Lithium-ion batteries are the backbone of novel energy vehicles and ultimately contribute to a more sustainable and environmentally friendly transportation system. Taking a 5 Ah ternary lithium-ion battery as an example, a two-dimensional axisymmetric electrochemical–thermal coupling model is developed via COMSOL Multiphysics 6.0 in this study and then is validated with the experimental data. The proportion of different types of heat generation in a 26,650 ternary lithium-ion battery during the charge/discharge cycle is investigated numerically. Moreover, the impact of essential factors such as charge/discharge multiplier and ambient temperature on the reaction heat, ohmic heat, and polarization heat are analyzed separately. The numerical results indicate that the total heat generated by the constant discharge process is the highest in the charging and discharging cycle of a single battery. The maximum heat production per unit volume is 67,446.99 W/m³ at 2 C multiplier discharge. Furthermore, the polarization heat presents the highest percentage in the charge/discharge cycle, reaching up to 58.18% at 0 C and 1 C multiplier discharge. In a high-rate discharge, the proportion of the reaction heat decreases from 34.31% to 12.39% as the discharge rate increases from 0.5 C to 2 C. As the discharge rate rises and the ambient temperature falls, the maximum temperature increase of the single-cell battery also rises, with a more pronounced impact compared to increasing the discharge rate.

Upon the implementation of the European Union Carbon Border Adjustment Mechanism (CBAM), substantial challenges are anticipated to impact the international trade of Chinese steel products. To safeguard the competitiveness of Chinese steel products on the global stage, this paper establishes a tripartite evolutionary game model, involving large steel enterprises, small- and medium-sized steel enterprises, and the government. The model integrates collaborative emission reduction and free-riding benefits among enterprises, along with the government’s dynamic subsidies and penalties. First, we calculate the replicator dynamic equations and conduct stability analysis to obtain the evolutionary trends and system equilibrium points in different phases of the CBAM. Then, we validate the evolutionary theoretical analysis of the model through example simulation analysis. Finally, we explore the impact of different parameters on the agents through a sensitivity analysis of parameters. The findings indicate that (1) large enterprises demonstrate greater sensitivity to CBAM, making their production structures more susceptible to changes in CBAM policies; (2) small- and medium-sized enterprises are more prone to free-riding behavior influence; (3) government intervention should be kept within appropriate boundaries, as excessive intervention may lead to strategic oscillation, with passive management being chosen by the government during the strengthening phase of CBAM; (4) elevating the price in the Chinese carbon market would slow down the structural changes in the production of Chinese steel enterprises, serving as an effective measure to counteract the impacts of CBAM. This paper provides theoretical support for how steel enterprises and the government can respond to CBAM, aiding stakeholders in selecting optimal strategies during different implementation stages and mitigating the impacts of the CBAM to the maximum extent possible.

The green and low-carbon transformation of the iron and steel industry stands as a pivotal cornerstone in the development of China. It is an inevitable trajectory guiding the future of industry. This study examined the energy consumption and carbon emission trends in the iron and steel industry. Variations under different scenarios were analyzed while emphasizing production control, changes in production structure and energy efficiency improvement. The analysis integrated the extreme energy efficiency model. This study proposed methods to enhance energy efficiency in the iron and steel industry. The costs of energy efficiency improvement and production structure changes were assessed using marginal energy saving and abatement cost curves. The findings showed that the carbon emission reduction contribution of crude steel production decline is the highest, while energy efficiency improvement technology offers the smallest, whose contribution, however, is substantial and cannot be overlooked by 2030. Energy efficiency improvement in the Chinese iron and steel industry results in an average unit energy saving and abatement cost of 27.0 yuan. It results in a total abatement cost of 21.02 billion yuan and a potential abatement of 780 Mt. Considering abatement potential, altering production structure offers significantly higher cumulative abatement compared to energy efficiency improvement technology. This is because the per unit abatement cost of production structure change is 702.7 yuan. However, this high cost poses a challenge to widespread adoption. The integration of the iron and steel industry into the carbon trading system necessitates reinforcing market constraints and expediting process adjustments. These steps are crucial to achieving the green and low-carbon transformation of the industry.

Integrated Energy Systems (IESs) interconnect various energy networks to achieve coordinated planning and optimized operation among heterogeneous energy subsystems, making them a hot topic in current energy research. However, with the high integration of renewable energy sources, their fluctuation characteristics introduce uncertainties to the entire system, including the corresponding indirect carbon emissions from electricity. To address these issues, this paper constructs a two-stage, three-layer robust optimization operation model for IESs from day-ahead to intra-day. The model analyzes the uncertainties in carbon emission intensity at grid-connected nodes, as well as the uncertainty characteristics of photovoltaic, wind turbine, and cooling, heating, and electricity loads, expressed using polyhedral uncertainty sets. It standardizes the modeling of internal equipment in the IES, introduces carbon emission trading mechanisms, and constructs a low-carbon economic model, transforming the objective function and constraints into a compact form. The column-and-constraint generation algorithm is applied to transform the three-layer model into a single-layer main problem and a two-layer subproblem for iterative solution. The Karush–Kuhn–Tucker (KKT) condition is used to convert the two-layer subproblem into a linear programming model. A case study conducted on a park shows that while the introduction of uncertainty optimization increases system costs and carbon emissions compared to deterministic optimization, the scheduling strategy is more stable, significantly reducing the impact of uncertainties on the system. Moreover, the proposed strategy reduces total costs by 5.03% and carbon emissions by 1.25% compared to scenarios considering only source load uncertainty, fully verifying that the proposed method improves the economic and low-carbon performance of the system.