Framework optimizes electricity-carbon transacctions with microgrids without overloading networks

As the public becomes more aware of carbon reduction, it is increasingly likely that local electrical grids, called microgrids, will couple carbon transactions with electricity transactions. Such changes are poised to make managing microgrids significantly more complex and pose risks of power flows exceeding microgrid limits.

Xin et al. have developed an optimization framework that facilitates electricity-carbon coupled transactions across multiple microgrids and safely works within microgrid networks. The group used a prediction-correction-based alternating direction method of multipliers (ADMM) algorithm framework to collaboratively optimize peer-to-peer electricity trading among microgrids and carbon trading with ladder pricing based on carbon emissions. They embedded carbon costs into the derivation of the distribution locational marginal price (DLMP), generating a price signal that incorporates carbon costs to guide low-carbon trading and dispatch in the power system.

“This study provides a scalable, bi-level optimization framework for the coordinated operation of electricity-carbon markets, which is particularly suitable for new power systems with multiple trading entities,” said author Luhao Wang. “A surprising finding was that the introduction of carbon costs significantly altered the spatiotemporal distribution of the DLMP, with electricity price fluctuations highly correlated with carbon emissions over time.”

They found that incorporating DLMP with carbon cost into the model reduced the power interaction between microgrids and the distribution grid, while improving the carbon trading benefits of the microgrid. Simulations showed cost savings of 12.2%, 2.1%, and 7.7% for three microgrids.

The group’s correction strategy reduces the number of iterations by 43% compared to traditional ADMM, cutting computational time.

Next, they plan to focus on how microgrids’ operational decisions proactively influence the uncertainty they face, providing key support for building a highly resilient, low-carbon power system.

Source: “Distributed optimization for electricity-carbon coupling transactions in multiple microgrids under network constraints,” by Xiangjin Xin, Luhao Wang, Yanlai Zhao, Sirui Zhang, Fengchen Song, Journal of Renewable and Sustainable Energy (2025). The article can be accessed at https://doi.org/10.1063/5.0279163 .