Energy storage model with gridable vehicles for economic load dispatch in the smart grid
Faculty of Health, Engineering and Science
School of Engineering
The intermittent nature of renewable energy sources (RESs) and unpredictable variable load demands have necessitated the inclusion of energy storage devices in the smart grid environment. Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs), with vehicle-to-grid capability, referred to as "gridable vehicles" (GVs), have become an option as storage devices. However, unsupervised use of GVs as storage devices presents new challenges due to concerns over battery lifetime and cost effectiveness of this two-way power transfer. These issues reduce the participation rate of GVs in the vehicle-to-grid discharge program. In this study, we present a system model, for GVs to act as distributed storage devices, which mitigates concerns over battery lifetime, and provides GV owners with a transparent cost-benefit analysis of their participation in the vehicle-to-grid discharge program. With this model in place, fuel and emissions cost has been reduced, as shown using particle swarm optimization. Simulation results show that up to 52% of GVs might be discharging at a net loss. In contrast, our proposed system ensures that no GVs are at loss when discharging to the grid. This factor alone is expected to increase the participation rate of GVs by a significant margin, and ensure economic load dispatch.