Effective and active consumers providing flexibility through Demand Response (DR) programs have three important aspects: rating each consumer according to previous participation, remuneration of that participation, and determining the rebound effect of consumption after the event. In this article, the authors design a rate to classify and select the proper participants for a DR event considering the context in which the event is triggered. The aggregator estimated the shifting of consumption to periods after the event is modeled, and the respective remuneration is estimated under different scenarios. This shifting can be done in several time frames in the future. The scenarios are developed to test the acceptable time range in which the load should be allocated according to the rebound effect. The results show that a higher time range can avoid huge peak consumption, optimizing the system operation with benefits for consumers, DSO, and the aggregator.