IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v357y2024ics0306261923018196.html
   My bibliography  Save this article

Joint operation of mobile battery, power system, and transportation system for improving the renewable energy penetration rate

Author

Listed:
  • Liu, Shan
  • Yan, Jie
  • Yan, Yamin
  • Zhang, Haoran
  • Zhang, Jing
  • Liu, Yongqian
  • Han, Shuang

Abstract

Future energy system will feature in a high-share of renewable energies (REs), which poses huge challenges to obtain full utilization of renewable power generation. To solve the problem, this paper presents a joint-operation two-stage mixed integer linear programming model to coordinate the power system and train transportation system by optimizing the logistics of mobile batteries and real-time charge/discharge in cities. The full/empty batteries are transported through the train transportation system between the load side and the renewable energy station, which improves renewable energy penetration, economics, and mobilities. The first-stage model deals with the preliminary logistic optimization of batteries including routes, time and capacities of transportation, and the second-stage model optimizes real-time schedule of charge/discharge of batteries. The aim of the proposed model is to minimize the transportation cost, maximize the utilization rate of renewable energy in an energy system and smooth the daily load curve. The proposed model considers technical constraints such as railway transportation capacity, load demand satisfaction and renewable energy consumption in the power system. The optimal logistics plan and real-time charging and discharging plan can be obtained for both full and empty battery transportation. The validity of the method is verified with real data from Northeast China and Northern China, including railway routes, renewable energy output, and load profiles. The results show that the renewable energy penetration rate increases from 84.4% to 95.3% in Northeast China and from 42.7% to 78.2% in Northern China under the 2050 scenario with the proposed method. The peak-to-valley difference in the daily load curve decreases by 84% and 100% in Northeast China and Northern China, respectively. Meanwhile, the case study shows that the costs of battery transportation decrease from 0.398 CNY/kWh and 0.377 CNY/kWh to 0.252 CNY/kWh and 0.254 CNY/kWh when energy density of battery increases from 0.170 kWh/kg to 0.250 kWh/kg. This indicates that mobile energy storage has great economics. Moreover, renewable energy penetration rate is increased and peak-to-valley difference of daily load curve is decreased with no additional transmission lines.

Suggested Citation

  • Liu, Shan & Yan, Jie & Yan, Yamin & Zhang, Haoran & Zhang, Jing & Liu, Yongqian & Han, Shuang, 2024. "Joint operation of mobile battery, power system, and transportation system for improving the renewable energy penetration rate," Applied Energy, Elsevier, vol. 357(C).
    • Handle: RePEc:eee:appene:v:357:y:2024:i:c:s0306261923018196
    DOI: 10.1016/j.apenergy.2023.122455
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923018196
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.122455?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. Shen, Yueqing & Qian, Tong & Li, Weiwei & Zhao, Wei & Tang, Wenhu & Chen, Xingyu & Yu, Zeyuan, 2023. "Mobile energy storage systems with spatial–temporal flexibility for post-disaster recovery of power distribution systems: A bilevel optimization approach," Energy, Elsevier, vol. 282(C).
    2. Pusceddu, Elian & Zakeri, Behnam & Castagneto Gissey, Giorgio, 2021. "Synergies between energy arbitrage and fast frequency response for battery energy storage systems," Applied Energy, Elsevier, vol. 283(C).
    3. J. -F. Mercure & H. Pollitt & A. M. Bassi & J. E Vi~nuales & N. R. Edwards, 2015. "Modelling complex systems of heterogeneous agents to better design sustainability transitions policy," Papers 1506.07432, arXiv.org, revised Feb 2016.
    4. Li, Shenglin & Zhu, Jizhong & Dong, Hanjiang & Zhu, Haohao & Fan, Junwei, 2022. "A novel rolling optimization strategy considering grid-connected power fluctuations smoothing for renewable energy microgrids," Applied Energy, Elsevier, vol. 309(C).
    5. Li, Ru & Tang, Bao-Jun & Yu, Biying & Liao, Hua & Zhang, Chen & Wei, Yi-Ming, 2022. "Cost-optimal operation strategy for integrating large scale of renewable energy in China’s power system: From a multi-regional perspective," Applied Energy, Elsevier, vol. 325(C).
    6. Barrington-Leigh, Christopher & Ouliaris, Mark, 2017. "The renewable energy landscape in Canada: A spatial analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 809-819.
    7. Christopher R. DeRolph & Ryan A. McManamay & April M. Morton & Sujithkumar Surendran Nair, 2019. "City energysheds and renewable energy in the United States," Nature Sustainability, Nature, vol. 2(5), pages 412-420, May.
    8. Lin, Boqiang & Huang, Chenchen, 2023. "Promoting variable renewable energy integration: The moderating effect of digitalization," Applied Energy, Elsevier, vol. 337(C).
    9. Jannati, M. & Hosseinian, S.H. & Vahidi, B. & Li, Guo-jie, 2016. "ADALINE (ADAptive Linear NEuron)-based coordinated control for wind power fluctuations smoothing with reduced BESS (battery energy storage system) capacity," Energy, Elsevier, vol. 101(C), pages 1-8.
    10. Hungerford, Zoe & Bruce, Anna & MacGill, Iain, 2019. "The value of flexible load in power systems with high renewable energy penetration," Energy, Elsevier, vol. 188(C).
    11. Lombardi, P. & Schwabe, F., 2017. "Sharing economy as a new business model for energy storage systems," Applied Energy, Elsevier, vol. 188(C), pages 485-496.
    12. Jeon, Soi & Choi, Dae-Hyun, 2022. "Joint optimization of Volt/VAR control and mobile energy storage system scheduling in active power distribution networks under PV prediction uncertainty," Applied Energy, Elsevier, vol. 310(C).
    13. Yan, Rujing & Wang, Jiangjiang & Huo, Shuojie & Qin, Yanbo & Zhang, Jing & Tang, Saiqiu & Wang, Yuwei & Liu, Yan & Zhou, Lin, 2023. "Flexibility improvement and stochastic multi-scenario hybrid optimization for an integrated energy system with high-proportion renewable energy," Energy, Elsevier, vol. 263(PB).
    14. He, Yi & Guo, Su & Zhou, Jianxu & Ye, Jilei & Huang, Jing & Zheng, Kun & Du, Xinru, 2022. "Multi-objective planning-operation co-optimization of renewable energy system with hybrid energy storages," Renewable Energy, Elsevier, vol. 184(C), pages 776-790.
    15. Wenig, Jürgen & Sodenkamp, Mariya & Staake, Thorsten, 2019. "Battery versus infrastructure: Tradeoffs between battery capacity and charging infrastructure for plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 255(C).
    16. Zheng, Menglian & Meinrenken, Christoph J. & Lackner, Klaus S., 2015. "Smart households: Dispatch strategies and economic analysis of distributed energy storage for residential peak shaving," Applied Energy, Elsevier, vol. 147(C), pages 246-257.
    17. Kang, Zixuan & Ye, Zhongnan & Lam, Chor-Man & Hsu, Shu-Chien, 2023. "Sustainable electric vehicle charging coordination: Balancing CO2 emission reduction and peak power demand shaving," Applied Energy, Elsevier, vol. 349(C).
    18. Zhang, Lei & Hu, Xiaosong & Wang, Zhenpo & Ruan, Jiageng & Ma, Chengbin & Song, Ziyou & Dorrell, David G. & Pecht, Michael G., 2021. "Hybrid electrochemical energy storage systems: An overview for smart grid and electrified vehicle applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    19. Frazier, A. Will & Cole, Wesley & Denholm, Paul & Greer, Daniel & Gagnon, Pieter, 2020. "Assessing the potential of battery storage as a peaking capacity resource in the United States," Applied Energy, Elsevier, vol. 275(C).
    20. Luerssen, Christoph & Gandhi, Oktoviano & Reindl, Thomas & Sekhar, Chandra & Cheong, David, 2020. "Life cycle cost analysis (LCCA) of PV-powered cooling systems with thermal energy and battery storage for off-grid applications," Applied Energy, Elsevier, vol. 273(C).
    21. Correa-Florez, Carlos Adrian & Gerossier, Alexis & Michiorri, Andrea & Kariniotakis, Georges, 2018. "Stochastic operation of home energy management systems including battery cycling," Applied Energy, Elsevier, vol. 225(C), pages 1205-1218.
    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, Yunfeng & Zhang, Chao & Mi, Zengqiang & Zhang, Long & Parisio, Alessandra, 2024. "Secondary flexibility market mechanism design and response behavior analysis among multi-microgrids with high proportional BTM-RERs," Applied Energy, Elsevier, vol. 367(C).
    2. Zhewei Huang & Yawen Yi, 2024. "Short-Term Load Forecasting for Regional Smart Energy Systems Based on Two-Stage Feature Extraction and Hybrid Inverted Transformer," Sustainability, MDPI, vol. 16(17), pages 1-25, September.

    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. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2022. "Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    2. Hafiz, Faeza & Rodrigo de Queiroz, Anderson & Fajri, Poria & Husain, Iqbal, 2019. "Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach," Applied Energy, Elsevier, vol. 236(C), pages 42-54.
    3. Li, Yanxue & Zhang, Xiaoyi & Gao, Weijun & Xu, Wenya & Wang, Zixuan, 2022. "Operational performance and grid-support assessment of distributed flexibility practices among residential prosumers under high PV penetration," Energy, Elsevier, vol. 238(PB).
    4. Zhuoxin Lu & Xiaoyuan Xu & Zheng Yan & Dong Han & Shiwei Xia, 2024. "Mobile Energy-Storage Technology in Power Grid: A Review of Models and Applications," Sustainability, MDPI, vol. 16(16), pages 1-19, August.
    5. Xia, Yuanxing & Xu, Qingshan & Chen, Lu & Du, Pengwei, 2022. "The flexible roles of distributed energy storages in peer-to-peer transactive energy market: A state-of-the-art review," Applied Energy, Elsevier, vol. 327(C).
    6. Shang, Ce & Ge, Yuyou & Zhai, Suwei & Huo, Chao & Li, Wenyun, 2023. "Combined heat and power storage planning," Energy, Elsevier, vol. 279(C).
    7. Tang, Hong & Wang, Shengwei, 2023. "Life-cycle economic analysis of thermal energy storage, new and second-life batteries in buildings for providing multiple flexibility services in electricity markets," Energy, Elsevier, vol. 264(C).
    8. Braeuer, Fritz & Rominger, Julian & McKenna, Russell & Fichtner, Wolf, 2019. "Battery storage systems: An economic model-based analysis of parallel revenue streams and general implications for industry," Applied Energy, Elsevier, vol. 239(C), pages 1424-1440.
    9. Smolenski, Robert & Szczesniak, Pawel & Drozdz, Wojciech & Kasperski, Lukasz, 2022. "Advanced metering infrastructure and energy storage for location and mitigation of power quality disturbances in the utility grid with high penetration of renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    10. Zhou, Yuan & Wang, Jiangjiang & Wei, Changqi & Li, Yuxin, 2024. "A novel two-stage multi-objective dispatch model for a distributed hybrid CCHP system considering source-load fluctuations mitigation," Energy, Elsevier, vol. 300(C).
    11. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    12. Lamperti, Francesco & Bosetti, Valentina & Roventini, Andrea & Tavoni, Massimo & Treibich, Tania, 2021. "Three green financial policies to address climate risks," Journal of Financial Stability, Elsevier, vol. 54(C).
    13. Chen, Yuzhu & Guo, Weimin & Zhang, Tianhu & Lund, Peter D. & Wang, Jun & Yang, Kun, 2024. "Carbon and economic prices optimization of a solar-gas coupling energy system with a modified non-dominated sorting genetic algorithm considering operating sequences of water-cooled chillers," Energy, Elsevier, vol. 301(C).
    14. Florian Knobloch & Hector Pollitt & Unnada Chewpreecha & Vassilis Daioglou & Jean-Francois Mercure, 2017. "Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5C," Papers 1710.11019, arXiv.org, revised May 2018.
    15. Nitsch, Felix & Deissenroth-Uhrig, Marc & Schimeczek, Christoph & Bertsch, Valentin, 2021. "Economic evaluation of battery storage systems bidding on day-ahead and automatic frequency restoration reserves markets," Applied Energy, Elsevier, vol. 298(C).
    16. Kun Wang & Bing Chen & Yuhong Li, 2024. "Technological, process or managerial innovation? How does digital transformation affect green innovation in industrial enterprises?," Economic Change and Restructuring, Springer, vol. 57(1), pages 1-32, February.
    17. Sardi, Junainah & Mithulananthan, N. & Hung, Duong Quoc, 2017. "Strategic allocation of community energy storage in a residential system with rooftop PV units," Applied Energy, Elsevier, vol. 206(C), pages 159-171.
    18. Luo, Shihua & Hu, Weihao & Liu, Wen & Liu, Zhou & Huang, Qi & Chen, Zhe, 2022. "Flexibility enhancement measures under the COVID-19 pandemic – A preliminary comparative analysis in Denmark, the Netherlands, and Sichuan of China," Energy, Elsevier, vol. 239(PC).
    19. Yurter, Gulin & Nadar, Emre & Kocaman, Ayse Selin, 2024. "The impact of pumped hydro energy storage configurations on investment planning of hybrid systems with renewables," Renewable Energy, Elsevier, vol. 222(C).
    20. Andrés Henao-Muñoz & Andrés Saavedra-Montes & Carlos Ramos-Paja, 2018. "Optimal Power Dispatch of Small-Scale Standalone Microgrid Located in Colombian Territory," Energies, MDPI, vol. 11(7), pages 1-20, July.

    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:357:y:2024:i:c:s0306261923018196. 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.