Heuristic Scheduling Algorithm for Load Shift DSM Strategy in Smart Grids and IoT Scenarios

Smart Grids (SG) contribute to the modernization of the current electric grid. Among many features, it includes the demand side management (DSM) strategies which deal with the optimization of the power consumption patterns and the efficient use of energy. These strategies play an important role in both the final cost of energy and the control of the peak to average power ratio (PAPR). This paper reviews the main strategies of DSM and proposes an algorithm for a multi-objective optimization (MOO) DSM problem based on the day-ahead load-shifting strategy of scheduling. A discrete time varying model for the price of energy over a day is considered. A greedy search algorithm with limited complexity is employed in order to perform scheduling on the controllable loads, aiming for the minimization of both the total energy daily cost and the PAPR. The loads considered have different average power values and time-constrained allowable intervals to be powered on. The proposed algorithm can deal with the constraints ensuring that all loads will be scheduled and presenting satisfactory results in terms of cost and PAPR minimization.