Multi-game optimization operation strategy for integrated energy system considering spatiotemporal correlation of renewable energy

Xun Xu, Zhenguo Shao, Feixiong Chen and Guoyang Cheng

Energy, 2024, vol. 303, issue C

Abstract: With the increasing diversity of market entities in the integrated energy system (IES), the interests of multiple entities become complex and variable, leading to disorganized competition among entities in the trading market. Therefore, this paper presents an optimal operation strategy for IES employing a multi-game with tri-level transactions. Firstly, a tri-level IES framework is established with the energy production provider alliance, energy sales agent, and energy user agents as the main entities. Secondly, to handle the uncertainty of renewable energy, a MD-K2 dynamic bayesian network method describing the spatiotemporal correlation of wind and photovoltaic is proposed, and generates probabilistic scenarios. Then, a tri-level multi-game optimization operation model is constructed considering multi-dimensional transactions and demand responses, and is proved to achieve the game equilibrium. Finally, the tri-level model is converted into bi-level mixed-integer linear programming (BMILP) problem, which is solved by a bisection-based distributed iterative algorithm. The simulation results indicate that the optimization strategy improves the interests of tri-level entities and promotes fair distribution of cooperative benefits among alliance members.

Keywords: Integrated energy system; Multi-game; Dynamic bayesian network; Distributed algorithm; Game equilibrium (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544224015470
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:303:y:2024:i:c:s0360544224015470

DOI: 10.1016/j.energy.2024.131774

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().