Configuration of the Actor and Critic Network of the Deep Reinforcement Learning controller for Multi-Energy Storage System

The computational burden and the time required to train a deep reinforcement learning (DRL) can be appreciable, especially for the particular case of a DRL control used for frequency control of multi-electrical energy storage (MEESS). This paper presents an assessment of four training configurations of the actor and critic network to determine...

Controller to enable the enhanced frequency response services from a multi-electrical energy storage system

The increased adoption of renewable energy generation is reducing the inertial response of the Great Britain (GB) power system, which translates into larger frequency variations in both transient and pseudo-steady-state operation. To help mitigate this, National Grid, the transmission system operator in GB, has designed a control scheme...