Types Of Energy Use Research Articles

Effects of Energy Economic Variables on the Economic Growth of the European Union (2010–2019)

The economic downturn caused by the financial crisis of 2008–2009 and the intensifying global climate policy trends forced changes in the energy management of the European Union. The study examined how the most relevant energy economic variables affected the economic growth of the E.U. between 2010–2019. The study used the PSL-PM methodology to explore the relationship between G.D.P. (dependent variable) and energy consumption, greenhouse gas emissions, the average energy price, and renewable energy use (independent variables). The main findings are: G.D.P. growth is negatively correlated with CO2 emissions, showing that the E.U. economy is still highly dependent on fossil fuels; the increase in the proportion of renewable energy consumption contributed to the growth of the E.U.’s G.D.P.; CO2 emissions, energy consumption, and the average energy price are more critical in E.U. member states with a lower G.D.P.; renewable energy use and energy balance are essential in countries where more emphasis is placed on replacing traditional energy sources and reducing energy dependence; there is a strong positive correlation between G.D.P. and renewable energy use, indicating that this type of energy use effectively supports E.U. economic growth. The results of the multicollinearity test show that there is also a strong linear dependence between the independent energy economic variables. One of the significances of the study is that the presented and analyzed variables and the relationships between them can contribute to optimizing the E.U.’s currently critical energy management and economic growth.

Building Energy Models at Different Time Scales Based on Multi-Output Machine Learning

Machine learning techniques are widely applied in the field of building energy analysis to provide accurate energy models. The majority of previous studies, however, apply single-output machine learning algorithms to predict building energy use. Single-output models are unable to concurrently predict different time scales or various types of energy use. Therefore, this paper investigates the performance of multi-output energy models at three time scales (daily, monthly, and annual) using the Bayesian adaptive spline surface (BASS) and deep neural network (DNN) algorithms. The results indicate that the multi-output models based on the BASS approach combined with the principal component analysis can simultaneously predict accurate energy use at three time scales. The energy predictions also have the same or similar correlation structure as the energy data from the engineering-based EnergyPlus models. Moreover, the results from the multi-time scale BASS models have consistent accumulative features, which means energy use at a larger time scale equals the summation of energy use at a smaller time scale. The multi-output models at various time scales for building energy prediction developed in this research can be used in uncertainty analysis, sensitivity analysis, and calibration of building energy models.

Carbon taxation: A review of the empirical literature

AbstractIn view of the challenges posed by climate change and the increasingly ambitious climate targets around the world, the search for effective climate policy instruments is gaining momentum. Carbon pricing, for example, in the form of a carbon tax, and its effects are therefore attracting increasing attention in academic as well as policy discussions. We review the empirical effects of carbon taxes with regard to several impact dimensions commonly studied in the literature: environmental effectiveness, macroeconomic effects, impacts on competitiveness and innovation, distributional implications, and public acceptance. An increasing body of empirical studies shows that carbon taxes can effectively reduce carbon emissions or at least dampen their growth while not negatively affecting economic growth, employment, and competitiveness. The existing empirical evidence suggests that the distributional impact of carbon taxes depends on the type of energy use and the indicators to capture distributional effects, as well as on household characteristics. Lump‐sum transfers are shown to be better suited to mitigate regressive effects for lower incomes, while higher incomes benefit more from a reduction of labor taxes. Public acceptance of carbon taxes can be increased by providing public information, avoiding negative distributional effects, and channeling part of the revenues into "environmental projects."

The Missing Link? Insights from an Innovative Feedback Exercise for Household Electricity and Travel Behaviour

The objective of this study was to explore how individuals perceive their different types of energy use and evaluate if this information could be useful for further understanding energy demand reduction. Based on a literature review, an innovative feedback exercise was developed that gave participants feedback on electricity use, travel, and then both electricity use and travel simultaneously. Through the use of an interdisciplinary mixed methods research approach, the findings indicate that electricity use and travel are viewed as being very different, there is an opportunity to improve travel-related feedback when compared to electricity, and most do not see a link between electricity and travel. A small number of participants did see a link between electricity and travel, and this was also explored. These findings, which until now have not been explored in the literature, take a first attempt at comparing how individuals perceive their different types of energy use and highlight the relevance of this type of research in order to further advance energy demand management. Implications for a low carbon energy transition and future areas of research were identified and discussed, including decreasing travel in a way that is perceived as being advantageous, improving feedback that illustrates the importance of individual choices, and the importance of examining multiple energy behaviours simultaneously.

Assessing Eco-Efficiency in Asian and African Countries Using Stochastic Frontier Analysis

This study aims to evaluate the economic and environmental efficiency of Asian and African economies. In the model proposed, Gross Domestic Product (GDP) is considered as the desired output and Greenhouse Gases (GHG), like carbon dioxide (CO2) emissions, as the undesirable output. Capital, labor, fossil fuels, and renewable energy consumption are regarded as inputs, and the GDP/CO2 ratio is the output, by using a log-linear Translog production function and using data from 2005 until 2018, including 22 Asian and 22 African countries. Results evidence cross-countries heterogeneity among production inputs, namely labor, capital, and type of energy use and its efficiency. The models complement each other and are based on different distributional assumptions and estimation methods while providing a picture of Eco-efficiency in Asian and African economies. Labor and renewable energy share increase technical Eco-efficiency, while fixed capital decreases it under time-variant models. Technical improvements in Eco-efficiency are verified through time considering the time variable into the model estimations, replacing fossil fuels with renewable sources. An inverted U-shaped Eco-efficiency function is found concerning the share of fossil fuel consumption. Important policy implications are drawn from the results regarding the empirical results.

Zero energy concept at neighborhood level: A case study analysis

The concept of zero energy has emerged as the flagship for the achievement of energy conservation and CO2 emissions reduction in the built environment. The implementation of the concept beyond single buildings offers the potential of expanding the scale of zero energy performance while overcoming the limitations of single buildings related to building use, size, on-site renewable energy availability and cost. Literature to date has discussed the zero energy concept at neighborhood scale mostly by looking at theoretical and simulated cases, including both existing and new developments. All types of energy use can be considered for achieving a zero energy balance at neighborhood scale or only the building related component. Often research focuses on Renewable Energy sizing and management for achieving the balance. The present paper analyses the real data obtained from the first year of monitoring of a pilot Zero Energy Neighborhood. A comprehensive monitoring schema, with a Web-GIS monitoring platform at its core, has been developed for the measurement and verification campaign. Performance analysis has shown that the pilot neighborhood has achieved the targets set for the net regulated consumption, renewable energy production, and cost. When considering the total consumption and PV production of the neighborhood, the first five months of monitoring starting from the beginning of summer, it has achieved a positive balance. Overall, the neighborhood has achieved a positive energy balance on a yearly basis for its regulated energy needs.

The dynamic relationships among CO2 emissions, renewable and non-renewable energy sources, and economic growth in India: Evidence from time-varying Bayesian VAR model

We apply a three-variable VAR model with probabilistic variability using a time-varying parametric approach to determine the dynamic interactions among GDP growth, energy use by renewable energy sources (RES, wind, solar, or hydro) and non-renewable energy sources (NRES, hydroelectric or coal) and CO2 emission. Further, we characterize and quantify the impact of the nexus on the CO2 emissions, energy sources (RES and NRES) vis-à-vis India's economic growth and fluctuations during 1965Q1-2015Q4. We contribute to the literature by finding that stochastic volatility for RES and NRES appear to be U-shaped besides using TVP-VAR model to the Indian context. This U-shaped pattern seems to be related to economic growth. We also observe the time-varying patterns of the impact transmission mechanisms among energy sources, CO2 emissions, and GDP. In addition, the impulse response of GDP from a positive shock to CO2 varies with the type of energy use in different time horizons.

Energy Resources and Its Present Use in India

Energy is an essential ingredient for human life on earth. It is used in all activities of society, for preparing meals, making cloth, building house, industries and other activities. Human beings require energy at an increasing rate for their sustenance and well-being. The present study is an attempt to understand the details with types of energy use in India. The largest energy source is coal, followed by petroleum and traditional biomass. According to the 2011 Census, the household-level data indicates that only 55.3 per cent of rural homes used electricity as the primary source for lighting. Energy access, with about one fourth of the population lacking access to electricity and energy security, with the country relying on imports for a considerable amount of its energy use, particularly for crude petroleum are key challenges that the country faces with respect to energy. Wide disparity in energy use pattern between the haves and have-nots, urban and rural are also a cause of concern.

Income and energy use in Bangladesh: A household level analysis

We examine how energy use at the household level moves with income in Bangladesh. Using the 2010 wave of Bangladesh Household Income and Expenditure Survey data, our analyses indicate a U-shaped relationship of both electricity use and other types of energy use (combined) with household expenditure. The findings imply that as income grows households increase their energy expenditure less than proportionally, up to a threshold level of income. Beyond the threshold income, energy use increases as a proportion of income, particularly for electricity use. We identify the threshold (turning point) for both electricity and other types of energy use. Based on the current level of expenditure and its growth, reaching the turning point would require 17years for the former category but only 7years for the latter group.

Income and Energy Use in Bangladesh: A Household Level Analysis

We examine how energy use at the household level moves with income growth in Bangladesh. Using the 2010 wave of Bangladesh Household Income and Expenditure Survey data, our analyses indicate a U-shaped relationship of both electricity use and other types of energy use (combined) with household consumption. The findings imply that as income grows, households increase their energy use less than proportionally up to a threshold. Energy use beyond the threshold increases at a higher rate than total consumption, particularly for electricity use. We identify the threshold (turning point) for both electricity and other types of energy use. Based on the current level of consumption and its growth, reaching at the turning point would require 17 years for the former category but only 7 years for the latter group.

A ‘Carbon Saving Multiplier’ as an alternative to rebound in considering reduced energy supply chain requirements from energy efficiency?

A growing area of research into rebound effects from increased energy efficiency involves application of demand-driven input-output models to consider indirect energy consumption effects associated with re-spending decisions by households with reduced energy spending requirements. However, there is often a lack of clarity in applied studies as to how indirect effects involving energy use and/or carbon emissions in supply chains of both energy and non-energy goods and services have been calculated. We propose that more transparency for policymakers may be introduced by replacing consideration of what are often referred to as ‘indirect rebound’ effects with a simple Carbon Saving Multiplier metric. We illustrate using results from a demand-driven input-output model that tracks supply chain activity at national and/or global level. We argue that this captures and conveys the same information on quantity adjustments in energy used in supply chain activity but does so in a manner that is more positive, transparent, understandable and useful for a policy audience. This is achieved by focusing (here via carbon emissions) on the net benefits of changes in different types of energy use at both household and supply chain levels when energy efficiency improves in households.

Estimating potential saving with energy consumption behaviour model in higher education institutions

Abstract Towards sustainable Higher Education Institutions (HEIs), energy consumption behaviour is one of several issues that require an attention by facilities manager. Information from the behavioural aspect would be useful for facilities manager on managing the energy and determining potential energy saving. A lack of information negatively affects this aim. Hence, this paper proposes a methodology for assessing the energy consumption behaviour with the objective determining potential energy saving. The method used energy culture framework as basis and joined with centrographic approach and multiple-regression analysis. A self-administrated survey carried out involving 1400 respondents in selected HEIs. There are four types of energy use among students in HEIs namely, 'high', 'low', ‘medium’ and 'conserve' determined from the centrographic analysis. The energy consumption behaviour model was developed and tested against the holdout sample. Through the model's application, there is a vast potential for energy savings with over 55 kWh daily among the students.

Environmental assessment of food waste valorization in producing biogas for various types of energy use based on LCA approach

This paper aims to evaluate the environmental impacts of valorizing food waste for three types of energy use, namely electricity and heat, city gas, and biogas fuel as a petrol, diesel, and liquefied petroleum gas substitute for vehicle use, with reference to the Hong Kong scenario. The life cycle based environmental assessment is conducted from bin-to-cradle system boundary via SimaPro 7.2.4 with ReCiPe 1.04. All of the inventory data of included processes is based on reports of government and industrial sectors. The results show that biogas fuel as a petrol substitute for vehicle use is advantageous over other types of energy use in regard to human health and ecosystems, and it is also the best considering the government’s future emission reduction targets set out for the power and transport sectors in Hong Kong. By turning 1080tonnes per day of food waste into biogas vehicle fuel as petrol substitute, it reduces 1.9% of greenhouse gas emissions in the transport sectors, which results a larger decrease of GHG emissions than the achieved mitigation in Hong Kong from 2005 to 2010.

A Preliminary Assessment of Energy Consumption Behaviour Pattern and Factors Influence Among Malaysian Higher Education Institutions Students

Towards sustainable campus of higher education institutions (HEIs), energy consumption behaviour is one of the several matters that require attention by the facilities manager. Information on energy consumption behaviour helps on developing a good strategy for energy management. The purpose of this study is to assess energy consumption behaviour among Malaysian HEIs student. This study has an objective to determine energy consumption patterns and analyse the factors that influence the pattern. The 'energy culture' framework consolidated with 'centrographic' approach and econometric analysis used to strengthen the findings. A self-administrated survey carried out involving 158 respondents in Universiti Teknologi Malaysia, Johor. There are three types of energy use among students in HEIs namely, 'high', 'low', and 'conserve'. The 'device', 'activities' and 'building regulation' are the influence factors on the pattern of energy use.

Factor space and study the process of electricity consumption of iron ore enterprises

In article results of researches of the analysis of energy consumption of the domestic mining enterprises with under-ground methods of mining iron ore are given. The structure of energy consumption is given. It was found that the main type of energy use is electricity. The relationship is shown between the consumption of electric power enterprises and the cost of mined iron ore. The need for process control of energy consumption and planning of energy consumption of enterprises is justified. The authors present a classification of factors that influence the effectiveness of the regulation system of electric energy specific losses. A method of creating factor system and integral indicator for controlling the energy supply companies have formulated. It is proposed a reasonable technique to implement effective process of power consumption control of iron ore production from underground activities, which provides step-by-step implementation of that process, and also gives the possibility to plan the activities of the enterprise.

Toward Meeting the Requirements of High-performance Buildings: A Case Study in the U.S. Federal Government

Legislation mandates that the U.S. Federal Government reduce the environmental impact of its buildings. For instance, all new buildings should achieve net-zero energy by 2030, reduce water use by 26% by 2020, and divert 50% of non-hazardous solid waste and construction debris from landfills. In order to meet these mandates, the U.S. Federal Government has incorporated several strategies to retrofit its current building portfolio such as employing integrated design principles, reducing the intensity and type of energy use, protecting and conserving water, and reducing the environmental impact of materials. However, most of these strategies are still in the implementation phase and have not been fully assessed. In response to this need, this exploratory study aims to compare the barriers and solutions to retrofitting a typical Federal office building. The research approach includes synthesizing previous studies and using a case study that examines water and energy data of an existing federal building. The results from this analysis will help to better understand the impact of these barriers, the efforts to overcome them and point toward systems frameworks that can aid in the process.

Selection of micro-cogeneration for net zero energy buildings (NZEB) using weighted energy matching index

Recently, the extended matching indices for electrical and thermal energy were defined for different types of energy use and conversion based on two basic matching indices: on-site energy fraction (OEF), which is the load proportion covered by the on-site generated energy, and on-site energy matching (OEM), which is the on-site generated energy proportion utilized by the load rather than being dumped or exported. Additionally, the overall weighted matching index (WMI) was proposed, combining the extended indices by multiplying them by certain weighting factors expressing the preferences of each. This study presents a new model calculating the weighting factors of the WMI based on the non-renewable primary energy factors of different energy carriers involving the imported fuel, for micro-cogeneration (μ-CHP) under thermal and electrical tracking strategies, with electrical and thermal heat grid feed-in schemes reflecting two opposite extreme matching situations in the net zero energy building: load-matching priority and energy export priority strategies. The model is generic and can be used for hybrid micro-generation options. As a case, a single family house served by a μ-CHP is analyzed under a wide range of electrical outputs and power-to-heat ratios. The μ-CHPs’ characteristics are selected according to the highest WMI.

An analysis of the optimization disaggregation algorithm in the estimation related to energy consumption of appliances in buildings

Generally speaking, energy monitoring system plays an important role in both energy use benchmarking and energy conservation service for large-scale buildings. However, it is often necessary for us to disaggregate the metered data according to types of energy use. Aiming at eliminating unclear concepts between monitoring and disaggregation and incorporating existing algorithms’ advantages into the process in which this estimation is generated, the optimal disaggregation algorithm is developed. Based on the assumption of mutually independent ends, a Bayes process is degenerated into maximization likelihood estimation. Following this, the process is expressed by the least squares. With a new algorithm, an unbiased and overall convergent posterior estimation is provided for each terminal category, which is powerfully supported by theoretical analyses and numerical calculation. Actually, it is proved that the disaggregation algorithm is quite appropriate and cost-efficient for sub-item energy monitoring systems in large-scale buildings. Meanwhile, this thesis also focuses on discussing the conditional probability of overall lessening estimation errors specifically. In this way, posterior estimations of overall accuracy are available when prior estimations are concordantly biased with much different accuracy.

Assessing Impact of Material Transition and Thermal Comfort Models on Embodied and Operational Energy in Vernacular Dwellings (India)

Vernacular dwellings are well-suited climate-responsive designs that adopt local materials and skills to support comfortable indoor environments in response to local climatic conditions. These naturally-ventilated passive dwellings have enabled civilizations to sustain even in extreme climatic conditions. The design and physiological resilience of the inhabitants have coevolved to be attuned to local climatic and environmental conditions. Such adaptations have perplexed modern theories in human thermal-comfort that have evolved in the era of electricity and air-conditioned buildings. Vernacular local building elements like rubble walls and mud roofs are given way to burnt brick walls and reinforced cement concrete tin roofs. Over 60% of Indian population is rural, and implications of such transitions on thermal comfort and energy in buildings are crucial to understand. Types of energy use associated with a buildings life cycle include its embodied energy, operational and maintenance energy, demolition and disposal energy. Embodied Energy (EE) represents total energy consumption for construction of building, i.e., embodied energy of building materials, material transportation energy and building construction energy. Embodied energy of building materials forms major contribution to embodied energy in buildings. Operational energy (OE) in buildings mainly contributed by space conditioning and lighting requirements, depends on the climatic conditions of the region and comfort requirements of the building occupants. Less energy intensive natural materials are used for traditional buildings and the EE of traditional buildings is low. Transition in use of materials causes significant impact on embodied energy of vernacular dwellings. Use of manufactured, energy intensive materials like brick, cement, steel, glass etc. contributes to high embodied energy in these dwellings. This paper studies the increase in EE of the dwelling attributed to change in wall materials. Climatic location significantly influences operational energy in dwellings. Buildings located in regions experiencing extreme climatic conditions would require more operational energy to satisfy the heating and cooling energy demands throughout the year. Traditional buildings adopt passive techniques or non-mechanical methods for space conditioning to overcome the vagaries of extreme climatic variations and hence less operational energy. This study assesses operational energy in traditional dwelling with regard to change in wall material and climatic location. OE in the dwellings has been assessed for hot-dry, warm – humid and moderate climatic zones. Choice of thermal comfort models is yet another factor which greatly influences operational energy assessment in buildings. The paper adopts two popular thermal-comfort models, viz., ASHRAE comfort standards and TSI by Sharma and Ali to investigate thermal comfort aspects and impact of these comfort models on OE assessment in traditional dwellings. A naturally ventilated vernacular dwelling in Sugganahalli, a village close to Bangalore (India), set in warm – humid climate is considered for present investigations on impact of transition in building materials, change in climatic location and choice of thermal comfort models on energy in buildings. The study includes a rigorous real –time monitoring of the thermal performance of the dwelling. Dynamic simulation models validated by measured data have also been adopted to determine the impact of the transition from vernacular to modern material-configurations. Results of the study and appraisal for appropriate thermal comfort standards for computing operational energy has been presented and discussed in this paper.

Integrated food–energy systems for climate-smart agriculture

Food production needs to increase by 70%, mostly through yield increases, to feed the world in 2050. Increases in productivity achieved in the past are attributed in part to the significant use of fossil fuels. Energy use in agriculture is therefore also expected to rise in the future, further contributing to greenhouse emissions. At the same time, more than two-fifths of the world’s population still depends on unsustainably harvested wood energy for cooking and heating. Both types of energy use have detrimental impacts on the climate and natural resources. Continuing on this path is not an option as it will put additional pressure on the already stressed natural resource base and local livelihoods, while climate change is further reducing the resilience of agro-ecosystems and smallholder farmers. Ecosystem approaches that combine both food and energy production, such as agroforestry or integrated crop–livestock–biogas systems, could substantially mitigate these risks while providing both food and energy to rural and urban populations. Information and understanding on how to change course through the implementation of the practices outlined in this paper are urgently needed. Yet the scientific basis of such integrated systems, which is essential to inform decision-makers and to secure policy support, is still relatively scarce. The author therefore argues that new assessment methodologies based on a systems-oriented analysis are needed for analyzing these complex, multidisciplinary and large-scale phenomena.