Methodology for managing cost-effective demand response campaigns based on demand elasticity profiles

We develop and evaluate a methodology for running manual implicit and explicit Demand Response campaigns in order to improve the sustainability of smart grids. Initially, we introduce a flexibility profiling engine that relies on the correlation among end-user's consumption, prices and environmental conditions. Then, we investigate two mechanisms so that an Aggregator, acting as an intermediate between the Distribution System Operator or Retailer and the consumers, achieves the desired demand flexibility. More precisely we introduce: (i) a price-based mechanism that determines the new price that consumers will be paying during the DR campaign, and (ii) a reward-based mechanism that determines which set of consumers should participate in the campaign, along with the load flexibility to be asked from each one and the reward offered. The proposed methodology is evaluated using a publicly-available dataset. It is seen that the CES model achieves high estimation accuracy. Also, the economic metrics obtained using both price-based and reward-based mechanisms, are more favorable than the ones obtained by the dynamic prices actually applied and by a naive reward-based method rewards, respectively.