Research on coordination optimization of DC modulation controller in multi-infeed transmission system based on improved Prony and chaos cloud particle swarm algorithm

Abstract

The application of DC power modulation of DC transmission lines can effectively suppress the phenomenon of inter-area low frequency oscillation between AC and DC interconnected grids. But in multi-infeed AC/DC transmission power system, the role of DC modulation is weakened due to the lack of mutual coordination. In order to improve the stability of the operation of the overall interconnected system, in this paper a control strategy is proposed to apply the improved Prony algorithm to identify the electromechanical mode of low frequency oscillation in interconnected power systems, and then chaos particle swarm algorithm combined with the cloud model of adaptive adjustment of inertia weight coefficient is adopted to coordinate and optimize the parameters of each DC modulation controller. In this method, multi-signal is firstly introduced into traditional Prony algorithm to combinationally identify low frequency oscillations in AC/DC hybrid systems, and then the mutual influence between the DC modulators are identified and simplified, which is used as the basis of the coordination and optimization model. On the basis of it, we use the chaos cloud particle swarm optimization algorithm with high precision and rapid convergence to optimize the parameters of each DC modulation controller. Through simulation in eight-generator three-region multi-infeed AC/DC power transmission system, and the results show that DC modulation controllers based on improved Prony with its parameters optimized by chaos cloud particle swarm algorithm attached to system can maximize regional power oscillation damping, and enhance the system operation stability, and possess quite good control effects.

Keywords

Inter-area low frequency oscillation DC modulation prony identification chaos cloud particle swarm algorithm coordination optimization

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