Assessing the technological responsibility of productive structures in electricity consumption

A methodology is developed which allows us to measure the responsibility of the productive structure of an economic system with respect to the consumption and generation of electricity within an input–output framework. We propose a technical indicator of technology responsibility in electricity consumption based on the assessment of technical coefficients. Technological responsibility refers to the capacity of a sector or economic transaction between sectors to induce electricity consumption regardless of the final demand vector. Sectors with a high technological responsibility are those whose technologies use inputs which either directly or indirectly require much electricity independently of the composition of the final demand in the economy. This methodology is applied to the productive sectors of the Spanish economy. It is found out that a few transactions between sectors are highly technologically responsible regarding electricity consumption. The results show that, although the service sectors are the ones with the greatest share in electricity consumption, the industrial sectors (particularly, the extractive, heavy and energy industries), the electricity generation sector and construction are the ones with the greatest technological responsibility, i.e., they have technology mixes with a large propensity to consume electricity, propagating to the other sectors. The sectors with the highest technological responsibility are clustered around three broad sectors: energy, metal manufacturing and transport.     

Assessing the influence of manufacturing sectors on electricity demand. A cross-country input-output approach

The production and consumption of electricity is a major source of CO₂ emissions in Europe and elsewhere. In turn, the manufacturing sectors are significant end-users of electricity. In contrast to most papers in the literature, which focus on the supply-side, this study tackles the demand-side of electricity. An input–output approach combined with a sensitivity analysis has been developed to analyse the direct and indirect consumptions of electricity by eighteen manufacturing sectors in fifteen European countries, with indirect electricity demand related to the purchase of industrial products from other sectors which, in turn, require the consumption of electricity in their manufacturing processes. We identify the industrial transactions and sectors, which account for a greater share of electricity demand. In addition, the impact of an electricity price increase on the costs and prices of manufacturing products is simulated through a price model, allowing us to identify those sectors whose manufacturing costs are most sensitive to an increase in the electricity price.     

Changes in industrial electricity consumption in china from 1998 to 2007

Electricity consumption in the industrial sector experienced a dramatic increase between 1998 and 2007, accounting for approximately 75% of China’s total electricity consumption. This study analyzes the potential factors influencing the growth of electricity consumption in China’s industrial sector over the past decade using a logarithmic mean Divisia index I decomposition method. Results show that activity effect and shift effect (caused by the change in the electricity’s share of industrial energy use) are the major factors responsible for the rise in electricity consumption between 1998 and 2007. It is found that structural change also contributed to the increase in electricity consumption, it had only a small effect. In contrast, the technological effect is responsible for a decrease in electricity consumption during this period. The influences of technological effects and shift effects followed approximately an inverse-U-shaped and U-shaped curve, respectively. Furthermore, the results show that the main contributors to incremental electricity consumption among industrial subsectors were manufacturing of raw chemical material and products, manufacturing of non-metal mineral products, smelting and pressing of ferrous and non-ferrous metals, and production and supply of electric power and heat power. These sectors should take priority for industrial restructuring in order to implement policies for energy and electricity savings.     

The impact of ICT investment and energy price on industrial electricity demand: Dynamic growth model approach

The authors investigate the effects of information and communications technology (ICT) investment, electricity price, and oil price on the consumption of electricity in South Korea's industries using a logistic growth model. The concept electricity intensity is used to explain electricity consumption patterns. An empirical analysis implies that ICT investment in manufacturing industries that normally consume relatively large amounts of electricity promotes input factor substitution away from the labor intensive to the electricity intensive. Moreover, results also suggest that ICT investment in some specific manufacturing sectors is conducive to the reduction of electricity consumption, whereas ICT investment in the service sector and most manufacturing sectors increases electricity consumption. It is concluded that electricity prices critically affect electricity consumption in half of South Korea's industrial sectors, but not in the other half, a finding that differs somewhat from previous research results. Reasons are suggested to explain why the South Korean case is so different. Policymakers may find this study useful, as it answers the question of whether ICT investment can ultimately reduce energy consumption and may aid in planning the capacity of South Korea's national electric power.     

Tracking the genealogy of CO2 emissions in the electricity sector: An intersectoral approach applied to the Spanish case

This paper analyses the factors leading to CO₂ emissions in the Spanish electricity generation sector in order to propose effective mitigation policies aimed at tackling those emissions. Traditionally, two broad categories of those factors have been considered in the literature: those related to the supply of electricity (technological features of the sector) and those related to the level of economic activity (demand factors). This paper focuses on an additional element, which has usually been neglected, the structural factor, which refers to the set of intersectoral transactions (related to the technologies used in other productive sectors) which connect, in either a direct or an indirect way, the general economic activity with the supply of electricity and, thus, with the emissions of the electricity generation sector. This analysis allows us to identify the so-called “sectors structurally responsible for emissions” (SSER), whose production functions involve transactions which connect the demand for goods and services with the emissions of the electricity generation sector. The methodology is based on an input–output approach and a sensitivity analysis. The paper shows that there are structural rigidities, deeply ingrained within the economic system, which lead to emissions from the electricity generation sector for which this sector cannot be held responsible. These rigidities limit the effectiveness of policies aimed at emissions mitigation in this sector.     

An outlook into energy consumption in large scale industries in India: The cases of steel,aluminium and cement

All the growth-oriented sectors in a developing economy consume enormous energy in their production processes. Steel, aluminium and cement are the key manufacturing industries in India which provide inputs to various other sectors such as construction, transportation, power transmission, etc. As a result, their demand is consistently rising. These industries are heavily energy-intensive and use raw materials such as iron ore, coal, electricity, steam, and fuel oil, whose supply can act as severe production constraints over a period of time and can hinder sustainable development. Hence it becomes imperative for these industries to continuously innovate more energy efficient techniques. This paper makes a foray into the energy demand for these industries and explores the potential of any future reduction in their energy consumption. The paper offers a projection scenario for 2001–2031 (based on the MARKAL Modeling exercise for India) for possible catching up in reduction in energy consumptions in these sectors under alternative situations. The analysis suggests the existence of some plausible energy efficiency enhancing techniques in these industries. Exploring these options will definitely ensure cost effectiveness and competitiveness of these three key sectors in the global market.     

Input-output table of electricity demand and its application

It is very important for electric utility to determine dominant sectors which have more impacts on electricity consumption in national economy system. In this paper, an input-output perspective and methodology is proposed to handle this issue. The input-output table of electricity demand (IOTED) is put forward based on the input-output table of national economy (IOTNE). The relevancy of electricity demand in various sectors is revealed by means of electricity consumption chains (ECCs), which are key components in the IOTED. Besides, a new concept, electricity demand multiplier (EDM), is presented to identify dominant sectors imposing great impacts on electricity demand quantitatively. In order to testify the effectiveness of the proposed methodology, a case based on provincial economy system in China is studied. Dominant sectors are identified and discussed.     

Structural analysis of electricity consumption by productive sectors. The Spanish case

The aim of this paper is to identify those sectors that contribute most to electricity consumption in Spain, using a methodology based on input–output tables, and to derive some recommendations aimed at increasing energy efficiency in those sectors. This input–output approach is complemented with a sector-focused study in which the availability of electricity-efficient technologies per sector and the barriers to their uptake are identified. This hybrid approach is deemed useful to derive policy implications. We thus propose several instruments to remove those barriers.     

Analysis of electricity consumption: a study in the wood products industry

This paper evaluates the effect of industry segment, year, and US region on electricity consumption per employee, per dollar sales, and per square foot of plant area for wood products industries. Data was extracted from the Industrial Assessment Center (IAC) database and imported into MS Excel. The extracted dataset was examined for outliers and abnormalities with outliers outside the quantile range 0.5–99.5 dropped from the analysis. A logarithmic transformation was applied to eliminate the skewness of the original data distributions. Correlation measurements indicated a moderate association between the response variables; therefore, a multivariate analysis of variance test was performed to measure the impact of the three factors: industry type, year, and region, simultaneously on all response variables. The results indicated some effect associated with all three factors on the three measures of electricity consumption. Subsequently, univariate ANOVA tests were conducted to determine the levels of the factors that were different. Most levels of industry type were associated with significantly different energy consumption, an expected result since some of the industries are more energy intensive than others. The industries in Standard Industry Code (SIC) 2493 (reconstituted wood products) are the groups with the highest electricity consumption with means of 38,096.28 kWh/employee, 0.86 kWh/sales, and 154.14 kWh/plant area while industries grouped in SIC 2451 (mobile homes) have the smallest consumption with means of 6811.01 kWh/employee, 0.05 kWh/sales, and 9.45 kWh/plant area. Interestingly, differences in regional consumption were found to be linked to the proportion of industry types by region. Data analysis also indicated differences in electricity consumption per employee for the factor year, but for the other response variables, no differences were found. These main results indicate that industries in the wood products sector have different electricity consumption rates depending on the type of manufacturing processes they use. Therefore, industries in this sector can use these comparisons and metrics to benchmark their electricity consumption as well to understand better how electricity costs might vary depending on the region they are located.     

What goes down must come up? Trends of industrial electricity use in the North-West of Russia

This article uses decomposition method to analyse industrial electricity consumption in North-Western Russia, namely in Archangelsk oblast, the Republic of Karelia and Murmansk oblast. The case sectors, forestry and electricity, have in most cases developed similarly in the chosen regions during 1990–2001. The decomposition analysis shows that the reduction of economic activity has reduced electricity consumption in all three regions but that it is not always the main factor reducing consumption. The changes in energy efficiency increased consumption in the forestry sector in all regions while in the electricity sector it led to a reduction. The changes in the structures of the regional economies increased electricity consumption in electricity industry which gained importance due to developments in the manufacturing industry. In Murmansk, forestry sector has almost disappeared during the observation period. This was the main observed electricity consumption reduction caused by structural changes. Many of the developments can be better understood against the general knowledge of transition factors.     

Analysis on energy intensive industries under Taiwan's climate change policy

This study addresses the planning and implementation of energy, industry, and carbon economy policies concerning the development of the Taiwan's energy intensive industries from perspective of climate change. As a newly industrialized country, Taiwan attaches greater importance to the development of green energy and low-carbon industries, in cooperation with global pressure for carbon reduction due to climate changes, through energy and industrial conferences. Thus, in the past year the Taiwanese government constructed four laws concerning energy and carbon reduction in order to drive the green energy industry; furthermore, it plans to reduce current carbon emission benchmarks. Nevertheless, statistical analysis found that in the last decade, energy intensive industries have presented structural unbalance regarding energy consumption, CO₂ emissions, energy intensity, contributions to the GDP, and product value. Industries in the industrial sector have high energy consumption, high carbon emissions, and increase total domestic consumption and carbon emissions, which have disproportionate contributions to industrial added value; nevertheless, the government continues to approve investments for such energy intensive industries, and results in continuous increases in energy consumption and carbon emissions. This contradictory phenomenon indicates that newly industrialized countries rely on a manufacturing economic structure, which is difficult to adjust and violates the trends of a global low-carbon economy. Hence, the government must examine and adjust such unbalanced industrial structures, where such adjustments are executed in a fair and just manner, and encourage the development of high value-added measures for low-carbon manufacturing and service sectors to become equal with competitors in a global economy.     

推进信息化领域的行业融合 促进智能电网发展

针对智能电网融合了电网、通信、IT、新材料等科技成果,指出只有行业高度融合,才能真正建设好智能电网。介绍了电力行业在智能电网方面做的大量工作,提出应加强行业间的交流与融合、提升信息化水平、促进智能电网发展,并给出了相应的建议。     

Energy requirements of output of the New Zealand economy, 1976–1977

This paper describes the methodology, data sources and results of an input-output energy analysis of the 1976–1977 inter-industry survey of the New Zealand economy. Results are tabulated (at 29-sector and 178-sector levels of detail) as the total energy intensities of output, for the following energy supply industries: coal mining and natural gas production; petroleum refining, oil and coal products; electricity, state supply; electricity, local body supply; and gas manufacture and distribution. The disposition of energy embodied in outputs to final demand sectors of the economy is discussed.     

Grey relation performance correlations among economics,energy use and carbon dioxide emission in Taiwan

This study explores the inter-relationships among economy, energy and CO₂ emissions of 37 industrial sectors in Taiwan in order to provide insight regarding sustainable development policy making. Grey relation analysis was used to analyse the productivity, aggregate energy consumption, and the use of fuel mix (electricity, coal, oil and gas) in relation to CO₂ emission changes. An innovative evaluative index system was devised to explore grey relation grades among economics, energy and environmental quality. Results indicate that a rapid increase in electricity generation during the past 10 years is the main reason for CO₂ emission increase in Taiwan. The largest CO₂ emitting sectors include iron and steel, transportation, petrochemical materials, commerce and other services. Therefore, it is important to reduce the energy intensity of these sectors by energy conservation, efficiency improvement and adjustment of industrial structure towards high value-added products and services. Economic growth for all industries has a more significant influence, than does total energy consumption, on CO₂ emission increase in Taiwan. It is also important to decouple the energy consumption and production to reduce the impacts of CO₂ on economic growth. Furthermore, most of the sectors examined had increased CO₂ emissions, except for machinery and road transportation. For high energy intensive and CO₂ intensive industries, governmental policies for CO₂ mitigation should be directed towards low carbon fuels as well as towards enhancement of the demand side management mechanism, without loss of the nation's competitiveness.     

Purchased energy and policy impacts in the US manufacturing sector

The US manufacturing sector, which consists of industries that produce durable and nondurable goods, accounts for about 30 % of all the final energy consumed in the country. In this study, manufacturing sector data coming primarily from the Annual Survey of Manufacturers are used to estimate the total impact of one mode of energy efficiency policy, market persuasion programs, on aggregate electricity consumption and energy expenditures. Using a panel model consisting of data for 184 industries, the findings indicate that the cumulative effects since 2002 of this policy mode is a reduction in 2010 electricity consumption of 5.4 %, of electricity expenditures of 2.4 %, and of all other fuel expenditures of 5.7 %. These estimates are derived after controlling for changes in output, other production inputs, and economic conditions. Particular attention in this study is given to the effects of a permanent shift in demand, and temporary business cycle shock, on model external validity.     

Measuring the efficiency of energy-intensive industries across European countries

This study evaluates the energy efficiency trends of five energy-intensive industries in 23 European Union (EU) countries over the period 2000–2009. In particular, the performance of the construction, electricity, manufacturing, mining and quarrying, and transport sectors is examined. The analysis is based on Data Envelopment Analysis (DEA) combined with the Malmquist Productivity Index (MPI), which allows for distinctions between efficiency and technology changes over time. At the second stage of the analysis, cross-classified multilevel modelling is applied to analyse the main drivers behind efficiency performance using a number of sector and country characteristics. Based on DEA results, an overall improvement in efficiency is observed in all sectors over the period. The decomposition of the MPI indicates that technology change is primarily responsible for the improvements achieved in most sectors. The results obtained by the cross-classified model show, among other things, that the high electricity prices, energy taxes, and market share of the largest generator in the electricity market have a negative effect on industrial energy efficiency.     

Retrospective and prospective decomposition analysis of Chinese manufacturing energy use and policy implications

AimsThe industrial sector dominates the China's total energy consumption, accounting for about 70% of energy use in 2010. Hence, this study aims to investigate the development path of China's industrial sector which will greatly affect future energy demand and dynamics of not only China, but the entire world.ScopeThis study analyzes energy use and the economic structure of the Chinese manufacturing sector. The retrospective (1995–2010) and prospective (2010–2020) decomposition analyses are conducted for manufacturing sectors in order to show how different factors (production growth, structural change, and energy intensity change) influenced industrial energy use trends in China over the last 15 years and how they will do so up to 2020.ConclusionsThe forward looking (prospective) decomposition analyses are conducted for three different scenarios. The scenario analysis indicates that if China wants to realize structural change in the manufacturing sector by shifting from energy-intensive and polluting industries to less energy-intensive industries, the value added average annual growth rates (AAGRs) to 2015 and 2020 should be more in line with those shown in scenario 3. The assumed value added AAGRs for scenario 3 are relatively realistic and are informed by possible growth that is foreseen for each subsector.     

Interactions of energy technology development and new energy exploitation with water technology development in China

Interactions of energy policies with water technology development in China are investigated using a hybrid input-output model and scenario analysis. The implementation of energy policies and water technology development can produce co-benefits for each other. Water saving potential of energy technology development is much larger than that of new energy exploitation. From the viewpoint of proportions of water saving co-benefits of energy policies, energy sectors benefit the most. From the viewpoint of proportions of energy saving and CO₂ mitigation co-benefits of water technology development, water sector benefits the most. Moreover, economic sectors are classified into four categories concerning co-benefits on water saving, energy saving and CO₂ mitigation. Sectors in categories 1 and 2 have big direct co-benefits. Thus, they can take additional responsibility for water and energy saving and CO₂ mitigation. If China implements life cycle materials management, sectors in category 3 can also take additional responsibility for water and energy saving and CO₂ mitigation. Sectors in category 4 have few co-benefits from both direct and accumulative perspectives. Thus, putting additional responsibility on sectors in category 4 might produce pressure for their economic development.     

An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors

This paper introduces an integrated approach based on data envelopment analysis (DEA), principal component analysis (PCA) and numerical taxonomy (NT) for total energy efficiency assessment and optimization in energy intensive manufacturing sectors. Total energy efficiency assessment and optimization of the proposed approach considers structural indicators in addition conventional consumption and manufacturing sector output indicators. The validity of the DEA model is verified and validated by PCA and NT through Spearman correlation experiment. Moreover, the proposed approach uses the measure-specific super-efficiency DEA model for sensitivity analysis to determine the critical energy carriers. Four energy intensive manufacturing sectors are discussed in this paper: iron and steel, pulp and paper, petroleum refining and cement manufacturing sectors. To show superiority and applicability, the proposed approach has been applied to refinery sub-sectors of some OECD (Organization for Economic Cooperation and Development) countries. This study has several unique features which are: (1) a total approach which considers structural indicators in addition to conventional energy efficiency indicators; (2) a verification and validation mechanism for DEA by PCA and NT and (3) utilization of DEA for total energy efficiency assessment and consumption optimization of energy intensive manufacturing sectors.     

The relationship between electricity consumption,electricity prices and GDP in Pakistan

This study analyzes the relationship among electricity consumption, its price and real GDP at the aggregate and sectoral level in Pakistan. Using annual data for the period 1960–2008, the study finds the presence of unidirectional causality from real economic activity to electricity consumption. In particular, growth in output in commercial, manufacturing and agricultural sectors tend to increase electricity consumption, while in residential sector, growth in private expenditures is the cause of rising electricity consumption. The study concludes that electricity production and management needs to be better integrated with overall economic planning exercises. This is essential to avoid electricity shortfalls and unplanned load shedding.