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A new approach for clustering in desulfurization system based on modified framework for gypsum slurry quality monitoring

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  • Gu, Hui
  • Cui, Yanfeng
  • Zhu, Hongxia
  • Xue, Rui
  • Si, Fengqi

Abstract

Wet flue gas desulfurization (WFGD) is very important in reduction of SO2 emission in power plant for its lower investment cost, higher desulfurization efficiency and useful by-products. Healthy slurry works as the premise of performance analysis and optimization in WFGD system. However, little research has been conducted on monitoring gypsum slurry quality deterioration. In this paper, an on-line clustering framework has been proposed to monitor gypsum slurry quality in desulfurization system based on data mining. Compound parameterγ, is put forward to remove the influences to slurry quality from gas volume and inlet SO2 concentration to CaCO3 slurry flow. Thus, after the simplification, desulfurization efficiency, pH value and γ are taken as parameters for gypsum slurry quality monitoring. A new clustering method, EKFCM, based on improved fuzzy clustering algorithm, Kmeans and fuzzy C-means combined with entropy theory is proposed. EKFCM is superior to basic FCM in finding the clustering number without prior knowledge when dealing with off-line data, verified by a self-defined function with validity indexes comparison. A new rule, Sub-TDFO, with time decay inserted into “first in first out” in the subset, is proposed to the framework for on-line learning. Another self-defined function is added to the former one for on-line process simulation to verify the effectiveness of the proposed framework. Then, WFGD system in a 600 MW unit is worked as the clustering case study for gypsum slurry quality on-line monitoring and quantization. The clustering results from the proposed on-line framework can be applied to illustrate the process of gypsum slurry quality variation. Moreover, this method be used in other industry processes data for its on-line features.

Suggested Citation

  • Gu, Hui & Cui, Yanfeng & Zhu, Hongxia & Xue, Rui & Si, Fengqi, 2018. "A new approach for clustering in desulfurization system based on modified framework for gypsum slurry quality monitoring," Energy, Elsevier, vol. 148(C), pages 789-801.
  • Handle: RePEc:eee:energy:v:148:y:2018:i:c:p:789-801
    DOI: 10.1016/j.energy.2018.01.175
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    References listed on IDEAS

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    1. Lee, Myung gyu & Jang, Young Nam & Ryu, Kyung won & Kim, Wonbeak & Bang, Jun-Hwan, 2012. "Mineral carbonation of flue gas desulfurization gypsum for CO2 sequestration," Energy, Elsevier, vol. 47(1), pages 370-377.
    2. Bagirov, Adil M. & Yearwood, John, 2006. "A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems," European Journal of Operational Research, Elsevier, vol. 170(2), pages 578-596, April.
    3. Galos, K. A. & Smakowski, T. S. & Szlugaj, J., 2003. "Flue-gas desulphurisation products from Polish coal-fired power-plants," Applied Energy, Elsevier, vol. 75(3-4), pages 257-265, July.
    4. Islas, Jorge & Grande, Genice, 2008. "Abatement costs of SO2-control options in the Mexican electric-power sector," Applied Energy, Elsevier, vol. 85(2-3), pages 80-94, February.
    5. Kisiela, Anna M. & Czajka, Krzysztof M. & Moroń, Wojciech & Rybak, Wiesław & Andryjowicz, Czesław, 2016. "Unburned carbon from lignite fly ash as an adsorbent for SO2 removal," Energy, Elsevier, vol. 116(P3), pages 1454-1463.
    6. Sun, Zhongwei & Wang, Shengwei & Zhou, Qulan & Hui, Shi'en, 2010. "Experimental study on desulfurization efficiency and gas-liquid mass transfer in a new liquid-screen desulfurization system," Applied Energy, Elsevier, vol. 87(5), pages 1505-1512, May.
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    2. Si, Tong & Wang, Chunbo & Liu, Ruiqi & Guo, Yusheng & Yue, Shuang & Ren, Yujie, 2020. "Multi-criteria comprehensive energy efficiency assessment based on fuzzy-AHP method: A case study of post-treatment technologies for coal-fired units," Energy, Elsevier, vol. 200(C).

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