A structural VAR analysis of electricity consumption and real GDP : evidence from the G7 countries

In this paper, we depart from the literature on electricity consumption–real GDP in that for the first time we examine the reaction of real GDP to shocks in electricity consumption. To achieve this goal, we use the structural vector autoregressive (SVAR) model and examine the impact of electricity consumption shocks on real GDP for the G7 countries. We find that except for the USA, electricity consumption has a statistically significant positive impact on real GDP over short horizons. This finding implies that except for the USA, electricity conservation policies will hurt real GDP in the G7 countries.

Multivariate granger causality between electricity consumption, exports and GDP : Evidence from a panel of Middle Eastern countries

This paper examines the causal relationship between electricity consumption, exports and gross domestic product (GDP) for a panel of Middle Eastern countries. We find that for the panel as a whole there are statistically significant feedback effects between these variables. A 1 per cent increase in electricity consumption increases GDP by 0.04 per cent, a 1 per cent increase in exports increases GDP by 0.17 per cent and a 1 per cent increase in GDP generates a 0.95 per cent increase in electricity consumption. The policy implications are that for the panel as a whole these countries should invest in electricity infrastructure and step up electricity conservation policies to avoid a reduction in electricity consumption adversely affecting economic growth. Further policy implications are that for the panel as a whole promoting exports, particularly non-oil exports, is a means to promote economic growth and that expansion of exports can be realized without having adverse effects on energy conservation policies.

The electricity consumption and GDP nexus for the Fiji Islands

Fiji is a small open island economy dependent on energy for its growth and development; hence, the relationship between energy consumption and economic growth is crucial for Fiji's development. In this paper, we investigate the nexus between electricity consumption and economic growth for Fiji within a multivariate framework through including the labour force variable. We use the bounds testing approach to cointegration and find that electricity consumption, GDP and labour force are only cointegrated when GDP is the endogenous variable. We use the Granger causality F-test and find that in the long-run causality runs from electricity consumption and labour force to GDP, implying that Fiji is an energy dependent country and thus energy conservation policies will have an adverse effect on Fiji's economic growth.

Electricity consumption, employment and real income in Australia evidence from multivariate Granger causality tests

This paper examines the relationship between electricity consumption, employment and real income in Australia within a cointegration and causality framework. We find that electricity consumption, employment and real income are cointegrated and that in the long-run employment and real income Granger cause electricity consumption, while in the short run there is weak unidirectional Granger causality running from income to electricity consumption and from income to employment.

Electricity consumption in G7 countries : a panel cointegration analysis of residential demand elasticities

This article applies recently developed panel unit root and panel cointegration techniques to estimate the long-run and short-run income and price elasticities for residential demand for electricity in G7 countries. The panel results indicate that in the long-run residential demand for electricity is price elastic and income inelastic. The study concludes that from an environmental perspective there is potential to use pricing policies in the G7 countries to curtail residential electricity demand, and thus curb carbon emissions, in the long run.

A data mining framework for electricity consumption analysis from meter data

This paper presents a novel data mining framework for the exploration and extraction of actionable knowledge from data generated by electricity meters. Although a rich source of information for energy consumption analysis, electricity meters produce a voluminous, fast-paced, transient stream of data that conventional approaches are unable to address entirely. In order to overcome these issues, it is important for a data mining framework to incorporate functionality for interim summarization and incremental analysis using intelligent techniques. The proposed Incremental Summarization and Pattern Characterization (ISPC) framework demonstrates this capability. Stream data is structured in a data warehouse based on key dimensions enabling rapid interim summarization. Independently, the IPCL algorithm incrementally characterizes patterns in stream data and correlates these across time. Eventually, characterized patterns are consolidated with interim summarization to facilitate an overall analysis and prediction of energy consumption trends. Results of experiments conducted using the actual data from electricity meters confirm applicability of the ISPC framework.

Does electricity consumption panel Granger cause GDP? A new global evidence

The goal of this paper is to undertake a panel data investigation of long-run Granger causality between electricity consumption and real GDP for seven panels, which together consist of 93 countries. We use a new panel causality test and find that in the long-run both electricity consumption and real GDP have a bidirectional Granger causality relationship except for the Middle East where causality runs only from GDP to electricity consumption. Finally, for the G6 panel the estimates reveal a negative sign effect, implying that increasing electricity consumption in the six most industrialised nations will reduce GDP. © 2010 Elsevier Ltd. All rights reserved.

Electricity consumption–real GDP causality nexus: Evidence from a bootstrapped causality test for 30 OECD countries

The goal of this paper is to examine any causal effects between electricity consumption and real GDP for 30 OECD countries. We use a bootstrapped causality testing approach and unravel evidence in favour of electricity consumption causing real GDP in Australia, Iceland, Italy, the Slovak Republic, the Czech Republic, Korea, Portugal, and the UK. The implication is that electricity conservation policies will negatively impact real GDP in these countries. However, for the rest of the 22 countries our findings suggest that electricity conversation policies will not affect real GDP.

Can the electricity market be characterised by asymmetric behaviour?

In this paper, we test for asymmetric behaviour of industrial and residential electricity demand for the G7 countries, using the entropy-based test for symmetry suggested by [Racine, J., and Maasoumi, E., 2007. A versatile and robust metric entropy test of time-reversibility, and other hypotheses. Journal of Econometrics 138(2), 547–567; Racine, J., and Maasoumi, E., 2008. A robust entropy-based test of asymmetry for discrete and continuous processes. Econometric Reviews 28, 246–261], the Triples test of [Randles, R., Flinger, M., Policello, G., and Wolfe, D., 1980. An asymptotically distribution-free test for symmetry versus asymmetry. Journal of the American Statistical Association 75, 168–172] and the [Bai, J., and Ng, S., 2001. A consistent test for conditional symmetry in time series models. Journal of Econometrics 103, 225–258] test for conditional symmetry. Using data that spans over three decades, we find overwhelming evidence of conditional symmetry of residential and industrial electricity consumption. This finding implies that the use of econometric tests based on linear data generating processes is credible.

Energy consumption at the state level: the unit root null hypothesis from Australia

In this paper, our goal is to examine the unit root null hypothesis in energy consumption for Australian states and territory. We consider sectoral energy consumption for Australia and its six states and one territory using time series data for the period 1973-2007. This is the first study that does this. Generally, except for some cases in South Australia, we find strong support that shocks to energy consumption have a temporary effect on energy consumption in Australia. © 2009 Elsevier Ltd. All rights reserved.

A study on energy performance of hotel buildings in Singapore

This paper presents a study on energy performance of Singapore's hotel buildings. Energy consumption data and other pertinent information were collected from 29 quality hotels through a national survey. Building features and operational characteristics contributing to the variations in hotel energy performance were discussed. The annual average total energy use intensity (EUI) in these hotels is 427 kWh/m2. Electricity and gas are used in all sampled hotels, and some hotels also use diesel to power standby generator or hot water boiler. We also investigated relationships between electricity consumption and number of occupied rooms in individual hotels; the weak correlations found indicate it is necessary to improve energy management when occupancy rate is low. Besides, Pearson correlations between hotel energy use intensity and possible explanatory indicators revealed that three-star hotels differ from high class establishments in energy use. Worker density and years after the last major energy retrofit were also found to be highly correlated to hotel building energy use intensity. Also discussed in this paper is the effect of weather conditions on electricity consumption of the hotels.

From design for ecologically sustainability to facilities management through building intelligence and knowledge management

Ecological sustainability basically concerns environmental protection and social benefits. An ecologically sustainable development is based upon reduced energy usage, increased efficiency, and upheld social responsibility; and it should be properly evaluated by financial, environmental and social aspects. Council House 2 (CH2) is claimed to change the way of Australia approaches in ecologically sustainable design and construction. This is the ‘Six-Star design and built’ green star facility assessed by the Green Building Council of Australia (GBCA), and the 10-story city council building was completed and opened in 2006, totally A$11.3 million was invested for the sustainability features. CH2 protects the environment, when it compares with the old council house, and is expected to reduce electricity consumption by 85%; reduce gas consumption by 87%; produce only 13% of the emissions; and reduce water mains supply by 72%. In this paper, the author examines its design reports and the researches paper, in the form of knowledge base, to case-study how the sustainability, effectiveness and efficiency of CH2 work. By leveraging the existing CH2 sustainability knowledge, design and building professions can learn and imitate it in further ‘green’ design without ‘re-inventing the wheel’; facilities executives can also use the existing knowledge to identify steps to boost up the facilities’ operating efficiency.

Type-aware task placement in geo-distributed data centers with low OPEX using data center resizing

With the rising demands on cloud services, the electricity consumption has been increasing drastically as the main operational expenditure (OPEX) to data center providers. The geographical heterogeneity of electricity prices motivates us to study the type-aware task placement problem over geo-distributed data centers. With the consideration of the diversity of user requests and server clusters in modern data centers, we formulate an optimization problem that minimizes OPEX while guaranteeing the quality-of-service, i.e., the expected response time of tasks. Furthermore, an efficient solution is designed for this formulated problem. The experimental results show that our proposal achieves much higher cost-efficiency than the greedy algorithm and much approaches the optimal results. © 2014 IEEE.

Optimal task placement with QoS constraints in geo-distributed data centers using DVFS

 With the rising demands on cloud services, the electricity consumption has been increasing drastically as the main operational expenditure (OPEX) to data center providers. The geographical heterogeneity of electricity prices motivates us to study the task placement problem over geo-distributed data centers. We exploit the dynamic frequency scaling technique and formulate an optimization problem that minimizes OPEX while guaranteeing the quality-of-service, i.e., the expected response time of tasks. Furthermore, an optimal solution is discovered for this formulated problem. The experimental results show that our proposal achieves much higher cost-efficiency than the traditional resizing scheme, i.e., by activating/deactivating certain servers in data centers.