AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (4.9 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Regular Paper | Open Access

Day-ahead P2P Energy Sharing Strategy Among Energy Hubs Considering Flexibility of Energy Storage and Loads

Penghua Li1( )Wanxing Sheng1Qing Duan1Jun Liang2Cunhao Zhu1
China Electric Power Research Institute, Beijing 100192, China
School of Engineering, Cardiff University, UK
Show Author Information

Abstract

Multi-energy systems are one of the key technologies to tackle energy crisis and environmental pollution. An energy hub (EH) is a minimum multi-energy system. Interconnection of multiple EHs through energy routers (ERs) can realize mutual energy assistance. This paper proposes a peer-to-peer (P2P) energy sharing strategy between EHs including ERs in an interconnected system, which is divided into two levels. In the lower level, a method of determining the charging/discharging constraints of energy storage devices is proposed. Based on the Lyapunov optimization method, virtual queues are used to model the energy storage devices and flexible loads in the system. The objective is to minimize the overall operating cost of the interconnected system. In the upper level, a non-cooperative game model is introduced to minimize the cost of purchasing power from other EHs for each EH. A best response-based method is adapted to find the Nash equilibrium. The simulation outcomes demonstrate that application of the proposed strategy can reduce operating costs of an interconnected system and each EH. On basis of a real-world dataset of interconnected EHs, both analytical and numerical results show the effectiveness of the proposed strategy.

References

[1]

T. H. Liu, D. D. Zhang, H. Dai, and T. Wu, “Intelligent modeling and optimization for smart energy hub,” IEEE Transactions on Industrial Electronics, vol. 66, no. 12, pp. 9898–9908, Dec. 2019.

[2]
M. Geidl, “Integrated modeling and optimization of multi-carrier energy systems,” Ph.D. dissertation, Swiss Federal Institute of Technology in Zurich, Switzerland, 2007.
[3]

V. Davatgaran, M. Saniei, and S. S. Mortazavi, “Optimal bidding strategy for an energy hub in energy market,” Energy, vol. 148, pp. 482–493, Apr. 2018.

[4]

M. Qadrdan, J. Z. Wu, N. Jenkins, and J. Ekanayake, “Operating strategies for a gb integrated gas and electricity network considering the uncertainty in wind power forecasts,” IEEE Transactions on Sustainable Energy, vol. 5, no. 1, pp. 128–138, Jan. 2014.

[5]

H. Guo, F. Wang, L. J. Zhang, and J. Luo, “A hierarchical optimization strategy of the energy router-based energy internet,” IEEE Transactions on Power Systems, vol. 34, no. 6, pp. 4177–4185, Nov. 2019.

[6]

A. Q. Huang, M. L. Crow, G. T. Heydt, J. P. Zheng, and S. J. Dale, “The future renewable electric energy delivery and management (freedm) system: The energy internet,” Proceedings of the IEEE, vol. 99, no. 1, pp. 133–148, Jan. 2011.

[7]

I. Syed, V. Khadkikar, and H. H. Zeineldin, “Loss reduction in radial distribution networks using a solid-state transformer,” IEEE Transactions on Industry Applications, vol. 54, no. 5, pp. 5474–5482, Sep./Oct. 2018.

[8]

W. Ni, L. Lv, Y. Xiang, J. Y. Liu, Y. F. Yang, and W. T. Zhang, “Optimal gas-electricity purchase model for energy hub system based on chance- constrained programming,” Power System Technology, vol. 42, no. 8, pp. 2477–2487, Aug. 2018.

[9]

V. Davatgaran, M. Saniei, and S. S. Mortazavi, “Smart distribution system management considering electrical and thermal demand response of energy hubs,” Energy, vol. 169, pp. 38–49, Feb. 2019.

[10]

J. Q. Shi, H. Hu, and J. H. Zhang, “Distributed low-carbon economy scheduling for integrated energy system with multiple individual energy-hubs,” Power System Technology, vol. 43, no. 1, pp. 126–134, Jan. 2019.

[11]

A. Bostan, M. S. Nazar, M. Shafie-Khah, and J. P. S. Catalão, “Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs,” Energy, vol. 190, pp. 116349, Jan. 2020.

[12]

S. Dong, C. F. Wang, J. Liang, X. M. Dong, Z. T. Liang, and H. D. Li, “Multi- objective optimal day-ahead dispatch of integrated energy system con- sidering power-to-gas operation cost,” Automation of Electric Power Systems, vol. 42, no. 11, pp. 8–15, 121, Jun. 2018.

[13]

T. Morstyn, N. Farrell, S. J. Darby, and M. D. McCulloch, “Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants,” Nature Energy, vol. 3, no. 2, pp. 94–101, Feb. 2018.

[14]
Y. L. Zhou, S. Ci, H. J. Li, and Y. Yang, “A new framework for peer-to-peer energy sharing and coordination in the energy internet,” in 2017 IEEE International Conference on Communications (ICC), 2017, pp. 1–6.
[15]

J. Guerrero, D. Gebbran, S. Mhanna, A. C. Chapman, and G. Verbič, “Towards a transactive energy system for integration of distributed energy resources: Home energy management, distributed optimal power flow, and peer-to-peer energy trading,” Renewable and Sustainable Energy Reviews, vol. 132, pp. 110000, Oct. 2020.

[16]
K. Patel, S. Sharma, and A. Verma, “Distributed framework for p2p energy sharing among building prosumers using stackelberg game,” in 2020 IEEE Power & Energy Society General Meeting (PESGM), 2020, pp. 1–5.
[17]

L. D. Chen, N. Liu, L. Y. Liu, X. H. Xue, and Y. S. Xue, “Data-driven stochastic game with social attributes for peer-to-peer energy sharing,” IEEE Transactions on Smart Grid, vol. 12, no. 6, pp. 5158–5171, Nov. 2021.

[18]

L. D. Chen, N. Liu, and J. H. Wang, “Peer-to-peer energy sharing in distribution networks with multiple sharing regions,” IEEE Transactions on Industrial Informatics, vol. 16, no. 11, pp. 6760–6771, Nov. 2020.

[19]

N. Liu, X. H. Yu, C. Wang, C. J. Li, L. Ma, and J. Y. Lei, “Energy-sharing model with price-based demand response for microgrids of peer-to-peer prosumers,” IEEE Transactions on Power Systems, vol. 32, no. 5, pp. 3569–3583, Sep. 2017.

[20]

W. J. Cole, J. D. Rhodes, W. Gorman, K. X. Perez, M. E. Webber, and T. F. Edgar, “Community-scale residential air conditioning control for effective grid management,” Applied Energy, vol. 130, pp. 428–436, Oct. 2014.

[21]

S. C. Cui, Y. W. Wang, Y. Shi, and J. W. Xiao, “A new and fair peer-to-peer energy sharing framework for energy buildings,” IEEE Transactions on Smart Grid, vol. 11, no. 5, pp. 3817–3826, Sep. 2020..

[22]

S. C. Cui, Y. W. Wang, Y. Shi, and J. W. Xiao, “An efficient peer-to-peer energy-sharing framework for numerous community prosumers,” IEEE Transactions on Industrial Informatics, vol. 16, no. 12, pp. 7402–7112, Dec. 2020.

[23]

B. C. Li, T. Y. Chen, X. Wang, and G. B. Giannakis, “Real-time energy management in microgrids with reduced battery capacity requirements,” IEEE Transactions on Smart Grid, vol. 10, no. 2, pp. 1928–1938, Mar. 2019.

[24]

P. H. Li, W. X. Sheng, Q. Duan, Z. Li, C. H. Zhu, and X. Y. Zhang, “A lyapunov optimization-based energy management strategy for energy hub with energy router,” IEEE Transactions on Smart Grid, vol. 11, no. 6, pp. 4860–4870, Nov. 2020, doi: 10.1109/TSG.2020.2968747.

[25]
Y. Xu, J. H. Zhang, W. Y. Wang, A. Juneja, and S. Bhattacharya, “Energy router: Architectures and functionalities toward energy internet,” in 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm), 2011, pp. 31–36.
[26]

M. Geidl, G. Koeppel, P. Favre-Perrod, B. Klockl, G. Andersson, and K. Frohlich, “Energy hubs for the future,” IEEE Power and Energy Magazine, vol. 5, no. 1, pp. 24–30, Jan./Feb. 2007.

[27]

G. T. Ayele, P. Haurant, B. Laumert, and B. Lacarrière, “An extended energy hub approach for load flow analysis of highly coupled district energy networks: Illustration with electricity and heating,” Applied Energy, vol. 212, pp. 850–867, Feb. 2018.

[28]

W. L. Wang, D. Wang, H. J. Jia, G. X. He, Y. Q. Zhi, L. Liu, and M. H. Fan, “Analysis of energy flow optimization in regional electricity-gas-heat integrated energy system considering operational constraints,” Proceedings of the CSEE, vol. 37, no. 24, pp. 7108–7120, Dec. 2017.

[29]
M. J. Neely, Stochastic Network Optimization with Application to Communication and Queueing Systems, Cham: Springer, 2010.
[30]

W. B. Shi, N. Li, C. C. Chu, and R. Gadh, “Real-time energy management in microgrids,” IEEE Transactions on Smart Grid, vol. 8, no. 1, pp. 228–238, Jan. 2017.

[31]
R. B. Myerson, Game Theory: Analysis of Conflict, Cambridge: Harvard University Press, 1997.
[32]
X. D. Zhang, Matrix analysis and Application, Beijing: Tsinghus University Press, 2004.
[33]

Y. M. Dai, Y. Gao, H. W. Gao, and G. H. Yuan, “Leader-follower game model for demand response in smart residential grid,” Automation of Electric Power Systems, vol. 41, no. 15, pp. 88–94, Aug. 2017.

[34]
T. BAŞAR and G. JAN OLSDER, Dynamic Noncooperative Game Theory, 2nd ed., San Diego: SIAM Classics, 1999.
[35]

S. X. Wang, Z. J. WU, and J. Zhuang, “Optimal dispatching model of CCHP type regional multi-microgrids considering interactive power exchange among microgrids and output coordination among micro-sources,” Proceedings of the CSEE, vol. 37, no. 24, pp. 7185–7194, Dec. 2017.

[36]
J. J. Li, T. Zhang, S. Guo, L. Wang, J. Yu, C. Wang, Q. Zhang, and H. Zeng, “Sequential model of the grid load structure with electric vehicle load,” in 2016 China International Conference on Electricity Distribution (CICED), 2016, pp. 1–4.
[37]

J. Q. Shi, H. HU, and J. H. Zhang, “Distributed low-carbon economy scheduling for integrated energy system with multiple individual energy-hubs,” Power System Technology, vol. 43, no. 1, pp. 126–134, Jan. 2019.

CSEE Journal of Power and Energy Systems
Pages 1105-1118
Cite this article:
Li P, Sheng W, Duan Q, et al. Day-ahead P2P Energy Sharing Strategy Among Energy Hubs Considering Flexibility of Energy Storage and Loads. CSEE Journal of Power and Energy Systems, 2024, 10(3): 1105-1118. https://doi.org/10.17775/CSEEJPES.2021.06510

179

Views

2

Downloads

0

Crossref

3

Web of Science

2

Scopus

0

CSCD

Altmetrics

Received: 31 August 2021
Revised: 15 December 2021
Accepted: 25 February 2022
Published: 09 December 2022
© 2021 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Return