With large-scale integration of wind farms and photovoltaic plants into the power system

it becomes necessary to take the wind power and photovoltaic power uncertainty into consideration during optimal power flow (OPF) calculation. The traditional Monte Carlo simulation method cannot be used for the thousands of stochastic simulations required to achieve a rational result. Hence the digital nets (DN) method with equivalent distribution sample values is proposed to improve the sample value coverage of random variable input spaces. And the method is used in the OPF calculation of power system containing wind farms and photovoltaic plants. The accuracy and validity of the proposed method tested on an IEEE 30-bus system and the simulation results show that the proposed method has the advantages of fast computation and high accuracy while capable of estimating the probability distribution of the output random variables and dealing with the uncertainties in the electricity market. Then the DN method is applied to an IEEE 300-bus system to study the influence of different capacities of photovoltaic plants on the location marginal price. Furthermore

a comparison between the wind farm/photovoltaic plant hybrid system and single wind farm system has led to the conclusion that the location marginal price

net loss and branch active power of the former are less volatile.