Title :
Aggregated load scheduling for residential multi-class appliances: Peak demand reduction
Author :
Azar, Armin Ghasem ; Jacobsen, Rune Hylsberg ; Qi Zhang
Author_Institution :
Dept. of Eng., Aarhus Univ., Aarhus, Denmark
Abstract :
The Smart Grid represents an unprecedented opportunity to move the energy industry into a new era. In this context, Demand Response programs provide mechanisms to regulate the power demand through load control according to conditions of the supply side, where consumers can efficiently schedule the operation of their appliances. This paper has proposed an efficient local load scheduling optimization strategy for residential multi-class multi-constraint appliances by shifting and interrupting load requests to flatten the aggregated consumption. One scenario for each smart house, including the desirable usage schedule of its appliances in a 24-hour period, is considered. The proposed strategy has supposed a time-independent constant electricity consumption threshold, imposed by the grid stability management, in each time interval. The demand response system attempts to optimally schedule the received load requests over time, aiming at flattening the aggregated consumption meanwhile, maximizing satisfaction of consumers. The results have indicated that decreasing the electricity consumption threshold up to 60% of the maximum peak demand results in significant aggregated consumption flattening and also admissible delay in appliance reception.
Keywords :
demand side management; domestic appliances; home automation; scheduling; smart power grids; aggregated load scheduling; demand response program; electricity consumption threshold; energy industry; grid stability management; load control; load request interruption; load scheduling optimization strategy; peak demand reduction; power demand; residential multiclass multiconstraint appliance; smart grid; smart house; timeindependent constant electricity consumption; Delays; Electric vehicles; Home appliances; Lighting; Optimization; Schedules; Scheduling; Load Management; Scheduling; Smart Grid; Supply and Demand;
Conference_Titel :
European Energy Market (EEM), 2015 12th International Conference on the
DOI :
10.1109/EEM.2015.7216702