The Determination of Optimal Excess Air Coefficient Based on Data Mining in Power Plant

  • Authors:
  • Jian-qiang Li;Cheng-lin Niu;Jun-jie Gu;Ji-zhen Liu

  • Affiliations:
  • -;-;-;-

  • Venue:
  • FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 05
  • Year:
  • 2008

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Abstract

Coal-fired boiler combustion system in power plant is a complex multi-input and multi-output plant with strong nonlinear and large time-delay. The determination of the optimal excess air coefficient is very important for economical analysis and operation optimization and it is a difficulty and bottleneck for operation optimization in power plants. Based on the association characteristic in electric industrial data, this paper proposes the operation optimization based on data mining in power plant. The improved fuzzy association rule mining algorithm is proposed and introduced to find the operation optimization values to guide the operation in power plant. Based on the actual history data in 300MW unit, the optimization values in typical load ranges are found out by data mining to provide better guidance. Experiment results show that the operation optimization value determined by the improved fuzzy association rule mining algorithm can improve the efficiency and can be used to guide the operation online.