Algorithm complexity analysis of sequence operation theory

Sequence Operation Theory has been widely applied to solving complex uncertainty problems. Algorithm complexity of Sequence Operation, and advantages over other uncertainty analysis methods, are important theoretical problems worth in-depth researching that confront with Sequence Operation Theory. We compared Sequence Operation Theory with Monte Carlo method by a case study of power market risk assessment, and analyzed the algorithm complexity of them. Finally, we used an example to accurately compare calculating time of different risk assessment methods. The results show that Sequence Operation Theory is more efficient in power market risk assessment than traditional methods, and has considerate room for further optimization. It also verifies the superiority of Sequence Operation Theory. © 2009 Chin. Sco. for Elec. Eng.