With the integration of renewable power and electric vehicle,the power system stability is of increasing concern because the active power generated by the renewable energy and absorbed by the electric vehicle vary randomly.Based on the deterministic differential equation model,the nonlinear and linear stochastic differential equation models of power system under Gauss type random excitation are proposed in this paper.The angle curves under different random excitations were simulated using Euler-Maruyama(EM) numerical method.The numerical stability of EM method was proved.The mean stability and mean square stability of the power system under Gauss type of random small excitation were verified theoretically and illustrated with simulation sample.
The power system controllers normally have more than one parameter.The distinguishability analysis of the controller parameters is to identify whether the optimal set of the parameters of the controllers is unique.It is difficult to obtain the analytic relationship between the objective of the optimization and the controller parameters,which means that the analytical method is not suitable for the distinguishability analysis.Therefore,a trajectory sensitivity based numerical method for the distinguishability analysis of the controller parameters is proposed in this paper.The relationship between the distinguishability and the sensitivities of the parameters is built.The magnitudes of the sensitivities are used to identify the key parameters,while the phase angles of the sensitivities are used to analyze the distinguishability of the key parameters.The distinguishability of the controller parameters of wind turbine with DFIG is studied using the proposed method,and dynamic simulations are performed to verify the results of the distinguishability analysis.
