Optimal pricing strategies in real-time electricity pricing environments: An Italian case study

The energy market has changed radically over the last decade, mainly due to an increased penetration of renewable energies. Now the end users have directly access to the energy market and can actively take part to the electricity market. Electricity customers can indeed modify their behavior through Demand Response (DR), namely by means of pricing strategies that support a change in the end-users habits. This can be accomplished through a "loads aggregator", a third party that collects the requests and signals for Active Demand-based services coming from the markets and the different power system participants. This paper describes a new framework able to optimally select the real-time pricing curves for the electricity customers. The algorithm uses a constrained optimization problem to generates the output curves, by using as objective function the aggregator's economic benefit maximization. A case study is performed to show the advantages/disadvantages of the proposed approach.