End-use Electricity Consumption Research Articles

Regional short-term load forecasting method based on power load characteristics of different industries

With the gradual increase in the proportion of end-user electricity consumption, the electrical load has become a crucial issue in carbon emission studies. Precise load forecasting will benefit the treatment, calculations, and markets of carbon emission. To explore the characteristics of industrial power load in depth and improve the accuracy of regional short-term load forecasting, this paper proposes a regional short-term load forecasting method based on the power load characteristics of different industries. First, a power load characteristic index system is established to obtain a fine industry classification. Considering the influence of external factors on the power load, the industries are then further classified depending on their sensitivity to external factors using a combination of grey correlation analyses. For the non-external factor-sensitive industries, an integrated model based on the Shapley value method is adopted; for the external factor-sensitive industries, a factor analysis-bidirectional gated recurrent unit-attention mechanism model is proposed. The final combination of the two is the output of the total regional load forecasting results. The combined forecasting method is tested using power load data from a city in Liaoning, China. The results show that the proposed method has apparent advantages over the traditional single forecasting model in terms of forecasting accuracy.

A Mixed-Methods Approach for Evaluating the Influence of Residential Practices for Thermal Comfort on Electricity Consumption in Auroville, India

With rapid global economic growth and a rise in disposable household income, particularly within a progressively warming planet, the escalating demand for energy to achieve thermal comfort has become a salient concern in the Global South, notably in emerging economies like India. This burgeoning need for cooling solutions has not only underscored the vital role of energy consumption but has also accentuated the imperative of comprehending the ensuing implications for electricity policy and strategic planning, particularly within the ambit of the Global South. This study explored the nuanced landscape of active cooling within an intentional community, Auroville, in southern India, aiming to discern the factors underpinning household preferences and practices in the pursuit of thermal comfort. Employing a mixed-methods approach, this study contributed empirically and methodologically to the interdisciplinary discourse by analysing residential electricity consumption patterns and cooling practices within selected households in the specified community. The study unfolded in three methodological stages: firstly, an analysis of climatic data coupled with an environmental stress index (ESI) assessment; secondly, the monitoring of end-user electricity consumption followed by rigorous data analysis; and lastly, the utilisation of qualitative in-depth interviews and observational techniques. This study’s outcome yielded empirical insights into the unprecedented shifts in the ESI for Auroville since 2014. Furthermore, the study unravelled the intricate complexities inherent in occupant behaviour within residential structures, thereby offering valuable insights into the practices that shape householders’ cooling preferences. This research enriched the understanding of the dynamics of energy consumption in the pursuit of thermal comfort and contributes to the broader discourse on sustainable development and energy policy in the context of climate change.

Monitoring Energy-Loss-Driven-Cost by Using Earned Value Simulation in Complex Systems

The economic impact of energy loss stemming from end-user electricity consumption is a significant concern, with historical trends revealing escalating costs. Effectively managing both peak and off-peak demands remains a formidable challenge due to the unpredictable nature of consumer behaviors, leading to energy wastage. This study delves into the nexus of demand uncertainty, financial repercussions, and potential strategies to mitigate energy losses in the evolving landscape of electricity consumption.that causes financial loss. This simulation measure of time series data serves the purpose of determining what possibly contributes to policy and regulatory reforms and its notion as an economic growth pathway in Australia. The objective of this study is to build a relationship between social factors and financial aspects and discuss the issue of energy loss that emerges from the lack of leverage between end-users, providers and suppliers of electricity. Recognising the financial burdens associated with energy loss as electricity demand continues to rise, the investigation aims to elucidate the complexities underlying the difficulties in controlling these losses. The distinctiveness of the electricity industry, characterised by its prototypical nature, introduces dynamics that contribute to energy losses, thereby impacting electricity prices. Employing quantitative analysis, this research employs the Earned Value Method (EVM) tool to scrutinise the influential role of consumer behavior in precipitating financial losses. The study provides a comprehensive examination of the interplay between electricity demand and the adverse effects of energy loss during peak and off-peak consumption periods. Utilising time series data through simulation measures, the research identifies key metrics influencing the formation of electricity costs and prices. The findings not only contribute to a deeper understanding of the energy loss parameter but also offer insights into potential policy and regulatory reforms. With a focus on Australia, the research aims to establish a relationship between social factors and financial considerations, emphasising the issue of energy loss arising from the lack of alignment between end-users, providers, and suppliers of electricity. The study concludes by proposing pathways for economic growth through strategic interventions and collaborative efforts within the electricity ecosystem.

Asymmetric effect of electricity consumption on CO2 emissions in the USA: analysis of end-user electricity consumption by nonlinear quantile approaches.

The study examines the asymmetric effect of electricity consumption on carbon dioxide (CO2) emissions by analyzing end-user groups. In this context, the study focuses on the USA, which is the largest economy. The study includes the most available monthly data from January 1973 to November 2021, performs nonlinear quantile approaches as Granger causality-in-quantiles, nonparametric causality-in-quantiles, and quantile-on-quantile regression (QQR). Besides, quantile regression (QR) approach is used for robustness checks. The empirical results show that (i) correlation relationship between the electricity consumption and CO2 emissions changes according to the terms; (ii) there are generally causality effects in quantiles excluding some lower (0.05, 0.25), middle (0.70, 0.75), and high (0.95) quantiles, while the results for end-user groups vary; (iii) similarly, there is nonparametric causality from the end-user electricity consumption indicators to the CO2 emissions for the mean (return) and the variance (volatility) in most of the quantiles excluding some; (iv) the effects of the electricity consumption indicators on the CO2 emissions are higher in lower quantiles; (v) the QR results show the robustness of the QQR results. Overall, the effects of the electricity consumption indicators on the CO2 emissions are asymmetric and change according to the terms, quantiles, mean, variance, and end-user groups. Furthermore, policy implications are discussed.

Empirical BAC factors method application to two real case studies in South Italy

The application of Building Automation and Control (BAC) systems has many advantages. One of these is the reduction of the end-user electricity consumption and, if applied to lighting systems, the achievement of well-acknowledged benefits from daylight, such as productivity, health, visual comfort and well-being. Concerning the first aspect, the international Standard EN 15232 proposes the so-called BAC Factors (BF) method to assess the impact of BAC systems on the final energy consumption. The method provides a simplified estimation of the energy savings due to automation in buildings and questions arise on its applicability in some situations. For this reason, the authors have carried out an experimental study aiming at comparing the energy savings calculated using the simplified BAC factor method with those evaluated with a measurement campaign on a laboratory setup. In particular, the BF are evaluated for an office and a residential environment, using sets of data measured in two cases study in South Italy by testing two lighting control systems in different end-uses (residential and office). The comparison between the sets of data shows the limits of the simplified BAC factor method.

Analysis on electricity use and indoor thermal environment for typical air-conditioning residential buildings in Malaysia

In residential buildings, accurate forecast of time-varying electricity demands is important for the estimation and prediction of electricity consumption. Information of the end user's electricity consumption patterns is necessary as it has a significant impact on the load curve in the utility grid. Thus, this study aims to provide detailed information on the electricity use and indoor thermal environment for typical residential buildings. Field measurements were conducted in 19 selected dwellings in Kuala Lumpur, Malaysia to specifically measure the total and the air conditioner (AC) electricity usage along with the indoor thermal environment. There were significant differences in the total electricity consumption among low-, middle-, and high-income dwellings. However, for the AC electricity consumption, the different income groups do not display notable differences. This might be due to the occupant behaviour of using the air conditioner mostly during sleeping hours. The measurement results of all targeted dwellings showed that the daily averages of the total and the AC electricity consumption are 14.5 kWh/day and 3.9 kWh/day, respectively. The daily averages of the AC electricity usage in the living room and the bedroom are 2.7 kWh and 4.4 kWh, respectively. The fraction of the daily peak demand from all targeted dwellings shows that the peak at the nighttime is due to the use of the air conditioner. Moreover, the patterns of hourly indoor thermal environment showed an average of 30.1 °C (living room) and 29.3 °C (bedroom). Generally, the comfort level for the indoor temperature lies between 23 °C and 26 °C, while for relative humidity, the comfortable range is between 40% and 70%. These findings provide preliminary understanding of the detailed characteristics of residential electricity use and indoor environment in Malaysian dwellings and can be used to predict the electricity demand in the future.

Implications of the timing of residential natural gas use for appliance electrification efforts

Current strategies for deep decarbonization of the residential building sector invoke the following three pillars of action: (1) radically improve the efficiency of end-use electricity consumption, (2) shift to 100% renewable generation of electrical grid power, and (3) move aggressively to electrify all remaining fossil fuel end-uses. Due to the previous unavailability of high temporal resolution natural gas consumption data, the pursuit of this policy agenda has largely occurred in the absence of a thorough understanding of hourly variations in the intensity of household natural gas use. These variations can have important downstream impacts on the electricity system once electrification has been achieved. This study presents a series of analyses which are based upon a novel dataset of hourly interval natural consumption data obtained for (N = 17,072) households located within a low-income portion of Southern California Gas Company’s service territory. Results indicate that diurnal patterns of hourly natural gas use largely coincide with the timing of daily peak electricity loads. These findings suggest that the aggressive electrification of residential end-use appliances has the potential to exacerbate daily peak electricity demand, increase total household expenditures on energy, and, in the absence of a fully decarbonized electrical grid, likely result in only limited greenhouse gas emissions abatement benefits.

Estimates of the impact of extreme heat events on cooling energy demand in Hong Kong

To better understand the relationship between energy consumption, and prevailing climatic condition, the present study uses Hong Kong’s observed air temperature records, end-use electricity consumption, and population datasets to: (a) investigate the spatial pattern of cooling energy requirement i.e. cooling degree days on a typical normal and extremely hot summer day using co-kriging geospatial mapping technique; (b) analyze the annual trend of cooling degree days in the city; and (c) quantify the impact of extreme heat events on the summer cooling energy requirements. Results revealed reasonable predictability of city-wide cooling degree days with the co-kriging method which uses two covariates i.e. “elevation of the weather station” and “building volume density within the 1000 m radius neighboring area”. Homogeneity and heterogeneity in cooling degree days’ distribution were found during the summer daytime and nighttime, respectively indicating the method’s ability to delineate the urban heat island effect with increased magnitude during extreme heat events. Quantitatively, the extreme heat events increased cooling degree days by 80–140% depending on the event type, a range consistent in recent years (2011–2015). Lastly, we provided the implications of our findings to building and urban design; and future energy planning.

Modelling of end-use electricity consumption and saving potential in household sector in northern thailand

This study presents the actual state of electricity consumption in the household sector in northern region. The characteristics of household electricity consumption was considered to be an essential information for overview estimation of energy usage. The feasibility of energy conservation by improving end-use electricity energy efficiency was investigated. A questionnaire interview survey of 2,500 households concerning 36 kinds of appliances was conducted covering urban and rural areas in northern region in 2016 to identify the characteristics of household electricity consumption. The survey covers three areas: (i) household characteristics, (ii) dwelling characteristics, and (iii) appliances. The survey results were extrapolating, by using the energy model which implies the majority of household electricity consumption in the area level, to estimate the whole electricity consumption for northern region. The result overall electricity consumption in the household in northern region will be 5,604.10 GWh in the year 2016 shows with a make-up of refrigerator (32.10 %), air conditioner (18.04 %), light bulb (17.72 %), television (9.36 %), fan (7.63 %), rice cooker (5.19 %), iron (4.57 %), water heater (3.07 %) and washing machine (2.32 %). Around 16.14 % of electricity consumption, 847.24 GWh or 479.96 kt CO2, could be reduced by means of replacement with higher efficiency appliances. The electricity saving potentials are 65.23 % by changing fluorescent light bulb (FL) to Light Emitting Diode bulb (LED), 44.83 % by changing Cathode Ray Tube television (CRT) to LED television, 1.58 % for rice cooker, 1.53 % for iron, 1.03 % for washing machine, 0.78 % for water heater, 0.70 % for fan, 0.29 % for refrigerator and 0.23 % for air conditioner. The greenhouse gas mitigation from energy reduction potential including the policy recommendation are also raised.

Climate sensitivity of end-use electricity consumption in the built environment: An application to the state of Florida, United States

The link between climate and energy needed for space conditioning has been widely studied, but is still beset with uncertainties. The uncertainties are further compounded by the projected climate change impacts, which will likely increase the frequency of weather and climate extremes. Unlike previous approaches, we leveraged non-linear statistical learning methods to develop predictive models for residential and commercial electricity usage to understand the relationship between weather, climate and electric power consumption. Our analyses were implemented for the state of Florida, one of the most energy intensive states with geographic and demographic vulnerability to climatic change. Our results indicate that the method of Bayesian additive regression trees (BART) best captures the complex structure of the data. We conclude that mean dew point temperature is a more suitable predictor of climate sensitive load than the most widely used degree-days variables. Moreover, wind-speed and precipitation are key predictors of the climate sensitive portion of electricity consumption. We also find that the residential electricity consumption has more spatio-temporal heterogeneity and is more influenced by consumer behavior than the commercial sector.

HVAC terminal hourly end-use disaggregation in commercial buildings with Fourier series model

One major obstacle encountered in building energy conservation and retrofit is the lack of detailed energy submetering data. Direct submetering is expensive and sometime very difficult to be installed in real practice. For example, the HVAC terminal end-use electricity consumption is extremely difficult to measure, because its data is always mixed together with lighting-plug or power submeter. This paper presents a new approach to solve this problem, which is based on a Fourier series model (FSM) for calculating the lighting-plug and power submeters in commercial buildings, and then disaggregate the HVAC terminal end-use hourly electricity consumption from them. Compared with black-box models, such as ANN, SVM and so on, FSM as a grey-box model has two key advantages (1) the application is convenient because of its simple model structure and (2) once a model is developed, it can be used in other same type commercial buildings directly. Measured data from two office buildings and two shopping malls located in Shanghai are analyzed in this paper. The disaggregation results demonstrate that the method is accuracy within a reasonable degree. The calculated hourly HVAC terminal end-use electricial consumption is close to the real measured data. The MRE (mean relative error) and CV (coefficient of variability) both can be controlled within 10%, and in some special cases they are almost within 1%.

A study of the potential benefits of semi-transparent photovoltaics in commercial buildings

This study investigates the potential benefits of semi-transparent photovoltaic windows on the energy, daylighting and thermal performance of commercial buildings. A general simulation methodology is proposed and utilized, integrating thermal, electrical and daylighting analysis. The impact of various building design parameters on the selection of ideal optical properties of semi-transparent photovoltaics is examined. The potential performance of Poly-Si, a-Si/μc-Si and organic cell technologies is also studied. The selection of the module optical properties is shown to be sensitive on the daylight and lighting controls applied and photovoltaic cell technology utilized. The selection of a semi-transparent photovoltaic module with 10% visible effective transmittance resulted in the lowest annual end-use electricity consumption (as low as 5kWh/m2/yr). Finally, simulation results suggest that high cell operating temperatures of up to 64°C could occur that might cause accelerated degradation when organic thin film technologies are used.

Assessment of end-use electricity consumption and peak demand by Townsville's housing stock

We have developed a comprehensive model to estimate annual end-use electricity consumption and peak demand of housing stock, considering occupants' use of air conditioning systems and major appliances. The model was applied to analyse private dwellings in Townsville, Australia's largest tropical city. For the financial year (FY) 2010–11 the predicted results agreed with the actual electricity consumption with an error less than 10% for cooling thermostat settings at the standard setting temperature of 26.5°C and at 1.0°C higher than the standard setting. The greatest difference in monthly electricity consumption in the summer season between the model and the actual data decreased from 21% to 2% when the thermostat setting was changed from 26.5°C to 27.5°C. Our findings also showed that installation of solar panels in Townville houses could reduce electricity demand from the grid and would have a minor impact on the yearly peak demand. A key new feature of the model is that it can be used to predict probability distribution of energy demand considering (a) that appliances may be used randomly and (b) the way people use thermostats. The peak demand for the FY estimated from the probability distribution tracked the actual peak demand at 97% confidence level.

An In-Depth Analysis of the Electricity End-Use Consumption and Energy Efficiency Trends in the Tertiary Sector of the European Union

In 2005 Joint Research Centre of the European Commission (EC-JRC) started an in-depth survey of the electricity end-use consumption and energy efficiency trends in order to assess the energy efficiency potential in the building sector in the European Union Member States (EU-27).1 The survey is updated every two years, the last one being carried out in 2009. Data for end-use electricity consumption for the tertiary sector are very scarce and are not routinely collected by any national or European statistical office. The data are assembled from a variety of sources: published reports and papers, interviews with experts and researchers, including electricity distribution companies' data. At the same time, data on efficiency trends of the most common end-use equipment are collected from multiple sources, including equipment manufacturers. The survey aims to link the efficiency improvements to the trends in consumption, and to have an estimate of the impact of efficiency policies on energy consumption. In particular, accounting for electricity consumption is a very important step for the development of energy policies, but so far electricity consumption analysis has been neglected or underestimated in policy development and related research. The paper presents the main results and conclusion of the 2009 survey. 1The European Union comprises the following 27 countries: Austria (At), Belgium (Be), Bulgaria (Bg), Cyprus (Cy), Czech Republic (Cz), Denmark (Dk), Estonia (Ee), Finland (Fi), France (Fr), Germany (De), Greece (Gr), Hungary (Hu), Ireland (Ie), Italy (It), Latvia (Lv), Lithuania (Lt), Luxembourg (Lu), Malta (Mt), Netherlands (Nl), Poland (Pl), Portugal (Pt), Romania (Ro), Slovak Republic (Sk), Slovenia (Sl), Spain (Es), Sweden (Se), and United Kingdom (UK).

Operational experience of a residential photovoltaic hybrid system

This paper reports on the operational experience acquired with a photovoltaic (PV) hybrid system installed as a line extension alternative at a residence located in northern New York State. The system includes an 850 W PV array, 25 kWh worth of battery storage, and a 4 kW propane generator. The paper features a detailed analysis of the energy flows through the system and quantifies all losses caused by battery storage round-trip, rectifier and inverter conversions, and non-optimum operation of the generator and of the PV array. The paper also analyzes the evolution of end-use electricity consumption since the installation of the PV hybrid system.

An analysis of residential sector energy use in Hong Kong

We have gathered and analysed energy-consumption data in the residential sector in Hong Kong. We surveyed 200 households in 5 different classes of residential units. Sub-sector and end-use electricity consumption have been estimated. Major electricity-consuming items are room air-conditioners, lighting and refrigerators. Ownership levels of most essential and common electrical appliances are above 80%. A major growth area willbe appliances associated with home entertainment and comfort cooling and heating. Implications for future demands of energy in the residential sector are discussed.