Energy Conservation Technologies Research Articles

Design of concrete incorporating microencapsulated phase change materials for clean energy: A ternary machine learning approach based on generative adversarial networks

The inclusion of microencapsulated phase change materials (MPCM) in construction materials is a promising solution for increasing the energy efficiency of buildings and reducing their carbon emissions. Although MPCMs provide thermal energy storage capability in concrete, they typically decrease its compressive strength. A unified framework for the mixture design of concrete incorporating MPCM is yet to be developed to facilitate practical applications. This study proposes a mix design procedure using a novel ternary machine learning (ML) paradigm. For this purpose, the tabular generative adversarial network (TGAN) was utilized to generate large synthetic mixture design data based on the limited available experimental observations. The synthetic data is then employed to construct robust predictive ML models. The gradient boosting regressor (GBR) model trained with synthetic data outperformed the model trained with real data, achieving a testing coefficient of determination (R2) of 0.963 and mean absolute error (MAE) of 2.085 MPa. The TGAN-GBR model was ultimately integrated with the particle swarm optimization (PSO) algorithm to construct a powerful recommendation system for optimizing the mixture design of concrete and mortar incorporating different types of MPCMs. Extensive parametric analyses along with the employed optimization procedure accomplished the mixture design of latent heat thermal energy storage concrete with maximum MPCM inclusion and minimum cement content for various compressive strength classes. The proposed framework enables energy conservation technology in the design of eco-friendly building materials with acceptable mechanical performance.

Influence of research and development, environmental regulation, and consumption of energy on CO2 emissions in China-novel spatial Durbin model perspective.

Global warming continues to be an intimidating factor for environmental protection, and reducing carbon emissions is an effective way to deal with the phenomenon. However, the energy sector is a significant contributor to greenhouse gas emissions. Therefore, investment in environmental regulations and research and development (R&D), is critical for fostering a low-carbon growth model. This study focuses on 30 provinces in China from 2004 to 2019. We used the spatial Durbin model to investigate how the spatial spillover effect of R&D and environmental regulation impacts carbon emissions. In addition, we applied the dynamic threshold panel model to mitigate potential problems of endogeneity. The results reveal that carbon emissions have a considerable spatial correlation in both temporal and spatial dimensions, exhibiting high and low-value accumulation characteristics. Furthermore, the combined effect of R&D intensity, environmental regulation, and energy consumption were found to contribute to the increase in carbon emissions across China's provinces, and they also suggest different influencing mechanisms. The spillover effects of increased carbon emissions in neighboring regions also contribute to the increase in local carbon emissions. The study also found that R&D and stringent environmental regulations measures strongly moderate the link between energy consumption and carbon emissions. In promoting carbon reduction, by breaking the dynamic equilibrium in China, the provincial investment outflow on R&D intensity could be optimized, and the regional levels should focus more on tightening environmental regulatory measures and promoting the development of energy-conserving technologies.

Robust passive daytime radiative coolers based on thermally insulating and spectrally selective composite aerogels with designed fiber-reinforced porous architecture

Passive daytime radiative cooling (PDRC) is an emerging energy conservation technology that spontaneously cools a surface by reflecting solar radiation and emitting excess heat to the cold space through the infrared atmospheric transparency window. A facile strategy to fabricate robust passive daytime radiative coolers based on thermally insulating and spectrally selective composite aerogels are demonstrated. The composited aerogels are constructed by P(VdF-HFP) matrix with abundant micrometer-scale air voids inside and surface modified chopped glass fibers randomly distributed in the porous polymeric matrix. Glass fibers act as skeleton are beneficial for enhancement of the rigidity, compressive strength, and flame retardancy of aerogels to satisfy practical PDRC applications. With a glass fiber mass ratio of 20 %, the aerogel can reach a high average solar reflectance of 0.951 and a high long-wave infrared (LWIR) emissivity of 0.954. By performing rooftop measurements, temperature decrease up to 8.05 °C is experimentally achieved under a high solar radiation (∼946 W m−2) at midday time (12:00–14:00). The promising cooling performance comparable to those of state-of-the-art radiative coolers is attributed to the efficiently scattering ability of sunlight by abundant air voids, and the high thermal insulation property to weaken parasitic heat gain from the ambient air.

Review and prospect of research on road traffic flow energy model

Energy is a necessary prerequisite for the operation of road traffic flow. Describing the phenomena of traffic flow from an energy perspective will promote energy conservation and emission reduction technologies. To clarify the application status and trend of traffic flow energy, this paper studies and summarizes the literature on traffic flow energy, classifies the traffic flow energy models into four groups, discusses the benefits and drawbacks and practical scenarios of various models, and suggests future research topics. The research revealed that the ultra-microscopic traffic flow energy model, based on the principle of vehicle energy flow, has high calculation accuracy but is hard to forecast traffic flow energy, which is adequate for estimating the energy of a single vehicle; The microscopic traffic flow energy model, which can predict traffic flow energy but with low calculation accuracy, considers interactions between fleet vehicles and helps evaluate the energy consumption features of various traffic flow states; The average characteristic parameter of the traffic flow is the key to the macroscopic traffic flow energy model, which calculates energy precisely for the uniform traffic flow but lacks the macroscopic traffic flow theoretical underpinnings; The simplified traffic flow energy model of traffic flow has a straightforward structure but the low calculation accuracy, making it suitable for assessing the effectiveness of the traffic flow model. Large-scale vehicle testing, the thorough integration of macro and micro traffic flow theories, and the decrease of computing complexity should be the main focuses of future research on traffic flow energy models.

Energy: life, power, and livelihood

We and our habitat are forms of energy, endowed with life, and irrevocably earthlings. A cosmological-to-locality appreciation of energy in food and nutrition science, practice and policy is overdue. Our livelihood, and any function we have, are energy dependent, as is planetary habitability. Energy cognisance has become an existential necessity in an increasingly self-destructive ‘anthropocene’ era when our own energy equilibrium is compromised. This is manifest in destruction and loss of our ecology, our livelihood expectations, and practices, and, in turn, our wellbeing and health. Most problematic has been the domination, skewing and loss of biomass caused by humans, both their over-population of the earth, and their exploitation of its natural resources. These resources provide fuel for warmth, cooking and transport, textiles, and clothing; are subject to land and aquatic harvest, are replaced by dwellings and infrastructural buildings, and yet are recreational assets. Wastage has been of scant regard. Energy misuse besets the entire food system. This has followed the development of the wood and coal-fired steam engine, the advent of gasoline powered internal combustion engines, use and transmission of electricity, and an insatiable arms industry. Now, we are at the brink of extinction. Profiteering and conflict over energy control has fostered unfettered industrial materialism, a major extinction risk factor. Not only is energy the power we need, but it has also underwritten the powerful. Can we be sufficiently insightful and collaborative to change this energy trajectory and survive healthfully on a habitable planet? Individuals, households, and communities, as opposed to unaccountable monopolies, could achieve control of the energy systems on which our livelihoods depend and render them sustainable, accessible, and affordable. Interconnected food and energy system ownership could be devolved to ‘The Commons’ as a cooperative, sustainability strategy. The social momentum and appropriate technology for energy conservation, renewability and personalisation is now available for mobilisation to address our food, nutrition, and health insecurity.

Modeling and assessment of operation economic benefits for hydronic snow melting pavement system

Hydronic snow melting pavement systems have been proposed as an energy conservation technology for pavement snow removal in response to global climate change. However, the quantification of these systems’ economic benefits remains unclear, and their operational decision-making does not consider the economic cost. This study proposes a novel method for calculating the hydronic snow melting pavement system’s economic cost and investigating the economic benefit evolution. A 2D thermo-economic model is developed. Measured data from the Beijing Daxing International Airport are utilized to validate the accuracy of the model, and the economic cost temporal variation under given snowfall conditions is demonstrated. Moreover, an extensive parametric analysis of economic cost is conducted, and sensitive parameters are identified. Then, a real operation case study under a comprehensive scenario is presented. Results show that economic cost can be divided into rapid reduction period (RRP) and stable period (SP). Fluid temperature can affect economic cost with a high fluid temperature resulting in a high economic cost in SP and a prolonged RRP. In the case study, the operation method with 0 h idling time can improve the snow melting performance and increase the economic cost by 7% compared with the method of opening after snowfall. The method with 3 h idling time can achieve optimal snow melting performance. However, its economic cost is 32 % higher than that of the method with 0 h idling time. Furthermore, staged heating method can reduce the economic cost by 7.9 % relative to constant heating method, thus providing an alternative cost-efficient solution.

Identifying Opportunities and Priorities for Energy Extension

An online survey was administered to all educators and specialists within the University of Maryland Extension to assess client-driven opportunities and priorities for energy-related programming, while in-service training evaluations were used to further assess programmatic needs. Results indicate the need for information related to energy conservation and clean energy technology for agricultural and residential clientele. Primary barriers were perceived as the insufficient understanding and high costs associated with clean energy, while experiential participation and firsthand observation were reported as preferred learning methods. These results provide an understanding of how energy-related programming can expand the role and relevancy of Extension.

Energy Conservation (EC) and Emission Reduction (ER) Technology Based on Genetic Algorithm (GA)

Energy Conservation (EC) and Emission Reduction (ER) Technology Based on Genetic Algorithm (GA)

Modeling the magnetic cooling efficiency of spinel ferrite magnetocaloric compounds for magnetic refrigeration application using hybrid intelligent computational methods

Spinel ferrite exhibits large magnetocaloric effect that promotes its candidature for solid state magnetic refrigeration technology. This method of cooling is promising and can conveniently replace the gas-compression method of refrigeration due to its energy saving capacity and ecological cleanliness. Among the available magnetocaloric materials, spinel ferrite metal oxide enjoys low production cost, non-toxicity, ease of preparation and non-oxidative. However, effective utilization of this magnetocaloric material for cooling technology requires determination of its magnetic cooling efficiency which is subjected to time consuming, intensive and laborious experimental procedures. This work employs the applied magnetic field, ionic radii and the concentrations of spinel ferrite constituents to develop a genetically hybridized support vector regression model (G-SVR) and extreme learning machine (ELM) intelligent model for determining magnetic cooling efficiency of spinel ferrite compounds. The developed G-SVR model outperforms ELM model for the testing set of spinel ferrite samples with percentage improvement of 60.57%, 19.69% and 64.73% using root mean square error, correlation coefficient and mean absolute error respectively, as performance measuring parameters. Influence of metal ions such as zinc, nickel and cadmium on magnetic cooling efficiency of various kinds of spinel ferrite compounds was investigated using the developed models. The presented intelligent approaches for spinel ferrite magnetic cooling efficiency determination in this work, with characteristic lower cost, quickness, effectiveness and precision would definitely facilitate and strengthen practical implementation of magnetic refrigeration technology for energy conservation and environmental friendliness.

Research on energy conservation and carbon emission reduction effects and mechanism: Quasi-experimental evidence from China

This paper aims to identify three batches of low-carbon city pilot (LCCP) policy on energy conservation and carbon emission reduction. Specifically, we first innovatively develop a theoretical model incorporating energy conservation and emission reduction technologies, industrial structure adjustment, and government environmental regulation into the traditional pollution emission model. Furthermore, we provide quasi-experimental evidence using a city-panel dataset from China for 2003–2017. Specifically, we adopt the time-varying difference-in-difference model to examine the mechanism of how LCCP policy affects energy conservation and carbon emission reduction through various channels. The results show that the implementation of LCCP led to a significant decrease in energy intensity and carbon emission intensity of the pilot cities. This conclusion is tested by placebo and endogeneity, and it is robust under multiple scenarios. We find that LCCP policy had a heterogeneous impact on different resource types, including the proportion of the secondary industry, financial support, and the city administrative level. The mechanism shows that the city’s innovation, industrial structure, and regulatory effect are important influencing channels. Our findings also indicate that LCCP policy has a positive spatial spillover effect, promoting energy and carbon reduction in neighboring cities.

SUSTAINABLE SUPPLY CHAIN MANAGEMENT IN CONSTRUCTION: AN EXPLORATORY REVIEW FOR FUTURE RESEARCH

Although the importance of supply chain management in the construction sector has been recognized in recent years, its implementation still faces significant challenges. For the long-term evaluation of this creative sector, numerous intricate sustainability components, such as environmental, social, and financial, are necessary. The study focuses on longterm sustainability considerations in the supply chain in the construction sector. This work aims to address this information and examine sustainable supply chain management (SSCM) research in the construction sector in this manner. More than 95 publications were studied from the beginning of 2017 to the end of 2021 using both in-depth content analysis and bibliometric methodologies. Several issues of SSCM in construction have been found including environmental, economic and social patterns which are most commonly known as the triple bottom line, typically enhanced by artificial intelligence. Many challenges were discovered including inefficiencies in the logistics system and a shortage of funding, environmental issues in demolition procedures and difficulties in applying sustainability measures due to high skill, data, and time requirements. The article offers a broad list of potentials for improving the current situation in the construction sector by using various types of supply chains such as increasing investment in energy conservation and emission reduction technologies to drive sustainable development, establishing strong green supply chain relationships, and forming a Covid-19 financial support group for small construction companies among other things. The study’s findings suggested that due to the significance of long-term relationships between construction companies, suppliers and customers, smart technology could make it simpler to reach every supply chain link. After an exhaustive literature review 59 research questions were formulated for the future research. In the future, the importance of these questions could be determined using expert questionnaires and multi-criteria evaluation.

Blue sky defense in low-carbon pilot cities: A spatial spillover perspective of carbon emission efficiency

The improvement of carbon emission efficiency is crucial to the realization of the global carbon peaking and carbon neutrality goals. Based on the panel data of 282 cities from 2004 to 2018 in China, this paper employs the stochastic frontier analysis approach combined with the Sheppard distance function to calculate the total factor carbon emission efficiency of each city. Regarding the low-carbon pilot city policy as a quasi-natural experiment, we evaluate the impact of the pilot policy on carbon emission efficiency and its spatial spillover effect using the spatial difference-in-differences model. The results show that the pilot policy can significantly improve the carbon emission efficiency and has long-term dynamic effects. Also, the effect of the policy has spatial spillover, and has a positive impact on the neighboring cities. Mechanism analysis implies that optimal allocation of resources, energy conservation and green technology innovation make the low-carbon policy play an important intermediary role in promoting carbon emission efficiency. Besides, the effects of the pilot policy have obvious heterogeneity, especially cities in large, higher population densities and the north. These findings reveal that low-carbon pilot city policies are indispensable for both implementing the dual-carbon strategy and winning the defense for the blue sky.

Study on the applicable technology of energy saving in rural residential buildings

In China，with the continuous development of the economic form and the increasing improvement of people's living standards, more and more people believe that housing research is a necessary way to improve residential happines［1］.Therefore, from the perspective of energy conservation, the research on the applicable technology of energy conservation about rural residential buildings in China mainly includes the current situation of rural residential buildings in China, the existing problems in energy conservation and the insulation of rural residential buildings, as well as the advantages and disadvantages of some applicable technologies and various technologies. This paper also analyzes the climate conditions and architectural features of different regions, and then puts forward relevant suggestions and prospects.

Analysis of Pakistan's electricity generation and CO2 emissions: Based on decomposition and decoupling approach

Electricity consumption plays an imperative role in the rising economy and carbon dioxide equivalent (CO 2eq ) emissions in Pakistan. This study employs the decomposition and decoupling methods in driving factors of CO 2es from electricity generation for the years 1990–2019. The study investigates the key driving factors in three ways: first, the study measures the CO 2eq emission from the electricity sector using the logarithmic mean Divisia index (LMDI) between population, activity, electricity intensity, total electricity, electricity generation structure, energy efficiency, and fuel emission factor effect. Second, Tapio's decoupling index method is employed to analyze the association between electricity CO 2eq emission and economic growth over the study period. Third, decoupling indexes of each factor are analyzed for future policies and sustainable growth. The results show that (1) the activity effect and the population is the key driving factors in rising CO 2eq emission by the contribution of trade and generation structure effect. (2) The decoupling states showed the five decoupling states using the effects of electricity CO 2eq emission and economy, presenting weak decoupling in the current period. (3) Each factor's decoupling states presents the long-run instability and relationship among them. Consequently, fossil fuel consumption in Pakistan should concentrate on promoting energy-conserving technology and industrial structure adjustment.

Impact of Energy Efficient Technologies Combined with Solar Roof Top MPPT Control Towards Achieving Sustainable Development in Indian Household

The primary energy demand in India is expected to increase about 1250 to 1500 million toe(tonne of oil equivalent) in 2030.As a result of increasing incomes and growth in economy, energy demand increases electric energy utility services in lighting, space cooling, industrial production, office automation etc. In 2011, annual average supply was only 0.6 toe per capita; whereas the world average was 1.88 toe per capita. To cater the energy demand with minimum CO2 emissions, two prolonged approach is employed. In the generation side, use of renewable such as solar and wind are promoted. In the customer end, a number of policy measures innovatively taken under Energy Conservation Act 2001.This paper analysis the impact of energy conservation technologies and along with the implementation of Solar Photovoltaic MPPT on the roof top of the Indian household. This combined approach will reduce grid dependency of Indian household and thereby minimizing the peak demand on utility.

Analysis of Energy Conservation and Environmental Protection Technology in Civil Engineering Construction

Analysis of Energy Conservation and Environmental Protection Technology in Civil Engineering Construction

Carbon neutral and techno-economic analysis for sewage treatment plants

Sewage treatment plants consume great lots of power and result in a large amount of indirect carbon dioxide emissions. Four typical energy conservation and emission reduction technologies were selected for sewage treatment plants, included reclaimed water source heat pump for heating, reclaimed water source heat pump for sludge drying, sludge anaerobic digestion technology with a biogas cogeneration system and photovoltaic power generation. The carbon neutral, energy and economic analysis model were established for the four typical technologies. The results show that reclaimed water source heat pump can achieve a higher carbon neutrality effect than sludge anaerobic digestion technology with a biogas cogeneration system. The reclaimed water source heat pump for sludge drying can recover a large amount of waste heat. The payback period of photovoltaic power generation is more sensitive to the electricity price changes, while reclaimed water source heat pump for heating is more sensitive to the heat price changes. From the discussion, Z-value have a greater effect on the reclaimed water source heat pump for heating. With the treatment load of the sewage plants increases, the reclaimed water source heat pump can achieve a higher carbon neutrality effect. The application of photovoltaic power generation needs to consider the geographical location, and it can achieve higher carbon neutral efficiency in rich solar energy resources areas. A combined district heating method with reclaimed water source heat pump is proposed to expand the district heating radius of the reclaimed water source heat pump, and improve waste heat recovery efficiency in sewage. • Green technology for sewage treatment plants are studied by carbon neutral, energy and economic analysis. • Multi-factor and sensitivity analysis of technical methods are established. • Sludge drying is a better technical route in sewage treatment plants.

When Energy Efficiency Begets Air Pollution: Fuel Conservation in Japan's Steel Industry, 1945-60.

Between 1945 and 1960, Japan had some of the most energy-efficient iron and steel industries in the world. Two technologies-heat management and oxygen steelmaking-were key enablers of significant energy conservation, an industrial success story commonly attributed to Japan's post-World War II development. Contrary to current understanding, both technologies had deep pre-World War II roots. Their development accelerated after the war through institutionalized exchanges of experience and expertise among Japanese companies. However, these energy conservation technologies had unintended and little-known consequences: they were a major source of air pollution. This article provides two correctives. First, energy conservation technologies took longer to develop than previously thought. Second, saving energy can dramatically increase an industry's environmental footprint. Japan's industrial experience provides an example of how the road to air pollution hell was paved with the best energy conservation intentions.

Assessment of energy conservation potential and cost in open-pit metal mines: Bottom-up approach integrated energy conservation supply curve and ultimate pit limit

Mitigating energy consumption and greenhouse gas (GHG) emissions in the metal mining industry heavily depends on the employment of energy conservation technologies in each individual metal mine. However, predicting the energy conservation potential and associated cost for a specific mine is difficult, especially considering the interaction between technology employment and open-pit limit variation. Therefore, this study integrates the conventional energy conservation-supply-curve (CSC) approach with the ultimate-pit-limit (UPL) analysis in the estimation of energy conservation potential and cost due to technology application. The results from the case study show that conventional CSC analysis provides overestimated potential with underestimated cost under market-based promotion policy. On the other hand, a target-responsibility-system-based (TRS-based) provides underestimated potential with overestimated cost. Sensitivity analysis shows that energy price has the largest impact on the energy conservation potential and associated cost. The policies that raise energy and carbon prices contribute not only to mitigating energy consumption, but also to reducing associated costs, even though they are accompanied by a reduction in mineral supply. This study suggests that the policy that subsidizes conserved energy should be integrated with a TRS-based policy to mitigate the elimination of energy conservation potential due to expansion of the open-pit limit.

Gender Aspects Influencing Adoption of Bioenergy Conservation Technologies, the Case Lower Eastern Kenya

This paper examines the influence of gender in adoption of biomass energy conservation in Eastern Kenya. The region suffers deforestation, environmental degradation and threatened species as result of overexploitation of tree resources for woodfuel production. The government of Kenya and development partners has developed and promoted energy conservation technologies in the region for increased access to sustainable energy resources in rural areas geared towards achievement of sustainable development goals (SDGs) relating to increased access to clean and affordable energy, the eradication of poverty and environmental sustainability, climate action as well as gender equality and the empowerment of women. Despite these efforts, adoption and continued use of improved bioenergy technologies has been low. The objective of the study was to determine gender aspects influencing adoption of biomass energy conservation technologies at household and community levels. The study was carried out in selected sub-counties of Kitui County using a survey design. Structured questionnaire and thematic guidelinesfor group discussions were used to collect data from 192 respondents. SPSS and Excel were used for data analysis. Results revealed that, at 0.05% level of significance, adoption of improved technologies were positively correlated to income and awareness levels. Inadequate awareness on benefits of improved bioenergy technologies among men, biased resource ownership, cultural roles and responsibilities, lack of inclusive decision making and over dependence on men and subsistence farming for financial support by women were indicated as key factors influencing adoption of improved technologies. The study concludes that though women are culturally responsible for provision of food and cooking energy, high poverty among women, and lack of awareness on the socio-economic benefits among men affects adoption of improved bioenergy technologies. The study recommends financial empowerment of women, inclusive decision making and mainstreaming gender at all levels of project implementation for increased adoption of new technologies.