Modeling and simulation of demand aggregation in a dynamic pricing scenario

There is a growing need for a more active participation of the demand side in power systems. As large scale demand response of electricity, which comes from the industrial sector, has been today largely activated, focus is moving towards commercial and residential sectors. In these sectors almost an untapped pool of demand response still remains. Consumers in these sectors are relatively small and their number is great. They are not experts in electricity business. A widespread view is that their demand response can be activated by the help of a demand aggregator. Aggregator plays an important role in electricity market design, in both reducing utility’s investment on peak generation and improving electricity bill savings for customers. In this paper, the preliminary design of the aggregator has been discussed. The principal role of the aggregator consists in supervising the actions of customers at lower level and dispatching the consumption constraints so as to minimize customers’ energy expenses and respect customers’ constraints on comfort level. A demand scheduling model for price-based Demand Response is presented under two different real-time pricing scenarios: linear pricing scenario and TOU (time-of-use) pricing scenario. For linear pricing, the problem is formulated as a convex optimization problem and the optimal forecasted customer consumption profile is given as a water-filling solution with flat water levels. For TOU scenario, which is more applied these days, though it can be separated into different section of linear pricing problem, we use a linearization method to solve the ramping limitation problems in the different sections’ junction points caused by the scenario.