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Decentralized optimal multi-energy flow of large-scale integrated energy systems in a carbon trading market


  • Qu, Kaiping
  • Yu, Tao
  • Huang, Linni
  • Yang, Bo
  • Zhang, Xiaoshun


This paper proposes a novel decentralized optimal multi-energy flow (OMEF) of large-scale integrated energy systems (IES) in a carbon trading market, to fully exploit economic and environmental advantages of the system considering difficulties of information collection from subareas. The decentralized OMEF is solved by three decentralized optimization algorithms, including auxiliary problem principle (APP), block coordinates down (BCD), and approximate Newton directions (AND). Moreover, a dynamic parameter adjustment is developed for APP and BCD to ensure convergence. So that a cooperative optimization among subareas can be achieved through utilizing only the local information and the boundary information. Finally, case studies of a two-area IES with 8 energy hubs and a three-area IES with 33 energy hubs are carried out to deeply compare the performance of the three decentralized algorithms, together with a thorough analysis about the effect of carbon trading price on the system.

Suggested Citation

  • Qu, Kaiping & Yu, Tao & Huang, Linni & Yang, Bo & Zhang, Xiaoshun, 2018. "Decentralized optimal multi-energy flow of large-scale integrated energy systems in a carbon trading market," Energy, Elsevier, vol. 149(C), pages 779-791.
  • Handle: RePEc:eee:energy:v:149:y:2018:i:c:p:779-791
    DOI: 10.1016/

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    References listed on IDEAS

    1. Francisco Nogales & Francisco Prieto & Antonio Conejo, 2003. "A Decomposition Methodology Applied to the Multi-Area Optimal Power Flow Problem," Annals of Operations Research, Springer, vol. 120(1), pages 99-116, April.
    2. Jan Abrell & Hannes Weigt, 2012. "Combining Energy Networks," Networks and Spatial Economics, Springer, vol. 12(3), pages 377-401, September.
    3. Zhu, Y. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Nie, S., 2015. "A dynamic model to optimize municipal electric power systems by considering carbon emission trading under uncertainty," Energy, Elsevier, vol. 88(C), pages 636-649.
    4. Xia, Yan & Tang, Zhipeng, 2017. "The impacts of emissions accounting methods on an imperfect competitive carbon trading market," Energy, Elsevier, vol. 119(C), pages 67-76.
    5. Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Liao, Siyang & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao, 2018. "Coordinated operation of gas-electricity integrated distribution system with multi-CCHP and distributed renewable energy sources," Applied Energy, Elsevier, vol. 211(C), pages 237-248.
    6. Gu, Wei & Wang, Jun & Lu, Shuai & Luo, Zhao & Wu, Chenyu, 2017. "Optimal operation for integrated energy system considering thermal inertia of district heating network and buildings," Applied Energy, Elsevier, vol. 199(C), pages 234-246.
    7. Wei, F. & Wu, Q.H. & Jing, Z.X. & Chen, J.J. & Zhou, X.X., 2016. "Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach," Energy, Elsevier, vol. 111(C), pages 933-946.
    8. Zhang, Xiaoshun & Yu, Tao & Yang, Bo & Li, Li, 2016. "Virtual generation tribe based robust collaborative consensus algorithm for dynamic generation command dispatch optimization of smart grid," Energy, Elsevier, vol. 101(C), pages 34-51.
    9. C. Beltran & F. J. Heredia, 2002. "Unit Commitment by Augmented Lagrangian Relaxation: Testing Two Decomposition Approaches," Journal of Optimization Theory and Applications, Springer, vol. 112(2), pages 295-314, February.
    10. Zhou, Kaile & Yang, Shanlin & Shao, Zhen, 2016. "Energy Internet: The business perspective," Applied Energy, Elsevier, vol. 178(C), pages 212-222.
    11. Hannes Weigt & Jan Abrell, 2012. "Storage and Investments in a Combined Energy Network Model," EcoMod2012 4319, EcoMod.
    12. Taliotis, Constantinos & Taibi, Emanuele & Howells, Mark & Rogner, Holger & Bazilian, Morgan & Welsch, Manuel, 2017. "Renewable energy technology integration for the island of Cyprus: A cost-optimization approach," Energy, Elsevier, vol. 137(C), pages 31-41.
    13. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Li, Xiaojing, 2017. "Security-constrained bi-level economic dispatch model for integrated natural gas and electricity systems considering wind power and power-to-gas process," Applied Energy, Elsevier, vol. 194(C), pages 696-704.
    14. Suleman, F. & Dincer, I. & Agelin-Chaab, M., 2014. "Development of an integrated renewable energy system for multigeneration," Energy, Elsevier, vol. 78(C), pages 196-204.
    15. Fu, Xueqian & Guo, Qinglai & Sun, Hongbin & Zhang, Xiurong & Wang, Li, 2017. "Estimation of the failure probability of an integrated energy system based on the first order reliability method," Energy, Elsevier, vol. 134(C), pages 1068-1078.
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    Cited by:

    1. Wang, Yongli & Wang, Yudong & Huang, Yujing & Yang, Jiale & Ma, Yuze & Yu, Haiyang & Zeng, Ming & Zhang, Fuwei & Zhang, Yanfu, 2019. "Operation optimization of regional integrated energy system based on the modeling of electricity-thermal-natural gas network," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    2. Li, Zhuoran & Ma, Linwei & Li, Zheng & Ni, Weidou, 2019. "Multi-energy cooperative utilization business models: A case study of the solar-heat pump water heater," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 392-397.
    3. Tang, Difei & Yang, Xiangguo & Yong, Jing & Xu, Wilsun, 2019. "Active method for mitigation of induced voltage in integrated energy systems," Applied Energy, Elsevier, vol. 235(C), pages 553-563.
    4. Qu, Kaiping & Shi, Shouyuan & Yu, Tao & Wang, Wenrui, 2019. "A convex decentralized optimization for environmental-economic power and gas system considering diversified emission control," Applied Energy, Elsevier, vol. 240(C), pages 630-645.
    5. Fu, Xueqian & Li, Gengyin & Wang, Huaizhi, 2018. "Use of a second-order reliability method to estimate the failure probability of an integrated energy system," Energy, Elsevier, vol. 161(C), pages 425-434.
    6. Liu, Zhiyuan & Yu, Hang & Liu, Rui, 2019. "A novel energy supply and demand matching model in park integrated energy system," Energy, Elsevier, vol. 176(C), pages 1007-1019.
    7. Fu, Xueqian & Li, Gengyin & Zhang, Xiurong & Qiao, Zheng, 2018. "Failure probability estimation of the gas supply using a data-driven model in an integrated energy system," Applied Energy, Elsevier, vol. 232(C), pages 704-714.
    8. Yin, Linfei & Wang, Tao & Wang, Senlin & Zheng, Baomin, 2019. "Interchange objective value method for distributed multi-objective optimization: Theory, application, implementation," Applied Energy, Elsevier, vol. 239(C), pages 1066-1076.
    9. Qin, Chao & Yan, Qingyou & He, Gang, 2019. "Integrated energy systems planning with electricity, heat and gas using particle swarm optimization," Energy, Elsevier, vol. 188(C).
    10. Qu, Kaiping & Yu, Tao & Zhang, Xiaoshun & Li, Haofei, 2019. "Homogenized adjacent points method: A novel Pareto optimizer for linearized multi-objective optimal energy flow of integrated electricity and gas system," Applied Energy, Elsevier, vol. 233, pages 338-351.
    11. Chen, Yue & Wei, Wei & Liu, Feng & Shafie-khah, Miadreza & Mei, Shengwei & Catalão, João P.S., 2018. "Optimal contracts of energy mix in a retail market under asymmetric information," Energy, Elsevier, vol. 165(PB), pages 634-650.
    12. Qu, Kaiping & Zheng, Baomin & Yu, Tao & Li, Haofei, 2019. "Convex decoupled-synergetic strategies for robust multi-objective power and gas flow considering power to gas," Energy, Elsevier, vol. 168(C), pages 753-771.
    13. Wang, Huaizhi & Meng, Anjian & Liu, Yitao & Fu, Xueqian & Cao, Guangzhong, 2019. "Unscented Kalman Filter based interval state estimation of cyber physical energy system for detection of dynamic attack," Energy, Elsevier, vol. 188(C).
    14. Xiaofeng Dong & Chao Quan & Tong Jiang, 2018. "Optimal Planning of Integrated Energy Systems Based on Coupled CCHP," Energies, MDPI, Open Access Journal, vol. 11(10), pages 1-27, October.


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