Exploring the impact of economic growth and energy consumption on SO_(2) emissions in China based on the Environmental Kuznets Curve hypothesis

This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China over the span of 2000-2019.This study also analyzes cross-sectional dependence tests,panel unit root tests,Westerlund panel cointegration tests,Dumitrescu-Hurlin(D-H)causality tests.According to the test results,there is an inverted U-shaped association between EG and SE,and the assumption of the Environmental Kuznets Curve(EKC)is verified.The signs of EG and EC in the fixed effect(FE)and random effect(RE)methods are in line with those in the dynamic ordinary least squares(DOLS),fully modified ordinary least squares(FMOLS)and autoregressive distributed lag(ARDL)estimators.Moreover,the results verified that EC can obviously positive impact the SE.To reduce SE in China,government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency.This requires the comprehensive use of policies,regulations,economic incentives,and public participation to promote sustainable development.

Analysis of the Energy Efficiency of Diesel Oil Consumption in the Brazilian Iron Ore Mining Company

This paper aims to evaluate the diesel oil consumption between 2008 and 2015 in the production of iron ore in Brazil, creating correlations between energy intensity (production), economy and checking the impact of fuel prices on the commodity. During the analyzed period, the years 2008-2009 indicated economic crises, which interfered in the price and the commercialization of iron ore products. The physical intensity was 0.2% higher than the economic intensity. In the period from 2010 to 2014, economic activity remained more stable, with a decreasing trend, mainly due to the increase of iron ore prices. The physical intensity is much higher than the economic intensity influenced by the expansion of the Chinese economy. The year of 2014 indicated the end of the high iron ore price cycle and the beginning of supply and demand stabilization with consequent reduction in prices. In 2015, the market entered the stabilization phase, with a continuous reduction in unit production costs and transportation logistics. There was an abrupt change due to the strong increase of the economic intensity due to the fall of the international prices of iron ore. The diesel oil consumption plays a vital role in the scenario of cost reduction in iron ore production and a deeper analysis must be done in order to discover some options to change the energy matrix.

Analysis of the Energy and Environmental Sustainability of a Built Space System: The Case of Patte d’Oie University Campus in Ouagadougou

The aim of this study was to carry out a dynamic simulation of the energy and environmental performance of a built space system, with a view to assessing its energy and environmental class. The use of a simulation and modeling tool, supported by various methodological references, formed the basis of our approach. Adopting a systemic perspective, we described the structural and functional aspects of the systems making up built spaces, as well as the associated energy flows. Our approach was also based on a typology, taking into account typical days, structural and functional configurations at different scales and angles of observation. The analysis tool we developed in Java was applied to the built space system of the Patte d’Oie university campus in Ouagadougou. Annual electricity consumption was measured at 124387.34 kWh, closely aligned with the average annual electricity bill (125224.31 kWh), with a maximum relative deviation of 1%, followed by a carbon emission balance of 58337.66 kg eq CO2 per year. This validation confirmed the effectiveness of our tool. In addition, following the analysis of electricity consumption using our tool, the university campus was classified in energy class B and environmental class C. These results will be based on the emission factors of the energy mix of the West African Economic and Monetary Union (WAEMU) territory, with particular emphasis on Burkina Faso.

Transitivity Analysis of the Energy in China’s New Era

At present,with the steady development of the global economy,more and more countries begin to pay attention to the impact of ecological environment on economic development and human society,so the ecological environment has become a global issue that cannot be ignored in today’s era.Therefore,from the perspective of the ecological philosophy of Diversity&Harmony as well as Interaction&Co-existence,this paper will conduct ecological discourse analysis on the Energy in China’s New Era based on the transitivity system of systemic-functional grammar,and use the Corpus analysis software UAM Corpus Tool 3.3x to label and make statistics on the transitivity system,aiming to explore the distribution characteristics of the transitivity system in this white paper.Through the transitivity analysis of the white paper,this study helps readers to have a deeper understanding of the positive significance contained in the white paper.To a certain extent,it enables readers at home and abroad to understand China’s stance on energy issues and the positive image of China in energy ecology.It also awaken readers’awareness of environmental protection and acquire good habits of resource conservation to be in harmony between human and nature for sustainable development.

Energy Consumption Analysis and Characterization of Aerospace Manufacturing Facilities in the United States–A Step towards Sustainable Development

In this study,information on energy usage in the United States(U.S.)aerospace manufacturing sector has been analyzed and then represented as energy intensities(kWh/m2)to establish benchmark data and to compare facilities of varying sizes.First,public sources were identified and the data from these previously published sources were aggregated to determine the energy usage of aerospace manufacturing facilities within the U.S.From this dataset,a sample of 28 buildings were selected and the energy intensity for each building was estimated from the data.Next,as a part of this study the energy data for three additional aerospace manufacturing facilities in the U.S.were collected firsthand.That data was analyzed and the energy intensity(kWh/m2)for each facility was calculated and then compared with the energy intensities of the 28 buildings from the sample.Three different indicators of energy consumption in aerospace manufacturing facilities were used as comparators to assist facility managers with determining potential energy savings and help in the decision-making process.On average,aerospace manufacturing facilities in the United States spent 4 cents for each dollar of sale on energy.The energy intensity(kWh/m2)and the power intensity(W/m2)for each facility were calculated based on the actual facility energy bills.The power intensity for these facilities ranges from 34 to 134 W/m2.The energy intensity ranged from 232 to 949 kWh/m2.We found that the power intensity could be used to estimate energy consumption when the annual operating hours of the facility are considered.and to estimate the energy-related carbon dioxide emissions.

Effects of connected automated vehicle on stability and energy consumption of heterogeneous traffic flow system

With the development of intelligent and interconnected traffic system,a convergence of traffic stream is anticipated in the foreseeable future,where both connected automated vehicle(CAV)and human driven vehicle(HDV)will coexist.In order to examine the effect of CAV on the overall stability and energy consumption of such a heterogeneous traffic system,we first take into account the interrelated perception of distance and speed by CAV to establish a macroscopic dynamic model through utilizing the full velocity difference(FVD)model.Subsequently,adopting the linear stability theory,we propose the linear stability condition for the model through using the small perturbation method,and the validity of the heterogeneous model is verified by comparing with the FVD model.Through nonlinear theoretical analysis,we further derive the KdV-Burgers equation,which captures the propagation characteristics of traffic density waves.Finally,by numerical simulation experiments through utilizing a macroscopic model of heterogeneous traffic flow,the effect of CAV permeability on the stability of density wave in heterogeneous traffic flow and the energy consumption of the traffic system is investigated.Subsequent analysis reveals emergent traffic phenomena.The experimental findings demonstrate that as CAV permeability increases,the ability to dampen the propagation of fluctuations in heterogeneous traffic flow gradually intensifies when giving system perturbation,leading to enhanced stability of the traffic system.Furthermore,higher initial traffic density renders the traffic system more susceptible to congestion,resulting in local clustering effect and stop-and-go traffic phenomenon.Remarkably,the total energy consumption of the heterogeneous traffic system exhibits a gradual decline with CAV permeability increasing.Further evidence has demonstrated the positive influence of CAV on heterogeneous traffic flow.This research contributes to providing theoretical guidance for future CAV applications,aiming to enhance urban road traffic efficiency and alleviate congestion.

Joint Optimization of Energy Consumption and Network Latency in Blockchain-Enabled Fog Computing Networks

Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(IoT)devices.To ensure the security of private data,in this paper,we introduce a blockchain-enabled three-layer device-fog-cloud heterogeneous network.A reputation model is proposed to update the credibility of the fog nodes(FN),which is used to select blockchain nodes(BN)from FNs to participate in the consensus process.According to the Rivest-Shamir-Adleman(RSA)encryption algorithm applied to the blockchain system,FNs could verify the identity of the node through its public key to avoid malicious attacks.Additionally,to reduce the computation complexity of the consensus algorithms and the network overhead,we propose a dynamic offloading and resource allocation(DORA)algorithm and a reputation-based democratic byzantine fault tolerant(R-DBFT)algorithm to optimize the offloading decisions and decrease the number of BNs in the consensus algorithm while ensuring the network security.Simulation results demonstrate that the proposed algorithm could efficiently reduce the network overhead,and obtain a considerable performance improvement compared to the related algorithms in the previous literature.

Optimising Energy Consumption in SD-DCN Networks (Software Defined-Data Center Network)

Over the last decade, the rapid growth in traffic and the number of network devices has implicitly led to an increase in network energy consumption. In this context, a new paradigm has emerged, Software-Defined Networking (SDN), which is an emerging technique that separates the control plane and the data plane of the deployed network, enabling centralized control of the network, while offering flexibility in data center network management. Some research work is moving in the direction of optimizing the energy consumption of SD-DCN, but still does not guarantee good performance and quality of service for SDN networks. To solve this problem, we propose a new mathematical model based on the principle of combinatorial optimization to dynamically solve the problem of activating and deactivating switches and unused links that consume energy in SDN networks while guaranteeing quality of service (QoS) and ensuring load balancing in the network.

Thermal comfort assessment and energy consumption analysis of ground-source heat pump system combined with radiant heating/cooling

A new ground source heat pump system combined with radiant heating/cooling is proposed, and the principles and the advantages of the system are analyzed. A demonstration of the system is applied to a rebuilt building： Xijindu exhibition hall, which is located in Zhenjiang city in China. Numerical studies on the thermal comfort and energy consumption of the system are carded out by using TRNSYS software. The results indicate that the system with the radiant floor method or the radiant ceiling method shows good thermal comfort without mechanical ventilation in winter. However, the system with either of the methods should add mechanical ventilation to ensure good comfort in summer. At the same level of thermal comfort, it can also be found that the annual energy consumption of the radiant ceiling system is less than that of the radiant floor system.

Research on the energy consumption mechanism and characteristics of the gallium indium tin liquid metal arcing process

For high-voltage direct current(HVDC)power grid transmission with higher voltages,the energyconsuming branch of the DC circuit breaker is required to dissipate huge energies of more than megajoules in a short time in the case of a fault and short circuit.The requirements for huge volume and weight are difficult to meet with energy-consuming equipment based on ZnO.In this paper,a new energy consumption method is proposed based on gallium indium tin(GaInSn)liquid metal in the arcing process,and a test platform with adjustable short-circuit current is built.The mechanism triggering GaInSn liquid metal arcing energy consumption is studied.It is found that short-circuit current and channel aperture are the key parameters affecting the energy consumption of liquid metal arcing.The characteristics of GaInSn liquid metal energy consumption are investigated,and four stages of liquid metal energy consumption are found:oscillatory shrinkage,arc breakdown,arc burning phase change and arc extinction.The influence of short-circuit current and channel aperture on the energy consumption characteristics of GaInSn liquid metal is investigated.To further explore the physical mechanism of the above phenomena,a magneto-hydrodynamic model of energy consumption in the GaInSn liquid metal arcing process is established.The influence of short-circuit current and channel aperture on the temperature distribution of the liquid metal arc is analyzed.The mechanism of the effect of short-circuit current and channel aperture on peak arc temperature and the temperature diffusion rate is clarified.The research results provide theoretical support for this new liquid metal energy consumption mode DC circuit breaker.

Optimization of Electricity Purchase and Sales Strategies of Electricity Retailers under the Condition of Limited Clean Energy Consumption

In the process of my country’s energy transition,the clean energy of hydropower,wind power and photovoltaic power generation has ushered in great development,but due to the randomness and volatility of its output,it has caused a certain waste of clean energy power generation resources.Regarding the purchase and sale of electricity by electricity retailers under the condition of limited clean energy consumption,this paper establishes a quantitative model of clean energy restricted electricity fromthe perspective of power system supply and demand balance.Then it analyzes the source-charge dual uncertain factors in the electricity retailer purchasing and selling scenarios in the mid-to long-term electricity market and the day-ahead market.Through the multi-scenario analysis method,the uncertain clean energy consumption and the user’s power demand are combined to form the electricity retailer’s electricity purchase and sales scene,and the typical scene is obtained by using the hierarchical clustering algorithm.This paper establishes a electricity retailer’s risk decisionmodel for purchasing and selling electricity in themid-and long-term market and reduce-abandonment market,and takes the maximum profit expectation of the electricity retailer frompurchasing and selling electricity as the objective function.At the same time,in themediumand longterm electricity market and the day-ahead market,the electricity retailer’s purchase cost,electricity sales income,deviation assessment cost and electricity purchase and sale risk are considered.The molecular results show that electricity retailers can obtain considerable profits in the reduce-abandonment market by optimizing their own electricity purchase and sales strategies,on the premise of balancing profits and risks.

Energy Consumption Analysis and Optimization of Electric Submersible Pump System

Electric submersible pumps account for a considerable proportion in the development of the Bohai Oilfield. Improving the system efficiency of the electric submersible pump wells, ensuring that the units operate in the high-efficiency zone, is essential. Analysis shows that the efficiency of the electric submersible pump system depends on the wear and tear of each component of the submersible pump equipment, the setting of operational parameters, and more importantly, the production status and daily management level of the oil well. Therefore, improving the structural performance of the submersible pump product, optimizing the parameters setting of the oil well, strengthening daily management, establishing a scientific management system, and improving the production management process and system can effectively improve the production efficiency and economic benefits of the oil well, and further achieve the goal of energy saving and emission reduction. In addition, it is necessary to actively promote the concept and technology of energy saving and emission reduction, encourage oilfield enterprises to explore effective measures to reduce the energy consumption of the electric submersible pump system by strengthening the scientific management system, and achieve a green, low-carbon, and high-quality development of oilfield production to achieve the unity of economic benefits, social benefits, and environmental benefits. This article applies the above measures in the P oilfield to achieve energy optimization of submersible electric pump systems, reducing the daily power consumption of single well submersible electric pump systems by 371 kWh per day, increasing the submersible electric pump's lifespan by 200 days, generating considerable project benefits.

Study on the Principle Model and Simplification of Subway Station Itemized Energy Consumption

Owing to the constant modernization and urbanization of China,most cities have subways,and the total power consumption of subway stations has been rising,which contradicts with China’s green goals.In this regard,energy consumption indicators for major energy use projects in subway stations should be established,comprehensive evaluation and detailed research on the current situation of subway operation should be conducted,and specific energy-saving measures should be taken from a diversified perspective.It is crucial to systematically sort out the principle of sub-item energy consumption in subway stations,and practice and explore the specific simplification measures of the principle model of sub-item energy consumption,so as to lay a solid foundation for achieving the goal of reducing energy consumption of subway stations.

Analysis of Energy Consumption and Energy Conservation Measures for RFCCU at Shengli Petrochemical Company

This article introduces a string of energy conservation measures adopted over the past sev- eral years by the RFCC unit at Shengli Petrochemical Complex, including the optimization of feedstock properties, the adoption of high-efficiency atomizing nozzles, the revamp of CO boiler, the atomization by means of dry gas, the post-burning of flue gas as well as the application of frequency converting machines and pumps, resulting in ideal effects. The energy consumption of the RFCC unit was gradually decreased to 2984.25 MJ/t from the original level of 3716.99 MJ/t. After comparing basic energy con- sumption values with actual consumption values, the authors have set forward measures for further energy conservation, such as the recovery of low-temperature excess heat contained in oil/gas streams exiting from the fractionation tower top, addition of the fourth cyclone, delivery of hot oil slurry, and heat tracing with hot water.

Analysis on the Change Characteristics of the Correlation between Land Use Structure and Energy Consumption and Carbon Emissions in Kunming from 1997 to 2017

This study takes Kunming City, Yunnan Province, China as the research area, to provide reference basis for revealing the change law of land use structure and energy consumption and carbon emissions in Kunming, optimizing land use structure and realizing the development of low-carbon city. Based on the data of land use structure and energy consumption in Kunming from 1997 to 2017, based on the estimation of total energy consumption carbon emissions, carbon intensity and per capita carbon emissions, the correlation between land use structure and energy consumption carbon emissions in Kunming has been calculated and analyzed in the past 20 years. Results: 1) The total amount of carbon emissions in Kunming has increased significantly in the past 20 years. It increased from 34.46 × 105 t to 95.09 × 105 t, an increase of about 2.8 times. 2) The types of land use with the highest correlation between land use structure and total carbon emissions of energy consumption, carbon emission intensity and per capita carbon emissions are urban and village and industrial and mining land (0.8258), cultivated land (0.8733) and garden land (0.7971) respectively. 3) The correlation between construction land and total carbon emissions is greater than that of agricultural land. Conclusion: There is a close correlation between land use structure and carbon emissions from energy consumption in Kunming.

NeTrainSim:a network-level simulator for modeling freight train longitudinal motion and energy consumption

Although train modeling research is vast, most available simulation tools are confined to city-or trip-scale analysis, primarily offering micro-level simulations of network segments. This paper addresses this void by developing the Ne Train Sim simulator for heavy long-haul freight trains on a network of multiple intersecting tracks. The main objective of this simulator is to enable a comprehensive analysis of energy consumption and the associated carbon footprint for the entire train system. Four case studies were conducted to demonstrate the simulator's performance. The first case study validates the model by comparing Ne Train Sim output to empirical trajectory data. The results demonstrate that the simulated trajectory is precise enough to estimate the train energy consumption and carbon dioxide emissions. The second application demonstrates the train-following model considering six trains following each other. The results showcase the model ability to maintain safefollowing distances between successive trains. The next study highlights the simulator's ability to resolve train conflicts for different scenarios. Finally, the suitability of the Ne Train Sim for modeling realistic railroad networks is verified through the modeling of the entire US network and comparing alternative powertrains on the fleet energy consumption.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

Comparative Study on Energy Consumption Structure of Ordinary Rural Households and Rural Tourism Households in Zhejiang Province, China

With the rapid development of rural tourism in China, more and more rural households operate a rural tourism business. The purpose of this study is to understand the energy consumption characteristic of ordinary rural households (ORHs) and rural tourism households (RTHs) in the mountainous area and islands area in Zhejiang province. 225 households were surveyed, including 185 ORHs and 40 RTHs, based on a field survey in Quzhou (mountainous area) and Zhoushan (islands area). Results reveal that energy consumption of ORHs is low, but energy comsumption of RTHs is high, about 3 to 5 times higher than that of ORHs. Given the results, the government and RTHs should pay more attention to take measures to reduce energy comsumption. Meanwhile, the factors affecting households’ energy consumption are also analyzed. Energy consumption of ORHs is affected by frequently used area, family income level and permanent population. Then energy consumption of RTHs is mainly related to the total building area, number of air conditioner (AC), number of guestrooms and family income level.

Economic feasibility and efficiency enhancement approaches for in situ upgrading of low-maturity organic-rich shale from an energy consumption ratio perspective

The technical feasibility of in situ upgrading technology to develop the enormous oil and gas resource potential in low-maturity shale is widely acknowledged.However,because of the large quantities of energy required to heat shale,its economic feasibility is still a matter of debate and has yet to be convincingly demonstrated quantitatively.Based on the energy conservation law,the energy acquisition of oil and gas generation and the energy consumption of organic matter cracking,shale heat-absorption,and surrounding rock heat dissipation during in situ heating were evaluated in this study.The energy consumption ratios for different conditions were determined,and the factors that influence them were analyzed.The results show that the energy consumption ratio increases rapidly with increasing total organic carbon(TOC)content.For oil-prone shales,the TOC content corresponding to an energy consumption ratio of 3 is approximately 4.2%.This indicates that shale with a high TOC content can be expected to reduce the project cost through large-scale operation,making the energy consumption ratio after consideration of the project cost greater than 1.In situ heating and upgrading technology can achieve economic benefits.The main methods for improving the economic feasibility by analyzing factors that influence the energy consumption ratio include the following:(1)exploring technologies that efficiently heat shale but reduce the heat dissipation of surrounding rocks,(2)exploring technologies for efficient transformation of organic matter into oil and gas,i.e.,exploring technologies with catalytic effects,or the capability to reduce in situ heating time,and(3)establishing a horizontal well deployment technology that comprehensively considers the energy consumption ratio,time cost,and engineering cost.

Deep Learning Based Energy Consumption Prediction on Internet of Things Environment

The creation of national energy strategy cannot proceed without accurate projections of future electricity consumption;this is because EC is intimately tied to other forms of energy,such as oil and natural gas.For the purpose of determining and bettering overall energy consumption,there is an urgent requirement for accurate monitoring and calculation of EC at the building level using cutting-edge technology such as data analytics and the internet of things(IoT).Soft computing is a subset of AI that tries to design procedures that are more accurate and reliable,and it has proven to be an effective tool for solving a number of issues that are associated with the use of energy.The use of soft computing for energy prediction is an essential part of the solution to these kinds of challenges.This study presents an improved version of the Harris Hawks Optimization model by combining it with the IHHODL-ECP algorithm for use in Internet of Things settings.The IHHODL-ECP model that has been supplied acts as a useful instrument for the prediction of integrated energy consumption.In order for the raw electrical data to be compatible with the subsequent processing in the IHHODL-ECP model,it is necessary to perform a preprocessing step.The technique of prediction uses a combination of three different kinds of deep learning models,namely DNN,GRU,and DBN.In addition to this,the IHHO algorithm is used as a technique for making adjustments to the hyperparameters.The experimental result analysis of the IHHODL-ECP model is carried out under a variety of different aspects,and the comparison inquiry highlighted the advantages of the IHHODL-ECP model over other present approaches.According to the findings of the experiments conducted with an hourly time resolution,the IHHODL-ECP model obtained a MAPE value of 33.85,which was lower than those produced by the LR,LSTM,and CNN-LSTM models,which had MAPE values of 83.22,44.57,and 34.62 respectively.These findings provided evidence of the IHHODL-ECP model’s improved ability to provide accurate forecasts.