Residential Energy Demand Research Articles

Heterogeneous Impacts of Building Codes on Residential Energy Demand: Evidence from Turkey

Heterogeneous Impacts of Building Codes on Residential Energy Demand: Evidence from Turkey

Impacts of family household dynamics on residential energy demands in Hebei Province of China

This article presents analyses and projections of the residential energy demands in Hebei Province of China, using the ProFamy extended cohort-component method and user-friendly free software and conventional demographic data as input. The results indicate that the future increase in residential energy demands will be dominated by large increase in small households with 1–2 persons. We found that increase of residential energy demands will be mainly driven by the rapid increase of older adults’ households. Comparisons between residential energy demand projections by household changes and by population changes demonstrate that projections by population changes seriously under-estimate the future residential energy demands. We recommend that China needs to adopt policies to encourage and facilitate older parents and adult children to live together or near-by, and support rural-to-urban family migration. Promoting inter-generation co-residence or living near-by between older parents and young adults would result in a mutually beneficial outcome for both older and younger generations as well as to effectively reduce energy demands. We suggest governments to carefully formulate strategies on efficient residential energy use to cope with the rapid households and population aging, and strengthen data collections/analyses on household residential energy demands for sound policy-making and sustainable development.

Risk identification of residential energy demand: the case studies of Australia, Chile, the United Kingdom and the United States

ABSTRACT A wide range of residential sector energy models have been developed in recent years to determine energy demand and CO2 emissions and to evaluate energy saving policies. However, modelling outputs are subject to significant variations due to multiple sources of uncertainty, primarily stemming from input parameters and assumptions. This study aims to assess the transferability of the Transferable Energy Model (TREM) and quantify the prediction uncertainty of residential sector energy demand until 2030 in four case study countries (Australia, Chile, United Kingdom and the United States). TREM is able to determine the future annual energy demand in the residential sector according to the area of energy use (space heating, hot water provision, cooking, electrical appliances, lighting), whilst quantifying uncertainties in the results. Significant variations (between −12% and +63%) in residential energy demand in the year 2030 with respect to 2010 were found among the case study countries, suggesting that single total energy demand estimates are associated with considerable uncertainties. This paper also presents a comprehensive database of the range of possible variations in residential energy demand related to a wide range of energy saving measures in each case study country.

Residential energy demands in Rwanda: Evidence from Robust models

The United Nations Sustainable Development Goals 7 highlights the need to achieve universal access to clean and affordable energy, however, sub-Saharan African (SSA) countries have serious limitations with access to clean and affordable energy. Most households in SSA, especially those in rural areas, remain decidedly dependent on using polluting fuels, such as kerosene, wood and charcoal as their main household energy use. In this study, we explore how income and other household attributes explain the variations in energy use in Rwanda. Using robust methods that account for possible outliers and measured errors, we estimate the Engel curves of four energy types: electricity, charcoal, biomass and other energy types in the country. We notice two striking results. First, the income elasticity from electricity is elastic for urban households, an indication that electricity is treated as luxury for urban household. Second, the energy consumption patterns show significant heterogeneity between rural and urban households. The heterogeneities observed in the energy use patterns between rural and urban dwellers suggest that the framers of national energy policy should take cognisance of this fact. Further, there is the need to intensify efforts that decarbonize energy sector by availing affordable alternative energy sources, including LPG especially in rural areas to reduce the biomass consumption.

Residential space-heating energy demand in urban Southern China: An assessment for 2030

Residential space heating in urban Southern China has been booming in the recent decade. The massive increase in space-heating demand poses significant challenges to sustainability. A systematic assessment of energy consumption and CO2 emissions resulting from residential space heating is particularly important in guiding policymakers and market stakeholders. This study projects and assesses the energy consumption and CO2 emissions of distributed heating and centralized heating systems in urban Southern China under five different scenarios. The results suggest that by 2030, under the business-as-usual scenario, urban Southern China will consume 77–167 million tce (Mtce) of energy to support its potential space-heating demands and will generate 126–275 million tons (Mt) of CO2 emissions. The corresponding proportion of national total consumption and emissions in 2019 is 1.5–3% and 1.1%–2.4%, respectively. If aggressive decarbonization policies are adopted, the total energy consumption and CO2 emissions will be reduced by 47–53% and 54–60%, respectively. These policies include developing clean heating sources, improving heating system efficiency, and increasing electrification levels. In addition, from the regional perspective, the top 5 out of 133 cities (Shanghai, Chongqing, Hangzhou, Nanjing, and Chengdu) contribute 27% of all sample cities' energy and 23% of CO2 emissions. Some cities, such as Dali and Qianxinan, may suffer a severe gas shortage because the projected gas demand exceeds the current infrastructure capacity. The results demonstrate the importance of adapting suitable heating systems to local conditions.

Stochastic RCM-driven cooling and heating energy demand analysis for residential building

Changes associated with global warming are expected to significantly alter existing heating and cooling demands in buildings. In order to develop appropriate adaptation measures in response to these climate changes, policy makers will require reliable and comprehensive assessments of anticipated variations in building energy use. In this study, a stochastic RCM-driven residential energy demand analysis is developed to provide robust support for policy makers to consider various adaptation actions for building energy system. High-resolution climate projections are firstly generated via proposed approach, based on which the heating and cooling energy demand of residential buildings in the province of British Columbia, Canada is analyzed from a comprehensive perspective (i.e., considering optimistic, neutral, and pessimistic levels). The results show that energy-related infrastructure and adaptation policies are likely to face huge challenges in the next 80 years due to a large increase in the energy use demand for space cooling and a relatively slight decrease in that for heating. Under an optimistic level, annual heating energy use is projected to decline 6% while cooling energy use will increase by 23% in 2088–2099. However, under a pessimistic level these changes could surge by 21% and 88%, respectively. The difference in projected energy use between these two levels can be equivalent to 1.30 Mt of CO2e greenhouse gas emissions. The analysis proposed in this study could also be applied in other regions under similar contexts.

Evaluating the Effects of Access to Air Quality Data on Household Air Pollution and Exposure—An Interrupted Time Series Experimental Study in Rwanda

In Sub-Saharan Africa, around 80% of residential energy demand is for cooking, with over 760 million people without access to clean cooking fuels and stoves. Particulate matter smaller than 2.5 microns (PM2.5) is a significant pollutant from biomass burning and is linked to respiratory and cardiovascular diseases, as well as adverse pregnancy outcomes. Energy poverty further reinforces gender disparities, keeps children from schools, causes environmental degradation, and interferes with social and economic development. Lack of access to and inadequate adoption of clean cooking stoves and fuels are key barriers to improved air quality. This paper presents a field experiment nested within a large-scale health efficacy trial. The aim of the experiment was to evaluate the effects of access to air quality data and dynamic feedback on indoor air pollution (IAP) and personal exposure. Ninety households in Rwanda were enrolled and provided with an air quality sensor and feedback device, which measured real-time indoor air quality as PM2.5 for sixteen weeks. After six weeks, PM2.5 levels were provided dynamically to households through a display and an auditory alarm. We examined the effects of receiving this feedback on IAP and personal exposure. While access to air quality data did not, in aggregate, improve PM2.5 levels, we did observe several promising correlations worthy of further investigation. The associations between personal exposure or rainfall and increased PM2.5 were reduced after households had access to air quality data. We hypothesized that the behavior changes required to observe these effects—opening doors and windows and moving away from cooking sources—are easy and immediate, in contrast to the costs and complex logistics of entirely eliminating biomass cooking. The types of behavior changes that would directly impact household air pollution and exposure require more than just awareness and willingness to act.

Revisiting heat energy consumption modeling: Household production theory applied to field experimental data

This paper offers new insights on utility-driven heat energy consumption derived from using an interdisciplinary modeling framework that is based on Becker's household production theory. The research question addressed is whether economic aspects affect short-term, less conscious behavior in the same way as long-term, more conscious behavior. From the investigation, new insights on the usefulness of price-based energy policy measures targeting heat energy consumption are gained. The household production model proposed for analyzing residential heat energy demand integrates economic, engineering and behavioral elements. Comparative statics enables an interdisciplinary integration of price- and income functions to cover economic influences on heat energy (service) consumption, the production function to cover technical influences, and the utility-based choice architecture to cover utility maximization influences. Based on a functional representation of the theories, a panel data model of heat energy consumption is estimated. The empirical analysis is based on data from 60 adjacent apartments in South-West Germany. We find empirical evidence that the price elasticity of demand is only statistically significant when using yearly aggregated data. This result provides evidence that occupants apparently do not act much based upon energy price levels when following their daily home heating routine. In less frequent considerations, as e.g. according to their yearly billing cycles, occupants adjust their heat energy consumption in response to the fuel price changes noticed on the energy bill. Furthermore, in relation to the other influences on heat energy consumption, we find that the price impact is less pronounced than the impact of comfort conditions. Therefore, a CO2 price on heat energy might set the right incentives to invest in more energy-efficient heating technology, but hardly alter comfort-taking or rebound effects.

Evaluating decarbonization scenarios and energy management requirement for the residential sector in Japan through bottom-up simulations of energy end-use demand in 2050

Decarbonization scenarios for achieving net zero greenhouse gas emissions in the Japanese residential sector by 2050 were examined using a bottom-up simulation model of energy end-use demand. The examined scenarios involve the dissemination of currently available technology, including highly insulated houses, high-efficiency equipment, high-efficiency appliances, electrification, and building-integrated photovoltaics (PV) in detached houses. The results show that decarbonization can be mostly achieved by the studied scenarios, especially through the dissemination of highly insulated buildings and high-efficiency water heaters as well as the installation of PV for all detached houses. This scenario reduced the total primary energy demand by 61% in 2013. A land-use strategy for increased detached houses is preferable for increasing PV capacity. For the scenario that achieves net zero energy, the predicted heat load intensity and electricity consumption per capita are almost the same as those of the Low Energy Demand (LED) scenario. Increased dependence on PV will create an imbalance in the relationship between electricity supply and demand, and 26% of the residential energy demand would rely on non-battery energy storage, such as pumped hydropower and hydrogen, owing to the seasonal time gap between residual and deficit electricity.

Framework for Developing a Low-Carbon Energy Demand in Residential Buildings Using Community-Government Partnership: An Application in Saudi Arabia

Rapid population growth has led to significant demand for residential buildings around the world. Consequently, there is a growing energy demand associated with increased greenhouse gas (GHG) emissions. The residential building energy demand in arid countries such as Saudi Arabia is supplied with fossil fuel. The existing consumption pattern of fossil fuels in Saudi Arabia is less sustainable due to the depletion of fossil fuel resources and resulting environmental impacts. Buildings built in hot and arid climatic conditions demand high energy for creating habitable indoor environments. Enormous energy is required to maintain a cool temperature in hot regions. Moreover, climate change may have different impacts on hot climatic regions and affect building energy use differently. This means that different building interventions may be required to improve the performance of building energy performance in these geographical regions, thereby reducing the emissions of GHGs. In this study, this framework has been applied to Saudi Arabia, a hot and arid country. This research proposes a community–government partnership framework for developing low-carbon energy in residential buildings. This study focuses on both the operational energy demand and a cost-benefit analysis of energy use in the selected geographical regions for the next 30 years (i.e., 2050). The proposed framework primarily consists of four stages: (1) data collection on energy use (2020 to 2050); (2) setting a GHG emissions reduction target; (3) a building intervention approach by the community by considering cost, energy, and GHG emissions using the Technique for Order of Performance by Similarity to the Ideal Solution (TOPSIS) to select the best combinations in each geographical region conducting 180 simulations; and (4) a clean energy approach by the government using grey relational analysis (GRA) to select the best clean energy system on the grid. The clean energy approach selected six different renewable power generation systems (i.e., PV array, wind turbine, hybrid system) with two storage systems (i.e., battery bank and a combination of electrolyte, fuel cell, and hydrogen tank storage). This approach is designed to identify the best clean energy systems in five geographical regions with thirty scenario analyses to define renewable energy-economy benefits. This framework informs through many engineering tools such as residential building energy analysis, renewable energy analysis, multi-criteria decision analysis (MCDA) techniques, and cost-benefit analysis. Integration between these engineering tools with the set of energy policies and public initiatives is designed to achieve further directives in the effort to reach greater efficiency while downsizing residential energy demands. The results of this paper propose that a certain level of cooperation is required between the community and the government in terms of financial investments and the best combinations of retrofits and clean energy measures. Thus, retrofits and clean energy measures can help save carbon emissions (enhancing the energy performance of buildings) and decrease associated GHG emissions, which can help policy makers to achieve low-carbon emission communities.

Optimal investment and scheduling of residential multi-energy systems including electric mobility: A cost-effective approach to climate change mitigation

Residential energy and mobility demand are responsible for a substantial share of global greenhouse gas emissions due to high dependency on fossil fuels in heating and motorized individual transport. Technology upgrades might enable cost-effective climate change mitigation in decentralized mobility-including Multi-energy Systems (MIMES). Their holistic and cross-sectoral optimization with respect to design and operation can innovatively identify tradeoffs between ecological and economical solutions, quantify potential benefits and show drawbacks over current solutions. To this end, this work provides a novel, hourly-resolved, consumer-centric, multi-objective optimization framework based on the Energy Hub concept that includes private mobility investments. It compares four distinct technology portfolios for minimal lifecycle emissions and total annualized cost when supplying residential demands to promote beneficial solutions. In a case study, consumers may modify their combustion-based heating and mobility systems (1) by switching to e-mobility (2), by switching to stationary Multi-energy Systems (3), or by switching to e-mobility and Multi-energy Systems simultaneously (4). Optimizations on 83 stochastically selected single- and multi-family buildings in St. Gallen, Switzerland, demonstrate that all three technological upgrades offer improved performance over (1): While costs decrease moderately in cost-driven optimizations, emission reductions range from 16% up to 68% when emission-driven optimizations are performed. The joint electrification of stationary and mobile assets (4) is particularly attractive and outperforms all other technology cases. Scenario (3) offers the second-best performance. While the optimal design and operation of assets depend on the technology availability, emission reduction targets, building size, and demand properties, an uncertainty analysis underpins the overall benefits of upgrades and accredits robustness to abovementioned ranking for wide techno-economic parameter variations and objectives. Pathways for further emission reductions are additionally shown, and the increased initial cost and seasonal dependence on the electricity grid are discussed as hurdles for a widespread implementation of economical and climate-friendly MIMES.

Quantitative estimation of the impact of climate change on residential electricity demand for the city of Greater Accra, Ghana

Quantitative estimation of the impact of climate change on residential electricity demand for the city of Greater Accra, Ghana

Saving energy in residential buildings: the role of energy pricing

A zero-carbon society requires dramatic change everywhere including in buildings, a large and politically sensitive sector. Technical possibilities exist but implementation is slow. Policies include many hard-to-evaluate regulations and may suffer from rebound mechanisms. We use dynamic econometric analysis of European macro data for the period 1990–2018 to systematically examine the importance of changes in energy prices and income on residential energy demand. We find a long-run price elasticity of −0.5. The total long-run income elasticity is around 0.9, but if we control for the increase in income that goes towards larger homes and other factors, the income elasticity is 0.2. These findings have practical implications for climate policy and the EU buildings and energy policy framework.

Urban Residential Energy Demand and Rebound Effect in China: A Stochastic Energy Demand Frontier Approach

The energy rebound effect is a potential threat to energy-saving targets based on energy efficiency improvements. This paper employs a stochastic energy demand frontier model to analyze the energy demand and rebound effect in China’s urban residential sector. Using a panel data set of 30 Chinese provincial-level regions over the period 2001-2014, for the first time, we investigate the degrees and determinants of China’s urban residential energy demand and energy rebound effect.The results show that residents’ income level, energy price, temperature deviation, population scale, household size, and district heating system are significant influencing factors of residential energy consumption. Regarding the energy rebound effect, we find that energy price is negatively correlated with the rebound effect, and an inverted U-shaped relationship between residents’ income level and rebound-effect size exists. The magnitude of the rebound effect varies across regions, with an average of 65.4%. The main policy implication generated by this study is that it should be in urgent need of energy pricing reform to mitigate the rebound effect in China.

Nexus between household energy consumption and economic growth in Bangladesh (1975–2018)

Bangladesh, a climate-vulnerable country, has taken initiatives to reduce greenhouse gas emissions. The country's most significant challenge to achieving that goal is keeping economic growth even after ensuring commercial and residential energy for its people, primarily dependent on fossil fuel. This research investigates the residential electricity and gas consumption and its effect on Bangladesh's economic growth with the data period 1975–2018. Household energy consumption is one of the critical factors for sustainable economic growth, although it is not directly converted to the country's manufacturing output. Autoregressive Distributed Lag (ARDL) bound testing approach has been used due to the robust and better performance in this study with the smaller size of the sample. The country's labor-intensive economy has been found with a unidirectional relationship from household electricity consumption and population growth, which stresses the significance of ensuring electricity for all. Therefore, the country cannot take the energy conservation policy right now as it could obstruct its growth. However, energy sources might be replaced with renewable energies to meet the country's residential energy demand.

Linking complexity economics and systems thinking, with illustrative discussions of urban sustainability

Abstract The expanding research of complexity economics has been signalling its preference for a formal quantitative investigation of diverse interactions between heterogeneous agents at the lower, micro-level resulting in emergent, realistic socioeconomic dynamics at the higher, macro-level. However, there is scarcity in research that explicitly links complexity perspectives in economics with the systems thinking literature, despite these being highly compatible, with strong connections and common historical traces. We aim to address this gap by exploring commonalities and differences between the two bodies of knowledge, seen particularly through an economics lens. We argue for a hybrid approach, in that agent-based complexity perspectives in economics could more closely connect to two main systems thinking attributes: a macroscopic approach to analytically capturing the complex dynamics of systems, and an inter-subjective interpretivist dimension, when investigating complex social-economic order. Illustrative discussions of city sustainability are provided, with an emphasis on decarbonisation and residential energy demand aspects.

Grassroots retrofit: Community governance and residential energy transitions in the United Kingdom

Residential energy demand accounts for a significant proportion of the UK’s carbon emissions. As ~80% of the existing housing stock is expected to be in use by 2050, low carbon retrofit is essential in meeting climate and fuel poverty targets. Recent policy has failed to deliver retrofit at scale, leading to an emerging movement of grassroots initiatives approaching the challenge through community governance. This paper explores the role of these grassroots initiatives in the UK, identifying and evaluating how they address key barriers associated with delivering retrofit at scale, including engaging households, developing local supply chains and overcoming economic barriers. The research takes a qualitative approach with ten semi-structured interviews to understand the perspectives of community practitioners, intermediaries and policymakers. Our findings suggest community-led retrofit is effective at engaging households, can contribute to local supply chain development, help households access financing, and be a valuable delivery partner for local authority fuel poverty schemes. However, while community-led retrofit offers an alternative approach to retrofit governance, it is unlikely to deliver residential retrofit at scale without a broader government programme of financial and regulatory support.

The Impact of Climate Change on the Energy Consumption of Passive Residential Buildings in the Yangtze River Delta

With the global warming in the future, the meteorological data based on the Typical Meteorological Year (TMY) can no longer accurately reflect the changes in building energy consumption under future meteorological conditions. This paper selects the typical meteorological year (TMY) in the Yangtze River Delta region as the base year data and the monthly scale forecast data provided by the IPCC, and uses the “Morphing” method to predict hourly weather data in 2050 and 2080. The use of energy simulation software Energy Plus of the Yangtze River Delta region in a passive multi-storey residential building energy simulation, analysis of building energy performance under future climate change, projected changes passive residential building energy demand over the next 60 years of trend.

Regional management of flare gas recovery based on water-energy-environment nexus considering the reliability of the downstream installations

Water-energy-environment nexus was employed in a sample city for flare gas recovery while the reliability of downstream installation is taken into account. First, considering the average characteristics of a house, water and energy demands were estimated. The residential section's water and energy demands were then supplied using flare gas recovery from an oil field near the city. The study was conducted in two scenarios based on meeting the total annual electricity demand and the residential sector's total annual natural gas demand. A hybrid system including a natural-gas liquid refinery, a gas turbine power plant, a heat recovery steam generator, and multi-effect desalination was proposed as downstream installations. By system reliability's consideration using the Markov technique, a novel integrated model was developed to assess different proposed scenarios. In both scenarios, the water and energy shortages could be provided by the network, and the surplus can be sold to the network. It was shown that considering the reliability of technology significantly affects the final configuration of flare gas recovery technology. It was shown that consideration of employed installations' reliability affects the proposed flare gas recovery technologies' features. Accordingly, the first scenario with a capital cost of 236.94 M$ and a product sales income of 93.31 M$, with 1.3 years of return payback period, was selected as the best solution.

HOW LARGE THE DIRECT REBOUND EFFECT FOR RESIDENTIAL ELECTRICITY CONSUMPTION WHEN THE ARTIFICIAL NEURAL NETWORK TAKES ON THE ROLE? A TAIWAN CASE STUDY OF HOUSEHOLD ELECTRICITY CONSUMPTION

Amid the energy reform efforts by the Taiwan government, residential energy demand continues to face an escalating trend every year. This indicates the phenomenon of the energy efficiency gap. One of the factors that control the energy efficiency gap is the rebound effect. The rebound effect is related to the increase in energy consumption through efforts to reduce the use of energy itself. This can be due to the low cost of usage that causes a person to be encouraged to use more energy. This study aims to estimate the magnitude of the direct rebound effect of household electricity consumption in Taiwan using monthly time series data from January 1998 to December 2018 and to implement the artificial neural network (ANN) as an alternative approach to measure the direct rebound effect. Based on the simulation results, the direct rebound effect magnitude for household electricity consumption in Taiwan is in the range of 11.17% to 21.95%. GDP growth is the most important input in the model. Additionally, population growth and climate change are also critical factors and have significant implications in the model.