Security Games and Risk Minimization for Automatic Generation Control in Smart Grid

The power grid, on which most economic activities rely, is a critical infrastructure that must be protected against potential threats. Advanced monitoring technologies at the center of smart grid evolution increase its efficiency but also make it more susceptible to malicious attacks such as false data injection. This paper develops a game-theoretic approach to smart grid security by combining quantitative risk management with decision making on protective measures. Specifically, the consequences of data injection attacks are quantified using a risk assessment process based on simulations. Then, the quantified risks are used as an input to a stochastic game model, where the decisions on defensive measures are made taking into account resource constraints. Security games provide the framework for choosing the best response strategies against attackers in order to minimize potential risks. The theoretical results obtained are demonstrated using numerical examples.