Estimating Participation Abilities of Industrial Customers in Demand Response Programs: A Two-Level Decision-Making Tree Analysis

Industrial loads play an important role in the success of demand response programs (DRPs). However, these programs may lead to consumers' inconvenience which can overshadow their practicality. In response, this paper provides a two-level decision-making tree approach to effectively determine the participation abilities of different industrial processes in DRPs considering various features and abilities of these customers. The first level of this framework introduces some classifying variables by which a basic criterion is extracted to classify different industrial processes applying the analytic hierarchy process (AHP). A participation factor is then introduced in level II of the suggested decision tree to estimate the level of participation for different classes attained in Level I. Finally, a desirability coefficient is formulated, offering the system operators an efficient indicator to verify the attractiveness of different incentive-based programs in the viewpoint of industrial customers. Implementing the presented framework on industrial customers of a region in Iran, it is shown that applying this method lends the decision-makers a hand in practically and effectively introduce DRPs for industrial customers.