@Article{ee.2026.076964,
AUTHOR = {Tianhui Zhao, Jingbo Zhao, Peishuai Li, Hongjin Pan, Zhe Chen, Bingcheng Cen},
TITLE = {Coordinated Market Clearing and Operation for Virtual Power Plants with Multiple Electricity Commodities},
JOURNAL = {Energy Engineering},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/energy/online/detail/27672},
ISSN = {1546-0118},
ABSTRACT = {Virtual power plants (VPPs) serve as an effective means to aggregate and manage large-scale distributed energy resources (DERs). They can supply multiple electricity commodities—including electric energy, reserve capacity, and carbon allowances—to power systems. This paper proposes a coordinated market clearing and operation (CMCO) method for VPPs involved in trading multiple electricity commodities. First, we establish a bi-level CMCO framework that integrates the energy, reserve, and carbon markets. At the upper level, we build a distribution system decision model designed to minimize the total system costs, which cover wholesale market transactions and trades between VPPs involving various commodities. At the lower level, we construct a VPP operation model to optimize DER operation strategies and multi-commodity trading plans. Transactions between different VPPs follow a peer-to-peer (P2P) structure. This bi-level framework enables coordinated optimization of multi-commodity trading and operational decision-making. To efficiently solve the bi-level model with binary variables while protecting VPP privacy, we develop a distributed algorithm combining the dichotomy method and the alternating direction method of multipliers (ADMM). Numerical simulations on a test system with three VPPs verify that the proposed method reduces operational costs by facilitating multi-commodity trading. The results also show that this approach improves DER utilization and supports the low-carbon transition of power systems.},
DOI = {10.32604/ee.2026.076964}
}