This paper proposes a component-oriented modeling method for power system simulation, which optimizes the modeling process of the FPGA-based real-time digital simulator (FRTDS) to enhance its computational efficiency. In this paper, a component modeling method for various types of elements in the power system is presented, which makes the modeling process in FRTDS more user-friendly and highly scalable. By applying the concepts of combination and reconstruction of components to electrical components, the component-oriented modeling method becomes better suited for combined elements with fixed connection modes and elements that require online model replacement in the power system. Utilizing the characteristics of component-oriented modeling, the variable declaration structure and node elimination strategy in the simulation script are optimized, enabling the simulation script to fit better with the hardware structure of FRTDS. Additionally, a substation is simulated in FRTDS with a simulation step size of 50 µs, thus verifying the correctness of the component-oriented modeling method and its ability to improve the computational power of FRTDS.
Aiming at the problems of the high switch numbers, complex working mechanisms, and complicated real-time simulation of modular multilevel converters (MMCs) composed of dual-port submodules, in this study, we designed a unified equivalent model of the multiple submodule network by analyzing the combination of parallel submodules in the bridge arm. The proposed model decouples the submodules that do not affect each other in the subnetwork calculation process, thereby reducing the number of prestored parameters in the subnetwork simulation. In the Xilinx Virtex-7 FPGA VC709 (Xilinx Corporation, San Jose, CA, USA) development board, we replaced the inline computation combined with the prestorage of parameters with the proposed equivalent model to optimize the execution unit structure and redesigned the FPGA-Based Real-Time Digital Solver (FRTDS). Taking the P-FBSM-based MMC–HVDC system as the simulation object, we performed a real-time simulation with a step size of 10 μs, which verified the effectiveness of the proposed model and the improvement in the hardware. We compared the results with the offline MATLAB/Simulink simulation results to verify the accuracy of the simulation.
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