A cluster analysis of energy-consuming activities in everyday life

ABSTRACT

Flexible consumption in the household sector concerns individuals’ daily choices and the routines that develop in their households. Targeting household-level energy consumption therefore requires an understanding of energy consumption in relation to individual household members’ activity patterns. Individual time-diaries reveal when, for how long and where energy-related activities occur, permitting discussions of the temporal flexibility of these activities. Using multiple time-diaries (n?=?6477) from a population reveals differences in activity patterns in larger groups and permits recorded activities to be clustered. Few explorative studies perform cluster analyses of energy-consuming activities in order to examine when and for how long these activities occur. When clustering is done, it is usually based on socio-economic factors, and not on the activities performed in sequence. This paper reports a time-geographically inspired cluster analysis based on when and for how long some activities requiring electricity are performed in the home by individuals in a population. The presented cluster analysis based on activities gives a new perspective to the discussion of flexible users and provides a basis for deeper analyses, for example, of whether activities are moveable in time for individuals, complementing cluster analysis based on other variables.     

Electric Arc Holes in Corrugated Stainless Steel Tubing

Corrugated stainless steel tubing (CSST) has become a common product installed in new and retrofitted older homes. The ease of installation due to its flexibility and the need for fewer joints significantly lowers labor costs. Despite the advantages of lower cost and ease of installation, however, the thin wall of CSST presents an increased risk of perforation by both mechanical puncturing and electrical arcing from either household current or lightning strikes. In the course of forensic investigations of household fires, perforated tubing is occasionally identified as a potential cause. The metallurgical features of the perforated area are capable of distinguishing the cause of the hole as being from either lightning current or household current.     

Estimating energy savings from behaviours using building performance simulations

Occupants’ behaviours are a major determinant of energy use in buildings. The related savings potential has been insufficiently exploited. Although research has addressed behavioural savings through real-world interventions and quantitative modelling approaches, it has not yet explored the full variety of household activities. This work proposes an integrative modelling approach of energy behaviours in the residential setting as a tool to estimate the behavioural impact of households on energy consumption. It uses building energy performance simulation (BEPS) tools to exploit the behavioural savings potential associated with usage and investment energy behaviours when using different energy services in daily household activities. Simulations have estimated significant behavioural savings potential associated with energy behaviours, which may be materialized if some forms of behaviour are induced. Investment behaviours have higher savings potential than usage behaviours, and the behavioural savings potential per energy service is proportional to the energy consumption breakdown. BEPS tools enable a quantitative estimate of the behavioural impact on energy consumption, but further improvements to these tools are needed to incorporate the complexity of behavioural dimensions. Estimating the behavioural savings potential is important for a more effective design of behaviour change interventions, which in turn will support more effective energy efficiency policies.     

A study on environmental impact of nanofluid-based concentrating solar water heating system

The rising cost of fossil fuels and the growing concern for a clean environment have paved the way for adoption of renewable and sustainable sources of energy. Domestic water heating can result from solar energy, a clean and renewable alternative, which can at the same time help to reduce greenhouse gas emissions. This paper examines the potential of the nanofluid-based concentrating solar water heating system (NCSWHS) as an alternative to systems based on fossil fuels. The paper reports a quantitative assessment to assess the potential environmental benefits which could be obtained from NCSWHS if substituted for those using fossil fuels. The analysis reveals that considerable emission reductions (about 2.2 x 10³ kg of CO₂/household/ year) and fuel savings can be achieved if the NCSWHS are adopted.     

Design and development of smart electricity meter – the path towards sustainable globe

Reducing energy demand in the domestic segment is an important problem worldwide. This study focused on the awareness of residents on energy conservation and on the potential of reducing energy demand through energy-saving activities. The following observations were noted down during the experiment of smart meter in 10 houses of Mumbai city. (1) Its installation led to a reduction in power consumption, (2) a change in energy-saving behaviours of the household members such as the reduction of standby power and a better control of appliance operation, and (3) energy-conservation awareness affected not only the power consumption of the appliances explicitly shown on the display monitor but also other household appliances. (4) Development of sustainable environmental system.     

Constructing load profiles for household electricity and hot water from time-use data—Modelling approach and validation

Time-use data, describing in detail the everyday life of household members as high-resolved activity sequences, have a largely unrealized potential of contributing to domestic energy demand modelling. A model for computation of daily electricity and hot-water demand profiles from time-use data was developed, using simple conversion schemes, mean appliance and water-tap data and general daylight availability distributions. Validation against detailed, end-use specific electricity measurements in a small sample of households reveals that the model for household electricity reproduces hourly load patterns with preservation of important qualitative features. The output from the model, when applied to a large data set of time use in Sweden, also shows correspondence to aggregate profiles for both household electricity and hot water from recent Swedish measurement surveys. Deviations on individual household level are predominantly due to occasionally ill-reported time-use data and on aggregate population level due to slightly non-representative samples. Future uses and developments are identified and it is suggested that modelling energy use from time-use data could be an alternative, or a complement, to energy demand measurements in households.     

A high spatial resolution residential energy model based on American Time Use Survey data and the bootstrap sampling method

A high spatial resolution model of energy use in residential buildings was developed based on time use data. The development of this model was guided by a theoretical framework that explains the nature of a dwelling's physical characteristics, the nature of its occupants’ energy use behaviors and the ways in which the dwelling and its occupants interact to determine the energy use of a household. Energy Plus was used as the model platform.In the model, the occupants’ domestic activity pattern was extracted from American Time Use Survey (ATUS) data via bootstrap sampling. The dwelling's physical characteristics were based on real world scenarios.Virtual experiments with 3- to 5-occupant household compositions were conducted to examine the model properties. Simulation results show that (1) bell-shaped distributions were present in annual heating load demands for all household compositions, (2) the load demands for different batches of samples of the same household composition demonstrated a narrow range of variations, and (3) the simulated hourly appliance and lighting load profiles were in agreement with those generated from field-metered data at both whole-house and sub-house levels. These results indicate the model's overall robustness and verify its ability to simulate realistic residential energy use load profiles.     

A surface model approach to small area population estimation

The author applies a surface model approach to the estimation of small-area population and household characteristics. "The representation of population-related information by means of surface concepts offers a way to overcome many of the limitations of traditional, 'fixed' zone-based methods. The approach has the potential to give planners and policy-makers greatly improved flexibility in handling and interpreting spatially referenced data. One practical area of application is the estimation of population at local levels for which the underlying concepts and methods are discussed in this article."     

Energy-saving potential by improving occupants’ behavior in urban residential sector in Hangzhou City, China

Besides technical measures, occupants’ behavior is one of the most important issues with respect to energy efficiency in households. This paper will discuss the relationship between electricity consumption and household lifestyle and evaluate the energy-saving potential by improving occupants’ behavior in domestic life through energy-saving education. After 124 households in three typical residential buildings in Hangzhou city of China being selected as research subjects, a series of surveys were conducted: (1) recording of the monthly electricity uses of all subject households from March 2007 to July 2008; (2) energy-saving education to the half of the households before July 2008; (3) a comprehensive survey about the household lifestyle of all subject households in the beginning of August 2008. By comparison analysis of the survey data, major findings are as follows: (1) residential electricity consumption will increase continually in the next years in China, because of the improvement of people's living standard and more dependency on electric appliances; (2) improving occupants’ behavior in domestic life can save more than 10% household electricity use; and (3) some effort on residential energy savings should be shifted from technological measures to improving occupants’ behavior in ordinary domestic life.     

Map of ecological networks for landscape planning

This paper presents a method based on a geographical information system (GIS) to model ecological networks in a fragmented landscape. The ecological networks are generated with the help of a landscape model (which integrate human activities) and with a wildlife dispersal model. The main results are maps which permit the analysis and the understanding of the impact of human activities on wildlife dispersal. Three applications in a study area are presented: ecological networks at the landscape scale, conflicting areas at the farmstead scale and ecological distance between biotopes. These applications show the flexibility of the model and its potential to give information on ecological networks at different planning scales.     

The enhancement of spatial microsimulation models using geodemographics

The generation of synthetic population estimates through spatial microsimulation has been a popular technique in recent years, with applications to research and policy problems in many areas of social science. Estimation techniques typically involve cloning or matching households in surveys with small-area census data. When model estimates are benchmarked against real-world data, the models are typically well behaved and very robust, but they can struggle to capture the diversity of spatial variations shown by observed data. We argue in this paper that this is the result of 3 potential problems in spatial microsimulation estimation techniques. The first issue results from the matching process in the estimation techniques, and the second problem relates to the variations of household types in the surveys being reweighted. Third, similar household types may show different behaviours or have different attributes depending on geographical factors not contained in surveys (such as the proximity of service or job locations). The aim of this paper is to demonstrate and measure the loss of accuracy and intensity induced by spatial microsimulation in the context of real individual data. It will be argued in particular that while the first two problems have begun to be addressed in the literature, the third issue is still largely unreported. The paper will thus suggest a solution framework which involves linking spatial microsimulation models with geodemographics and demonstrates the promise of this technique with real numerical experiments.     

基于Jini技术的智能家居系统集成研究

家庭网络具有软硬件资源复杂和动态的特点．如何集成这些异构系统并开发新的应用，成为智能家居系统中亟待解决的问题。本文分析比较了UPnP、OSGi、HAVi和Jini等家庭网络中常用的几种中间件．对Jini技术进行了较为深入的研究．说明了Jini技术在智能家居系统中具有广阔应用前景。同时针对Jini自身的特点，提出了一套家居系统的Jini解决方案，可较好地解决智能家居系统集成问题。     

Measurements of occupancy levels in multi-family dwellings—Application to demand controlled ventilation

The occupancy level of dwellings is an important parameter to know to determine the energy efficiency, energy use and indoor air quality, especially in low-energy buildings where the user-related energy uses, such as household electricity and domestic hot water heating, are significant parts of the energy balance in a building. For residential buildings, there is a lack of occupancy level data, which also needs to be resolved over time, in a way so that both short term and long term variations can be described. As a part of an ongoing study, occupancy levels were measured as building average levels in 18 apartment buildings containing 342 apartments in total with readings every 30 min for more than a year. Averages and standard deviations of occupancy level, and variation in occupancy during the year, week and day respectively are presented. The results show a highly varying occupancy level over time, which indicates the potential of demand controlled ventilation in dwellings.     

Energy Cost Burdens for Low-Income and Minority Households

Abstract

Problem, research strategy, and findings: Of the three primary components of housing affordability measures—rent, transportation, and utilities—utility costs are the least understood yet are the one area where the cost burden can be reduced without household relocation. Existing data sources to estimate energy costs are limited to surveys with small samples and low spatial and temporal resolution, such as the American Housing Survey and the Residential Energy Consumption Survey. In this study, we present a new method for small-area estimates of household energy cost burdens (ECBs) that leverages actual building energy use data for approximately 13,000 multifamily properties across five U.S. cities and links energy costs to savings opportunities by analyzing 3,000 energy audit reports. We examine differentials in cost burdens across household demographic and socioeconomic characteristics and analyze spatial, regional, and building-level variations in energy use and expenditures. Our results show the average low-income household has an ECB of 7%, whereas higher income households have an average burden of 2%. Notably, even within defined income bands, minority households experience higher ECBs than non-Hispanic White households. For lower income households, low-cost energy improvements could reduce energy costs by as much as $1,500 per year.

Takeaway for practice: In this study we attempt to shift the focus of energy efficiency investments to their impact on household cost burdens and overall housing affordability. Our analysis explores new and unique data generated from measurement-driven urban energy policies and shows low-income households disproportionately bear the burden of poor-quality and energy-inefficient housing. Cities can use these new data resources and methods to develop equity-based energy policies that treat energy efficiency and climate mitigation as issues of environmental justice and that apply data-driven, targeted policies to improve quality of life for the most vulnerable urban residents.     

住区密度与家庭能耗碳排放相关性研究——以上海曹杨新村为例

住区空间形态及模式类型划分与密度特征相关,家庭能耗产生的空间碳排放与密度分布有着逻辑对应关系。国内外相关研究表明,家庭特征、住房特征和能耗行为等因素对家庭生活能耗有着显著的影响,而有关密度与家庭能耗碳排放之间的相关研究尚需更多实证案例。本文以上海曹杨新村作为研究对象,通过调研问卷数据来估算54个小区样本的家庭能耗人均碳排放值,并对住区密度指标与碳排放进行相关性研究。从回归分析结果看,曹杨新村的家庭能耗消费与家庭特征、住房特征等因素存在着显著的线性关系,且家庭人口规模具有主导作用。在密度指标与碳排放相关性研究中,家庭能耗碳排放在物质密度与人口密度指标中分别具有区段波动性特征,通过进一步分析密度与碳排放影响变量之间的非线性逻辑对应关系,研究得出不同密度区段条件下的住区家庭能耗碳排放差异是居民家庭人口规模、收入水平等相关社会因素叠合作用造成的。因此,判断住区是否"低碳"首先当明确密度区段的选择条件,结合本国国情、地区发展条件、家庭社会经济特征等因素来引导未来住区发展模式。     

锅炉入户供热方式的技术经济分析

以实际工程为例，从热用户的角度对比分析了集中供热、燃油（气）锅炉房供热和户式供热的经济性与适用性，认为户式供热有着舒适灵活、计费方便等优点，是热用户可以选择的一种比较理想的供热方式。     

用最小势能原理的有限元法分析一般梁的单刚

应用最小势能原理中的有限元分析法，选择单元位移函数，并计算单元的应变能，对有竖向挠度和剪切变形的梁的单元刚度矩阵进行了推导，从而为实际计算应用提供了方便。     

Understanding domestic fuel use practices in an urban township

Due to the complex interactions between socio-economic, cultural and political factors, some urban households consume a portfolio of energy sources, e.g. electricity, coal, paraffin, gas and solar power. A social construction of technology perspective is used to understand the choices underlying these multiple fuel practices. Nine participants (household energy managers, consumers and users) were purposefully selected from Soshanguve, an urban township in Pretoria, South Africa. Data were collected through individual in-depth interviews and narrative analysis was used to generate findings. Stories about multiple fuel use in the household showed this practice is common and forms part of the participants’ lifestyles. Social, cultural and political meanings of fuel use are identified in the narratives. Suggested interventions to optimize multiple fuel use in this context include additional technology such as solar power, collaborations with manufacturers to improve existing fuel types that are seen as potentially hazardous, and leveraging women’s knowledge and position in the household to formalize education about multiple fuels. The role of government in providing subsidies for alternative energies and reviewing accessibility to electricity was also highlighted by the participants. This research demonstrates that policy-makers should actively involve consumers in household energy system decisions through deliberative dialogue with communities.     

Energy Efficiency in Tenant–Owners' Residences: The Process of Going from Objective to Implementation

This article focuses on how Sweden's largest tenant–owners' organization, HSB, deals with energy efficiency. The aim is to examine HSB's energy goals, how they are determined and how they should be implemented at four levels: the national association, the regional office, the local housing co-operatives and the tenant–owners. Representatives of all four levels were interviewed. Achieving energy goals calls for common strategies involving all levels of HSB. The analysis indicates that ambitious energy goals have not been followed up with similarly ambitious implementation plans by the organization. Champions in HSB mobilize support for energy efficiency at the regional and co-operative levels, but have no effect on household engagement. The lack of interest in energy efficiency on the part of households was not only due to the collective metering of energy, but also because energy constitutes only a small part of household life.     

Rapid visualization of the potential residential cost savings from energy storage under time-of-use electric rates

Buildings feature a prominent role in electric grid loading, as they use about 75% of the total electricity generated in the United States and are main drivers of electric peak demand in the summer due to electrically driven air conditioning systems. Energy storage is a key technology that can increase energy cost savings, and add flexibility to the grid. However, cost is an important factor to consider. This study proposes a rapid approach that allows for visualization of potential cost savings by introducing energy storage as a peak load control for residential buildings in California. A combination of EnergyPlus load data generation, Matlab post-processing, and Google Fusion Tables data presentation analyses the potential cost savings when energy storage is implemented and TOU rates are applied. The study presents potential annual cost savings of $420 per home with storage capacities of 24?kWh.