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A model-less control algorithm of DC microgrids based on feedback optimization
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DOI：10.1016/j.ijepes.2022.108087.png)
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Abstract
En 中文
This work addresses the problem of the optimal real-time control of a DC microgrid without relying on its corresponding network model. The main goal of such a controller is to keep the nodal network voltages within the regulatory limits while offering current sharing capability between the different controllable generators powering the DC microgrid. The proposed model-less methodology is based on feedback optimization, which takes advantage of the available real-time measurements to update the setpoints of the DC generation assets. The optimal control variables are determined in an iterative manner by applying a primal-dual saddle-point method, which guarantees appropriate convergence features. The paper details both centralized and distributed implementations which are compared through simulations. The results evidence a good dynamic performance and an optimal steady-state operation as the proposed control algorithm converges to the solution provided by a conventional model-based Optimal Power Flow.
Keywords:
DC microgrids
Distributed control
Feedback optimization
Load sharing control
Secondary voltage control
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5
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