FPGA Accelerated Large-Scale State-Space Equations for Multi-Converter Systems

The increasing integration of high-frequency power electronic converters in renewable energy-grid systems has escalated reliability concerns, necessitating FPGA-accelerated large-scale real-time electromagnetic transient (EMT) computation to prevent failures. However, most existing studies prioritize computational performance and struggle to achieve large-scale EMT computation. To enhance the computational scale, we propose a scalable hardware architecture comprising domain-specific components and data-centric processing element (PE) arrays. This architecture is further enhanced by a graph-based matrix mapping methodology and matrix-aware fixed-point quantization for hardware-efficient computation. We demonstrate our principles with FPGA implementations of large-scale multi-converter systems. The experimental results show that we set a new record of supporting 1200 switches with a computation latency of 373 ns and an accuracy of 99.83% on FPGA implementations. Compared to the state-of-the-art large-scale EMT computation on FPGAs, our design on U55C FPGA achieves an up-to 200.00× increase in the switch scale, without I/O resource limitations, and demonstrates up-to 71.70% reduction in computation error and 51.43% reduction in DSP consumption, respectively.