Adaptive Rescheduling of Energy Consumption Based on User Preferences for the Future Smart Grid

Abstract

In the future smart grid, Demand Side Management (DSM) will be implemented to facilitate utility companies and consumers in order to achieve mutual benefits such as minimizing total energy cost and reducing consumption peaks. The optimal energy consumption scheduling is calculated based on user preferences in advance, e.g., day-ahead schedules. Most of the prior works in the literature have reported good results under the assumption that users are committed to the optimal schedules and do not deviate from their preferences, which may not be true in practice. In this paper, we consider the implications of allowing users to change their preferences and request new schedules at any time. We propose single-user and multi-user adaptive rescheduling algorithms which address these changes in user preferences. The algorithms reschedule deviating energy consumption optimally thus reducing the total energy cost. Simulation results show that the total energy cost of the community can be reduced by as much as 11.4% in specific scenarios.