Aggregate Energy Efficiency Research Articles

Energy Demand and Energy Efficiency in Developing Countries

This paper investigates relative aggregate energy efficiency for a panel of 39 developing countries by econometrically estimating an energy-demand function (EDF) using the stochastic frontier analysis (SFA) approach to provide relative energy efficiency scores over the period 1989 to 2008. Energy efficiency is arguably difficult to define or even conceptualise with several interpretations in the literature but here it is based on an economists’ perspective of efficiency. Hence, the estimates of ‘true’ energy efficiency found in the paper using this approach approximate the economically efficient use of energy capturing both technical and allocative efficiency and the results confirm that energy intensity should not be considered as a de facto standard indicator of energy efficiency. While, by controlling for a range of socio-economic factors, the measurements of energy efficiency obtained by the analysis are deemed more appropriate and hence it is argued that this analysis should be undertaken to avoid potentially misleading advice to policy makers. This study contributes to the literature since it is, as far as is known, the first attempt to apply the benchmarking parametric stochastic frontier technique to econometrically estimate energy efficiency for a large panel of only developing counties around the world. Moreover, the results from such analysis are arguably particularly relevant in a world dominated by environmental concerns, especially in the aftermath of energy price increase as a result of the unrest in Ukraine.

Unfolding the painting scroll of energy intensity changes in Chinese mainland (1990–2019): A regional perspective

Improving the aggregate energy efficiency is consequential for China's sustainable development and carbon dioxide reduction, but there lacks a systematic analysis of China's energy intensity long-term changes. China's energy intensity fell sharply by 74.7% with great heterogeneity across regions during the years 1990–2019, but rose steadily by 7% from 2001 to 2005. This paper combined decomposition approach and econometric analysis to unfold the painting scroll of energy intensity changes in Chinese mainland (1990–2019) from a regional perspective. Decreased by the increase of relative energy price, the expansion of technology transactions and the surrounding provinces' efforts, provincial intensity was found as the main driving force of the aggregate energy intensity reduction in general from 1990 to 2019. Yet, after controlling the effects of these factors, macroeconomic cyclical fluctuation, triggered by Chinese reindustrialization process, increased the provincial intensity, hence amplified the aggregate energy intensity between 2001 and 2005. The results of this study will provide sufficient basis for the policy implications on the improvement of energy efficiency in China and developing countries in the future.

Resource Allocation for the Backhaul of NOMA-Based Cellular UAV Network

A cellular unmanned-aerial-vehicle (UAV)-enabled system is studied in this research, where multiple UAVs work cooperatively to upload the collected sensory data to the base station (BS). The UAVs form a two-tier network with two kinds of communication modes, i.e., UAV-to-Network (U2N) and UAV-to-UAV (UAV) communications. We investigate the communication resource allocation for UAVs to maximize the aggregate energy efficiency of the system. The formulated problem is mixed-integer and NP-hard. To make the formulated problem tractable, an efficient matching-based algorithm is proposed to complete the transmission mode selection and subchannel allocation, respectively. Then the transmission power is optimized based on game theory. The simulation results reveal that the uplink energy efficiency can be improved with the proposed scheme, compared with the maximum power strategy.

Antarctic Shipborne Tourism: Carbon Emission and Mitigation Path

The rapidly increasing concentrations of carbon dioxide lead to a threat of global climate change. As one of the major sources of carbon emissions in the Antarctic region, shipborne tourism in the Antarctic is expanding rapidly. Consequently, the carbon emissions of shipborne tourism in Antarctica are rapidly increasing. However, there is not enough attention being paid to this issue. In this paper, a calculation model was established to calculate the carbon emissions of cruise ships from the 2003/04 season to the 2016/17 season. The evolution of the carbon emissions from Antarctic cruise ships was described. An aggregate energy efficiency index was developed to evaluate the energy efficiency performance of Antarctic vessels. The key drivers were analyzed to find the paths of carbon reduction. The results show that: (1) The emissions per passenger-trip did not show a downward trend. The total carbon emissions increased continuously with the increasing number of tourists. The total carbon emissions in the 2016/17 season was double that in the 2003/04 season. (2) The aggregate energy efficiency index of Antarctic tour vessels has not reached an advanced level yet. It is the main reason for the high value of emissions per passenger-trip. (3) Due to the oversupply of Antarctica tour ships, there is a low rate of occupancy, which accounts for the decline in aggregate energy efficiency from the 2014/15 season to the 2016/17 season. This study suggests that the administrators of Antarctica should strengthen supervision of the tourism market, control the rapid growth in the number of cruise ships, improve the aggregate energy efficiency of cruise ships and form an efficient and green Antarctic tourism management system.

Increased Fossil Fuel Consumption and Its Impact on Energy Efficiency and Economic Growth

Energy efficiency improvement is believed to be an effective means of reducing energy consumption thereby reducing green-house gas emission and as well promoting sustainable economic development. Therefore, ascertaining the energy efficiency level will guide policy makers on the right kind policy intervention that will guarantee energy security, climate change mitigation and sustainable growth and development. The study employed a multivariate regression technique to estimation of the impact of a change in the energy structure on aggregate energy efficiency and economic growth. It was revealed in the study that, though an increase usage of fossil fuel is an important factor input for economic growth, however, it is inimical to the efforts aimed at combating climate change. The study also revealed that the marginal efficiency of the energy inputs is important for ensuring increased output as well as sustainable energy supply. Energy efficiency was seen as a mechanism for improving optimal energy utilization. Therefore, improving the level of energy efficiency will significantly assist in providing clean energy coupled with achieving sustainable development goals. This will benefit the nation in terms of ensuring energy security together with climate change mitigation. Policy makers should also focus more on investing in energy efficiency promoting technologies in order to reduce the per capita energy consumption without compromising the economic output level.
 
 Received: 16 June 2021 / Accepted: 7 November 2021 / Published: 3 January 2022

Drivers of Declining Energy Intensity all over the World: Based on the Perspective of National Industrial Production

Improving the world's aggregate energy efficiency is consequential for global sustainable development. This paper evaluated the world's aggregate energy intensity reduction along with economic growth and industrial transformationusing the panel data of all countries around the world from 1971 to 2016. The overall energy intensity of the world was decomposed into activity mix and national intensity based on LMDI approach, and we found that the latter was the main driving force for the reduction of the world's overall energy intensity. We further analyzed the relationship between energy prices, technological progress, and national intensity. The results showed that technological progress and energy prices significantly decreased national intensity, with significant regional differences, however, no significant impact appeared in a price-declining period. To reduce energy intensity, localized measures in different supra-national regions are needed.

Exploring the links between total factor productivity and energy efficiency: Portugal, 1960–2014

A good understanding of the sources of economic growth is fundamental. Total factor productivity (TFP) – frequently taken as synonymous of technical change but computed as a residual – is credited as a major driver of growth. Despite considerable efforts, the sources of TFP growth are still poorly understood. As all economic processes necessarily entail the conversion of energy, aggregate energy (conversion) efficiency is a plausible candidate to measure technical change. Here, we test the hypothesis that there is a statistically significant long-term relationship between TFP and aggregate energy efficiency (measured as final-to-useful aggregate exergy efficiency), for Portugal, 1960–2014. Our results strongly suggest that these variables are cointegrated, with unit elasticity between technical change and energy efficiency. This link is stronger when TFP is computed considering the more theoretically correct capital services and schooling-corrected labour measures. Since we also find that aggregate energy efficiency Granger-causes TFP, we can legitimately claim that the former is the main driver of economic growth. As thermodynamic laws impose that aggregate energy efficiency is upper bounded at 100%, our findings also suggest there are thermodynamic limits on growth. This carries implications for models currently used to inform policymakers on economic growth, sustainable development, and climate change scenarios.

Promoting Energy Efficiency and Proportional Fairness in Densely Deployed Backscatter-Aided Networks

Recently, energy-efficient ambient backscatter communication has emerged as a promising technology to build up self-sustainable wireless networks. However, the limited transmission range and rate restrict the communication capability of a single backscatter node. To ensure network coverage and connectivity, the nodes in ambient backscatter-aided wireless networks (AmBWNs) have to be densely deployed. Unfortunately, the fickle and sporadic nature of the energy source and carrier in AmBWNs would lead to unreliable and unstable transmissions. We argue that the network throughput can be significantly improved if we can take full advantages of both stable active transmission and energy-saving backscattering. However, it is challenging to jointly determine nodes' transmission mode to enhance the throughput and energy efficiency. Moreover, the fairness in terms of traffic load at each node of AmBWNs is not thoroughly considered in the existing research. The improper load allocation would hinder the network throughput and even cause network partition if some bottleneck nodes deplete the energy. In this article, a novel metric is defined to measure the aggregate energy efficiency of neighboring nodes, capturing the beneficial interaction of active links and backscatter links. Subsequently, we address the aggregate energy efficiency maximization problem constrained by Gini threshold. The Gini coefficient is used to adjust the load in proportion to the delivery capacity of each node, achieving proportional fairness in the dense AmBWN. The simulation result shows that the well-designed metric can improve the energy efficiency by 11 times and the throughput by 86%.

Future western U.S. building electricity consumption in response to climate and population drivers: A comparative study of the impact of model structure

Projections of building electricity consumption are used in multiple fields and for a variety of purposes, from energy utility investment decisions to global climate assessments. Existing approaches to modeling building electricity consumption span a range of structural methodologies, spatial resolutions, and temporal scales, potentially leading to divergent projections. This paper compares how two models with different structures and resolutions respond to a common set of population and climate drivers in the western U.S. The BEND model simulates hourly residential and commercial building electricity consumption at the county scale by weighting the results of simulations of thousands of representative buildings. In contrast, the projected electricity demand in GCAM-USA is determined for each state, year, sector (residential/commercial), and service (e.g., heating, cooling, and others), based on population, income, technology, energy prices, and average annual climate. This paper aggregates the two models’ results to a common resolution: annual residential and commercial building electricity consumption by state. Both models show similar responses to future projected population change and climate change, with population change having the larger impact between the two. Differences are primarily due to how the models capture changes in the aggregate energy efficiency of the building stock as it evolves over time.

Enabling High Order SCMA Systems in Downlink Scenarios With a Serial Coding Scheme

In the future fifth generation communication systems, sparse code multiple access (SCMA) shows strong competitiveness as a novel non-orthogonal multiple access (NOMA) technique. Attributing to multi-dimensional codebooks, the SCMA can obtain shaping gain and provide a better performance than some other NOMA schemes, such as pattern division multiple access, low-density signature (LDS), and so on. However, under higher user load, each orthogonal resource in high-order SCMA systems is occupied by more users and the constellations of these systems possess smaller Euclidean distances, both of which will degrade the link performance. The iterative algorithm employed in SCMA decoding, namely message passing algorithm, will also bring an exponential growth of computational complexity. In this paper, a scheme with serial codes for system order reduction in downlink scenarios, namely serial SCMA, is proposed to tackle these issues. Based on the idea of hierarchical coding, the processes of encoding and decoding in a high-order system are decomposed into several processes in low-order systems. Specific mapping modules are designed to recover the original user binary bits. Simulation results show that serial SCMA will substantially cut down the detection complexity and enjoy better link performance while maintaining sparser codebooks. Besides, it still inherits the advantages of original SCMA systems such as overloading and average aggregate energy efficiency over OMA and other NOMA schemes.

A framework for understanding energy for water

This article offers a framework for understanding how energy is used to meet water demand in countries. Specifically, the relationships between energy use and water scarcity, the location of renewable water resources, and aggregate water demand are explored. The article also examines how policy options such as water price reforms, agriculture subsidies and crop elimination may influence the energy use and energy intensity of water withdrawals. Conclusions suggest that while policy options exist, certain uncontrollable factors such as severe water scarcity or substantial freshwater abundance limit the ability of some countries to significantly improve the aggregate energy efficiency of water provision.

Energy intensity developments in 40 major economies: Structural change or technology improvement?

This study analyzes energy intensity trends and drivers in 40 major economies using the WIOD database, a novel harmonized and consistent dataset of input–output table time series accompanied by environmental satellite data. We use logarithmic mean Divisia index decomposition to (1) attribute efficiency changes to either changes in technology or changes in the structure of the economy, (2) study trends in global energy intensity between 1995 and 2007, and (3) highlight sectoral and regional differences. For the country analysis we apply the traditional two factor index decomposition approach, while for the global analysis we use a three factor decomposition which includes the consideration of regional structural changes in the global economy. We first show that heterogeneity within each sector across countries is high. These general trends within sectors are dominated by large economies, first and foremost the United States. In most cases, heterogeneity is lower within each country across the different sectors. Regarding changes of energy intensity at the country level, improvements between 1995 and 2007 are largely attributable to technological change while structural change is less important in most countries. Notable exceptions are Japan, the United States, Australia, Taiwan, Mexico and Brazil where a change in the industry mix was the main driver behind the observed energy intensity reduction. At the global level we find that despite a shift of the global economy to more energy-intensive countries, aggregate energy efficiency improved mostly due to technological change.

Energy structure, marginal efficiency and substitution rate: An empirical study of China

Energy efficiency is an important factor in developing energy policies as it represents the extent to which resources support economic output. In recent literature, relevant studies have mainly focused on aggregate energy efficiency, but rarely touched on the marginal efficiency of diverse energy resources and their comparative substitution rate. During 1978-2003, China's energy efficiency continually increased; and consequently became a hot topic in contemporary literature. However, there is no empirical study on the relationship between energy structure and energy efficiency. In order to close the gap, this paper reports the empirical study of the impact of China's energy structure on its energy efficiency from 1978 to 2003. The work covered primary estimation of the marginal efficiency of coal and petroleum in China, as well as the comparative substitution rate. Results indicate that the substitution rate between petroleum and coal is a factor of 5.38. (c) 2006 Elsevier Ltd. All rights reserved.

Technology Diffusion in Energy-Economy Models: The Case of Danish Vintage Models

Technological progress is an important issue in long-term energy demand projections and in environmental analyses. Different assumptions on technological progress and diffusion of new technologies are among the reasons for diverging results obtained using bottom-up and top-down models for analysing the costs of greenhouse gas mitigation. This paper examines the effect on aggregate energy efficiency of using technological vintage models to describe technology diffusion. The focus is on short- to medium-term issues. Three different models of Danish energy supply and demand are used to illustrate the consequences of the vintage modelling approach. The fluctuating utilisation rates for power capacity in Denmark are found to have a significant impact on average fuel efficiencies. Diffusion of electric appliances is linked to economic activity and saturation levels for each appliance. In the sector of residential heat demand, fuel price increases are found to accelerate diffusion by increasing replacement rates for heating equipment.

Social structure and energy efficiency: A preliminary cross-national analysis

This study questions the assumption that there is an immutably positive relationship between per capita GNP and per capita energy consumption among human societies. A ratio of per capita GNP to per capita energy consumption ($U.S./kg coal equivalent) is proposed as a measure of energy efficiency for a cross-national analysis of 118 world nation-states and a subset of 25 developed market economies. This ratio is found to vary considerably, between 0.19 and 9.80. A review of literature suggests possible relationships among several sociodemographic characteristics of nations and levels of efficiency with which energy is converted into goods and services. Among the total sample, level of production (measured in terms of per capita GNP) bears a substantial inverse association with energy efficiency. When per capita GNP is held constant, agricultural share of gross domestic product and percentage of labor force in agriculture continue to be positively associated with energy efficiency among the total sample. Variables measuring defense expenditure, urbanization, and population density exhibit somewhat smaller multivariate relationships with energy efficiency when per capita GNP is controlled, i.e., these variables have significant multivariate parameters, but are less closely related to energy efficiency than level of production and agricultural composition of the economy and labor force. Agricultural composition of the economy and labor force is the major predictor of energy efficiency among the subset of 25 developed market economies. The results suggest that among the developed industrial societies level of production is less important than the composition of production activities in determining aggregate energy efficiency.