A Stochastic Approach to Optimizing Energy Management in Smart Homes with PHEVsand Distributed Energy Resources

With the growing integration of distributed generation units, advancements in energy storage systems(ESS), and the increasing adoption of plug-in hybrid electric vehicles (PHEVs) in smart homes, there isa pressing need to develop effective strategies for coordinating these energy resources. The aim is tobalance the objectives of all stakeholders within the microgrid (MG) framework. In this scenario, theprimary objective of the operator is to implement an efficient energy management plan that not onlyoptimizes system performance but also ensures the comfort and satisfaction of the home's residents.Thisresearch introduces an innovative framework for managing energy in smart buildings equipped withplug-in hybrid electric vehicles and energy storage systems under demand response programs (DRP).The proposed model optimizes the scheduling of household appliances, PHEVs, and ESS to minimizeoperating costs and enhance energy efficiency. By employing stochastic programming, the frameworkaccounts for renewable generation uncertainty and consumer preferences. Simulation resultsdemonstrate a reduction of 37% in operational costs and a 10% improvement in critical load supplyreliability. The findings highlight the model's potential to balance energy supply and demand whilepromoting sustainable energy usage in microgrid environments.

A Stochastic Approach to Optimizing Energy Management in Smart Homes with PHEVsand Distributed Energy Resources Keywords:

Smart home , MG , electric vehicles , demand response , energy storage