In order to evaluate the reliability of large-scale photovoltaic power plant

firstly

we established a reliability evaluation model of the main components of photovoltaic power station.Then

the reliability evaluation index system of photovoltaic power station was defined.Finally

the reliability of photovoltaic power station was evaluated by Markov Chain Monte Carlo（MCMC） method.In the modeling process of PV array

the backward scene reduction technology is used to reduce and divide the states

which can keep the accuracy of original sample as much as possible

and also improve the speed of evaluation.Through an example of the reliability evaluation of a large-scale photovoltaic power station

the convergence speed and stability of MCMC method and Monte Carlo（MC） method are compared and analyzed.The results show that the results of this method are consistent with the results of MC method

and the sampling time is less and the speed is faster under the same convergence condition.