The Simulation On Probabilistic Power Flow Of Smart Distribution Grid Based On PSCAD

One of the problem of smart distribution grid is the access of distributed generators, a lot of distributed generators belong to intermittent power. In the randomness of the injection power, how to ensure the safe and economic operation of the system is to solve the problem of smart distribution grid. So this article study on the risk assessment of smart grid branch overload power. The emphasis of the study is the relationship between the probability distribution of the brance power and the probability distribution of power injection power.This paper first will use the method of linear load flow equations, establishing the relationship between the model of the branch power and the node injection power. Then establish the PSCAD simulation model of stachastic flow of smart distribution grid. Using the voltage source with controllable amplitude and phase is to simulate the intermittent power of random injection power. Through the PSCAD, generating random number module and building the accumulate distribution anti-function module is to produce the random injection power according to the demand. By using PI control link, control the voltage phase of the power supply, and then control the injection power of random source. The load with the PI control variable impedance is to simulate the random load by some distribution.On the basis of simulation model, choose the complicated distribution network IEEE9standard network to simulate.Simulation results verify that the measured data by PSCAD and the theory analysis that is the distribution of convolution get match. This indicates that the branch power and the node injection power and simulation model are correct.It is proved that the model of random power source and load are very accurate. Through the Matlab data processing, the accumulated distribution function and the probability density function have certain value for study. Brance over-load on the stachastic flow lay on the foundation of theory and simulation model for further.