Reinforcement Learning to Initialize Newton-Raphson for AC Power Flow with Quantum Annealing-Based Environment Updates
The work integrates Reinforcement Learning (RL) with quantum annealing to improve Newton-Raphson (NR) methods for power flow analysis. The system uses RL to learn optimal initial voltage settings, and a quantum-enhanced mechanism solves a complex optimization problem using quantum annealers. This results in significantly faster convergence and more robust solutions than traditional RL methods.