Industrial Energy Conservation Research Articles

Study on mechanical and thermal properties of alkali-excited fly ash aerogel foam concrete

With increasing focus on low-carbon energy conservation and environmental protection, there is a need to consider all aspects of life in future developments. To meet the concept and requirements of energy conservation and environmental protection in the building industry, we have developed alkali-excited aerogel-foamed concrete that exhibits excellent thermal insulation performance and mechanical strength. The variables involved in its production include fly ash, foam, aerogels, and polypropylene fibres. In this study, the microstructure and mechanical and thermal properties of alkali-excited fly ash aerogel foam concrete was analysed. The results indicated that fly ash can replace a portion of the cement, resulting in a reduction in the thermal conductivity of the concrete. The addition of aerogels and foams to the concrete can significantly decrease its thermal conductivity. Specifically, when the aerogel content reaches 12 % and the foam content reaches 75 %, the thermal conductivity of the concrete decreases from 0.498 W/m·K to 0.183 W/m·K and 0.19 W/m·K, respectively. However, this decrease in thermal conductivity comes at a cost of approximately 50 % reduction in the flexural and compressive strengths of the concrete. The findings reveal that the aerogel has excellent thermal insulation performance similar to that of the foam, but it has little influence on the mechanical properties of the concrete. Additionally, an increase in the polypropylene fibre content significantly improves the mechanical properties of alkali-excited fly ash aerogel concrete, but the thermal properties of the concrete remain mostly unaffected.

Study of environmental regulation on industrial energy conservation and emission reduction

ObjectiveChina has become the top emitter of carbon dioxide (CO2), since 2006 and continued to maintain a rapid economic expansion alongside rising energy conservation and emission reduction. China faces a deteriorating environment regulation and increased domestic and international pressure to reduce emissions. MethodsThe Emission Trading Scheme (ETS) must be able to decrease emissions and promote energy conservation in developing countries in order for these countries to experience sustainable economic and environmental growth. The impact of China's carbon dioxide (CO2) ETS pilot law, which took effect in 2011, on energy efficiency and carbon reduction was examined in this article. To examine how the CO2 ETS affects energy efficiency and emission reduction, we employ the difference-in-differences (DID) model based on the panel data of the two-digit sector at the province level. ResultsAccording to the findings, regulated industries in pilot areas use 22.8% less energy and emit 15.5% less CO2 than those in non-pilot areas. These reductions were the outcome of the CO2 ETS. According to additional analysis, boosting energy technical efficiency and modifying the industrial structure are the major factors driving the consequences of policy. ConclusionThe CO2 ETS also functions better, according to our research, in regions with strong environmental regulation and marketization. According to our research, developing countries' attempts to conserve energy and reduce emissions have benefited from the CO2 ETS.

Comparative life cycle assessment and techno-economic analysis of electric arc furnace steelmaking processes integrated with solar energy system

Electric arc furnace (EAF) steelmaking process is an environmentally friendly, energy saving, and low-carbon route to produce steel, but its further development is restricted by extensive electricity consumption in China. In this paper, the EAF steelmaking processes driven by solar energy system (EAF-SES) was developed, which supplies electricity for the whole process, and reduce the dependence on traditional energy sources. Life cycle assessment and techno-economic analysis of EAF steelmaking processes integrated with traditional energy system (EAF-TES) and EAF-SES was conducted according to the data of 1536 heats based on the function unit of 1000 kg of molten steel (MS). EAF-SES and EAF-TES were studied and compared from perspectives of life cycle carbon footprint (LCCF), production cost (PC), raw materials cost (RMC), solar energy price (SEP), and carbon tax (CT). The results indicated that EAF-SES enjoyed lower LCCF but higher PC than EAF-TES. The LCCF of EAF-SES was 220 kg lower than that of EAF-TES. Besides, compared to the PC of 478 $ per ton of MS in EAF-TES, the PC in EAF-SES increased by 9.13%. While the electricity price was lower than 0.041 $/kWh or CT higher than 217 $/t CO2, respectively, EAF-SES had both significant advantages of economic and environmental benefits. Vigorously employing clean energy power generation, cutting down hot metal supply, and adopting full scrap melting mode in EAF steelmaking processes achieve better environmental performance. This research is expected to supply a technical idea for energy conservation, emission reduction, and cleaner production in future iron and steel industry.

A novel method for intelligent heating: On-demand optimized regulation of hydraulic balance for secondary networks

In the context of carbon neutrality, energy conservation and carbon reduction in the heating industry have become the focus of attention. However, severe heat loss is currently occurring in the secondary heating system due to hydraulic imbalance, which is unable to supply heat according to users' needs. In view of this, a thermodynamic-hydraulic model of users’ demand for heat and flow rate for the heating system is established. Then, a novel method to regulate hydraulic imbalance is proposed, with the dynamic heat demand satisfied by regulating the valve opening based on NSGA-II. The optimization results show that the comprehensive hydraulic imbalance coefficient has been reduced from 23.08 to less than 0.019, which means that almost 100% of users can get heat supplies corresponding to their needs, while the energy consumption is reduced by about 30%. Additionally, when there are 1000 population and iteration steps, good convergence and high speed are presented using this method. In summary, an on-demand optimized model of hydraulic balance for the secondary heating network is put forward, which provides powerful engineering support and guidance for intelligent heating construction.

High-temperature precipitation behavior of W-containing 444-type ferritic stainless steel in a simulated cyclic annealing process

An important aspect of energy conservation and emission reduction in automotive industry is to improve the combustion efficiency of gasoline. The full combustion of gasoline will inevitably cause an increase in exhaust temperature. The coarsening and dissolution behavior of precipitates in steel will lead to a decrease in its high-temperature mechanical properties when the engine is used for a long time in such an alternating heating and cooling environment. In order to obtain ferritic stainless steel with good high-temperature resistance, this paper is based on 444 ferritic stainless steel and attempts to partially replace Mo element with W element to obtain Laves phase containing W, Mo, and Nb with more stable high-temperature performance. A simulated cyclic high-temperature annealing process up to 1050 °C was designed to investigate the precipitation behavior in this modified ferritic stainless steel. The results show that using W to replace Mo in 444 ferritic stainless steel can refine the grains of ferritic stainless steel. It can not only provide better solid solution strengthening at elevated temperature, but also stabilize the Laves phase and provide precipitation strengthening. The reason is that the W elements can change the composition of the Laves phase in ferritic stainless steels and precipitate Fe2(Nb, W) with high thermal stability to provide stable precipitation strengthening during long-term alternating annealing. The W-rich Laves phase is prone to precipitation at grain boundaries, effectively pinning grain boundaries and preventing microcracks from propagating along grain boundaries during service, thereby improving the service life of the steel.

Ontological how and why: action and objective of planned processes in the food domain.

The computational modeling of food processing, aimed at various applications including industrial automation, robotics, food safety, preservation, energy conservation, and recipe nutrition estimation, has been ongoing for decades within food science research labs, industry, and regulatory agencies. The datasets from this prior work have the potential to advance the field of data-driven modeling if they can be harmonized, but this requires a standardized language as a starting point. Our primary goal is to explore two interdependent aspects of this language: the granularity of process modeling sub-parts and parameter details and the substitution of compatible inputs and processes. A delicate semantic distinction-categorizing planned processes based on the objectives they seek to fulfill vs. categorizing them by the actions or mechanisms they utilize-helps organize and facilitate this endeavor. To bring an ontological lens to process modeling, we employ the Open Biological and Biomedical Ontology Foundry ontological framework to organize two main classes of the FoodOn upper-level material processing hierarchy according to objective and mechanism, respectively. We include examples of material processing by mechanism, ranging from abstract ones such as "application of energy" down to specific classes such as "heating by microwave." Similarly, material processing by objective-often a transformation to bring about materials with certain qualities or composition-can, for example, range from "material processing by heating threshold" to "steaming rice".

Use of Alkali-Activated Slag as an Environment-Friendly Agent for High-Performance Stabilized Soil.

Discharged slag not only occupies a large amount of land for disposal, but also causes serious environmental pollution. The use of alkali-activated slag (AAS) instead of cement as a soil-stabilization agent is beneficial for industrial waste disposal and energy conservation, which complies with the concept of green and low-carbon sustainable development in the construction industry. In this study, the compressive strength, water permeability coefficient, chloride migration coefficient and sulfate resistance of alkali-activated slag-stabilized soil (AASS) were evaluated, and compared with those of cement-stabilized soil (CSS). The hydrated crystalline phases and microscopic pore structures were analyzed by X-ray diffraction, electrochemical impedance spectroscopy (EIS) and mercury intrusion porosimetry (MIP) tests, respectively. The results indicate that, compared with CSS, AASS exhibits a higher compressive strength, lower water permeability, chloride migration coefficient and better resistance to sulfate attack, with the optimum dosage higher than 10 wt.%. The results of the MIP analysis show that the addition of AAS reduces the porosity by 6.47%. The combined use of soil and AAS proves to be a viable and sustainable method of waste utilization and carbon emission reduction in the construction industry, which provides a practical path towards carbon peaking and carbon neutrality.

The role of carbon pricing in achieving energy transition in the Post-COP26 era: Evidence from China's industrial energy conservation

Carbon pricing is expected to meet COP26 targets and carbon neutrality goals by promoting energy transition. However, the role of carbon pricing in energy transition has been challenged largely because of limited empirical evidence. Most empirical studies draw on samples with low-to-moderate carbon prices, which might underestimate the potential impact of carbon pricing with much higher prices. Accordingly, this study takes energy prices as proxies for carbon prices to estimate the price elasticity of energy consumption. It employs a mapping relationship between carbon and energy prices to conduct simulations under various carbon price scenarios. Using China's industry as an example, the following main findings were obtained. First, the price elasticities of energy consumption are heterogeneous across sectors, implying that the role of carbon pricing may be underestimated if sector heterogeneity is not considered. Second, carbon pricing could considerably decrease energy consumption, particularly in high-energy-consuming sectors, such as ferrous metals, petroleum processing, chemicals, non-metal products, as well as power and heat. Third, by adopting China's Emissions Trading Scheme, the eight planned covered sectors could achieve reductions of 8% or 19% in energy consumption with carbon prices set at 100 or 300 Yuan/tCO2, respectively, which would significantly contribute to the phasedown of coal. Therefore, carbon pricing could play an important role in achieving energy transition in the post-COP26 era.

The energy conservation and emission reduction potentials in China's iron and steel industry: Considering the uncertainty factor

Energy conservation and emission reduction in China's iron and steel industry are crucial for mitigating its environmental pressures. However, uncertainties raise significant management risks when setting energy conservation and emission reduction pathways. Therefore, this paper explores the energy conservation and emission reduction potential in China's iron and steel industry. A 10,000-time Latin hypercube sampling is conducted to simulate the distribution of five types of uncertain factors. In addition, this study uses a Sobol’ sensitivity analysis method to recognize the most sensitive factor, and, in specific, analyzes the cost-effectiveness of the technologies via conservation supply curve. The results show that: (1) The uncertainty factors lead to significant fluctuate to the results. In particular, energy conservation will fluctuate by 18.24–40.77%, carbon mitigation by 28.96–55.34%, and SO2, NOx and PM mitigation effects will fluctuate by 48.32–79.53%, 22.12–51.77% and 23.92–50.03%, respectively. (2) Structure and equipment parameters are more the most sensitive to energy conservation and carbon mitigation targets, whose Sobol’ indices are beyond 0.45. End-of-pipe treatment technologies are more the most sensitive to SO2 and PM reduction targets with Sobol’ indices above 0.9. Penetration rates and equipment parameters are more the most sensitive to economic cost targets above 0.8. (3) In 2035, 33 energy conservation technologies and 34 emission reduction technologies will be cost-effective, and they can achieve 69.05–70.14% of energy conservation and 79.03–81.58% of emission reduction potentials, respectively. Based on these findings, this study proposes policy recommendations such as changing the raw material/product structure, upgrading equipment, cooperating actively, and introducing economic incentives and guidelines for technology application.

Designing of system for high grade heat recovery in thermal coolingsystem for process heat applications

An experimental investigation on design of a vapour absorption system using LiBr-H2Ofor high grade heat recovery in thermal cooling system for process heat applications has been conducted. A 1.5 kW cooling capacityof the LiBr-H2O vapour absorption system has beend esigned and tested under various operating conditions. Generator temperature, absorber tem-perature, condenser temperature and evaporator temperature have been varied and perfor-mance of LiBr-H2O vapour absorption system has been analysed. Experimental results are presented in terms of COP and circulation ratio. Further, to validate the results thermody-namic model is developed using first law of thermodynamics and simulate in Engineering Equation Solver. The COP and the circulation ratio estimated through simulationsand exper-iments have been in good agreement with ±5% standard deviation. Further, this this research work is beneficial for dairy industries in process heat applications and realizing the impor-tance of the need for energy conservation in dairy industries.

Introduction to Energy Accounting in Higher Education: A Theoretical Discussion

This review discusses the importance of energy accounting in the curriculum of accounting study programs at universities in Indonesia. Commitment to energy conservation in industry is important to get attention because it has become a commitment from the Indonesian government. Energy conservation has the form of efficiency, savings, and energy management. In the context of higher education, energy accounting discusses energy audits, environmental accounting, green accounting, energy saving measures, as well as other energy cases such as greenwashing and others. Energy accounting learning needs to be followed up to be included in the curriculum of the accounting study program as a form of the commitment of the younger generation to energy conservation. So far, energy accounting has not been specifically discussed. Several universities teach energy accounting in the sub-chapters of social and environmental accounting, sustainability accounting, and green accounting. The next hope is that energy accounting will become a separate subject by getting the full portion of the lesson. The contribution of this review is to improve the accounting study program curriculum so that it has benefits for future accounting developments.

Evaluation of Resource Utilization Efficiency in the Machining Process Based on the SBM-DEA Model with Non-Expected Output

As one of the basic industries in the manufacturing industry, the modeling and evaluation of resource utilization efficiency in the machining process is the premise of energy conservation and consumption reduction in the manufacturing industry. Mechanical processing is the process of using resources to change the shape and performance of the blank to form the workpiece and generate emissions. However, the current research on the utilization of machining process resources, whether focusing on energy efficiency or emissions, cannot provide a comprehensive solution to this problem. Therefore, this paper proposes a Data Envelopment Analysis (DEA) model with a slacks-based measure (SBM) to evaluate the resource utilization efficiency of a machining process with non-expected output. Through the relative effectiveness of DEA, the resource utilization efficiency of each processing process can be compared, which can provide a feasible and specific method for enterprises to evaluate their existing processing processes from the perspective of reducing unexpected output. In this case, the input-output model of the machining process is used to analyze the processed resource list. Then the mathematical model of each process in the processing process is established, and the dynamic resources are determined quantitatively. Finally, the accuracy of the method is verified by combining the resource utilization efficiency of each working procedure in the shaft gear machining process of an enterprise.

Analysis and Suggestions on the Application of China's Industrial Energy Saving Technology

Industrial energy saving is an important measure to achieve carbon neutrality, and energy saving technology is the core driving force for industrial energy saving. In order to study the development of China's industrial energy-saving technology, this paper organizes and analyzes the "Guidelines and Cases of China's Industrial Energy Conservation Technology Application" issued by the Ministry of Industry and Information Technology according to a unified format, and finds out the characteristics of energy conservation technologies in different industries, the deficiencies in sorting and categorizing cases, and the regions of technology suppliers. In order to help the promotion and application of energy-saving technology and equipment, suggestions are put forward to adjust the collection and reporting methods of cases, optimize the content of case templates, strengthen the publicity and application of cases, and strengthen policy support.

Effective pathways for energy conservation and emission reduction in iron and steel industry towards peaking carbon emissions in China: Case study of Henan

As the world's largest steel producer, China's iron and steel industry is facing an urgent task need for energy conservation and emission reduction. Discussion of the green and low-carbon transformation of the iron and steel industry at the provincial level is critical for achieving China's ‘Dual-carbon target’. To explore the road-map towards peaking carbon emissions of the iron and steel industry, a comprehensive assessment framework, based on steel demand and scrap recycling model alongside energy consumption-carbon emission-air pollutant emission model, was developed. Five scenarios were designed to quantify the potential for energy conservation and emission reduction of the iron and steel industry in Henan Province. The material flow analysis model predicted that the total steel demand will peak at 36.06 Mt in 2020, and the steel demand of main sub-sectors such as construction, machinery, vehicle, appliances and others will peak before 2024. Driven by the boom in depreciation scrap, future steel scrap resources and scrap ratio will show a significant growth trend. By 2035, the integrated scenario will show the most significant potential, and the emissions of CO2, SO2, NOx, CO, PM10, PM2.5, and VOCs will decrease by 55.2%, 54%, 33.3%, 16.6%, 43%, 36.4%, and 31.8%, compared to that in the business-as-usual scenario. The results also indicated that advanced technology implementation poses an advantage in mitigation potential before 2025, while electric arc furnace promotion and hydrogen substitution will be the main forces for energy conservation and emission reduction in the iron and steel industry from a long-term perspective. Finally, several policy recommendations regarding the transformation direction for the government and steelmakers were proposed here.

Intelligent management of industrial building energy saving based on artificial intelligence

In order to improve the efficiency of energy-saving management of industrial buildings, this paper combines artificial intelligence technology to analyze the intelligent energy-saving of industrial buildings, and reduces the energy consumption of industrial buildings through intelligent energy-saving management. Moreover, this paper analyzes the circuit structure design, work flow, and functional description of industrial energy-saving buildings to realize the control interface of electrical equipment, and explains the specific hardware design of energy consumption acquisition module and intelligent gateway. In addition, this paper uses the data collected by the hardware as the input to establish the impulse prediction model. Finally, this paper constructs an intelligent management system for industrial building energy conservation based on constraints and optimization conditions. The data analysis results show that the intelligent energy-saving management system of industrial buildings based on artificial intelligence constructed in this paper has good effects and can play an important role in the energy-saving management of industrial buildings.

Simulation-assisted multi-process integrated optimization for greentelligent aluminum casting

Aluminum casting is one of the most important, yet energy-intensive, lightweight-enabling technologies. To achieve carbon peak and carbon neutrality goals, it is critical to reduce energy consumption without sacrificing productivity. Production optimization of aluminum casting for green and intelligent—i.e., greentelligent—operation is an effective way to accomplish this objective, but this is not sufficient for separately optimizing different processes. Instead, simultaneously optimizing multiple processes is a more advantageous approach, which, however, has not yet been performed. This paper proposes a simulation-assisted approach for the integrated optimization of three primary processes in aluminum casting (i.e., melting, transferring, and holding) to fill this gap. A comprehensive manufacturing cost optimization model that considers the energy, material loss, manpower, and pauses in production for the three processes was first built. Simulation was the key to the formation of the optimization model. Then, a dynamic solution mode with parallel computing and four algorithms (pattern search, genetic algorithm, particle swarm optimization, and simulated annealing) were selected to solve the optimization model. The proposed approach was applied to two die-casting factories to verify its optimization performance. The integrated optimized parameters reduced the comprehensive cost by approximately 8.4% and 16.4% for cases 1 and 2, respectively, for which energy reduction was the primary contributor to the comprehensive cost reduction. The proposed approach was found to be promising for energy conservation and related carbon emissions reduction in the aluminum casting industry.

Analysis of the Factors Affecting China’s Manufacturing Servitization from the Perspective of the Ecological Environment

Manufacturing servitization (MS) can effectively alleviate the contradiction between economic growth and ecological carrying capacity and can promote energy conservation and emission reduction in the manufacturing industry (MI). However, China’s MI is in the primary stage of servitization and lacks sufficient ability to provide services; thus, the environmental benefits of MS are not obvious. Therefore, in the context of current pressure to normalize environmental protection, how servitization can drive low-carbon development in MI while taking into account economic development has become an important topic at present. Thus, this study constructs an evaluation index system of factors based on a driver–pressure–state–impact–response (DPSIR) model, and uses the decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) model to analyze the causal relationship and key elements among the influencing factors. The results show that from the perspective of the ecological environment, many factors affect MS, although to varying degrees. Among them, the proportion of R&D personnel, input intensity, and the proportion of clean energy are the main factors. Based on the transmission mechanism among these factors, we propose two paths to realizing the service-oriented, low-carbon development of China’s MI.

A novel insight into energy conservation and efficiency enhancement in wastewater treatment process: Low-frequency mechanical vibration induced

One important way to break the bottleneck of energy conservation and consumption reduction in sewage treatment process is to attenuate the mass transfer resistance, which is thought as one of key factors to determine the efficiency of activated sludge treatment system. Thus, in this study, two independent Anacrobic/Oxic reactors were operated under low dissolved oxygen (DO) condition to evaluate the effects of low-frequency mechanical vibrations on the removal efficiency of pollutants. Results indicate that 40 Hz low-frequency mechanical vibration could greatly strengthen the efficiency of pollutants removal. Microelectrode-mass transfer efficiency test platform revealed that 40 Hz low-frequency mechanical vibration could increase the oxygen transfer coefficient from gas to liquid by approximately 145.19 %, and oxygen diffusion coefficient from liquid to solid by 75.2 %. Fractal dimension of flocs, particle size and zeta potential analyses jointly suggested that low-frequency mechanical vibrations treatment can form more adsorption points and mass transfer channels to enhance mass transfer efficiency of oxygen in floc. In addition, low-frequency mechanical vibrations treatment further stimulated the biological activities associated with nitrogen metabolism (i.e., specific metabolism rate, metabolism enzyme activities), but slightly alerted the overall microbial community. The findings in this study suggest that low-frequency mechanical vibrations could effectively accelerate the pollutants removal under low-DO condition by enhancing oxygen transfer coefficient and stimulating the associated biological activities. Collectively, this study provides a new technical strategy for efficiency enhancement and energy conservation in the global sewage treatment industry.

Naturalistic data-driven and emission reduction-conscious energy management for hybrid electric vehicle based on improved soft actor-critic algorithm

Energy management strategies (EMSs) are critical to saving fuel and reducing emissions for hybrid electric vehicles (HEVs). Given that, this article proposes a naturalistic data-driven and emission reduction-conscious EMS based on deep reinforcement learning (DRL) for a power-split HEV. In this article, for the purpose of evaluating the practical fuel economy of an HEV driving in a certain city region, a specific driving cycle is constructed by using a naturalistic data-driven method. Furthermore, to realize the multi-objective optimization in terms of fuel conservation and emission reduction as well as the state of charge (SOC) sustaining, an intelligent EMS based on the improved soft actor-critic (SAC) algorithm with a novel experience replay method is innovatively proposed. Finally, the effectiveness and optimality of the proposed EMS are verified. Simulation results indicate that the constructed driving cycle can effectively reflect the real traffic scenarios of the test region. Moreover, the proposed EMS achieves 95.25% fuel economy performance of the global optimum, improving the fuel economy by 5.29% and reducing the emissions by 10.42% compared with the emission reduction-neglecting EMS based on standard SAC. This article contributes to energy conservation and emission reduction for the transportation industry through advanced DRL methods.

Review of Green Supply-Chain Management Diffusion in the Context of Energy Transformation

Against the background of continuously rising energy carbon emissions, accelerated energy transformation in developed countries, and increased international attention to energy security, there is still a large amount of energy consumption in the manufacturing industry. Promoting the diffusion of green supply-chain management is becoming a powerful tool to support energy transformation and energy conservation and emission reduction in the manufacturing industry. Based on this, we first conducted a scientific metrological analysis of 4960 articles in relevant fields in the Web of Science database, presenting the research status of green supply-chain management diffusion in the context of energy transformation. Second, we identified factors that affect the implementation of green supply-chain management, and analyzed the diffusion path of green supply-chain management among enterprises. Finally, based on the energy situation, enterprise operation, and implementation of environmental protection laws and regulations in Shaanxi Province, China, we determined the current situation, obstacles, and development direction of green supply-chain management diffusion of enterprises in the context of energy transformation. The research found that: at this stage, there are still some deficiencies in the research on the mechanism of green supply-chain management in the internal communication of enterprises; in the future, the diffusion of green supply-chain management can be further developed around social performance and energy transformation technology; and we can help energy transformation by strengthening policy guidance and assisting enterprise reform.