Robust optimization for home-load scheduling under price uncertainty in smart grids

In this paper, the emerging problem of residential energy scheduling for smart grid under the energy-price uncertainty is investigated, where the prices randomly vary around nominal values with a known underlying distribution. The objective of the focused optimization problem is to minimize the user´s cost of energy consumption. The robust optimization methodology will be used to deal with the uncertainty programming. We schedule the amounts of charged/discharged energy of the energy storage devices varied continuously within each time slot, which is more realistic and cost-effective. In addition, the mathematical model we adopts here is more practical because we consider the linear dynamical model of the temperature-related appliances. The involvement of the price uncertainty makes our devised algorithm more robust. Simulation results illustrate that our proposed new scheme is more effective than the conventional method without smart grid in terms of total energy cost.