A stochastic game for energy resource trading in the context of Energy Internet

Chaojie Li; Xinghuo Yu; Peter Sokolowski; Nian Liu; Guo Chen

doi:10.1109/PESGM.2016.7741891

A stochastic game for energy resource trading in the context of Energy Internet

Chaojie Li
, Xinghuo Yu
, Peter Sokolowski
, Nian Liu
, Guo Chen

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

3 Citations (Scopus)

Abstract

In this paper, the problem of energy resource trading in an Energy Internet context is studied. By collecting information about energy bidding of multiple microgrids, an aggregator aims to maximize each microgrids' profit while minimizing the risk of overbidding for renewable energy resources trading-based microgrids. A novel stochastic game-theoretic model and the conditional value-at-risk (CVaR) measurement are introduced to characterize the payoff function of each microgrid. The sample average approximation technique is employed to approximate the stochastic Nash equilibrium. The existence of a sample average approximated (SAA) Nash equilibrium is investigated and the corresponding seeking algorithm is also proposed. The results are illustrated by numerical simulations, which show the SAA Nash equilibrium could reduce the risk of not meeting the demand and improve the economic benefits. © 2016 IEEE.

Original language	English
Title of host publication	2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Publisher	IEEE Computer Society
Volume	2016-November
ISBN (Print)	9781509041688
DOIs	https://doi.org/10.1109/PESGM.2016.7741891
Publication status	Published - 10 Nov 2016
Externally published	Yes
Event	2016 IEEE Power and Energy Society General Meeting, PESGM 2016 - Boston, United States Duration: 17 Jul 2016 → 21 Jul 2016

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2016-November
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Place	United States
City	Boston
Period	17/07/16 → 21/07/16

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1109/PESGM.2016.7741891

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Li, C., Yu, X., Sokolowski, P., Liu, N., & Chen, G. (2016). A stochastic game for energy resource trading in the context of Energy Internet. In 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 (Vol. 2016-November). Article 7741891 (IEEE Power and Energy Society General Meeting; Vol. 2016-November). IEEE Computer Society. https://doi.org/10.1109/PESGM.2016.7741891

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title = "A stochastic game for energy resource trading in the context of Energy Internet",

abstract = "In this paper, the problem of energy resource trading in an Energy Internet context is studied. By collecting information about energy bidding of multiple microgrids, an aggregator aims to maximize each microgrids' profit while minimizing the risk of overbidding for renewable energy resources trading-based microgrids. A novel stochastic game-theoretic model and the conditional value-at-risk (CVaR) measurement are introduced to characterize the payoff function of each microgrid. The sample average approximation technique is employed to approximate the stochastic Nash equilibrium. The existence of a sample average approximated (SAA) Nash equilibrium is investigated and the corresponding seeking algorithm is also proposed. The results are illustrated by numerical simulations, which show the SAA Nash equilibrium could reduce the risk of not meeting the demand and improve the economic benefits. {\textcopyright} 2016 IEEE.",

author = "Chaojie Li and Xinghuo Yu and Peter Sokolowski and Nian Liu and Guo Chen",

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doi = "10.1109/PESGM.2016.7741891",

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Li, C, Yu, X, Sokolowski, P, Liu, N & Chen, G 2016, A stochastic game for energy resource trading in the context of Energy Internet. in 2016 IEEE Power and Energy Society General Meeting, PESGM 2016. vol. 2016-November, 7741891, IEEE Power and Energy Society General Meeting, vol. 2016-November, IEEE Computer Society, 2016 IEEE Power and Energy Society General Meeting, PESGM 2016, Boston, United States, 17/07/16. https://doi.org/10.1109/PESGM.2016.7741891

A stochastic game for energy resource trading in the context of Energy Internet. / Li, Chaojie; Yu, Xinghuo; Sokolowski, Peter et al.
2016 IEEE Power and Energy Society General Meeting, PESGM 2016. Vol. 2016-November IEEE Computer Society, 2016. 7741891 (IEEE Power and Energy Society General Meeting; Vol. 2016-November).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A stochastic game for energy resource trading in the context of Energy Internet

AU - Li, Chaojie

AU - Yu, Xinghuo

AU - Sokolowski, Peter

AU - Liu, Nian

AU - Chen, Guo

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2016/11/10

Y1 - 2016/11/10

N2 - In this paper, the problem of energy resource trading in an Energy Internet context is studied. By collecting information about energy bidding of multiple microgrids, an aggregator aims to maximize each microgrids' profit while minimizing the risk of overbidding for renewable energy resources trading-based microgrids. A novel stochastic game-theoretic model and the conditional value-at-risk (CVaR) measurement are introduced to characterize the payoff function of each microgrid. The sample average approximation technique is employed to approximate the stochastic Nash equilibrium. The existence of a sample average approximated (SAA) Nash equilibrium is investigated and the corresponding seeking algorithm is also proposed. The results are illustrated by numerical simulations, which show the SAA Nash equilibrium could reduce the risk of not meeting the demand and improve the economic benefits. © 2016 IEEE.

AB - In this paper, the problem of energy resource trading in an Energy Internet context is studied. By collecting information about energy bidding of multiple microgrids, an aggregator aims to maximize each microgrids' profit while minimizing the risk of overbidding for renewable energy resources trading-based microgrids. A novel stochastic game-theoretic model and the conditional value-at-risk (CVaR) measurement are introduced to characterize the payoff function of each microgrid. The sample average approximation technique is employed to approximate the stochastic Nash equilibrium. The existence of a sample average approximated (SAA) Nash equilibrium is investigated and the corresponding seeking algorithm is also proposed. The results are illustrated by numerical simulations, which show the SAA Nash equilibrium could reduce the risk of not meeting the demand and improve the economic benefits. © 2016 IEEE.

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UR - https://www.scopus.com/pages/publications/85002377915#tab=impact

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DO - 10.1109/PESGM.2016.7741891

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SN - 9781509041688

VL - 2016-November

T3 - IEEE Power and Energy Society General Meeting

BT - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016

PB - IEEE Computer Society

T2 - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016

Y2 - 17 July 2016 through 21 July 2016

ER -

A stochastic game for energy resource trading in the context of Energy Internet

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