Quantum- Inspired Optimal Power Flow

This paper addresses the critical challenge of Op-timal Power Flow (OPF) in electrical engineering, emphasizing the intersection of complexity and technological advancements. Leveraging quantum computation, particularly the Primal-Dual Interior Point Method (PD-IPM) and the Harrow-Hassidim-Lloyd (HHL) algorithm, we explore enhanced solutions for both Alternating Current OPF (ACOPF) and Direct Current OPF (DCOPF). PD-IPM generates linear systems during optimization, aligning with the selected quantum techniques that offer expo-nential speedup. We investigate the scalability and challenges of HHL, emphasizing the current limitations for larger power systems. Additionally, we introduce a hybrid approach that dynamically transitions between quantum and classical methods to optimize convergence. Our study evaluates the proposed methodology's performance under diverse error conditions, em-phasizing its potential to revolutionize solving times for OPF in power systems.