|Title||Evaluation of distributed energy storage for ancillary service provision|
Researchers have proposed that distributed energy storage devices could be used to perform ancillary services for the electric grid. This work focuses on vehicle-to-grid and battery-to-grid distributed energy storage devices. In conceptual studies, distributed energy storage devices were shown to be able to accrue revenue for performing these grid stabilization services, and these revenues were used to show that the use of vehicle-to-grid and battery-to-grid can help to offset the initial increased capital cost of electric vehicles. These conceptual studies have assumed a command architecture that allows for a direct and deterministic communication between the grid system operator and the distributed energy storage devices. The first part of this thesis compares this direct, deterministic command architecture to an aggregative command architecture on the basis of the availability, reliability and value of the vehicle-to-grid provided ancillary services. This research incorporates a new level of detail into the modeling of vehicle-to-grid ancillary services by incorporating probabilistic vehicle travel models, time series ancillary services pricing, a consideration of ancillary services reliability. Results show that including an aggregating entity in the command and contracting architecture can improve the scale and reliability of vehicle-to-grid ancillary services, thereby making vehicle-to-grid ancillary services more compatible with the current ancillary services market. However, the aggregative architecture has the deleterious effect of reducing the revenue accrued by plug-in vehicle owners relative to the default architectures. The second part of this work investigates the effects of introducing battery state of charge and time series generation control signals. Results show that in order to integrate a vehicle-to-grid system into the existing markets and power grid the distributed energy storage system will require: 1) an aggregative architecture to meet current industry reliability standards, 2) the construction of low net energy automatic generation control signals, 3) a lower percent call for distributive energy storage systems even if the pool of contracted ancillary service resources gets smaller, 4) a consideration of vehicle performance degradation due to the potential loss of electrically driven miles, and 5) the incorporation of power-to-energy ratios. The third part of this work adapts the vehicle-to-grid model to a battery-to-grid system. Results show that if the automatic generation control signals contain low energy content, battery-to-grid has higher revenue potential than vehicle-to-grid due not having to account for vehicle driving behavior. Additionally, the third portion of this work proposed and performed high level analyses of operational options for battery-to-grid systems receiving automatic generation control signals with high energy content.
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