Vehicle-to-grid and grid-to-vehicle : impact assessment and resource modelling to enable grid support

Abstract

The demand for energy is steadily increasing with its worldwide growing usage. International Energy Agency (IEA), the United States, has reported that transportation sector accounts for 30% of worldwide energy consumption and is the second largest source of CO2 emissions contributing to 20% of global Greenhouse Gases (GHG). It is envisaged that there will be an enormous increase in transportation energy consumption with continuously growing travel demand for personal vehicles. Thus, electrification of transportation sector with voluminous use of one of the most promising automobile technologies, the energy-efficient and environment- friendly state-of-the-art electric drive vehicles, is critical to reducing our dependence on expensive, polluting fossil fuel based conventional vehicles and GHG emissions. However, the mass adoption of Electric Vehicles (EV) will put an additional load on the existing power system and may adversely affect its operation by overloading or exceeding the limits of its various components. The preparedness of power grid is critical to see EVs as a strategic capital for the electricity sector and avoid any poor load management. Nonetheless, abreast technical and operational challenges associated with managing the charging demand caused by the penetration of large-scale EVs into the system, it offers a great deal of grid assistance opportunities such as renewable energy storage and ancillary services provision. In light of this, the objective of this thesis is to assess the grid level charging/discharging impacts and propose models to exploit the storage potential of the batteries of an aggregation of a large number of light-duty EVs, primarily the electric cars, for grid support services. The hypotheses developed presents the charging/discharging impacts and introduce grid assistance models through charging and discharging of EVs, exploring the technical and operational challenges in integrating this storage, a movable and changeable of its kind, with the power system. To ascertain whether the existing grid capacity will be able to support additional EV load with random charging, the assessment of charging load profiles based on the driving pattern of the owners is integral. The selection of charging power magnitude among the existent charging standards as well as the charging physics plays a crucial role in shaping the load profiles generated by the EVs. Thus, the initial step presents the development of charging load curves of EVs based on mobility attributes and charging protocols. In transportation, the average car is parked almost 95% of the time leaving enormous time margin during the day to exploit the storage potential of the battery for grid support services. This led the researchers to propose the Vehicle-to-Grid (V2G) mode of operation of EVs in which a proportion of energy stored in the battery (after accounting for driving consumption) can be injected back into the grid at the peaking periods. Based on this, the second stepinvolves realizing the V2G energy profiles with various discharge power levels for a defined mobility pattern. The V2G support is not only dependent on the number of vehicles available to support the grid but is also dependent on the heterogeneity of the aggregation where Battery Electric Vehicles (BEV) may contribute more to V2G than Plug-in Hybrid Electric Vehicles (PHEV), an important factor necessary to be incorporated to create any future robust model of EV dominated transportation system. The heterogeneity in the vehicles as well as in the mobility behavior is further incorporated to determine the Grid-to-Vehicle (G2V) and V2G power capabilities of the aggregation at different moments of parking under varying penetrations of the electric vehicles. The quantification of the effects of the simultaneous combination of resulting G2V and V2G profiles with the conventional load on hourly loading and electricity market price is presented taking IEEE Test Bus system as an example. The coordinated grid connection of EV aggregation can also be employed to provide shortterm ancillary services like regulation, thereby increasing the power system reliability and side by side forming a revenue stream for the grid-connected vehicles for the contracts made in the competitive services market. To test this, a simulative model for minute wise power scheduling during the charging and discharging phases is developed to obtain the MW capacity through a large pool of vehicles which can be contracted as the regulation capacity commitment in the ancillary services market. Considering the aspect of vehicles of changeable locations, two operational places, the workplace, and the home is selected as per the driving practices to simulate the V2G and G2V activities. The application of aggregation of the EV battery storage is also analyzed through a distinct charging (G2V) / discharging (V2G) coordination scheme to achieve the control over the peak shaving, valley filling and load levelling functions of the system operator. These functions simplify the load forecasting and dispatch exercises in the system operation by reducing the complexities associated with the oscillating load, and thereby the regulation up / down requirements. Additionally, this work also outlines the possible roles to be played by the key participants, comprising system operator, vehicle aggregator, EV supply equipment, and vehicle owner in a collaborative EV and electric power utility interfacing to manage the centrally dispatched EV aggregation.