In view of the degradation of improvement character of the quasi-Monte Carlo method in handling high dimension problems

a dimensional importance based quasi-Monte Carlo method for power system reliability evaluation is proposed. First

the error estimation principle of quasi-Monte Carlo is described

and the uniformity degradation of low discrepancy sequence on increasing dimensions is analyzed. Secondly

the decomposition term of error bounds is derived by analysis of variance and sampling in the descending order of dimensional importance is proposed to reduce the error bounds. Then a model for quantifying dimensional importance is developed. Finally

a quasi-Monte Carlo model for power system reliability evaluation based on dimensional importance and a cross entropy quasi-Monte Carlo model are developed. Then the accuracy index of evaluating the error between computed value and the true value is presented. The accuracy indices in calculating loss of load probability(LOLP)and expected demand not supplied(EDNS)of the proposed method and those of the crude method are compared on the test systems of RTS79 generation system

292-unit generation system and RBTS generation and transmission system. Results show that the method proposed has better error accuracy in the calculation of both indices mentioned above. This work is supported by National Natural Science Foundation of China(No. 51277140).