A view on deep reinforcement learning in system optimization
Many real-world systems problems require reasoning about the long term consequences of
actions taken to configure and manage the system. These problems with delayed and often …
actions taken to configure and manage the system. These problems with delayed and often …
Decentralized safe reinforcement learning for inverter-based voltage control
Inverter-based distributed energy resources provide the possibility for fast time-scale voltage
control by quickly adjusting their reactive power. The power-electronic interfaces allow these …
control by quickly adjusting their reactive power. The power-electronic interfaces allow these …
Load–frequency control: a GA-based multi-agent reinforcement learning
F Daneshfar, H Bevrani - IET generation, transmission & distribution, 2010 - IET
The load–frequency control (LFC) problem has been one of the major subjects in a power
system. In practice, LFC systems use proportional–integral (PI) controllers. However since …
system. In practice, LFC systems use proportional–integral (PI) controllers. However since …
CityLearn v1. 0: An OpenAI gym environment for demand response with deep reinforcement learning
Demand response has the potential of reducing peaks of electricity demand by about 20% in
the US, where buildings represent roughly 70% of the total electricity demand. Buildings are …
the US, where buildings represent roughly 70% of the total electricity demand. Buildings are …