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Real-Time Optimization-Based Reference Calculation Integrated Control for MMCs Considering Converter Limitations.
- Source :
- IEEE Transactions on Power Delivery; Aug2022, Vol. 37 Issue 4, p2886-2901, 16p
- Publication Year :
- 2022
-
Abstract
- The paper addresses a real-time optimization-based reference calculation integrated with a control structure for Modular Multilevel Converters (MMC) operating under normal and constrained situations (where it has reached current and/or voltage limitations, as it may occur during system faults). Firstly, a nonlinear optimization problem has been developed in which it prioritizes to satisfy the AC grid current set-points imposed by the transmission System Operator (TSO). The constrained nonlinear optimization problem is formulated based on the steady-state model of the MMC, whereby the prioritization is achieved through distinct weights defined in the Objective Function’s (OF) terms. The resultant optimization problem, however, is highly nonlinear requiring high computation burden to be solved in real-time. To cope with this issue, this paper applies a Linear Time-Varying (LTV) approximation, which permits to represent the nonlinear dynamics of the system as constant parameters, while a Linear Time-Invariant (LTI) system is used to formulate the optimization constraints. The converter’s current references are determined in real-time by solving a constrained linearized optimization problem at each control time step, which considers the TSO’s demands, the current MMC operating point and its physical limitations. Theoretical analyses comparing the responses of the linear and nonlinear optimization problems are performed to validate the accuracy of the LTV approximation. Finally, the linearized-optimization problem is integrated with the MMC controllers, evaluated under different AC and DC network conditions and compared with conventional control strategies, where it is shown that the presented method can be potentially employed to obtain the MMC current references for distinct network scenarios. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08858977
- Volume :
- 37
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Power Delivery
- Publication Type :
- Academic Journal
- Accession number :
- 158186386
- Full Text :
- https://doi.org/10.1109/TPWRD.2021.3119148