Appliance Ownership Research Articles

Modelling of rural electrical appliances saturation in developing countries to project their electricity demand: A case study of sub-Saharan Africa

Rural electrification projects are mostly listed as a priority in developing countries due to the numerous benefits it brings to improve people’s quality of life. The starting point for these projects is the accurate estimation of the households’ energy demand, but the large amount of resources that requires the on-site data collection makes this process unattractive to investors. This paper brings a potential solution to that matter, presenting a methodology for modelling the appliances saturation of rural households in developing countries to project their electricity demand. Based on a statistical approach, and including training data from more than 1,100 household samples from Nigeria and Ethiopia, the correlation between household survey data of saturation rates of the most common electricity-consuming appliances in developing countries and different socio-economic, demographic and geographic variables are investigated. Its accuracy is tested using other sets of validation data at a household, state, and national level. Finally, the results are projected using a Geographic Information Systems approach for identifying possible sites to be electrified. The high potential of using this approach for projecting the appliances saturation rates for rural areas was proven by obtaining a good overall accuracy in the results. As expected, the errors obtained at a household level were bigger than at a state or national level, these deviations are attributed to the presence of outliers due to the human behaviour incidence at household scale; which also affects the correlation patterns between the appliances ownership and evident socioeconomic factors.

Household appliance ownership and income inequality: Evidence from micro data in China

As the residential sector is becoming increasingly important in the total energy consumption and appliance ownership is a significant but under-examined driver, this study investigates the relationship between income inequality and appliance ownership using panel data from the China Health and Nutrition Survey (CHNS). We find that income inequality has negative impacts on appliance penetration rate across specifications, except for the initial development stage. On average, households start adopting air conditioners at a threshold of over 60,000 (2011 RMB) based on annual income, much higher than TV, fridge and washer (8500–9000 RMB). The empirical results validate the S-shape curve of appliance established in the literature. To understand the magnitude of the impact and policy implications, we further simulate the impact of poverty alleviation and the penetration paths under inclusive versus exclusive income growth. Our results demonstrate that current poverty line is too low to achieve appliance adoption – a signal for modern life-styles. In addition, a more inclusive growth path could lead to much higher penetration for regions that have relatively low growth rate.

How does slum rehabilitation influence appliance ownership? A structural model of non-income drivers

This study explores the effect of slum rehabilitation on appliance ownership and its implications on residential electricity demand. The low-income scenario makes it unique because the entire proposition is based on the importance of non-income drivers of appliance ownership that includes effects of changing the built environment (BE), household practices (HP) and appliances characteristics (AC). This study demonstrates quantitatively that non-income factors around energy practices influence appliance ownership, and therefore electricity consumption. The methodology consists of questionnaire design across the dimension of BE, HP and AC based on social practice theory, surveying of 1224 households and empirical analysis using covariance-based structural equation modelling. Results show that higher appliance ownership in the slum rehabilitation housing is due to change in household practice, built environment and affordability criteria of the appliances. Change in HP shifts necessary activities like cooking, washing and cleaning from outdoor to indoor spaces that positively and significantly influences higher appliance ownership. Poor BE conditions about indoor air quality, thermal comfort and hygiene; and product cost, discounts and ease of use of the appliances also triggers higher appliance ownership. The findings of this study can aid in designing better regulatory and energy efficiency policies for low-income settlements.

Disaggregation and characterization of residential electricity use: Analysis for Ghana

As the socio-economic need of mankind and population continue to grow, electricity consumption estimates become necessary for energy system planning. In Ghana, residential electricity is currently the second largest and growing rapidly. Unfortunately, adequate and reliable data on electricity consumption of household appliances is insufficient to enhance policy design and implementation. Therefore, the aim of this paper is to comprehensively disaggregate and characterize the residential electricity demand in Ghana. Nine scenarios were designed and tested between 2015 and 2050, considering 21 household appliances and 4 lighting technologies under 8 classes of electricity end-uses. A bottom-up approach based on stock accounting model and a technological-based top-down approach were adopted to estimate electricity consumption using demand factors such as population, gross domestic product and appliance ownership. Electricity consumption in 2015 was estimated as 3146 GW h for all scenarios while it varied between 6596 GW h and 19693 GW h by 2050. The results show that seven appliances and one lighting technology consisting of refrigerator, air conditioner, television, freezer, fan, electric iron, washing machine and CFL constituted about 93% of residential electricity consumption in 2015 and are projected to hold a dominant 90% share in 2050.

Discomfort and distress in slum rehabilitation: Investigating a rebound phenomenon using a backcasting approach

Slum rehabilitation policies in India is observed to have a rebound effect on the occupants, where rehabilitated occupants move back to the horizontal slums. In this study, we investigate the cause behind this rebound phenomenon based on a theory of homeostasis, where the loss of homeostasis refers to occupants' heightened discomfort and distress in their built environment. A novel methodological framework was developed to investigate it based on the principles of participatory backcasting approach and the theory of homeostasis. Thirty households in Mumbai's slum rehabilitation housing were interviewed to determine the social, economic and environmental cause of distress and discomfort. Granular information was obtained by further investigating the factors that influence occupants' attitude, emotions, health, control and habits in their built environment that regulates their holistic comfort and lack of stress. The causal linkages among these factors were established using a qualitative fault tree. Results show two primary cause of distress and discomfort in the study area owing to economic distress and built environment related discomfort. Economic distress was from low-income and high electricity bills due to higher household appliance ownership, and built environment discomfort was due to lack of social spaces and poor design of the slum rehabilitation housing. This study showed that mitigating such non-income drivers of distress and discomfort can prevent rebound phenomenon and improve the sustainability of the slum rehabilitation process.

Household investment in durable appliances and outcomes for children: Evidence from China

Does the ownership of time-saving household appliances have a positive impact on children’s outcomes? I use micro-level data from the China Health and Nutrition Survey from 1989 through 2011 to infer that ownership of time-saving household appliances results in a decrease in time allocated to household work, increase in school enrollment rates, and decrease in labor force participation rates for children aged 12 to 18. When the sample is partitioned on the basis of gender, these outcomes are more pronounced among females. To deal with endogeneity of household durable goods, I instrument household ownership of time-saving appliances by average ownership rate among households with no children living in the same community and two family-specific time-using household assets. With gender equality and women’s empowerment being a top priority among developing countries according to the United Nations, the results presented in this paper suggest one effective way to increase girls’ school enrollment is to reduce their household obligations. Time-saving appliances are tools that can provide the requisite decrease in time dedicated to household work. This study is the first to estimate the effect of time-saving technologies on child outcomes.

Socioeconomic status and the association between arsenic exposure and type 2 diabetes

ObjectiveEvaluate whether arsenic-related diabetes risks differ between people of low and high socioeconomic status (SES). MethodsWe used data collected between October 2007-December 2010 from a population-based cancer case-control study (N = 1301) in Northern Chile, an area with high arsenic water concentrations (>800 µg/L) and comprehensive records of past exposure. Information on lifetime exposure and potential confounders were obtained using structured interviews, questionnaires, and residential histories. Type 2 diabetes was defined as physician-diagnosed diabetes or oral hypoglycemic medication use. SES was measured using a 14-point scale based on ownership of household appliances, cars, internet access, or use of domestic help. Logistic regression was used to assess the relationship between arsenic and diabetes within strata of SES. ResultsAmong those with low SES, the odds ratio (OR) for diabetes comparing individuals in the highest to lowest tertile of lifetime average arsenic exposure was 2.12 (95% confidence interval (CI) 1.29–3.49, p = 0.004). However, those in the high SES group were not at increased risk (OR = 1.12 [95% CI = 0.72–1.73]). ConclusionsOur findings provide evidence that risks of arsenic-related diabetes may be higher in Chile in people with low versus high SES.

Analysis of the impact of energy efficiency labelling and potential changes on electricity demand reduction of white goods using a stock model: The case of Switzerland

This paper presents the development and application of a dynamic model which allows to quantify the changes in the number of white goods in stock, the related evolution of energy efficiency as well as the changes/projections of electricity consumption in the next 20 years using data from Switzerland. According to the “reference scenario” based on observed market trends the electricity demand of white goods is expected to decrease by 8% between 2015 and 2035. The analysis shows that this is the combined result of having more energy efficient appliances in the stock, a higher appliance ownership level, and an increased number of dwellings. The “maximum efficiency” scenario based on new technologies shows an electricity saving potential of white goods of 25%. These findings confirm that energy efficiency standards and labelling can be effective instruments for achieving energy and CO2 emissions reduction targets. The assessment for cost effectiveness indicates the current limited scope for economically viable energy efficiency improvements of white goods, while novel technological solutions are likely to expand the economic energy efficiency potential. Since white goods and their components are mass-produced and traded internationally, similar findings can be expected for other countries with comparable legislation (e.g. EU member states) but country-specific analyses are nevertheless recommended.

Assessing Households’ Gas and Electricity Consumption: A Case Study of Djelfa, Algeria

Abstract Households are the major energy consumer and contributor to the emission of greenhouse gases. The Algerian policy of mastering energy has improved building energy efficiency since 1994 by introducing thermal regulation (DTR). However, energy consumption is still increasing instead of decreasing, which is mainly due to occupants’ behaviour which is difficult to estimate and predict. This paper explores the impact of households and housing characteristics on residential gas and electricity consumption in the 36 municipalities of the department of Djelfa (Algeria) which is located in an arid and semi-arid climate zone. This paper is based on GIS and statistical techniques. It considers the yearly gas and electricity energy consumption (2013) of the municipalities of the department of Djelfa. The method is organised in four steps: (a) a multiple linear regression is used to construct two estimative models of gas and electricity. The models have more than 93% of accuracy for both gas and electricity models; (b) estimating gas and electricity consumption for 2008 according to the developed models; (c) organisation of the census data of 2008 in five dimensions: the population distribution, household characteristics, housing type and occupancy, and finally household appliance ownership; (d) a set of sensitivity analysis is performed based on Principal Component Analysis (PCA) and Pearson’s bivariate correlation and finally a path analysis is performed based on Structural Equation Model (SEM) to assess the importance of each variable. The overall impact of all these variables indicates that increasing the household size is the first factor reducing the electricity and gas consumption followed by the housing surface, density, room occupancy, and older households, while increasing the education level and appliance ownership boosts both per-capita gas and electricity consumption.

An income-reflective scalable energy level transition system for low/middle income households

In mitigating against energy poverty in Nigeria, research interest has focused mainly on electricity access and reduced electricity bills for low/medium income households. However, energy poverty in the global south is not only a problem of access but also of mobility which plays a crucial role in the economic productivity of a country. The need therefore arises for a scheme that guides low/medium income level households in increasing ownership of electrical appliances in a way that will improve their quality of life at the least-cost possible. Such a scheme is expected to address a prevailing challenge of poor satisfaction from the utilization of electrical appliances commonly observed with low/medium income households to achieve comfort, using Nigeria as a test case. This paper thus proposes a progressive system of electrical appliance ownership for low/medium income households in Nigeria for improved comfort. Furthermore, this paper advances discussions on building comfort by establishing the relationship between household comfort and economic output for Nigeria. The proposed system and the results obtained find relevance in developing countries especially in sub-Saharan Africa and developing Asia for improving household comfort, mitigating poverty and precipitating economic growth.

Drivers of domestic electricity users’ price responsiveness: A novel machine learning approach

Time-based pricing for domestic electricity users has been effective in reducing peak demand and facilitating integration of renewable energies. However, high cost, price non-responsiveness and adverse selection present challenges. To tackle these challenges, it would be important to investigate which users exhibit a higher potential to respond to price change, such that time-based pricing can be introduced to such users. Few studies have examined which users are more price-responsive and what drives price responsiveness. This article aims to fill this gap by comprehensively identifying the drivers that determine electricity users’ price responsiveness, in order to facilitate the selection of high potential users. We adopt a novel machine-learning approach to select the high potential users, using the Irish smart meter dataset (2009–10), which forms part of the national Time of Use trial. Our methodological novelties cover two aspects: First, using a feed-forward neural network model, we aim to determine precisely the price responsiveness of individual households, and address the nonlinearity of energy consumption and price response attributes. Second, we apply an integrated machine learning methodology to identify the drivers of price responsiveness. Our integrated approach outperforms the traditional variable selection methods by identifying drivers that are reliable. Our empirical results have shown that demographic and residential characteristics, psychological factors, historical electricity consumptionand appliance ownership are significant drivers. In particular, historical electricity consumption, income, household size, perceived behavioural control, and adoption of specific appliances, including immersion water heater and dishwasher, are significant drivers of price responsiveness across the Irish electricity users. Our results have also verified that continual price increase within a moderate range will not drive additional peak demand reduction; there is an intention-behaviour gap, where stated intention does not lead to actual peak reduction behaviours. Based on such results, we have conducted a scenario analysis to demonstrate the feasibility of selecting high potential users of achieving significant peak electricity reduction.

A Potential Role of the Widespread Use of Microwave Ovens in the Obesity Epidemic

Organisms acquire more calories from eating hot food than eating the identical food cold; thus, the widespread use of microwave ovens might have played a small role in the current obesity epidemic, just as the widespread use of refrigerators might have retarded the historic increase in obesity a century ago. Analysis of the British Cohort Study showed that, net of dietary habit, physical activities, genetic predisposition, and other demographic factors, the ownership of a microwave was associated with an increase of .781 in body mass index (BMI) and 2.1 kg in weight (when the ownership of other kitchen appliances was not associated with increased BMI or weight), and it more than doubled the odds of being overweight. In the United States from 1960 to 2015, the adult overweight, obesity, and extreme obesity rates were very highly correlated ( r = .94–.98) with the proportion of households with microwaves, and it was not because both were consequences of increasing wealth. Net of median household income, the proportion of households with microwaves was very strongly ( ds > 1.0) associated with adult overweight, obesity, and extreme obesity rates, while median household income was not at all associated with them. Individual data from the United Kingdom and historical data from the United States highlighted the possible role of the widespread use of microwave ovens in the obesity epidemic.

A study of appliance ownership and electricity consumption determinants in urban Ghanaian households

The residential sector in Ghana accounts for about 40% of aggregate electricity consumption out of which urban centers contribute 70%. The high weighted share of residential electricity use is attributed to high appliance ownership and use, and other household/building factors. The ability to determine how changes in the pattern of these factors influence electricity demand is critical if efforts to reduce consumption are to be effective. This study combines a residential electricity consumption survey (RECS) with electricity end-use monitoring of 60 households in Tema city Ghana, to yield the first ever comprehensive investigation of city-scale electricity consumption in urban Ghanaian homes. A multiple linear regression analysis is used to identify the most statistically significant indicators of appliance ownership and household electricity consumption. Results indicate that ownership of air conditioner, freezer, fan, refrigerator and television; and changes in socio-economic and building factors such as energy efficiency awareness and practice; income; household size and floor space show high statistical significance, and collectively explain 57% variance in households’ total electricity consumption. The presence of dependent children increases ownership of television, iron, washing machine and small kitchen appliances. This work provides a solid foundation for developing more tailored energy-saving policy interventions targeted at households.

Household appliances penetration and ownership trends in residential buildings

Understanding the development of the trends in the ownership of different appliances in a historic context in various countries of the world can not only provide important insights for understanding the dynamics of adoption of different appliances, but can also help with foresight: how the future may develop for these or other, new appliances on the market. Although available literature in household appliances energy consumption, energy management and energy efficiency has seen some advances, there is a clear lack in the literature on household appliance ownership. In this paper, historic data is gathered and analysed for several groups of appliance types (white appliances, brown appliances and small appliances) for 12 countries representing four continents, when available since 1970 to date. Countries representing different parts of the world were selected to present an overview on household appliances ownership and energy consumption. One of the first conclusions of the study is that there is little or no information in many countries from South America, Africa or South Asia. Refrigerators, freezers and washing machines ownership are an example of most other white goods. Brown goods appeared in the market at very different time, depending on each one (from the 70s to the late 90s) and their ownership growth is much higher than for the previous ones. Most of small line appliances ownership has not reached saturation yet.

“Everyone has a peer in the low user tier”: the diversity of low residential energy users

Low residential energy use is typically associated with undesirable characteristics, such as poverty, thermal discomfort, or small dwelling size. The association of low energy use with deprivation has been an obstacle to promoting more aggressive goals for reduction of residential use. However, there is little research on the composition of the low user population. We investigated the demographics, behavior, and satisfaction of the lowest 10% of electricity consumers in Sacramento, CA, to see what attributes best correlated with low use. California, like many other regions, has GHG emissions goals requiring drastic reductions in residential consumption. Households in Sacramento’s lowest decile of electricity consumption already live at electricity consumption levels consistent with the goals for 2050. Our investigation of 700 of these households found that diversity of low users with regard to age, income, education, appliance ownership, and dwelling characteristics is similar to that of the general population. Low-use households tend to be smaller, but not enough to explain the entirety of low usage. Surveys and interviews revealed that those in the lowest 10% typically pursued low consumption deliberately and enthusiastically and were aware of their status as low users. Conversations about energy conserving strategies were embedded in their social lives. They employed diverse and creative strategies to maintain thermal comfort without excess energy use, often exceeding expert recommendations. Finally, the distribution of self-reported quality of life was no different from that of the general population living at much higher consumption levels. Overall, the key determinants of low use were a positive engagement with improvisation and experimentation, and the salience of energy in personal or social life. The population of low users should be treated as a valuable source of peer advice and lifestyle modeling.

Towards an understanding of residential electricity consumption in India

ABSTRACT Residential electricity consumption in India has increased by a factor more than 50 since 1971. India’s electrified households on average still consume less than one-third of the world’s average for electricity. Rapid electrification, increasing incomes and technology development can result in increased appliance ownership and higher electricity use. A better understanding of this demand can help to develop effective energy-efficiency policies, optimize the addition of generation capacity, and tackle challenges of climate change and environmental pollution. However, research on residential electricity consumption has received limited attention in India until now. A systematic examination of determinants of residential electricity consumption will require an interdisciplinary approach involving the fields of engineering, economics (traditional and behavioural), anthropology, architecture and others. A two-step approach is presented to advance understanding. First, a critical literature review from different disciplines is presented that explores residential electricity consumption in India. Public data sets are also analyzed to gather insights and highlight inconsistencies. Second, an interdisciplinary approach is proposed and developed that can be adopted for research on residential electricity consumption in India. The data needs and systems to facilitate such an approach are provided.

Linking residential electricity consumption and outdoor climate in a tropical city

The link between climate and energy consumption has been widely established in many cities. The residential electricity consumption majorly for space conditioning is especially responsive to the outdoor climate. As a hot and humid tropical city, Singapore is expected to see increasing residential electricity consumption with global climate change. In this study, a multiple regression analysis is performed to relate the residential electricity consumption per capita and per household with outdoor climate during a 12-year period (2005–2016). The per-capita electricity consumption during 2008–2016 sees substantial decrease from that during 2005–2007, possibly due to the various energy saving measures taken by Singapore government. The different responses to outdoor climate variation in different household types are examined. It is found that generally dwellers in public households are more sensitive to outdoor climate variations, while private household occupants are not much affected by climate. Due to increasing ownership of electricity-consuming appliances in 1–2 Room and 3 Room public households, their electricity consumptions show a consistent increasing trend during the period studied. Under the worst scenario of projected future temperature increase, the per-capita and per-household electricity consumptions are projected to increase by 47% and 41%, respectively.

Estimating Residential Electricity Consumption in Nigeria to Support Energy Transitions

Considering the challenge of accessing reliable household metering data in Nigeria, how can electricity consumption levels be determined? And how do disparities in electricity consumption patterns across the country affect the pursuit of sustainability, universal access and energy transition objectives? This study combined household-reported data on ownership of electrical appliances and energy expenditure with online sales records of household appliances to estimate current and future residential electricity demand in Nigeria, as well as the required generation capacity to achieve 100% electricity access, under various scenarios. Median residential electricity consumption was estimated at 18–27 kWh per capita but these estimates vary between the geographical zones with the North East and South West representing extremes. Under a universal access scenario, the future electricity supply system would be expected to have installed generation capacity sufficient to meet the estimated residential demand of 85 TWh. To further understand the required infrastructure investment as a whole and the approaches that might be preferred in rural versus urban areas, the disaggregated, zone-by-zone and urban/rural data may offer more insight than a whole-of-country approach. The data obtained is useful for identifying specific transitions at the sub-national level that can minimize the required investment while maximizing households’ energy access.

Characterizing domestic electricity consumption in the Indian urban household sector

The aim of this work is to forecast electricity consumption for energy efficient management in the Indian urban household by evaluating current practices which are followed in a living place (residence/home). Conclusions and electricity consumption forecasting are derived from the data obtained through a questionnaire survey conducted in three different climate zones of India. Utilizing micro level primary data obtained through the household survey, authors have analysed the variation in the electricity consumption and the factors such as demographic and dwelling attributes which cause such variations. Ownership of major home appliances like air conditioner, refrigerator and electric water heaters (geyser) have seen a significant rise over the years in households. They are found to contribute high electricity consumption in Indian urban households.Price elasticity of electricity consumption is found as −0.72 (negative sign indicates that when the price of electricity increases, the consumption decreases). Electricity consumption in the Indian urban household is observed more responsive to ownership of air conditioner rather than demographic variables and other appliances. Considering predicted accountability of India for increased global emission due to air conditioning, ownership of air conditioners was investigated in depth, based on the data captured in the questionnaire survey. Factors considered were tonnage, energy star rating, usage duration, year of purchase, and numbers. It is observed that, electricity consumption in air conditioning could be reduced by 15% to 31%; if existing household air conditioners, older than 7 years were replaced by new energy efficient air conditioners, subject to all other parameters like tonnage and usage remain constant. The outcomes of this study can be utilized for swotting the electricity prices and policy making.

Energy efficiency deployment: A pathway to sustainable electrification in Ghana

Abstract Electricity is a key input for socio-economic development and its demand is expected to grow rapidly throughout the world, especially in developing countries. In Ghana, where supply challenges persist with increasing residential demand, promoting energy efficiency in households is a needful pathway. This study aims at estimating energy consumption, energy savings and peak demand reduction by introducing different standards and labelling regimes for some household appliances under different gross domestic product (GDP) scenarios for the period 2020–2050. The analysis concentrates on 5 intensive energy consuming appliances: refrigerator, freezer, air conditioner, washing machine and television; and 4 lighting technologies. A bottom-up and a top-down approach were adopted to estimate electricity consumption with the dynamic characteristics of data such as appliance ownership, population and GDP. The summary results indicate that with the implementation of the various energy efficiency scenarios, the energy consumption of the 5 appliances and 4 lighting technologies can be reduced by 24–51% in 2050 while the estimated potential cumulative energy savings range 31–104 TWh for the 30-year period. The peak demand reduction in 2050 ranges 721–2952 MW for all scenarios considered and represents 40–165% of Ghana's peak demand in 2013. Refrigerators were found to account for the highest share of the cumulative energy savings, 37–57%, while televisions contribute the highest, 28–42%, to peak demand reduction by 2050. The methods deployed in this study can easily be adapted for related studies in other countries with even little household load data, providing an important instrument for helping decision makers set adequate energy efficiency policies.