Markov processes

Two-Stage Deep Reinforcement Learning for Inverter-Based Volt-VAR Control in Active Distribution Networks

Model-based Vol/VAR optimization method is widely used to eliminate voltage violations and reduce network losses. However, the parameters of active distribution networks(ADNs) are not onsite identified, so significant errors may be involved in the …

Bi-Level Off-policy Reinforcement Learning for Two-Timescale Volt/VAR Control in Active Distribution Networks

In Volt/Var control (VVC) of active distribution networks (ADNs), both slow timescale discrete devices (STDDs, e.g. on-load tap changers) and fast timescale continuous devices (FTCDs, e.g. distributed generators) are involved and should be …

Exploiting the Flexibility Inside Park-Level Commercial Buildings Considering Heat Transfer Time Delay: A Memory-Augmented Deep Reinforcement Learning Approach

The energy consumed by commercial buildings for heating and cooling is significantly increased. To better cope with the uncertainty introduced by the high penetration of renewable generation units, exploiting the potential flexibility of commercial …