In the pursuit of global carbon neutrality, the energy sector is grappling with the challenge of integrating Carbon Capture, Utilization, and Storage (CCUS) technology into thermal power systems. A recent study published in the journal “IEEE Access” offers a novel approach to optimize peaking costs and ensure fair cost allocation, potentially reshaping the future of energy production and consumption.
The research, led by Yihui Song from the Shenyang Institute of Engineering in China, addresses a critical issue: the large-scale application of CCUS technology has significantly reduced the peaking margin of thermal power units. Traditional peaking cost allocation models often overlook the unique challenges faced by carbon capture power plants, leading to inequitable cost distribution.
Song and his team propose a multidimensional characterization method to quantify peaking costs. “We’ve developed a two-layer architecture that considers both temporal and spatial characteristics,” Song explains. “This ensures that each peaking entity actively participates in peaking and benefits from it.”
The study introduces a dynamic peak-shifting model that accounts for the impact of carbon capture power plants’ participation in peak shifting on carbon emission reduction and carbon cost. The researchers employed an improved kernel method to establish a coalition reorganization trigger mechanism, solving the problem of unfair cost sharing.
The results are promising. Using the improved IEEE34 node as an example, the study found that the total cost of thermal power peak shaving using CCUS is 6.5% lower than that of conventional thermal power units. This highlights the economic advantages of CCUS technology in reducing the burden of peak shaving.
Moreover, when the carbon price is between 150-250 yuan/ton, carbon emissions are reduced by 40%-50%, with a cost increase of less than 5%. This demonstrates the feasibility of achieving large-scale carbon emission reduction while strictly controlling economic costs.
The research also shows that the correlation coefficient of the contribution of the kernel method is increased to 0.91, indicating a significant improvement in the accuracy of multi-agent contribution evaluation. This enhances the fairness of the peak-shifting cost-sharing model, providing a reliable solution for balancing costs between traditional power supply and CCUS units.
The implications of this research are far-reaching. As the energy sector transitions towards carbon neutrality, the integration of CCUS technology into thermal power systems becomes increasingly important. This study offers a robust framework for optimizing peaking costs and ensuring equitable cost allocation, paving the way for more sustainable and economically viable energy solutions.
“The unity of economy and environmental protection is achieved,” Song notes, underscoring the dual benefits of the model in deep emission reduction and carbon price co-optimization. This research not only advances the scientific understanding of CCUS technology but also provides practical tools for the energy sector to navigate the complexities of the transition to a low-carbon future.
Published in the esteemed journal “IEEE Access,” this study is poised to influence future developments in the field, offering a blueprint for the synergistic integration of CCUS and new energy sources. As the world moves towards a greener future, such innovations will be crucial in shaping the energy landscape.