This paper proposes an optimal charging strategy for plug-in electric vehicles (PEVs) to be used in electric distribution networks. The optimization algorithm is made up of two phases: 1) an optimal power flow calculation; and 2) a linear optimization. The former, while taking into account the power system technical constraints, sets the upper bounds to the recharge power for each vehicle and the latter defines the recharge profiles of each PEV. In order to test the effectiveness of the optimization algorithm, a case study was set up. The connection of 300 PEVs to the Conseil International des Grands Réseaux Électriques (CIGRÉ) European low voltage benchmark network has been simulated. The proposed algorithm has been compared with a nonoptimal charging strategy, which assigns a flat charging profile by dividing the energy requested by the desired recharge time. The results show that the optimization algorithm both complies with the energy requests set by the end users and with the technical operation limits of the network. This allows for PEVs to provide a basic—although of paramount importance—service to the grid: the smart charge.

A Two-Stage Margin-Based Algorithm for Optimal Plug-in Electric Vehicles Scheduling

GRILLO, SAMUELE;
2015-01-01

Abstract

This paper proposes an optimal charging strategy for plug-in electric vehicles (PEVs) to be used in electric distribution networks. The optimization algorithm is made up of two phases: 1) an optimal power flow calculation; and 2) a linear optimization. The former, while taking into account the power system technical constraints, sets the upper bounds to the recharge power for each vehicle and the latter defines the recharge profiles of each PEV. In order to test the effectiveness of the optimization algorithm, a case study was set up. The connection of 300 PEVs to the Conseil International des Grands Réseaux Électriques (CIGRÉ) European low voltage benchmark network has been simulated. The proposed algorithm has been compared with a nonoptimal charging strategy, which assigns a flat charging profile by dividing the energy requested by the desired recharge time. The results show that the optimization algorithm both complies with the energy requests set by the end users and with the technical operation limits of the network. This allows for PEVs to provide a basic—although of paramount importance—service to the grid: the smart charge.
2015
Battery recharging optimization; optimal dispatching; optimal power flow; plug-in electric vehicle; smart charge; elettrici
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/886043
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