Adaptive Load Shedding for Grid Emergency Control via Deep Reinforcement Learning

Understand

Emergency control, typically such as under-voltage load shedding (UVLS), is broadly used to grapple with low voltage and voltage instability issues in practical power systems under contingencies.

• However, existing emergency control schemes are rule-based and cannot be adaptively applied to uncertain and floating operating conditions.
• This paper proposes an adaptive UVLS algorithm for emergency control via deep reinforcement learning (DRL) and expert systems.
• We first construct dynamic components for picturing the power system operation as the environment.