Real-time simulation of demand side management and vehicle to grid power flow in a smart distribution grid

The price per kilowatt-hour of energy delivered by the electric power utility varies as the total power demand supplied to the region it serves throughout the day. To save money and protect power system equipment, it may be necessary to schedule the energy consumed during these periods of high/critical demand and higher pricing. In this project, a number of demand-side management strategies (DSM) are tested and compared on a modified IEEE 37-bus distribution feeder model in real time using an OPAL-RT real time simulator. This study focuses on the use of battery electric vehicles (BEVs) as energy storage components of a smart-grid. A stochastic model is used to predict the location of BEVs and their state of charge (SOC) over a 24-hour period. During the high demand periods or fault conditions, a number of BEV users may connect to the grid and supply power by using vehicle-to-grid (V2G) power flow. This number depends on the level of consumer interest in participating in V2G service as well as the location and SOC of each vehicle. The results show that a power utility will benefit by offering incentives to consumers with BEVs that are available to supply power to the grid.