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Studies in systems, decision and control

Implementation of Quantum Computing Algorithms in Electrical Power System Optimization

Jasgurpreet Singh Chohan, Jatinder Kumar, Krishna Kant Dixit, Safeyah Tawil, Dalal Kadim Sakr, Nilesh P. Bhosle, Mohammed Al-Farouni, Arun Kumar, Jayant P Giri

Published Nov 6, 2025• 1 citation
Publisher
DOI
10.1007/978-3-031-89771-9_50

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We present the first direct comparison between gate-based quantum computing (GQC) and adiabatic quantum computing (AQC) paradigms for solving the AC power flow (PF) equations. The PF problem is reformulated as a combinatorial optimization problem. For the GQC approach, the Quantum Approximate Optimization Algorithm (QAOA) is employed, while for the AQC approach, the problem is formulated as an Ising model. Numerical experiments on a 4-bus test system evaluate solution accuracy and computational performance. Results obtained using QAOA are benchmarked against those produced by D-Wave's Advantage system and Fujitsu's latest-generation Digital Annealer, implemented through the Quantum-Inspired Integrated Optimization (QIIO) software. The findings provide quantitative insights into the performance trade-offs, scalability, and practical viability of GQC and AQC paradigms for PF analysis, highlighting the potential of quantum optimization algorithms to address the computational challenges associated with the operation of modern electricity grids in the fault-tolerant era.