Role In Energy Consumption Research Articles

The role of energy consumption in robotic mobile fulfillment systems: Performance evaluation and operating policies with dynamic priority

The robotic mobile fulfillment system (RMFS), with wide application in warehousing and logistics, requires many robots powered by electricity, which significantly impacts energy consumption. This paper investigates the energy consumption in the RMFS under a classic e-business environment, which classifies the orders into regular orders and expedited orders. We evaluate the impact of three dynamic priority policies (the earliest deadline first policy, waiting time-dependent policy, and weighted waiting time first policy) on throughput time and energy consumption. This paper proposes multi-class semi-open queuing network models (SOQN) with dynamic priority policies to investigate energy consumption. We validate the accuracy of the analytical models by simulation models. This paper makes the following contributions: (1) In methodology, we propose new methods to solve the SOQN with dynamic priority policies. (2) In operational planning and control, we are among the earliest to investigate the impact of dynamic priority policies on order throughput time and energy consumption in an RMFS. (3) In design optimization, we propose a decision tool to optimize the robot number for realizing the required throughput time with minimal energy consumption. Our model can also decide the optimal warehouse shape to minimize energy consumption. (4) In system analysis, we estimate the energy consumption per transaction in an RMFS, providing logistics managers insights into energy saving of warehouses.

Retraction Note: Role of energy consumption and sustainability-oriented eco-innovation on economic growth: evidence from Middle Eastern economy.

Retraction Note: Role of energy consumption and sustainability-oriented eco-innovation on economic growth: evidence from Middle Eastern economy.

Retraction Note: The role of energy consumption and economic growth on the ecological environment in ASEAN countries.

Retraction Note: The role of energy consumption and economic growth on the ecological environment in ASEAN countries.

Energy Consumption and Trade Liberalization: Investigating Performance of Economic Growth for French Economy

This study is organized to determine the performance of economic growth in the French economy. For this purpose, this study considers the role of energy consumption, trade openness and consumer prices as determining factors. The ARDL bounds test will be used for the sample from 1986 to 2022 to obtain empirical results. The results confirm that economic growth and its determinants are cointegrated in the long run. Moreover, the results also reveal that only energy consumption and trade openness significantly boost economic growth. It is further witnessed that capital accumulation is expanding economic growth in France. Among these three factors, trade openness's impact is stronger than the other factors taken in this research.

Role of energy consumption, information and communications technology, and economic complexity in promoting environmental sustainability: Implications for gulf countries

AbstractIn this empirical investigation, we analyze the correlation among Information and Communication Technology (ICT), economic complexity, CO2, financial development, and energy in Gulf countries over the period from 1995 to 2019. The study also incorporates the role of financial development and energy in understanding these relationships. Various panel techniques are employed to assess these intricate interconnections. The CSD and slope heterogeneity tests support the adoption of second‐generation techniques. The Westerlund cointegration results affirm a long‐term association between CO2 and the independent variables. The findings from the CS‐ARDL model reveal that economic growth, financial development, and oil energy contribute to increased CO2, resulting in a decline in ecological quality. By contrast, economic complexity and gas energy contribute to improved ecological quality by reducing CO2. The MMQR analysis corroborates these results, establishing significant relationships across various quantile distributions of CO2. Furthermore, with the exception of economic complexity, all the variables demonstrate predictive capabilities concerning CO2. These empirical insights provide practical policy implications aimed at achieving Sustainable Development Goals (SDGs) 7, 9, and 13.

Carbon emission oriented life cycle assessment and optimization strategy for meat supply chain

Reducing greenhouse gas (GHGs) emissions is imperative to achieve sustainable meat production and supply. Few previous studies have assessed the carbon emissions of the whole meat supply chain from the sheep fattening stage to the meat distribution stage. Therefore, this study established a boundary model of the carbon emission system of the mutton supply chain and adopted the life cycle assessment (LCA) method to comprehensively analyze the carbon emissions during breeding, transportation, processing, and distribution, and then assessed the overall carbon emissions, and optimized the route planning of the supply chain subsystems using improved genetic algorithms (GA) in order to reduce energy consumption and carbon emissions. The results show (1) The fattening sheep process generates a relatively large share of carbon emissions, but the unit emissions are stable. The carbon emissions from the transportation and marketing phases are lower than those from the fattening phase, but their carbon emissions are uncertain, which is the focus of optimization. (2) By optimizing the routes of the subsystems in the life cycle analysis model, carbon emissions due to changes in route planning can be reduced by 24.19%. Therefore, life cycle analysis can comprehensively assess the carbon emissions and total carbon emissions of each link in the mutton supply chain, and the optimization strategy plays an important role in energy consumption and carbon emissions.

The Role of Energy Consumption and Economic Growth in Environmental Degradation in Asian Countries

The Role of Energy Consumption and Economic Growth in Environmental Degradation in Asian Countries

A Deep Dive into Indonesia's CO2 Emissions: The Role of Energy Consumption, Economic Growth and Natural Disasters

This study examines the influence of non-renewable energy consumption, renewable energy consumption, economic growth, and natural disasters on Indonesia's carbon dioxide (CO2) emissions spanning from 1980 to 2021. The Autoregressive Distributed Lag (ARDL) model is employed, with supplementary robustness checks utilizing Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR). The findings reveal that economic growth, along with non-renewable and renewable energy consumption, significantly affects CO2 emissions in both the short and long term. Robustness checks confirm the positive impact of non-renewable energy consumption and economic growth, while renewable energy consumption has a negative effect on CO2 emissions. Moreover, natural disasters exhibit a positive short-term impact on CO2 emissions. Pairwise Granger causality results further underscore the intricate relationships between the variables. To mitigate climate change and curb CO2 emissions in Indonesia, the study recommends implementing policies that foster sustainable economic development, encourage the adoption of renewable energy, and enhance disaster resilience.

The Role of Energy Consumption and Economic Growth on Carbon Emission- Application of Artificial Neural Network

This paper examines the influence of gross domestic product (GDP) and energy consumption (renewable energy and non-renewable energy) on carbon emissions in European Union (EU) Countries use of panel data from 2000 to 2020. By using Artificial Neural Network (ANN) machine learning computational technique, variables are categorized into input and output parameters. The result from the analyses shows that RMSE values of all variables are significant. Further, the normalized importance obtained from the multilayer perception ANN algorithm highlights the importance of variables and their association. The finding suggests that EU countries should adopt a clean energy strategy and policy for environmental protection without compromising economic growth.

The Relationship between Energy Consumption (Renewable Energy), Economic Growth and Agro-Industrial Complex in Kazakhstan

This study analyzes the relationship between energy consumption (renewable energy), economic growth, and developments in Kazakhstan's agricultural industry complex (agriculture and livestock outputs) between 1991 and 2021 and the interaction of these factors. Analysis data were retrieved from the databases of Our World in Data, the World Bank, and the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. The study examines energy consumption over two variables. The first is the share of energy obtained from renewable energy sources in the total energy consumption, and the second is the total energy consumption. It is only natural to expect an increase in agricultural production due to new technologies in the industry. However, it is also essential to examine whether the country's economic growth, agricultural fields, and employment in agriculture play a role in energy consumption. One of the significant indicators of the developments in the agricultural industry is the reflection of the production in agriculture and animal husbandry on internationally valid indices. Therefore we deemed it appropriate to compare the input variables with the food index produced by the World Bank. The effects of agricultural industry assets and agricultural developments on energy consumption were examined using the hierarchical regression analysis approach. The findings showed that agricultural developments affect energy consumption, especially renewable energy consumption. This study concludes that it is necessary to examine the causality of this effect and whether it transforms into a short-term or long-term effect.

Assessing the emissions of short sea international shipping: a case study of the Mytilini–Ayvalik route

Short sea shipping involves transporting passengers and cargo between European ports and coastal countries bordering Europe on enclosed seas. Challenges include aging fleets and environmental concerns, but efforts to reduce emissions are in progress through the use of low-sulfur fuels, hybrid and electric vessels, and improved energy efficiency. This study focuses on emissions from international short shipping routes between Mytilini and Ayvalik, using standardized emission factors to calculate CO2, SO2, NOx, PM, and HC emissions. The research aims to bridge knowledge gaps and provide insights into these emissions, identifying the main commercial ships on the route, analyzing their emissions, and discussing the findings. Overall, six ships completed the route, consuming an average of 60 L of fuel per hour per 100 HP, depending on factors like speed and total load. Notably, NOx emissions are the highest, followed by sulfur oxides, with values exceeding 12.9 and 3.5 tons, respectively. As anticipated, cruising is the shipping practice with the highest energy footprint, amounting to 695 MWh. An essential discovery is that hoteling plays a significant role in energy consumption and emissions, accounting for 152 MWh out of the total 881 MWh consumed across all shipping practices. The potential adoption of hydrogen as a fuel holds the promise of substantial reductions in greenhouse gas emissions, enhancements in air quality, and noise pollution mitigation.

Evaluating Savings Potentials Using Energy Retrofitting Measures for a Residential Building in Jeddah, KSA

Residential buildings in the Kingdom of Saudi Arabia (KSA) contribute to nearly half of the overall electricity consumption in the building stock, highlighting their significant role in energy consumption. While an upgraded energy code has been established and enforced for new buildings, existing buildings continue to operate at the same level of energy consumption. Therefore, there is a need for further energy upgrades in existing buildings. This study evaluates the energy savings potential of various energy retrofitting measures for a case study in Jeddah, KSA. Data from previous studies and current practices were collected and analyzed. Different energy upgrade measures, such as windows replacement, wall insulation upgrade, roof insulation upgrade, and air conditioning unit replacement, were selected and evaluated using a digital simulation tool called Design-Builder. The simulation results were compared to understand the potential percentage of energy savings. The average annual energy consumption (AAEC) was used as the primary performance indicator to compare the energy savings among the scenarios. The results demonstrate significant reductions in energy consumption for the proposed scenarios. Furthermore, the study examined the significant impact of uncertainties, specifically, the infiltration rate and AC setback temperature, on AAEC. In conclusion, the proposed scenarios have the potential to achieve substantial energy savings, ranging from 25% to 66%, depending on the number of energy retrofitting interventions employed. The findings of this study can serve as a useful reference for similar energy retrofitting projects.

The asymmetric effect of ICT on CO2 emissions in the context of an EKC framework in GCC countries: the role of energy consumption, energy intensity, trade, and financial development.

This study examines how "information and communication technology (ICT)" affects carbon dioxide (CO2) emissions in Gulf Cooperation Council (GCC) nations asymmetrically, controlling energy consumption, its intensity, trade, and financial development following an environmental Kuznets curve (EKC) approach. It employs panel data covering 1995-2019, 2nd generation unit root, Westerlund cointegration tests, nonlinear pooled mean group (PMG) estimate, and Dumitrescu-Hurlin causality check. The Westerlund test validates a long-run association among variables. The study confirms the EKC proposition for the GCC countries. It reveals that a decrease in CO2 emissions is associated with both positive and negative parts of ICT and the expansion of financial development. While per capita GDP increases pollution, squared GDP per capita reduces it; energy consumption, intensity, and trade amplify carbon emissions. D-H causality check yields several bidirectional and one-way causalities and verifies the robustness of PMG outcomes. Our findings suggest that promoting ICT becomes one of the critical techniques to decrease CO2 emissions in GCC nations due to its significant negative influence on CO2 emissions.

Use of Context Aware Game Theoretic Approach to Minimize the Overall Energy Consumption of Mobile Cloud Computing

Mobile cloud computing (MCC) is an emerging technology which has been an important and a hot research topic, recently. It is a boon for resource constrained mobile phones as it allows them to offload the computation to the cloud servers, which helps them to execute the code remotely. There have been various models, designs, techniques and tools to support the MCC but as the user base and their demands are increasing day by day, we are required to come up with more efficient models which are well- defined and cost-effective. Building block of MCC or any such technology is user, no user no usage. Hence, the cost of this technology must be minimized, for the growth of MCC. In this paper, we talk about the role of energy consumption in reducing the cost of MCC for the mobile user. We propose a context-aware-game-theoretic approach to minimize the overall energy consumption of the MCC system; which, in turn, will minimize the cost of the service, for the user.

Role of energy consumption, tourism and economic growth in carbon emission: evidence from Kuwait

Even though the Paris Agreement and the Sustainable Development Goals say that low-carbon economic growth is essential, more research must be done to determine how the tourism sector affects carbon productivity. So, to see if increased energy usage, tourism, and economic growth jointly raise carbon productivity in Kuwait, this study uses a vector error correction strategy to look at the years 1995–2020. Predictions about how sustainable tourism will affect energy efficiency, and carbon productivity improvements are also an excellent way to learn more about this subject. As the amount of carbon dioxide in the air increases, tourism will go down by 0.13 percent. Inverse cointegration is the term for this phenomenon. However, the vector error correction model showed that carbon emissions go down as the economy grows and people pay more attention to how much energy they use. Nevertheless, Granger’s theory of cause and effect says that carbon emissions, energy use, and economic growth can only lead to more tourism in one way.

Sandpiper optimization algorithm with cosine similarity based cross‐layer routing protocol for smart agriculture in wireless sensor network assisted internet of things systems

SummaryThe Internet of Things (IoT) has recently attained a prominent role in enabling smooth and effective communication among various networks. Wireless sensor network (WSN) is utilized in IoT to collect peculiar data without interacting with humans in specific applications. Energy is a major problem in WSN‐assisted IoT applications, even though better data communication is achieved through cross‐layer models. This paper proposes a new cross‐layer‐based clustering and routing model to provide a scalable and energy‐efficient long data communication in WSN‐assisted IoT systems for smart agriculture. Initially, the fuzzy k‐medoids clustering approach is used to split the network into various clusters since the formation of clusters plays an important role in energy consumption. Then, a new swarm optimization known as enhanced sparrow search algorithm (ESSA), which is the combination of SSA and chameleon swarm algorithm (CSA), has been introduced for optimal cluster head (CH) selection to solve the energy‐hole problems in WSN. A cross‐layer strategy has been preferred to provide efficient data transmission. Each sensor node parameter of the physical layer, network layer and medium access control (MAC) is considered for processing routing. Finally, a new bio‐inspired algorithm is known as the sandpiper optimization algorithm (SOA), and cosine similarity (CS) has been employed to determine the optimal route for efficient data transmission and retransmission. The simulation of the proposed protocol is implemented by network simulator (NS2), and the simulation results are taken in terms of end‐to‐end delay, PDR, communication overhead, communication cost, average consumed energy, and network lifetime.

Research on Envelope Thermal Performance of Ultra-Low Energy Rural Residential Buildings in China

Rural energy consumption plays an important role in energy consumption due to the improvement of rural residents’ living quality requirements in China. Ultra-low energy rural residential buildings are proposed to decrease rural energy consumption. First of all, this paper aims to provide the definition of ultra-low energy rural residential buildings, which is to reduce 50% of the building energy consumption of the rural residential benchmark building according to the Chinese standard for energy efficiency of rural residential buildings. Secondly, this paper presents the heat transfer coefficients of building envelopes of ultra-low energy rural residential buildings in the severe cold zone, cold zone and hot summer and cold winter zone in China. Based on optimized design and simulation analysis, the heat transfer coefficients of building envelopes are determined by the construction cost, energy efficiency and retrofit feasibility. Thirdly, the suitable combination of a high-performance external wall and internal wall is recommended based on carbon emission and cost efficiency. As an achievement, a technical specification for ultra-low energy rural buildings has been proposed by the China Academy of Building Research. It is beneficial to design ultra-low energy rural residential buildings in China and other countries.

Controlling the Energy Relaxation: Organic Doping in AIEgen Nanoparticles for Highly Enhanced Intravital Two‐Photon Imaging

AbstractAggregation‐induced emission luminogens (AIEgens) as a new class of optical probes for two‐photon imaging (2PI) have attracted extensive attention in the research community. However, their non‐radiative energy dissipation plays a non‐negligible role in energy consumption, thereby weakening their performance in 2PI. Exploration of a facile and general approach to control the energy relaxation pathways is thus a fascinating yet significantly challenging task. To address this concern, an organic doping method is proposed herein by using TPE‐Br as the doping AIEgen and MeOTTMN as the functional AIEgen. With increased amount of doping molecules, a steadily strengthened brightness (up to 29‐fold of quantum yield) is observed at the expense of reactive oxygen species production. Remarkably, an ultradeep imaging depth of 1000 µm in a mouse brain is realized via 2PI using the heavily organic‐doped AIEgen(ODA) nanoparticles (NPs). Such result is far superior to the imaging depth of 156 µm enabled by MeOTTMN NPs. The safe use of ODA NPs is further evaluated by in vitro and in vivo toxicity assessment. This study thus provides an attractive paradigm to control the energy relaxation of AIEgen NPs and maximize their performance in 2PI while circumventing the difficulties in molecular engineering.

Technical, economical, and environmental scenario based modeling of the building equipped with ground source heat pump (GSHP) and solar system

Owing to fossil fuel price fluctuation as well as its environmental adverse impact, quick running renewable energy system is inevitable. The building sector is one of the most energy-intensive sectors that play an important role in energy consumption and pollutants emission. This study aims to present an alternative plan to reduce fossil energy consumption in residential buildings. Considering the high potential of renewable energy sources, especially ground source heat pumps (GSHP) combined with solar energy near to residential sector can lead to a shift to zero energy building. Here, an attempt is made to provide the building energy requirement including the domestic hot water, heating, cooling, as well as electricity generation for sale to the national network, by presenting and comparing three scenarios assessment; the first scenario is the reference building, the second one equipped building with the GSHP system, and the third scenario includes the combination of GSHP and building integrated photovoltaics (BIPV) along with the solar collector. The dynamic simulation is performed using TRNSYS software. By comparing the proposed scenarios, the results confirmed that a decrease in energy consumption is observed in the second and third scenarios by 2 and 26 percent, respectively compared to the First scenario. Economically assessment revealed that the initial net present value (NPV) in the third scenario is 18.8% and 14.1% higher than the NPV of the first and second scenarios, respectively. The return on investment (ROI) calculation shows that the investment return after 7 years for the second scenario, while this is 8 years for the first and the third scenarios. Moreover, from the environmental point of view, the second and third scenarios have led to a reduction of 11% and 41% in carbon dioxide emissions, respectively.

Exergy analysis of China’s transportation sector

In China, transportation plays an increasingly important role in energy consumption. This study aims to uncover the evolution of energy consumption structures and intensities within China’s transportation during 2000–2018 from the perspective of exergy. Our study will analyse five sub-sectors; highways, railways, waterways, civil aviation, and pipelines. China’s transportation exergy consumption witnessed a notable increase from 3228 PJ in 2000 to 12,017 PJ in 2018, with an annual growth of 7%. Highways and railways were the two largest sub-sectors in terms of exergy consumption. The exergy efficiencies of the transportation sector show an upward trend, with railways and pipelines sub-sectors growing conspicuously faster than other sub-sectors. Potential factors influencing the evolution of transportation’s exergy consumption are identified by using the Log-Mean Divisia Index (LMDI) decomposition method. The sub-sector effect and the activity effect have a strong positive correlation with exergy consumption. The exergy intensity effect shows a strong negative correlation with exergy consumption. Owing to the railways’ exergy intensity effect, the rebound effect is higher than that of technological progress, creating a positive influence on exergy consumption. Improvement in exergy efficiencies and joint efforts among transportation sub-sectors, will improve the overall performance of China’s transportation sector, leading to sustainable development.