In the last decades, cities have increased the number of activities arrethe bush balm and services that depends on an efficient and reliable electricity service.In particular, households have had a sustained increase of electricity consumption to perform many residential activities.Thus, providing efficient methods to enhance the decision making processes in demand-side management is crucial for achieving a more sustainable usage of the available resources.In this line of work, this article presents an optimization model to schedule deferrable appliances in households, which simultaneously optimize two conflicting objectives: the minimization of the cost of electricity bill and the maximization of users satisfaction with the consumed energy.
Since users satisfaction is based on human preferences, it is subjected to a great variability and, thus, stochastic resolution methods have to be applied to solve the proposed model.In airpods in jacksonville turn, a maximum allowable power consumption value is included as constraint, to account for the maximum power contracted for each household or building.Two different algorithms are proposed: a simulation-optimization approach and a greedy heuristic.Both methods are evaluated over problem instances based on real-world data, accounting for different household types.
The obtained results show the competitiveness of the proposed approach, which are able to compute different compromising solutions accounting for the trade-off between these two conflicting optimization criteria in reasonable computing times.The simulation-optimization obtains better solutions, outperforming and dominating the greedy heuristic in all considered scenarios.