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Mostafa Sahraei-Ardakani ; Mingxi Liu (Ed.)This paper proposes a data-driven adaptive coordination of damping controllers to enhance power system stability. The coordination uses wide-area frequency measurements to select the switching status (on/off) of damping controllers (DC) enabled in electronically-interfaced resources (EIR). This is done by using the total action (TA), a dynamic performance measure of the oscillation energy related to the synchronous generators; and deep neural networks (DNNs), a powerful learning algorithm capable of providing accurate model regression between the grid measurements and the TA. The concept is tested in the Western North America Power System (wNAPS) and compared with a model-based approach for coordination of damping controllers. These are the first results of an extensive research related to coordination of DC-EIR, showing good adaptability and performance to different fault locations across the grid.Free, publicly-accessible full text available October 1, 2023
Mostafa Sahraei-Ardakani ; Mingxi Liu (Ed.)This paper explores the application of deep reinforcement learning (DRL) to create a coordinating mechanism between synchronous generators (SGs) and distributed energy resources (DERs) for improved primary frequency regulation. Renewable energy sources, such as wind and solar, may be used to aid in frequency regulation of the grid. Without proper coordination between the sources, however, the participation only results in a delay of SG governor response and frequency deviation. The proposed DRL application uses a deep deterministic policy gradient (DDPG) agent to create a generalized coordinating signal for DERs. The coordinating signal communicates the degree of distributed participation to the SG governor, resolving delayed governor response and reducing system rate of change of frequency (ROCOF). The validity of the coordinating signal is presented with a single-machine finite bus system. The use of DRL for signal creation is explored in an under-frequency event. While further exploration is needed for validation in large systems, the development of this concept shows promising results towards increased power grid stabilization.Free, publicly-accessible full text available October 1, 2023