TY - JOUR
T1 - Model-predictive control with admittance matrix estimation for the optimal power sharing in isolated DC microgrids
AU - Ramirez-Marin, Santiago Alberto
AU - Garcés-Ruiz, Alejandro
AU - Cortés-Borray, Andres Felipe
AU - Perez-Basante, Angel
AU - Rodríguez-Seco, José Emilio
N1 - Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2025/4
Y1 - 2025/4
N2 - Direct current (DC) microgrids are relevant in modern energy systems due to their high efficiency, simplified architecture, and capability of direct integration of distributed resources (DERs). A proportional power-sharing is essential in these grids to balance the power injections according to the capability of each DER. However, the intermittency of DERs, load variations, and the non-linear nature of the model are major challenges. Therefore, this paper proposes a non-linear model predictive control (MPC) alongside an estimator for the nodal admittance matrix. By using MPC, it is possible to achieve optimal operation, considering voltage and power constraints. Moreover, the estimator enables the consideration of load variations with a reduced number of measurements. The robustness of the proposed control strategy is evaluated both in simulations and through a Power-Hardware-in-the-loop (PHIL) implementation. Radial and meshed microgrids were tested with different numbers of nodes. These results validate the practical feasibility and performance of the proposed approach.
AB - Direct current (DC) microgrids are relevant in modern energy systems due to their high efficiency, simplified architecture, and capability of direct integration of distributed resources (DERs). A proportional power-sharing is essential in these grids to balance the power injections according to the capability of each DER. However, the intermittency of DERs, load variations, and the non-linear nature of the model are major challenges. Therefore, this paper proposes a non-linear model predictive control (MPC) alongside an estimator for the nodal admittance matrix. By using MPC, it is possible to achieve optimal operation, considering voltage and power constraints. Moreover, the estimator enables the consideration of load variations with a reduced number of measurements. The robustness of the proposed control strategy is evaluated both in simulations and through a Power-Hardware-in-the-loop (PHIL) implementation. Radial and meshed microgrids were tested with different numbers of nodes. These results validate the practical feasibility and performance of the proposed approach.
KW - DC microgrid
KW - Model predictive control
KW - Power-hardware-in-the-loop
KW - Proportional power-sharing
KW - Secondary control
KW - Supervisory control
KW - Tertiary control
KW - Voltage regulation
UR - http://www.scopus.com/inward/record.url?scp=85213238464&partnerID=8YFLogxK
U2 - 10.1016/j.epsr.2024.111380
DO - 10.1016/j.epsr.2024.111380
M3 - Article
AN - SCOPUS:85213238464
SN - 0378-7796
VL - 241
JO - Electric Power Systems Research
JF - Electric Power Systems Research
M1 - 111380
ER -