Integrating renewable offshore wind generation into global power grids is a critical issue in the energy industry. Modular Multilevel Converter (MMC)-based High Voltage Direct Current (HVDC) grids are the most effective and promising technical solution for the new offshore wind energy power system connections. Stable and compliant operation of MMCs requires implementing MMC control strategies and controllers. This project investigates the intricacies of HVDC technologies, focusing on MMC control strategies and controllers. The research explores grid-forming converter control strategies, essential for ensuring the stable and compliant operation of MMC-based HVDC grids.
The research elaborates on the Model Predictive Control (MPC), which is a promising control strategy for MMC-based HVDC grids. The MPC controller makes the control strategies respond faster, emphasizing constraints and cost functions. Furthermore, a comparative analysis of Proportional Integral (PI)-based and MPC-based controllers is conducted across various scenarios, highlighting the speed of response of MPC-based controllers over PI-based.
This project illustrates the capabilities of grid-forming control strategy through Model Predictive controllers for FPGA-based MMC-MTDC networks on RSCAD/RTDS®. The FPGA-based converters enable the use of detailed models of the converters without sacrificing the speed of the simulations. For the implementation of MPC, MATLAB /Simulink is used to tune the controller, then a user-defined block in RSCAD software is used to implement it in a real-time environment of RSCAD/RTDS®.
The outcomes of this project possess the capacity to significantly augment the progression of HVDC technologies and control strategies, with implications for enhancing the stability and efficiency of MMC-based HVDC grids.
Rohan Tarcar | TU Delft