A Probabilistic Approach for the Optimal Sizing of Storage Devices to Increase the Penetration of Plug-in Electric Vehicles in Direct Current Networks
Elio Chiodo,
Maurizio Fantauzzi,
Davide Lauria and
Fabio Mottola
Additional contact information
Elio Chiodo: Department of Industrial Engineering, University of Naples Federico II, Naples 80125, Italy
Maurizio Fantauzzi: Department of Industrial Engineering, University of Naples Federico II, Naples 80125, Italy
Davide Lauria: Department of Industrial Engineering, University of Naples Federico II, Naples 80125, Italy
Fabio Mottola: Department of Engineering, University of Naples Parthenope, Naples 80143, Italy
Energies, 2018, vol. 11, issue 5, 1-20
Abstract:
The growing diffusion of electric vehicles connected to distribution networks for charging purposes is an ongoing problem that utilities must deal with. Direct current networks and storage devices have emerged as a feasible means of satisfying the expected increases in the numbers of vehicles while preserving the effective operation of the network. In this paper, an innovative probabilistic methodology is proposed for the optimal sizing of electrical storage devices with the aim of maximizing the penetration of plug-in electric vehicles while preserving efficient and effective operation of the network. The proposed methodology is based on an analytical solution of the problem concerning the power losses minimization in distribution networks equipped with storage devices. The closed-form expression that was obtained is included in a Monte Carlo simulation procedure aimed at handling the uncertainties in loads and renewable generation units. The results of several numerical applications are reported and discussed to demonstrate the validity of the proposed solution. Also, different penetration levels of generation units were analyzed in order to focus on the importance of renewable generation.
Keywords: energy storage; design optimization; plug-in electric vehicles; energy efficiency (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:5:p:1238-:d:146057
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