Artículo
A model-less control algorithm of DC microgrids based on feedback optimization
Autor/es | Olives Camps, Juan Carlos
Rodríguez del Nozal, Álvaro Mauricio Ferramola, Juan Manuel Maza Ortega, José María |
Departamento | Universidad de Sevilla. Departamento de Ingeniería Eléctrica |
Fecha de publicación | 2022-10 |
Fecha de depósito | 2022-07-07 |
Publicado en |
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Resumen | 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 ... 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. |
Identificador del proyecto | VI PPIT-US
764090 ENE2017-84813-R HySGrid+ (CER-20191019) |
Cita | Olives Camps, J.C., Rodríguez del Nozal, Á., Mauricio Ferramola, J.M. y Maza Ortega, J.M. (2022). A model-less control algorithm of DC microgrids based on feedback optimization. International Journal of Electrical Power and Energy Systems, 141, 108087. |
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