Optimal Data Center Energy Management With Hybrid Quantum-Classical Multi-Cuts Benders' Decomposition Method
Zhongqi Zhao, Lei Fan, Zhu Han
Abstract
The flourishing of the data era has led to a higher demand for hyper-scale data centers, resulting in a great energy gap. It is necessary to comprehensively analyze the energy management in data centers to minimize the operation cost. In this article, we first propose a new optimal energy management model for data centers by considering energy consumers such as heating, ventilation, air conditioning (HVAC), server, solar, and battery. Then, inspired by the great computation power of quantum computing techniques, we propose a new hybrid quantum-classical multi-cuts Benders' decomposition algorithm, which utilizes quantum advantages in parallel computing for generating multi-cuts in a single iteration. Finally, experiments are conducted to verify the effectiveness and efficiency of the novel model and algorithms.