IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v112y2013icp12-22.html
   My bibliography  Save this article

Stochastic optimization approach to water management in cooling-constrained power plants

Author

Listed:
  • Salazar, Juan M.
  • Diwekar, Urmila
  • Constantinescu, Emil
  • Zavala, Victor M.

Abstract

A stochastic optimization framework for water management in cooling-constrained power plants is proposed. The approach determines optimal set-points to maximize power output in the presence of uncertain weather conditions and water intake constraints. Weather uncertainty is quantified in the form of ensembles using the state-of-the-art numerical weather prediction model WRF. The framework enables the handling of first-principles black-box simulation models by using the reweighting scheme implemented in the BONUS solver. In addition, it enables the construction of empirical distributions from limited samples obtained from WRF. Using these computational capabilities, the effects of cooling constraints and weather conditions on generation capacity are investigated. In a pulverized coal power plant study it has been found that weather fluctuations make the maximum plant output vary in the range of 5–10% of the nominal capacity in intraday operations. In addition, it has been found that stochastic optimization can lead to daily capacity gains of as much as 245MWh over current practice and enables more robust bidding procedures. It is demonstrated that reweighting schemes can enable real-time implementations.

Suggested Citation

  • Salazar, Juan M. & Diwekar, Urmila & Constantinescu, Emil & Zavala, Victor M., 2013. "Stochastic optimization approach to water management in cooling-constrained power plants," Applied Energy, Elsevier, vol. 112(C), pages 12-22.
    • Handle: RePEc:eee:appene:v:112:y:2013:i:c:p:12-22
    DOI: 10.1016/j.apenergy.2013.05.077
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626191300500X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2013.05.077?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dubreuil, Aurelie & Assoumou, Edi & Bouckaert, Stephanie & Selosse, Sandrine & Maı¨zi, Nadia, 2013. "Water modeling in an energy optimization framework – The water-scarce middle east context," Applied Energy, Elsevier, vol. 101(C), pages 268-279.
    2. Kemal Sahin & Urmila Diwekar, 2004. "Better Optimization of Nonlinear Uncertain Systems (BONUS): A New Algorithm for Stochastic Programming Using Reweighting through Kernel Density Estimation," Annals of Operations Research, Springer, vol. 132(1), pages 47-68, November.
    3. Jeff Linderoth & Alexander Shapiro & Stephen Wright, 2006. "The empirical behavior of sampling methods for stochastic programming," Annals of Operations Research, Springer, vol. 142(1), pages 215-241, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Martín, Mariano & Martín, Mónica, 2017. "Cooling limitations in power plants: Optimal multiperiod design of natural draft cooling towers," Energy, Elsevier, vol. 135(C), pages 625-636.
    2. Pablo T. Rodriguez-Gonzalez & Vicente Rico-Ramirez & Ramiro Rico-Martinez & Urmila M. Diwekar, 2019. "A New Approach to Solving Stochastic Optimal Control Problems," Mathematics, MDPI, vol. 7(12), pages 1-13, December.
    3. Wang, Weiliang & Zhang, Hai & Li, Zheng & Lv, Junfu & Ni, Weidou & Li, Yongsheng, 2016. "Adoption of enclosure and windbreaks to prevent the degradation of the cooling performance for a natural draft dry cooling tower under crosswind conditions," Energy, Elsevier, vol. 116(P2), pages 1360-1369.
    4. Guerra, Omar J. & Reklaitis, Gintaras V., 2018. "Advances and challenges in water management within energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 4009-4019.
    5. Zhu, Xiaojie & Guo, Ruipeng & Chen, Bin & Zhang, Jing & Hayat, Tasawar & Alsaedi, Ahmed, 2015. "Embodiment of virtual water of power generation in the electric power system in China," Applied Energy, Elsevier, vol. 151(C), pages 345-354.
    6. Khayyam, Hamid & Naebe, Minoo & Bab-Hadiashar, Alireza & Jamshidi, Farshid & Li, Quanxiang & Atkiss, Stephen & Buckmaster, Derek & Fox, Bronwyn, 2015. "Stochastic optimization models for energy management in carbonization process of carbon fiber production," Applied Energy, Elsevier, vol. 158(C), pages 643-655.
    7. Wu, Zhiyong & Lu, Zhibin & Zhang, Bingjian & He, Chang & Chen, Qinglin & Yu, Haoshui & Ren, Jingzheng, 2022. "Stochastic bi-objective optimization for closed wet cooling tower systems based on a simplified analytical model," Energy, Elsevier, vol. 250(C).
    8. Wang, Weiliang & Zhang, Hai & Liu, Pei & Li, Zheng & Lv, Junfu & Ni, Weidou, 2017. "The cooling performance of a natural draft dry cooling tower under crosswind and an enclosure approach to cooling efficiency enhancement," Applied Energy, Elsevier, vol. 186(P3), pages 336-346.
    9. Jamil, Ahmad & Javed, Adeel & Wajid, Abdul & Zeb, Muhammad Omar & Ali, Majid & Khoja, Asif Hussain & Imran, Muhammad, 2021. "Multiparametric optimization for reduced condenser cooling water consumption in a degraded combined cycle gas turbine power plant from a water-energy nexus perspective," Applied Energy, Elsevier, vol. 304(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Can & Zheng, Xinzhu & Cai, Wenjia & Gao, Xue & Berrill, Peter, 2017. "Unexpected water impacts of energy-saving measures in the iron and steel sector: Tradeoffs or synergies?," Applied Energy, Elsevier, vol. 205(C), pages 1119-1127.
    2. Dai, Jiangyu & Wu, Shiqiang & Han, Guoyi & Weinberg, Josh & Xie, Xinghua & Wu, Xiufeng & Song, Xingqiang & Jia, Benyou & Xue, Wanyun & Yang, Qianqian, 2018. "Water-energy nexus: A review of methods and tools for macro-assessment," Applied Energy, Elsevier, vol. 210(C), pages 393-408.
    3. Güzin Bayraksan & David P. Morton, 2011. "A Sequential Sampling Procedure for Stochastic Programming," Operations Research, INFORMS, vol. 59(4), pages 898-913, August.
    4. Yulei Xie & Linrui Wang & Guohe Huang & Dehong Xia & Ling Ji, 2018. "A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China," Energies, MDPI, vol. 11(8), pages 1-24, August.
    5. Emelogu, Adindu & Chowdhury, Sudipta & Marufuzzaman, Mohammad & Bian, Linkan & Eksioglu, Burak, 2016. "An enhanced sample average approximation method for stochastic optimization," International Journal of Production Economics, Elsevier, vol. 182(C), pages 230-252.
    6. Shi, Qingxin & Li, Fangxing & Dong, Jin & Olama, Mohammed & Wang, Xiaofei & Winstead, Chris & Kuruganti, Teja, 2022. "Co-optimization of repairs and dynamic network reconfiguration for improved distribution system resilience," Applied Energy, Elsevier, vol. 318(C).
    7. Guerra, Omar J. & Reklaitis, Gintaras V., 2018. "Advances and challenges in water management within energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 4009-4019.
    8. Jörn Dunkel & Stefan Weber, 2010. "Stochastic Root Finding and Efficient Estimation of Convex Risk Measures," Operations Research, INFORMS, vol. 58(5), pages 1505-1521, October.
    9. Soham Ghosh & Sujay Mukhoti, 2023. "Non-parametric generalised newsvendor model," Annals of Operations Research, Springer, vol. 321(1), pages 241-266, February.
    10. Bieber, Niclas & Ker, Jen Ho & Wang, Xiaonan & Triantafyllidis, Charalampos & van Dam, Koen H. & Koppelaar, Rembrandt H.E.M. & Shah, Nilay, 2018. "Sustainable planning of the energy-water-food nexus using decision making tools," Energy Policy, Elsevier, vol. 113(C), pages 584-607.
    11. Bouckaert, Stéphanie & Assoumou, Edi & Selosse, Sandrine & Maïzi, Nadia, 2014. "A prospective analysis of waste heat management at power plants and water conservation issues using a global TIMES model," Energy, Elsevier, vol. 68(C), pages 80-91.
    12. Masato Wada & Felipe Delgado & Bernardo K. Pagnoncelli, 2017. "A risk averse approach to the capacity allocation problem in the airline cargo industry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 643-651, June.
    13. Xie, Y.L. & Huang, G.H. & Li, W. & Ji, L., 2014. "Carbon and air pollutants constrained energy planning for clean power generation with a robust optimization model—A case study of Jining City, China," Applied Energy, Elsevier, vol. 136(C), pages 150-167.
    14. Lee, Adrian J. & Diwekar, Urmila M., 2012. "Optimal sensor placement in integrated gasification combined cycle power systems," Applied Energy, Elsevier, vol. 99(C), pages 255-264.
    15. Aydin, Nezir & Murat, Alper, 2013. "A swarm intelligence based sample average approximation algorithm for the capacitated reliable facility location problem," International Journal of Production Economics, Elsevier, vol. 145(1), pages 173-183.
    16. Ankur Kulkarni & Uday Shanbhag, 2012. "Recourse-based stochastic nonlinear programming: properties and Benders-SQP algorithms," Computational Optimization and Applications, Springer, vol. 51(1), pages 77-123, January.
    17. Nesbitt, Peter & Blake, Lewis R. & Lamas, Patricio & Goycoolea, Marcos & Pagnoncelli, Bernardo K. & Newman, Alexandra & Brickey, Andrea, 2021. "Underground mine scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 294(1), pages 340-352.
    18. Vakilifard, Negar & A. Bahri, Parisa & Anda, Martin & Ho, Goen, 2019. "An interactive planning model for sustainable urban water and energy supply," Applied Energy, Elsevier, vol. 235(C), pages 332-345.
    19. Fang, Delin & Chen, Bin, 2017. "Linkage analysis for the water–energy nexus of city," Applied Energy, Elsevier, vol. 189(C), pages 770-779.
    20. Philpott, A.B. & de Matos, V.L., 2012. "Dynamic sampling algorithms for multi-stage stochastic programs with risk aversion," European Journal of Operational Research, Elsevier, vol. 218(2), pages 470-483.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:112:y:2013:i:c:p:12-22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.