Optimal scheduling method of controllable loads in smart house considering forecast error

From the perspective of global warming suppression and depletion of energy resources, renewable energies, such as the solar collector (SC) and photovoltaic generation (PV), are getting attention in distribution systems. Houses with PV and heat pump (HP) systems are also gaining wide use recently in residential areas recently because of using time-of-use electricity pricing. Thus, optimal scheduling of the distributed energy resources (DER) is required to reduces the operational cost for the consumers, however DERs of then deviate from forecast data. Hence, optimal scheduling of these appliances may not be achieved due to uncertainty of the weather. In this paper, we propose an optimal scheduling method of controllable loads considering forecast error in the smart house, where HP, fixed battery and EV systems are used as controllable loads. The scenario based approach is applied in roder to solve the optimization problem involving the uncertainty. Furthermore, a novel electricity pricing system is also suggested in this paper. In order to confirm the proposed method is useful, and in to verify the effectiveness of the proposed system, MATLAB® is used for simulations.