Print Email Facebook Twitter Interoperability of classical and advanced controllers in MMC based MTDC power system Title Interoperability of classical and advanced controllers in MMC based MTDC power system Author Liu, L. (TU Delft Intelligent Electrical Power Grids) Shetgaonkar, A.D. (TU Delft Intelligent Electrical Power Grids) Lekić, A. (TU Delft Intelligent Electrical Power Grids) Date 2023 Abstract This paper presents the modular-multilevel-converter (MMC) control interoperability (IOP) and interaction within the High Voltage Direct Current (HVDC)-based power system. IOP is a crucial issue in the large-scale HVDC grid with different suppliers. To accommodate future multi-vendor HVDC grids developments, this article comprehensively investigates the MMC control IOP issue. Firstly, the most commonly adopted proportional-integral (PI) control and other non-linear controllers, e.g., model predictive control (MPC), back-stepping control (BSC), and sliding mode control (SMC), are constructed for MMC. Then, the IOP simulations are carried out in a multi-terminal direct current (MTDC) system in real-time digital simulator (RTDS) environment. The most frequent transients of the practical projects, e.g., power flow changing, wind speed changing, and DC/AC grid faults, are simulated with eight different scenarios. Each scenario presents different control capabilities in maintaining system stability, more precisely, the scenarios with non-linear controllers show faster settling time and fewer DC voltage and power variations. Controller switchings are also achieved without bringing large system oscillations. This paper provides the optimal allocation strategy of controllers to cope with system transients. Subject InteroperabilityMMC non-linear controlMTDC systemMPCBack-stepping controlSliding-mode controlRTDSPower system transients To reference this document use: http://resolver.tudelft.nl/uuid:10411ae0-5545-4f31-946d-978354a8a0af DOI https://doi.org/10.1016/j.ijepes.2023.108980 ISSN 0142-0615 Source International Journal of Electrical Power & Energy Systems, 148 (108980) Part of collection Institutional Repository Document type journal article Rights © 2023 L. Liu, A.D. Shetgaonkar, A. Lekić Files PDF 1_s2.0_S0142061523000376_main.pdf 5.57 MB Close viewer /islandora/object/uuid:10411ae0-5545-4f31-946d-978354a8a0af/datastream/OBJ/view