Optimal Power Scheduling for a Cooperative Network of Smart Residential Buildings

This paper attempts to contribute to the development of a new concept focused on a cooperative control scheme for a smart network of residential buildings (SNRB) and to demonstrate advantages of interconnections and coordination among a set of smart residential buildings (SRBs), by taking advantages of fluctuations of stochastic renewable sources and loads, and exploiting the operational flexibilities of thermal loads defined as the required hot water and desired buildings temperature. A comprehensive finite-horizon scheduling optimization problem is formulated to optimally control a SNRB using model predictive control (MPC) method, which integrates both forecasts and newly updated information. The cooperation is reached through a bidirectional communication infrastructure in the SNRB, where the master controller (MC) is available at the network level and in charge of coordinating and managing power in the SNRB. A MPC-based algorithm is used for the future scheduling of power exchanges, charge/discharge state of each energy storage device (ESD), the state of each micro-CHP and the charging state of each plug-in electric vehicle (PEV) available in the network. The MPC strategy is tested through case studies where the influences of both network topology and thermal loads on the operation of each SRB are analyzed via numerical results.