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A generic algorithm of sustainability (GAS) function for industrial complex steam turbine and utility system optimisation

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  • Douglas, Tamunosaki
  • Big-Alabo, Akuro

Abstract

The GAS-function methodology is introduced in this paper in order to identify the sustainability objective function for optimisation of multiple interconnected complex steam turbines and utility network (ICSTUN) systems. Also, the complex steam turbine was modelled based on induction machine operation which enhances its performance. The boiler models were identified as the sustainability objective function which was further investigated under given operating constraints for optimisation of the ICSTUN system. The validated results show that relative error between field operation and simulation data were less than 1% on average, which is acceptable for engineering applications. The optimisation results indicate that contrary to previous authors' results and by comparing with actual field operational data information, coal flow rates for total site utility system of this investigated ICSTUN can be significantly reduced. It was therefore concluded that a significant reduction in the coal flow rate amounts is practicable in order to significantly reduce operating costs as well as the environmental and social issues associated with utilising fossil-fuels, while still satisfying the demand-side management objectives for the plant.

Suggested Citation

  • Douglas, Tamunosaki & Big-Alabo, Akuro, 2018. "A generic algorithm of sustainability (GAS) function for industrial complex steam turbine and utility system optimisation," Energy, Elsevier, vol. 164(C), pages 881-897.
    • Handle: RePEc:eee:energy:v:164:y:2018:i:c:p:881-897
    DOI: 10.1016/j.energy.2018.09.016
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    References listed on IDEAS

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    1. Luo, Xianglong & Zhang, Bingjian & Chen, Ying & Mo, Songping, 2013. "Operational planning optimization of steam power plants considering equipment failure in petrochemical complex," Applied Energy, Elsevier, vol. 112(C), pages 1247-1264.
    2. Gerta Zimmer, 2008. "Modelling and simulation of steam turbine processes: individual models for individual tasks," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 14(6), pages 469-493, July.
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    Cited by:

    1. Paweł Ziółkowski & Marta Drosińska-Komor & Jerzy Głuch & Łukasz Breńkacz, 2023. "Review of Methods for Diagnosing the Degradation Process in Power Units Cooperating with Renewable Energy Sources Using Artificial Intelligence," Energies, MDPI, vol. 16(17), pages 1-28, August.
    2. Yu Huang & Weizhen Hou & Yiran Huang & Jiayu Li & Qixian Li & Dongfeng Wang & Yan Zhang, 2020. "Multi-Objective Optimal Operation for Steam Power Scheduling Based on Economic and Exergetic Analysis," Energies, MDPI, vol. 13(8), pages 1-18, April.
    3. Shen, Feifei & Zhao, Liang & Du, Wenli & Zhong, Weimin & Qian, Feng, 2020. "Large-scale industrial energy systems optimization under uncertainty: A data-driven robust optimization approach," Applied Energy, Elsevier, vol. 259(C).

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