IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v339y2023ics0306261923003173.html
   My bibliography  Save this article

Risk-averse restoration of coupled power and water systems with small pumped-hydro storage and stochastic rooftop renewables

Author

Listed:
  • Yang, Yesen
  • Li, Zhengmao
  • Mandapaka, Pradeep V.
  • Lo, Edmond Y.M.

Abstract

Modern coupled power and water (CPW) systems exhibit increasing integration and interdependence, which challenges system performance to disasters and makes service restoration complex during post-disruption. Meanwhile, new technologies, such as small pumped-hydro storage (PHS) and rooftop renewables, are being widely installed and further deepen the interdependencies. To capture these features and improve overall performance, this paper proposes a coordinated restoration framework for a CPW system to respond to disruptions. The proposed CPW model comprises physical networks and mechanisms, considering available units, such as water desalination/treatment plants, pump stations and small PHS, in the water system, and rooftop renewables, distributed generators, in power system. The interdependencies are modeled through component-wise connections and consumer behavior, then grouped into three phases: production, distribution, and consumption. Aggregate service loss with respect to different consumer loads and time periods, is chosen as performance metric and to be minimized using network reconfiguration, energy/water dispatching, load curtailment, and operation management of components. A two-stage risk-averse stochastic programming is applied for reliable restoration and manage risks, to tackle the uncertainties in renewable power generations and water/power demands that affect method effectiveness. Finally, the method is implemented on a modified 33-bus/25-node CPW system, and the results demonstrate the effectiveness of the proposed restoration framework.

Suggested Citation

  • Yang, Yesen & Li, Zhengmao & Mandapaka, Pradeep V. & Lo, Edmond Y.M., 2023. "Risk-averse restoration of coupled power and water systems with small pumped-hydro storage and stochastic rooftop renewables," Applied Energy, Elsevier, vol. 339(C).
    • Handle: RePEc:eee:appene:v:339:y:2023:i:c:s0306261923003173
    DOI: 10.1016/j.apenergy.2023.120953
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923003173
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.120953?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. 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. Zhang, Wei & Valencia, Andrea & Gu, Lixing & Zheng, Qipeng P. & Chang, Ni-Bin, 2020. "Integrating emerging and existing renewable energy technologies into a community-scale microgrid in an energy-water nexus for resilience improvement," Applied Energy, Elsevier, vol. 279(C).
    3. Almoghathawi, Yasser & Barker, Kash & Albert, Laura A., 2019. "Resilience-driven restoration model for interdependent infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 12-23.
    4. Goodarzi, Mostafa & Li, Qifeng, 2022. "Evaluate the capacity of electricity-driven water facilities in small communities as virtual energy storage," Applied Energy, Elsevier, vol. 309(C).
    5. Wu, Jiaxin & Wang, Pingfeng, 2021. "Risk-averse optimization for resilience enhancement of complex engineering systems under uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Træholt, Chresten, 2018. "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable Energy, Elsevier, vol. 123(C), pages 204-217.
    7. Fang, Yi-Ping & Sansavini, Giovanni, 2019. "Optimum post-disruption restoration under uncertainty for enhancing critical infrastructure resilience," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 1-11.
    8. Shi, Qingxin & Li, Fangxing & Dong, Jin & Olama, Mohammed & Wang, Xiaofei & Winstead, Chris & Kuruganti, Teja, 2022. "Co-optimization of repairs and dynamic network reconfiguration for improved distribution system resilience," Applied Energy, Elsevier, vol. 318(C).
    9. Sharkey, Thomas C. & Cavdaroglu, Burak & Nguyen, Huy & Holman, Jonathan & Mitchell, John E. & Wallace, William A., 2015. "Interdependent network restoration: On the value of information-sharing," European Journal of Operational Research, Elsevier, vol. 244(1), pages 309-321.
    10. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Optimisation modelling tools and solving techniques for integrated precinct-scale energy–water system planning," Applied Energy, Elsevier, vol. 318(C).
    11. Marqusee, Jeffrey & Ericson, Sean & Jenket, Don, 2021. "Impact of emergency diesel generator reliability on microgrids and building-tied systems," Applied Energy, Elsevier, vol. 285(C).
    12. Li, Zhengmao & Wu, Lei & Xu, Yan & Wang, Luhao & Yang, Nan, 2023. "Distributed tri-layer risk-averse stochastic game approach for energy trading among multi-energy microgrids," Applied Energy, Elsevier, vol. 331(C).
    13. Wang, Jing & Zuo, Wangda & Rhode-Barbarigos, Landolf & Lu, Xing & Wang, Jianhui & Lin, Yanling, 2019. "Literature review on modeling and simulation of energy infrastructures from a resilience perspective," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 360-373.
    14. Gassar, Abdo Abdullah Ahmed & Cha, Seung Hyun, 2021. "Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales," Applied Energy, Elsevier, vol. 291(C).
    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. Chunxia Gao & Zhaoyan Zhang & Peiguang Wang, 2023. "Day-Ahead Scheduling Strategy Optimization of Electric–Thermal Integrated Energy System to Improve the Proportion of New Energy," Energies, MDPI, vol. 16(9), pages 1-30, April.
    2. Carlos Merino & Rui Castro, 2024. "Optimization of a Hybrid Solar–Wind Microgrid for Sustainable Development: A Case Study in Antofagasta, Chile," Sustainability, MDPI, vol. 16(9), pages 1-19, April.
    3. Sharma, Santosh & Li, Qifeng, 2024. "Decentralized optimization of energy-water nexus based on a mixed-integer boundary compatible algorithm," Applied Energy, Elsevier, vol. 359(C).
    4. Zhou, Siyu & Han, Yang & Zalhaf, Amr S. & Lehtonen, Matti & Darwish, Mohamed M.F. & Mahmoud, Karar, 2024. "Risk-averse bi-level planning model for maximizing renewable energy hosting capacity via empowering seasonal hydrogen storage," Applied Energy, Elsevier, vol. 361(C).
    5. Karol Sidor & Piotr Miller & Robert Małkowski & Michał Izdebski, 2024. "Optimization of Division and Reconfiguration Locations of the Medium-Voltage Power Grid Based on Forecasting the Level of Load and Generation from Renewable Energy Sources," Energies, MDPI, vol. 17(19), pages 1-21, October.
    6. Jianzu Hu & Yuefeng Wang & Fan Cheng & Hanqing Shi, 2024. "A Long-Term Power Supply Risk Evaluation Method for China Regional Power System Based on Probabilistic Production Simulation," Energies, MDPI, vol. 17(11), pages 1-23, May.
    7. Huang, Yu & Jin, Mingyue & Xie, Jiale & Peng, Yanjian & Zhong, Junjie, 2024. "Dynamic Bayesian game optimization method for multi-energy hub systems with incomplete load information," Energy, Elsevier, vol. 301(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. Xu, Min & Li, Guoyuan & Chen, Anthony, 2024. "Resilience-driven post-disaster restoration of interdependent infrastructure systems under different decision-making environments," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Sharma, Santosh & Li, Qifeng, 2024. "Decentralized optimization of energy-water nexus based on a mixed-integer boundary compatible algorithm," Applied Energy, Elsevier, vol. 359(C).
    3. Hao, Yucheng & Jia, Limin & Zio, Enrico & Wang, Yanhui & Small, Michael & Li, Man, 2023. "Improving resilience of high-speed train by optimizing repair strategies," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    4. Ahmadi, Somayeh & Saboohi, Yadollah & Vakili, Ali, 2021. "Frameworks, quantitative indicators, characters, and modeling approaches to analysis of energy system resilience: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    5. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    6. Alkhaleel, Basem A. & Liao, Haitao & Sullivan, Kelly M., 2022. "Risk and resilience-based optimal post-disruption restoration for critical infrastructures under uncertainty," European Journal of Operational Research, Elsevier, vol. 296(1), pages 174-202.
    7. Bellè, Andrea & Abdin, Adam F. & Fang, Yi-Ping & Zeng, Zhiguo & Barros, Anne, 2023. "A resilience-based framework for the optimal coupling of interdependent critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    8. Umunnakwe, A. & Huang, H. & Oikonomou, K. & Davis, K.R., 2021. "Quantitative analysis of power systems resilience: Standardization, categorizations, and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    9. Kong, Jingjing & Zhang, Chao & Simonovic, Slobodan P., 2021. "Optimizing the resilience of interdependent infrastructures to regional natural hazards with combined improvement measures," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    10. Almoghathawi, Yasser & Selim, Shokri & Barker, Kash, 2023. "Community structure recovery optimization for partial disruption, functionality, and restoration in interdependent networks," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    11. Sun, Qin & Li, Hongxu & Wang, Yuzhi & Zhang, Yingchao, 2022. "Multi-swarm-based cooperative reconfiguration model for resilient unmanned weapon system-of-systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    12. Xu, Min & Ouyang, Min & Hong, Liu & Mao, Zijun & Xu, Xiaolin, 2022. "Resilience-driven repair sequencing decision under uncertainty for critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    13. Alkhaleel, Basem A., 2024. "Machine learning applications in the resilience of interdependent critical infrastructure systems—A systematic literature review," International Journal of Critical Infrastructure Protection, Elsevier, vol. 44(C).
    14. Talebiyan, Hesam & Dueñas-Osorio, Leonardo, 2023. "Auctions for resource allocation and decentralized restoration of interdependent networks," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    15. Su, Rui & Chen, Bin & Wang, Saige & Duan, Cuncun, 2024. "Energy technical resilience assessment based on complex network analysis – A case study of China," Applied Energy, Elsevier, vol. 364(C).
    16. Jalilpoor, Kamran & Oshnoei, Arman & Mohammadi-Ivatloo, Behnam & Anvari-Moghaddam, Amjad, 2022. "Network hardening and optimal placement of microgrids to improve transmission system resilience: A two-stage linear program," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    17. Liu, Xing & Fang, Yi-Ping & Zio, Enrico, 2021. "A Hierarchical Resilience Enhancement Framework for Interdependent Critical Infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    18. Shang, Ce & Lin, Teng & Li, Canbing & Wang, Keyou & Ai, Qian, 2021. "Joining resilience and reliability evaluation against both weather and ageing causes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    19. Linas Martišauskas & Juozas Augutis & Ričardas Krikštolaitis & Rolandas Urbonas & Inga Šarūnienė & Vytis Kopustinskas, 2022. "A Framework to Assess the Resilience of Energy Systems Based on Quantitative Indicators," Energies, MDPI, vol. 15(11), pages 1-25, May.
    20. Xinhua Mao & Xin Lou & Changwei Yuan & Jibiao Zhou, 2020. "Resilience-Based Restoration Model for Supply Chain Networks," Mathematics, MDPI, vol. 8(2), pages 1-16, January.

    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:339:y:2023:i:c:s0306261923003173. 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.