Home energy management (HEM) systems optimize electricity demand of appliances
according to the price-based demand response (DR) programs. Undoubtedly, customer …

With the rise in household computing power and the increasing number of smart devices,
more and more residents are able to participate in demand response (DR) management …

In smart grids, demand-side management (DSM) has become an important topic since it can
reduce the total electricity cost by smart control and rescheduling of loads, meanwhile …

With the increase in global energy consumption, the demand-side management (DSM)
system has grown into an important research topic because of its ability to reduce the total …

This paper presents a hierarchical deep reinforcement learning (DRL) method for the
scheduling of energy consumptions of smart home appliances and distributed energy …

Home automation is seen as a potential pillar of the smart city revolution that combines
smart mobility, lifestyle and ecosystem governed by intelligent sensors connected to the …

In the current era, electricity demand has skyrocketed. Power grids have to face a lot of
uneven power demand daily. During a certain period in a day, the power demand peaks …

Considering the popularity of electric vehicles and the flexibility of household appliances, it
is feasible to dispatch energy in home energy systems under dynamic electricity prices to …

This paper proposes a novel framework for home energy management (HEM) based on
reinforcement learning in achieving efficient home-based demand response (DR). The …

With the development of a smart grid and smart home, massive amounts of data can be
made available, providing the basis for algorithm training in artificial intelligence …