Stochastic Optimization for Residential Demand Response With Unit Commitment and Time of Use

As compensation to power generation dispatch, demand response (DR) enables demand controllability by changing the consumers' electricity usage patterns, which can be used to reduce electricity cost, integrate renewable energy, and provide ancillary services. To reveal the benefits from residential DR, this study develops the following two approaches: optimal load aggregation under augmented time-of-use (TOU) pricing; and active DR participation in unit commitment (UC) under rewards. We have shown that plain TOU pricing is not a promising DR policy if residential customers are equipped with home energy management systems (EMSs). We, therefore, propose an augmented TOU by radial basis functions. With a 60% participation level, the proposed optimal load aggregation model under the augmented TOU can reduce the power generation cost by 24% and decrease the standard deviation of the load profile by 42%. However, these results can be affected by the customer's participation level, which is also quantitatively studied. Specifically, when the participation level exceeds 80%, this method becomes less efficient. The second proposed approach, a two-stage stochastic UC model with DR flexibility, reduces the power generation cost by 20% and decreases the standard deviation of the load profile by 77%. In addition, the inconvenience of DR participation is quantitatively evaluated, and a Pareto surface is developed, which can be used as a baseline for residential customers to set up the home EMS for DR implementation. Both the proposed mechanisms can be used to improve the energy efficiency by uncovering the residential DR potential.