  In the risk assessment of cascading outages, the rationality of simulation
and efficiency of computation are both of great significance. To overcome the
drawback of sampling-based methods that huge computation resources are required
and the shortcoming of initial contingency selection practices that the
dependencies in sequences of outages are omitted, this paper proposes a novel
risk assessment approach by searching on Markovian Tree. The Markovian tree
model is reformulated from the quasi-dynamic multi-timescale simulation model
proposed recently to ensure reasonable modeling and simulation of cascading
outages. Then a tree search scheme is established to avoid duplicated
simulations on same cascade paths, significantly saving computation time. To
accelerate the convergence of risk assessment, a risk estimation index is
proposed to guide the search for states with major contributions to the risk,
and the risk assessment is realized based on the risk estimation index with a
forward tree search and backward update algorithm. The effectiveness of the
proposed method is illustrated on a 4-node power system, and its convergence
profile as well as efficiency is demonstrated on the RTS-96 test system.
