title: Key words: machine learning; explainable; grid frequency; stability
text: Namangan Institute of Engineering and Technology
  nammti.uz
  10.25.2023
  Pg.291
  is so important, it is critical to comprehend and separate these various effects on the grid frequency.
  Moreover, control measures are required to stabilise the frequency [1]. Research on the
  relationship between these control requirements and outside influences is still ongoing [11].
  In this article, we present how eXplainable Artificial Intelligence (XAI) may be used to better
  comprehend the factors that influence frequency stability and control, as well as the hazards
  involved. We demonstrate applications of our technique to frequency stability indicators [1],
  deterministic frequency deviations [6], and frequency control activation in Germany [11]
  throughout Europe using operational data from key European power systems.