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燃煤发电机组灵活运行控制技术研究进展

Progress of flexible operational control technology for coal-fired units

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【作者】 孙源张启超张忠孝郭欣维孔成栋徐嘉叶叶妮娜黄林鹏ARONSON Konstantin Erlenovich乌晓江

【Author】 SUN Yuan;ZHANG Qichao;ZHANG Zhongxiao;GUO Xinwei;KONG Chengdong;XU Jiaye;YE Nina;HUANG Linpeng;ARONSON Konstantin Erlenovich;WU Xiaojiang;School of Mechanical Engineering, Shanghai Jiao Tong University;Ural Institute, North China University of Water Resources and Electric Power;College of Power Engineering, Ural Federal University;

【通讯作者】 乌晓江;

【机构】 上海交通大学机械与动力工程学院华北水利水电大学乌拉尔学院乌拉尔联邦大学动力工程学院

【摘要】 加快构建新型电力系统是助推“双碳”目标实现的核心关键。风、光可再生能源的大比例接入给电力系统的安全稳定运行带来了新的挑战,对燃煤机组的安全、深度、灵活调峰控制也提出了更高要求。依据煤电机组智能灵活调峰控制技术的发展历程,从被控对象建模和灵活运行控制方法两个层面进行梳理与分析,研究结果表明,辅以机器学习和其他智能系统辨识方法的混合建模方式,以及融合预测控制、自适应控制、多目标智能寻优等先进控制技术更加适合未来煤电机组灵活智能控制的需要,是未来煤电机组灵活、智能控制技术发展的主要方向。

【Abstract】 Speeding up the construction of a new power system is the key to promoting the realization of the "dual carbon" target. The connection of a large proportion of intermittent wind and solar renewable energy has brought new challenges to the safe and stable operation of the power system, and has also put forward higher requirements for the fast, deep and flexible operation capabilities of coal-fired units. In this paper, the modeling methodology and flexible operational control technology for coal-fired units were described and analyzed based on the the development history of intelligent and flexible peakshaving control technology. The analysis results show that the hybrid modeling method supplemented by machine learning and other intelligent system identification methods, as well as the integration of predictive control, adaptive control, multi-objective intelligent optimization, etc. are more suitable for the needs of flexible and intelligent control of future coal-fired units, and are the main direction for the development of flexible and intelligent control technology for coal-fired units.

【基金】 国家重点研发计划(2022YFB2403200)
  • 【文献出处】 上海理工大学学报 ,Journal of University of Shanghai for Science and Technology , 编辑部邮箱 ,2023年05期
  • 【分类号】TM621
  • 【下载频次】3
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