- and underinvestment in grid capacity. To address this, we apply global sensitivity analysis (GSA) to a grid investment optimization model, which allows us to rank the input factors according to their contribution to the output uncertainty. A voltage-constrained 22 kV distribution grid with expected connection of a FCS is used as case study. The results of the sensitivity analysis show that the uncertainty of the voltage limit planning criterion and the placement of the FCS in the grid, are responsible for most of the output variance of the calculated present value costs of grid investments. This indicates that, to improve grid investment decisions, it is more important to select an appropriate voltage limit and have knowledge about the location of new FCSs, than to improve the estimates of other FCS-related input parameters. In the paper we discuss the use of GSA for guiding data gathering and modelling efforts, leading to improved models and analyses for electric vehicle integration and distribution grid planning. • Global Sensitivity Analysis is used on an investment planning case for a distribution grid with connection of a Fast-Charging Station. • Two variance-based and one moment-independent sensitivity analysis methods are used to validate the results. • The results show that the FCS location is the most important input factor, followed by the planning criterion (voltage planning limit) set by the planner. • The most important FCS-related input factors besides the FCS location, are the responsibility factor and installed capacity. • The results are useful for prioritization of modelling and data gathering efforts.

Sustainable Energy Grids and NetworksVol. 43
SINTEF (NO), SINTEF Energy Research (NO), General Electric (Norway) (NO)
Openalex Percentile: Top 18%
Integrated Energy Systems Optimization
1.46
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