The paper's state-of-the-art review focuses on an in-depth evaluation of smart home energy
management systems which employ reinforcement learning-based methods to integrate …

With the rapid development of renewable energy, photovoltaic energy storage systems (PV-
ESS) play an important role in improving energy efficiency, ensuring grid stability and …

With the development of energy Internet and intelligent buildings, the interactions of supply
and demand sides of integrated energy system (IES) offer an attractive route for flexible …

In a multi-regional integrated energy system (MIES), optimal scheduling under random
renewable supply and user demand is crucial to promote the process of carbon neutrality …

The increasing load demands and the extensive usage of renewable energy in integrated
energy systems pose a challenge to the most efficient scheduling of integrated energy …

Energy predictions for buildings are the basis for energy efficiency and the implementation
of smart technologies to cope with operational and energy planning issues in buildings …

Abstract The use of Deep Reinforcement Learning (DRL) in building energy management is
often hampered by data efficiency and computational challenges. The long training time …

The concepts of visual comfort and lighting quality are among key components of
architectural design. Although the building industry shows significant signs of progress in …

Low-carbon parks composed of concentrated and contiguous low-carbon buildings has the
characteristics of the high proportion of renewable energy penetration and low-carbon …

Energy depletion and rising demand cause a demand–supply imbalance and power system
instability. Centralized energy production makes the system less reliable and less efficient …