Reforming Quantum Microgrid Formation
Chaofan Lin, Peng Zhang, Mikhail A. Bragin, Yacov A. Shamash

TL;DR
This paper presents a lossless quantum microgrid formation method that optimizes power system operations efficiently, requiring fewer qubits and demonstrating high accuracy on real quantum hardware.
Contribution
It introduces a novel lossless reformulation of quantum microgrid formation using graph-theory-based QUBO, enabling high-accuracy, low-qubit quantum solutions.
Findings
Achieves classical-level accuracy with fewer qubits
Demonstrates effectiveness on real quantum processors
Offers a scalable approach for quantum microgrid optimization
Abstract
This letter introduces a novel compact and lossless quantum microgrid formation (qMGF) approach to achieve efficient operational optimization of the power system and improvement of resilience. This is achieved through lossless reformulation to ensure that the results are equivalent to those produced by the classical MGF by exploiting graph-theory-empowered quadratic unconstrained binary optimization (QUBO) that avoids the need for redundant encoding of continuous variables. Additionally, the qMGF approach utilizes a compact formulation that requires significantly fewer qubits compared to other quantum methods thereby enabling a high-accuracy and low-complexity deployment of qMGF on near-term quantum computers. Case studies on real quantum processing units (QPUs) empirically demonstrated that qMGF can achieve the same high accuracy as classic results with a significantly reduced number…
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Taxonomy
TopicsMicrogrid Control and Optimization · Solar-Powered Water Purification Methods · Smart Grid Energy Management
