华电技术 ›› 2020, Vol. 42 ›› Issue (8): 90-96.

• 创新与探索 • 上一篇    

量子计算在火电机组优化控制中的应用综述

  

  1. 1. 新能源电力系统国家重点实验室(华北电力大学),北京 102206;2. 中国华电集团天津公司,天津 300203;
    3. 华电国际电力股份有限公司 天津开发区分公司,天津 300270
  • 出版日期:2020-08-25 发布日期:2020-09-01

Review on the application of quantum computing in optimization control on thermal power units

  1. 1.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China
    Electric Power University),Beijing 102206,China;2.Tianjin Company,China Huadian
    Corporation Limited,Tianjin 300203,China;3.Tianjin Development Area Branch,
    Huadian Power International Corporation Limited,Tianjin 300270,China
  • Online:2020-08-25 Published:2020-09-01

摘要: 量子计算及其衍生算法近年来快速发展,成为优化领域和人工智能领域的研究热点。随着我国电力行业
清洁化和智能化的发展,量子计算逐渐应用于火电机组优化控制领域并取得了诸多成效。介绍了量子计算的基本
理论,详细论述了众多量子衍生算法在火电机组优化控制领域中的应用研究进展。从量子群智能优化算法、量子
遗传算法和量子机器学习算法等多个角度综述了量子计算在火电机组优化控制领域的机遇与挑战。最后总结并
展望了量子计算未来在火电机组优化控制领域的发展趋势。

关键词: 量子计算, 量子衍生算法, 火电机组, 优化控制, 智能算法, 人工智能

Abstract: Quantum computing and its inspired algorithms have developed rapidly in recent years,and have become the hot
spot in optimization and artificial intelligence fields. With the clean and intelligent development of China's electric power
industry,quantum computing has gradually been being applied in the optimization control on thermal power units and has
obtained certain achievements.Starting by a brief introduction to quantum computing basic theory,the progress of quantum-
inspired algorithm in optimization control on thermal power units is expounded in details. The opportunities and challenges
of quantum computing in this field is analyzed from multiple aspects including the quantum swarm intelligence optimization
algorithm,the quantum genetic algorithm and machine learning algorithm. At last,the prospects of quantum computing in
the optimization control on thermal power units are summarized.

Key words: quantum computing, quantum-inspired algorithm, thermal power plant, optimization control on units,
intelligence algorithm,
AI