IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i9p1317-d110578.html
   My bibliography  Save this article

Economic Valuation of Low-Load Operation with Auxiliary Firing of Coal-Fired Units

Author

Listed:
  • Gang Wang

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, No.1037, Luoyu Road, 430074 Wuhan, China)

  • Daihai You

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, No.1037, Luoyu Road, 430074 Wuhan, China)

  • Suhua Lou

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, No.1037, Luoyu Road, 430074 Wuhan, China)

  • Zhe Zhang

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, No.1037, Luoyu Road, 430074 Wuhan, China)

  • Li Dai

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, No.1037, Luoyu Road, 430074 Wuhan, China)

Abstract

It is often claimed that coal-fired units are highly inflexible to accommodate variable renewable energy. However, a recently published report illustrates that making existing coal-fired units more flexible is both technically and economically feasible. Auxiliary firing is an effective and promising measure for coal-fired units to reduce their minimum loads and thus augment their flexibility. To implement the economic valuation of low-load operation with auxiliary firing (LLOAF) of coal-fired units, we improve the traditional fuel cost model to express the operating costs of LLOAF and present the economic criterion and economic index to assess the economics of LLOAF for a single coal-fired unit. Moreover, we investigate the economic value of LLOAF in the power system operation via day-ahead unit commitment problem and analyze the impacts on the scheduling results from unit commitment policies and from extra auxiliary fuel costs. Numerical simulations show that with the reduction of the extra auxiliary fuel costs LLOAF of coal-fired units can remarkably decrease the total operating costs of the power system. Some further conclusions are finally drawn.

Suggested Citation

  • Gang Wang & Daihai You & Suhua Lou & Zhe Zhang & Li Dai, 2017. "Economic Valuation of Low-Load Operation with Auxiliary Firing of Coal-Fired Units," Energies, MDPI, vol. 10(9), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:9:p:1317-:d:110578
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/9/1317/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/9/1317/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shengli Liao & Zhifu Li & Gang Li & Jiayang Wang & Xinyu Wu, 2015. "Modeling and Optimization of the Medium-Term Units Commitment of Thermal Power," Energies, MDPI, vol. 8(11), pages 1-17, November.
    2. Morales-España, Germán & Ramírez-Elizondo, Laura & Hobbs, Benjamin F., 2017. "Hidden power system inflexibilities imposed by traditional unit commitment formulations," Applied Energy, Elsevier, vol. 191(C), pages 223-238.
    3. Baringo, L. & Conejo, A.J., 2013. "Correlated wind-power production and electric load scenarios for investment decisions," Applied Energy, Elsevier, vol. 101(C), pages 475-482.
    4. Ilias G. Marneris & Pandelis N. Biskas & Anastasios G. Bakirtzis, 2017. "Stochastic and Deterministic Unit Commitment Considering Uncertainty and Variability Reserves for High Renewable Integration," Energies, MDPI, vol. 10(1), pages 1-25, January.
    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. Ma, Ziming & Zhong, Haiwang & Xia, Qing & Kang, Chongqing & Jin, Liming, 2020. "Constraint relaxation-based day-ahead market mechanism design to promote the renewable energy accommodation," Energy, Elsevier, vol. 198(C).
    2. Gang Wang & Dahai You & Zhe Zhang & Li Dai & Qi Zou & Hengwei Liu, 2018. "Network-Constrained Unit Commitment Based on Reserve Models Fully Considering the Stochastic Characteristics of Wind Power," Energies, MDPI, vol. 11(2), pages 1-20, February.

    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. Després, Jacques & Hadjsaid, Nouredine & Criqui, Patrick & Noirot, Isabelle, 2015. "Modelling the impacts of variable renewable sources on the power sector: Reconsidering the typology of energy modelling tools," Energy, Elsevier, vol. 80(C), pages 486-495.
    2. Feng, Zhong-kai & Niu, Wen-jing & Wang, Wen-chuan & Zhou, Jian-zhong & Cheng, Chun-tian, 2019. "A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy," Energy, Elsevier, vol. 175(C), pages 618-629.
    3. Zhang, Menghan & Yang, Zhifang & Lin, Wei & Yu, Juan & Dai, Wei & Du, Ershun, 2021. "Enhancing economics of power systems through fast unit commitment with high time resolution," Applied Energy, Elsevier, vol. 281(C).
    4. Baringo, Luis & Boffino, Luigi & Oggioni, Giorgia, 2020. "Robust expansion planning of a distribution system with electric vehicles, storage and renewable units," Applied Energy, Elsevier, vol. 265(C).
    5. Luis Montero & Antonio Bello & Javier Reneses, 2022. "A Review on the Unit Commitment Problem: Approaches, Techniques, and Resolution Methods," Energies, MDPI, vol. 15(4), pages 1-40, February.
    6. Vrionis, Constantinos & Tsalavoutis, Vasilios & Tolis, Athanasios, 2020. "A Generation Expansion Planning model for integrating high shares of renewable energy: A Meta-Model Assisted Evolutionary Algorithm approach," Applied Energy, Elsevier, vol. 259(C).
    7. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    8. Rintamäki, Tuomas & Siddiqui, Afzal S. & Salo, Ahti, 2020. "Strategic offering of a flexible producer in day-ahead and intraday power markets," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1136-1153.
    9. Niina Helistö & Juha Kiviluoma & Hannele Holttinen & Jose Daniel Lara & Bri‐Mathias Hodge, 2019. "Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(5), September.
    10. Sergio Montoya-Bueno & Jose Ignacio Muñoz-Hernandez & Javier Contreras & Luis Baringo, 2020. "A Benders’ Decomposition Approach for Renewable Generation Investment in Distribution Systems," Energies, MDPI, vol. 13(5), pages 1-19, March.
    11. Wang, Qi & Huang, Chunyi & Wang, Chengmin & Li, Kangping & Xie, Ning, 2024. "Joint optimization of bidding and pricing strategy for electric vehicle aggregator considering multi-agent interactions," Applied Energy, Elsevier, vol. 360(C).
    12. Philipsen, Rens & Morales-España, Germán & de Weerdt, Mathijs & de Vries, Laurens, 2019. "Trading power instead of energy in day-ahead electricity markets," Applied Energy, Elsevier, vol. 233, pages 802-815.
    13. Manzano, J.M. & Salvador, J.R. & Romaine, J.B. & Alvarado-Barrios, L., 2022. "Economic predictive control for isolated microgrids based on real world demand/renewable energy data and forecast errors," Renewable Energy, Elsevier, vol. 194(C), pages 647-658.
    14. Zhao, Yongning & Ye, Lin & Li, Zhi & Song, Xuri & Lang, Yansheng & Su, Jian, 2016. "A novel bidirectional mechanism based on time series model for wind power forecasting," Applied Energy, Elsevier, vol. 177(C), pages 793-803.
    15. Villalobos, Cristian & Negrete-Pincetic, Matías & Figueroa, Nicolás & Lorca, Álvaro & Olivares, Daniel, 2021. "The impact of short-term pricing on flexible generation investments in electricity markets," Energy Economics, Elsevier, vol. 98(C).
    16. Ian M. Trotter & Torjus F. Bolkesj{o} & Eirik O. J{aa}stad & Jon Gustav Kirkerud, 2021. "Increased Electrification of Heating and Weather Risk in the Nordic Power System," Papers 2112.02893, arXiv.org.
    17. Boffino, Luigi & Conejo, Antonio J. & Sioshansi, Ramteen & Oggioni, Giorgia, 2019. "A two-stage stochastic optimization planning framework to decarbonize deeply electric power systems," Energy Economics, Elsevier, vol. 84(C).
    18. Yin, S. & Wang, J. & Li, Z. & Fang, X., 2021. "State-of-the-art short-term electricity market operation with solar generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    19. Seyed Reza Seyednouri & Amin Safari & Meisam Farrokhifar & Sajad Najafi Ravadanegh & Anas Quteishat & Mahmoud Younis, 2023. "Day-Ahead Scheduling of Multi-Energy Microgrids Based on a Stochastic Multi-Objective Optimization Model," Energies, MDPI, vol. 16(4), pages 1-17, February.
    20. Masoud Agabalaye-Rahvar & Amin Mansour-Saatloo & Mohammad Amin Mirzaei & Behnam Mohammadi-Ivatloo & Kazem Zare & Amjad Anvari-Moghaddam, 2020. "Robust Optimal Operation Strategy for a Hybrid Energy System Based on Gas-Fired Unit, Power-to-Gas Facility and Wind Power in Energy Markets," Energies, MDPI, vol. 13(22), pages 1-21, November.

    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:gam:jeners:v:10:y:2017:i:9:p:1317-:d:110578. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.