**3. Targeting Customers for Incentive DR Using a Two-stage Load Profile Clustering Method**

Selecting and recruiting appropriate customers for DR programs is essential for the successful operation of incentive-based DR. DR potential can be estimated by analyzing customer load characteristics. In this study, we derived adequate customer groups for residential DR from demand data through the load profile segmentation. There are many methods for clustering such as k-means, SOM, fuzzy clustering, Gaussian Mixture Models (GMMs), and hierarchical clustering. We adopted k-means methods in view of simplicity and accuracy, and designed load profile segmentation framework as two-stage methodology considering load characteristics in the first step and load profile value in the second step.
