Load commitment in a smart home

Although demand response (DR) potentially brings miscellaneous advantages, it is currently faced with challenges in its implementation due to customers’ difficulty in manually responding to the time-varying prices. This paper presents an optimal and automatic residential load commitment (LC) framework to achieve the household minimum payment. Problem decision variables are the operating status of responsive appliances and charging/discharging cycles of battery storage and plug-in hybrid electric vehicles (PHEVs). Storage capability in residential centers provide the customers with this opportunity to not only supply the local demand during the high price hours but also sell the energy back to the utility. The optimization-based LC shifts the responsive loads to inexpensive periods which rationally coincide with the valley of consumption profile. As a matter of fact, the peak to average ratio (PAR) of the load profile would likely decrease which, although might be unappealing to the customers, is desirable from the utility viewpoint. Direct load control (DLC) is also modeled by using the proposed LC approach. In the DLC program, a customer receives a rather fair tariff allowing the utility to control a set of specific devices. Customer inconvenience is considered as the factor restricting a complete DLC realization. Numerical simulations are conducted to illustrate the proposed notions and to verify the efficiency of the developed model.

► This paper addresses the load commitment (LC) problem to schedule household appliances.
► The objective function of LC problem is minimizing the customer payment.
► Responsive appliances, battery storage, and plug-in hybrid electric vehicles are scheduled.
► Direct load control (DLC) is also modeled in the proposed LC approach.
► With LC realization, the customer payment is reduced while the peak load is controlled as well.