Real Energy Use Research Articles

Occupant's health and energy use in an office building: A sensor-enabled life cycle assessment

Indoor air quality (IAQ) has an important impact on human health and productivity. For this reason, its integration into the life cycle assessment (LCA) framework contributes to sustainably manage the operation of a building and improve the living and working conditions in homes and offices. In this study, the damages on human health caused by IAQ are quantified starting from the air pollutants’ concentrations recorded by dedicated sensors placed in an office building located in Luxembourg. Data on concentrations of total volatile organic compounds, particulate matter and radon are combined with estimated occupancy and intake fractions to calculate the total human health impact expressed in Disability Adjusted Life Years (DALYs). The impacts of indoor air quality on human health prove to be relevant, representing one tenth of the score obtained in a conventional LCA on the operational phase of the building. It can be highlighted that radon, a substance usually overlooked in IAQ studies, had the highest impact, contributing to 46% of the impact caused by exposure to indoor pollutants. The heating loads and the influence of different air exchange rates are analyzed starting from a simplified energy model of the building fed with real energy use data. LCA has proven a useful tool to analyze this trade-off in the operation of the building, where it is found that doubling the ventilation rate would reduce the impact of indoor pollutants on human health by 34% while resulting in less than 1% increase in the total energy demand over the studied period.

Is export quality a viable option for sustainable development paths of Asian countries?

This paper investigates the role of export quality in climate action goal of the sustainable development goals in emerging Asian countries. For this purpose, the empirical model that observes the impact of real GDP, energy use and export quality index on carbon emissions is constructed and is analyzed by ARDL bounds testing approach for the period from 1970 to 2014. We also include the square of real GDP as independent variable to observe the existence of environmental Kuznets curve (EKC) hypothesis which implies the parabolic relationship between economic growth and environmental degradation. The findings show that increase in export quality leads to a fall in CO2 emissions for China and India. In contrast, the effect of increasing export quality increases CO2 emissions in Thailand and the Philippines. Lastly, our asymmetric causality results show that the positive shocks of export quality causes positive shocks of CO2 emissions in Thailand and Indonesia. Furthermore, we found that positive export quality shocks cause negative CO2 emissions shocks in India while negative export quality shocks cause positive CO2 emissions shocks in China. We also confirm the inverted U-shaped EKC hypothesis in China and Thailand.

Using Real Building Energy Use Data to Explain the Energy Performance Gap of Energy-Efficient Residential Buildings: A Case Study from the Hot Summer and Cold Winter Zone in China

The International Energy Agency (IEA) emphasizes that using real building energy use data (RBEUD) to reflect the actual condition of buildings and inform policy-making is the most effective way to reduce buildings’ carbon emissions. However, based on IEA’s evaluation, regional and national building stock data are limited and lacking. Especially for China, the lack of RBEUD in buildings has limited our ability to address the energy performance gap (EPG). In this research, EPG refers to the difference between regulated energy consumption by design standards and actual energy usage. EPG makes it difficult to develop buildings that are energy-efficient. Therefore, this study aims to gather and analyze RBEUD in order to understand the role of occupants’ behavior in explaining the EPG of energy-efficient residential buildings in China. The results suggest that the actual consumption of residential buildings is less than 1/5–1/3 of the theoretical limits. The heat pump and air conditioner’s actual schedules and setpoint settings are the significant drivers that explain the EPG. In addition, the presentation of a database of 1128 households provides actual usage behavior parameters for policy-makers to improve the accuracy of building energy forecasting models.

Development of a bottom-up white-box building stock energy model for single-family dwellings

A new bottom-up white-box building stock energy modelling approach is presented in this paper. The model is a physics simulation-based stock model that can be used to compare the base case building stock with technological variations for comparative assessments. The model accuracy is compared to known stock data for a variety of categories, including end-use, energy source and building type. The model predicts the energy use of a building stock in a Canadian region with good agreement across all categories, with the total energy consumption of the model within 1.5% of the real stock energy use. Our analysis shows that modelling a sufficiently large sample of stock is required to reduce the expected deviation for lesser-represented portions of the stock. A case study illustrates how the model can be applied to compare different heating system distributions, in order to assess their impact on greenhouse gas emissions and peak electricity demand.

Large-scale statistical analysis and modelling of real and regulatory total energy use in existing single-family houses in Flanders

ABSTRACT Large-scale statistical studies on the gap between the real and regulatory energy use in residential buildings in Europe have shown that the regulatory calculation overestimated the real energy use, inflated true energy savings and undermined national energy policy making. Using data from 122,680 Flemish existing single-family houses, this research builds further on existing studies by contributing results for Flanders. The study also examines to what extent available aggregated variables explain the real annual total building energy use using statistical linear models and addresses the problem of multicollinearity and the importance of bootstrapped confidence intervals for model quality control. The overestimation of the real total energy use (and potential energy savings) by the Flemish regulatory method is exceedingly large compared to studies from other EU countries. The Flemish labels prove very poor indicators of the real energy use. Statistical linear models explain up to 46.6% of all variability and indicate that a significant extent of multicollinearity had to be corrected. Half of the variability has been left unexplained and has to be attributed to variables that were not available and the fact that the data were insufficiently accurate. Future analysis will explore whether more complex models identify more evidence.

The Effect of the Internet on Inflation: A Research on ASEAN-5 Countries

Information and communication technologies have become widespread with the onset of globalization, affecting almost every facet of human life. Increasing internet usage has made accessing information swift and easy. The internet has also had a significant economic impact and provided financial benefits to nations all around the world to increase productivity and efficiency and reduce costs. Customers had been able to access products at lower prices as a result of the reduction in market entry barriers and search costs, which led to an increase in competition in the markets. The research aimed to investigate the effect of the internet on inflation in ASEAN-5 countries (Indonesia, Malaysia, Philippines, Singapore, and Thailand). Consumer prices (annual %) were used as an indicator of inflation, and individuals using the internet (% of population) were used as an indicator of internet usage. Control variables such as unemployment rate, real interest rate, energy use and money growth were also included in the research. Panel data analysis was performed using the data of ASEAN-5 countries covering the period of 1994-2014. Pooled least squares method (Pooled OLS) was applied to obtain an estimation of the model. As a result, it is found that as internet usage increases, inflation rates decrease in ASEAN-5 countries.

Does higher innovation intensity matter for abating the climate crisis in the presence of economic complexities? Evidence from a Global Panel Data

Industrial development generally entails a structural transition from resource-based and low-technology activities to medium- and high-tech industrial (MHT) activities that represent higher innovation intensity. A modern, highly complex production structure creates better opportunities for skills development and technological innovation. The present study examines the relationship between innovation intensity and climate change crises by incorporating the factor of economic complexities. For this purpose, we used panel data pertaining to 120 global economies from 1996 to 2019 and applied the CS-ARDL estimation technique to achieve empirically valid results. The outcomes of the estimations revealed that real GDP, trade openness, energy use, and economic complexities have a positive and significant relationship with climate change crises in these economies, whereas innovation intensity has a negative and significant relationship with climate change crises. However, the joint effect of the interaction between innovation intensity and real GDP with economic complexities is positive and significant in terms of climate change crises. Thus, the study concludes that higher innovation intensity has a significant role in determining climate change crises in the presence of complex economic structures.

How Resilient Is the U.S. Economy to Foreign Disturbances?

We assess the relative importance of domestic and foreign disturbances in explaining fluctuations in key macroeconomic variables and find that both types of shocks are equally important. We reach this conclusion within a constructed two-sector open economy DSGE model context, where we isolate the relative contributions of each group of disturbances to post-WWII U.S. business cycles. Our approach is to apply the indirect inference method to test the model’s fit against a four-equation VAR(1) of output, real exchange rate, energy use, and consumption. Our main result is that foreign disturbances are pivotal to driving movements in these home variables; accounting for 38% of the variability in aggregate output, 73% of the variation in the real exchange rate, 45% of the variance of energy use, and 84% of the volatility of consumption. Further, foreign disturbances are also identified to be crucial for some other home macroeconomic variables, explaining larger fractions in changes to investment, labour hours, and real interest rate. However, the U.S. economy appears to be resilient to foreign disturbances with respect to certain macroeconomic variables; in particular, exports, imports, real wages, and domestic absorption.

Statistical data-driven analysis and modelling of total energy use in new or thoroughly renovated single-family houses

The subject of this paper is to analyse how the regulatory calculated energy use relates to the real total energy use for new or thoroughly renovated Flemish single-family houses where electricity is the only energy carrier. Additionally, the authors determine whether statistical data-driven models can help inform current and future home owners and tenants about their energy use (and thus also potential energy savings when applying energy saving measures). These questions are investigated by using housing datasets from the Flemish energy performance database and real energy use data from the Belgian grid operator. The paper comprises outlined database cleansing and filtering choices and enlightening statistical database analyses and figures. The results clearly demonstrate that the regulatory calculation method poorly estimates the real energy use (RMSE-/MAE-results of respectively 7227 kWh/y and 5242 kWh/y), yet both are moderately correlated (τ = .548, p < .001). Further, the statistical regression models show good results at stock level for new or thoroughly renovated Flemish single-family houses (where electricity is the only energy carrier) (adj. R2 up to 65.3%). Nevertheless, their performance at individual building level is still limited and considered too poor for inference as a considerable part of the variance is left unexplained.

Empirical evidence on the impact of urban overheating on building cooling and heating energy consumption

SummaryA primary contributor to urban overheating is the urban heat island (UHI) formed due to increased urbanization. The adverse effects of UHI on building energy use are substantial and well documented. However, such effects are typically demonstrated through numerical simulations which are susceptible to modeling uncertainties and lack of validation resulting in a pressing research gap. Here, for the first time, we conduct a large-scale assessment to demonstrate the devastating impact of UHI on building energy consumption using real building energy use data. We find empirical evidence correlating UHI with building energy use; changes in average UHI intensity of 0.5 K correspond to an increase in monthly cooling energy consumption in a range of 0.17 kWh/m2–1.84 kWh/m2. The study validates theoretical evidence on the impact of UHI on building energy and proposes a highly innovative methodology to assess the impact of overheating on the energy balance of cities.

Do country risks influence carbon dioxide emissions? A non-linear perspective

Abstract This study explores the non-linear effects of real income, energy use, and country risks on carbon dioxide (CO2) emissions in a panel of 111 countries from 1985 to 2014. By applying the panel smooth transition regression model, we find that real income, energy use, and country risks have different impacts on CO2 emissions when using country risks as thresholds. As to the full sample, the results show an inverted U-shaped relationship between CO2 emissions and economic risk, and that the financial and political risk indices have monotonically increasing effects on CO2 emissions. As country risks decrease, the positive effects of real income and energy use on CO2 emissions are first large and then become small. Moreover, with country risks changing, low-income countries have larger sensitivities to CO2 emissions.

Generation and representation of synthetic smart meter data

Advanced energy algorithms running at big-data scale will be necessary to identify, realize, and verify energy savings to meet government and utility goals of building energy efficiency. Any algorithm must be well characterized and validated before it is trusted to run at these scales. Smart meter data from real buildings will ultimately be required for the development, testing, and validation of these energy algorithms and processes. However, for initial development and testing, smart meter data are difficult to work with due to privacy restrictions, noise from unknown sources, data accessibility, and other concerns which can complicate algorithm development and validation. This study describes a new methodology to generate synthetic smart meter data of electricity use in buildings using detailed building energy modeling, which aims to capture the variability and stochastics of real energy use in buildings. The methodology can create datasets tailored to represent specific scenarios with known truth and controllable amounts of synthetic noise. Knowledge of ground truth also allows the development and validation of enhanced processes which leverage building metadata, such as building type or size (floor area), in addition to smart meter data. The methodology described in this paper includes the key influencing factors of real-world building energy use including weather data, occupant-driven loads, building operation and maintenance practices, and special events. Data formats to support workflows leveraging both synthetic meter data and associated metadata are proposed and discussed. Finally, example use cases of the synthetic meter data are described to illustrate potential applications.

Economic growth, exports, and role of energy conservation: Evidence from panel co-integration-based causality models in South Asia

This study examines the relationship among energy use, real gross domestic product, and exports and thereby the impact of energy conservation for the quest of a sustainable environment-gross domestic product growth in the panel of five South Asian countries. The aggregate production function framework is estimated by employing first/second generational panel co-integration-based models for the panel data covering the years 1980–2014. The empirical findings demonstrate a statistically significant panel error correction mechanism among real gross domestic product, capital, labor, and energy use in both export-added and export-excluded models. The findings of panel causality test depict a significant causal relationship running from export and energy use towards gross domestic product in the long run. Furthermore, a significant feedback relationship between energy use and gross domestic product and between exports and gross domestic product has been found in the short run. These findings of vector error correction model-based panel causality test imply that reducing/cutting the extant aggregate energy use (fossil fuel dominant) via conservation policies are somewhat wanting and could be implemented at the cost of lower gross domestic product and export growths, ceteris paribus. Therefore, for reducing the level of carbon emissions arising from fossil fuel-based energy use and for a sustainable aggregate energy use to the production sector per se, there is an immense need of developing environment friendly/green sources of energy in the region. These consolidated and concerted strides of developing and substituting environment friendly energy options into the extant aggregate energy use will, inter alia, ensure the sustainability of environment-gross domestic product growth in South Asia.

Energy Performance, Indoor Air Quality and Comfort in New Nearly Zero Energy Day-care Centres in Northern Climatic Conditions

The European energy policy pushes the member states to transform building stock into nearly Zero-Energy Buildings (nZEB). This paper is focused on data collected from existing nZEB day-care centres,in order to be able to assess possible differences between predicted and actual energy and indoorenvironmental performance. Building structures, service systems and the indoor climate and energyperformance of five day-care centres were investigated in Estonia, Finland and Norway.Indoor climate condition measurements showed that in general, the thermal environment and indoor airquality corresponded to the highest indoor climate categories I and II (EN 15251). Building heating andventilation systems in studied buildings are working without major problems. Good indoor climate conditions were also reflected in the occupant satisfaction questionnaires. For most of the studied buildings, over 80%of the people marked all indoor environment condition parameters (thermal comfort, indoor air quality,acoustics, odour and illuminance) acceptable. The thermal environment in the cooling season was reportedproblematic because it was lower than the minimum temperature for indoor climate category II.Energy consumption analysis showed that measured real energy use was higher, or even significantlyhigher, than the energy use calculated during the design phase. Potential causes of the higher actualenergy consumption are caused by differences of measured and designed solutions, methodology of theenergy calculations, and the differences in user behaviour.Lessons learnt from previously constructed day-care centres can be utilised in the planning and designof new nZEBs.

Energy Performance, Indoor Air Quality and Comfort in New Nearly Zero Energy Day-care Centres in Northern Climatic Conditions

The European energy policy pushes the member states to transform building stock into nearly Zero-Energy Buildings (nZEB). This paper is focused on data collected from existing nZEB day-care centres,in order to be able to assess possible differences between predicted and actual energy and indoorenvironmental performance. Building structures, service systems and the indoor climate and energyperformance of five day-care centres were investigated in Estonia, Finland and Norway.Indoor climate condition measurements showed that in general, the thermal environment and indoor airquality corresponded to the highest indoor climate categories I and II (EN 15251). Building heating andventilation systems in studied buildings are working without major problems. Good indoor climate conditions were also reflected in the occupant satisfaction questionnaires. For most of the studied buildings, over 80%of the people marked all indoor environment condition parameters (thermal comfort, indoor air quality,acoustics, odour and illuminance) acceptable. The thermal environment in the cooling season was reportedproblematic because it was lower than the minimum temperature for indoor climate category II.Energy consumption analysis showed that measured real energy use was higher, or even significantlyhigher, than the energy use calculated during the design phase. Potential causes of the higher actualenergy consumption are caused by differences of measured and designed solutions, methodology of theenergy calculations, and the differences in user behaviour.Lessons learnt from previously constructed day-care centres can be utilised in the planning and designof new nZEBs.

Energy Efficiency of the Baltic Sea Countries: An Application of Stochastic Frontier Analysis

Using the stochastic frontier analysis (SFA) model, this research measures total-factor energy efficiency (TFEE) and disaggregate input efficiency for 10 countries across the Baltic Sea from 2004 to 2014. Real capital, labor, energy use, and carbon dioxide (CO2) are input variables, real gross domestic product (GDP) is the output variable, and renewable energy consumption and urban population are the environmental variables. The results provide not only the TFEE scores, in which statistical noise is considered, but also the determinants of inefficiency, which show the following. (i) Norway, Sweden, Finland, and Latvia perform better with respect to energy efficiency than other countries in the Baltic Sea Region. (ii) Interestingly, the average energy use efficiency scores from 2004 to 2014 in the 10 Baltic countries exhibit a gradual upward trend except for 2009. (iii) For the inefficiency estimates, higher renewable energy consumption and urban population correspond to higher TFEE scores.

Assessing the equity and effectiveness of the GB energy price caps using smart meter data

Keeping homes at a comfortable temperature and reducing household fuel bills are priorities for many governments. In the UK, several interventions have been implemented to achieve these objectives. This paper investigates one such policy lever - the Energy Price Cap - to understand if it has been designed and implemented efficiently and equitably. The price cap was introduced for customers on prepayment meters to combat increased levels of fuel poverty and a lack of competition in this group. However, the price cap was based on several assumptions of how energy is used. In this work, we assess how well the price cap accounts for real energy use using smart meter data. Households on economy 7 (EC7) tariffs were found to spend more than those on standard rate tariffs, as EC7 customers use more electricity during peak hours than assumed in government calculations. Additionally, many of the EC7 customers in this sample still use a considerable amount of gas, suggesting the EC7 heating product is either not sufficient, or is not being utilised in a cost-effective manner. Revisions to the input assumptions in government models for EC7 customers would therefore be beneficial in future price cap levels.

Energy-Related Occupant Behaviour and Its Implications in Energy Use: A Chronological Review

It is essential to understand how significantly occupants’ actions impact the performance of a building, as a whole, in terms of energy use. Consequently, this paper reviews the available resources on energy-related occupant behaviour and its implications in energy use in a building. A chronological review on energy-related occupant behaviour and its implications in energy use has been conducted. As a main existing gap, it was identified by researchers the difference between real energy performance and the one that is predicted during the design stage of a building. The energy predicted during the design stage of a building may be over twice the energy used in the operation stage. Buildings are one of the most energy intensive features in a country. They are affected by the interaction and correlation of several different variables, such as: its physical characteristics, technical systems, equipment, occupants, etc. Therefore, buildings are considered to be complex systems that require a careful and intensive analysis. Moreover, one of the key variables impacting real building energy use is occupant behaviour. The way occupants behave and their motivations are some of the main aspects that need to be considered in a building life-cycle.

The dynamic causal links between CO2 emissions from transport, real GDP, energy use and international tourism

ABSTRACTThis study examines the dynamic causality relationship between international tourism and carbon dioxide (CO2) emissions from transport, real gross domestic product and energy use. The vector error correction model and Granger causality test approach have been used to investigate these relationships for the top ten international tourism destinations spanning the period 1995–2013. Results reveal a unidirectional causality running from CO2 emissions to economic growth without feedback; a bidirectional causality between economic growth and energy use; a bidirectional causality between international tourism and economic growth; and a bidirectional causality between international tourism and energy use. They also suggest that energy use and international tourism both contribute to the decrease of emissions level coming from transport sector, while economic growth leads to the increase of CO2 emissions. This study can be used in policy recommendations by encouraging countries to use clean energy and to stimulate tourism sector for combating global warming.

Energy consumption, carbon dioxide emission and sustainable growth in Nigeria

This study investigates whether the observed reduction in energy intensity in Nigeria between 1970 and 2014 will be sustainable, given a possible tie between energy and output and whether de-intensification or de-carbonisation will be a more sustainable approach to ensuring greener growth in Nigeria. Using time series data on real GDP, energy use, and carbon emission obtained from the Global Economic Monitor (GEM) from 1970 to 2014, results of correlation, copula, cointegration, and Granger causality as well as impulse response analyses show evidence of a weak positive tie between energy and growth for Nigeria, and that de-carbonisation is more sustainable in the short term while de-intensification is more sustainable in the longer term. This study concludes that de-carbonisation and de-intensification policies should be adopted in the short term and in the longer term, respectively, in pursuing greener growth in Nigeria.