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Regular Paper | Open Access

Market Equilibrium Based on Cloud-edge Collaboration

Tong Cheng, Haiwang Zhong( ), Qing Xia
State Key Laboratory of Power Systems, the Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
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Abstract

Market participants can only bid with lagged information disclosure under the existing market mechanism, which can lead to information asymmetry and irrational market behavior, thus influencing market efficiency. To promote rational bidding behavior of market participants and improve market efficiency, a novel electricity market mechanism based on cloud-edge collaboration is proposed in this paper. Critical market information, called residual demand curve, is published to market participants in real-time on the cloud side, while participants on the edge side are allowed to adjust their bids according to the information disclosure prior to closure gate. The proposed mechanism can encourage rational bids in an incentive-compatible way through the process of dynamic equilibrium while protecting participants’ privacy. This paper further formulates the mathematical model of market equilibrium to simulate the process of each market participant’s strategic bidding behavior towards equilibrium. A case study based on the IEEE 30-bus system shows the proposed market mechanism can effectively guide bidding behavior of market participants, while condensing exchanged information and protecting privacy of participants.

Keywords

Cloud-edge collaborationmarket mechanismresidual demand curvestrategic bidding

References

[1]

X. Vives, “Strategic supply function competition with private information,” Econometrica, vol. 79, no. 6, pp. 1919–1966, Nov. 2011.
Crossref Google Scholar
[2]
P. Holmberg and F. Wolak, “Electricity markets: designing auctions where suppliers have uncertain costs, ” University of Cambridge, Cambridge, Dec. 2015.
[3]
PJM. Data directory.[Online]. Available: https://www.pjm.com/markets-and-operations/data-dictionary
[4]
ERCOT. Market information.[Online]. Available: http://www.ercot.com/mktinfo/dam
[5]
Nordpool. Market data.[Online]. Available: https://www.nordpoolgroup.com/en/Market-data1/#/nordic/table
[6]
South China Energy Regulatory Office of the National Energy Administration. Notice on soliciting opinions on rules for the southern electricity spot market (starting from guangdong).[Online]. Available: http://nfj.nea.gov.cn/adminContent/initViewContent.do?pk=402881e56579be6301658d7123c2001a
[7]
Shanxi Supervision Bureau of the National Energy Administration. Notice on the solicitation of Shanxi electricity market information disclosure guidelines.[Online]. Available: http://sxb.nea.gov.cn/adminContent/initViewContent.do?pk=297eb7f472ca167b0172e43cb2290012
[8]
North China Supervision Bureau of the National Energy Administration. Notice on printing the rules for electricity market in Western Part of Inner Mongolia.[Online]. Available: http://hbj.nea.gov.cn/adminContent/initViewContent.do?pk=000000006b42ce98016b4ca51af00019
[9]
Y. J. Li and L. Z. Zhang, “The sensitive information disclosure modes in electricity spot market abroad and their enlightenments for China, ” in Proceedings of 2018 2nd IEEE Conference on Energy Internet and Energy System Integration, Beijing, China, 2018, pp. 1–5.
[10]
E. Lazarczyk and C. Le Coq, “Information disclosure rules in the european electricity market: an overview, ” in Proceedings of the 15th International Conference on the European Energy Market, Lodz, Poland, 2018, pp. 1–4.
[11]
AEMO. Data (NEM).[Online]. Available: https://www.aemo.com.au/energy-systems/electricity/national-electricity-market-nem/data-nem/market-management-system-mms-data/yesterdays-bid JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 9
[12]

Q. X. Chen, X. C. Fang, H. Y. Guo, K. D. Zheng, Q. H. Tang, R. K. Lyu, K. K. Pan, P. Palensky, D. S. Kirschen, and C. Q. Kang, “The competition and equilibrium in power markets under decarbonization and decentralization,” iEnergy, vol. 1, no. 2, pp. 188–203, Jun. 2022.
Crossref Google Scholar
[13]

B. F. Hobbs, C. B. Metzler, and J. S. Pang, “Strategic gaming analysis for electric power systems: an MPEC approach,” IEEE Transactions on Power Systems, vol. 15, no. 2, pp. 638–645, May 2000.
Crossref Google Scholar
[14]

T. Li and M. Shahidehpour, “Strategic bidding of transmission-constrained GENCOs with incomplete information,” IEEE Transactions on Power Systems, vol. 20, no. 1, pp. 437–447, Feb. 2005.
Crossref Google Scholar
[15]

H. Haghighat, H. Seifi, and A. R. Kian, “Gaming analysis in joint energy and spinning reserve markets,” IEEE Transactions on Power Systems, vol. 22, no. 4, pp. 2074–2085, Nov. 2007.
Crossref Google Scholar
[16]

A. Baillo, M. Ventosa, M. Rivier, and A. Ramos, “Optimal offering strategies for generation companies operating in electricity spot markets,” IEEE Transactions on Power Systems, vol. 19, no. 2, pp. 745–753, May 2004.
Crossref Google Scholar
[17]

F. A. Campos, A. M. S. Roque, E. F. Sánchez-Úbeda, and J. P. González, “Strategic bidding in secondary reserve markets,” IEEE Transactions on Power Systems, vol. 31, no. 4, pp. 2847–2856, Jul. 2016.
Crossref Google Scholar
[18]

J. P. González, A. M. S. Roque, E. F. Sánchez-Úbeda, J. García-González, and R. G. Hombrados, “Residual demand curves for modeling the effect of complex offering conditions on day-ahead electricity markets,” IEEE Transactions on Power Systems, vol. 32, no. 1, pp. 50–61, Jan. 2017.
Crossref Google Scholar
[19]

H. H. Chen, L. B. Fu, L. Q. Bai, T. Jiang, Y. S. Xue, R. F. Zhang, B. Chowdhury, J. Stekli, and X. Li, “Distribution market-clearing and pricing considering coordination of DSOs and ISO: an EPEC approach,” IEEE Transactions on Smart Grid, vol. 12, no. 4, pp. 3150–3162, Jul. 2021.
Crossref Google Scholar
[20]
W. Q. Hua, H. Xiao, W. Pei, W. Y. Chiu, J. Jiang, H. J. Sun, and P. Matthews, “Transactive Energy and Flexibility Provision in Multi-microgrids Using Stackelberg Game, ” in CSEE Journal of Power and Energy Systems, vol. 9, no. 2, pp. 505–515, Mar. 2023.
[21]

H. Gao, F. Zhang, Y. Xiang, S. Ye, X. Liu and J. Liu, “Bounded Rationality Based Multi-VPP Trading in Local Energy Markets: A Dynamic Game Approach with Different Trading Targets,” CSEE Journal of Power and Energy Systems, vol. 9, no. 1, pp. 221–234, Jan. 2023.
Google Scholar
[22]

Y. F. Si, Y. H. Tan, F. Wang, W. N. Kang, and S. Liu, “Cloud-edge collaborative structure model for power internet of things,” Proceedings of the CSEE, vol. 40, no. 24, pp. 7973–7979, Dec. 2020.
Google Scholar
[23]

J. W. Zhang, P. Wang, and N. Zhang, “Frequency regulation from distributed energy resource using cloud-edge collaborations under wireless environments,” IEEE Transactions on Smart Grid, vol. 13, no. 1, pp. 367–380, Jan. 2022.
Crossref Google Scholar
[24]

Z. J. Zhang, Y. D. Zhang, D. Yue, C. X. Dou, X. H. Ding, and H. F. Zhang, “Economic-driven hierarchical voltage regulation of incremental distribution networks: a cloud-edge collaboration based perspective,” IEEE Transactions on Industrial Informatics, vol. 18, no. 3, pp. 1746–1757, Mar. 2022.
Crossref Google Scholar
[25]
AEMO. Pre-dispatch.[Online]. Available: https://www.aemo.com.au/-/media/files/electricity/nem/securityandreliability/powersystemops/procedures/soop3704-predispatch.pdf?la=en
[26]

X. M. Hu and D. Ralph, “Using EPECs to model bilevel games in restructured electricity markets with locational prices,” Operations Research, vol. 55, no. 5, pp. 809–827, Oct. 2007.
Crossref Google Scholar
[27]

R. D. Zimmerman, C. E. Murillo-Sánchez, and R. J. Thomas, “MATPOWER: steady-state operations, planning, and analysis tools for power systems research and education,” IEEE Transactions on Power Systems, vol. 26, no. 1, pp. 12–19, Feb. 2011.
Crossref Google Scholar
CSEE Journal of Power and Energy Systems
Volume 10 Issue 1,
January 2024
Pages 96-104
DOI: 10.17775/CSEEJPES.2022.07130
Cite this article:
Cheng T, Zhong H, Xia Q. Market Equilibrium Based on Cloud-edge Collaboration. CSEE Journal of Power and Energy Systems, 2024, 10(1): 96-104. https://doi.org/10.17775/CSEEJPES.2022.07130

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Received: 19 October 2022
Revised: 29 December 2022
Accepted: 31 January 2023
Published: 27 June 2023
© 2022 CSEE.

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