Research on collaborative optimization of the electric-carbon joint market based on renewable energy subsidies

This paper addresses the current challenges in coordinating interactions between the power market and the carbon market, particularly the shortcomings arising from the insufficient consideration of renewable energy subsidies. To tackle these issues, we propose a collaborative optimization approach for an integrated electric–carbon market that incorporates a renewable subsidy mechanism. The aim is to foster deeper integration between the power and carbon markets, enhance the share of clean energy in the overall mix, and drive low-carbon transitions. A joint market clearing model is constructed that explicitly includes renewable subsidy costs in the objective function, thereby capturing the true cost-benefit dynamics of renewable projects. A case study based on a regional power system demonstrates the model’s effectiveness and feasibility, with the Particle Swarm Optimization (PSO) algorithm successfully converging to a near-optimal solution. This research not only provides theoretical support for the real-world application of coordinated electric–carbon market operations but also offers significant practical value by incorporating renewable energy incentives into the market design.

Authors

Institutions

Publication Details

Journal
Frontiers in Physics
Published
2025-05-29
DOI
https://doi.org/10.3389/fphy.2025.1606657
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on collaborative optimization of the electric-carbon joint market based on renewable energy subsidies

Suyang Zhou, Bo Yuan, Gang Lü, Peng Xia et al.
1 citations
Frontiers in Physics
Integrated Energy Systems Optimization
0.73
article

Research on collaborative optimization of the electric-carbon joint market based on renewable energy subsidies

Suyang Zhou, Bo Yuan, Gang Lü, Peng Xia, Qiuli Zhao, Fuqiang Zhang
article en
1 citations

Abstract

This paper addresses the current challenges in coordinating interactions between the power market and the carbon market, particularly the shortcomings arising from the insufficient consideration of renewable energy subsidies. To tackle these issues, we propose a collaborative optimization approach for an integrated electric–carbon market that incorporates a renewable subsidy mechanism. The aim is to foster deeper integration between the power and carbon markets, enhance the share of clean energy in the overall mix, and drive low-carbon transitions. A joint market clearing model is constructed that explicitly includes renewable subsidy costs in the objective function, thereby capturing the true cost-benefit dynamics of renewable projects. A case study based on a regional power system demonstrates the model’s effectiveness and feasibility, with the Particle Swarm Optimization (PSO) algorithm successfully converging to a near-optimal solution. This research not only provides theoretical support for the real-world application of coordinated electric–carbon market operations but also offers significant practical value by incorporating renewable energy incentives into the market design.

Frontiers in PhysicsVol. 13
Energy Research Institute (CN), Southeast University (CN)
Openalex Percentile: Top 28%
Integrated Energy Systems Optimization
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.