IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v374y2024ics0306261924014727.html

Optimization of the capacity configuration of an abandoned mine pumped storage/wind/photovoltaic integrated system

Author

Listed:
  • Ren, Yan
  • Sun, Ketao
  • Zhang, Kai
  • Han, Yuping
  • Zhang, Haonan
  • Wang, Meijing
  • Jing, Xiang
  • Mo, Juhua
  • Zou, Wenhang
  • Xing, Xinyang

Abstract

Constructing a new power system with renewable energy as the main component is an important measure for coping with extreme weather and maintaining the stability and efficiency of the power system; in particular, pumped storage is an effective means of smoothing fluctuations in the wind and photovoltaic power output. Therefore, considering the reutilization of abandoned mines, this paper constructs an integrated abandoned mine pumped storage/wind power/photovoltaic system. By establishing the mathematical model and capacity configuration model of the system, an analysis of wind/photovoltaic output characteristics is carried out. A nondominated sorting genetic algorithm is used to solve the optimisation problem, with the goals of maximizing the power supply guarantee rate and new energy absorption rate and minimizing the levelized cost of energy. On this basis, a grid power transmission channel optimization strategy is established to ensure that power transmission to the grid is maximized. The monthly power supply guarantee rate and monthly new energy absorption rate in the configuration results are compared and analysed, and the sensitivity of wind power, optical power, initial investment cost, and effective on-grid power to the levelized cost of electricity is considered. Then, by combining the abandoned mine data, eight different sets of parameters of pumped storage are selected for the optimal configuration study, and the factors influencing the pumped storage regulation capacity are studied. Finally, based on the original three objective functions, the storage equivalent utilization rate, system complementarity, power generation revenue, new energy access rate and new energy utilization rate are added to the analysis, and the hierarchical analysis method combined with fuzzy comprehensive evaluation is used to evaluate the comprehensive benefits of pumped storage with nine different parameters. The optimized capacity configuration of the standard pumped storage of 1200 MW results in a levelized cost of energy of 0.2344 CYN/kWh under the condition that the guaranteed power supply rate and the new energy absorption rate are both >90%, and the study on the factors influencing the regulating capacity of pumped storage concludes that the rated head, the adjustable reservoir capacity and the installed capacity of the pumped storage are positively correlated with its regulating capacity. Through comprehensive benefit evaluation, it is concludes that pumped storage type 5 provides the greatest comprehensive benefit. This study provides valuable reference information for reducing the impact of renewable energy on the power grid and realizing the reuse of abandoned mines.

Suggested Citation

  • Ren, Yan & Sun, Ketao & Zhang, Kai & Han, Yuping & Zhang, Haonan & Wang, Meijing & Jing, Xiang & Mo, Juhua & Zou, Wenhang & Xing, Xinyang, 2024. "Optimization of the capacity configuration of an abandoned mine pumped storage/wind/photovoltaic integrated system," Applied Energy, Elsevier, vol. 374(C).
    • Handle: RePEc:eee:appene:v:374:y:2024:i:c:s0306261924014727
    DOI: 10.1016/j.apenergy.2024.124089
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924014727
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.124089?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Hao Zhang & Jingyue Yang & Chenxi Li & Pengcheng Guo & Jun Liu & Ruibao Jin & Jing Hu & Fengyuan Gan & Fei Cao, 2024. "Reasonable Energy-Abandonment Operation of a Combined Power Generation System with an Ultra-High Proportion of Renewable Energy," Energies, MDPI, vol. 17(8), pages 1-18, April.
    2. Zhou, Yue & Wang, Chengshan & Wu, Jianzhong & Wang, Jidong & Cheng, Meng & Li, Gen, 2017. "Optimal scheduling of aggregated thermostatically controlled loads with renewable generation in the intraday electricity market," Applied Energy, Elsevier, vol. 188(C), pages 456-465.
    3. Yang Li & Feilong Hong & Xiaohui Ge & Xuesong Zhang & Bo Zhao & Feng Wu, 2023. "Optimal Capacity Configuration of Pumped-Storage Units Used to Retrofit Cascaded Hydropower Stations," Energies, MDPI, vol. 16(24), pages 1-22, December.
    4. Zhi Zhang & Dan Xu & Xuezhen Chan & Guobin Xu, 2023. "Research on Power System Day-Ahead Generation Scheduling Method Considering Combined Operation of Wind Power and Pumped Storage Power Station," Sustainability, MDPI, vol. 15(7), pages 1-14, April.
    5. Estanislao Pujades & Philippe Orban & Pierre Archambeau & Vasileios Kitsikoudis & Sebastien Erpicum & Alain Dassargues, 2020. "Underground Pumped-Storage Hydropower (UPSH) at the Martelange Mine (Belgium): Interactions with Groundwater Flow," Energies, MDPI, vol. 13(9), pages 1-21, May.
    6. Ahmed S. Menesy & Hamdy M. Sultan & Ibrahim O. Habiballah & Hasan Masrur & Kaisar R. Khan & Muhammad Khalid, 2023. "Optimal Configuration of a Hybrid Photovoltaic/Wind Turbine/Biomass/Hydro-Pumped Storage-Based Energy System Using a Heap-Based Optimization Algorithm," Energies, MDPI, vol. 16(9), pages 1-26, April.
    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. Superchi, Francesco & Moustakis, Antonis & Pechlivanoglou, George & Bianchini, Alessandro, 2025. "On the importance of degradation modeling for the robust design of hybrid energy systems including renewables and storage," Applied Energy, Elsevier, vol. 377(PD).
    2. Yunfei Hu & Kefei Zhang & Sheng Liu & Zhong Wang, 2025. "Research on Day-Ahead Optimal Scheduling of Wind–PV–Thermal–Pumped Storage Based on the Improved Multi-Objective Jellyfish Search Algorithm," Energies, MDPI, vol. 18(9), pages 1-38, April.
    3. Zhang, Hao & Song, Yan & Zhang, Ming & Duan, Ye & Zhao, Danning, 2025. "Ecological environmental impact assessment of photovoltaic and "photovoltaic +" development in China," Renewable Energy, Elsevier, vol. 252(C).
    4. Gao, Chunyang & Wu, Haikun & Li, JiQing & Yu, Xiangyang & Nan, Haipeng & Guo, Pengcheng & Meng, Zhijie & Liu, Weixing & Shen, Shikang, 2025. "Mechanism analysis and suppression strategy of reverse flow phenomenon in variable speed pumped storage units under pump mode," Energy, Elsevier, vol. 325(C).
    5. Huaying Su & Yupeng Li & Yan Zhang & Yujian Wang & Gang Li & Chuntian Cheng, 2025. "A Mid-Term Scheduling Method for Cascade Hydropower Stations to Safeguard Against Continuous Extreme New Energy Fluctuations," Energies, MDPI, vol. 18(14), pages 1-17, July.
    6. Hai Jiang & Haoshuai Jia & Yong Qiao & Wenzhi Liu & Yijun Miao & Wuhao Wen & Ruonan Li & Chang Wen, 2025. "Rural Renewable Energy Resources Assessment and Electricity Development Scenario Simulation Based on the LEAP Model," Energies, MDPI, vol. 18(14), pages 1-21, July.
    7. Yan Ren & Haonan Zhang & Lile Wu & Kai Zhang & Zutian Cheng & Ketao Sun & Yuan Sun & Leiming Hu, 2025. "Research on the Health Evaluation of a Pump Turbine in Smoothing Output Volatility of the Hybrid System Under a High Proportion of Wind and Photovoltaic Power Connection," Energies, MDPI, vol. 18(5), pages 1-30, March.
    8. Li, Wanying & Dong, Fugui & Liu, Jiamei & Wang, Peijun & Zhao, Xinru, 2024. "A three-stage decision-making study on capacity configuration of hydropower-wind-photovoltaic-storage complementary systems considering uncertainty," Energy, Elsevier, vol. 313(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. Diaz, Cesar & Ruiz, Fredy & Patino, Diego, 2017. "Modeling and control of water booster pressure systems as flexible loads for demand response," Applied Energy, Elsevier, vol. 204(C), pages 106-116.
    2. Vasileios Kitsikoudis & Pierre Archambeau & Benjamin Dewals & Estanislao Pujades & Philippe Orban & Alain Dassargues & Michel Pirotton & Sebastien Erpicum, 2020. "Underground Pumped-Storage Hydropower (UPSH) at the Martelange Mine (Belgium): Underground Reservoir Hydraulics," Energies, MDPI, vol. 13(14), pages 1-16, July.
    3. Iria, José & Soares, Filipe & Matos, Manuel, 2019. "Optimal bidding strategy for an aggregator of prosumers in energy and secondary reserve markets," Applied Energy, Elsevier, vol. 238(C), pages 1361-1372.
    4. Ryan S. Montrose & John F. Gardner & Aykut C. Satici, 2021. "Centralized and Decentralized Optimal Control of Variable Speed Heat Pumps," Energies, MDPI, vol. 14(13), pages 1-18, July.
    5. Xiaolin Ayón & María Ángeles Moreno & Julio Usaola, 2017. "Aggregators’ Optimal Bidding Strategy in Sequential Day-Ahead and Intraday Electricity Spot Markets," Energies, MDPI, vol. 10(4), pages 1-20, April.
    6. Xin Zhou & Yuejin Zhou & Xiaoding Xu & Chunlin Zeng & Chaobin Zhu, 2023. "Hydraulic Characteristics Analysis of Double-Bend Roadway of Abandoned Mine Pumped Storage," Sustainability, MDPI, vol. 15(5), pages 1-15, February.
    7. Zhong, Shengyuan & Wang, Xiaoyuan & Zhao, Jun & Li, Wenjia & Li, Hao & Wang, Yongzhen & Deng, Shuai & Zhu, Jiebei, 2021. "Deep reinforcement learning framework for dynamic pricing demand response of regenerative electric heating," Applied Energy, Elsevier, vol. 288(C).
    8. Aswad Adib & Joao Onofre Pereira Pinto & Madhu S. Chinthavali, 2023. "GA-Based Voltage Optimization of Distribution Feeder with High-Penetration of DERs Using Megawatt-Scale Units," Energies, MDPI, vol. 16(13), pages 1-10, June.
    9. Wei, Congying & Xu, Jian & Liao, Siyang & Sun, Yuanzhang & Jiang, Yibo & Ke, Deping & Zhang, Zhen & Wang, Jing, 2018. "A bi-level scheduling model for virtual power plants with aggregated thermostatically controlled loads and renewable energy," Applied Energy, Elsevier, vol. 224(C), pages 659-670.
    10. Xia, Mingchao & Song, Yuguang & Chen, Qifang, 2019. "Hierarchical control of thermostatically controlled loads oriented smart buildings," Applied Energy, Elsevier, vol. 254(C).
    11. Baoyu Wei & Lu Gao & Hongbao Zhao, 2025. "Study on the Seismic Stability of Urban Sewage Treatment and Underground Reservoir of an Abandoned Mine Pumped Storage Power Station," Sustainability, MDPI, vol. 17(12), pages 1-25, June.
    12. Kai Ma & Chenliang Yuan & Jie Yang & Zhixin Liu & Xinping Guan, 2017. "Switched Control Strategies of Aggregated Commercial HVAC Systems for Demand Response in Smart Grids," Energies, MDPI, vol. 10(7), pages 1-18, July.
    13. Adhikari, Rajendra & Pipattanasomporn, M. & Rahman, S., 2018. "An algorithm for optimal management of aggregated HVAC power demand using smart thermostats," Applied Energy, Elsevier, vol. 217(C), pages 166-177.
    14. Iria, José & Soares, Filipe & Matos, Manuel, 2018. "Optimal supply and demand bidding strategy for an aggregator of small prosumers," Applied Energy, Elsevier, vol. 213(C), pages 658-669.
    15. Takele Ferede Agajie & Armand Fopah-Lele & Isaac Amoussou & Ahmed Ali & Baseem Khan & Om Prakash Mahela & Ramakrishna S. S. Nuvvula & Divine Khan Ngwashi & Emmanuel Soriano Flores & Emmanuel Tanyi, 2023. "Techno-Economic Analysis and Optimization of Hybrid Renewable Energy System with Energy Storage under Two Operational Modes," Sustainability, MDPI, vol. 15(15), pages 1-31, July.
    16. Kong, Xiangyu & Kong, Deqian & Yao, Jingtao & Bai, Linquan & Xiao, Jie, 2020. "Online pricing of demand response based on long short-term memory and reinforcement learning," Applied Energy, Elsevier, vol. 271(C).
    17. Diaz-Londono, Cesar & Enescu, Diana & Ruiz, Fredy & Mazza, Andrea, 2020. "Experimental modeling and aggregation strategy for thermoelectric refrigeration units as flexible loads," Applied Energy, Elsevier, vol. 272(C).
    18. Bomela, Walter & Zlotnik, Anatoly & Li, Jr-Shin, 2018. "A phase model approach for thermostatically controlled load demand response," Applied Energy, Elsevier, vol. 228(C), pages 667-680.
    19. Song, Yuguang & Xia, Mingchao & Chen, Qifang & Chen, Fangjian, 2023. "A data-model fusion dispatch strategy for the building energy flexibility based on the digital twin," Applied Energy, Elsevier, vol. 332(C).
    20. Bahrami, Shahab & Amini, M. Hadi, 2018. "A decentralized trading algorithm for an electricity market with generation uncertainty," Applied Energy, Elsevier, vol. 218(C), pages 520-532.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:374:y:2024:i:c:s0306261924014727. 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.