An iterative identification algorithm and its convergence analysis of closed-loop power system based on ambient signals

Abstract

Abstract Identification and control are important problems of closed-loop power system. At present, most studies are separate identification methods. This paper studies an online and real-time integrated identification method, which can solve the problems of model set and controller design of closed-loop power system. This paper investigates a new iterative identification algorithm and its convergence problem of closed-loop power system based on ambient signals. Firstly, the whole algorithm procedure is given. This algorithm uses the iterative process under the closed-loop condition, which combines system model identification with controller design. Then the complementary of model identification and control design has been realized. Secondly, because of the dynamic performance of the iterative identification algorithm, it has characteristics described from the perspective of a partitioned dynamic system. Regard each iterative identification step as a state node. In this situation, the algorithm guarantees all the state nodes converge to the Lyapunov stable equilibrium. Finally, the simulation results show the correctness and effectiveness of the proposed method through the simulation of a power system with four-machine-two-region.