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This paper presents a control framework for building demand response based on a comprehensive study of building loads. Building loads are divided into two categories according to their capabilities of adjusting their own power consumption, and it is necessary to consider loads of both categories in demand response. In this paper, in-house loads are classified into demand response loads, such as HVACs and PHEVs, and user-dictated loads which is normally utilized stochastically in a user-dictated manner. Subsequently, a comprehensive load profile is presented, making it possible for load prediction and load balancing capacity estimation. Furthermore, load and electricity price forecast in day-ahead market is introduced to the control scheme, along with a real-time adjustment strategy that corrects for the error in prediction. Simulation results prove the multilevel control framework to be effective, and variation in demand response capacity over time is fully considered and estimated.