Monte Carlo

With the rapid development of economy, the power users’demand of power quality becomes more and more high. Power supply continuously has already not reached requirements of power quality by the power users. Compared with power supply interruption, voltage sags occur frequently, and make serious influence and economic losses to the sensitive equipment. Voltage sags has gradually become the most attention in the dynamic power quality problems. How to estimate for voltage sag plays a crucial role for enhancing asset utilization ratio of power system and reducing economic losses.The core of voltage sag estimate is estimating the probability distribution of voltage sag amplitude and duration, and estimating the economic losses caused by voltage sag. This paper analyses the influence to amplitude and duration of voltage sag by different fault types and fault locations in detail and present a formula to estimate economic losses, on the basis of questionnaire aiming at power quality and the probability distribution of voltage sag amplitude and duration, combined with the sensitivity curve of different equipments.Voltage sag is random, people usually to predict random on voltage sag based on the failure probability. Monte Carlo is a kind of typical probability simulation method. Through building the various factors’probability distribution model influencing voltage sags, mainly included fault type, fault location, duration and operating time of protection, combined with the electromagnetic transient simulation software PSCAD/EMTDC, random numbers could sample from the probability distribution of the various factors. After multiple simulations, the probability density distribution of voltage sag amplitude and duration of every load bus could be established. According to statistical data, the influence of the random fault type and location to the probability of voltage sag amplitude and duration is analyzed. And calculating the economic losses of each node used the formula. Through the simulation and statistical analysis, the PSCAD model is proved correctly, and could be used to analyze power quality problem under different protection configurations. Theoretical and practical foundation is established for the next study.