Electricity Consumption Efficiency Research Articles

Renewal of the regression model for normalization of specific energy consumption

Purpose. To develop a method of updating the regression model for the normalization of specific energy consumption in the presence of frequent and significant changes in the energy efficiency of the production process. Methodology. Analysis of existing methods of updating regression models, comparison of their possibilities, and synthesis of the method of updating the model in conditions of frequent and significant changes in the energy efficiency of the production process. Findings. It was established that in the presence of a significant number of possible variants of structural and mode changes in the energy consumption of the control object, the introduction of associated variables into the regression model is problematic, as it requires an increase in the number of experimental data in conditions of their expected heterogeneity. The flaw of the well-known regression model for normalizing the power consumption of the object of control is revealed, which consists of the fact that the model does not take into account the last values in the sequence of their appearance of experimental data obtained in the process of energy efficiency control. This reduces the accuracy of predicted energy consumption values. It is proposed to update the regression model every time after performing the energy efficiency control and sample adjustment. Adjustments are implemented by checking the homogeneity of the obtained experimental data, followed by their addition to the elements of the existing sample and removal (if necessary) from the sample of outdated data. The defined sequence of adjustment of the initial data allows timely updating of the model and implementation of the forecast of specific energy consumption, entering data reflecting the latest changes that occurred in the facility's energy supply. The proposed method of updating the model implements the approximation in time of the moment of energy efficiency control to the moment of obtaining experimental data for building a regression dependence for normalizing energy consumption values. This helps to increase the accuracy of the forecast of normalized values. A significant change in the conditions of production of products with a violation of the homogeneity of data is accompanied by a transition to the transitional mode of adjustment, where it is proposed to reduce the number of elements of the existing sample, ensuring the sequential removal of the elements furthest from the next moment of control. Extraction continues until data homogeneity is achieved. During the daily control of the efficiency of electricity consumption, the change in the values of the regression model coefficients in the process of its renewal reflects the changes in the object's electricity consumption that occurred over the last day. This allows you to separate their impact from the impact of changes that occurred earlier and to assess the level of this impact. Originality. For the first time, the shortcomings of the existing methods of updating regression models in the conditions of frequent and significant changes in the energy efficiency of the production process were identified. A method of updating the model under these conditions has been developed, which involves adjusting the sample of experimental data by changing the number of its elements and checking the homogeneity of the data. Practical value is that the sequence of actions during the implementation of the developed method of updating the regression model is defined, which allows for an increase in the accuracy of calculating the normalized values of specific energy consumption.

Smart life and sustainable development: a comparative analysis on energy and water efficiency in China and the EU

Smart life relies on huge volumes of data analysis, which makes data centers become important infrastructure in smart city areas. Nowadays, data centers are constructed in many countries and have become increasingly large electricity consumers. The consumption of electricity is caused not only by the servers of data centers but also by the cooling systems. Meanwhile, data centers also demand water - cooling methods, which result in water consumption. As for sustainable development, water and energy consumption are huge challenges. Laws and rules are necessary for utilizing efficiently relevant sources. This paper will analyze China and the European Union (EU) as two examples of jurisdictions to compare how the governments regulate the construction of data centers to implement the thrift of electricity and water. In China, provinces and cities established diverse regulations based on their different natural and climate conditions, thus there is not a uniform model for the implementation in the country. In the EU, the amendment of Energy Efficiency Directive seeks to establish common policies. The difference of rules in these two jurisdictions reflects that China and the EU have their own principles and objectives: China attempts to balance the demand of developing smart city infrastructures and the consumption on natural resources, but the EU has strong ambition on low carbon emission in the whole Union. However, the two jurisdictions still have a common goal to maximize the efficiency of water and electricity consumption which is a fundamental issue for accelerating the transition towards sustainability.

The Effect of Electricity Generation on the Performance of Microbial Fuel Cells for Anammox

The Anammox anaerobic fluidized bed microbial fuel cell (Anammox AFB-MFC) exhibits exceptional performance in both nitrogen removal and electricity generation, effectively eliminating ammonia nitrogen (NH4+-N) and nitrite nitrogen (NO2−-N) pollutants. This technology offers the advantages of high efficiency in nitrogen removal and low electricity consumption. By coupling an AFB with an MFC, the Anammox AFB-MFC was developed through the introduction of anaerobic ammonia-oxidizing bacteria (AnAOB) into MFC. Anammox AFB-MFC’s nitrogen removal ability was found to be superior at an influent COD concentration of 200 mg/L, as determined by a study conducted under unchanged conditions. Subsequently, an open and closed-circuit experiment was performed on the Anammox AFB-MFC system while maintaining a COD concentration of 200 mg/L in the influent. Remarkably, the reactor exhibited significantly enhanced nitrogen removal performance when electricity generation occurred. Throughout the entire experimental process, the reactor consistently maintained high nitrogen removal efficiency and electricity production performance. Under optimal experimental conditions, the reactor achieved a remarkable nitrogen removal rate of 91.8% and an impressive output voltage of 439.1 mV. Additionally, the generation of Anammox bioparticles in MFC significantly contributed to efficient pollutant removal. This study elucidates the impact of organic matter on both the nitrogen removal and electricity generation capabilities of Anammox AFB-MFC, as well as highlights the synergistic effect between MFC electricity generation and nitrogen removal in the reactor.

РАНЖУВАННЯ ЕЛЕКТРОТЕХНІЧНИХ КОМПЛЕКСІВ ВУГІЛЬНИХ ШАХТ ЗА ЕНЕРГОЕФЕКТИВНІСТЮ

The purpose of the article is to improve the quality of the assessment of the efficiency of electricity consumption by electrotechnical complexes of coal mines due to the use of a multidimensional comparison with the application of various ranking rules. The study is devoted to the development of the organization of the assessment of the level of energy efficiency of electrotechnical complexes of coal mines. One of the main components of increasing the level of energy efficiency assessment of coal mines is the implementation of measures regarding the use and implementation of an adequate assessment of the level of their energy use. For this, it is necessary to apply such an evaluation mechanism that would allow to evaluate and analyze indicators that have an unequal effect on the efficiency of electricity use. It is relevant in this direction to determine the universal rules of the assessment procedure, which cover all the key areas of monitoring the level of energy efficiency using the ranking of coal mines. The result of ranking is a certain number of ratings by which the level of energy efficiency is assessed. Therefore, for research purposes, a procedure for evaluating the energy efficiency of electrotechnical complexes of coal mines is proposed, which is based on a multidimensional comparison of efficiency indicators through ranking according to different rules. At the same time, indicators that have the greatest impact on electricity consumption are taken into account. The ranks of coal mines according to energy efficiency have been determined. The assessment criteria were specific electricity consumption, mining and production of coal. It is shown that ranking rules make it possible to determine coal mines that are better or worse in terms of energy efficiency. It is proven that the use of the proposed energy efficiency assessment procedure ensures the reliability of management actions aimed at increasing the level of energy efficiency of the energy consumption system of electrical engineering complexes of coal mines.

Energy, exergy, economic and environmental (4E) analysis of a cryogenic carbon purification unit with membrane for oxyfuel cement plant flue gas

The carbon capture, utilisation and storage (CCUS) process chain is subject to increasing interest, and its overwhelming implementation on the industrial scale appears to be one of the main ways to reduce CO2 emissions. In this context, the optimisation of a CO2 purification process for oxy-combustion cement plant flue gases is proposed. This optimisation is based on a multidimensional study on the energy, exergy, economy, and environmental impacts of the process. The results of the optimisations carried out show that it is more favourable to increase the CO2 recovery above 90%, from an energy, exergy and economic point of view. The analysis of the evolution of the capture cost as a function of the CO2 recovery shows that for a given carbon tax, there is a minimum for the total cost which includes the sum of the carbon tax contributions for the uncaptured CO2 and the capture cost. As the unit uses only electrical energy, the cost and the electricity generation will directly impact the capture cost as well as the overall balance in terms of CO2 avoided. As the electricity price increases from 50 to 250 €/MWh, the CO2 capture cost increases by almost 250%. An analysis of the parameter uncertainties allows to observe their impacts on the results, and to define a standard deviation from the optimised points and show the robustness of these. Considering the technical parametric uncertainties, the standard deviation on the electrical consumption (3.65 kWh/tCO2), CO2 recovery (0.09%) and exergy efficiency (0.92%) is limited.

Experimental performance of a spray tower system for water desalination and indoor thermal comfort

Present work characterizes a spray tower-based desalination system, designed to simultaneously provide fresh water by condensation and supply dehumidified air to occupied spaces. Its configuration is open air-open water, with Celdek 7090 packing in the humidification section and water-cooled helical coils for dehumidification. The performance parameters calculated are: gained output ratio, recovery ratio, coefficient of performance, specific electrical energy consumption, mass ratio, humidification, and dehumidification efficiency. This performance is analyzed for varying air Reynold’s number and water flow rate. The best results were obtained for the sea water flow rate tested of 18 liters per hour, and showed maximum humidification efficiency, dehumidification efficiency, COP, freshwater rate, gained output ratio and concentration factor equal to 87.14%, 94.56%, 3.34, 0.9 liters per hour and 1.05, respectively. Exit air meets the thermal comfort requirements which avoids the ventilation thermal loads in the space cooling.

Графическое исследование показателей энергетической эффективности потребления топливно-энергетических ресурсов странами мира

The article is devoted to the comparative study of the energy characteristics of countries around the world, which is based on the construction of graphic maps of energy characteristics. The article presents the author’s maps of the energy intensity and electrical capacity of GDP by PPP of the countries of the world, the energy intensity and electrical capacity of per capita GDP by PPP of the countries of the world, a map of per capita energy consumption and electricity consumption in various countries of the world, and a map of the characteristics of CO2 emissions in various countries of the world, with the distribution of characteristics along the axes of GDP per capita and per capita electricity consumption. The materials analyze the results of the constructed maps and draw appropriate conclusions. Based on the maps of the energy intensity and electrical intensity of GDP by PPP of the countries of the world, conclusions are drawn about the high differences in the level of energy efficiency of the economies of different countries of the world, both in terms of total consumption of fuel and energy resources and electric energy, in particular. The constructed map of the energy intensity and electrical intensity of per capita GDP by PPP in various countries of the world makes it possible to group countries by indicators of energy efficiency of electricity consumption, taking into account the scale of economic development per capita. The identified country groups make it possible to carry out a subsequent analysis of the energy and economic characteristics of individual countries, to identify common features, and to develop principles, mechanisms, and methods of managing the economy and energy facilities of countries, taking into account the identified features. The map of per capita energy consumption and electricity consumption in various countries of the world presented in the materials made it possible to clearly identify that the indicators of per capita energy consumption and electricity consumption of the countries of the world are proportional. The article presents a map of the characteristics of CO2 emissions from different countries of the world, reflecting the distribution of countries relative to each other in terms of relative CO2 emissions, which allows us to clearly identify a significant difference in carbon dioxide emissions, which indicates a difference in the characteristics of the efficiency of consumption of fuel and energy resources. The results obtained make it possible to perform a subsequent grouping of countries with the identification of common features as well as the development of differentiated directions of energy policy aimed at effective economic development.

Backward and forward linkages in electricity consumption. The influence of supply factors

A higher energy efficiency is a vital component of the decarbonised energy transition. In the current geopolitical context, it also increases the resilience of those economies which do not have meaningful energy resources, particularly in a context of high fossil fuel prices. Identifying the sectors which are mostly responsible for electricity consumption in the production system is relevant to design policies which enhance the efficiency of such consumption. Input-output analysis is an appropriate analytical framework to address this objective, since it allows a deep analysis of the relationships between sectors and between sectors and final demand. Backward and forward effects can be calculated using, respectively, the demand and supply multipliers in the input-output models. Past contributions have not been able to fully capture the electricity consumption of a sector related to its intermediate product demand, including the feedback effects. Therefore, this paper proposes a model which identifies the intersectoral links which are relevant from an electricity consumption point of view, taking into account the total direct and indirect requirements of the products which are used to obtain a final demand and an intermediate demand. This methodology is applied to the Spanish case. The results show that a few sectors concentrate many effects which lead to electricity consumption, suggesting that they should be the focus of energy policies. Policy measures are identified to tackle different effects in distinct types of sectors in order to increase the efficiency in electricity consumption.

Decoupling of Electricity Consumption Efficiency, Environmental Degradation and Economic Growth: An Empirical Analysis

The present study investigates electricity consumption, carbon dioxide (CO2) emission, and economic growth decoupling using data from 1971 to 2020 for the economy of China. The study uses decoupling analysis (DA) as the prime methodology for analysis. Furthermore, the findings put forward a significant contribution to an economic picture of the economy of China and a sizeable addition to related research and findings under the assigned issues discussed in the study. The study’s main contribution is to decouple electricity consumption from the gross domestic product (GDP), which is rare in the existing literature in the context of China. Moreover, the study shows the decoupling of environment affects electricity consumption, and GDP growth. The DA model shows that electricity consumption is the main driving force enhancing economic growth. However, industrialization has increased greenhouse gases, global warming, and climate change due to production and consumption. China’s economy uses coal for energy resources, which indicates that China produces a large proportion of electricity with coal, which causes high CO2 emissions. Finally, further analysis with the Granger causality test confirms the main findings.

Industrial electricity consumption efficiency and energy policy in Japan

This study analyzes the potential for energy savings by identifying inefficiencies in electricity use and their determinants in the Japanese industrial sector. Specifically, we used stochastic frontier analysis to estimate inefficiencies in electricity consumption based on data obtained from electric power companies. We identified significant determinants of electricity consumption efficiency and that changes in national energy policy following the Great East Japan Earthquake changed electricity consumption behavior. The contribution of this study is that its findings can be used to improve the cost-effectiveness of policies aimed at improving energy efficiency.

Intellectual measurement of electrical energy consumption - monitoring device and software

The article presents the principle scheme and software of the intelligent measurement - controldevice that allows determining the efficiency of electricity consumption and the energy efficiency of electrical devices. Mathematical expressions and calibration coefficients of the device for measuringelectrical quantities were calculated. Electronic devices for converting and amplifying analog signals todigital signals were selected and their communication circuits with Arduino microcontroller weredeveloped. Based on the C++ programming language, the software that integrates with the device has beendeveloped. The software determines the efficiency indicators of electricity consumption on 4 interfaces atthe same time. Based on this software tool and device, it was possible to create a control system based oncloud technologies, which allows determining the energy efficiency indicators of a certain area. At the same time Algorithm of the program of regulation of fuel energy resources for the measurement and control system of the efficiency of electric power consumption, and, The Cloud Meters model of the electricity consumption efficiency measurement and monitoring system has been developed.

Ценовые параметры поставки электроэнергии как базис управления спросом на электропотребление в регионе

Energy cost management (more than 45 % in the structure of total costs) can significantly reduce own energy supply costs and improve operational efficiency of an enterprise. The study examines regional electricity price parameters, affected by retail and wholesale electricity markets, in terms of the possibilities for industrial enterprises to implement price-dependent demand management to reduce energy purchase costs. The article aims to distribute Russian regions according to the prospects for reducing energy purchase costs by managing electricity demand schedules. The following methods were utilised: statistical analysis of hourly average electricity prices per year, month and day in the regional context; mathematical modelling and calculation of authors’ coefficients of average electricity prices and coefficients of daily price volatility for assessing prospects for effective energy demand management in Russian regions; construction of positioning maps for grouping and identifying regions where the implementation of price-dependent demand management is possible. Electricity price parameters of all Russian regions were examined. The paper analysed principles of electricity pricing for domestic industrial enterprises, researched the impact of price volatility on energy purchase costs, assessed the contribution of electricity costs to total energy consumption costs of enterprises. Coefficients of average electricity prices, coefficients of daily price volatility and coefficients of efficiency of price-dependent electricity consumption were applied to study electricity price parameters in the regional context. As a result, the article presented a map of electricity price parameters, where regions are grouped according to the possibility of implementing demand management mechanisms. Additionally, specific practical recommendations on price-dependent demand management for electricity consumption of industrial enterprises were given for each identified regional group.

Causes of the appearance of current waves in high voltage electric arc furnaces, and methods of their reduction

This article presents a method of generation and reduction of current waves in high-voltage electric arc furnaces in industrial and mining enterprises, in contrast to existing methods. The developed method is currently relevant for the solution of problems related to the generation of current waves during the operation of high-voltage electrics are furnaces with a power of 3 MWt used in the melting and pouring of metals of different densities at the Navoi mechanical engineering plant. The main goal of implementing the developed method is to reduce the electric energy consumption of high-voltage electrics arc furnaces and to increase the efficiency of electric energy consumption of the furnace.

Analysis of payment priority for electricity consumed in industrial enterprises on the base of classified tariffs

The following issues are considered and resolved in the article: the advantage of using tariffs stratified by time to increase the efficiency of electricity consumption by industrial enterprises; Analysis of the tariff system in the electric power system of the Republic of Uzbekistan and the essence of the effectiveness of the application of differentiated tariffs; In order to justify the application of time-differentiated tariffs, the electricity consumption of the industrial enterprise is analyzed; parameters of electricity consumption are optimized according to different tariffs. In order to regulate the load schedule of the energy system using time-graded tariffs in the morning and evening “peak” periods, a method of reducing the load in "peak" periods is proposed in exchange for increasing energy consumption in the night periods.

Research on the Characteristics and Influencing Factors of Chinese Urban Households’ Electricity Consumption Efficiency

Improving energy efficiency is a key global policy goal for climate protection. Residential energy consumption has also increased rapidly with the acceleration of China’s urbanization process, there is still a lack of studies that deeply explore the microscopic urban household energy efficiency and the main determinants in China, although urban household energy efficiency has attracted the attention of many scholars. We use a two-step method to analyze the electricity consumption efficiency of Chinese urban households in 2014 and 2016, the changing characteristics of household electricity efficiency who live in two-bedroom houses are measured with data envelopment analysis (DEA) method in the first step and the driving factors of changes are analyzed with Tobit model in the second step. The results show that household electricity efficiency gained a small but significant improvement between 2014 and 2016. Household income, age, and education level of the head of household, and housing type are the main drivers of inefficiency. We also adopt robustness tests, such as Bootstrap truncated regression to find this effect still exists. This information can be used in activities such as subsidized energy-saving equipment, energy audits, and information campaigns that aimed at improving household electricity efficiency, thereby increasing their cost-effectiveness and minimizing electricity consumption.

Improving the Efficiency of Electricity Consumption by Applying Real-Time Fuzzy and Fractional Control

Using energy more efficiently is one of the easiest ways to save money, reduce greenhouse gas emissions, and meet growing energy demands. Electricity consumption control is an emergent topic worldwide. The passive house idea is not new, but it is still actual and is discussed by researchers. This paper brings to the reader’s attention the combined use of fuzzy and fractional control methods to increase the performance of electricity consumption control, taking into account the current challenges in the energy field, together with a method for the automatic definition of fuzzy rules. In comparison with the no-control case, a 20% reduction in consumption is achieved with the present proposal. In the case of another control method, a 15% reduction was possible using Shakeri’s team’s method. The simulation of the proposed passive house control proves that it could ensure efficient electricity consumption that can be translated into electricity cost savings between 10 and 50 percent.

A Nonlinear Optimized Hybrid System For Energy Consumption Forecasting From Smart Meters

Smart grids are an alternative to minimize environmental impacts, such as CO2 emissions, and improve the efficiency of electricity consumption in buildings. Power grids enable adequate management and monitoring of consumption because of the periodic storage of measurements and easy access to them. In this scenario, an accurate prediction is a challenging task. Forecasting of consumption series is a defiant problem because data present linear and nonlinear patterns, and a dependence on external variables may be observed. Hybrid models are an alternative to mapping both patterns, which have been widely used to forecast load time series. Autoregressive Integrated Moving Average (ARIMA) and Support Vector Regression (SVR) models are used for this purpose, to map the linear and nonlinear patterns of the series, respectively. In this paper, a nonlinear optimized hybrid system based on ARIMA, SVR, and Particle Swarm Optimization (PSO) is proposed. The system can be divided into three steps. First, the linear patterns are predicted by the statistical model ARIMA. Then, the residual series is modeled using an optimized SVR, in which the parameters are selected from the PSO. One particularity from the proposal is to incorporate the choice of the topology and the inertia coefficient into the system. Lastly, the predictions are combined using the SVR. The simulations were conducted using a real database from smart meters of a building in Taiwan. To evaluate the performance of the proposed method, four related approaches were implemented and compared: a single ARIMA, two linear combination systems, and one non-linear combination system. The results show a superiority of the proposed method in terms of the metrics Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE).

APPLICATION OF SIMULATION RESEARCH TO ANALYSE THE PRODUCTION PROCESS IN TERMS OF SUSTAINABLE DEVELOPMENT

Sustainable development is an very important idea nowadays and it influences on many factors. It is very important to focus on the goals of sustainable development and implement them both in industry and in everyday life. The aim of the article is to analyse the impact of implementing an automatic conveyor belt transport system between the stands of an exemplary assembly line on sustainable development in economic and environmental terms. The analyzed production process consists of one production line with six assembly stations. The efficiency of individual design solutions and electricity consumption were adopted as the evaluation criteria. To compare the two processes, a simulation analysis was performed in the Plant Simulation program. First chapter is the introduction to the article. The second chapter describes the current applications of simulation tests. The third chapter describes the production system that is improved by adding conveyors. The next chapter compares the processes with and without the use of conveyors and presents how much energy must be used additionally by implementing conveyor belts, but also what energy savings can be obtained by installing additional stop sensors. The fifth chapter presents the conclusions: the conducted research allowed concluding that the implementation of conveyor belts affects a higher number of finished products at the same time as the transport of components is manual. However, the best solution is to use conveyors with stop sensors, and the power consumption is then low and more profitable for the enterprise.

Research on the synergies between low-carbon pilot city policy and high-speed railways in improving Chinese urban electricity efficiency

PurposeGlobal climate change is a serious threat to the survival and development of mankind. Reducing carbon emissions and achieving carbon neutrality are the keys to reducing greenhouse gas emissions and promoting sustainable human development. For many countries, taking China as an example, the electric power sector is the main contributor to the country’s carbon emissions, as well as a key sector for reducing carbon emissions and achieving carbon neutrality. The low-carbon transition of the power sector is of great significance to the long-term low-carbon development of the economy. Therefore, on the one hand, it is necessary to improve the energy supply structure on the supply side and increase the proportion of new energy in the total power supply. On the other hand, it is necessary to improve energy utilization efficiency on the demand side and control the total primary energy consumption by improving energy efficiency, which is the most direct and effective way to reduce emissions. Improving the utilization efficiency of electric energy and realizing the low-carbon transition of the electric power industry requires synergies between the government and the market. The purpose of this study is to investigate the individual and synergistic effects of China’s low-carbon policy and the opening of urban high-speed railways (HSRs) on the urban electricity consumption efficiency, measured as electricity consumption per unit of gross domestic product (GDP).Design/methodology/approachThis study uses a panel of 289 Chinese prefecture-level cities from the years 1999–2019 as the sample and uses the time-varying difference-in-difference method to test the relationship between HSR, low-carbon pilot cities and urban electricity consumption efficiency. In addition, the instrumental variable method is adopted to make a robustness check.FindingsEmpirical results show that the low-carbon pilot policy and the HSR operation in cities would reduce the energy consumption per unit of GDP, and synergies occur in both HSR operated and low-carbon pilot cities.Research limitations/implicationsThis study has limitations that would provide possible starting points for future studies. The first limitation is the choice of the proxy variable of government and market factors. The second limitation is that the existing data is only about whether the high-speed rail is opened or not and whether it is a low-carbon pilot city, and there is no more informative data to combine the two aspects.Practical implicationsThe findings of this study can inform policymakers and regulators about the effects of low-carbon pilot city policies. In addition, the government should consider market-level factors in addition to policy factors. Only by combining various influencing factors can the efficient use of energy be more effectively achieved so as to achieve the goal of carbon neutrality.Social implicationsFrom the social perspective, the findings indicate that improving energy utilization is dependent on the joint efforts of the government and market.Originality/valueThe study provides quantitative evidence to assess the synergic effect between government and the market in the low-carbon transition of the electric power industry. Particularly, to the best of the authors’ knowledge, it is the first to comprehend the role of the city low-carbon pilot policy and the construction of HSR in improving electricity efficiency.

Estimating the efficiency in overall energy consumption: Evidence from Slovenian household-level data

This study measures the efficiency of energy consumption in the residential sector in Slovenia. It extends the existing research on the estimation of electricity consumption efficiency by considering the consumption efficiency of multiple energy sources used in households. The detailed disaggregated data from two cross-sectional surveys conducted in the years 2010 and 2014, resulting in a sample of 6882 Slovenian households, is used in the estimation. The study includes energy services in a stochastic frontier framework through a sub-vector Shephard energy input distance function. Several household characteristics are considered in the estimation of energy consumption to control for household heterogeneity. The results reveal that Slovenian households have substantial potential for energy savings, which can be achieved through the replacement of inefficient energy-using capital stock and changed behavioural patterns. Specifically, we found the average inefficiency of energy consumption in Slovenian households to be 25.1% in 2010 and 23.3% in 2014, indicating a slight improvement in residential energy efficiency in the observed period, which is also in line with the EU energy-efficiency targets.