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Operation Optimization of Steam Accumulators as Thermal Energy Storage and Buffer Units

Author

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  • Wenqiang Sun

    (Department of Thermal Engineering, School of Metallurgy, Northeastern University, Shenyang 110819, China
    State Environmental Protection Key Laboratory of Eco-Industry, Northeastern University, Shenyang 110819, China)

  • Yuhao Hong

    (Department of Thermal Engineering, School of Metallurgy, Northeastern University, Shenyang 110819, China
    Department of Technology, Hangzhou Boiler Group Co., Ltd., Hangzhou 310021, China)

  • Yanhui Wang

    (Department of Thermal Engineering, School of Metallurgy, Northeastern University, Shenyang 110819, China)

Abstract

Although steam is widely used in industrial production, there is often an imbalance between steam supply and demand, which ultimately results in steam waste. To solve this problem, steam accumulators (SAs) can be used as thermal energy storage and buffer units. However, it is difficult to promote the application of SAs due to high investment costs, which directly depend on the usage volume. Thus, the operation of SAs should be optimized to reduce initial investment through volume minimization. In this work, steam sources (SSs) are classified into two types: controllable steam sources (CSSs) and uncontrollable steam sources (UCSSs). A basic oxygen furnace (BOF) was selected as an example of a UCSS to study the optimal operation of an SA with a single BOF and sets of parallel-operating BOFs. In another case, a new method whereby CSSs cooperate with SAs is reported, and the mathematical model of the minimum necessary thermal energy storage capacity (NTESC) is established. A solving program for this mathematical model is also designed. The results show that for UCSSs, applying an SA in two parallel-operating SSs requires less capacity than that required between a single SS and its consumer. For CSSs, the proposed minimum NTESC method can effectively find the optimal operation and the minimum volume of an SA. The optimized volume of an SA is smaller than that used in practice, which results in a better steam storage effect.

Suggested Citation

  • Wenqiang Sun & Yuhao Hong & Yanhui Wang, 2016. "Operation Optimization of Steam Accumulators as Thermal Energy Storage and Buffer Units," Energies, MDPI, vol. 10(1), pages 1-16, December.
    • Handle: RePEc:gam:jeners:v:10:y:2016:i:1:p:17-:d:86053
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    1. Gareth R.T. White & Svetlana Cicmil, 2016. "Knowledge acquisition through process mapping," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 65(3), pages 302-323, March.
    2. Shahin Shamsi & Mohammad R. Omidkhah, 2012. "Optimization of Steam Pressure Levels in a Total Site Using a Thermoeconomic Method," Energies, MDPI, vol. 5(3), pages 1-16, March.
    3. Tanton, D. M. & Cohen, R. R. & Probert, S. D., 1987. "Improving the effectiveness of a domestic central-heating boiler by the use of heat storage," Applied Energy, Elsevier, vol. 27(1), pages 53-82.
    4. Wil M. P. Aalst & Marcello La Rosa & Flávia Maria Santoro, 2016. "Business Process Management," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 58(1), pages 1-6, February.
    5. ., 2016. "The planning process," Chapters, in: Urban Strategies for Culture-Driven Growth, chapter 2, pages 15-30, Edward Elgar Publishing.
    6. Egorov D.A. (Егоров, Д.А.) & Perevyshina E.A. (Перевышина, Е.А.), 2016. "Modelling of Inflationary Processes in Russia [Моделирование Инфляционных Процессов В России]," Working Papers 2138, Russian Presidential Academy of National Economy and Public Administration.
    7. Wang, Yizao, 2016. "Large jumps of q-Ornstein–Uhlenbeck processes," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 110-116.
    8. ., 2016. "The scientific research process," Chapters, in: Structuring Public–Private Research Partnerships for Success, chapter 2, pages 17-26, Edward Elgar Publishing.
    9. Xu, Ershu & Yu, Qiang & Wang, Zhifeng & Yang, Chenyao, 2011. "Modeling and simulation of 1 MW DAHAN solar thermal power tower plant," Renewable Energy, Elsevier, vol. 36(2), pages 848-857.
    10. Yu. A. Kutoyants & A. Motrunich, 2016. "On multi-step MLE-process for Markov sequences," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(6), pages 705-724, August.
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