IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v386y2025ics0306261925002612.html
   My bibliography  Save this article

Risk-based optimal network planning considering resources remuneration and daily uncertainty

Author

Listed:
  • Castro, Fábio
  • Canizes, Bruno
  • Soares, João
  • Almeida, José
  • Francois, Bruno
  • Vale, Zita

Abstract

The integration of renewable energy into power networks introduces challenges due to intermittency and unpredictability, making precise expansion planning essential. This research introduces a novel two-stage stochastic approach for distribution network expansion planning in smart grids with high renewable energy penetration, addressing uncertainty, risk, and distributed generators' remuneration. Key contributions include: the incorporation of third-party generation owners' economic remuneration into a risk-based stochastic model; the use of conditional value-at-risk to manage uncertainty and extreme events, with a detailed analysis of cost evolution for various confidence levels and risk aversion parameters; the optimization of energy storage systems sizing and placement, alongside the location and type of new power lines and substation transformers, ensuring a reliable and radial network topology; and the integration of multiple factors, including uncertainty, risk aversion, ESS allocation, remuneration, and reliability, into a unified model that ensures optimal network design under technical constraints. Tested on a 180-bus network in Leiria, Portugal and on a 13-bus smart city mockup from Salamanca, Spain, the approach proved economically viable, reducing extreme scenario costs by up to 34 % through CVaR-based risk management, and demonstrating its potential for sustainable, risk-averse network expansion.

Suggested Citation

  • Castro, Fábio & Canizes, Bruno & Soares, João & Almeida, José & Francois, Bruno & Vale, Zita, 2025. "Risk-based optimal network planning considering resources remuneration and daily uncertainty," Applied Energy, Elsevier, vol. 386(C).
    • Handle: RePEc:eee:appene:v:386:y:2025:i:c:s0306261925002612
    DOI: 10.1016/j.apenergy.2025.125531
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925002612
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.125531?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. Canizes, Bruno & Soares, João & Lezama, Fernando & Silva, Cátia & Vale, Zita & Corchado, Juan M., 2019. "Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation," Renewable Energy, Elsevier, vol. 138(C), pages 937-954.
    2. Shahryar Behnia & Saeed Kharrati & Farshad Khosravi & Abdollah Rastgou, 2024. "Simultaneous costs minimizing in electricity and gas micro-grids with the presence of distributed generation," PLOS ONE, Public Library of Science, vol. 19(9), pages 1-25, September.
    3. Munoz, Francisco D. & van der Weijde, Adriaan Hendrik & Hobbs, Benjamin F. & Watson, Jean-Paul, 2017. "Does risk aversion affect transmission and generation planning? A Western North America case study," Energy Economics, Elsevier, vol. 64(C), pages 213-225.
    4. Bruno Canizes & João Soares & Zita Vale & Juan M. Corchado, 2019. "Optimal Distribution Grid Operation Using DLMP-Based Pricing for Electric Vehicle Charging Infrastructure in a Smart City," Energies, MDPI, vol. 12(4), pages 1-40, February.
    5. Ahmadisourenabadi, Bahador & Marzband, Mousa & Hosseini-Hemati, Saman & Sadati, S. Muhammad Bagher & Rastgou, Abdollah, 2024. "Quantifying and enabling the resiliency of a microgrid considering electric vehicles using a Bayesian network risk assessment," Energy, Elsevier, vol. 308(C).
    6. Mu, Yunfei & Wang, Congshan & Cao, Yan & Jia, Hongjie & Zhang, Qingzhu & Yu, Xiaodan, 2022. "A CVaR-based risk assessment method for park-level integrated energy system considering the uncertainties and correlation of energy prices," Energy, Elsevier, vol. 247(C).
    7. Esmaeeli, Mostafa & Kazemi, Ahad & Shayanfar, Heidarali & Chicco, Gianfranco & Siano, Pierluigi, 2017. "Risk-based planning of the distribution network structure considering uncertainties in demand and cost of energy," Energy, Elsevier, vol. 119(C), pages 578-587.
    8. Shao, Zhentong & Cao, Xiaoyu & Zhai, Qiaozhu & Guan, Xiaohong, 2023. "Risk-constrained planning of rural-area hydrogen-based microgrid considering multiscale and multi-energy storage systems," Applied Energy, Elsevier, vol. 334(C).
    9. Masato Wada & Felipe Delgado & Bernardo K. Pagnoncelli, 2017. "A risk averse approach to the capacity allocation problem in the airline cargo industry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 643-651, June.
    10. Xuan, Ang & Shen, Xinwei & Guo, Qinglai & Sun, Hongbin, 2021. "A conditional value-at-risk based planning model for integrated energy system with energy storage and renewables," Applied Energy, Elsevier, vol. 294(C).
    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. Liu, Zeyu & Li, Hang & Hou, Kai & Xu, Xiandong & Jia, Hongjie & Zhu, Lewei & Mu, Yunfei, 2023. "Risk assessment and alleviation of regional integrated energy system considering cross-system failures," Applied Energy, Elsevier, vol. 350(C).
    2. Wang, Jiangjiang & Deng, Hongda & Qi, Xiaoling, 2022. "Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks," Energy, Elsevier, vol. 261(PA).
    3. Simshauser, Paul, 2024. "On static vs. dynamic line ratings in renewable energy zones," Energy Economics, Elsevier, vol. 129(C).
    4. Zhang, Xiao-Yan & Wang, Cenfeng & Xiao, Jiang-Wen & Wang, Yan-Wu, 2025. "A transactive energy cooperation scheduling for hydrogen-based community microgrid with refueling preferences of hydrogen vehicles," Applied Energy, Elsevier, vol. 377(PC).
    5. Chen, Lei & Jiang, Yuqi & Zheng, Shencong & Deng, Xinyi & Chen, Hongkun & Islam, Md. Rabiul, 2023. "A two-layer optimal configuration approach of energy storage systems for resilience enhancement of active distribution networks," Applied Energy, Elsevier, vol. 350(C).
    6. Botor, Benjamin & Böcker, Benjamin & Kallabis, Thomas & Weber, Christoph, 2021. "Information shocks and profitability risks for power plant investments – impacts of policy instruments," Energy Economics, Elsevier, vol. 102(C).
    7. Paul Simshauser & Farhad Billimoria & Craig Rogers, 2021. "Optimising VRE plant capacity in Renewable Energy Zones," Working Papers EPRG2121, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    8. Inzunza, Andrés & Muñoz, Francisco D. & Moreno, Rodrigo, 2021. "Measuring the effects of environmental policies on electricity markets risk," Energy Economics, Elsevier, vol. 102(C).
    9. Munoz, Francisco D. & Pumarino, Bruno J. & Salas, Ignacio A., 2017. "Aiming low and achieving it: A long-term analysis of a renewable policy in Chile," Energy Economics, Elsevier, vol. 65(C), pages 304-314.
    10. Zhao, Zhenyu & Xu, Hanting & Bao, Geriletu, 2025. "Study on energy resource-project mode-load demand chain flexibility adaptation of park-level integrated energy systems," Energy, Elsevier, vol. 320(C).
    11. Keyong Hu & Qingqing Yang & Lei Lu & Yu Zhang & Shuifa Sun & Ben Wang, 2025. "Two-Stage Distributionally Robust Optimal Scheduling for Integrated Energy Systems Considering Uncertainties in Renewable Generation and Loads," Mathematics, MDPI, vol. 13(9), pages 1-30, April.
    12. Ruengwit Khwanrit & Saher Javaid & Yuto Lim & Chalie Charoenlarpnopparut & Yasuo Tan, 2025. "Hierarchical Multi-Communities Energy Sharing Management with Electric Vehicle Integration," Energies, MDPI, vol. 18(2), pages 1-26, January.
    13. Elkholy, M.H. & Metwally, Hamid & Farahat, M.A. & Senjyu, Tomonobu & Elsayed Lotfy, Mohammed, 2022. "Smart centralized energy management system for autonomous microgrid using FPGA," Applied Energy, Elsevier, vol. 317(C).
    14. Simshauser, Paul, 2021. "Renewable Energy Zones in Australia's National Electricity Market," Energy Economics, Elsevier, vol. 101(C).
    15. Felix Schmidt, 2025. "On long-duration storage, weather uncertainty and limited foresight," Papers 2505.12538, arXiv.org, revised Jun 2025.
    16. Wang, Liying & Lin, Jialin & Dong, Houqi & Wang, Yuqing & Zeng, Ming, 2023. "Demand response comprehensive incentive mechanism-based multi-time scale optimization scheduling for park integrated energy system," Energy, Elsevier, vol. 270(C).
    17. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "A review of co-optimization approaches for operational and planning problems in the energy sector," Applied Energy, Elsevier, vol. 304(C).
    18. Suryakiran, B.V. & Nizami, Sohrab & Verma, Ashu & Saha, Tapan Kumar & Mishra, Sukumar, 2023. "A DSO-based day-ahead market mechanism for optimal operational planning of active distribution network," Energy, Elsevier, vol. 282(C).
    19. Zhang, Y.Q. & Chen, J.J. & Wang, Y.X. & Feng, L., 2024. "Enhancing resilience of agricultural microgrid through electricity–heat–water based multi-energy hub considering irradiation intensity uncertainty," Renewable Energy, Elsevier, vol. 220(C).
    20. Jiao, P.H. & Chen, J.J. & Cai, X. & Zhao, Y.L., 2024. "Fuzzy semi-entropy based downside risk to low-carbon oriented multi-energy dispatch considering multiple dependent uncertainties," Energy, Elsevier, vol. 287(C).

    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:386:y:2025:i:c:s0306261925002612. 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.