Dynamic modeling and small signal stability analysis of distributed photovoltaic grid-connected system with large scale of panel level DC optimizers

[Display omitted] The distributed maximum power point tracking (DMPPT) technologies, based on a DC optimizer (DCO) for every single photovoltaic (PV) panel, are increasingly proposed to mitigate the waste of solar energy due to the mismatch problems of PV arrays. However, the stability problem of DMPPT based distributed PV grid-connected systems that involve a large amount of DCOs remains to be further studied. Therefore, modeling, deservedly, is the basis for stability analysis. Usually the model of the PV power plant consists of hundreds or even thousands of DCOs, which results in a heavy computation burden during the simulation. To solve the modeling problem, this paper proposes a matrix variables based modeling method for the distributed PV grid-connected system. The core idea of the modeling method is to convert the complex model that contains plenty of PV-DCO generation units to an average model consisting of only two typical submodules, by constructing the block matrix formed variables. In this way, the model has the advantages of good scalability and high simulation efficiency, and can be realized by the vector simulation feature of Matlab/Simulink. Besides, it is easy to obtain the linearization results directly by using the Linearization Toolbox in Simulink, which avoids the complexity of writing programs for linearization calculation when studying the stability of large-scale systems. Based on the average model and corresponding linearization results, the key impacts on the small signal stability of the system are determined via the eigenvalue analysis method and root locus method. It is shown that the total active power output by PV array, the controller parameters of the grid-connected inverter, and the strength of the AC system are critical factors affecting the small signal stability of distributed PV grid-connected system. Different simulation results verify the effectiveness of the proposed approach.