Quantum Computing for Operation Analysis and Optimization of Sustainable Power Systems: The Potential to Substantially Boost Performance
Quan Yuan, Han Wang, Xiaoyuan Xu +4 more
With the rapid development of renewable energy generation, the computational efficiency and accuracy requirements for the operation analysis and optimization of sustainable power systems are constantly increasing. Although numerous classical methods have been widely used, they still face challenges in global optimization, efficiency, and complex constraint handling for large-scale and real-time systems. Quantum computing, as a new tool, provides a promising computational paradigm for accelerating optimization and operation analysis in sustainable power systems. This article reviews the applications of quantum computing in sustainable power systems. First, the basic principles of quantum computing, the major hardware routes, and representative algorithms are introduced. Then, the applications of quantum computers and algorithms in sustainable power system operation analysis and optimization are summarized. Finally, the key challenges and the application prospects of quantum computing in sustainable power systems are discussed. The review indicates that quantum computing is more suitable as an enhancement to classical workflows rather than a complete replacement in existing studies. Future research would focus on quantum–classical hybrid computation frameworks and subproblem decomposition based on quantum computing for the sustainable development of power systems.
IEEE Energy Sustainability Magazine•Oct 29, 2026•0 citations