Maximizing the profit of a load aggregator by optimal scheduling of day ahead load with EVs

This paper proposes optimal scheduling of imported power of a load aggregator (LA) with the utilization of electric vehicles (EVs) to maximize its profit. As with the increase of renewable energy resources, electricity price in competitive market becomes more uncertain and on the other hand with the penetration of renewable distributed generators in the distribution network the predicted load of an LA also becomes uncertain in real time. Though there is uncertainties in both load and price but the use of EVs storage capacity can make the operation of load aggregator flexible. LA submits its offer to day-ahead market based on predicted loads and optimized use of its EVs to maximize its profit as well as in real time operation it uses its energy storage capacity such as way that it can maximize its profit. In this project load aggregators profit maximization algorithm is formulated and the optimization problem is solved with the help of a MATLA based optimization tool CVX (convex). As in real time operation the forecasted loads differ from actual load, the mismatches are settled in real time balancing market. Simulation results compare the profit of an LA with a hypothetical group of 1000 EVs and without EVs.