Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v228y2018icp1341-1352.html
   My bibliography  Save this article

Robust hydroelectric unit commitment considering integration of large-scale photovoltaic power: A case study in China

Author

Listed:
  • Ming, Bo
  • Liu, Pan
  • Guo, Shenglian
  • Cheng, Lei
  • Zhou, Yanlai
  • Gao, Shida
  • Li, He
Abstract
Hybrid generation of large-scale photovoltaic (PV) power together with hydropower offers a promising option to promote the integration of PV power, because hydro units can complement variable PV generation rapidly at relatively low cost. However, the strong variations in PV generation create uncertainties for the operation of the hydro units. To improve guidelines for large-scale hydro–PV plant operation, a stochastic hydro unit commitment model considering the uncertainty in forecasting PV power is presented. This model seeks robust solutions (i.e., hydro unit status) to minimize the hydro plant’s water consumption when external load demands are imposed onto the hybrid system. A two-layer nested optimization framework is proposed to solve the model in a hierarchical structure. In the outer layer, a cuckoo search algorithm, combined with a novel encoding strategy, optimizes the number of online units that can meet the load demand under all PV generation processes. In the inner layer, load dispatch schemes for the given number of online units are determined by dynamic programming. China’s Longyangxia hydro–PV plant was selected as a case study. Operational results were compared for three scenarios: actual operation, deterministic operation without consideration of PV forecast errors, and stochastic operation with consideration of PV forecast errors. The results indicate that: (1) the encoding strategy can handle the minimum online and offline time constraints, and can decrease optimization dimensionality; (2) the two-layer nested optimizer can make robust and effective decisions within an acceptable period when using the pre-stored optimization results provided by dynamic programming; and (3) water consumption in deterministic and stochastic operation scenarios decreased by 1.5% and 1.0%, respectively, compared to that of actual operation. These findings verify the applicability and effectiveness of the proposed methods, and also highlight the importance of decreasing uncertainty in the PV power forecast.

Suggested Citation

  • Ming, Bo & Liu, Pan & Guo, Shenglian & Cheng, Lei & Zhou, Yanlai & Gao, Shida & Li, He, 2018. "Robust hydroelectric unit commitment considering integration of large-scale photovoltaic power: A case study in China," Applied Energy, Elsevier, vol. 228(C), pages 1341-1352.
    • Handle: RePEc:eee:appene:v:228:y:2018:i:c:p:1341-1352
    DOI: 10.1016/j.apenergy.2018.07.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918310468
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2018.07.019?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. Jurasz, Jakub & Ciapała, Bartłomiej, 2017. "Integrating photovoltaics into energy systems by using a run-off-river power plant with pondage to smooth energy exchange with the power gird," Applied Energy, Elsevier, vol. 198(C), pages 21-35.
    2. Nguyen, Thang Trung & Vo, Dieu Ngoc & Truong, Anh Viet, 2014. "Cuckoo search algorithm for short-term hydrothermal scheduling," Applied Energy, Elsevier, vol. 132(C), pages 276-287.
    3. Pan Liu & Tri-Dung Nguyen & Ximing Cai & Xinhao Jiang, 2012. "Finding Multiple Optimal Solutions to Optimal Load Distribution Problem in Hydropower Plant," Energies, MDPI, vol. 5(5), pages 1-20, May.
    4. François, B. & Borga, M. & Creutin, J.D. & Hingray, B. & Raynaud, D. & Sauterleute, J.F., 2016. "Complementarity between solar and hydro power: Sensitivity study to climate characteristics in Northern-Italy," Renewable Energy, Elsevier, vol. 86(C), pages 543-553.
    5. Ding, Huajie & Hu, Zechun & Song, Yonghua, 2012. "Stochastic optimization of the daily operation of wind farm and pumped-hydro-storage plant," Renewable Energy, Elsevier, vol. 48(C), pages 571-578.
    6. Paska, Józef & Biczel, Piotr & Kłos, Mariusz, 2009. "Hybrid power systems – An effective way of utilising primary energy sources," Renewable Energy, Elsevier, vol. 34(11), pages 2414-2421.
    7. Mahmoudimehr, Javad & Shabani, Masoume, 2018. "Optimal design of hybrid photovoltaic-hydroelectric standalone energy system for north and south of Iran," Renewable Energy, Elsevier, vol. 115(C), pages 238-251.
    8. Shabani, Masoume & Mahmoudimehr, Javad, 2018. "Techno-economic role of PV tracking technology in a hybrid PV-hydroelectric standalone power system," Applied Energy, Elsevier, vol. 212(C), pages 84-108.
    9. Campana, Pietro Elia & Li, Hailong & Yan, Jinyue, 2013. "Dynamic modelling of a PV pumping system with special consideration on water demand," Applied Energy, Elsevier, vol. 112(C), pages 635-645.
    10. Jurasz, Jakub & Mikulik, Jerzy & Krzywda, Magdalena & Ciapała, Bartłomiej & Janowski, Mirosław, 2018. "Integrating a wind- and solar-powered hybrid to the power system by coupling it with a hydroelectric power station with pumping installation," Energy, Elsevier, vol. 144(C), pages 549-563.
    11. Deshmukh, M.K. & Deshmukh, S.S., 2008. "Modeling of hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(1), pages 235-249, January.
    12. Moghimi Ghadikolaei, Hadi & Ahmadi, Abdollah & Aghaei, Jamshid & Najafi, Meysam, 2012. "Risk constrained self-scheduling of hydro/wind units for short term electricity markets considering intermittency and uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4734-4743.
    13. Zhou, Yanlai & Guo, Shenglian & Chang, Fi-John & Liu, Pan & Chen, Alexander B., 2018. "Methodology that improves water utilization and hydropower generation without increasing flood risk in mega cascade reservoirs," Energy, Elsevier, vol. 143(C), pages 785-796.
    14. Bo Ming & Jian-xia Chang & Qiang Huang & Yi-min Wang & Sheng-zhi Huang, 2015. "Optimal Operation of Multi-Reservoir System Based-On Cuckoo Search Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5671-5687, December.
    15. Chen, J.J. & Zhuang, Y.B. & Li, Y.Z. & Wang, P. & Zhao, Y.L. & Zhang, C.S., 2017. "Risk-aware short term hydro-wind-thermal scheduling using a probability interval optimization model," Applied Energy, Elsevier, vol. 189(C), pages 534-554.
    16. Purvins, Arturs & Zubaryeva, Alyona & Llorente, Maria & Tzimas, Evangelos & Mercier, Arnaud, 2011. "Challenges and options for a large wind power uptake by the European electricity system," Applied Energy, Elsevier, vol. 88(5), pages 1461-1469, May.
    17. Chang, Jianxia & Li, Yunyun & Yuan, Meng & Wang, Yimin, 2017. "Efficiency evaluation of hydropower station operation: A case study of Longyangxia station in the Yellow River, China," Energy, Elsevier, vol. 135(C), pages 23-31.
    18. Baptiste François & Benoit Hingray & Marco Borga & Davide Zoccatelli & Casey Brown & Jean-Dominique Creutin, 2018. "Impact of Climate Change on Combined Solar and Run-of-River Power in Northern Italy," Energies, MDPI, vol. 11(2), pages 1-22, January.
    19. Chen, Yue & Wei, Wei & Liu, Feng & Mei, Shengwei, 2016. "Distributionally robust hydro-thermal-wind economic dispatch," Applied Energy, Elsevier, vol. 173(C), pages 511-519.
    20. Ming, Bo & Liu, Pan & Guo, Shenglian & Zhang, Xiaoqi & Feng, Maoyuan & Wang, Xianxun, 2017. "Optimizing utility-scale photovoltaic power generation for integration into a hydropower reservoir by incorporating long- and short-term operational decisions," Applied Energy, Elsevier, vol. 204(C), pages 432-445.
    21. Liu, Zhijian & Xu, Wei & Zhai, Xue & Qian, Cheng & Chen, Xi, 2017. "Feasibility and performance study of the hybrid ground-source heat pump system for one office building in Chinese heating dominated areas," Renewable Energy, Elsevier, vol. 101(C), pages 1131-1140.
    22. Kougias, Ioannis & Szabó, Sándor & Monforti-Ferrario, Fabio & Huld, Thomas & Bódis, Katalin, 2016. "A methodology for optimization of the complementarity between small-hydropower plants and solar PV systems," Renewable Energy, Elsevier, vol. 87(P2), pages 1023-1030.
    23. Monforti, F. & Huld, T. & Bódis, K. & Vitali, L. & D'Isidoro, M. & Lacal-Arántegui, R., 2014. "Assessing complementarity of wind and solar resources for energy production in Italy. A Monte Carlo approach," Renewable Energy, Elsevier, vol. 63(C), pages 576-586.
    24. Yang, Weijia & Norrlund, Per & Bladh, Johan & Yang, Jiandong & Lundin, Urban, 2018. "Hydraulic damping mechanism of low frequency oscillations in power systems: Quantitative analysis using a nonlinear model of hydropower plants," Applied Energy, Elsevier, vol. 212(C), pages 1138-1152.
    25. Beluco, Alexandre & Kroeff de Souza, Paulo & Krenzinger, Arno, 2012. "A method to evaluate the effect of complementarity in time between hydro and solar energy on the performance of hybrid hydro PV generating plants," Renewable Energy, Elsevier, vol. 45(C), pages 24-30.
    26. Li, Fang-Fang & Qiu, Jun, 2016. "Multi-objective optimization for integrated hydro–photovoltaic power system," Applied Energy, Elsevier, vol. 167(C), pages 377-384.
    27. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian & Wu, Xin-yu, 2017. "Optimization of hydropower system operation by uniform dynamic programming for dimensionality reduction," Energy, Elsevier, vol. 134(C), pages 718-730.
    28. Ding, Ming & Xu, Zhicheng & Wang, Weisheng & Wang, Xiuli & Song, Yunting & Chen, Dezhi, 2016. "A review on China׳s large-scale PV integration: Progress, challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 639-652.
    29. Bekele, Getachew & Tadesse, Getnet, 2012. "Feasibility study of small Hydro/PV/Wind hybrid system for off-grid rural electrification in Ethiopia," Applied Energy, Elsevier, vol. 97(C), pages 5-15.
    30. François, B. & Hingray, B. & Raynaud, D. & Borga, M. & Creutin, J.D., 2016. "Increasing climate-related-energy penetration by integrating run-of-the river hydropower to wind/solar mix," Renewable Energy, Elsevier, vol. 87(P1), pages 686-696.
    31. François, B. & Zoccatelli, D. & Borga, M., 2017. "Assessing small hydro/solar power complementarity in ungauged mountainous areas: A crash test study for hydrological prediction methods," Energy, Elsevier, vol. 127(C), pages 716-729.
    32. Ogliari, Emanuele & Dolara, Alberto & Manzolini, Giampaolo & Leva, Sonia, 2017. "Physical and hybrid methods comparison for the day ahead PV output power forecast," Renewable Energy, Elsevier, vol. 113(C), pages 11-21.
    33. Wang, Xianxun & Mei, Yadong & Kong, Yanjun & Lin, Yuru & Wang, Hao, 2017. "Improved multi-objective model and analysis of the coordinated operation of a hydro-wind-photovoltaic system," Energy, Elsevier, vol. 134(C), pages 813-839.
    Full references (including those not matched with items on IDEAS)

    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. Li, He & Liu, Pan & Guo, Shenglian & Ming, Bo & Cheng, Lei & Yang, Zhikai, 2019. "Long-term complementary operation of a large-scale hydro-photovoltaic hybrid power plant using explicit stochastic optimization," Applied Energy, Elsevier, vol. 238(C), pages 863-875.
    2. Kumbuso Joshua Nyoni & Anesu Maronga & Paul Gerard Tuohy & Agabu Shane, 2021. "Hydro–Connected Floating PV Renewable Energy System and Onshore Wind Potential in Zambia," Energies, MDPI, vol. 14(17), pages 1-42, August.
    3. Li, He & Liu, Pan & Guo, Shenglian & Cheng, Lei & Huang, Kangdi & Feng, Maoyuan & He, Shaokun & Ming, Bo, 2021. "Deriving adaptive long-term complementary operating rules for a large-scale hydro-photovoltaic hybrid power plant using ensemble Kalman filter," Applied Energy, Elsevier, vol. 301(C).
    4. Ming, Bo & Liu, Pan & Guo, Shenglian & Zhang, Xiaoqi & Feng, Maoyuan & Wang, Xianxun, 2017. "Optimizing utility-scale photovoltaic power generation for integration into a hydropower reservoir by incorporating long- and short-term operational decisions," Applied Energy, Elsevier, vol. 204(C), pages 432-445.
    5. Ming, Bo & Liu, Pan & Guo, Shenglian & Cheng, Lei & Zhang, Jingwen, 2019. "Hydropower reservoir reoperation to adapt to large-scale photovoltaic power generation," Energy, Elsevier, vol. 179(C), pages 268-279.
    6. Canales, Fausto A. & Jurasz, Jakub & Beluco, Alexandre & Kies, Alexander, 2020. "Assessing temporal complementarity between three variable energy sources through correlation and compromise programming," Energy, Elsevier, vol. 192(C).
    7. Jurasz, Jakub & Kies, Alexander & Zajac, Pawel, 2020. "Synergetic operation of photovoltaic and hydro power stations on a day-ahead energy market," Energy, Elsevier, vol. 212(C).
    8. Yang, Yuqi & Zhou, Jianzhong & Liu, Guangbiao & Mo, Li & Wang, Yongqiang & Jia, Benjun & He, Feifei, 2020. "Multi-plan formulation of hydropower generation considering uncertainty of wind power," Applied Energy, Elsevier, vol. 260(C).
    9. Jurasz, Jakub & Dąbek, Paweł B. & Kaźmierczak, Bartosz & Kies, Alexander & Wdowikowski, Marcin, 2018. "Large scale complementary solar and wind energy sources coupled with pumped-storage hydroelectricity for Lower Silesia (Poland)," Energy, Elsevier, vol. 161(C), pages 183-192.
    10. Wei, Hu & Hongxuan, Zhang & Yu, Dong & Yiting, Wang & Ling, Dong & Ming, Xiao, 2019. "Short-term optimal operation of hydro-wind-solar hybrid system with improved generative adversarial networks," Applied Energy, Elsevier, vol. 250(C), pages 389-403.
    11. Xianxun Wang & Lihua Chen & Qijuan Chen & Yadong Mei & Hao Wang, 2018. "Model and Analysis of Integrating Wind and PV Power in Remote and Core Areas with Small Hydropower and Pumped Hydropower Storage," Energies, MDPI, vol. 11(12), pages 1-24, December.
    12. Guo, Yi & Ming, Bo & Huang, Qiang & Wang, Yimin & Zheng, Xudong & Zhang, Wei, 2022. "Risk-averse day-ahead generation scheduling of hydro–wind–photovoltaic complementary systems considering the steady requirement of power delivery," Applied Energy, Elsevier, vol. 309(C).
    13. Shabani, Masoume & Mahmoudimehr, Javad, 2018. "Techno-economic role of PV tracking technology in a hybrid PV-hydroelectric standalone power system," Applied Energy, Elsevier, vol. 212(C), pages 84-108.
    14. Jurasz, Jakub & Beluco, Alexandre & Canales, Fausto A., 2018. "The impact of complementarity on power supply reliability of small scale hybrid energy systems," Energy, Elsevier, vol. 161(C), pages 737-743.
    15. Yuan, Wenlin & Wang, Xinqi & Su, Chengguo & Cheng, Chuntian & Liu, Zhe & Wu, Zening, 2021. "Stochastic optimization model for the short-term joint operation of photovoltaic power and hydropower plants based on chance-constrained programming," Energy, Elsevier, vol. 222(C).
    16. Feng, Zhong-kai & Huang, Qing-qing & Niu, Wen-jing & Su, Hua-ying & Li, Shu-shan & Wu, Hui-jun & Wang, Jia-yang, 2024. "Peak operation optimization of cascade hydropower reservoirs and solar power plants considering output forecasting uncertainty," Applied Energy, Elsevier, vol. 358(C).
    17. Jurasz, Jakub & Mikulik, Jerzy & Krzywda, Magdalena & Ciapała, Bartłomiej & Janowski, Mirosław, 2018. "Integrating a wind- and solar-powered hybrid to the power system by coupling it with a hydroelectric power station with pumping installation," Energy, Elsevier, vol. 144(C), pages 549-563.
    18. Xu, Bin & Zhu, Feilin & Zhong, Ping-an & Chen, Juan & Liu, Weifeng & Ma, Yufei & Guo, Le & Deng, Xiaoliang, 2019. "Identifying long-term effects of using hydropower to complement wind power uncertainty through stochastic programming," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    19. Handriyanti Diah Puspitarini & Baptiste François & Marco Baratieri & Casey Brown & Mattia Zaramella & Marco Borga, 2020. "Complementarity between Combined Heat and Power Systems, Solar PV and Hydropower at a District Level: Sensitivity to Climate Characteristics along an Alpine Transect," Energies, MDPI, vol. 13(16), pages 1-19, August.
    20. Wang, Fengjuan & Xie, Yachen & Xu, Jiuping, 2019. "Reliable-economical equilibrium based short-term scheduling towards hybrid hydro-photovoltaic generation systems: Case study from China," Applied Energy, Elsevier, vol. 253(C), pages 1-1.

    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:228:y:2018:i:c:p:1341-1352. 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.