Physics-Informed Hybrid Quantum-Classical Dispatching for Large-Scale Renewable Power Systems:A Noise-Resilient Framework

• URL: http://arxiv.org/abs/2601.18482v1
• Date: Mon, 26 Jan 2026 13:35:54 GMT
• Title: Physics-Informed Hybrid Quantum-Classical Dispatching for Large-Scale Renewable Power Systems:A Noise-Resilient Framework
• Authors: Fu Zhang, Yuming Zhao,
• Abstract summary: High-penetration energy introduces significantity and non-Classicality into power system dispatching optimization.<n>Existing approaches typically treat the power grid as a "black box"<n>This paper proposes a Hybrid Quantum-Bridging Dispatching (PIHQ-CD) framework.
• Score: 9.378801906395179
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The integration of high-penetration renewable energy introduces significant stochasticity and non-convexity into power system dispatching, challenging the computational limits of classical optimization. While Variational Quantum Algorithms (VQAs) on Noisy Intermediate-Scale Quantum (NISQ) devices offer a promising path for combinatorial acceleration, existing approaches typically treat the power grid as a "black box", suffering from poor scalability (barren plateaus) and frequent violations of physical constraints. Bridging these gaps, this paper proposes a Physics-Informed Hybrid Quantum-Classical Dispatching (PI-HQCD) framework. We construct a topology-aware Hamiltonian that explicitly embeds linearized power flow equations, storage dynamics, and multi-timescale coupling directly into the quantum substrate, significantly reducing the search space dimensionality. We further derive a noise-adaptive regularization mechanism that theoretically bounds the effective Lipschitz constant of the objective function, guaranteeing convergence stability under realistic quantum measurement noise. Numerical experiments on the IEEE 39-bus benchmark and a 118-bus regional grid demonstrate that PI-HQCD achieves superior economic efficiency and higher renewable utilization compared to stochastic dual dynamic programming (SDDP). Theoretical analysis confirms that this topology-aware design leads to an O(1/N) gradient variance scaling, effectively mitigating barren plateaus and ensuring scalability for larger networks. This work establishes a rigorous paradigm for embedding engineering physics into quantum computing, paving the way for practical quantum advantage in next-generation grid operations.

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