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A flexible urban load density-dependent framework for low-carbon distribution expansion planning in the presence of hybrid hydrogen/battery/wind/solar energy systems

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  • Artis, Reza
  • Shivaie, Mojtaba
  • Weinsier, Philip D.

Abstract

Popularization of renewable energy sources (RESs), driven by the goal of carbon footprint mitigation in urban areas, invites unprecedented uncertainties into power distribution networks (PDNs). The uncertainties stemming from intrinsic intermittency of the RESs force network planners to meet flexibility requirements. For handling this challenge, multiple energy storage systems have recently emerged as a pivotal component across the PDNs. In this sense, the authors of this current study present here a new urban-load density-dependent framework for multi-period distribution expansion planning (DEP) considering hybrid hydrogen/battery/wind/solar energy systems for both flexibility enhancement and transition toward low-carbon PDNs. The proposed framework, from a new perspective, aims to divide the PDNs into multiple zones, according to load density of different urban areas under two simultaneous incommensurable objective functions: (i) minimization of investment and operation and maintenance costs; and, (ii) maximization of the supply-demand-related flexibility (SDF) improvement metric minus network-related flexibility (NTF) degradation metric. As the resultant optimization problem formulation has a challenging non-convex mixed-integer nonlinear structure, a fuzzy-based symphony orchestra search algorithm (F-SOSA) was employed to determine the final optimal solution. The effectiveness of the newly developed framework was verified through simulation results on standard 54-node and realistic 95-node distribution test networks. The results illustrate that the integration of hydrogen/battery energy systems brought about an increase of 9.52% and a decrease of 14.96% for the SDF and NTF, respectively, in comparison to their absence. One can further stat that applying these multiple energy systems is associated with a reduction of 20.64% of the total investment cost.

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  • Artis, Reza & Shivaie, Mojtaba & Weinsier, Philip D., 2024. "A flexible urban load density-dependent framework for low-carbon distribution expansion planning in the presence of hybrid hydrogen/battery/wind/solar energy systems," Applied Energy, Elsevier, vol. 364(C).
    • Handle: RePEc:eee:appene:v:364:y:2024:i:c:s0306261924005373
    DOI: 10.1016/j.apenergy.2024.123154
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    References listed on IDEAS

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    1. Zhou, Siyu & Han, Yang & Yang, Ping & Mahmoud, Karar & Lehtonen, Matti & Darwish, Mohamed M.F. & Zalhaf, Amr S., 2022. "An optimal network constraint-based joint expansion planning model for modern distribution networks with multi-types intermittent RERs," Renewable Energy, Elsevier, vol. 194(C), pages 137-151.
    2. Shivaie, Mojtaba & Dienel, Hans-Liudger & Weinsier, Philip D., 2023. "DG-integrated stochastic multiyear distribution expansion planning considering fault current-limiting high-temperature superconducting cables," Applied Energy, Elsevier, vol. 336(C).
    3. Tabandeh, Abbas & Hossain, M.J. & Li, Li, 2022. "Integrated multi-stage and multi-zone distribution network expansion planning with renewable energy sources and hydrogen refuelling stations for fuel cell vehicles," Applied Energy, Elsevier, vol. 319(C).
    4. Zhang, XiaoWei & Yu, Xiaoping & Ye, Xinping & Pirouzi, Sasan, 2023. "Economic energy managementof networked flexi-renewable energy hubs according to uncertainty modeling by the unscented transformation method," Energy, Elsevier, vol. 278(PB).
    5. Tabar, Vahid Sohrabi & Banazadeh, Hamidreza & Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Nasir, Mohammad & Jurado, Francisco, 2022. "Stochastic multi-stage multi-objective expansion of renewable resources and electrical energy storage units in distribution systems considering crypto-currency miners and responsive loads," Renewable Energy, Elsevier, vol. 198(C), pages 1131-1147.
    6. Artis, Reza & Assili, Mohsen & Shivaie, Mojtaba, 2022. "A seismic-resilient multi-level framework for distribution network reinforcement planning considering renewable-based multi-microgrids," Applied Energy, Elsevier, vol. 325(C).
    7. Akbari, Ehsan & Mousavi Shabestari, Seyed Farzin & Pirouzi, Sasan & Jadidoleslam, Morteza, 2023. "Network flexibility regulation by renewable energy hubs using flexibility pricing-based energy management," Renewable Energy, Elsevier, vol. 206(C), pages 295-308.
    8. Sun, Qirun & Wu, Zhi & Gu, Wei & Zhu, Tao & Zhong, Lei & Gao, Ting, 2021. "Flexible expansion planning of distribution system integrating multiple renewable energy sources: An approximate dynamic programming approach," Energy, Elsevier, vol. 226(C).
    9. Fan, Vivienne Hui & Dong, Zhaoyang & Meng, Ke, 2020. "Integrated distribution expansion planning considering stochastic renewable energy resources and electric vehicles," Applied Energy, Elsevier, vol. 278(C).
    10. Gustavo L. Aschidamini & Gederson A. da Cruz & Mariana Resener & Roberto C. Leborgne & Luís A. Pereira, 2022. "A Framework for Reliability Assessment in Expansion Planning of Power Distribution Systems," Energies, MDPI, vol. 15(14), pages 1-24, July.
    11. Norouzi, Mohammadali & Aghaei, Jamshid & Pirouzi, Sasan & Niknam, Taher & Fotuhi-Firuzabad, Mahmud, 2022. "Flexibility pricing of integrated unit of electric spring and EVs parking in microgrids," Energy, Elsevier, vol. 239(PB).
    12. Dong, Yuchen & Zheng, Weibo & Cao, Xiaoyu & Sun, Xunhang & He, Zhengwen, 2023. "Co-planning of hydrogen-based microgrids and fuel-cell bus operation centers under low-carbon and resilience considerations," Applied Energy, Elsevier, vol. 336(C).
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