Low complexity approach for energy management in residential buildings

Energy management in residential buildings is one of the major keys for achieving the ambitious goals of efficient energy consumption, minimum carbon footprint, and reduced consumers energy expenditures. In this paper, we propose a novel residential energy management (REM) approach that is different from the conventional approaches. We formulate a REM problem with the objective to maximize the consumers utility under various practical constraints that include human interaction factor, unavailability of power supply, consumers preferences, and priorities. These constraints involve very high number of binary decision variables and result in extremely high search space that renders the solution of the REM problem prohibitively difficult. The application of standard optimization methods to this problem either require huge computational complexity or cannot find its optimal solution. Therefore, to optimally solve this problem, we propose a novel approach where we convert the original problem into an equivalent mathematical model with reduced number of constraints and decision variables. This significantly reduces the solution space of the problem, and standard optimization methods can be used for finding its optimal solution. The simulation conforms that the solution of the reformulated equivalent problem obtains optimal solution to the original REM problem with remarkably reduced computational complexity.