Development of a MATLAB based power system simulator to investigate the impact of vehicle to grid (V2G) operation

Abstract

As the number of electric vehicles (EVs) is expected to increase significantly during the next few years, it is essential for the power system operators to study the possible aggregate impact of those vehicles and investigate ways to mitigate and control the resulting effect on the grid. In addition, these vehicles offer application as a grid scale energy storage system which could be used to provide different services to improve the performance of the grid. In this way, the energy stored in the EV batteries can be injected back into the grid using Vehicle to grid (V2G) technology. However, the actual impact of V2G participation on the long-term performance of EV batteries is yet to be investigated.
In this paper, the capabilities of the simulator developed by the authors to model the integration of EVs in the power system are described in detail. The simulator utilises the MATPOWER engine for power flow analysis within the MATLAB GUI environment. Currently, two power system networks, namely the IEEE30 test system and the United Kingdom Generic Distribution System (UKGDS), which represents a typical distribution grid in the UK, are included in the simulator. A number of scenarios can then be analysed with the simulator where individual EVs, EV aggregators and wind farms (as an example of typical embedded generators) can be added to the power system to find their impact on the network with or without utilisation of V2G technology. After performing a power flow analysis, the simulator is able to display a wide range of results, including power system parameters, EV parameters and aggregator results. The simulator is able to apply a range of control strategies to charge or discharge the EV batteries while it considers the vehicle movement within the network, battery capacity, State of Charge (SoC) and the grid operator and driver requirements. The authors are currently engaged in investigating and analysing V2G control strategies through comprehensive use of the simulator.

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Identifiers

ORCID for Mahdi Kiaee: orcid.org/0000-0002-4169-7188

ORCID for Andrew Cruden: orcid.org/0000-0003-3236-2535

ORCID for Suleiman Sharkh: orcid.org/0000-0001-7335-8503

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