517

Optimized Inter Real-Time Simulator Communication Utilizing Transmission Line Delay Variety

Fang Hou(1,2), Zhuoxuan Shen(3), An Chen(3), Donghui Zhang(2,3), Shaofu Li(1)

1. School of Information Engineering Southwest University of Science and Technology Mianyang, Sichuan (China)
2. Sichuan Energy Internet Research Institute. Tsinghua University
Chengdu, Sichuan (China)
3. Chengdu Mite Smart Power Technology Co., Ltd.
Chengdu, Sichuan (China)

2026-02-15

Hardware-in-the-loop (HIL) testing based on real-time simulators is one of the critical methods for the power system and the power electronics system research. Using multiple interconnected simulators to enhance parallel computing performance is a common method. However, with the increasing demand for enlarging system scale and shortening simulation time-step, more dedicated communication resources and a higher amount of transferred data are required. This paper proposed a method for optimizing inter real-time simulator communication utilizing the delay variety of the distributed transmission line model, which can reduce the communication hardware resources and increase the data throughput with no loss of the simulation accuracy. In the case study of a system containing 100 wind turbines and 20 sets of IEEE 39-bus system on four real-time simulators, the communication resource consumption is reduced by 48.78% with the proposed optimization method.

Key words: Real-time Simulator, Transmission Line Model, Communication Optimization

[1] D. Chen, L. Miao, F. Wang, Q. Mu, and M. Gao, “Electromagnetic transient simulation of power system based on PSCAD calling ADPSS”, Journal of Physics: Conference Series (2024), Vol. 2782, no. 1.

[2] S. Subedi, M. Rauniyar, S. Ishaq, T. M. Hansen, R. Tonkoski, M. Shirazi, et al., “Review of methods to accelerate electromagnetic transient simulation of power systems”, IEEE Access (2021), Vol. 9, pp. 89714–89731.

[3] R. Mirzahosseini and R. Iravani, “Small time-step FPGA-based real-time simulation of power systems including multiple converters”, IEEE Transactions on Power Delivery (2019), Vol. 34, no. 6, pp. 2089–2099.

[4] E. Bompard, S. Bruno, A. Cordoba-Pacheco, C. Diaz-Londono, G. Giannoccaro, M. La Scala, et al.,“Latency and simulation stability in a remote power hardware-in-the-loop cosimulation testbed”, IEEE Transactions on Industry Applications (2021), Vol. 57, no. 4, pp. 3463–3473.

[5] K. Sozański, “Low-cost hardware analog and digital real-time circuit simulators for developing power electronics control circuits”, Energies (2024), Vol. 17, no. 24.

[6] S. Fan, H. Ding, A. Kariyawasam, and A. M. Gole, “Parallel electromagnetic transients simulation with shared memory architecture computers”, IEEE Transactions on Power Delivery (2017), Vol. 33, no. 1, pp. 239–247.

[7] M. C. de Barros, M. E. Almeida, L. Dubé, and B. Stein, “A general-purpose transmission line model and its interface with an electromagnetic transients programme”, International Journal of Electrical Power & Energy Systems (1997), Vol. 19, no. 4, pp. 249–254.

[8] P. Li, X. Wang, Z. Wang, X. Fu, H. Fu, and K. Wang, “Parallel kernel solver of an FPGA‐based real‐time simulator for active distribution networks”, IET Renewable Power Generation (2023), Vol. 17, no. 1, pp. 162–175.

[9] A. Myaing and V. Dinavahi, “FPGA-based real-time emulation of power electronic systems with detailed representation of device characteristics”, Proceedings of IEEE Power and Energy Society General Meeting (2011), pp. 1–11.

[10] R. Razzaghi, M. Mitjans, F. Rachidi, and M. Paolone, “An automated FPGA real-time simulator for power electronics and power systems electromagnetic transient applications”, Electric Power Systems Research (2016), Vol. 141, pp. 147–156.

[11] E. Bompard, S. Bruno, A. Cordoba-Pacheco, C. Diaz-Londono, G. Giannoccaro, M. La Scala, et al., “Latency and simulation stability in a remote power hardware-in-the-loop cosimulation testbed”, IEEE Transactions on Industry Applications (2021), Vol. 57, no. 4, pp. 3463–3473.

[12] L. Yi, D. Lu, and Y. Liu, “Analytical multi-section Bergeron model of transmission lines and application to accurate fault location for long HVDC lines”, Electric Power Systems Research (2023), Vol. 223, p. 109510.

[13] N. Suyaroj, S. Premrudeepreechacharn, and N. R. Watson, “Transient state estimation with the Bergeron transmission line model”, Turkish Journal of Electrical Engineering and Computer Sciences (2017), Vol. 25, no. 2, pp. 806–819.

[14] H. W. Dommel, “Digital computer solution of electromagnetic transients in single-and multiphase networks”, IEEE Transactions on Power Apparatus and Systems (1969), no. 4, pp. 388–399.

[15] X. UG902, Vivado Design Suite User Guide, High-Level Synthesis (2016) [Online]. Available: https://www.xilinx.com.

[16] D. D. Gajski, N. D. Dutt, A. C. Wu, and S. Y. Lin, High-Level Synthesis: Introduction to Chip and System Design, Springer Science & Business Media, New York, NY (2012).

[17] S. Ma, X. Shi, and D. Andrews, “Parallelizing maximum likelihood classification (MLC) for supervised image classification by pipelined thread approach through high-level synthesis (HLS) on FPGA cluster”, Big Earth Data (2018), Vol. 2, no. 2, pp. 144–158.