Domestic Electricity Use Research Articles

Determinants of Urban Residential Electricity Consumption in Burkina Faso: A Study of Dwelling, Household, Socio-Economic and Appliance-Related Factors

This study analyses the dwelling, household, socio-economic and appliance-related determinants of urban domestic electricity use in Burkina Faso. A survey of 387 households in Ouagadougou was conducted and combined with their electricity use, collected from energy bills. To the authors’ knowledge, this is the first large-scale, city-wide household electricity study undertaken in Burkina Faso. Linear regression models were applied to the data to assess the influence of household, dwelling, socio-economic and appliance-related factors on electricity use. Significant and unambiguous predictors of urban domestic electricity use included household income, dwelling tenure type and ownership, and use of lighting fixtures, television sets, fridges, fans, freezers and air conditioners. Dwelling, household and socio-economic factors explained 70.2% and 70.5% of the variance in electricity use, respectively, when combined with appliance ownership and use factors. This study provides an understanding of the driving factors of domestic electricity use and discusses the implications and applications of this research for a range of stakeholders in the electricity sector.

Urban domestic electricity consumption in relation to households’ lifestyles and energy behaviours in Burkina Faso: Findings from a large-scale, city-wide household survey

Information on actual domestic electricity use in Burkina Faso, where the urban zones and residential sector account for 74% and 33% respectively of the total electricity use, remains very challenging to find, as little research currently exists. This study aimed therefore, to provide the first ever insights into the actual urban residential electricity use. A survey with 387 households, the first large-scale, city-wide household electricity study undertaken in Burkina Faso to the authors’ knowledge, was conducted in the city of Ouagadougou. Information on the households' characteristics and behaviours were collected to yield a first comprehensive analysis on the actual city-scale domestic electricity use. Findings demonstrated an average electricity use of 2395 kWh/year by households. Cooling accounts for almost 40% of the total domestic electricity use, followed mainly by cooking and food preserving (23%) and information-communication-entertainment (19%) activities. Three groups of consumers were then formed based on their electricity use level, to investigate interactions between electricity use and households’ lifestyles. The study’s findings lay therefore, the foundations for a better understanding of actual urban domestic electricity use patterns and could help to develop more suitable policies and actions targeting energy conservation in the residential sector.

Iranian Household Electricity Use Compared to Selected Countries

Buildings account for nearly 40% of energy use in global contexts and climatic conditions tend to contribute to consumption. Human activities are also influential in energy consumption and carbon dioxide (CO2) emissions that lead to global warming. Residential buildings are responsible for a considerable share. There are countries aggravating this situation by heavily relying on fossil fuels. Oil-rich countries are allocating an energy subsidy to the public, making energy cheaper for their consumers. This may result in negative consequences, including households’ inefficient energy use behaviours in countries such as Iran. Beyond the impact of energy subsidy allocation, this study aims to explore the climatic and non-climatic factors that affect the increase in domestic electricity use, particularly in Iran. For this purpose, this study begins with a comparative analysis between countries with and without the energy subsidy to examine the trends in domestic electricity use. Afterwards, the tendency of households’ electricity use in Iran will be analysed in consideration of climatic and non-climatic factors among several provinces in Iran. This study exploited published statistical data for the analysis. The results indicate the tendency of increased domestic electricity use due to the country’s generous subsidy offered to the public as well as climatic and non-climatic factors in Iran. These results may provide an opportunity for future studies regarding building occupants’ inefficient energy use behaviours for policy enactment in Iran and other oil-rich countries.

ON THE RELATIONS AMONG CO2 EMISSIONS, GROSS DOMESTIC PRODUCT, ENERGY CONSUMPTION, ELECTRICITY USE, URBANIZATION, AND INCOME INEQUALITY FOR A SAMPLE OF 134 COUNTRIES

This paper is aimed at examining the relations among CO2 emissions, gross domestic product (GDP) growth, energy consumption, electricity use, urbanization, and income inequality for a sample of 134 countries by using principal components analysis, Granger causality, vector error correction (VEC) models, and panel vector autoregression (PVAR) models. Data was obtained from the World Bank with annual observations from 1990 to 2014. The chosen countries are those with ten years or more of concurrent data of the variables under study. The main empirical findings suggest a Kuznets curve between CO2 emissions per capita and GDP per capita. In addition, CO2 emissions have a long-term relationship with economic growth, energy use, electricity use, urbanization, and inequality. Finally, in the short run, CO2 emissions depend on economic growth, urbanization, and income inequality.

Energy efficiency in postpaid-prepaid metered homes: analyzing effects of socio-economic, housing, and metering factors in Lagos, Nigeria

Advances in automated energy metering system over the years have engendered transparency, self-control, efficiency, and equity in energy use especially among residential households globally. Despite this development, only few studies have shown the disaggregated effects of household attributes, dwelling characteristics, and metering systems on residential energy efficiency in the Global South. This paper argues that apart from household contextual factors—socio-economic and housing—the metering systems could indirectly account for energy disparities among urban households. This study therefore compared electricity consumption by urban households under the postpaid meter system and the prepaid meter system using electricity utility data obtained from residents in Ojo Lagos, Nigeria. Findings indicated that electricity consumption levels differed significantly between the postpaid and the prepaid metered households. Further analyses showed that the prepaid meter households used 47% less electricity kWh per annum compared with the postpaid meter households, intra-group variations in domestic electricity use were attributed to the household socio-economic and residential characteristics, and inter-group variations in electricity use rates were attributed to the metering system used by households. This study has both practical and policy implications for urban energy management especially with regard to the metering systems put in place for residential energy use and the need to ensure energy justice in socio-economically polarized cities.

A unified probabilistic model for predicting occupancy, domestic hot water use and electricity use in residential buildings

A novel strategy that combines separate probabilistic models developed by other researchers into a unified model for generating schedules of active occupancy, domestic hot water (DHW) use, and non-HVAC electricity use in multiple residences with a 10-min resolution for every day of the year is described. A variety of new model functions are introduced in order to generate stochastic predictions for each of numerous residences at once, to enforce appropriate variability of behaviors between dwellings and to ensure that domestic hot water and electricity use are coincident with occupancy. The separate models used in this paper were previously developed for the US and the UK; in the unified model, scaling factors were added to these models to adjust the predictions so as to better agree with national aggregated data for Canada. The unified model was validated with measurements of domestic hot water use and electricity consumption from the 40 residential units of a social housing building in Quebec City, Canada. The behavior of occupants in the case study building was simulated 100 times in order to validate the outputs of the unified model. Goodness-of-fit tests applied to each of these simulations showed that the fit between simulated and measured dwelling-per-dwelling distributions was acceptable for 97% of the DHW consumption profiles and for 92% of the electricity consumption profiles. However, there remain discrepancies between simulations and measurements, such as an overestimation of the DHW and electricity consumption in the morning.

Determinants of high electrical energy demand in UK homes: Appliance ownership and use

This paper provides an analysis of the appliance ownership and use factors contributing to high electrical energy demand in UK homes. The data were collected during a large-scale, city-wide survey, carried out in Leicester, UK, in 2009–2010. Annual electricity consumption and appliance ownership and use were established for 183 dwellings and an odds ratio analysis used to identify the factors that led to high electricity consumption. Many of the appliance ownership and use factors have not previously been studied for the UK domestic sector. The results of this study should be of key interest to government policy makers and energy supply companies interested in the underlying drivers of the highly positively skewed distribution of UK domestic electricity use. The study identifies those appliances that could be targeted for technical improvements or subjected to campaigns to encourage more energy efficient use in order to reduce electricity consumption among high demand households. This paper builds on earlier work by the current authors which identified the households (socio-demographic and dwelling characteristics) most likely to be high electricity consumers. The current work provides the basis for advice and guidance to those households that would enable them to, over time, reduce their electricity use.

Biogas potential for electricity generation in the Emirate of Abu Dhabi

In 2009, the Government of Abu Dhabi made a commitment to generate 7 % of its total power output from renewable sources of energy by 2020. Biomethane is considered a viable option in accomplishing this goal. The objective of this work is to estimate the biogas to electricity potential from nine different biomasses found in the Emirate of Abu Dhabi, i.e., sheep dung, goat dung, cattle dung, camel dung, print paper, newspaper, carton paper, food waste, and animal waste blood. These biomasses are considered waste, and they were selected for their organic content and relative abundance in the Emirate. The objective was accomplished through experimental work measuring the biomethane potential of the nine biomasses and the estimation of their availability in the Emirate. Food waste had the highest biomethane potential yield of 517.36 mL-CH4/g-VSadded at standard conditions of temperature and pressure (STP), while newspaper had the lowest yield of 76.6 mL-CH4/g-VSadded STP, despite its high cellulose content. Varying levels of inhibition were also observed across the biomasses. An estimation of the total biomethane potential showed that the nine biomasses are able to provide 6 % of domestic electricity use in Abu Dhabi Emirate and 1.9 % of renewable energy commitment, with food waste contributing the highest fraction (51 %) and paper waste having the highest specific electricity potential (0.94 kWh/t).

Fuzzy logic based economical analysis of photovoltaic energy management

Since 2002 the European Union has seen a rapid growth in the photovoltaic (PV) sector. During the last two years incentives for PV installations were cut almost worldwide slowing the growth of the market. In this scenario the design of a new plant ensuring economic convenience is strongly related to household electricity consumption patterns and energy management actions. This paper presents a high-resolution model of domestic electricity use based on Fuzzy Logic Inference System. Taking into account consumers sensibility concerning the rational use of energy, the model gives as output a 1-min resolution overall electricity usage pattern of the household. The focus of this work is the use of a novel fuzzy model combined with a cost benefits analysis to evaluate the real economic benefits of load shifting actions. A case study is presented to quantify its effectiveness in the new net metering Italian scenario.

Trends in home computing and energy demand

Household energy demand due to domestic computer usage has changed beyond recognition over the past thirty years. Computers are now used in most homes, almost every day and laptop ownership has overtaken traditional desktop computers. Mobile devices give access to services that in the past required desktops, and they are usually more energy efficient. Today's computers usually rely on wireless routers that are often run all day. The effect of these changes on electricity use in the home has been profound. At least 60% more electricity was used for UK home computing in 2012 than in 1990. The implications of recent changes in information technology use are assessed for domestic electricity use and carbon emissions, using data from the Household Electricity Survey (HES) – the most detailed survey of electricity consumption in UK homes. On average, routers use twice as much energy per day as the laptops they serve. Laptops also draw power at a different time of day compared with desktop computers – which has implications for generation. Policy and practical recommendations are made for reducing energy use for information technology, including the estimated energy savings that could be achieved if UK routers met the US Energy Star standard for energy efficiency.

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%.

Fuzzy logic home energy consumption modeling for residential photovoltaic plant sizing in the new Italian scenario

In recent years, Italy has seen a rapid growth in the PV (photovoltaic) sector, following the introduction of the FIT (feed in tariff) scheme known as Conto Energia. In July 2013 the Italian government definitively cut FITs, leaving only tax benefits and a revised net metering scheme (known as “Scambio sul Posto”) for new PV installations. In this scenario, the design of a new PV plant ensuring savings on electricity bills is strongly related to household electricity consumption patterns. This paper presents a high-resolution model of domestic electricity use. The model is based on Fuzzy Logic Inference System. Using as inputs patterns of active occupancy and typical domestic habits, the fuzzy model give as output the likelihood to start each appliance within the next minute. The model has been validated with electricity demand data recorded over the period of one year within 12 dwellings in the central east coast of Italy. The tool has been used to evaluate the self consumption percentage to correctly size a residential photovoltaic plant in a case study. A cost benefits analysis is presented to show the effectiveness of PV-generation in the new Italian scenario.

20∶60∶20 - Differences in Energy Behaviour and Conservation between and within Households with Electricity Monitors

The introduction of electricity monitors (in-home displays; IHDs), which show accurate and up-to-the-minute energy usage, is expected to lead to reduction in consumption. Studies of feedback on domestic electricity use have generally supported this view. However, such studies also demonstrate wide variation between households. Examining the heterogeneity of responses is essential for understanding the actual and potential effectiveness of IHDs and in order to target interventions effectively. To explore differences between households' responses to IHDs, we conducted a qualitative study with 21 households who had an IHD for more than six months. Of the 21, only four households continued to refer to the IHD and the findings suggest that attempts to reduce energy consumption were situated in wider social and physical contexts. Further, the participants demonstrated energy saving behaviour before and outside of IHD usage. The patterns of energy behaviours and attempts at electricity conservation could best be understood by categorising the households into three types: the Monitor Enthusiasts (20%), the Aspiring Energy Savers (60%) and the Energy Non-Engaged (20%). The factors of importance in energy behaviour differed between the categories. Financial savings contributed to efforts to reduce energy use but only up to boundaries which varied considerably between households. Social practices and social relationships appeared to constrain what actions households were prepared to undertake, illuminating aspects of inter-household variation. Within the household, all energy users were not equal and we found that women were particularly influential on energy use through their primary responsibility for domestic labour on behalf of the household. The implications of the findings for environmental campaigning are discussed.

Enhanced Load Profiling for Residential Network Customers

Anticipating load characteristics on low voltage circuits is an area of increased concern for Distribution Network Operators with uncertainty stemming primarily from the validity of domestic load profiles. Identifying customer behavior makeup on a LV feeder ascertains the thermal and voltage constraints imposed on the network infrastructure; modeling this highly dynamic behavior requires a means of accommodating noise incurred through variations in lifestyle and meteorological conditions. Increased penetration of distributed generation may further worsen this situation with the risk of reversed power flows on a network with no transformer automation. Smart Meter roll-out is opening up the previously obscured view of domestic electricity use by providing high resolution advance data; while in most cases this is provided historically, rather than real-time, it permits a level of detail that could not have previously been achieved. Generating a data driven profile of domestic energy use would add to the accuracy of the monitoring and configuration activities undertaken by DNOs at LV level and higher which would afford greater realism than static load profiles that are in existing use. In this paper, a linear Gaussian load profile is developed that allows stratification to a finer level of detail while preserving a deterministic representation.

Domestic electricity use: A high-resolution energy demand model

The pattern of electricity use in an individual domestic dwelling is highly dependent upon the activities of the occupants and their associated use of electrical appliances. This paper presents a high-resolution model of domestic electricity use that is based upon a combination of patterns of active occupancy (i.e. when people are at home and awake), and daily activity profiles that characterise how people spend their time performing certain activities. One-min resolution synthetic electricity demand data is created through the simulation of appliance use; the model covers all major appliances commonly found in the domestic environment. In order to validate the model, electricity demand was recorded over the period of a year within 22 dwellings in the East Midlands, UK. A thorough quantitative comparison is made between the synthetic and measured data sets, showing them to have similar statistical characteristics. A freely downloadable example of the model is made available and may be configured to the particular requirements of users or incorporated into other models.

Real-life energy use in the UK: How occupancy and dwelling characteristics affect domestic electricity use

The patterns of electricity consumption were studied for 27 representative dwellings in Northern Ireland. The type of dwelling, its location, ownership and size, household appliances, attributes of the occupants including number of occupants, income, age and occupancy patterns have differing but significant impacts on electricity consumption. A clear correlation was found between average annual electricity consumption and floor area. The monthly consumption of detached houses is between 3.57 and 5.17 kWh m −2; semi-detached between 3.44 and 4.59 kWh m −2 and terraced houses between 2.5 and 3.9 kWh m −2. The average winter consumption exceeded the average summer consumption by 1.59 kWh m −2 for detached, by 1.16 kWh m −2 for semi-detached and by 1.78 kWh m −2 for terraced houses. The difference in the annual demand on the grid between detached and terraced houses is between 24 and 30%. The electricity consumption per person decreases as the number of occupants increases. This is particularly significant in large dwellings but smaller numbers of occupants.

Improved efficiency in domestic electricity use

This paper describes how domestic appliances (excluding water and space heaters) and lighting devices can be redesigned to use electricity more efficiently. Three levels of conservation strategy are analysed: ‘moderate’, ‘strong’ and ‘radical’. These result in the reduction of electricity consumption to 80%, 50% and 35% respectively, without affecting the service and comfort obtained. The calculations are based on Danish behaviour patterns and appliances sold in Denmark, but the results can be transferred to other countries. The savings reported are shown to be economically attractive as well as technologically possible.