A Review of Three Methods of Artificial Intelligence in Smart Grid Cyber Security: Machine Learning, Reinforcement Learning, Ensemble Methods

Abstract

Renewable energy is gradually replacing traditional fossil fuels. The change of power generation energy structure brings new challenges to the traditional power grid. Through the efficient bidirectional movement of electricity and information, smart grids might include renewable energy. For the complex informational and financial operations required by smart grid, communication systems are crucial, but they also make smart grid vulnerable to numerous cyber attacks. Smart grid cyber security has been widely concerned. The purpose of this paper is to explore the use of artificial intelligence technology in smart grid cyber security. Three methods in the field of artificial intelligence are highlighted: Machine Learning, Reinforcement Learning, and Ensemble Methods. This paper summarizes the benefits and drawbacks of their use of smart grid cyber security, and further makes a qualitative comparison of the three methods from multiple performance indicators.