Exploring theoretical energy consumption introduces a fresh perspective for energy-saving research within the iron and steel industry, with a primary focus on the energy expended during material transformation. Building upon the theory of theoretical energy consumption, this study meticulously investigates the theoretical energy consumption associated with each stage of the iron and steel making process, including coking, sintering, pelletizing, ironmaking, steelmaking, and hot rolling. The findings reveal that, under specific conditions, the theoretical energy consumption for each process is as follows: coking (2.59 GJ), sintering (1.36 GJ), pelletizing (1.02 GJ), ironmaking (8.81 GJ), steelmaking (−0.16 GJ), and hot rolling (0.76 GJ). Additionally, this study delves into the analysis of influencing factors on theoretical energy consumption. Using the coking process as an illustrative example, it is observed that the theoretical energy consumption in coking decreases with a reduction in both moisture and volatile content in coal. Under the specified conditions, the minimum theoretical energy consumption for each process is as follows: coking (2.51 GJ), sintering (0.98 GJ), pelletizing (0.67 GJ), ironmaking (8.38 GJ), steelmaking (−0.58 GJ), and hot rolling (0.07 GJ), respectively. This comprehensive analysis serves as a valuable resource for advancing sustainable practices in the iron and steel industry.

Carbon tariffs are designed to prevent carbon leakage and encourage global industries to adopt low-carbon practices, which present significant challenges for China’s aluminum industry. A critical issue for China’s aluminum sector is how to effectively reduce carbon emissions while maintaining competitiveness in the face of increasingly strict carbon regulations. This review is based on an extensive examination of high-quality, authoritative research literature, industry data, and policy reports. Accurate data have been systematically summarized, and key findings from reputable studies have been extracted to support the perspectives presented in this review. On this basis, this review systematically analyzes the current status of China’s aluminum industry, emphasizing its reliance on fossil fuels, slow transition to low-carbon technologies, and the inadequate use of recycled aluminum. The potential impacts of carbon tariffs are assessed, highlighting increased carbon costs, reduced production scales, and diminished market competitiveness in foreign markets. To address these challenges, the study proposes several pathways for carbon reduction in China’s aluminum industry, including accelerating the adoption of recycled aluminum, enhancing energy efficiency, advancing low-carbon innovations, and developing supportive policy frameworks. Implementing these measures is vital for decreasing carbon emissions and ensuring the long-term sustainability of the industry amid global climate initiatives.

The coordinated optimization of energy conservation, efficiency improvement, and pollution reduction in the sintering production process is vital for the efficient and sustainable development of the sintering department. However, previous studies have shown shortcomings in the multi-objective collaborative optimization of sintering systems and the quantification of pollutant impacts. To address these, this paper proposes a multi-objective optimization method integrated with the NSGA-III algorithm and establishes an integrated system optimization model for sintered ore production and high-temperature waste heat recovery. The results demonstrate significant improvements: energy utilization efficiency increased by 0.67%, energy consumption decreased by 17.3 MJ/t, production costs were reduced by 11.45 CNY/t, and the emissions of CO₂, SO₂, and NO_x were reduced by 0.464 kg/t, 0.034 kg/t, and 0.008 kg/t, respectively. Additionally, the study identified optimal configuration parameters and analyzed the quantitative impact of several key factors on multiple indicators. The results also show that reducing the water content of the mixture, decreasing the middling coal content in the fuel, and increasing the thickness of the material layer are effective strategies to reduce energy consumption and pollutant emissions in the sintering process. Overall, implementing these optimizations can bring significant economic and environmental benefits to the steel industry.

The iron and steel industry, a major energy consumer, faces significant pressure to reduce CO₂ emissions. As the world’s largest steel producer, China must prioritize this sector to meet its carbon neutrality goals. This study provides a comprehensive review of various carbon reduction technologies to drive decarbonization in the steel industry. China’s iron and steel sector, which accounted for approximately 15% of the country’s total CO₂ emissions in 2022, predominantly relies on coke and coal combustion. This study provides a comprehensive review of a variety of carbon reduction technologies to advance decarbonization in the iron and steel industry. This study categorizes carbon reduction technologies in the steel sector into low-carbon, zero-carbon, and negative-carbon technologies. Low-carbon technologies, which are the most widely implemented, are further divided into energy structure adjustment, material structure adjustment, energy efficiency improvement technologies, etc. This study specifically reviews dry quenching technology, high-scale pellet technology for blast furnace, and top pressure recovery turbine power generation technology. As a zero-carbon technology, hydrometallurgy is a central focus of this study and a key area of research within China’s iron and steel industry. While negative-carbon technologies are primarily centered around carbon capture, utilization technologies are still in early stages. By presenting the latest advancements, this study offers valuable insights and guidance to facilitate the iron and steel industry’s transition to a low-carbon future, crucial for mitigating global climate change.

With the increasing liberalization of energy markets, the penetration of renewable clean energy sources, such as photovoltaics and wind power, has gradually increased, providing more sustainable energy solutions for energy-intensive industrial sectors or parks, such as iron and steel production. However, the issues of the intermittency and volatility of renewable energy have become increasingly evident in practical applications, and the economic performance and operational efficiency of localized microgrid systems also demand thorough consideration, posing significant challenges to the decision and management of power system operation. A smart microgrid can effectively enhance the flexibility, reliability, and resilience of the grid, through the frequent interaction of generation–grid–load. Therefore, this paper will provide a comprehensive summary of existing knowledge and a review of the research progress on the methodologies and strategies of modeling technologies for intelligent power systems integrating renewable energy in industrial production.