数据驱动型实时燃烧优化控制架构及应用
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TM621

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Architecture and application of data-driven on-line combustion optimization control
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    摘要:

    在安全运行基础上,为提高火电机组经济性和环保性,提出了基于历史运行数据、燃烧试验数据和实时运行数据的燃烧优化自动控制架构。在该架构中引入稳态检测、锅炉效率在线计算、数据挖掘、非线性建模、智能优化等技术,得到用于燃烧优化的运行控制基准和实时控制增量指令。这些数据经过可靠的通信和安全无扰的控制逻辑与原控制系统进行融合,根据机组运行状态参与锅炉燃烧实时控制优化。基于该架构的燃烧优化系统已在燃煤电厂实际应用,在宽负荷范围内实现了燃烧运行状态分析、指令自动优化和锅炉效率提升。可基于该自动控制架构拓展优化其中各技术要素,并应用到其他各种炉型和控制系统中。

    Abstract:

    Under the premise of safe operation, to improve the economy and environmental protection of thermal power units, a combustion optimization framework is proposed, based on the historical operation data, combustion adjustment data and real-time running data. In this framework, steady-state detection, on-line calculation of boiler efficiency, data mining, nonlinear modeling, intelligent optimization and other techniques are adopted, and basic control references and real-time control increments are obtained. After reliable communication and undisturbed configuration with DCS, these results can participate in the real-time control optimization of boiler combustion, according to the running state of the thermal power unit. It has been applied in coal-fired power plant, realizing analysis of combustion states, automatic optimization of setpoints and improvement of boiler efficiency in a wide range of load. Based on the framework, the technical elements can be expanded and optimized, and it can be applied to various types of boilers and control systems.

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吴坡,段松涛,张江南,贺勇,朱峰.数据驱动型实时燃烧优化控制架构及应用[J].电力工程技术,2021,40(2):197-204

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历史
  • 收稿日期:2020-10-07
  • 最后修改日期:2020-11-22
  • 录用日期:2020-03-04
  • 在线发布日期: 2021-04-02
  • 出版日期: 2021-03-28