Performance evaluation of power demand scheduling scenarios in a smart grid environment

• We present and analyze power demand scheduling scenarios for peak demand reduction.
• All scenarios consider that consumers are equipped with a specific appliances’ number.
• The energy scheduling scenario assumes power compression for peak demand reduction.
• The task scheduling scenarios postpone power requests to reduce peak demand.
• Our models achieve better power consumption performance, over the state of the art.

Smart grid technology is considered as the ultimate solution to challenges that emerge from the increasing power demands, the subsequent increase in pollution, and the outmoded power grid infrastructure. The successful implementation of the smart grid is mainly driven by the utilization of modern communication technologies, which aim at the provision of advanced demand side management mechanisms, such as demand response. In this paper, we present and analyze four power-demand scheduling scenarios that aim to reduce the peak demand in a smart grid infrastructure. The proposed scenarios consider that each consumer is equipped with a certain number of appliances of different power demands and different operational times, while the percentage of consumers that agree to participate in the demand scheduling program is also incorporated in our models. We provide the analysis for the determination of the peak demand in a residential area, based on recursive formulas. The proposed analysis is validated through simulations; the accuracy of the analytical models is found to be quite satisfactory. Moreover, we unveil the consistency and necessity of the proposed scenarios and corresponding analytical models.