Predictive control offers significant advantages in nonlinear control, high thermal inertia, and
dynamic control. This article uses a Systematic Reviews and Meta-Analyses methodology to …

To balance the competing interests between economy, security, and computational burden
caused by the uncertainty of the electricity‑hydrogen integrated energy systems (EH-IESs), a …

Urban microgrids have become the main body of energy consumption in modern power
systems. To reduce carbon emissions, distributed generators (DGs), such as roof …

The large-scale integration of intermittent renewable energy resources introduces increased
uncertainty and volatility to the supply side of power systems, thereby complicating system …

Rapidly increasing distributed energy resources (DERs) bring more fluctuating output power
to the distribution network and put forward a higher requirement on local regulation …

Designing customized dynamic pricing is a promising way to incent consumers to adjust
their daily energy consumption behaviors. It helps manage flexible demand response …

The concern for privacy and scalability has motivated a paradigm shift to decentralized
energy management methods in microgrids. The absence of a central authority brings …

Currently, an increasing number of residential customers have access to distributed flexible
resources, including dispatchable or nondispatchable distributed generation and various …

This paper presents two novel deep reinforcement learning (DRL) approaches aimed at
solving complex power system control problems in a data-driven sense to maintain the …

The district cooling system (DCS) is a promising resource to smooth tie-line power
fluctuations in a grid-connected microgrid with high-penetration renewable generation …