Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

Enhancing the crystallinity and stability of perovskite solar cells with 4-tert-butylpyridine induction for efficiency exceeding 24%

Perovskite solar cells(PSCs)have emerged as a promising photovoltaic technology because of their high light absorption coefficient,long carrier diffusion distance,and tunable bandgap.However,PSCs face challenges such as hysteresis effects and stability issues.In this study,we introduced a novel approach to improve film crystallization by leveraging 4-tert-butylpyridine(TBP)molecules,thereby enhancing the performance and stability of PSCs.Our findings demonstrate the effective removal of PbI_(2)from the perovskite surface through strong coordination with TBP molecules.Additionally,by carefully adjusting the concentration of the TBP solution,we achieved enhanced film crystallinity without disrupting the perovskite structure.The TBP-treated perovskite films exhibit a low defect density,improved crystallinity,and improved carrier lifetime.As a result,the PSCs manufactured with TBP treatment achieve power conversion efficiency(PCE)exceeding 24%.Moreover,we obtained the PCE of 21.39%for the 12.25 cm^(2)module.

Cooperative activation of sodium channels for downgrading the energy efficiency in neuronal information processing

The Hodgkin–Huxley model assumes independent ion channel activation,although mutual interactions are common in biological systems.This raises the problem why neurons would favor independent over cooperative channel activation.In this study,we evaluate how cooperative activation of sodium channels affects the neuron’s information processing and energy consumption.Simulations of the stochastic Hodgkin–Huxley model with cooperative activation of sodium channels show that,while cooperative activation enhances neuronal information processing capacity,it greatly increases the neuron’s energy consumption.As a result,cooperative activation of sodium channel degrades the energy efficiency for neuronal information processing.This discovery improves our understanding of the design principles for neural systems,and may provide insights into future designs of the neuromorphic computing devices as well as systematic understanding of pathological mechanisms for neural diseases.

Reinforcement Learning Model for Energy System Management to Ensure Energy Efficiency and Comfort in Buildings

This article focuses on the challenges ofmodeling energy supply systems for buildings,encompassing both methods and tools for simulating thermal regimes and engineering systems within buildings.Enhancing the comfort of living or working in buildings often necessitates increased consumption of energy and material,such as for thermal upgrades,which consequently incurs additional economic costs.It is crucial to acknowledge that such improvements do not always lead to a decrease in total pollutant emissions,considering emissions across all stages of production and usage of energy and materials aimed at boosting energy efficiency and comfort in buildings.In addition,it explores the methods and mechanisms for modeling the operating modes of electric boilers used to collectively improve energy efficiency and indoor climatic conditions.Using the developed mathematical models,the study examines the dynamic states of building energy supply systems and provides recommendations for improving their efficiency.These dynamic models are executed in software environments such as MATLAB/Simscape and Python,where the component detailing schemes for various types of controllers are demonstrated.Additionally,controllers based on reinforcement learning(RL)displayed more adaptive load level management.These RL-based controllers can lower instantaneous power usage by up to 35%,reduce absolute deviations from a comfortable temperature nearly by half,and cut down energy consumption by approximately 1%while maintaining comfort.When the energy source produces a constant energy amount,the RL-based heat controllermore effectively maintains the temperature within the set range,preventing overheating.In conclusion,the introduced energydynamic building model and its software implementation offer a versatile tool for researchers,enabling the simulation of various energy supply systems to achieve optimal energy efficiency and indoor climate control in buildings.

Effect of building energy efficiency standards on carbon emission efficiency in commercial buildings

The building sector plays a crucial role in the worldwide shift toward achieving net-zero emissions.Building energy efficiency standards(BEESs)are highly effective policies for reducing carbon emissions.Therefore,exploring the provincial variations in carbon emission efficiency(CEE)in the building sector and identifying the effect of BEESs on CEE is crucial.This study focuses on commercial buildings in China and applies a difference in differences model to evaluate the impact of BEESs on the CEE of commercial buildings.The slacks-based measure–data envelopment analysis model is employed to assess the CEE of commercial buildings in 30 Chinese provinces from 2000 to 2019.Furthermore,heterogeneous tests are used to explore how climate characteristics and economic conditions affect the efficiency of BEESs.The results indicate that BEESs positively influence the CEE of commercial buildings.Specifically,a 1%increase in the intensity of BEESs causes a 0.1484%increase in the CEE of commercial buildings.Moreover,the impact of BEESs is particularly pronounced in the southern and western provinces.This study provides valuable scientific evidence for governments to enhance BEESs implementation.

Spatiotemporal variations,influencing factors,and configurational promotion paths of energy efficiency in China’s cities

The promotion of energy efficiency(EE)helps address energy constraints and promote environmental sustainability.This study comprehensively explores the spatiotemporal variations,influencing factors,and configuration promotion paths of EE in 284 Chinese cities during 2003‒2019 using the global super-efficiency minimum distance to strong efficient frontier(G-S-MinDS),exploratory spatial data analysis(ESDA),multiscale geographically weighted regression(MGWR),and fuzzy set qualitative comparative analysis(fsQCA)methods.The findings are:①China’s cities have an annual average EE of 0.658 with a growth rate of 0.53%,showing considerable promotion potential.②Industrial structure optimization,population agglomeration,economic development,and increased green coverage contribute positively,while government intervention and openness hinder China’s urban EE.③Four configurational promotion paths for enhancing China’s urban EE are identified,where among those paths population density is a core condition,while government intervention is not.This study provides valuable insights into substantially improving urban EE,emphasizing the need for targeted policies to address energy and environmental crises in China.

Do smart city policies improve energy efficiency?Evidence from China

To address air pollution and offer a convenient and comfortable living environment,the Chinese government launched a smart city pilot(SCP)project in 2012,accompanied by a comprehensive set of environmental and energy-related laws and regulations.Although academic interest in smart cities has surged,there remains a notable gap in empirical research exploring the economic,environmental,and energy effects of such initiatives.Taking 232 prefecture-level cities from 2003 to 2017 as research subjects,this study measures energy effi‐ciency by using energy consumption per unit of GDP and adopts a difference-in-differences(DID)analysis to investigate the impact of SCPs on energy efficiency.The empirical results indicate that SCPs improved energy efficiency by promoting urban technological innovation capabilities and green total factor productivity,and this effect was more pronounced in cities that were more dependent on traditional fossil fuel energy sources and had more developed fiscal and financial levels.Studying the impact of smart city construction on energy utilization efficiency in developing countries,such as China,is not only significantly enlightening for China’s green and low-carbon transition but also provides reference opinions for constructing smart cities and the path to enhancing energy efficiency in other developing countries.The findings provide valuable insights into the global development of smart cities,urban sustainability,and high-quality economic growth.

Energy efficiency aware dynamic rate and power adaptation in carrier sensing based WLANs under Rayleigh fading and shadowing

We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and transmission power of the users in carrier sensing based Wireless Local Area Networks(WLANs)in the presence of path loss,Rayleigh fading and log-normal shadowing.For a data packet transmission,we formulate an optimization problem,solve the problem,and propose a rate and transmission power adaptation scheme with a restriction methodology of data packet transmission for achieving the optimal energy efficiency.In the restriction methodology of data packet transmission,a user does not transmit a data packet if the instantaneous channel gain of the user is lower than a threshold.To evaluate the performance of the proposed scheme,we develop analytical models for computing the throughput and energy efficiency of WLANs under the proposed scheme considering a saturation traffic condition.We then validate the analytical models via simulation.We find that the proposed scheme provides better throughput and energy efficiency with acceptable throughput fairness if the restriction methodology of data packet transmission is included.By means of the analytical models and simulations,we demonstrate that the proposed scheme provides significantly higher throughput,energy efficiency and fairness index than a traditional non-adaptive scheme and an existing most relevant adaptive scheme.Throughput and energy efficiency gains obtained by the proposed scheme with respect to the existing adapting scheme are about 75%and 103%,respectively,for a fairness index of 0.8.We also study the effect of various system parameters on throughput and energy efficiency and provide various engineering insights.

Artificial-intelligent-powered safety and efficiency improvement for controlling and scheduling in integrated railway systems

The multi-mode integrated railway system,anchored by the high-speed railway,caters to the diverse travel requirements both within and between cities,offering safe,comfortable,punctual,and eco-friendly transportation services.With the expansion of the railway networks,enhancing the efficiency and safety of the comprehensive system has become a crucial issue in the advanced development of railway transportation.In light of the prevailing application of artificial intelligence technologies within railway systems,this study leverages large model technology characterized by robust learning capabilities,efficient associative abilities,and linkage analysis to propose an Artificial-intelligent(AI)-powered railway control and dispatching system.This system is elaborately designed with four core functions,including global optimum unattended dispatching,synergetic transportation in multiple modes,high-speed automatic control,and precise maintenance decision and execution.The deployment pathway and essential tasks of the system are further delineated,alongside the challenges and obstacles encountered.The AI-powered system promises a significant enhancement in the operational efficiency and safety of the composite railway system,ensuring a more effective alignment between transportation services and passenger demands.

Industrialization,Efficiency and Social Housing:Sustainable Prefabrication for the Colombian Social and Cultural Context

This research aims to generate processes of industrialization and qualification of social housing in Colombia through prefabrication,low energy consumption and high environmental quality to reduce the current deficit and improve the quality of life in communities with fewer economic resources.Modular coordination and the use of materials with thermal behaviors,appropriate to the country’s climatic characteristics,reduce production costs,avoid waste and improve the architectural and environmental quality of social housing.Passive cooling strategies,such as controlling solar incursion and generating natural cross ventilation eliminate energy consumption and allow reaching desired standards of comfort.In a context in which traditional construction systems have still not resolved the social housing deficit in Colombia and which generate high costs for energy consumption in the search for thermal comfort,industrialized and efficient construction with high environmental quality provides solutions according to the economic,geographic,social and cultural context in Colombia.

Evaluation of Energy Efficiency and Analysis of Influencing Factors of Company CW’s Manufacturing Workshops

In this work,the Slacks-Based Measure(SBM)model within Data Envelopment Analysis was employed to establish a set of indicators for evaluating the energy efficiency of manufacturing workshops.The energy efficiency of 12 Company CW’s manufacturing workshops from 2016 to 2022 was assessed.The findings indicated that aside from a few workshops operating at the production frontier,the rest exhibit significant fluctuations in energy efficiency and generally low energy efficiency.Subsequently,a combined GRA-Tobit analysis model was introduced to identify factors influencing the energy efficiency of Company CW’s manufacturing workshops.Regression analysis revealed that technological investments,employee quality,workshop production scale,investment in clean energy,and the level of pollution control all significantly impact the energy efficiency of Company CW’s manufacturing workshops.By evaluating the energy efficiency of Company CW’s manufacturing workshops and studying their influencing factors,this research aids company managers in understanding the energy efficiency of the manufacturing process.It optimizes the combination of various production elements,thereby offering effective guidance for improving the energy efficiency issues of the company’s manufacturing workshops,which can contribute to enhancing the corporation’s overall energy efficiency.

Power Matching and Energy Efficiency Improvement of Hydraulic Excavator Driven with Speed and Displacement Variable Power Source

Mobile machinery energy efficiency and emission pollution are the national and worldwide issues. This paper contributes in solving these problems by applying a speed variable power source. Unfortunately, almost all of the speed variable systems have the dynamic response problem when the motor starts with full load or heavy load. To address this problem, a hydraulic accumulator is used to balance the load of the power source for assisting starting of the motor and a matching method combined with speed and displacement control of the pump is proposed to improve the energy efficiency and dynamic performance simultaneously under different working conditions. Also, the power source/valve combined control strategy of an independent metering system is designed to realize flow matching of the whole system. Firstly, a test system is established to study the dynamic performance and energy efficiency of the speed variable power source with an auxiliary accumulator. Working performance and energy consumption of the power source under different rotating speeds and different loads are studied. And then, the hydraulic excavator test rig with the proposed system is constructed. Furthermore, the working performance of the excavator with the speed-fixed and speed-variable strategy are studied comparatively. Results show that, compared with fixed-speed strategy, the electric power consumption during the idle period and partial load condition can be reduced about 2.05 kW and 1.37 kW. The energy efficiency of speed variable power source is about 40%-71%, which is higher than that of the fixed-speed power source by 3%–10%.

Research on the Impact of Digital Finance on Energy Efficiency in China

Digital finance and green technology innovation(GTI)serve as powerful engines for promoting energy efficiency(EE)and economic development.This paper explores the mechanism by which digital finance impacts EE based on panel data from 30 provinces in China spanning from 2011 to 2019.The results demonstrate that digital finance can significantly enhance EE,with a particularly pronounced effect in the eastern region.Through mechanistic analysis,it is evident that GTI serves as the transmission pathway through which digital finance influences EE,accounting for 45.3%of the effect.The policy implication of this study suggests that China should expedite the digitization of financial markets to further harness the development of digital finance,particularly in pursuit of its technological innovation and green,lowcarbon environmental protection effects.

Strategies for Energy Efficiency Improvement in Zimbabwean Industries Using the Energy Audit

Energy efficiency is a modern approach for using energy resources economically. Energy audit ensures that every unit of energy gives the maximum in terms of production. This paper brings out the advantages of using energy audit to save future installation of power generation capacity and load reduction of distribution systems. It also envisages the introduction of energy conservation techniques to eliminate sub-standard equipment.

Dietary supplementation with xylooligosaccharides and exogenous enzyme improves milk production,energy utilization efficiency and reduces enteric methane emissions of Jersey cows

Background Sustainable strategies for enteric methane(CH_(4))mitigation of dairy cows have been extensively explored to improve production performance and alleviate environmental pressure.The present study aimed to investigate the effects of dietary xylooligosaccharides(XOS)and exogenous enzyme(EXE)supplementation on milk production,nutrient digestibility,enteric CH_(4) emissions,energy utilization efficiency of lactating Jersey dairy cows.Forty-eight lactating cows were randomly assigned to one of 4 treatments:(1)control diet(CON),(2)CON with 25 g/d XOS(XOS),(3)CON with 15 g/d EXE(EXE),and(4)CON with 25 g/d XOS and 15 g/d EXE(XOS+EXE).The 60-d experimental period consisted of a 14-d adaptation period and a 46-d sampling period.The enteric CO_(2)and CH_(4) emissions and O2 consumption were measured using two GreenFeed units,which were further used to determine the energy utilization efficiency of cows.Results Compared with CON,cows fed XOS,EXE or XOS+EXE significantly(P<0.05)increased milk yield,true protein and fat concentration,and energy-corrected milk yield(ECM)/DM intake,which could be reflected by the significant improvement(P<0.05)of dietary NDF and ADF digestibility.The results showed that dietary supplementation of XOS,EXE or XOS+EXE significantly(P<0.05)reduced CH_(4) emission,CH_(4)/milk yield,and CH_(4)/ECM.Furthermore,cows fed XOS demonstrated highest(P<0.05)metabolizable energy intake,milk energy output but lowest(P<0.05)of CH_(4) energy output and CH_(4) energy output as a proportion of gross energy intake compared with the remaining treatments.Conclusions Dietary supplementary of XOS,EXE or combination of XOS and EXE contributed to the improvement of lactation performance,nutrient digestibility,and energy utilization efficiency,as well as reduction of enteric CH_(4) emissions of lactating Jersey cows.This promising mitigation method may need further research to validate its long-term effect and mode of action for dairy cows.

Energy Efficiency in ARQ-Based Multi-Hop Systems and the Tradeoff with Throughput

The minimum energy per bit(EPB)as the energy efficiency(EE)metric in an automatic retransmission request(ARQ)based multi-hop system is analyzed under power and throughput constraints.Two ARQ protocols including type-I(ARQ-I)and repetition redundancy(ARQ-RR)are considered and expressions for the optimal power allocation(PA)are obtained.Using the obtained optimal powers,the EE-throughput tradeoff(EETT)is analyzed and the EETT closed-form expressions for both ARQ protocols and in arbitrary average channel gain values are obtained.It is shown that how different throughput requirements,especially the high levels,affect the EE performance.Additionally,asymptotic analysis is made in the feasible high throughput values and lower and upper EETT bounds are derived for ARQ-I protocol.To evaluate the EE a distributed PA scenario,as a benchmark,is presented and the energy savinggain obtained from the optimal PA in comparison with the distributed PA for ARQ-I and ARQ-RR protocols is discussed in different throughput values and node locations.

Evaluation and empirical research on the energy efficiency of 20 mining cities in Eastern and Central China

The gap of energy efficiency of eastern and central mining cities in China continues to expand, getting more attention from relevant departments. In this work, 20 mining cities in Eastern and Central China from 2010 to 2014 have been selected as research samples using data envelopment analysis(DEA).Research results show that the level of energy efficiency in mining cities is still low. China is in an extensive economic growth mode with high input, high consumption, low output and low efficiency. Mining cities in China have a huge potential to conserve energy and reduce emissions. China should optimize industrial structures, strengthen scientific and technological input and innovation, as well as implement energy-saving emissions reductions, and increase investment in environmental protection and ideological propaganda.

Meta-analysis of CO_(2) conversion,energy efficiency,and other performance data of plasma-catalysis reactors with the open access PIONEER database

This paper brings the comparison of performances of CO_(2)conversion by plasma and plasma-assisted catalysis based on the data collected from literature in this field,organised in an open access online database.This tool is open to all users to carry out their own analyses,but also to contributors who wish to add their data to the database in order to improve the relevance of the comparisons made,and ultimately to improve the efficiency of CO_(2)conversion by plasma-catalysis.The creation of this database and database user interface is motivated by the fact that plasma-catalysis is a fast-growing field for all CO_(2)conversion processes,be it methanation,dry reforming of methane,methanolisation,or others.As a result of this rapid increase,there is a need for a set of standard procedures to rigorously compare performances of different systems.However,this is currently not possible because the fundamental mechanisms of plasma-catalysis are still too poorly understood to define these standard procedures.Fortunately however,the accumulated data within the CO_(2)plasma-catalysis community has become large enough to warrant so-called“big data”studies more familiar in the fields of medicine and the social sciences.To enable comparisons between multiple data sets and make future research more effective,this work proposes the first database on CO_(2)conversion performances by plasma-catalysis open to the whole community.This database has been initiated in the framework of a H_(2)0_(2)0 European project and is called the“PIONEER Data Base”.The database gathers a large amount of CO_(2)conversion performance data such as conversion rate,energy efficiency,and selectivity for numerous plasma sources coupled with or without a catalyst.Each data set is associated with metadata describing the gas mixture,the plasma source,the nature of the catalyst,and the form of coupling with the plasma.Beyond the database itself,a data extraction tool with direct visualisation features or advanced filtering functionalities has been developed and is available online to the public.The simple and fast visualisation of the state of the art puts new results into context,identifies literal gaps in data,and consequently points towards promising research routes.More advanced data extraction illustrates the impact that the database can have in the understanding of plasma-catalyst coupling.Lessons learned from the review of a large amount of literature during the setup of the database lead to best practice advice to increase comparability between future CO_(2)plasma-catalytic studies.Finally,the community is strongly encouraged to contribute to the database not only to increase the visibility of their data but also the relevance of the comparisons allowed by this tool.

Managing System Losses to Improve Energy Efficiency within the Electricity Company of Ghana (ECG) Limited

The inability to achieve the target of universal access to electricity is influenced by several factors including funding limitations, the use of obsolete equipment, power theft, and system losses confronting the electricity distribution services of the Electricity Company of Ghana Limited (ECG). The study assessed the components of system losses within the ECG by determining and computing the percentage of system losses within ECG, examining the causes of both commercial and technical losses in ECG, and determining ways to improve energy efficiency by reducing system losses in the most cost-efficient manner. The study adopted deductive reasoning and a quantitative approach to guide data collection and analysis of the research output. A sample of 345 technical and non-technical staff of ECG in the Greater Accra Metropolis was selected from a population of 2500. Purposive, simple random, and cluster sampling techniques were used in identifying and accessing respondents for the study. Descriptive statistics were applied to measure central tendency and degrees of dispersion and the Relative Importance Index (RII) to predict criterion and predictor variables. The impact of low voltage network losses can adversely contribute to technical losses (20%) and reduce energy efficiency in power or electricity distribution companies. Non-technical losses are mainly caused by illegal connections, meter problems, and billing problems. Each of the non-technical losses contributes a maximum of 10% to system losses. Contributors to system losses at ECG are ranked first for power theft and least for lack of incentives. System losses at ECG include metering inaccuracies, bad workmanship, unmetered supply, and lengthy distribution lines, each recording a mean value of above 3.5. Measures to improve monitoring of the networks and systems at ECG and discourage power theft should include an extensive quantification, patrolling, and inspection of the entire network to assess the extent of the network and conditions relevant for the placement of systematically planned maintenance programmes.

Energy Efficiency and Rebound Effect:Does Energy Efficiency Save Energy?

The aim of this study is to examine the theoric and empirical literature about “rebound effect”. This study summarizes energy efficiency policy and programs in general and in Turkey. Also it gives defination of the “rebound effect” concept. The rebound effect is related to consumer’s tendency to consume more energy due to economic benefit from efficiency improvement. The ‘rebound effect’ is the focus of a long-running dispute of energy economics but it is very new concept in the most developing countries. In literature according to some economist gains in energy efficiency will also reduce the real per unit price of energy services and hence the consumption of energy will rise and partially offset the initial reduction in the usage of energy sources. However for others size of the rebound effect is too small to take attention. The empirical literature shows that the size of rebound effect can change from country to country and sector to sector.