Household Energy Research Articles

Can low-input agriculture in semi-arid Burkina Faso feed its soil, livestock and people?

Agriculture in semi-arid Burkina Faso is dominated by mixed crop-livestock smallholder farms with limited investment capacity in production factors, such as improved seeds, fertilizer and equipment. Hence, to make a living, farmers try to make the best use of available resources based on principles of agro-ecology, including crop diversity and nutrient and biomass recycling. We investigated farm-level management of resources (soil, crops and livestock) through time to assess whether the current management options were able to sustain crop and livestock production and fulfil household food requirements. We ran a one-year detailed farm monitoring campaign in collaboration with 22 volunteer farmers representing the diversity of the farming system in our study area. We quantified inputs and outputs in the cropping system (177 fields) for one rainy season. In addition, the weekly dynamics of crop residues left on field were quantified. Moreover, inflow and outflow of resources at farm level were quantified weekly. The cropping system was characterized by a negative nitrogen balance of about 12 kg N/ha/year, with market-oriented farms and large livestock owners having the most negative balance. Legumes grown (sole and intercropping) contributed to alleviate the nitrogen depletion by adding 15 kg N/ha/year to the nitrogen inputs through atmospheric fixation. However, cereal-legume intercropping did not significantly reduce the nitrogen deficit in comparison to sole cereal cropping mainly because of the small proportion of legumes (8%) in intercropped fields. Livestock grazed crop residues left on the soil (739 kg dry matter/ha on average) at a rate of 26 − 76 kg/ha/week, thus strongly reducing the potential for mulching in the region. Livestock protein requirements were rarely met from farm-produced feed with average feed gaps ranging between 40% and 89% of the daily requirements for small and large herd keepers respectively. Large livestock (cattle) owners relied on transhumance during the rainy season, grazing and frequent purchase of crop residues and concentrates to feed their livestock. We estimated that grazed biomass provided on average at least 73% and 58% of metabolizable energy and protein feed requirement of livestock respectively. Concerning food availability, the amount of grain produced was generally enough to fulfil household energy requirements (89–175% of required energy, in kcal), even if households with higher people to land ratio were not self-sufficient. We concluded that the current farm management, even if it provides enough food for the majority of investigated farms, results in soil fertility mining and poor crop livestock production and integration. Our detailed farm data indicate that an appropriate diversity of crops and a better integration of legume crops in the cropping system, associated to improved manure and forage management is needed to sustain crop and livestock production.

Improving the Feed-in Tariff Policy for Renewable Energy Promotion in Ukraine’s Households

This paper deals with improving the feed-in tariff policy for green energy advancement in Ukraine’s households based on assessing the economic efficiency of investment project implementation under the current state support mechanisms. This study was conducted for solar and wind power plants with different installed capacities. The Levelized Cost of Electricity and the payback period for such power plants were calculated considering the ongoing feed-in tariffs and discount rates determined by various equity and debt capital ratios. The results showed that the state support provides attractive payback periods for solar and wind power plants with an installed capacity of ≥30 kW. In comparison, 5 kW solar power plants and wind power plants with a capacity of up to 10 kW are not paid off during the power plants’ lifecycle. It confirmed that the ongoing energy policy in Ukraine’s residential sector is still designed to obtain profits by the owners of generating facilities by selling the excess electricity. In the meantime, its main goal—providing households energy independence—has been levelled. To resolve the issues caused by such a state support model, a methodical approach to improve the feed-in tariff calculation is proposed. In addition, recommendations for reconsidering other policy measures to ensure effective renewable energy development in the residential sector have been made.

Off-farm income promotes energy transition in the Pan-Third Pole cross-national region

The Pan-Third Pole region comprises multiple nations affected by climate vulnerability and energy inequality, wherein promoting energy transitions in rural households would provide a path to combat climate change. Identifying the factors that drive rural household energy consumption and the transition is important. This study performed a micro-survey of 1060 rural households in five countries in the Pan-Third Pole region and empirically analyzed the relationships between off-farm income, energy consumption, and energy transitions. The off-farm income of rural households was found to have a significantly positive effect (p < 0.01) on energy expenditure, indicating that energy expenditure increased with increasing off-farm income. Off-farm income has a significantly positive effect (p < 0.01) on the proportion of commercial energy but a significantly negative effect on the proportion of noncommercial energy. These results indicate that increasing off-farm income can adjust the energy consumption structure of rural households. Furthermore, a robustness check by substituting independent variables, instrumental variable method (IV), and propensity score matching method (PSM) provided strong evidence to prove the robustness of the results. The heterogeneity analysis showed that the effects of off-farm income on energy expenditure and transitions differed among countries, off-farm income had no significant impact on energy expenditure in Cambodia and Myanmar, but it worked for China, Nepal, and Thailand. Finally, policy implications are proposed to promote energy transition in the Pan-Third pole region: providing more full-time or part-time off-farm employment opportunities, employment assistance or skill training by local governments; increasing the pace of infrastructure construction to solve energy inaccessibility; multiple measures to promote the education and environmental knowledge.

Indoor exposure to polycyclic aromatic hydrocarbons associated with solid fuel use in rural China.

Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental contaminants associated with various health risks including lung cancer. Indoor exposure to PAHs, particularly from the indoor burning of fuels, is significant; however, long-term large-scale assessments of indoor PAHs are hampered by high costs and time-consuming in field sampling and laboratory experiments. A simple fuel-based approach and statistical regression models were developed as a trial to predict indoor BaP, as a typical PAH, in China, and consequently spatiotemporal variations in indoor BaP and indoor exposure contributions were discussed. The results show that the national population-weighted indoor BaP concentration has decreased substantially from 46.1ng/m3 in 1992 to 6.60ng/m3 in 2017, primarily due to the increased use of clean energies for cooking and heating. Indoor BaP exposure contributed to > 70% of the total inhalation exposure in most cities, particularly in regions where solid fuels are widely utilized. With limited experimental observation data in building statistical models, quantitative results of the study are associated with high uncertainties; however, the study undoubtedly supports effective countermeasures on indoor PAHs from solid fuel use and the importance of promoting clean household energy usage to improve household air quality.

Application of machine learning to assess people's perception of household energy in the developing world: A case of Nepal

Research on social aspects of energy and those applying machine learning (ML) is limited compared to the ‘hard’ disciplines such as science and engineering. We aim to contribute to this niche through this multidisciplinary study integrating energy, social science and ML. Specifically, we aim: (i) to compare the applicability of different ML models in household (HH) energy; and (ii) to explain people's perception of HH energy using the most appropriate model. We carried out cross-sectional survey of 323 HHs in a developing country (Nepal) and extracted 14 predictor variables and one response variable. We tested the performance of seven ML models: K-Nearest Neighbors (KNN), Multi-Layer Perceptron (MLP), Extra Trees Classifier (ETC), Random Forest (RF), Ridge Classifier (RC), Multinomial Regression–Logit (MR-L) and Probit (MR-P) in classifying people's responses. The models were evaluated against six metrics (confusion matrix, precision, f1 score, recall, balanced accuracy and overall accuracy). In this study, ETC outperformed all other models demonstrating a balanced accuracy of 0.79, 0.95 and 0.68 respectively for the Agree, Neutral and Disagree response categories. Results showed that, compared to conventional statistical models, data driven ML models are better in classifying people's perceptions. It was seen that the majority of the surveyed people from rural (68%) and semi-urban areas (67%) tend to resist energy changes due to economic constraints and lack of awareness. Interestingly, most (73%) of the urban residents are open to changes, but still resort to fuel-stacking because of distrust in the state. These grass-root level responses have strong policy implications.

Governments can nudge household solar energy adoption: Evidence from a field experiment in Switzerland

The use of photovoltaic (PV) systems on residential buildings is a key element in the societal transition to renewable energies. However, despite economic and ecological benefits, many homeowners struggle to adopt PV due to technical complexity, administrative burden, and cognitive biases such as inertia. There is also a lack of research on this issue and on how interventions informed by behavioral science could help increase adoption. We address this gap in the literature by conducting a preregistered field experiment involving 600 homeowners in Switzerland, testing whether two types of personalized behavioral interventions, one based on prosocial motives and one focusing on self-interest, lead to tangible actions towards PV adoption. The results from our pilot study show that both interventions substantially increase adoption behavior compared to a control group and a group that received only general information on PV. The intervention focusing on self-interest, which highlighted homeowners' missed revenues in the past year and thereby invoked loss aversion, yielded the largest effect. In summary, our study contributes to a better understanding of how public organizations can use behavioral interventions to promote renewables without large subsidies.

Cooking Fuel Choice and Wellbeing: A Global Perspective

This paper assesses the relationship between the proportion of the population with primary reliance on different types of fuels for cooking (national averages) and a number of key wellbeing indices. The study uses a data set created from a combination of the Gallup World Poll database and the World Health Organisation (WHO) Household Energy Database. The Gallup database comprises multinational survey data and contains wellbeing indices (Personal Health, Social Life, Civic Engagement, Life Evaluation, Negative Experience, etc.). The WHO database gives the proportion of a population with primary reliance on different types of cooking fuels. In order to understand the relative importance of the choice of cooking fuels in terms of wellbeing, regression modelling is used to control for the effects of demographic variables (income per capita, age, education level, employment, etc.), available in the Gallup database, on the wellbeing indices. The regression analysis results show that clean cooking fuels are strongly influential in health-related indices. By adding access to electricity as an additional predictor variable, the analysis highlights the potential for integrating eCooking into national electrification plans as part of sustainable energy transitions, given that health outcomes appear to be as closely linked to the choice of cooking fuels as to access to electricity.

Assessment of Energy and Heat Consumption Trends and Forecasting in the Small Consumer Sector in Poland Based on Historical Data

The paper outlines the methodology employed for desk-based research, which involved gathering and analyzing empirical data on energy and heating consumption in the Polish small consumer sector. Secondary sources, including reports, documents, scientific publications, and public statistics, were utilized to ensure a comprehensive understanding of the subject matter. The research methodology ensured the acquisition and examination of reliable and extensive data regarding energy and heat consumption among small consumers in Poland. The study investigated consumption trends of hard coal, electricity, and natural gas in Polish households from 2006 to 2021. The findings revealed an increasing pattern in electricity and natural gas consumption, alongside a simultaneous decline in the usage of hard coal. Future consumption was estimated using trend models, and factors contributing to changes in energy consumption patterns were examined, with forecasts to 2027. To achieve decarbonization and address climate objectives, the study underscores the need to increase the proportion of renewable energy sources and boost energy efficiency. The significance of reducing household energy consumption through enhanced insulation, smart energy management systems, and low-carbon alternatives is emphasized. Additionally, the study addresses Poland’s future energy plans as a proactive step toward decarbonizing the national economy. In summary, the study furnishes valuable insights into energy consumption trends and their determinants in the Polish small consumer sector.

Testing the effectiveness of household fuel conservation strategies: Policy implications for increasing the affordability of exclusive clean cooking

BackgroundExclusive clean fuel use is essential for realizing health and other benefits but is often unaffordable. Decreasing household-level fuel needs could make exclusive clean fuel use more affordable, but there is a lack of knowledge on the amount of fuel savings that could be achieved through fuel conservation behaviors relevant to rural settings in low- and middle-income countries. MethodsWithin a trial in Peru, we trained a random half of intervention participants, who had previously received a liquefied petroleum gas (LPG) stove and were purchasing their own fuel, on fuel conservation strategies. We measured the amount of fuel and mega joules (MJ) of energy consumed by all participants, including control participants who were receiving free fuel from the trial. We administered surveys on fuel conservation behaviors and assigned a score based on the number of behaviors performed. ResultsIntervention participants with the training had a slightly higher conservation score than those without (7.2 vs. 6.6 points; p = 0.07). Across all participants, average daily energy consumption decreased by 9.5 MJ for each 1-point increase in conservation score (p < 0.001). Among households who used exclusively LPG (n = 99), each 1-point increase in conservation score was associated with a 0.04 kg decrease in LPG consumption per household per day (p = 0.03). Using pressure cookers and heating water in the sun decreased energy use, while using clay pots and forgetting to close stove knobs increased energy use. ConclusionOur findings suggest that a household could save 1.16 kg of LPG per month for each additional fuel conservation behavior, for a maximum potential savings of 8.1 kg per month. Fuel conservation messaging could be integrated into national household energy policies to increase the affordability of exclusive clean fuel use, and subsequently achieve the environmental and health benefits that could accompany such a transition.

Charcoal Trade in Niger—Product Flows and Business Models

Charcoal is used in Africa for household energy, and the sector involves different actors with specific business strategies. Based on theories on sustainable business models and livelihoods, charcoal traders in five cities in Niger were surveyed about supply chains and strategies. Most charcoal is imported from Nigeria, and smaller quantities come from Benin and Burkina Faso or domestically. Men dominate the trade. Customers value charcoal quality, tree species, packaging, and low prices. Three groups of traders and their business models were identified: small-scale retailers, large-scale retailers, and wholesalers. The charcoal trade is typically combined with trade in other products and is frequently conducted with family members or friends; laborers are employed for loading and unloading. The charcoal business provides a complementary income for the traders’ livelihoods. Most respondents believed that trade would increase in the future; wholesalers expected promising future business opportunities. This study concludes that improvements should focus on quality, better marketing skills, and more sustainable charcoal sourcing. Charcoal use in the Sahel region of Africa should also be studied further to enable the development of effective policies in the West African bioenergy sector. The cross-border charcoal trade creates a need for coordinated policies for a sustainable charcoal sector in the Sahel region.

Forecasting household energy consumption based on lifestyle data using hybrid machine learning

Household lifestyle play a significant role in appliance consumption. The overall effects are that, it can be a determining factor in the healthy functioning of the household appliance or its abnormal functioning. The rapid growth in residential consumption has raised serious concerns toward limited energy resource and high electricity pricing. The propose 134% electricity tariffs adjustment by Electricity Company of Ghana (ECG) at the heat of economic hardships caused by Covid-19 has raised serious public agitation in Ghana (west Africa) . The unpredictable lifestyle of residential consumers in an attempt to attain a comfortable lifestyle and the rippling effects of population growth burdens energy demand at the residential sector. This study attempts to identify the lifestyle factors that have great influence on household energy consumption and predict future consumption of the household with mitigating factors to cushion the effects on high consumption. The study is based on lifestyle data using hybrid machine learning. The hybrid model achieved high accuracy (96%) as compared to previous models. The hybrid model performance was evaluated using mean absolute percentage error (MAPE), root mean square error (RMSE) and correlation coefficient (R) metrics.

A step towards a just transition in the EU: Conclusions of a regression-based energy inequality decomposition

The conceptual and regulatory framework of the European just transition does not consider inequality in household energy consumption. This study addresses the causes of this inequality across the 27 Member States of the European Union (EU) in the period 2010–2020 to contribute to its reduction. To identify these causes, the regression-based inequality decomposition approach is used. The results show that the variation in per capita gross domestic product (GDP), which contributes 38.76% to the inequality of household energy consumption, is the main cause of this inequality. Moreover, the average contribution of GDP per capita in the inequality of household energy consumption is almost negligible in the most developed states. In contrast, it is much higher in the least developed states, suggesting that decoupling between household energy consumption and economic development has not been achieved in all Member States. To promote a just transition to climate neutrality by 2050, the energy transition framework should therefore be broadened to help the least developed states achieve decoupling and align their energy consumption with that of the most developed states.

Risk-based Peer-to-peer Energy Trading with Info-Gap Approach in the Presence of Electric Vehicles

Small-scale smart microgrid is prone to economic consideration of adequate transactive energy sharing and reliable certified power pool hub. Moreover, direct integration of efficient with renewable energy providers in presence of storage such as electric vehicle (EV) aggregation improves the performance of energy systems and guarantees secure trade among the consumers. However, unified modeling of the energy community framework faces the challenge of load management. In this paper, an optimal risk management procedure is proposed for renewable-based prosumers such as photovoltaic (PV), and EV to maximize the horizon of uncertainty parameter. The energy demand in peer-to-peer (P2P) household energy sharing is considered as the uncertain parameter. To this end, in order to study the behavior of a risk-averse and a risk-seeker decision-maker, an information-gap decision theory (IGDT) probability model is applied. In order to demonstrate the performance of the proposed approach, the model is implemented in a test microgrid and the simulation results are presented and discussed.

Exploring factors affecting household energy consumption in the internet era: Empirical evidence from Chinese households

Household sector is the second largest energy consumption sector after industrial sector. With the increasing popularity of the Internet, empirical studies based on large-scale households to study factors affecting household energy consumption are quite rare. This paper integrates Internet behaviors into structural equation model based on the data of Chinese household energy consumption survey in an effort to find out the factors affecting household energy consumption and explore the relationship between these factors. According to the findings of this study, the increased frequency of using Internet has mitigated the positive effect of income on household energy consumption to a certain extent. This paper also comes to some interesting conclusions. For example, the understanding of energy conservation policies has significantly increased the energy consumption of Chinese households. Moreover, different regions and different types of households are faced with different factors affecting energy consumption. With reference to the characteristics of Chinese households, this paper discusses the possible underlying cause of these conclusions, which is of great significance for Chinese government to formulate targeted energy conservation policies and provides a reference for other countries.

Assessing the Impact of Household Energy Transition on Winter Indoor Air Quality in Rural Beijing, China: Field Evidence and Implications

Assessing the Impact of Household Energy Transition on Winter Indoor Air Quality in Rural Beijing, China: Field Evidence and Implications

Predicting household energy consumption in an aging society

Social aging will significantly affect energy consumption in the residential sector, with a critical influence on the demand side of the energy sector, especially for megacities. Despite previous studies on the total change in energy demand due to aging, limited research has focused on high-frequency effects. Using a machine learning model, this study examines how social aging will affect household hourly consumption patterns, covering both the change in total consumption and the hourly distribution. We first unsupervised cluster household high-frequency consumption patterns in Shanghai from 2016 to 2018 into 12 groups, and then trained a finite mixture model to analyze the correlation between clusters and household features. We further used the well-tuned model based on the out-of-sample result to simulate the consumption patterns under scenarios of social aging and income growth. The simulation results demonstrate that in addition to increasing overall energy consumption, an aging society will also change the hourly consumption pattern, leading to a larger gap between peak and non-peak periods.

Climate change impacts on future residential electricity consumption and energy burden: A case study in Phoenix, Arizona

Transitioning to an equitable electricity sector requires a deep understanding of a warming climate's impacts on vulnerable populations. A vital climate adaptation measure is deploying air-conditioning (AC), but AC use can increase household energy costs. We evaluate how a warming climate will affect regional energy equity by tying temperature projections with household temperature response functions derived from smart-meter electricity data in Phoenix, Arizona. We simulate future consumption changes under two climate change scenarios from 2020 to 2070, with and without AC efficiency upgrades.We find that the median elderly and low-income household percentage changes are nearly 5 percentage points higher than their counterparts after controlling for decadal, housing, and cooling infrastructural differences. Improving AC efficiency reduces cooling consumption by up to 70% for vulnerable groups. However, a disproportionate share of racial minorities (Hispanic (21%), Black (18%), Asian (12%)) have energy burdens above 6%, indicating affordability challenges.The energy justice implications of this work suggest that intentional considerations of how technology adoption will affect energy affordability and cooling needs are imperative for households to adapt to a warming climate. Such insights are essential for mitigating risk in vulnerable populations, given that policies often rely on ACs as a primary extreme-heat adaptation strategy.

Drivers of natural gas and renewable energy utilization in the USA: How about household energy efficiency-energy expenditure and retail electricity prices?

Besides the substantial investments in renewable energy development across various economies, natural gas is being widely considered as a transitional fuel to advance global efforts towards achieving carbon neutrality. The study utilizes a dataset spanning the period from 1970 to 2022 and employs recently developed and appropriate econometric methodologies, primarily centered around Fourier functions. Additionally, the analysis includes controls for economic growth and energy expenditure per household to yield findings that are both relevant and actionable for policymakers. Crucially, the bootstrap Fourier quantile causality analysis has revealed several noteworthy findings. Firstly, it indicates that retail electricity prices exert a negative influence on renewable energy consumption, particularly in the upper quantiles, signifying a stronger impact when renewable energy usage is already high. Secondly, household energy efficiency is associated with a reduction in renewable energy consumption, predominantly observed in the first quantile. Thirdly, both energy expenditure per household and economic growth contribute to a notable increase in renewable energy consumption, particularly in the initial three quantiles. Likewise, concerning natural gas consumption, household energy efficiency and retail electricity prices exhibit a dampening effect, albeit in different quantiles–household energy efficiency impacting in the upper quantiles and retail electricity prices affecting the lower quantiles.

Optimization model for home energy management system of rural dwellings

In the context of the increasing popularity of distributed energy, this paper proposes a home energy management system method considering the working state of flexible load to deal with the problem of mismatch between home energy supply and demand. Specifically, in this paper, the flexible load in the system is studied, and the model of flexible load and its working state are established. On this basis, combined with the real-time electricity price of the grid, the model of home energy management system is constructed to minimize the electricity purchase cost and improve the utilization rate of renewable energy, the genetic algorithm is used to solve it, and the influence of time step, flexible load ratio and whether to use energy storage equipment on the optimization degree of the model are analyzed. The research results show that, while meeting the requirements of human comfort and electricity demand, the daily electricity purchase cost of the system with flexible load scheduling is 22.5% lower than that of the system without flexible load scheduling, and the utilization rate of renewable energy is increased by 16.5%. In terms of model optimization, shortening the prediction time step, increasing the proportion of flexible load and using energy storage equipment can further reduce the electricity purchase cost. The case study confirms the effectiveness of the proposed home energy management system model, which can provide an efficient optimal scheduling scheme for household energy saving.

Managing energy efficiency and renewable energy in the residential sector: A bibliometric study

The recent surge in publications addressing household energy efficiency and renewable energy highlights their vital roles in managing national decarbonization and green power transition. The study aims to analyze the research trends in this field to comprehend their significance in shaping residential decarbonization changes. Bibliometric and visualization analyses are applied to bridge existing knowledge gaps by focusing on technology and managerial mechanisms for implementing energy efficiency and renewable energy concepts. Leveraging the Scopus database and VOSviewer 1.6.19 software, the study covers energy efficiency publications from 1978 to 2023 and renewable energy papers from 1984 to 2023. The study clusters academic articles in two ways: keyword co-occurrence and co-authorship analyses. The first one reveals the merging of renewable energy and energy efficiency studies, covering sustainable development, heating/cooling mechanisms, and emerging technology trends. While both topics share commonalities like smart grids and the Internet of Things, renewable energy clusters spotlight specific areas such as bioenergy and wind/solar power. Co-authorship analysis highlights a notable increase in countries considering research topics, reflecting growing international collaboration. Leading contributors include the United States, the United Kingdom, China, Germany, and India. This study equips scientists with a systematic understanding of the evolution and latest research trends in managing household energy efficiency and renewable energy transformations. It aids in identifying promising research directions, further advancing these crucial fields. AcknowledgmentsThe publication was prepared in the framework of the research project “Formation of economic mechanisms to increase energy efficiency and provide sustainable development of renewable energy in Ukraine’s households” (No. 0122U001233), funded by the National Research Foundation of Ukraine.