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.

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.

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.

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.

Analysis on Carbon Emissions from Energy Consumption in Agriculture and Reduction Measures in Guangdong Province

[Objective] The aim was to study CO2 emissions from energy consumption in agricultural production in Guangdong Province and put forward feasible reduction measures.[Method] Based on the data from China Energy Statistical Yearbook and Guangdong Statistical Yearbook,CO2 emissions from agricultural energy use in Guangdong Province from 2000 to 2009 was estimated by using the formula of carbon emissions recommended by Intergovernmental Panel on Climate Change (IPCC),and corresponding reduction measures were put forward.[Result] With the rapid increase of agricultural output and energy consumption,CO2 emissions from energy consumption in agricultural production in Guangdong Province showed increasing trend from 2000 to 2009,that is to say,increasing from 423.63×104 t C million tons in 2000 to 605.99×104 t C in 2009,with annual growth rate of 4.1%.Meanwhile,carbon emissions intensity during energy consumption in agriculture went down in recent ten years,in other words,decreasing from 0.424 t C/×104 yuan in 2000 to 0.301 t C/×104 yuan in 2009,and its annual decreasing rate was 3.7%.The variation of CO2 emissions from energy consumption in agriculture mainly resulted from the increase of agricultural output,improvement of energy utilization efficiency,high carbonization in agricultural energy consumption structure and so forth.Therefore,in order to reduce CO2 emissions from energy consumption in agriculture,it is necessary to vigorously develop rural renewable energy,develop and popularize advanced technology for energy utilization,advance the energy conservation of agricultural machines,establish and improve the macroeconomic control mechanism for carbon emissions from the energy consumption in agricultural production in the further.[Conclusion] The study could provide references for the establishment of policy about reducing carbon emissions from agricultural energy consumption in Guangdong Province.

Comparison of Energy Consumption of the 12 Classroom Typical School Buildings in Selected 4 City in Turkey

School is a special place where students come together to become productive individuals of society,acquire basic skills and acquire citizenship knowledge.With the introduction of the new education system(4+4+4)in Turkey in 2012-2013,some difficulties occurred in the spatial structure of the schools.After the new system,increasing number of students and decreasing student requirements have been tried to be solved with temporary solutions.At the same time that millions of students studying in primary schools all over Turkey have the same architectural feature as one type of architectural school project,regardless of the geographical and social situation began to be implemented in all parts of the city.Therefore,the increase in consumption varies depending on the geographical reasons where the type projects are implemented.Selected regions of the four thermal zones in Turkey for this research are provided below:1^st Thermal district in Antalya;2^nd Thermal district in Bursa;3^rd Thermal district in Elaz??;4^th Thermal district in Kars.The calculation of the energy consumption created by the above cities by means of BEP-TR program and comparing classes.

Energy-efficient Approach to Minimizing the Energy Consumption in An Extended Job-shop Scheduling Problem

The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production plarming and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed small- and large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.

Energy consumption in rock fragmentation at intermediate strain rate

In order to determine the relationship among energy consumption of rock and its fragmentation, dynamic strength and strain rate, granite, sandstone and limestone specimens were chosen and tested on large-diameter split Hopkinson pressure bar (SHPB) equipment with half-sine waveform loading at the strain rates ranging from 40 to 150 s- 1. With recorded signals, the energy consumption, strain rate and dynamic strength were analyzed. And the fragmentation behaviors of specimens were investigated. The experimental results show that the energy consumption density of rock increases linearly with the total incident energy. The energy consumption density is of an exponent relationship with the average size of rock fragments. The higher the energy consumption density, the more serious the fragmentation, and the better the gradation of fragments. The energy consumption density takes a good logarithm relationship with the dynamic strength of rock. The dynamic strength of rock increases with the increase of strain rate, indicating higher strain rate sensitivity.

Modeling of Energy Consumption and Effluent Quality Using Density Peaks-based Adaptive Fuzzy Neural Network

Modeling of energy consumption(EC) and effluent quality(EQ) are very essential problems that need to be solved for the multiobjective optimal control in the wastewater treatment process(WWTP). To address this issue, a density peaks-based adaptive fuzzy neural network(DP-AFNN) is proposed in this study. To obtain suitable fuzzy rules, a DP-based clustering method is applied to fit the cluster centers to process nonlinearity.The parameters of the extracted fuzzy rules are fine-tuned based on the improved Levenberg-Marquardt algorithm during the training process. Furthermore, the analysis of convergence is performed to guarantee the successful application of the DPAFNN. Finally, the proposed DP-AFNN is utilized to develop the models of EC and EQ in the WWTP. The experimental results show that the proposed DP-AFNN can achieve fast convergence speed and high prediction accuracy in comparison with some existing methods.

A review of China's energy consumption structure and outlook based on a long-range energy alternatives modeling tool

China＇s energy consumption experienced rapid growth over the past three decades, raising great concerns for the future adjustment of China＇s energy consumption structure. This paper first presents the historical evidence on China＇s energy consumption by the fuel types and sectors. Then, by establishing a bottom-up accounting framework and using long-range energy alternatives plan- ning energy modeling tool, the future of China＇s energy consumption structure under three scenarios is forecast. According to the estimates, China＇s total energy con- sumption will increase from 3014 million tonnes oil equivalent （Mtoe） in 2015 to 4470 Mtoe in 2040 under the current policies scenario, 4040 Mtoe in 2040 under the moderate policies scenario and 3320 Mtoe in 2040 under the strong policies scenario, respectively, lower than those of the IEA＇s estimations. In addition, the clean fuels （gas, nuclear and renewables） could be an effective alternative to the conventional fossil fuels （coal and oil） and offer much more potential. Furthermore, the industry sector has much strong reduction potentials than the other sectors. Finally, this paper suggests that the Chinese government should incorporate consideration of adjustment of the energy consumption structure into existing energy policies and measures in the future.

Calculating Method for Influence of Material Flow on Energy Consumption in Steel Manufacturing Process

From the viewpoint of systems energy conservation, the influences of material flow on its energy consumption in a steel manufacturing process is an important subject. The quantitative analysis of the relationship between material flow and the energy intensity is useful to save energy in steel industry. Based on the concept of standard material flow diagram, all possible situations of ferric material flow in steel manufacturing process are analyzed. The expressions of the influence of material flow deviated from standard material flow diagram on energy consumption are put forward.

The relationship between energy consumption and economic growth and the development strategy of a low-carbon economy in Kazakhstan

Fossil energy is the material basis of human survival, economic development and social progress. The relationship between energy consumption and economic growth is becoming increasingly close. However, energy consumption is the major source of greenhouse gases, which can significantly affect the balance of the global ecosystem. It has become the common goal of countries worldwide to address climate change, reduce carbon dioxide emissions, and implement sustainable development strategies. In this study, we applied an approximate relationship analysis, a decoupling relationship analysis, and a trend analysis to explore the relationship between energy consumption and economic growth using data from Kazakhstan for the period of 1993-2010. The results demonstrated： （1） the total energy consumption and GDP in Kazakhstan showed a ＂U＂-type curve from 1993 to 2010. This curve was observed because 1993-1999 was a period during which Kazakhstan transitioned from a republic to an independent country and experienced a difficult transition from a planned to a market economy. Then, the economic system became more stable and the industrial production increased rapidly because of the effective financial, monetary and industrial policy support from 2000 to 2010. （2） The relationships between energy con- sumption and carbon emissions, economic growth and energy exports were linked; the carbon emissions were mainly derived from energy consumption, and the dependence of economic growth on energy exports gradually increased from 1993 to 2010. Before 2000, the relationship between energy consumption and economic growth was in a recessional decoupling state because of the economic recession. After 2000, this relationship was in strong and weak decoupling states because the international crude oil prices rose and energy exports increased greatly year by year. （3） It is forecasted that Kazakhstan cannot achieve its goal of energy consumption by 2020. Therefore, a low-carbon economy is the best strategic choice to address climate change from a global perspective in Kazakhstan. Thus, we proposed strategies including the improvement of the energy consumption structure, the development of new energy and renewable energy, the use of cleaner production technologies, the adjustment and optimization of the industrial structure, and the expansion of forest areas.

Comprehensive optimized GM(1,1) model and application for short term forecasting of Chinese energy consumption and production

In order to improve prediction accuracy of the grey prediction model and forecast China energy consumption and production in a short term, this paper proposes a novel com- prehensively optimized GM（1,1） model, also named COGM（1,1）, based on the grey modeling mechanism. First, the relationship of the background value formula and its whitenization equation is analyzed and a new method optimizing background values is proposed to eliminate systemic errors in the modeling process. Second, the solving process of the new model is derived. For parameter estimation, a set of auxiliary parameters are used to change grey equation＇s form. Then, original parameters are re- stored by an equations system. After solving the whitenization equation, initial value in time response function is established by least errors criteria. Finally, a numerical case and comparison with other grey prediction models are made to testify the new model＇s effectiveness, and the computational results show that the COGM（1,1） model has a better property and achieves higher precision. The new model is used to forecast China energy con- sumption and production, and the ability of energy self-sufficiency is further analyzed. Results indicate that gaps between consump- tion and production in future are predicted to decline.

Analyses of influence of residential buildings' space organization on heating energy consumption in Lhasa

The heating load simulation models of the residential buildings in Lhasa are established for enhancing the space organization’s adaptability to climate and radiation and improving its energy saving performance.The space organization items a e analyzed for both the existing buildings without insulation and new buildings with good insulation.The items include orientation design,south a d north balcony design,the north and south partition wall’s position design,storey height design and window-wall ratio design.Simulation results show that orientation is the key design element for energy saving design,and adverse orientation can obviouslyincrease heating energy consumption;south and north balconies can reduce winter heating energy consumption;partition walls move to the north,which means that the south room’s big depth design leads to less heating energy consumption,but the effect is not inconspicuous;smaier storey height results in less heating load.For the existing buildings,the window-wall ratio of south side has a balance point for energy saving design in the calculation condition.For the new buildings with good insulation,enlarging the south window-wal ratio can continuously reduce heating energy consumption,but the energy saving rate between models gets smaier.The heating energy consumption comparison study between the common model and optimal space design model demonstrates that the energy saving design can significantly reduce heating energy consumption

Energy Consumption in Comminution of Mica with Cavitation Abrasive Water Jet

We have studied the efficiency of energy consumption in the comminution of mica powder with cavitation abrasive water jet technology. The energy required to create new surfaces in the comminution of mica powder with cavitation abrasive water jet was calculated,in order to estimate its efficiency of energy consumption. The particle size distribution and the specific surface area were measured by applying a JEM-200CX transmission electron microscope and an Autosorb-1 automatic surface area analyzer. The study results show that the efficiency of energy consumed in creating new surface areas is as high as 2.92%,or 4.94% with the aid of cavitation in the comminution of mica powder. This efficiency will decrease with an increase in the number of comminutions. After three comminutions,the efficien-cies will become 1.91% and 2.29% for comminution without cavitation and with cavitation,respectively. The abrasive water jet technology is an effective way for comminution of mica powder.

Energy consumption and emission mitigation prediction based on data center traffic and PUE for global data centers

With the rapid development of technologies such as big data and cloud computing,data communication and data computing in the form of exponential growth have led to a large amount of energy consumption in data centers.Globally,data centers will become the world’s largest users of energy consumption,with the ratio rising from 3%in 2017 to 4.5%in 2025.Due to its unique climate and energy-saving advantages,the high-latitude area in the Pan-Arctic region has gradually become a hotspot for data center site selection in recent years.In order to predict and analyze the future energy consumption and carbon emissions of global data centers,this paper presents a new method based on global data center traffic and power usage effectiveness(PUE)for energy consumption prediction.Firstly,global data center traffic growth is predicted based on the Cisco’s research.Secondly,the dynamic global average PUE and the high latitude PUE based on Romonet simulation model are obtained,and then global data center energy consumption with two different scenarios,the decentralized scenario and the centralized scenario,is analyzed quantitatively via the polynomial fitting method.The simulation results show that,in 2030,the global data center energy consumption and carbon emissions are reduced by about 301 billion kWh and 720 million tons CO2 in the centralized scenario compared with that of the decentralized scenario,which confirms that the establishment of data centers in the Pan-Arctic region in the future can effectively relief the climate change and energy problems.This study provides support for global energy consumption prediction,and guidance for the layout of future global data centers from the perspective of energy consumption.Moreover,it provides support of the feasibility of the integration of energy and information networks under the Global Energy Interconnection conception.

Optimized model-based control of main mine ventilation air flows with minimized energy consumption

In early 2018,the Boliden Garpenberg operation implemented an optimized control strategy as an addition to the existing ventilation on demand system.The purpose of the strategy is to further minimize energy use for main and booster fans,whilst also fulfilling airflow setpoints without violating constraints such as min/max differential pressure over fans and interaction of air between areas in mines.Using air flow measurements and a dynamical model of the ventilation system,a mine-wide coordination control of fans can be carried out.The numerical model is data driven and derived from historical operational data or step changes experiments.This makes both initial deployment and lifetime model maintenance,as the mine evolves,a comparably easy operation.The control has been proven to operate in a stable manner over long periods without having to re-calibrate the model.Results prove a 40%decrease in energy use for the fans involved and a greater controllability of air flow.Moreover,a 15%decrease of the total air flow into the mine will give additional proportional heating savings during winter periods.All in all,the multivariable controller shows a correlation between production in the mine and the ventilation system performance superior to all of its predecessors.