Controlled Islanding as Robust Operator Response Under Uncertainty

Abstract

In the past decade there have been multiple high-profile cases of cascading blackouts, often resulting in the disconnection of tens of millions of consumers in large areas. It appears that in hindsight many of these disturbances could have been prevented by timely interventive action. In the actual cases, however, lack of complete knowledge about the state of the system undergoing a blackout event has prevented such action. This chapter reviews approaches to the problem of finding optimal interventions for a power system in the early stages of a cascading blackout. Conceptually the problem is one of optimization under uncertainty or robust optimization: the goal is to find a set of corrective actions that will guarantee power supply to as many customers as possible, in all, or at least most, of the possible states that the system may be in. To tackle the problem directly as a stochastic or robust optimization problem is intractable due to the complexities involved, foremost the number of possible states that would have to be considered. We argue, guided by example, that a robust response is to disconnect lines in such a manner as to create an island containing the affected part of the network. We give an overview of such approaches, notably those involving mixed-integer programming to directly design islands that admit a stable steady-state operating point.