LSTM-based Evaluation Algorithm for the Adequacy of Frequency Regulation Resources in Renewables-Penetrated Power Systems

Nowadays, renewable energy generation shares an increasing proportion of all power generation. However, the randomness of renewable energy generation leads to higher uncertainty in power systems, especially in regions with a high proportion of renewable energy. One of the uncertainty problems is the frequency problem. To cope with the fluctuation of renewable energy generation output, a large amount of frequency regulation resources is required. Here comes the need for a method to evaluate whether the resources are sufficient in real time. In this paper, we proposed an evaluation score
$S$
to precisely assess the sufficiency of frequency regulation resources and proposed an evaluation algorithm based on the long short-term memory network (LSTM) to assess the sufficiency of frequency regulation resources. Numerical experiments based on Elia's real operating data are used to validate the effectiveness and efficiency of the proposed method.