• Propose a cyber–physical–social framework for analyzing transactive energy markets. • Reveal key barriers of bounded rationality, strategic gaming, and secure clearing. • Integrate behavioral economics with multi-agent game and network optimization. • Develop a cross-domain, non-iterative secure clearing mechanism under information asymmetry. The transactive energy market serves as an important mechanism for promoting efficient utilization and flexible interaction of distributed energy resources in the new power systems. It is a key path to achieving source-grid-load-storage collaboration and low-carbon transformation of distributed resources. However, given their reliance on the assumptions of complete rationality and complete information, traditional market models are ill-equipped to capture the heterogeneity of energy prosumers, as well as the information asymmetry in the actual power grid. This hinders the promotion of the transactive energy market in new power systems. Therefore, this paper systematically reviews the research progress of transactive energy markets for new power systems, summarizing and analyzing from three core levels: bounded rationality modeling, game mechanism design, and security-constrained market clearing methods. It first summarizes different types of bounded rationality modeling methods and their applicability in characterizing prosumers’ behavior. It then compares the balancing effect of multi-level game mechanisms between market incentives and fairness. Finally, it explores the security-constrained market clearing strategies and cross-domain collaboration mechanisms under conditions of information asymmetry. Future researches need to further integrate cognitive behavior modeling, asynchronous game solving, and differential privacy protection to construct a theoretical system for transactive energy markets that combines behavior authenticity, computation feasibility, and operation security. This exploration can provide support for the market-oriented and intelligent development of new power systems.
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Yue Xia
Beijing City University
Renxi Yu
Yang Li
Stanford University
University of Manchester
Stanford Medicine
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Xia et al. (Sun,) studied this question.
synapsesocial.com/papers/69b5ff6e83145bc643d1be7c — DOI: https://doi.org/10.1016/j.cpes.2025.12.001