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Consensus-based decentralized scheduling method for collaborative operation in seaport virtual power plant

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  • Xiong, Chang
  • Su, Yixin
  • Wang, Hao
  • Dong, Zhengcheng
  • Tian, Meng
  • Shi, Binghua

Abstract

The accelerating trend towards electrification in seaport operations presents the opportunities for ports to achieve near zero and decarbonization strategies. However, integrating a large number of flexible resources into seaport energy systems introduces complex management challenges, including the need for coordinated charging of electrified vessels and the optimized energy utilization of seaport equipment. To address these challenges, we establish a seaport virtual power plant (SVPP) system model and an energy service model that leverages the concepts of vessel-to-shore (V2S) and vessel-to-vessel (V2V) for facilitating diverse energy transfer modes among the grid, shore, and vessels. To unlock the flexible value of electrified vessels, we propose an energy sharing scheduling method that integrates a hybrid V2S and V2V mode. This method considers the diversity in vessel berthing durations and charging demands, utilizing V2V interaction mechanisms among electrified vessels to determine the optimal shore-vessel scheduling schemes. To ensure the privacy and reliability of multi-entity operations, we design a decentralized energy management algorithm for the SVPP based on the consensus alternating direction method of multipliers (ADMM). A decentralized optimization framework is designed based on the consensus mechanism. By introducing coupling information as consensus variables, we fully decouple the operations of multiple owners and solve the primal optimization problem in parallel. Additionally, by formulating two baseline optimization problems, we evaluate the effects of V2S and V2V on the overall SVPP and on the individual vessels. Simulation results demonstrate that introducing V2S can reduce the total cost by 13.68%, while the further integration of V2V can achieve a cost reduction of 26.56%. Notably, V2V interactions enhance the scheduling potential, particularly for vessels with longer berthing durations.

Suggested Citation

  • Xiong, Chang & Su, Yixin & Wang, Hao & Dong, Zhengcheng & Tian, Meng & Shi, Binghua, 2024. "Consensus-based decentralized scheduling method for collaborative operation in seaport virtual power plant," Applied Energy, Elsevier, vol. 373(C).
    • Handle: RePEc:eee:appene:v:373:y:2024:i:c:s030626192401331x
    DOI: 10.1016/j.apenergy.2024.123948
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    as
    1. Yang, Qing & Wang, Hao & Wang, Taotao & Zhang, Shengli & Wu, Xiaoxiao & Wang, Hui, 2021. "Blockchain-based decentralized energy management platform for residential distributed energy resources in a virtual power plant," Applied Energy, Elsevier, vol. 294(C).
    2. Wang, Lifen & Liang, Chengji & Shi, Jian & Molavi, Anahita & Lim, Gino & Zhang, Yue, 2021. "A bilevel hybrid economic approach for optimal deployment of onshore power supply in maritime ports," Applied Energy, Elsevier, vol. 292(C).
    3. Bhuiyan, Erphan A. & Hossain, Md. Zahid & Muyeen, S.M. & Fahim, Shahriar Rahman & Sarker, Subrata K. & Das, Sajal K., 2021. "Towards next generation virtual power plant: Technology review and frameworks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    4. Ehsan, Ali & Yang, Qiang, 2019. "State-of-the-art techniques for modelling of uncertainties in active distribution network planning: A review," Applied Energy, Elsevier, vol. 239(C), pages 1509-1523.
    5. Tushar, Wayes & Yuen, Chau & Saha, Tapan K. & Morstyn, Thomas & Chapman, Archie C. & Alam, M. Jan E. & Hanif, Sarmad & Poor, H. Vincent, 2021. "Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges," Applied Energy, Elsevier, vol. 282(PA).
    6. Bjerkan, Kristin Ystmark & Seter, Hanne, 2021. "Policy and politics in energy transitions. A case study on shore power in Oslo," Energy Policy, Elsevier, vol. 153(C).
    7. Hany Elgamal, Ahmed & Kocher-Oberlehner, Gudrun & Robu, Valentin & Andoni, Merlinda, 2019. "Optimization of a multiple-scale renewable energy-based virtual power plant in the UK," Applied Energy, Elsevier, vol. 256(C).
    8. Zhang, Yue & Liang, Chengji & Shi, Jian & Lim, Gino & Wu, Yiwei, 2022. "Optimal Port Microgrid Scheduling Incorporating Onshore Power Supply and Berth Allocation Under Uncertainty," Applied Energy, Elsevier, vol. 313(C).
    9. Abbasi, Mohammad Hossein & Taki, Mehrdad & Rajabi, Amin & Li, Li & Zhang, Jiangfeng, 2019. "Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach," Applied Energy, Elsevier, vol. 239(C), pages 1294-1307.
    10. Carli, Raffaele & Dotoli, Mariagrazia & Jantzen, Jan & Kristensen, Michael & Ben Othman, Sarah, 2020. "Energy scheduling of a smart microgrid with shared photovoltaic panels and storage: The case of the Ballen marina in Samsø," Energy, Elsevier, vol. 198(C).
    11. Wang, Han & Riaz, Shariq & Mancarella, Pierluigi, 2020. "Integrated techno-economic modeling, flexibility analysis, and business case assessment of an urban virtual power plant with multi-market co-optimization," Applied Energy, Elsevier, vol. 259(C).
    12. Kong, Xiangyu & Xiao, Jie & Wang, Chengshan & Cui, Kai & Jin, Qiang & Kong, Deqian, 2019. "Bi-level multi-time scale scheduling method based on bidding for multi-operator virtual power plant," Applied Energy, Elsevier, vol. 249(C), pages 178-189.
    13. Fan, Shuai & Liu, Jiang & Wu, Qing & Cui, Mingjian & Zhou, Huan & He, Guangyu, 2020. "Optimal coordination of virtual power plant with photovoltaics and electric vehicles: A temporally coupled distributed online algorithm," Applied Energy, Elsevier, vol. 277(C).
    14. Iris, Çağatay & Lam, Jasmine Siu Lee, 2019. "A review of energy efficiency in ports: Operational strategies, technologies and energy management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 170-182.
    15. Dong, Lianxin & Fan, Shuai & Wang, Zhihua & Xiao, Jucheng & Zhou, Huan & Li, Zuyi & He, Guangyu, 2021. "An adaptive decentralized economic dispatch method for virtual power plant," Applied Energy, Elsevier, vol. 300(C).
    16. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    17. Tang, Ruoli & Zhang, Shihan & Zhang, Shangyu & Lai, Jingang & Zhang, Yan, 2023. "Semi-online parameter identification methodology for maritime power lithium batteries," Applied Energy, Elsevier, vol. 339(C).
    Full references (including those not matched with items on IDEAS)

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