Modeling and Simulation of DC Microgrids for Electric Vehicle Charging Stations

Fabrice Locment and Manuela Sechilariu
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Fabrice Locment: Sorbonne University, Université de Technologie de Compiègne, EA 7284 AVENUES, Centre Pierre Guillaumat CS 60319, Compiègne 60203 Cedex, France
Manuela Sechilariu: Sorbonne University, Université de Technologie de Compiègne, EA 7284 AVENUES, Centre Pierre Guillaumat CS 60319, Compiègne 60203 Cedex, France

Energies, 2015, vol. 8, issue 5, 1-22

Abstract: This paper focuses on the evaluation of theoretical and numerical aspects related to an original DC microgrid power architecture for efficient charging of plug-in electric vehicles (PEVs). The proposed DC microgrid is based on photovoltaic array (PVA) generation, electrochemical storage, and grid connection; it is assumed that PEVs have a direct access to their DC charger input. As opposed to conventional power architecture designs, the PVA is coupled directly on the DC link without a static converter, which implies no DC voltage stabilization, increasing energy efficiency, and reducing control complexity. Based on a real-time rule-based algorithm, the proposed power management allows self-consumption according to PVA power production and storage constraints, and the public grid is seen only as back-up. The first phase of modeling aims to evaluate the main energy flows within the proposed DC microgrid architecture and to identify the control structure and the power management strategies. For this, an original model is obtained by applying the Energetic Macroscopic Representation formalism, which allows deducing the control design using Maximum Control Structure. The second phase of simulation is based on the numerical characterization of the DC microgrid components and the energy management strategies, which consider the power source requirements, charging times of different PEVs, electrochemical storage ageing, and grid power limitations for injection mode. The simulation results show the validity of the model and the feasibility of the proposed DC microgrid power architecture which presents good performance in terms of total efficiency and simplified control.

Keywords: DC microgrid; plug-in electric vehicle; self-consumption; modeling; simulation; Energetic Macroscopic Representation; Maximum Control Structure (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: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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