A preference-based multi-objective demand response mechanism

The demand response (DR) aims to balance the purveyance and demand of electricity to maximize the reliability and efficiency of the energy supply process in the electrical power system (EPS). However, one of the main impediments to the insertion of DR in the residential context is the need of programming the use of various electrical appliances and the scheduling of renewable resources and storage system in the same time interval, that requires a range of specific knowledge and time availability of the consumer to handle the various home appliances. This article presents a preference-based multi-objective optimization model based on real-time electricity price to solve the problem of optimal residential load management. The proposal’s purpose is to minimize both the electricity consumption associated cost and the inconvenience caused to consumers. The proposed model was formalized as a nonlinear programming problem subject to a set of constraints associated with the consumption of electrical energy and operational aspects related to the residential appliance categories. The proposed multi-objective model was solved computationally by the Constrained Many-Objective Non-Dominated Sorted Genetic Algorithm (NSGA-III) to determine the new scheduling of residential appliances, renewable energy resources, and energy storage system utilization for the entire time horizon, considering consumer preferences. The results show that the multi-objective DR model proposed using the NSGA-III technique can minimize the total cost associated with energy consumption as well as reduce the inconvenience of consumers, besides helping consumers to take advantage of DR’s benefits without requiring manual intervention.