The widespread increase of electric vehicles sales forces Distribution System Operators to evaluate and improve the capability of the distribution system to host distributed charging infrastructures. This paper suggests a procedure to identify grid reinforcements to increase the capability of the system as well as to evaluate the current hosting capacity. The developed procedure is based on a micro-genetic algorithm and its solution identifies the optimal grid reinforcements to be planned on a Medium Voltage network in order to increase the number of charging stations that can be connected. The procedure requires the model of the network, the yearly load profiles of the secondary substations and the algorithm output takes into account an envisioned budget to be spent, avoiding network violations and an iniquitous distribution of the charging stations. The procedure was firstly validated considering a 70 nodes test network. Furthermore, the real case study of the distribution system of the city of Terni was assessed focusing on one of its main subnetwork with 471 nodes; the procedure was exploited to assess the current hosting capacity and to estimate that on average 0.01 M€ has to be spent on grid reinforcements in order to further increase hosting capacity.

Developing a public EV charging infrastructure in a DSO's perspective: Hosting capacity assessment and grid reinforcements on a real case study

Carere, F.;
2023-01-01

Abstract

The widespread increase of electric vehicles sales forces Distribution System Operators to evaluate and improve the capability of the distribution system to host distributed charging infrastructures. This paper suggests a procedure to identify grid reinforcements to increase the capability of the system as well as to evaluate the current hosting capacity. The developed procedure is based on a micro-genetic algorithm and its solution identifies the optimal grid reinforcements to be planned on a Medium Voltage network in order to increase the number of charging stations that can be connected. The procedure requires the model of the network, the yearly load profiles of the secondary substations and the algorithm output takes into account an envisioned budget to be spent, avoiding network violations and an iniquitous distribution of the charging stations. The procedure was firstly validated considering a 70 nodes test network. Furthermore, the real case study of the distribution system of the city of Terni was assessed focusing on one of its main subnetwork with 471 nodes; the procedure was exploited to assess the current hosting capacity and to estimate that on average 0.01 M€ has to be spent on grid reinforcements in order to further increase hosting capacity.
2023
distribution system
hosting capacity
grid reinforcement
electric vehicle
charging stations
micro genetic algorithm
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12607/46213
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