1. A method comprising: obtaining energy consumption information representative of energy consumption behaviors of multiple customers, the energy consumption information including past weather information of respective geographical regions corresponding to each of the multiple customers and energy usage of the multiple customers including a number of energy consumption peaks and time frames for each of the energy consumption peaks for each of the multiple customers; grouping the multiple customers into multiple different clusters based on the energy consumption behaviors of the multiple customers including grouping customers with a same number of energy consumption peaks in same respective time periods in a same cluster of the multiple different clusters; obtaining predicted future weather information for the respective geographical regions; aggregating the predicted future weather information to reduce an amount of weather information and unify the weather information to a specified sampling frequency; generating an energy consumption model for each different cluster of the multiple different clusters to enable forecasting of energy demand of the multiple customers, the energy consumption model generated based on the predicted future weather information for the customers in the cluster and the energy consumption behavior of the multiple customers for each different cluster of the multiple different clusters; estimating energy consumption for one customer in each of the clusters of the multiple different clusters using the respective energy consumption models; multiplying each estimated energy consumption by a number of customers in a corresponding cluster of the multiple different clusters to determine a total estimated energy consumption; obtaining a load modification criterion; simulating, using an energy forecaster, an effect of demand response (DR) signals on customers selected from different clusters of the multiple different clusters, the energy forecaster using the generated energy consumption model associated with the cluster of each selected customer; and sending DR signals to the selected customers at selected times based on the simulations associated with each cluster of the multiple different clusters in order to meet the load modification criterion, wherein energy consumption behaviors of at least some of the selected customers at selected times are changed in response to the sent DR signals.