Xiupeng Chen

Phd student, University of Groningen


Email: [email protected]


Faculty of Science and Engineering

University of Groningen



A Network-Constrained Demand Response Game for Procuring Energy Balancing Services


Journal article


Xiupeng Chen, Koorosh Shomalzadeh, J. Scherpen, N. Monshizadeh
Under review, IEEE transactions on Smart grid, 2024

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APA   Click to copy
Chen, X., Shomalzadeh, K., Scherpen, J., & Monshizadeh, N. (2024). A Network-Constrained Demand Response Game for Procuring Energy Balancing Services. Under Review, IEEE Transactions on Smart Grid.


Chicago/Turabian   Click to copy
Chen, Xiupeng, Koorosh Shomalzadeh, J. Scherpen, and N. Monshizadeh. “A Network-Constrained Demand Response Game for Procuring Energy Balancing Services.” Under review, IEEE transactions on Smart grid (2024).


MLA   Click to copy
Chen, Xiupeng, et al. “A Network-Constrained Demand Response Game for Procuring Energy Balancing Services.” Under Review, IEEE Transactions on Smart Grid, 2024.


BibTeX   Click to copy

@article{xiupeng2024a,
  title = {A Network-Constrained Demand Response Game for Procuring Energy Balancing Services},
  year = {2024},
  journal = {Under review, IEEE transactions on Smart grid},
  author = {Chen, Xiupeng and Shomalzadeh, Koorosh and Scherpen, J. and Monshizadeh, N.}
}

Abstract

Procuring flexibility services from energy consumers has been a potential solution to accommodating renewable generations in future power system. However, efficiently and securely coordinating the behaviors of diverse market participants within a privacy-preserving environment remains a challenge. This paper addresses this issue by introducing a game-theoretic market framework for real-time energy balancing. The competition among energy consumers is modeled as a Generalized Nash Game (GNG), which enables the analysis of their strategic decision-making. To mitigate the market power exerted by active energy consumers, we employ a supply function-based bidding method in this market design. We incorporate physical constraints to ensure the secure operation of the distribution network. Previous approaches to steering consumers towards the Generalized Nash Equilibrium (GNE) of this game often necessitate the sharing of private information, either in full or in part, which may not be practically feasible. To overcome this limitation, we propose a preconditioned forward-backward algorithm, with analytical convergence guarantees, that only requires participants to share limited, non-private sensitive information with others. Finally, numerical simulations on the enhanced IEEE 33-bus test case validate the effectiveness of our proposed market mechanism and algorithm.





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