Matrix Low-dimensional Qubit Casting Based Quantum Electromagnetic Transient Network Simulation Program

TL;DR

This paper introduces a quantum computing-based method to efficiently simulate electromagnetic transient networks in power systems, overcoming computational challenges with a novel matrix low-dimension qubit casting approach.

Contribution

It proposes the matrix low-dimension qubit casting technique and a real-only quantum circuit reduction to improve quantum EMTP simulation of complex power networks.

Findings

Successfully verified on large EMT networks with high-frequency switching.

Reduces data inflation in quantum preprocessing of admittance matrices.

Demonstrates potential for exponential acceleration in power system simulations.

Abstract

In modern power systems, the integration of converter-interfaced generations requires the development of electromagnetic transient network simulation programs (EMTP) that can capture rapid fluctuations. However, as the power system scales, the EMTP's computing complexity increases exponentially, leading to a curse of dimensionality that hinders its practical application. Facing this challenge, quantum computing offers a promising approach for achieving exponential acceleration. To realize this in noisy intermediate-scale quantum computers, the variational quantum linear solution (VQLS) was advocated because of its robustness against depolarizing noise. However, it suffers data inflation issues in its preprocessing phase, and no prior research has applied quantum computing to high-frequency switching EMT networks.To address these issues, this paper first designs the matrix low-dimension qubit casting (MLQC) method to address the data inflation problem in the preprocessing of the admittance matrix for VQLS in EMT networks. Besides, we propose a real-only quantum circuit reduction method tailored to the characteristics of the EMT network admittance matrices. Finally, the proposed quantum EMTP algorithm (QEMTP) has been successfully verified for EMT networks containing a large number of high-frequency switching elements.