Profitably scheduling the energy hub of inhabitable houses considering electric vehicles, storage systems, revival provenances and demand side management through a modified particle swarm optimization

To increase power proficiency, reliability, and productive gain, hubs of energy are widely used as poly-transfer approaches. Therefore, the schedule can technically and commercially improve the inhabitable department. As one of the most prominent issues, system uncertainties can negatively affect energy hubs and inhabitable energy hubs. The random modality of power delivery over the provenance of revival power has been perceived as more of a supply-side ambiguity in inhabitable energy hubs than in modeling and demand-side studies, such as hybrid electric vehicles (PHEV). Accordingly, in terms of the demand-side management schedule by the energy storage system, this paper introduces the Energy Hub model for the indeterminacy of revival resources and electricity rates. The production and reduction scenarios were applied to model the indeterminacy of revival provenances. Subsequently, the proposed model would become an optimization problem and would benefit from the improved particle swarm algorithm with local and global operators. Finally, the proposed approach and model were discussed in a study system in different scenarios. The results showed that PHEV and thermal storage systems can act as suitable solutions to reduce utilization expenses of the inhabitable energy hub. Hence, implementing a demand-side management schedule could shift loads from peak hours to other times and avoid higher operational costs.