Residential energy demand response management algorithm considering consumer usage patterns

Demand Response (DR) is a key attribute to enhance the operation of smart grid. It aims to schedule the various appliances in residence to let their energy consumption match the real-time electricity price provided by smart grid. A residential energy DR management algorithm is presented on the basis of real-time home energy management systems (RHEMS). It defines the user target price (UTP) to indicate different user requirements, learns the comfortable working time (CWT) of the appliances in the house by logistic regression and learns the comfortable working power (CWP) of the appliances in the house by difference exponential smoothing. Thus, the presented algorithm dynamically adjusts the maximum power threshold (MPT), and then automatically arranges the appliances operation to achieve buildings economic energy consumption. Simulation results show that the presented algorithm can significantly reduce the power demand during peak price period while ensuring the user's comfort, and the total energy cost can be reduced by 16% compared with the user's expectation.