Residential Energy Efficiency Research Articles

Residential and Industrial Energy Efficiency Improvements: A Dynamic General Equilibrium Analysis of the Rebound Effect

Residential and Industrial Energy Efficiency Improvements: A Dynamic General Equilibrium Analysis of the Rebound Effect

Residential and Industrial Energy Efficiency Improvement: A Dynamic General Equilibrium Analysis of the Rebound Effect

The aim of this paper is to investigate bi-directional spillovers into residential and industrial sectors induced by energy efficiency improvement (EEI) in both the short- and long-term, and the impact of nesting structure as well as the size of elasticities of substitution of production and utility functions on the magnitude and the transitional dynamic of rebound effect. Developing a dynamic general equilibrium model, we demonstrate that residential EEIs spillovers into the industrial sector through the labor supply channel and industrial EEIs spill-overs into the residential sector through the conventional income channel. Numerical simulations calibrated on the U.S. suggest that not taking into account these spillover effects could lead to mis-estimate the rebound effect especially of residential sector EEIs. We also demonstrate how the size and the duration of the rebound effect depend on the value of elasticities of substitution. Especially, the elasticity of substitution between energy and non-energy consumption in household utility and the elasticity of substitution between physical capital and labor in production play a major role. Numerical simulations suggest that alternative sets of value for the elasticities of substitution may give sizable different patterns of rebound effects in both the short- and long-term. In policy terms, our results suggest that energy effciency policies should be implemented simultaneously with rebound effect offsetting policies by considering short- and long-term wide-economy feedbacks. As a consequence, they recall for considering debates about what type of policy pathways is more effective in mitigating the rebound effect.

Low Carbon Transition of Residential Electricity Consumption in Nigeria: A System Dynamics Modeling Approach

It is imperative that Nigeria reduces wastage in residential electricity consumption and motivate energy saving behaviors through energy efficiency measures. These strategies aim to minimize frequent power sheds, which in turn increase reliability, thus benefiting the environment and electricity consumers. This article examines the effects of such innovative approaches to electricity savings in Nigeria through: 1) prepaid electricity metering systems and 2) fast replacements of inefficient and aging appliances. Relationships between residential electricity consumption, energy efficiency, and carbon footprint were also assessed vis-a-vis the replacement of old energy appliances and analogue electricity billing systems with more efficient devices and through prepaid metering systems, respectively. These techniques intend to promote energy saving behaviors. A System Dynamics model built on Stella platform, is used to analyze the implication of energy efficiency policy implementation on residential electricity consumption based on a simulation period of 41 years (2010 - 2050). Secondary data were sourced from the Bureau of Statistics, published articles, Nigerian power sector, World Bank, and primary data using cross sectional surveys of residential electricity consumers. Results, not only revealed that availability and utilization of prepaid electric meters and efficient appliances would motivate electricity saving behaviors, but also showed that efficient technologies could be the main drivers to future energy savings. Results also showed that carbon emissions were cut down by 45% in 2050. In addition, changes in electricity tariffs did not have any consequential effect on electricity consumption, but would rather influence electricity demand. Also, large number of occupant per house might have a negative impact on the Nigerian economic growth. Finally, results suggest that subsidies should be used on new household appliances as an effective energy policy measures. The developed model can be replicated in similar sectors in other emerging economies.

Understanding the residential energy efficiency financing coverage gap and market potential

Access to upfront capital remains a primary barrier in residential energy efficiency adoption. Government-sponsored programs exist for low-income households while traditional financing serves creditworthy households. However, there remains a coverage gap for those with moderate incomes too high to qualify for low- income programs, but without access to friendly capital. With limited research in this space, this study aims to: (1) develop a model to estimate the number of households in the coverage gap; and (2) explore their spatial distribution. For the state of Michigan, we used data from the US Census Bureau and approximately 12,000 green bank loans to estimate the energy efficiency financing coverage gap across the state's 83 counties using a binomial mixed model. We found that credit score and income interacted to largely determine whether an applicant was approved. Households in the highest income quintile achieved a 50% chance of approval with a moderate credit score (662) while those in the lowest needed a very high credit score (715) for the same odds. Overall, this created an estimated 12% energy efficiency financing coverage gap of households statewide, with individual county levels between 0% and 24%. Broadly, understanding the market potential and spatial distribution of this coverage gap could allow impact-driven financiers such as green banks or community development financial institutions to expand programs that may offer alternative underwriting criteria. Expanding loan access to this underserved market can promote energy system improvements, policy goals, household living conditions, and an equitable clean energy transition.

A statistics-based method to quantify residential energy consumption and stock at the city level in China: The case of the Guangdong-Hong Kong-Macao Greater Bay Area cities

The residential sector is a substantial consumer of energy worldwide, especially in China, and therefore a focus of energy conservation efforts. Although cities are basic executive units nowadays, their residential energy consumption (REC) is often overlooked. By revealing this research gap, we develop a REC calculation model at the city level (CRECM) and an improved residential stock turnover model (RSTM) to calculate the REC and residential stock of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) cities. Based on these two indicators, the REC intensity is quantified to measure residential energy efficiency. The results show that 11 GBA cities see a dramatic increase in REC over the past 16 years and REC intensities of most cities have plateaued out. The total REC of GBA is expected to rise until that of Guangzhou and Shenzhen reaches the peak. Also, the over residential stock of GBA has tended to saturation in recent years after significant growth, while some cities (i.e. Zhuhai, Huizhou, and Zhongshan) tend to increase. The gaps in REC among cities can be attributed to socio-economic factors (population, GDP, and residential stock) and building characteristics (unit area and construction vintage). Both CRECM and RSTM proposed in this study can provide robust data support for developing building energy efficiency policies for GBA cities as well as other cities across the country

Predictive Counterfactuals for Event Studies with Staggered Adoption: Recovering Heterogeneous Effects from a Residential Energy Efficiency Program

This paper introduces an approach for estimation of treatment effect heterogeneity in event studies with staggered adoption. Traditional impact evaluation methods can be near-term biased in those settings. The proposed approach attenuates biases and recovers heterogeneity more efficiently than traditional methods. It is shown that machine learning algorithms can be used to accurately predict counterfactuals, which can then be used to estimate a distribution of treatment effects. Simulations demonstrate how that approach can be accurate and efficient, even in the presence of dynamic treatment effects. The paper concludes with an application to a large energy efficiency program in the US.

The impact of climate change on thermal climate zones and residential energy efficiency designs during the past decades in China

ABSTRACT In this paper, the impact of climate change on thermal climate zones was reported by using more recent weather data published by the China’s National Climate Center. The impact of these changes on current building energy standards was also investigated. To quantitatively analyse the potential impact of these changes on building energy consumption, building energy simulation techniques were used. This study has found that 27 of the 200 cities investigated in this analysis are assigned to new thermal climate zones, and most of these cities have shifted into a warmer climate zone. Three cities shift into uncategorized zone. According to the building energy standards for residential buildings, the maximum U-factor allowed for building envelope will increase and overall shading coefficient allowed for windows will decrease when the city is reassigned into a warmer zone. The simulation results show that it will generally have an adverse effect on building energy savings for residential buildings. The outcomes of this study reveal that current thermal climate zones cannot provide an adequate instruction for building energy efficiency and updating building energy standards, and thermal climate zones is necessary in future.

Bridging the rural efficiency gap: expanding access to energy efficiency upgrades in remote and high energy cost communities

Islands and remote rural communities throughout the USA pay some of the highest costs for electricity and heating fuel in the nation. For areas with such high energy costs, the benefits of energy efficiency can be significant but rural residents face several geographic, financial, and awareness barriers that make it difficult to invest in home energy upgrades. These barriers combine to create a market failure that we call the “rural energy efficiency gap.” The existence of the rural efficiency gap is supported by data collected from Alaska, Maine, New Hampshire, and Vermont which indicate that the “energy burden,” or percentage of household income spent on energy bills, is 33% higher in rural areas and that participation in residential energy efficiency financing and rebate programs can be significantly lower. The combination of higher energy burdens and greater barriers to participation can lead to inequitable distribution of available resources for energy efficiency, meaning that those who could benefit most from efficiency upgrades are often least able to access them. This work is designed to be a resource for energy efficiency program administrators but may also be of interest to energy efficiency program implementers, policymakers, and regulators. It provides data about the rural energy efficiency gap and identifies barriers to energy efficiency in rural communities. It also highlights strategies that are helping to bridge the gap by making it easier for residents in cold climate, petroleum-dependent states—those with high thermal energy burdens—to increase comfort and safety in their homes while also reducing energy bills. The barriers to rural energy efficiency identified in this paper have been grouped into three categories: geographic barriers, financial barriers, and awareness and access barriers. There are many differences between rural areas across the country, e.g., demographics, utility model and rate structures, energy sources, and consumption patterns. This paper is not intended to suggest that the strategies documented here will necessarily be applicable to all rural areas in the USA

Do residential building energy efficiency standards reduce energy consumption in China? – A data-driven method to validate the actual performance of building energy efficiency standards

Building energy efficiency standards (BEES) are believed to be one of the most effective policies to reduce building energy consumption, especially in the case of the rapid urbanization content in China. However, there is little evidence backed up by measured data to validate the actual effectiveness of BEES in China. Using survey data collected from 1128 households in Chongqing China, this study applied the propensity scores matching method to estimate the effect of two BEES levels: the 50%-BEES (low level) and the 65%-BEES (high level). Results show that buildings built with 65%-BEES, on average, can reduce cooling and heating electricity use intensity (kWh/m2/a) by 41%, compared to buildings in the absence of the BEES. Meanwhile, the adoption of 50%-BEES can reduce cooling and heating electricity use intensity (kWh/m2/a) by 38%. However, energy savings are not significant if comparing buildings with 65%-BEES and 50%-BEES. The results indicate that there exists a performance gap between calculated design performance savings and actual operation energy savings. These empirical findings provide policymakers with valuable feedback on buildings' actual performance. The findings suggest that it is necessary to incorporate outcome-based compliance pathways into the current BEES system. Lastly, a data-driven building policy evaluation mechanism should be developed in China. Energy consumption databases should be developed to support policies such as building energy codes and standards' development and performance evaluation.

Target Setting Outlook for New Residential Building Energy Efficiency Promotion in China: A Frontline Perspective Using Delphi

Promoting energy efficiency (EE) requirements for new residential buildings has been proven to be an effective way to slow down the rapid increase of energy consumption. Its successful implementation relies significantly on the attitudes and participation of various stakeholders within the industry, yet they are normally taken for granted. This paper explores and reports both the consensus among and the diversity of the attitudes of frontline stakeholders toward future EE requirements in the new residential building sector via a nationwide Delphi questionnaire distributed to 29 institutes and 25 experts. Results indicate that promotion of approximately 30% EE every five years until 2030 is suggested and that 20% EE promotion every five years is the most likely to be achieved. In addition, China should progressively adopt the energy intensity index into the current building EE evaluation system. This paper also gives a detailed description of opinions from frontline stakeholders. The findings are expected to help researchers and policymakers better understand the true attitudes of stakeholders, thereby enabling the formation of a proper outlook for new residential building EE promotion.

Large scale residential energy efficiency prioritization enabled by machine learning

Cost-effective energy efficiency improvements in residential buildings can realize 30% energy reduction within this energy sector for the USA. Unfortunately, audits on residences to identify potential savings, generally based on detailed energy models, tend to over-estimate anticipated savings. This leads to wariness on the part of potential investors. We address this issue by taking an integrated data- and physics-based approach, using residential building geometrical and energy system characteristics (e.g., envelope, appliances, and HVAC systems), as well as historical energy consumption for each residence and weather data, to predict monthly natural gas energy consumption and savings from the adoption of individual energy saving measures. This approach requires only those geometrical and energy system characteristics associated with the greatest potential for realized savings which are also easy to obtain. We construct a dataset from a collection of houses with a wide range of energy effectiveness, and train a single statistical model that accurately predicts natural gas energy consumption in any of the individual residences. The model is then used to estimate the savings from most impactful energy efficiency investments for individual residences, as well as the collective grouping. The specific case considered here involves hundreds of university-owned student residences in the U.S. Midwest. The resulting machine-learning derived model is used to predict monthly natural gas consumption with a mean squared error of 0.00023 for unitary scaled cross-validation data. We use a nearest neighbor approach to validate savings estimates for virtually improved residences, identifying the surrogate residence most like an improved residence. This validation demonstrates a savings prediction accuracy to within 3.5% for most of the measures considered. The validated models are shown capable of prioritizing investments among the collective of residences considered. Sequential adoption of the most cost-effective energy efficiency measure among a group of residences renders a total energy reduction of 36%. The practical implications of this research are significant. This integrated machine-learning and physics-based approach to estimate savings could be used in any utility district and throughout all of the USA to enable district-wide residential energy reduction based upon sequential adoption of the most cost-effective energy measures.

The Elusive Effects of Residential Energy Efficiency Improvements: Evidence from Ukraine

Untapped improvements in energy efficiency in the residential sector may deliver large savings in energy use and the CO2 associated emissions. Yet empirical assessments have been difficult and controversial. We collect monthly natural gas meter readings from a sample of homes in Transcarpathia, in Western Ukraine, an early adopter of the country’s trend away from district heating, from January 2013 to April 2017, a period over which the residential natural gas tariffs rose by over 700%. We combine the monthly meter readings with documentation about each household’s heating-related energy efficiency upgrades to the home (wall, attic or basement insulation; new windows; boiler replacement, and insulation around pipes) to form a panel dataset. We estimate the effect of the energy efficiency renovations on natural gas consumption, controlling for weather, income and government energy assistance. The decision to do the renovations and natural gas consumption are likely endogenous (people do the renovations because they hope to consume less), so we instrument for the renovations by creating a cross-validation instrument based on a supply-side argument. Even for a given type of energy efficiency upgrades, the estimated effect of the renovations varies dramatically in magnitude, depending on whether the renovations are instrumented for and on how detailed the fixed effects are. The coefficients on the renovations are almost always negative in our regressions, but practically and statistically significant only when we instrument for the renovations. This is in agreement with our respondents’ difficulty assessing whether the renovations had saved them gas or money. The IV estimates indicate that insulation delivers 13-24% reductions in natural gas usage, and up to a 5% internal rate of return (IRR) to the investment over 20 years. Judicious use of an existing government program can yield positive IRRs and make energy efficiency upgrades a good investment in a generally poor-performing housing market.

What Affects the Progress and Transformation of New Residential Building Energy Efficiency Promotion in China: Stakeholders’ Perceptions

Nationwide energy efficiency (EE) promotion of new residential buildings is affected by multiple factors regarding policies, markets, technologies, capacities, and economics. The perceived influences of these factors by stakeholders are crucial to the effectiveness evaluation of current policies and the selection of policy instruments. However, they are normally assumed or taken for granted. The knowledge gap between stakeholders’ perceptions and research assumptions may lead to researchers’ recognition bias. Correspondingly, this paper aims to identify the significant factors, perceived by frontline stakeholders, influencing nationwide EE promotion of new residential buildings before 2020 and 2030. Factors were collected through literature review and their influence were evaluated via Analytical Hierarchy Process based on the data collected in the questionnaires distributed to 32 institutes. The theory of Nested Policy Design Framework and Policy Environment was used to structure the hierarchy and generate policy implications. Results indicate that (1) policy factors are of the greatest influence before 2020 and market perfection factors will have great influences from 2020 to 2030, indicating the transformation of governance arrangement to “market-based” and “network-based” from the current legal-based system; and (2) factors regarding market needs are of significant influence in both terms, revealing the way the transformation should be accomplished.

Addressing health and equity in residential low carbon transitions – Insights from a pragmatic retrofit evaluation in Australia

Health and equity present obligations and currently under-realised opportunities in low carbon transitions. Energy efficiency improvements of homes may benefit health and access to affordable energy, yet better knowledge about contextual mechanisms and household practices is needed for the development of effective programs. This paper presents a mixed methods evaluation of a quasi-randomised controlled retrofit trial targeting low-income older householders. Socio-technical systems thinking offered a useful approach to explore the construct of the engineering-dominated concept of residential energy efficiency in combination with the people-focused experience of housing and health. The study combined a phenomenological enquiry into householder practices with quantitative analyses to explain health, energy cost, temperature and psycho-social outcomes for winter.The findings showed that small retrofits may mitigate the growing energy demands of this ageing population group, provide better comfort and reduce energy costs, but that the effectiveness of the retrofits was reduced by socially shared heating and ventilation practices that contradicted engineering assumptions, the physiological capabilities of the householder and the modes of energy bill payments. A program that is framed around caring and safety and combines retrofits, tariff optimisations and householder practices could provide equitable climate change mitigation outcomes and co-benefits for health for this population group. The paper concludes with implications for the integration of equity and health as goals into low carbon transitions.

A Multidimensional Approach to Measuring Fuel Poverty

In this study we suggest that a more careful and systematic understanding of fuel poverty can be developed through a multidimensional approach to the relationship between monetary poverty, residential energy efficiency, and heating restriction. Our objective is to provide new ways to better identify those who suffer the most from fuel poverty to optimize policy. Thus, the purpose of this paper is to measure poverty in three steps following Sen (1979): (i) combining poverty characteristics into an aggregate measure involving a fuel poverty index (FPI), (ii) identification and comparison of poor people according to existing and new definitions and (iii) testing the robustness of the fuel poverty composite indicator. Our results show that the usual measures reveal a gap that does not consider all the dimensions of fuel poverty, excluding those who are at or above a certain threshold, but who are nevertheless vulnerable.

Effects of building size growth on residential energy efficiency and conservation in California

Many utility and government programs exist to promote energy efficiency (EE) in residential buildings. While programs have succeeded in reducing per square foot energy usage intensity (EUI), they do not necessarily promote conservation, in terms of reduced total energy consumption. Using statistical analysis and data mining techniques, we examined relationships between home size, electricity and natural gas EUIs, and neighborhood level socio-economic attributes among ∼1.3 million single-family homes in Los Angeles County (LAC). We observed that among homes constructed between 1900 and 2010, the growth in median home size by construction vintage year has outpaced combined EUI reductions by 60%. Results of a Monte-Carlo sampling procedure derived from these observed trends indicate that past historical energy savings within LAC, attributable to state mandated EE policies, could have been equivalently achieved by constraining growth in the size of newly constructed homes. These findings have significant implications for the design of future energy conservation policies within growing urban areas.

A semi-empirical financial assessment of combining residential photovoltaics, energy efficiency and battery storage systems

Extraordinary declines in the cost of photovoltaic systems (PV), combined with a growing range of energy efficient consumer technologies (EE), has driven significant deployment of these two options in many jurisdictions. This deployment has proven to be a key way to mitigate the risks of catastrophic climate change. However, existing retail electricity arrangements can create mixed incentives for households contemplating investing in both PV and EE. This is caused by net metering arrangements that value self-consumption of PV generation far more than PV exports to the grid. This means that falling household demand due to EE may significantly reduce the financial value of PV. Meanwhile, the continuous cost decline of battery storage systems (BS) has encouraged more PV owners to consider storing PV exports to maximise self-consumption. However, there has been little research on whether the addition of BS could reduce barriers to the combined uptake of PV and EE. In this paper, real PV generation and electricity consumption data is used from numerous households in Sydney (Australia), together with a battery cyclelife model, to assess the financial outcomes of combining PV, EE and BS. The results indicate that EE can reduce PV system revenue, that adding BS to a combination of PV and EE generally increases PV revenue, that BS costs are still high for this residential application, and that the uptake of EE can result in deeper BS cycling which reduces the battery lifetime.

Energy Life Cycle Analysis of a Residential Building with the Help of BIM in Different Climates of Iran

With energy resource scarcity and energy crisis in the world, energy efficiency has become a subject of great importance. In warm and humid climates along with cold and mountainous ones, annual energy consumption is too high to achieve desirable living conditions in built environments, and hence energy efficiency measures and practices in such buildings is of utmost priority. Given the direct relationship of amount energy consumption and comfort level of occupants in residential buildings, energy saving and energy efficiency are of increasing importance specifically in the residential sector. In this study, a combination of building information modeling (BIM) and building performance modeling (BPM) is applied to identify appropriate dimensions and building materials to reduce energy in the lifecycle of a building. To perform this modeling, we evaluated various software applications employed in different studies and after identifying their advantages and disadvantages, finally Autodesk Revit and Autodesk Ecotect were chosen. Moreover, suitable building materials and optimum sizes are computed corresponding to different weather conditions and climates in Iran. In another part of this study, the breakdown of energy consumption in the commercial and residential areas in Iran is examined. Given the 38% share of space heating in total building energy consumption, the essential role of thermal insulation of external walls is emphasized. The effect of insulating in this region is calculated and marked applying simulation of energy consumption. Utilizing a suitable insulation system, can save 35% in lifecycle energy consumption.

Applicability of different energy efficiency calculation methods of residential buildings in severe cold and cold zones of China

With the accelerated development of dynamic energy consumption simulation software, the accuracy and feasibility of steady-state calculation method for energy efficiency designs of residential buildings in severe cold and cold zones should be investigated. A six-story residential building model as a case study is introduced to be calculated and simulated by steady-state calculation method elaborated in ‘Design standard for energy efficiency of residential buildings in severe cold and cold zones’ and dynamic energy consumption simulation of EnergyPlus software respectively, in order to compare and analyze the differences between these two methods in five typical cities of China (Xi’an, Lhasa, Xining, Harbin and Hailar). The findings indicate that the index of heat loss of building obtained from both methods is different to typical cities with varied difference ratios. Especially in cities of high altitude, strong radiation and greater diurnal range, namely Lhasa and Xining, the difference ratio is as high as 43.83% and 16.63%. Thus, dynamic energy consumption simulation should be used for counting residential building energy efficiency instead of steady-state calculation method in above mentioned zones by analyzing main factors concerning the differences.

The Influence of Insulation Styles on the Building Energy Consumption and Indoor Thermal Comfort of Multi-Family Residences

The properties of building envelopes significantly affect indoor building energy consumption, indoor thermal comfort, and building durability. In the current standards for Japanese residential energy efficiency, insulation placement is not well regulated. Meanwhile, it is common in Japan to use air-conditioning intermittently, rather than having the units operate continuously. Therefore, considering specific Japanese lifestyles, we investigated insulation performance. In this research, we: (1) developed the interior insulation to include insulation on walls, ceilings and floors of building units (all of the interior surfaces) to achieve building energy savings by avoiding heat loss through thermal bridges; (2) discussed and demonstrated the effects of high heat capacitance for each of the building components and the thermal bridge by conducting building environmental simulations; (3) conducted simulations in seven cities in Japan and discussed the applicability of these different weather conditions; and (4) compared temperature distributions to investigate differences in indoor comfort with partial heating on winter nights. We demonstrated the energy saving and thermal comfort advantages of interior insulation. This research provides an innovative insulation style based on Japanese lifestyles that contributes to new energy-saving standards and formulations.