Reciprocally altruistic agents for the mitigation of cascading failures in electrical power networks

Abstract

Cascading failures in electrical power networks often come with disastrous consequences. A variety of schemes for mitigating cascading failures exist, but the vast majority depend upon centralized control architectures. Centralized designs are frequently more susceptible to communications latency and bandwidth limitations and can be vulnerable to random failures and directed attacks. This paper proposes a decentralized approach. We place control agents at each substation in a power network, each of which uses decentralized model predictive control to select emergency control actions. When making decisions the control agents consider not only their own goals, but also the goals of nearby agents. Thus the agents act with reciprocal altruism. Results from simulations of extreme cascading failures within the IEEE 300 bus test network indicate that this approach can dramatically reduce the average size and social cost of large cascading failures. Simulations also show that the bandwidth required for message passing is well within the limits of current technology.