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Joint planning of electrical storage and gas storage in power-gas distribution network considering high-penetration electric vehicle and gas vehicle

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  • Gu, Chenjia
  • Zhang, Yao
  • Wang, Jianxue
  • Li, Qingtao

Abstract

Increasing penetration of electric vehicles (EVs) and gas vehicles (GVs) will endanger safe and stable operation of power-gas distribution network. Energy storage systems are considered effective tools to deal with the surge of charging demands brought by EV/GV and enhance energy supply reliability. Meanwhile, the coupling between power and gas distribution systems has been strengthened in recent years via gas turbines. This makes it possible and imperative to jointly optimize the configuration of electrical and gas storage systems and avoid the overinvestment commonly occurring in separate planning. To this end, this paper proposes a joint electrical and gas energy storage planning approach considering the interdependency between power-gas distribution network and transportation network. First, the semi-dynamic traffic assignment method is utilized to obtain EV/GV traffic flow and its transition between two adjacent periods. EV/GV traffic flow is directly related to EV/GV charging demands and can be further converted into their spatial–temporal distribution. Second, a novel second-order cone formulation is proposed to accurately describe the nonlinear operating characteristic of gas storage system. This can help to incorporate the constraints associated with the effective operation of gas storage systems into the planning model, while ensuring the computational tractability. Finally, the proposed planning problem is formulated as a mixed-integer second-order conic programming problem. A penalty convex-concave procedure algorithm is developed to ensure the exactness of all second-order cone relaxations in our proposed model. Numerical results indicate that joint planning strategy can fulfill the peak charging load while yielding to low investment cost.

Suggested Citation

  • Gu, Chenjia & Zhang, Yao & Wang, Jianxue & Li, Qingtao, 2021. "Joint planning of electrical storage and gas storage in power-gas distribution network considering high-penetration electric vehicle and gas vehicle," Applied Energy, Elsevier, vol. 301(C).
    • Handle: RePEc:eee:appene:v:301:y:2021:i:c:s0306261921008370
    DOI: 10.1016/j.apenergy.2021.117447
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    References listed on IDEAS

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    5. Carlos Henrique Valério de Moraes & Jonas Lopes de Vilas Boas & Germano Lambert-Torres & Gilberto Capistrano Cunha de Andrade & Claudio Inácio de Almeida Costa, 2022. "Intelligent Power Distribution Restoration Based on a Multi-Objective Bacterial Foraging Optimization Algorithm," Energies, MDPI, vol. 15(4), pages 1-23, February.
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    7. Gu, Chenjia & Wang, Jianxue & Zhang, Yao & Li, Qingtao & Chen, Yang, 2022. "Optimal energy storage planning for stacked benefits in power distribution network," Renewable Energy, Elsevier, vol. 195(C), pages 366-380.
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    9. Pokpong Prakobkaew & Somporn Sirisumrannukul, 2022. "Practical Grid-Based Spatial Estimation of Number of Electric Vehicles and Public Chargers for Country-Level Planning with Utilization of GIS Data," Energies, MDPI, vol. 15(11), pages 1-19, May.
    10. Zhou, Siyu & Han, Yang & Mahmoud, Karar & Darwish, Mohamed M.F. & Lehtonen, Matti & Yang, Ping & Zalhaf, Amr S., 2023. "A novel unified planning model for distributed generation and electric vehicle charging station considering multi-uncertainties and battery degradation," Applied Energy, Elsevier, vol. 348(C).
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