Domestic Electricity Consumption Research Articles

Smart meters and energy savings in Italy: Determining the effectiveness of persuasive communication in dwellings

To secure a sustainable energy development in the residential sector, attitudes and human behavior need to be modified toward more efficient and conscious energy usage. The goal of this research is to assess evaluations and to test the effectiveness in reducing domestic electricity consumption. The aim of the smart monitoring system we evaluate is to provide households with a user-friendly tool that improves awareness of energy behavior in homes, enabling better management via the visualization of consumption and persuasive tailored information on domestic electricity use. In our study, the system was tested on 31 Italian families selected among volunteers all over Italy, participating to the first trial phase from October 2012 to November 2013. A combination of persuasive communication strategies such as graphical real-time and historical feedback based on real data and comparison tools to encourage competitiveness against “similar” households were provided to users through a domestic user-friendly interface. In addition, personalized energy saving prompts were sent via web-newsletters to trial users. The study concludes that energy related persuasive communication is effective in reducing electricity consumption in dwellings on average −18% and up to −57%.

Antecedents and consequences of monitoring domestic electricity consumption

Despite evidence that monitoring domestic electricity usage can reduce consumption, there is currently little information on what factors motivate people to monitor their consumption. The present research used an augmented version of the theory of planned behavior as a framework for understanding householders' intentions. Participants (N = 346) completed a questionnaire measuring their beliefs about electricity use and monitoring consumption, their environmental behavior, and concern about climate change. Regression revealed that the primary predictors of intentions to monitor consumption were perceived behavioral control, attitudes toward monitoring, past behavior, descriptive, and subjective norms. In addition, we developed a modified home electricity monitor that legged when participants looked at their consumption. A subset of participants (n = 38) were given a monitor for three months. Participants looked at the monitor relatively frequently during the first week but usage rapidly declined. There was, however, some evidence that participants found the monitor beneficial.

Is social norms marketing effective?

Purpose – The purpose of this paper is to present details of a large-scale experiment that evaluated the impact of communicating two types of feedback to householders regarding their domestic electricity consumption: feedback on their own consumption and feedback of both their own consumption and that of others in their locality. Design/methodology/approach – Digital technologies were used to automatically measure and communicate the electricity consumption of 316 UK residents for a period of 16 weeks. Participants were randomly assigned to one of three experimental conditions: one involving no feedback; one involving feedback about a household's own usage, and one involving a household's own usage plus social norms feedback (the average consumption of others in the locality). At the end of the study, a selection of participants took part in interviews or focus groups. Findings – Both types of feedback (individual and individual-plus-social-norms) led to reductions in consumption of about 3 per cent. Those receiving social norms feedback were significantly more likely to engage with the information provided. However, the social norms information had no additional impact on consumption. Survey and interview data confirmed that participants from both conditions had been encouraged to adopt new energy-saving practices. The study concludes that near real-time individual feedback can be sufficient for usage reduction if it is provided in a historical format. It also suggests that the impact of social norms information may previously have been confounded with that of individual feedback. Originality/value – This is the first time that a controlled experiment in the field of domestic electricity consumption has compared the impact of real-time social norm information with that of information that only contains individual household usage.

Electricity Consumption, Labor Force and GDP in Turkey: Evidence From Multivariate Granger Causality

This article attempts to examine the dynamic relationship between gross domestic product (GDP), electricity consumption, and labor force in Turkey over the period 1980–2008. Applying the bounds test approach to cointegration developed by Pesaran et al. (2001), we found that there was a long-run relationship between electricity consumption, GDP, and labor force when electricity consumption and labor force are the dependent variable. Using four long-run estimators, we also concluded that electricity consumption has a positive and a statistically significant impact on Turkey's economic growth. The coefficient on labor force is positive and statistically significant at the 1% level where a 1% increase in labor force generates a 1.22% and 2.52% increase in electricity consumption, respectively. Turning to the model where labor force is taken as a dependent variable, the coefficient on income is positive and statistically significant for all estimators with a 1% increase in real income generating between 0.23 and 2.77% increase in employment. We concluded that there exists bidirectional Granger causality between electricity consumption and GDP which confirms the feedback hypothesis. On the other hand, there is neutrality between labor force and electricity consumption. When we examine the long-run results, the coefficient on the lagged error correction term which indicates the speed of the adjustment process to restore equilibrium following a disturbance in the long-run equilibrium relationship is significant in the electricity consumption equation at the 5% level. We concluded that almost 5% of the disequilibrium of the previous year's shocks adjusts back to the long run equilibrium—an indication that once shocked convergence to equilibrium is slow.

Analysis and modeling of active occupancy of the residential sector in Spain: An indicator of residential electricity consumption

The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy.

Quantifying the domestic electricity consumption for air-conditioning due to urban heat islands in hot arid regions

Authoritative reports show that building electricity consumption can increase steadily once temperature values within urban regions exceed their rural values. This study first assesses the role of higher temperatures in the variation of Bahrain’s domestic electricity consumption for air-conditioning, using the cooling degree days (CDD) as a quantitative index. It then examines how this consumption is affected by urban features. The assessment is performed using established scenarios of the urban heat island (UHI), advanced statistics of building stock and data for electricity consumption. Simple regression equations are developed to predict the effects of temperature alterations on the electricity consumption. This work shows that the variation in CDD is a direct result of modifications to the urban microclimate. The annual total urban CDD value is up to 17% higher than the rural CDD value. A sharp increase of up to 10% in electricity consumption for air-conditioning occurs in urban regions from April to October. Estimates of the electricity demand for dense urban centres that are based on air temperature values measured in open areas, such as airports, can cause an error of almost 6%. The developed statistical equations can be a valuable and convenient method of quantifying the domestic electricity consumption for air-conditioning in Bahrain and other Gulf countries.

Simulation of a stand-alone residential PEMFC power system with sodium borohydride as hydrogen source

Catalytic hydrolysis of sodium borohydride (NaBH4) has been investigated as a method to generate hydrogen for fuel cell applications. The high purity of the generated hydrogen makes this process a potential source of hydrogen for polymer electrolyte membrane fuel cells (PEMFCs). In this paper, a PEMFC power system employing a NaBH4 hydrogen generator is designed to supply continuous power to residential power applications as stand-alone loads and simulated using Matlab/Simulink software package. The overall system is sized to meet a real end-use load, representative of standard European domestic medium electric energy consumption, over a 1-week period. Supervisory control strategies are proposed to manage the hydrogen generation and storage, and the power flow. Simulation results show that the proposed supervisory control strategies are effective and the NaBH4–PEMFC power system is a technologically feasible solution for stand-alone residential applications.

Dynamic Seasonality in Time Series

In this research, a new class of time series models capturing dynamic seasonality is introduced. Unlike traditional seasonal models which focus mainly on the mean process, our approach can accommodate dynamic seasonality in the mean and variance processes. This feature allows us to perform statistical inference of the dynamic seasonality in heteroskedastic time series models. Quasi-maximum likelihood estimation and a model selection procedure are adopted. Simulation study is carried out to evaluate the efficiency of the estimation method. In the empirical examples, our model outperforms deterministic seasonality model and Holt-Winter method in forecasting the monthly domestic electricity consumption in Hong Kong and the intraday stock return variation in out-of-sample analysis.

Washing when the sun is shining! How users interact with a household energy management system

To make optimal use of sustainable energy, domestic electricity consumption should shift to match local supply conditions. Energy management systems (EMS) are a new sustainable technology that can help to disrupt consumers’ habits concerning electricity consumption, whilst reinforcing desired behaviours. This research examined the factors that influence the likelihood that people will shift their electricity consumption to match sustainable supply. Twenty-one interviews were conducted with households who had used the EMS ‘Smart Wash’ for several months. The findings showed that the likelihood of behaviour change is influenced by a combination of the user's motivation, specific contextual factors and the design of the EMS. Based on these results, several recommendations are given for the future design of EMSs. Practitioner Summary: Energy management systems (EMS) are a new technology that encourages people to shift electricity consumption to match local solar supply. Interviews among users of an EMS showed that the likelihood of behaviour change is influenced by the combination of the user's motivation, contextual factors and the EMS design.

Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: A comparative case study from China's cities

Urbanization process involving increased population size, spatially extended land cover and intensified economic activity plays a substantial role in anthropogenic environment changes. Remotely sensed nighttime lights datasets derived from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) provide a consistent measure for characterizing trends in urban sprawl over time (Sutton, 2003). The utility of DMSP/OLS imagery for monitoring dynamics in human settlement and economic activity at regional to global scales has been widely verified in previous studies through statistical correlations between nighttime light brightness and demographic and economic variables (Elvidge et al., 2001; Ghosh et al., 2010). The quantitative relationship between long-term nighttime light signals and urbanization variables, required for extensive application of DMSP/OLS data for estimating and projecting the trajectory of urban development, however, are not well addressed for individual cities at a local scale. We here present analysis results concerning quantitative responses of stable nighttime lights derived from time series of DMSP/OLS imagery to changes in urbanization variables during 1994–2009 for more than 200 prefectural-level cities and municipalities in China. To identify the best-fitting model for nighttime lights-based measurement of urbanization processes with different development patterns, we comparatively use three regression models: linear, power-law and exponential functions to quantify the long-term relationships between nighttime weighted light area and four urbanization variables: population, gross domestic product (GDP), built-up area and electric power consumption. Our results suggest that nighttime light brightness could be an explanatory indicator for estimating urbanization dynamics at the city level. Various quantitative relationships between urban nighttime lights and urbanization variables may indicate diverse responses of DMSP/OLS nighttime light signals to anthropogenic dynamics in urbanization process in terms of demographic and economic variables. At the city level, growth in weighted lit area may take either a linear, concave (exponential) or convex (power law) form responsive to expanding human population and economic activities during urbanization. Therefore, in practice, quantitative models for using DMSP/OLS data to estimate urbanization dynamics should vary with different patterns of urban development, particularly for cities experiencing rapid urban growth at a local scale.

Keeping energy visible? Exploring how householders interact with feedback from smart energy monitors in the longer term

This paper reports on how, over a 12-month period, UK householders interacted with feedback on their domestic electricity consumption in a field trial of real time displays or smart energy monitors. Drawing on the findings of 11 follow-up qualitative interviews with householders involved in a ‘Visible Energy Trial’, the paper suggests that: (i) over time, smart energy monitors gradually become ‘backgrounded’ within normal household routines and practices; (ii) the monitors do increase householders’ knowledge of and confidence about the amount of electricity they consume; (iii) but, beyond a certain level and for a wide variety of reasons, the monitors do not necessarily encourage or motivate householders to reduce their levels of consumption; and (iv) once equipped with new knowledge and expertise about their levels of electricity consumption, household practices may become harder to change as householders realise the limits to their energy saving potential and become frustrated by the absence of wider policy and market support. The paper concludes by reflecting on the policy and research implications of these findings in relation to future transition pathways to a low-carbon economy.

Characterising domestic electricity consumption patterns by dwelling and occupant socio-economic variables: An Irish case study

This paper examines the influence of dwelling and occupant characteristics on domestic electricity consumption patterns by analysing data obtained from a smart metering survey of a representative cross section of approximately 4200 domestic Irish dwellings. A multiple linear regression model was applied to four parameters: total electricity consumption, maximum demand, load factor and time of use (ToU) of maximum electricity demand for a number of different dwelling and occupant socio-economic variables. In particular, dwelling type, number of bedrooms, head of household (HoH) age, household composition, social class, water heating and cooking type all had a significant influence over total domestic electricity consumption. Maximum electricity demand was significantly influenced by household composition as well as water heating and cooking type. A strong relationship also existed between maximum demand and most household appliances but, in particular, tumble dryers, dishwashers and electric cookers had the greatest influence over this parameter. Time of use (ToU) for maximum electricity demand was found to be strongly influenced by occupant characteristics, HoH age and household composition. Younger head of households were more inclined to use electricity later in the evening than older occupants. The appliance that showed the greatest potential for shifting demand away from peak time use was the dishwasher.

Climate Injustice: CO2 from Domestic Electricity Consumption and Private Car Use by Income Decile

Environmental justice is primarily concerned with uneven distribution of environmental harms and with the consequences such inequality often has for individual and community well-being, development, and growth. Recent expansion in quantity and improvement in quality of data on current and historic greenhouse gas (GHG) emission levels by country has drawn attention to differentiated national responsibilities for the intensification of the atmosphere's greenhouse effect and, concomitantly, for global warming. This shift is pertinent for environmental justice, a field that tended in the past to focus more on the uneven distribution of environmental harms than on responsibility for initially causing them. Building on the new sensitivity to differentiated responsibility for climate change, this article focuses on a hitherto understudied field: differences in GHG emissions between populations within countries. Using Israel as a case study, and focusing on GHG from domestic electricity consumption (DEC) and private vehicle use (PVU), it looks at emissions by income decile. Results suggest that individuals belonging to the top income decile are responsible for per-capita emissions that are approximately 25 times higher than those of individuals belonging to the bottom decile, and that carbon inequality between the top and bottom deciles can sometimes amount to over four times the monetized consumer inequality between them. Recognition of GHG emission as multiplier of socio-economic inequalities is essential for the design and implementation of ambitious, workable, and fair corrective climate policies.

The impact of consumers’ feedback preferences on domestic electricity consumption

Despite all initiatives introduced for maximizing energy savings domestic energy consumption is in constant increase. However, very little investigation has been carried out on the integration of household’ consumption trends, the parameters influencing them and the characteristics of the provided feedback. 2000 Swedish households were included in this study. Electricity consumption data for apartments and houses has been analyzed for a 4year period as well as possible household socio-economic factors affecting it. The data has been further compared to other households located in different cities in Sweden. The effects of the different ways of presenting feedback used for the different households groups have also been evaluated. From the results obtained from the questionnaire used, several households’ characteristics were proposed together with consumers’ preferences to be considered during the development of feedback. Web based feedback resulted in being the most effective (when compared to display and bills), achieving electricity savings of approximately 15% within households that visited the web-site. The monthly income is amongst the most influential factors determining electricity consumption although only in high and low income groups.

Insights into the design, use and implementation of home energy management systems

Between 2008 and 2011, three different home energy management systems (HEMS)that give feedback on energy consumption were implemented in households in the Netherlands. Home energy management systems are defined as intermediary devices that can visualise, monitor and/or manage domestic gas and/or electricity consumption. Through a series of questionnaires, interviews, focus groups and usability tests, a wide range of knowledge was gathered on factors influencing the effectiveness of the three systems. The resulting insights were structured with the help of a conceptual model, which outlines the various interactions between users, energy monitors, and their social and physical environments. The insights provide a broad spectrum of factors to be considered for the successful design and implementation of home energy management systems. This paper aims to provoke an open discussion to ascertain the value of the different factors and further the development of effective and useful HEMS.

An evaluation of domestic solar energy potential in Taiwan incorporating land use analysis

Solar energy is widely regarded as a major renewable energy source, which in future energy systems will be able to contribute to the security of energy supply and the reduction of CO 2 emissions. This study combined an evaluation of solar energy resources in Taiwan with land use analysis, which allows the potentials and restrictions of solar energy exploitation resulting from local land use conditions to be considered. The findings unveiled in this study indicate that photovoltaic electricity generation and solar water heating have the potential of producing 36.1 and 10.2 TWh of electricity and thermal energy annually in Taiwan, accounting for 16.3% and 127.5% of the total domestic consumption of electricity and energy for household water heating in 2009, respectively. However, the exploited solar photovoltaic power generation in 2009 accounted for only 0.02% of total potential in Taiwan, while the exploited solar water heating accounted for 11.6% of total potential. Market price and investment incentive are the dominant factors that affect market acceptance of solar energy installation in Taiwan. The administrative barriers to the purchase and transmission of electricity generated from renewable energy sources have to be removed before the potential contribution of solar energy can be realized.

The effect of appliance energy efficiency improvements on domestic electric loads in European households

Across Europe domestic electricity consumption is on the rise. In an attempt to counter this increase, various initiatives have been introduced to promote the replacement of less energy-efficient appliances with more efficient ones. Whilst the likely aggregate effect of such measures over long time periods has been modelled extensively, little is known about the affect that a change to higher efficiency appliances will have on the electrical demand profile of individual households at higher temporal resolutions. To address this issue a means by which established approaches to detailed electrical demand modelling can be adapted to simulate the improvements in the efficiency of appliances is elaborated in this paper. A process is developed by which low-resolution empirical appliance demand data can be transformed to produce high-resolution electrical demand data for different periods in the year, factoring in improvements in appliance performance. The process is applied to simulate the effects a changeover to more energy-efficient appliances would have on the minute resolution demand profiles of a group of households. Results indicate that improving the energy-efficiency of appliances in households leads to a significant reduction in electrical energy requirements but does not appear to have a significant affect on the peak electrical demand.

The causal relationship between electricity consumption and economic growth ina Gaming and Tourism Center: The case of Macao SAR, the People's Republic ofChina.

A number of Asian cities decided to establish gaming and resort facilities in order to capitalize on the growing number of gamblers and their family members in Asia. In doing so, they expect to sustain economic growth but, on the other hand, will consume a considerable amount of energy. Nevertheless, the causal relationship between economic growth and electricity consumption in this type of service-oriented territories has never been investigated. Using the historical data obtained from the Government of Macao SAR, we found that electricity consumption and economic growth in terms of gross domestic product are co-integrated for the period of 1999 Quarter 1–2008 Quarter 4. Moreover, vector error correction (VEC) models indicated a lack of short-run relationships but showed that there was a long-run equilibrium relationship between electricity consumption and gross domestic product. The accuracy of VEC models was assessed by using the mean squared error and the mean absolute error. The error analysis shows that VEC models reproduced time series of gross domestic product and electricity consumption in difference form accurately.

In-use stock analysis using satellite nighttime light observation data

Nighttime light observation data are considered an economic indicator because of their strong correlation with such aspects of human activity as population, gross domestic product (GDP) and electricity consumption. We are developing an in-use stock analysis method that uses nighttime light observation data. In this study, we developed new sets of data for 1999, 2000, 2003 and 2006 with which to analyze temporal changes. The relationship between the in-use stock of copper and the net amount of nighttime light were correlated. The result shows that this analysis method can be used for evaluating the in-use stock in an area where statistical data are incomplete. We used the approach to estimate the in-use stocks of copper in Asian countries.

Nexus between Electricity Demand and Gross Domestic Product in Sri Lanka: A Cointegration Analysis

Electricity has become one of the most essential factors in economic growth in Sri Lanka. This paper applies a simple econometric model to identify the causal relationship between Gross Domestic Product (GDP) and electricity consumption in industrial and commercial sectors of Sri Lanka for the period 1979 – 2006. A causal relationship between GDP and electricity demand was found. Engle - Granger two-step procedure for cointegrating regressions was employed to estimate the short run dynamics, as well as the long run equilibrium or cointegrating relationship between electricity demand and GDP. A unique equilibrium relationship was found. According to the long run relationship, when the GDP increases by one million rupees, the electricity demand goes up by 1.3 Giga Watt hours. The speed of adjustment coefficient is 73 percent and this shows that when the GDP deviates from long-run equilibrium, the electricity demand variable will return to its long term equilibrium at a rate of 73 percent.