IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v164y2016icp200-210.html
   My bibliography  Save this article

Optimal capacity and type planning of generating units in a bundled wind–thermal generation system

Author

Listed:
  • Xie, Kaigui
  • Dong, Jizhe
  • Singh, Chanan
  • Hu, Bo

Abstract

Integration of large-scale wind power creates challenges for power system operations. One of the effective ways of dealing with these challenges is to build thermal power plants to form bundled wind–thermal generation system (BWTGS), i.e., using thermal power to alleviate the fluctuation of wind power. This paper presents a method for optimal capacity and type planning of BWTGS with the given wind farms. Branch-descending technique (BDT) is used to generate candidate schemes of thermal generating units by analyzing the rules of total cost changing with the reduction of the number of thermal generating units. The optimal scheme of BWTGS can be obtained by simulating a long-term operation process of BWTGS and comparing the total costs of all schemes. Techniques to accelerate computation, such as combining redundant states in dynamic programming (DP) algorithm and the saving-branch-cost technique in BDT, are developed to reduce the computational complexity. The major advantage of the proposed method is that it can be used to obtain not only the optimal capacity of thermal generating units, but also the optimal type and number of thermal generating units. Case studies are conducted to demonstrate the effectiveness of this proposed method.

Suggested Citation

  • Xie, Kaigui & Dong, Jizhe & Singh, Chanan & Hu, Bo, 2016. "Optimal capacity and type planning of generating units in a bundled wind–thermal generation system," Applied Energy, Elsevier, vol. 164(C), pages 200-210.
    • Handle: RePEc:eee:appene:v:164:y:2016:i:c:p:200-210
    DOI: 10.1016/j.apenergy.2015.12.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915015706
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2015.12.004?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. Mc Garrigle, E.V. & Leahy, P.G., 2015. "Quantifying the value of improved wind energy forecasts in a pool-based electricity market," Renewable Energy, Elsevier, vol. 80(C), pages 517-524.
    2. Wang, J. & Botterud, A. & Bessa, R. & Keko, H. & Carvalho, L. & Issicaba, D. & Sumaili, J. & Miranda, V., 2011. "Wind power forecasting uncertainty and unit commitment," Applied Energy, Elsevier, vol. 88(11), pages 4014-4023.
    3. Alishahi, Ehsan & Moghaddam, Mohsen P. & Sheikh-El-Eslami, Mohammad K., 2011. "An investigation on the impacts of regulatory interventions on wind power expansion in generation planning," Energy Policy, Elsevier, vol. 39(8), pages 4614-4623, August.
    4. Deane, J.P. & Drayton, G. & Ó Gallachóir, B.P., 2014. "The impact of sub-hourly modelling in power systems with significant levels of renewable generation," Applied Energy, Elsevier, vol. 113(C), pages 152-158.
    5. Gitizadeh, Mohsen & Kaji, Mahdi & Aghaei, Jamshid, 2013. "Risk based multiobjective generation expansion planning considering renewable energy sources," Energy, Elsevier, vol. 50(C), pages 74-82.
    6. Wang, Jiadong & Wang, Jianhui & Liu, Cong & Ruiz, Juan P., 2013. "Stochastic unit commitment with sub-hourly dispatch constraints," Applied Energy, Elsevier, vol. 105(C), pages 418-422.
    7. Xu, M. & Zhuan, X., 2013. "Optimal planning for wind power capacity in an electric power system," Renewable Energy, Elsevier, vol. 53(C), pages 280-286.
    8. Quan, Hao & Srinivasan, Dipti & Khambadkone, Ashwin M. & Khosravi, Abbas, 2015. "A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources," Applied Energy, Elsevier, vol. 152(C), pages 71-82.
    9. Baringo, L. & Conejo, A.J., 2011. "Wind power investment within a market environment," Applied Energy, Elsevier, vol. 88(9), pages 3239-3247.
    10. Thangavelu, Sundar Raj & Khambadkone, Ashwin M. & Karimi, Iftekhar A., 2015. "Long-term optimal energy mix planning towards high energy security and low GHG emission," Applied Energy, Elsevier, vol. 154(C), pages 959-969.
    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. Ji, Ling & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao & Song, Yi-Hang, 2017. "Explicit cost-risk tradeoff for renewable portfolio standard constrained regional power system expansion: A case study of Guangdong Province, China," Energy, Elsevier, vol. 131(C), pages 125-136.
    2. Zulkafli, Nur I. & Kopanos, Georgios M., 2016. "Planning of production and utility systems under unit performance degradation and alternative resource-constrained cleaning policies," Applied Energy, Elsevier, vol. 183(C), pages 577-602.
    3. Guo, Zheng & Cheng, Rui & Xu, Zhaofeng & Liu, Pei & Wang, Zhe & Li, Zheng & Jones, Ian & Sun, Yong, 2017. "A multi-region load dispatch model for the long-term optimum planning of China’s electricity sector," Applied Energy, Elsevier, vol. 185(P1), pages 556-572.
    4. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    5. Wang, B. & Liu, L. & Huang, G.H. & Li, W. & Xie, Y.L., 2018. "Effects of carbon and environmental tax on power mix planning - A case study of Hebei Province, China," Energy, Elsevier, vol. 143(C), pages 645-657.

    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. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    2. Azizipanah-Abarghooee, Rasoul & Golestaneh, Faranak & Gooi, Hoay Beng & Lin, Jeremy & Bavafa, Farhad & Terzija, Vladimir, 2016. "Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power," Applied Energy, Elsevier, vol. 182(C), pages 634-651.
    3. Jadidoleslam, Morteza & Ebrahimi, Akbar & Latify, Mohammad Amin, 2017. "Probabilistic transmission expansion planning to maximize the integration of wind power," Renewable Energy, Elsevier, vol. 114(PB), pages 866-878.
    4. Hemmati, Reza & Saboori, Hedayat & Saboori, Saeid, 2016. "Assessing wind uncertainty impact on short term operation scheduling of coordinated energy storage systems and thermal units," Renewable Energy, Elsevier, vol. 95(C), pages 74-84.
    5. Yang, Linfeng & Zhang, Chen & Jian, Jinbao & Meng, Ke & Xu, Yan & Dong, Zhaoyang, 2017. "A novel projected two-binary-variable formulation for unit commitment in power systems," Applied Energy, Elsevier, vol. 187(C), pages 732-745.
    6. Wei, Wei & Liu, Feng & Wang, Jianhui & Chen, Laijun & Mei, Shengwei & Yuan, Tiejiang, 2016. "Robust environmental-economic dispatch incorporating wind power generation and carbon capture plants," Applied Energy, Elsevier, vol. 183(C), pages 674-684.
    7. Goudarzi, Arman & Swanson, Andrew G. & Van Coller, John & Siano, Pierluigi, 2017. "Smart real-time scheduling of generating units in an electricity market considering environmental aspects and physical constraints of generators," Applied Energy, Elsevier, vol. 189(C), pages 667-696.
    8. Wang, Wenxiao & Li, Chaoshun & Liao, Xiang & Qin, Hui, 2017. "Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm," Applied Energy, Elsevier, vol. 187(C), pages 612-626.
    9. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    10. Pavić, Ivan & Capuder, Tomislav & Kuzle, Igor, 2016. "Low carbon technologies as providers of operational flexibility in future power systems," Applied Energy, Elsevier, vol. 168(C), pages 724-738.
    11. Nikoobakht, Ahmad & Aghaei, Jamshid & Mardaneh, Mohammad, 2017. "Securing highly penetrated wind energy systems using linearized transmission switching mechanism," Applied Energy, Elsevier, vol. 190(C), pages 1207-1220.
    12. Wang, Qin & Wu, Hongyu & Florita, Anthony R. & Brancucci Martinez-Anido, Carlo & Hodge, Bri-Mathias, 2016. "The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales," Applied Energy, Elsevier, vol. 184(C), pages 696-713.
    13. Li, Zhigang & Qiu, Feng & Wang, Jianhui, 2016. "Data-driven real-time power dispatch for maximizing variable renewable generation," Applied Energy, Elsevier, vol. 170(C), pages 304-313.
    14. Geng, Zhaowei & Conejo, Antonio J. & Chen, Qixin & Xia, Qing & Kang, Chongqing, 2017. "Electricity production scheduling under uncertainty: Max social welfare vs. min emission vs. max renewable production," Applied Energy, Elsevier, vol. 193(C), pages 540-549.
    15. Moghaddas Tafreshi, Seyed Masoud & Ranjbarzadeh, Hassan & Jafari, Mehdi & Khayyam, Hamid, 2016. "A probabilistic unit commitment model for optimal operation of plug-in electric vehicles in microgrid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 934-947.
    16. Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
    17. Sadeghi, Hadi & Rashidinejad, Masoud & Abdollahi, Amir, 2017. "A comprehensive sequential review study through the generation expansion planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1369-1394.
    18. Liang, Zhengtang & Liang, Jun & Zhang, Li & Wang, Chengfu & Yun, Zhihao & Zhang, Xu, 2015. "Analysis of multi-scale chaotic characteristics of wind power based on Hilbert–Huang transform and Hurst analysis," Applied Energy, Elsevier, vol. 159(C), pages 51-61.
    19. Luís A. C. Roque & Dalila B. M. M. Fontes & Fernando A. C. C. Fontes, 2017. "A Metaheuristic Approach to the Multi-Objective Unit Commitment Problem Combining Economic and Environmental Criteria," Energies, MDPI, vol. 10(12), pages 1-25, December.
    20. Chinmoy, Lakshmi & Iniyan, S. & Goic, Ranko, 2019. "Modeling wind power investments, policies and social benefits for deregulated electricity market – A review," Applied Energy, Elsevier, vol. 242(C), pages 364-377.

    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:164:y:2016:i:c:p:200-210. 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.