Household Energy Research Articles

Challenges, Opportunities, and possible Interventions in the Biogas sector in Rural areas of Limpopo, South Africa

Biogas technology offers a sustainable and eco-friendly solution for addressing energy needs, particularly in rural areas. Despite its potential benefits, the adoption of biogas technology in rural Limpopo, South Africa, remains limited. This paper critically examines the factors hindering its uptake. Using an exploratory approach (Qualitative study), data were gathered through interview guide, field surveys, literature reviews, and expert opinions. The analysis indicates that while biogas is a superior thermal option for household energy crises, several challenges need resolution. Key obstacles include ineffective strategies for promoting biogas in Limpopo. Understanding stakeholder perspectives—such as government bodies, local communities, and private enterprises—is crucial for developing strategies to increase biogas use. Necessary interventions include training, capacity-building, and educational awareness initiatives in rural areas to boost adoption. The financial sector's role in renewable energy is critical, especially as cleaner fuels gain attention. Despite its significant benefits in reducing greenhouse gas emissions and enhancing household energy security, biogas technology's acceptance and use remain low.

Performance of a pilot-scale microbial electrolysis cell coupled with biofilm-based reactor for household wastewater treatment: simultaneous pollutant removal and hydrogen production.

The septic tank is the most commonly used decentralized wastewater treatment systems for household wastewater treatment in on-site applications. The removal rate of various pollutants is lower in different septic tank configurations. The integration of a microbial electrolysis cells (MEC) into septic tank or biofilm-based reactors can be a green and sustainable technology for household wastewater treatment and energy production. In this study, a 50-L septic tank was converted into a 50-L MEC coupled with biofilm-based reactor for simultaneous household wastewater treatment and hydrogen production. The biofilm-based reactor was integrated by an anaerobic packed-bed biofilm reactor (APBBR) and an aerobic moving bed biofilm reactor (aeMBBR). The MEC/APBBR/aeMBBR was evaluated at different organic loading rates (OLRs) by applying voltage of 0.7 and 1.0V. Result showed that the increase of OLRs from 0.2 to 0.44kg COD/m3 d did not affect organic matter removals. Nutrient and solids removal decreased with increasing OLR up to 0.44kg COD/m3 d. Global removal of chemical oxygen demand (COD), biochemical oxygen demand (BOD), total nitrogen (TN), ammoniacal nitrogen (NH4+), total phosphorus (TP) and total suspended solids (TSS) removal ranged from 81 to 84%, 84 to 85%, 53 to 68%, 88 to 98%, 11 to 30% and 76 to 88% respectively, was obtained in this study. The current density generated in the MEC from 0 to 0.41 A/m2 contributed to an increase in hydrogen production and pollutants removal. The maximum volumetric hydrogen production rate obtained in the MEC was 0.007 L/L.d (0.072 L/d). The integration of the MEC into biofilm-based reactors applying a voltage of 1.0V generated different bioelectrochemical nitrogen and phosphorus transformations within the MEC, allowing a simultaneous denitrification-nitrification process with phosphorus removal.

Stop procrastinating, start renovating! Exploring the decision-making process for household energy efficiency renovations

A tricky contributor to the “energy efficiency gap” is homeowners who fail to finalize a planned Energy Efficiency Renovation (EER) project, even after having received an offer from a contractor. However, there is a lack of evidence on drivers and barriers of homeowners' EER in the final stage of the decision process, including the role of the energy consultation and homeowners' perceptions of barriers and impediments that can potentially lead to procrastination, that is, to the postponement of tasks. This study contributes to filling this gap based on a survey of 609 Danish homeowners in the final stage of an EER decision-making processes. Through a comparative analysis of adopters and non-adopters, we find that procrastination is a common reason for non-adoption. First, we identify potential predictors that differ between adopters and non-adopters. Next, these variables are included in a structural equation path model (SEM) to estimate their direct and indirect effects on EER adoption. We find that homeowners' final implementation of EER decisions is complex and far from a simple weighing of monetary costs and benefits. Psychological factors such as expected hassle and interpersonal aspects of the consultation, as well as perceived difficulties and impediments, specifically related to how easy an EER offer is to understand and ultimately accept, are identified as core antecedents of EER adoption or procrastination. Implications for interventions to reduce procrastination in EER decisions are discussed, including financial support measures and interventions designed to make it easier for homeowners to implement their EER decisions.

How can interventions of building renovation and household energy conversion effectively improve the physical and mental health outcomes? A systematic review and meta-analysis

Household energy efficiency measures can effectively reduce indoor air pollution and positively impact the health of residents, but there is no conclusive evidence on the effectiveness of different energy efficiency measures for various diseases. This study used systematic review and meta-analysis to research the effects of two interventions on residents’ physical and mental health: building renovation (heating, insulation, double-glazed windows and ventilation) and household energy conversion (stove upgrading and clean energy use). A total of 79 papers published between 1977 and 2023 were reviewed in this study, providing comprehensive meta-analytic evidence on the effectiveness of energy efficiency measures. The results show that household energy-saving measures have a minor but significant positive influence on residents’ physical and mental health, with the effect on mental health being larger than the impact on physical health. Stove upgrading is advantageous in respiratory and cardiovascular diseases; insulation can greatly reduce the risk of skin diseases; heating is beneficial in sensory and digestive diseases; and clean energy use can successfully mitigate integrative diseases. Furthermore, a combination of heating and insulation measures has the most favourable influence on mental health conditions such as depression, anxiety and social isolation. The study findings can help residents, policymakers and relevant organizations take appropriate interventions to promote residents’ physical and mental health.

Green means go: The effect of a visualization tool towards increased use of renewable energy in households

There is a need to further develop digital and hardware tools to support consumers in the adaptation of their energy use to, for example, integrate renewable sources into it and/or reduce expenses. This paper presents an evaluation study of a tool, including its hardware and software versions, that supports consumers in their electricity consumption optimization, most notably concerning renewable energies for specific devices. We conducted a six-week study in Oldenburg, Germany involving 43 participants divided into three groups: one hardware and one digital variant each of an energy visualization tool, as well as a control group. We furthermore collected quantitative data on energy usage patterns and qualitative insights through semi-structured interviews. Here the participants received information about the percentage of renewable energy currently in the grid, and were asked to document their washing machine and dishwasher use. This paper provides insights into the perception of the proposed visualization tools achieved through semi-structured interviews, comparing the digital and hardware versions, while outlining the challenges of and possibilities for changing energy use behavior, especially regarding the time of day of an appliance's use. Even though the measurable influences of the tool were limited due to thresholds being reached too easily as a result of e.g. high wind levels generating higher-than-anticipated amounts of renewable energy, in terms of the amount of renewable energy use, slight improvements in the two test groups were observed compared to the control group. Regarding consumer behavior, changes in the appliances' use time show slightly higher improvement compared to the control group.

Adoption of smart energy apps and household energy practices: empirical insights from Norway

ABSTRACT This study examines the adoption and usage patterns of household energy apps among a sample of Norwegian households to explore their potential in visualising and controlling home energy consumption and influencing sustainable energy practices. Through a questionnaire survey of 150 respondents using energy apps, this study gathers empirical insights into adoption motivations, user perceptions and factors associated with self-reported changes in household energy practices. Findings indicate that app-related factors, such as perceived app insights applicability, ease of use, and appealing user interface, are more positively associated with self-reported changes in daily energy habits than demographic factors. This research underscores the importance of prioritising user experience and data security in app development to foster sustainable energy practices. It also offers practical recommendations for targeted engagement strategies and policy interventions to promote the wider adoption of smart energy apps and maximise their potential to facilitate household energy transitions.

Assessing Yield Disparities: Anticipated versus Optimal Rooftop Photovoltaic Systems and Implications for Prosumer Viability

Solar photovoltaics, especially rooftop systems also called distributed solar photovoltaics, are crucial in the ongoing energy transition. Modeling these systems is vital to understanding their role in a decentralized energy system. While ground‐mounted photovoltaic power plants are easier to model, generalizing yield profiles for rooftop systems is challenging. This study aims to estimate yield loss effects for rooftop solar photovoltaic systems compared to optimized ground‐mounted systems. Anticipated yield losses are 18% for residential, 7% for commercial, and 4% for industrial rooftop systems. The impact on residential prosumers’ viability is assessed by comparing prosumer system optimization results with and without yield losses. Results show a non‐uniform change in installed solar photovoltaic and battery capacities, with a tendency to compensate for reduced yields by increasing photovoltaic capacity by up to 20%, given favorable cost prospects by 2050. The annualized total cost of energy for prosumer households could therefore increase by up to 20% by 2050. Despite yield reductions, installing a solar photovoltaic prosumer system remains more favorable than relying entirely on‐grid electricity. This study highlights the importance of considering yield losses in rooftop solar photovoltaics and the significant role of prosumers despite identified yield losses.

Household energy consumption forecasting based on adaptive signal decomposition enhanced iTransformer network

With the presence of volatility and noise in the energy consumption data, existing energy consumption forecasting methods have difficulties in achieving satisfactory forecasting results from multiple perspectives, including accuracy, robustness, generalization, and efficiency. This study introduces a novel energy consumption forecasting framework that combines the adaptive signal decomposition method and iTransformer (ASSA-iTransformer) to tackle the above-mentioned difficulties. Each subsequence obtained by ASSA decomposition was fed into the iTransformer framework, and deep-level time series information was extracted. Compared to state-of-the-art methods across various evaluation dimensions, ASSA-iTransformer has improved the average mean absolute error (MAE) by 23.7%, root mean square error (RMSE) by 27.6%, and mean absolute percentage error (MAPE) by 16.4%. Moreover, the R2 values on five real-world household energy consumption datasets are close to 1, demonstrating overall outstanding performance.

EOS: Impact Evaluation of Electric Vehicle Adoption on Peak Load Shaving Using Agent-Based Modeling

The increasing adoption of electric vehicles (EVs) by the general population creates an opportunity to deploy the energy storage capability of EVs for performing peak energy shaving in their households and ultimately in their neighborhood grid during surging demand. However, the impact of the adoption rate in a neighborhood might be counterbalanced by the energy demand of EVs during off-peak hours. Therefore, achieving optimal peak energy shaving is a product of a sensitive balancing process that depends on the EV adoption rate. In this paper, we propose EOS, an agent-based simulation model, to represent independent household energy usage and estimate the real-time neighborhood energy consumption and peak shaving energy amount of a neighborhood. This study uses Residential Energy Consumption Survey (RECS) and the American Time Use Survey (ATUS) data to model realistic real-time household energy use. We evaluate the impact of the EV adoption rates of a neighborhood on performing energy peak shaving during sudden energy surges. Our findings reveal these trade-offs and, specifically, a reduction of up to 30% of the peak neighborhood energy usage for the optimal neighborhood EV adoption rate in a 1089 household neighborhood.

Cooking Energy, Health, and Happiness of Women in Nigeria

This study utilizes novel data to investigate the impact of cooking energy sources and indoor air pollution on the happiness, life satisfaction, physical, and mental health of women in Nigeria. The existing body of literature relies on ambient air pollution data, which can be limiting in resource-constrained settings. To address this gap, we employ a direct approach, measuring Carbon Monoxide (CO) levels in participants’ blood using the Rad-57 CO-oximeter. Our analysis reveals strong positive correlations between the utilization of clean cooking energy and women’s reported happiness and life satisfaction. Additionally, the study finds that clean cooking energy usage is associated with a significant reduction in mental health problems among women. These findings highlight a substantial disparity in well-being based on access to clean cooking energy sources. Furthermore, exposure to carbon monoxide, as measured in this study, demonstrates a detrimental effect on women’s health and overall well-being. Consequently, policymakers and stakeholders should prioritize initiatives that promote household energy access and facilitate the transition to clean cooking practices, especially in rural areas where the use of polluting fuels and exposure to indoor air pollution remain prevalent concerns. JEL Classification: D12, I31, I100, Q420.

Analyzing variability and coordinated demand management for various flexible integrations of residential distributed energy resources

Deploying distributed energy resources (DERs) is crucial for decarbonizing the building sector, but challenges arise due to the energy mismatch between on-site generation and consumption. Impacts of large-scale development of distributed energy technology are seldom evaluated from a system-wide perspective. This study primarily utilizes high-resolution meter data to analyze residential energy consumption behaviors and variability of solar photovoltaics (PV), heat pump and fuel cell throughout the year. Then, rolling horizon optimization is applied to harness demand flexibility through scheduling developed integrated energy systems, considering synergies between on-site energy resources and demand side management. The techno-economic performances of the integrated systems are investigated by adopting wholesale spot prices for PV grid feed-in. Results show that flexible schedule of integrated energy systems can deliver multiple benefits, including energy saving, cost reduction and grid-support interaction, improvement in PV self-consumption through flexible coupling can exceed 40 % compared to the measured results. The effectiveness of demand-side solutions strongly depends on the density and variability of household energy consumption, micro cogeneration presents a greater potential of cost-saving and carbon reduction in winter months. Findings emphasize the importance of coordinated demand management strategy in enhancing effectiveness of energy usage and grid-friendly interactions under widespread DERs implementation.

The influence of disruptive events on energy-related household practices: Results of a longitudinal study in the Netherlands

Household energy use relates to our socio-cultural identity, our socio-economic status and the socio-cultural and material contexts in which we live. Around the world, households experienced dramatic changes in light of the COVID-19 pandemic and the drastic increase of energy prices following the Russian invasion of Ukraine. Habits and routines were disrupted, reinterpreted, reorganized and renegotiated, albeit under constraints and in most cases involuntarily. This paper analyses how the practice of ‘keeping warm’ responds to disruptive events ranging from a small-scale and short-lived experiment to much more drastic and far-reaching geopolitical events. Following an initial study challenging households to reduce temperatures inside their homes during October/November 2018, the same households were revisited for follow-up questioning two and a half years after the start of the COVID-19 pandemic in Europe and six months after the attack of Russian armed forces on Ukraine. Quantitative and qualitative data were collected before, during, and three months as well as three years after the original ‘heating challenge’. The final follow-up survey took place in August 2022 and turned the initial short-lived Living Lab-based experiment into a longitudinal study.The experimental exploration of possibilities to reduce household energy use through the disruption of routinized practices in Living Labs enables an analysis of the effects of disruptive events, including the role of values, social norms, habits and routines (Sahakian et al., 2021). But what happens, when experiments get serious and large-scale upheaval affecting many challenges and changes meanings, thus contributing to changes in social norms and practices? This research explores lasting-changes in energy-related household practices following voluntary disruptive experimentation and subsequent involuntary disruptions. Compared to the macro-systemic disruptions experienced during the COVID-19 pandemic and the more recent energy crisis, the disruptions induced through the initial ‘heating challenge’ are of a much smaller magnitude. Our findings show that reductions in energy use are possible when routinized practices are disrupted through voluntary experimentation. In addition, our results indicate that the meanings tied up with indoor comfort had changed due to the initial experiment and that participants who initially experimented in an interactive community setting had learned more about how to connect, share experiences and reflections to adapt to other, also large-scale disruptions collaboratively.

Mapping the Path to Sustainability: A Study on Household Renewable Energy Adoption Trends

This study investigates household renewable energy adoption trends in Rohini, Delhi, with a focus on women and climate change mitigation. The transition to renewable energy is crucial for combating climate change and reducing environmental impact. This research surveys 50 households to assess awareness, attitudes, and adoption barriers and drivers for renewable energy technologies owing to climate change. Findings reveal that while many are aware of government incentives and express a willingness to adopt renewable energy, actual implementation is hindered by high costs, lack of information, and technical challenges. Key drivers include environmental concerns and financial savings. The study suggests enhancing adoption through improved financial incentives, community education, and women-focused initiatives. Addressing these factors can foster broader adoption of renewable energy, contributing to effective climate change mitigation strategies.

US federal resource allocations are inconsistent with concentrations of energy poverty.

Recent data from the US Energy Information Administration reveals that nearly one in three households in the United States report experiencing energy poverty, and this number is only expected to rise. Federal assistance programs exist, but allocations across states have been nearly static since 1984, while the distribution of energy poverty is dynamic in location and time. We implement a LASSO-based machine learning approach using sociodemographic and geographical information to estimate energy burden in each US census tract for 2015 and 2020. We then compare the allocation to states from the Low Income Home Energy Assistance Program to an optimized allocation. We allocate funds to the most burdened households, providing them with enough assistance to reduce their energy expenditures so that their household energy burden is equal to a new maximum allowable energy burden. This markedly shifts funds from the northern cold-weather states to the southern warm-weather states.

Household residential energy choices in green transition: insights from a household survey in rural China.

It has been widely recognized that accelerating green residential energy transition from traditional solid fuels (biomass and coal) to clean and high-efficient energy sources is critical for rural sustainable development. However, little attention has been paid to estimate panel data discrete choice models to analyze the dynamic behavior information of individual households in the process of energy transition. Hence, this paper investigates green residential energy transition using a panel dataset from 3308 rural households in eight provinces of China in 2015 and 2018. The results show that although traditional solid biomass still plays a dominating role in rural residential energy choice, fuel switching from solid fuels to modern clean energy alternatives is taking place. Off-farm employment plays an important role in the transition towards more sustainable energy sources, as households with off-farm employed heads and higher off-farm income level are highly likely to choose superior energy alternatives other than traditional biomass. Besides, the educational level of the household head and household location are also important influencing factors of household residential energy choices. Based on these findings, this paper suggests that job creation in non-farm sectors should be given a priority in future policy design to promote rural green energy transition in residential sector. North-south differences should be taken into account, whereas more policy options for optimizing biomass energy use should be explored.

Has the Development of Broadband Infrastructure Improved Household Energy Consumption in Rural China?

Digital infrastructure plays a crucial role in shaping household energy consumption behaviors, especially in the context of achieving carbon peaking and carbon neutrality goals in China. In this study, we explored the impact of broadband infrastructure on household energy consumption and clean fuel choices, using data from the China Health and Retirement Longitudinal Study (CHARLS). In a difference-in-differences (DID) framework, our findings indicate that the promotion of broadband infrastructure significantly increases rural household energy consumption and facilitates a transition to cleaner energy sources. Notably, households with better socioeconomic status, particularly those with higher education and income levels, benefit more from enhanced broadband internet access. Mechanism analysis reveals that the “Broadband China” policy can positively influence household consumption through several potential channels: fostering technological innovation, enhancing energy efficiency in cities, and improving overall environmental awareness. These findings contribute to our understanding of the role of broadband infrastructure in shaping household energy consumption patterns and have important implications for policymakers, particularly in the context of sustainable development and energy transition efforts.

Physical, socio-psychological, and behavioural determinants of household energy consumption in the UK

Determining which attitudes and behaviours predict household energy consumption can help accelerate the low-carbon energy transition. Conventional approaches in this domain are limited, often relying on survey methods that produce data on individuals’ motivations and self-reported activities without pairing these with actual energy consumption records, which are particularly hard to collect for large, nationally representative samples. This challenge precludes the development of empirical evidence on which attitudes and behaviours influence patterns of energy consumption, thus limiting the extent to which these can inform energy interventions or conservation programs. This study demonstrates a novel methodology for estimating energy consumption in the absence of actual energy records by using a large, publicly available data set of energy consumption in the UK. We develop a predictive model using the Smart Energy Research Laboratory (SERL) data portal (with records from nearly 13,000 UK households) and then use this model to predict energy consumption (both electric and gas) for a sample of 1,000 UK householders for which we separately collect over 200 variables relating to climate change attitudes and practices. Our approach uses a set of over 50 independent variables that are shared between the data sets, allowing us to train a model on the SERL data and use it to analyse the relationship between energy consumption and the opinions, motivations, and daily practices of survey respondents. Results show that electricity consumption is influenced by a broader range of factors compared to gas. Household energy use is best explained by physical dwelling characteristics, socio-demographic variables, and certain behavioural and attitudinal measures. Notably, pro-environmental attitudes, frugality, and conscientiousness correlate with lower energy use, while income and consumerism are linked to higher consumption. We discuss how these findings can inform efforts to decarbonise home energy use in the UK.

Empowering energy conservation: A prototype of household energy consumption monitoring based on Internet of Things

Abstract One of the obstacles to control household energy consumption is unavailability electricity instruments/tools to monitor electricity energy consumed by appliances causing a lack of awareness of household energy saving. Energy meter installed on buildings only show electricity consumption in total. This study aims to design and create a prototype system that can monitor and control the electrical appliances usage utilizing the Internet of Things (IoT)-based electronic devices where electricity usage data is stored in Firebase real-time database. The methods carried out are arranged in several stages, starting from data collection, design, configuration, and implementation. The tools used in this research will utilize the ESP8266 as the microcontroller, the PZEM-004T as current sensor and the Blynk as the web server. The tool will send current voltage (Volt (V)) and capacity (Watt (W)) data and then converted to energy and also the costs incurred from electricity usage based on the basic electricity tariff of National Electricity Company (PLN) and the results can be seen directly through IoT (i.e. smartphone, PC, laptop). The accuracy of power measurement by the system is 97.4% compared to measurement used by watt-checker. The results of this study show that an electrical power monitoring system makes people easier to monitor electrical power consumption by appliances used. The pilot measurement shows that a unit system can monitor electricity usage for four units of electronic equipment i.e. water pump, Television, fridge, electrical iron, rice cooker, etc. precisely and succeeded to control and increase energy saving awareness to reduce electricity consumption at the end.

Power Control for Household Energy Storage Inverter With Smooth Mode Transition

Power Control for Household Energy Storage Inverter With Smooth Mode Transition

Household Energy Poverty in European Union Countries: A Comparative Analysis Based on Objective and Subjective Indicators

The study aims to assess household energy poverty in European Union (EU) countries, comparing them based on the Objective Energy Poverty Index and the Subjective Energy Poverty Index. The Objective Energy Poverty Index is derived from indicators such as energy expenditure share, risk-of-poverty rate, and electricity prices. The Subjective Energy Poverty Index includes indicators such as the inability to keep the home adequately warm, arrears on utility bills, and bad housing conditions. Both indices aggregate the indicators mentioned above using equal and non-equal weighting approaches. The analysis uses country-level data from 2019 to 2023 sourced from Eurostat. The findings indicate considerable variation in household energy poverty across the EU, with more pronounced inequalities in subjective indicators than objective ones. Additionally, the study reveals a weak correlation between the Objective Energy Poverty Index and the Subjective Energy Poverty Index, leading to differing country rankings based on these indices. However, the choice of weights in constructing the energy poverty indices does not significantly impact a country’s energy poverty ranking. The paper also identifies countries where household energy poverty decreased in 2023 compared to 2019 and those where it increased. Regarding the Subjective Energy Poverty Index, Croatia and Hungary showed the most notable improvement in their rankings among European countries, while France, Germany, and Spain deteriorated their positions. According to the Objective Energy Poverty Index, Bulgaria, Croatia, Portugal, and Spain demonstrated the most significant improvement, whereas Greece experienced a considerable decline.