  This paper introduces a new stochastic hybrid system (SHS) framework for
contingency detection in modern power systems (MPS). The framework uses
stochastic hybrid system representations in state space models to expand and
facilitate capability of contingency detection. In typical microgrids (MGs),
buses may contain various synchronous generators, renewable generators,
controllable loads, battery systems, regular loads, etc. For development of SHS
models in power systems, this paper introduces the concept of dynamic and
non-dynamic buses. By converting a physical power grid into a virtual
linearized state space model and representing contingencies as random switching
of system structures and parameters, this paper formulates the contingency
detection problem as a joint estimation problem of discrete event and
continuous states in stochastic hybrid systems. This method offers unique
advantages, including using common measurement signals on voltage and current
synchrophasors to detect different types and locations of contingencies,
avoiding expensive local direct fault measurements and detecting certain
contingencies that cannot be directly measured. The method employs a small and
suitably-designed probing signal to sustain the ability of persistent
contingency detection. Joint estimation algorithms are presented with their
proven convergence and reliability properties. Examples that use an IEEE 5-bus
system demonstrate the main ideas and derivation steps. Simulation case studies
on an IEEE 33-bus system are used for detecting transmission line faults and
sensor interruptions.
