A novel self-evolving multi-agent architecture for power system monitoring and protection against attacks of malicious intent

In this paper, we propose a novel self-evolving multi-agent methodology (MAM) for power system monitoring and protection. The uniqueness of the proposed architecture is the ability of MAM to evolve in the wake of an attack of malicious intent by mutation and thus always monitoring a power system bus remotely. Also, the architecture interacting with the mutated agents uses a voting methodology thus alleviating the effect of agent malfunction in the presence of attack. This novel architecture is tested on a Single Machine Infinite Bus (SMIB) power network and a two area network with five equivalent generators and eight bus, two area power system for abnormal condition detection and generator bus isolation. Simulation studies indicate that the proposed methodology is capable of not only detecting the power grid attack once, but can also continuously monitor and isolate the generator bus even in the presence of sustained attack as the agents are regenerated.