Domestic Electricity Research Articles

How promoting domestic electricity became physics outreach

How promoting domestic electricity became physics outreach

Design of a hybrid solar and biomass-based energy system integrated with near-zero energy building: Techno-environment investigation and multicriteria optimization

The current research aims to meet the energy needs of a group of residential buildings in Norway with the least amount of carbon dioxide emission and the greatest amount of renewable energy. The supply side based on the renewable renewable-based energy system is planned and scaled using the real-time data use of domestic hot water (DHW), heating and electricity necessary for the buildings. PVT panels are used in the hybrid solar and biomass-based energy systems to produce both the DHW requirements and the electricity production. The digester is used with the heat pump, which generates heat. A double-effect absorption refrigeration system is also utilized to provide the necessary cooling requirements. On the supply side, the management of the heat streams and the redirection of flows are done using a rule-based regulating system. The whole plant's size is supplied, and the dynamic energy simulation is run. The primary deciding criteria for heating the buildings are the costs of electricity and biomass. The whole system is then optimized depending on operating circumstances, and the outcomes are compared to the design point. PVT may be used to create more than 80% of the yearly DHW. Furthermore, summertime radiation accounts for 64.8% of cooling output since it is more intense and may be converted into cooling energy. Digester/CC also contributes 66.55% of the building's heating, showing that the designers should rely on biomass as wintertime energy costs are higher. The parametric study demonstrates that increasing PVT time and tank capacity has varied effects on efficiency and emissions. Also, On winter days, there was a significant drop in renewable energy generation from summer to autumn, from 82.7 MWh to 28.52 MWh. The optimization results show that at the TOPSIS point, the total cost, efficiency, and emission index are 9.73 $/hr, 36.8%, and 7.75kg/MWh, respectively.

Ischemic Stroke Induced by an Electric Shock in a Patient with Ischemic Cardiomyopathy: An Unusual Association of Events

Electrocution is a well-known accident that can lead to a highly variable clinical presentation, including cardiac and neurological complications. Some studies have shown that electric shock contributes to arterial ischemia; either through vasospasm or by inducing thrombotic reactions. Here, we present a 66-year-old male patient with unrecognized cardiac disease who developed brachio-facial paresis related to ischemic stroke immediately after being electrocuted with domestic electricity.

Domesticating energy flexibility. Learning from great britain’s 2022–2023 demand flexibility service

Demand-response is essential for balancing electricity grids with increasing proportions of intermittent renewable sources of generation. Harnessing the potential for demand-response in domestic settings could deliver widespread benefits for electricity systems and householders. This study applies domestication theory to a major national domestic electricity demand-response programme in Great Britain, exploring how participants integrate demand-response sessions into their everyday routines. The study uses empirical data from twenty-five participants who completed diaries reflecting on their experience of taking part in thirteen demand-response sessions scheduled over a five-month period in winter 2022–23. The study identifies and analyses five pathways for domesticating demand-response, making recommendations to support system-actors in boosting and sustaining the adoption of demand-response. The study concludes that designing electricity demand-response programmes, as a staple of secure low-carbon energy systems, will need to take full account of users’ non-financial motivations, previous experiences of demand-response, and access to enabling technology.

Applying trade mechanisms to quantify dynamic GHG emissions of electricity consumption in an open economy - The case of Switzerland

Quantifying greenhouse gas (GHG) emissions from electricity consumption presents a significant challenge due to the variable nature of the generation mix throughout the year and the complex dynamics of cross-border electricity trade. In this paper, we introduce an innovative methodology designed to accurately capture the hourly GHG emissions linked to electricity imports, and thus electricity consumption. Contrary to conventional approaches, our methodology identifies the relevant generation technologies in exporting countries which are activated for export. This selection is based on (i) the classification of the technologies according to their dispatch cost (merit order), and (ii) considers trade mechanisms from economic theory.We apply this methodology to Switzerland, a country characterized by a low-carbon electricity generation mix, which however heavily relies on imports from neighbouring countries, particularly during the winter months. Over the period from 2017 to 2021, we find that 88 % of Switzerland's domestic electricity demand is met by its own generation—primarily hydro and nuclear—while the remaining 12 % is imported, mainly from fossil-fuel-based sources. Consequently, the average annual GHG emission factor for electricity consumption in Switzerland is 98 g-CO2eq/kWh, with 29 % attributed to domestic generation and 71 % to imports. This figure is 40 % higher than the 70 g-CO2eq/kWh estimated using a conventional approach, which typically underestimates the specific impacts of electricity imports.The disparity between these approaches becomes even more pronounced when considering the seasonal and hourly variations in the electricity mix and the resulting emission factors. These insights are particularly crucial in the context of emerging electricity demands, such as heat pumps and electric vehicles, where accurate GHG accounting can significantly influence policy and investment decisions.

Estimation of Domestic Load Profile for Effective Demand-Side Management

In this article domestic base and shift based load profile are estimated for effective Demand Side Management (DSM). Domestic electricity consumption in Pakistan accounts for approximately 40% of total electricity sales. Effective DSM can reduce electricity consumption. Power generation companies are increasingly recognising the importance of analysing their customers' consumption patterns. This article proposes an agent-based modelling approach for forecasting household electricity consumption profile. AnyLogic software is used for establishing the model that uses variables and functions to estimate base and shiftable load of three hundred households. This article also estimates the weekly and 24- hour load profile for effective DSM operations by smart grid infrastructure. The results show that the agent-based simulation closely approximates real-time data, with a difference of only 2.4%.

Predicting UK Domestic Electricity and Gas Consumption between Differing Demographic Household Compositions

This paper examines the influence of building characteristics, occupant demographics and behaviour on gas and electricity consumption, differentiating between family groups; homes with children; homes with elderly; and homes without either. Both regression and Lasso regression analyses are used to analyse data from a 2019 UK-based survey of 4358homes (n = 1576 with children, n = 436 with elderly, n = 2330 without either). Three models (building, occupants, behaviour) were tested against electricity and gas consumption for each group. Results indicated that homes without children or elderly consumed the least energy. Property Type emerged as the strongest predictor in the Building Model (except for homes with elderly), while Current Energy Efficiency was less significant, particularly for homes with elderly occupants. Homeownership and number of occupants were the most influential factors in the Occupants Model, though this pattern did not hold for homes with elderly. Many occupant and behaviour variables are often considered ‘unregulated energy’ in calculations such as SAP and are thus typically disregarded. However, this study found these variables to be significant, especially as national standards improve. The findings suggest that incorporating occupant behaviour into energy modelling could help reduce the energy performance gap.

Comparative assessment of simple and detailed energy performance models for urban energy modelling based on digital twin and statistical typology database for the renovation of existing building stock

The renovation wave calls for an integrated, participatory, and neighbourhood to neighbourhood approach tailored to the local environments. This can be hindered by the lack of geometric and performance input data about the existing building stock. A parametric digital urban building energy modelling (UBEM) tool was developed for local municipalities to automate calculations for comprehensive renovation strategies utilizing public databases specifically at the neighbourhood level. This article compares the accuracy of two energy performance calculation models (seasonal heat balance method and hourly resistance–capacitance method) used within the tool to detailed energy simulation software and measured energy consumption data of existing group of residential buildings in a same neighbourhood. The accuracy for estimating the total primary energy demand was roughly below 10 % for both simplified models. The seasonal calculation method showed consistent overestimation of space heating, depending on building characteristics. Solar and internal heat gains significantly affect the accuracy of simplified heat balance calculations, particularly in well-insulated buildings, while the more detailed 5R1C lumped capacitance hourly method provides improved accuracy for space heating demand. The comparison of uniform (proportional) and project based window area distribution used in the calculation models showed only marginal difference. The study validated simple seasonal and 5R1C hourly calculation methods using data from an apartment building neighbourhood with 22 apartment buildings. Despite larger deviations in the case of individual buildings, the average deviation from measured heating demand was only around 3 %, the seasonal method slightly overestimating and the 5R1C hourly method slightly underestimating the measured values. The primary energy demand including typical values of domestic hot water and household electricity was overestimated by both simplified methods due to lower electricity and water consumption in reality although the difference was below 7 % for the entire district. This concludes that pooling the building envelope heat loss calculation on a district level improves accuracy on average allowing better assessment of comparative renovation strategies.

Price trends in the global electricity market

The relevance of the research topic is determined by the need to adapt to rapid global changes in the electric power industry, which is associated with a change in the structure of the energy balance, the strengthening of geopo­litical factors, the impact of climate change, economic globalization, new regulatory require­ments, and the rapid development of energy storage technologies and smart networks. These changes lead, on the one hand, to challenges in ensuring energy security, and on the other hand, contribute to significant price volatility in the electricity market. As a result of the influence of global price trends and world energy develop­ment priorities on the domestic electricity sector, the study of these trends is of great importance for Ukraine. The aim of the research is to establish the price trends of the global electricity market with the determination of the key factors of price growth in the context of challenges for Ukraine regarding the stabilization of electricity prices. The research is based on the hypothesis that the factors that determine the trajectory of price changes on the international electricity market are also characteristic of the Ukrainian electricity market. The research was conducted using the methods of statistical analysis, syn­thesis, grouping, tabular and graphical display of results. A retrospective analysis of price dyna­mics on the global energy market was carried out, which showed a faster pace of price changes for energy products than for other products, with a faster increase in oil prices than for coal. The current trends in the development of changes in electricity prices were analyzed, the reasons for their rapid growth in 2021 were identified, and it was noted that in some countries, such as the USA and China, prices remained stable. Using the example of the EU countries, it has been analytically proven that electricity tariffs depend on the price structure. The factors that affect pricing in the field of electricity in the world are determined: energy prices, global crisis pheno­mena, the amount of available supply, weather conditions, supply chain problems, grid infra­struc­ture and distribution, the structure of the electricity market, the share occupied by taxes and fees in electricity prices and the purchasing power of the population. The current state of the electricity market of Ukraine is analyzed, which is characterized by a price imbalance, especially in the retail sector, a settlement crisis between the main market participants, a lack of real competition, limited transparency of the market and opportunities for manipulation on it, and the imperfection of the legislative framework. These factors are exacerbated by external negative influences in the form of a full-scale Russian invasion due to the destruction of electric power infrastructure and loss of capacity

A numerical investigation of a new horizontal wind turbine performance for rural use

In this paper, a new configuration of a horizontal axis wind turbine with three blades for domestic electricity production on farms was numerically simulated. Three configurations were tested numerically: a standard single-blade wind turbine (STWT), a single wind turbine (SWT), and a tandem three-blade wind turbine (TWT) for rural use. For the tandem wind turbine, the effects of pitch angle and the distance between the blades were also investigated. The Gambit and Fluent 19.2 codes were, respectively, used to generate different meshes and determine various parameters. The resolution of the averaged Navier–Stokes equations (RANS) using a finite volume method was conducted. The k–[Formula: see text] realizable two-equation model was chosen for turbulence calculation. The obtained results showed that the maximum power coefficient (Cp) was 0.444 for one of the tandem configurations (TWT), compared to the conventional blade (STWT). The maximum Cp obtained in this study is slightly greater than the experimental results found in the literature. It has also been observed that the flow on these new turbines exhibits a complex phenomenon on both surfaces.

A Feature Engineering‐Based NILM Framework for Appliance Recognition Considering Data Class Imbalance

Due to the diversity and randomness of residential consumption behavior, as well as the different share of domestic electricity demand by appliances, class imbalance problems exist in the non‐intrusive load monitoring (NILM) system. The recognition model becomes biased toward the majority class, which makes the recognition of the minority class difficult. To tackle this challenge, we propose a novel NILM framework for appliance recognition to overcome the insufficient learning problems of the minority class, which combines a multi‐domain feature extraction module, a two‐stage feature selection, and a data oversampling method. Multiple features are extracted to make full of the complementarity of combined features to enhance appliance recognition. Furthermore, a two‐stage feature selection based on minimal‐redundancy‐maximal‐relevance (mRMR) and random forest (RF) is developed to select an optimal feature set. Subsequently, an oversampling method combining K‐medoids and the synthetic minority oversampling technique (KM‐SMOTE) with sampling weights is proposed for data augmentation of the minority class to handle imbalance learning problems. The effectiveness of the proposed method is verified by the experiments on the public dataset PLAID. The results show that, compared with the state‐of‐the‐art techniques, the overall recognition accuracy and F1‐score with the proposed method are enhanced by 4.61% and 2.04%, respectively. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Invisible threats: An investigation of electrical hazards and safety practices among residential electricity consumers

Understanding electrical hazards and implementing safety measures is paramount to protecting lives and property. Therefore, this research investigates electrical hazards in households and safety measures taken by residents in Sokode–Etoe, Ghana. The primary objective is to identify gaps in knowledge regarding electrical hazards among domestic electricity consumers and offer recommendations to enhance safety and mitigate the risks. The data were systematically collected from 200 participants, including both homeowners and tenants, using a structured questionnaire. The results were presented using Likert scale analysis, sample t-test, binary logistic regression analysis, involving statistical hypothesis testing of predictor variable coefficients, Importance-Performance Map Analysis (IPMA) and Necessary Condition Analysis (NCA). Participants showed a high awareness of electrical hazards, yet demonstrated a weaker grasp of safety practices, correct emergency procedures, and infrequent testing of wiring systems by homeowners. The predominant electrical accident that emerged was electrical shock. Most homeowners have not engaged certified electrical inspectors for a decade, reflecting uncertainty about the safety protocols in place. Furthermore, respondents expressed a degree of uncertainty regarding the safety measures implemented in their households concerning electricity usage. This study underscores the pressing need to raise awareness and promote safe electrical practices in residential environments. Such an educational initiative could utilize a variety of communication channels, social media influencers, renowned personalities, customised mobile applications and other platforms. This research stands out as the inaugural investigation offering a comprehensive examination of the hazards related to energy consumption and safety precautions in Ghana. It focuses on an often-overlooked demographic of electricity users in Ghana, shedding light on domestic electrical safety issues and the growing hazards.

Bolivia’s domestic electricity cost supporting scheme during COVID-19: Changes in electricity consumption and household welfare

ABSTRACT In Autumn 2020, the Bolivian government introduced a scheme to support electricity costs, aiming to alleviate the financial strain of a nationwide lockdown on households. Our study delves into the effects of this policy on electricity consumption and its monetary implications for recipients. Focusing on six major Bolivian cities, we analyze a comprehensive dataset comprising monthly electricity usage records from all meters within these urban centers. Additionally, we examine the distribution of consumption changes and monetary benefits across different demographic segments within each city. Our findings reveal that while absolute reductions in bills predominantly favor households with higher incomes, education levels, and smaller sizes, relative reductions, adjusted for income per capita, favor households with lower incomes, education levels, and larger sizes. From a policy perspective, we emphasize the need for targeted assistance for low-income households to uphold the implicit pro-poor objectives of similar emergency subsidy programs.

Confirmation of the power gain for solar photovoltaic systems in alpine areas and across scales

Introduction: High Alpine regions show a great potential for solar photovoltaic electricity production in winter due to the reflective properties of snow and the larger number of sun hours compared to lower urban and peri-urban regions. In countries with a pronounced deficit in domestic electricity production such as Switzerland, utility-scale projects of Alpine-PV power plants are now flourishing. The harsh environmental conditions and the complexity of the high-Alpine topography however challenge the conventional design practices. In this context, the main question the article addresses is the representation of test-scale measurement in the performances of Alpine-PV, utility-scale power plants.Methods: This article focuses on the comparison between long term tests and the first Alpine-PV utility-scale power plant in Switzerland.Results: The results show that the main performance indicators such as the Alpine-to-Midlands final yield ratio or the winter fraction, do scale. However, absolute final yield values are consistently lower at the utility scale.Discussion: The paper discusses the possible impacts of the complex Alpine topography as constraint for the design of the larger extent of utility-scale power plants as well as the influence of scale on the snow induced losses.

Evaluating Offshore Wind as a Catalyst for Trinidad and Tobago’s Petrochemical Sector

This study introduces a comprehensive analysis of offshore wind resource potential in Trinidad and Tobago, leveraging both the Wind Atlas Methodology (WAM) and the numerical wind atlas methodologies to address the region’s sparse wind measurement data. Utilizing atmospheric re-analysis data, specifically the ERA5 dataset, in conjunction with the Weather Research and Forecasting (WRF) model, a generalized wind climates (GWCs) for Trinidad and Tobago was generated. These GWCs, refined with topographical and roughness data, guide the siting of offshore wind farms within the Exclusive Economic Zone (EEZ), considering water depths and proximate onshore terrain influences. The study quantifies the economic feasibility of offshore wind through both a levelized cost of electricity (LCOE) analysis and by evaluating the value of redirected natural gas to the petrochemical industry. The LCOE, though currently higher than subsidized domestic electricity rates, is projected to decrease significantly by 2035. Notably, the value of displaced natural gas for petrochemical production offers substantial economic benefits, with potential payback periods for offshore wind investments well under a decade when considering 2021 methanol and ammonia prices. These findings underscore the strategic significance of offshore wind in Trinidad and Tobago’s energy mix. By transitioning to renewable energy sources, the nation can mitigate reliance on fossil fuels for power generation while optimizing natural gas usage in high-value sectors.

An optimization model for integrated water allocation in the parallel system of Segawe regulating weir and Wonorejo multipurpose dam, Tulungagung, East Java

The parallel system of Segawe Regulating Weir and Wonorejo Multipurpose Dam is one of waterworks in the Brantas river basin. Segawe Regulating Weir was built to divert its local inflow into Wonorejo Reservoir as well as to release certain amounts of water downstream needed for ecosystem maintenance and irrigation. On the other hand, Wonorejo Multipurpose Dam was built to serve for ecosystem maintenance, irrigation, domestic water supply and electricity generation. This research discusses an optimization model that integrates the purposes of the two river structures based on the release-demand ratio and by considering the priority constraints. The optimization model was used to derive the operating pattern under requirement for the initial condition of Wonorejo Reservoir in the first period must be the same as the final condition in the last period. The results show that the reliabilities of Segawe Regulating Weir and Wonorejo Multipurpose Dam for all the purposes can reach 100% in dry, normal and wet years, where the potential energies are 20.33, 22.45 and 24.16 GWh, respectively. However, the results come with some trade-offs in the release capability of each river structure due to the integration concept.

Robotic photogrammetric underwater inspection of hydropower plants

Hydropower is the most important domestic source of renewable energy in Switzerland, accounting for around 57 % of domestic electricity production. The high intensity usage of hydropower plants results in high costs for regular maintenance and inspection, which are currently carried out through manual inspections by professional divers. The aim of this work is to develop a workflow for underwater photogrammetry with Remotely Operated Vehicles (ROV) to supplement or replace these dangerous and expensive dives. A calibration frame was developed to provide a scale reference for the data collected during the inspection. With different acquisition missions, investigations on camera calibration and 3D reconstruction were performed. The reconstruction of underwater objects was successfully implemented. Well- distributed control points provide accurate results as a point cloud with a sub-centimetre accuracy at object distances of up to 6 m. 80 % of the point cloud differ less than 1 cm from the reference scan.

날씨 변수를 고려한 전력 수요량 예측구간 시계열 분석 연구

Annual electricity demand is steadily increasing and the importance of forecasting the electricity demand is emerging since the dependence on domestic electricity is also increasing. The purpose of this study is analysis of the electricity demand considering seasonality and weather variables, for which we study time series modelling and forecasting analysis. ARIMA, SARIMA, ARIMAX, SARIMAX models are handled with optimally selected orders. Out-of-sample forecasting analysis is carried out to evaluate predicted values and their errors such as RMSE, MAE, MAPE and MSLE. The errors by four models are compared. As the optimal model, SARIMAX(2,1,1) (2,1,2,12) model with CDD, HDD and insolation has been chosen. For strict statistical analysis of prediction intervals, normal distribution, laplace distribution and bootstrap method are adopted to construct 80%, 95% prediction intervals. Coverage probability (CP), average length (AL) and mean interval score (MIS) of the prediction intervals by three approximations are evaluated. This study contributes with novelty in that it provides three approaches of prediction intervals along with their comparison. The results of this study are expected to be of practical help in the efficient operation of electricity supply system.

Paving the way: Analysing energy transition pathways and green hydrogen exports in developing countries – The case of Algeria

The measures needed to limit global warming pose a particular challenge to current fossil fuel exporters, who must not only decarbonise their local energy systems, but also compensate for the expected decline in fossil fuel revenues. One possibility is seen in the export of green hydrogen. Using Algeria as a case study, this paper analyses how different levels of ambition in hydrogen exports, energy efficiency and fuel switching affect the cost-optimal expansion of the power sector for a given overall emissions reduction path. Despite falling costs for photovoltaics and wind turbines, the results indicate that in countries with very low natural gas prices, such as Algeria, a fully renewable electricity system by 2050 is unlikely without appropriate policy measures. The expansion of renewable energy should therefore start early, given the high annual growth rates required, which will be reinforced by additional green hydrogen exports. In parallel, energy efficiency is a key factor as it directly mitigates CO2 emissions from fossil fuels and reduces domestic electricity demand, which could instead be used for hydrogen production. Integrating electrolysers into the power system could potentially help to reduce specific costs through load shifting. Overall, it seems advisable to analyse hydrogen exports together with local decarbonisation in order to better understand their interactions and to reduce emissions as efficiently as possible. These results and the methodology could be transferred to other countries that want to become green hydrogen exporters in the future and are therefore a useful addition for researchers and policy makers.

Geo-spatial epidemiology of gallbladder cancer in Bihar, India

Recently, a substantial increase in gallbladder cancer (GBC) cases has been reported in Bihar, India. The region's groundwater can naturally contain harmful concentrations of arsenic, which appears to be epidemiologically linked to the unusually high incidence. However, the root causes remain largely unexplored. Recent findings of uranium in the state's groundwater may also have associations. This study investigates the geo-spatial epidemiology of GBC in Bihar, India—with a focus on the correlation between environmental carcinogens, particularly arsenic and uranium in groundwater, and the incidence of GBC. Utilizing data from 8460 GBC patients' registration records over an 11-year period at a single health center, the research employs Semi-parametric Geographically Weighted Poisson Regression (S-GWPR) to account for non-stationarity associations and explores significant factors contributing to GBC prevalence at a subdistrict level. The S-GWPR model outperformed the standard Poisson regression model. The estimates suggest that arsenic and uranium concentrations in groundwater did not present significant associations; however, this could be due to the lower resolution of this data at the district level, necessitating higher resolution data for accurate estimates. Other socio-environmental factors included demonstrated significant regional heterogeneity in their association with GBC prevalence. Notably, each 1 % increase in the coverage of well- and canal-irrigated areas is associated with a maximum of 3.0 % and 5.2 % rise in the GBC incidence rate, respectively, likely attributable to carcinogen exposure from irrigation water. Moreover, distance to the health center and domestic electricity connections appear to influence the number of reported GBC cases. The latter suggests that access to electricity might have facilitated the use of groundwater pumps—increasing exposure to carcinogens. The results underscore the necessity for targeted health policies and interventions based on fine-resolution spatial analysis, as well as ongoing environmental monitoring and research to better understand the multifaceted risk factors contributing to GBC.