Uncertainty Analysis Of Power System Time-domain Simulation Based On Generalized Polynomial Chaos Method

Time domain simulation method usually uses deterministic simulation model.By numerical calculation,we can simulate the actual operating status of a system,which is widely used in power system planning,design and operation.However,there exists many uncertain factors in power system,because of which the results from deterministic simulation method are often inconsistent with the actual situation,which is not conducive to make a comprehensive judgment on operation of the system.Aiming at the uncertainty of power system model parameters and steady state conditions,a method based on generalized polynomial chaos(gPC)is proposed for uncertainty analysis of time-domain simulation.Approximately,the method assumes that there exists a polynomial relationship between the variables and the random factors at any time.The solution procedure is as follows:firstly,the optimal orthogonal polynomial basis function is constructed to approximate the random input variables and unknown variables.Then,by using the Galerkin method,the stochastic equations which describe the system's transient process are transformed into the corresponding deterministic equations.Finally,by solving these equations,the polynomial approximation coefficients of unknown variables are obtained,which can be used to calculate the statistical results and probability distribution of relevant variables at any time.In order to adapt to the characteristics of the gPC method,a polynomial model is proposed from existing transient model through mathematical transformation.In this paper,the polynomial model is deduced theoretically,and its correctness is verified based on IEEE 9 bus system.Compared with Monte Carlo method,the computational efficiency of gPC method is analyzed theoretically in this paper.And through example analysis,the effectiveness of the proposed method is verified.