A systematic approach to ON-OFF event detection and clustering analysis of non-intrusive appliance load monitoring

The aim of non-intrusive appliance load monitoring (NIALM) is to disaggregate the energy consumption of individual electrical appliances from total power consumption utilizing non-intrusive methods. In this paper, a systematic approach to ON-OFF event detection and clustering analysis for NIALM were presented. From the aggregate power consumption data set, the data are passed through median filtering to reduce noise and prepared for the event detection algorithm. The event detection algorithm is to determine the switching of ON and OFF status of electrical appliances. The goodness-of-fit (GOF) methodology is the event detection algorithm implemented. After event detection, the events detected were paired into ON-OFF pairing appliances. The results from the ON-OFF pairing algorithm were further clustered in groups utilizing the K-means clustering analysis. The K-means clustering were implemented as an unsupervised learning methodology for the clustering analysis. The novelty of this paper is the determination of the time duration an electrical appliance is turned ON through combination of event detection, ON-OFF pairing and K-means clustering. The results of the algorithm implementation were discussed and ideas on future work were also proposed.     

A systematic approach in load disaggregation utilizing a multi-stage classification algorithm for consumer electrical appliances classification

The potential to save energy in existing consumer electrical appliances is very high. One of the ways to achieve energy saving and improve energy use awareness is to recognize the energy consumption of individual electrical appliances. To recognize the energy consumption of consumer electrical appliances, the load disaggregation methodology is utilized. Non-intrusive appliance load monitoring (NIALM) is a load disaggregation methodology that disaggregates the sum of power consumption in a single point into the power consumption of individual electrical appliances. In this study, load disaggregation is performed through voltage and current waveform, known as the V-I trajectory. The classification algorithm performs cropping and image pyramid reduction of the V-I trajectory plot template images before utilizing the principal component analysis (PCA) and the k-nearest neighbor (k-NN) algorithm. The novelty of this paper is to establish a systematic approach of load disaggregation through V-I trajectory-based load signature images by utilizing a multi-stage classification algorithm methodology. The contribution of this paper is in utilizing the “k-value,” the number of closest data points to the nearest neighbor, in the k-NN algorithm to be effective in classification of electrical appliances. The results of the multi-stage classification algorithm implementation have been discussed and the idea on future work has also been proposed.     

Energy labeling for electric fans in Malaysia

To reduce energy consumption in the residential sector, Malaysia Energy Commission is considering implementing energy labels for household electrical appliances including electric fans in 2005. The purpose of the energy labels is to provide the consumers a guideline to compare the size, features, price and efficiency of the appliance. This paper discusses the energy label for electric fans in this country based on Malaysian Standards developed by a technical committee that reviewed the performance of household electrical appliances. This study includes methodology for the calculation of the energy efficiency star rating and projected energy usage, performance requirements, details of the energy label and the requirements for the valid application in Malaysia. The label also can be adopted for other household electrical appliances with only slight modifications.     

新建住宅实际能耗状况的研究

以满足新的节能设计标准的住宅楼内的44户住户为研究对象,基于住宅采暖耗热量和用电量的数据采集和统计分析,掌握新建住宅楼在实际使用过程中的采暖、空调以及生活用电能耗状况,研究分析住宅建筑的能耗结构。结果表明新建住宅建筑的采暖能耗远未达到、节能标准的要求,其次生活用电的能耗也很大。进一步的问卷调查、测试、模拟计算以及对比分析表明,导致住宅高能耗的主要原因在于居住者不合理的采暖、空调和生活用电行为。因此,在住宅节能的研究工作中,应对建筑中的人行为状况予以足够的重视。     

Effectiveness of an energy-consumption information system on energy savings in residential houses based on monitored data

Reducing energy demand in the residential sector is an important problem worldwide. This study focused on the awareness of residents to energy conservation and on the potential of reducing energy demand through energy-saving activities. To carry out quantitative analysis, an on-line interactive “energy consumption information system” for motivating energy-saving activities is constructed, and it was installed in nine residential houses. By utilizing data of measured power consumption, ambient and room temperatures before and after installation of the system, and the responses of the residents to the system, its effectiveness was evaluated. Major findings were as follows: (1) installation of the system led to a 9% reduction in power consumption, (2) comparisons of daily-load curves and load-duration curves for each appliance, before and after installation, revealed various energy-saving behaviors of the household members such as the reduction of standby power and 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.     

Energy use and appliance ownership in Ireland

This paper examines household energy use and appliance ownership in Ireland. Logit regression analyses on a large micro-dataset reveal how household characteristics can help explain the ownership of energy using appliances. Using OLS regression models, we explore the factors affecting residential energy demand conditional on appliance ownership. Results suggest that the methods of space and water heating employed by a household are even more important than electrical appliances in explaining domestic energy usage. However, the stock of appliances must be included in such models so that results will not be biased. The methods employed in this paper can be easily adopted for studies of household energy use in other countries where household expenditure survey data are available.     

Energy efficiency standards for refrigerators in Brazil: A methodology for impact evaluation

In Brazil energy efficiency standards for cold appliances was established in 2007. A specified single set of MEPS (minimum energy performance standards) for refrigerators, freezers and freezer refrigerators was implemented without evaluating its impacts and estimation of potential electricity savings. This paper presents a methodology for assessing the impacts of the Brazilian MEPS for cold appliances. It uses a bottom-up approach to estimate residential end-use consumption and to evaluate the energy saving potential for refrigerators. The household electricity consumption is projected by modeling appliance ownership using an econometric approach based on the recent household survey data. A cost–benefit analysis for more stringent standards is presented from the perspective of the society and electricity customers. The results showed that even considering the current market conditions (high discount rate for financing new efficient equipment) some MEPS options are advantageous for customers. The analysis also demonstrates significant cost-effective saving potential from the society perspective that could reach 21 TWh throughout the period of 2010–2030—about 25% of current residential consumption.     

Decision-making in electrical appliance use in the home

This paper presents the results of a survey as well as an argument from the viewpoint of behavioral economics with the aim of clarifying how consumers make decisions about electrical appliance use in the home. A survey of consumers showed that most have little awareness of the energy efficiency of appliances, the price of the services produced by electrical appliances, or electricity rates. These findings indicate that price does not function as a signal in electricity consumption through electrical appliance use. Rather, we found that consumer decision-making in electricity consumption is dependent on the characteristics of the particular electrical appliances they use. Additionally, we argue that the payment system for home electricity consumption plays an important role in decision-making, causing biases due to aspects of human psychology discussed here in terms of satisficing and heuristics, payment decoupling, and budgeting. We conclude that decision-making about electrical appliance use and electricity consumption in the home is not always rational and is affected both by the particular characteristics of appliances and the payment system for electricity consumption along with human psychology.     

A run-around heat exchanger system to improve the energy efficiency of a home appliance using hot water

A significant portion of the energy consumed by many home appliances using hot water is used to heat cold supply water. Such home appliances generally are supplied water at a temperature lower than the ambient temperature, and the supply water is normally heated to its maximum operating temperature, often using natural gas or an electrical heater. In some cases, it is possible to pre-heat the supply water and save energy that would normally be consumed by the natural gas or electrical heater. In order to save the energy consumed by an appliance using water heater, a run-around heat exchanger system is used to transfer heat from the ambient to the water before an electrical heater is energized. A simple model to predict the performance of this system is developed and validated, and the model is used to explore design and operating issues relevant to the run-around heat exchanger system. Despite the additional power consumption by the fan and pump of the run-around heat exchanger system, the experimental data and analysis show that for some systems the overall energy efficiency of the appliance can be improved, saving about 6% of the energy used by the baseline machine.     

How do household characteristics affect appliance usage? Application of conditional demand analysis to Japanese household data

Although both appliance ownership and usage patterns determine residential electricity consumption, it is less known how households actually use their appliances. In this study, we conduct conditional demand analyses to break down total household electricity consumption into a set of demand functions for electricity usage, across 12 appliance categories. We then examine how the socioeconomic characteristics of the households explain their appliance usage. Analysis of micro-level data from the Nation Survey of Family and Expenditure in Japan reveals that the family and income structure of households affect appliance usage. Specifically, we find that the presence of teenagers increases both air conditioner and dishwasher use, labor income and nonlabor income affect microwave usage in different ways, air conditioner usage decreases as the wife's income increases, and microwave usage decreases as the husband's income increases. Furthermore, we find that households use more electricity with new personal computers than old ones; this implies that the replacement of old personal computers increases electricity consumption.     

Evaluation of city-scale impact of residential energy conservation measures using the detailed end-use simulation model

Energy conservation policies for the residential sector are evaluated by a model that simulates city-scale energy consumption in the residential sector by considering the diversity of household and building types. In this model, all the households in the city are classified into 380 categories based on the household and building type. The energy consumption for each household category is simulated by the dynamic energy simulation model, which includes an energy use schedule model and a heating and cooling load calculation model. Since the energy usage of each appliance is simulated for every 5 min according to the occupants’ energy usage activity, this model can evaluate not only the energy conservation measures by improving the buildings and appliances but also the measures that involve changing the occupants’ activities. The accuracy of the model is verified by comparing its results with the statistical and the measured data on Osaka City, Japan. Various types of energy conservation measures planned by the Japanese government for the residential sector are simulated and their effects on Osaka City are evaluated quantitatively. The future effects of these combined measures on the energy consumption are also predicted.     

Characterization of the electrical energy consumption of a building for the dimensioning of a solar‐hydrogen energy system

The photovoltaic (PV) applications where the dimensioning is effected through the daily energy balance criteria obtained by the estimation of the energy consumption depending on the power and time of use of the electrical apparatus are limited to autonomous PV systems with well‐defined end use. Applications where one would like to electrify complex end use, such as office buildings, schools, hospitals, laboratories, residential units, etc., quantifying the daily energy consumption is difficult mainly due to two aspects. First, there will be great number of a variety of electrical appliances and second the proportionate electrical consumption of each one of them is unpredictable. For this reason it is necessary to establish a methodology that permits one to quantify precisely the daily energy consumption pattern to predict the energetic functioning of the PV system whose size may be determined by this procedure. In this work we describe a methodology for the energetic quantification of the installed equipments by using a Power Quality Analyzer to obtain the historical global energy consumption, daily energy consumption (kWh day⁻¹, kVAh day⁻¹) and the energy quality for the dimensioning of the PV system. Copyright © 2009 John Wiley & Sons, Ltd.     

Using billing and weather data to separate thermostat from insulation effects

A simple methodology, which uses aggregate utility sales data to measure and decompose residential conservation trends, is demonstrated. The data base is the aggregate natural gas consumption of the nearly one million houses in New Jersey which use gas for heating. The conservation index resulting from the analysis is normalized annual consumption, which adjusts per-household consumption to typical weather conditions. To smooth erratic year-to-year changes, four-year composite analyses are moved forward in time over the period 1970–1982.Dramatic decreases in consumption, totaling 26% since the oil embargo, are evident. A decomposition of the results for the four years following the embargo suggests that over half of this conservation effect is due to changes in interior temperatures, with the policy implication that thermostat setbacks have played a far greater conservation role than have either structural changes through retrofitting or modifications in appliance usage. In more recent years, for which the overall reduction in energy usage is lower, the dominant conservation role appears to have shifted to reductions in temperature-independent, base-level consumption by water heaters and appliances, while the effects of retrofitting remain relatively small.     

When do energy-efficient appliances generate energy savings? Some evidence from Canada

Improvements in the energy efficiency of household appliances have the potential to decrease residential energy use, but these reductions accrue gradually over time as newer appliances replace older models. SHEU-2003 data are used to examine appliance replacement patterns in Canada for refrigerators, freezers, dishwashers, clothes washers and clothes dryers. The data indicate that the ages at which appliances are replaced tend to be lowest for dishwashers and highest for freezers, with over 40% of freezers in use for more than 20 years before being retired. The life spans of Canadian appliances are compared to the underlying assumptions regarding appliance lifetimes used in models of residential energy demand. We find that Canadian appliance retirement patterns differ from those assumed in the previous literature. Socioeconomic factors related to appliance replacement are also examined. We find that replacement patterns can be sensitive to household characteristics such as income, providing evidence that there may be scope for targeted policies aimed at inducing earlier replacements of older household appliances with new energy-efficient models.     

Demographics,energy and our homes

The projected growth in households in the UK is a key factor in future domestic energy consumption, particularly electricity consumption. While every household needs a home and its heating, lighting and appliances, increasing incomes have historically led to significantly higher appliance ownership, higher expectations of levels of energy service and greater usage. In the past this trend was combined with increasing household numbers to drive growth in domestic electricity demand. Official projections for population growth and household composition indicate significant drivers for future growth in energy demand. Curbing this will require policies to reverse the tendency for energy–efficiency improvements to be overwhelmed by growing numbers of households, more widespread appliance ownership and increased service expectations.     

Correction of load curves estimated by electrical appliances ownership surveys using mass memory meters

Through the PPHs (Energy Audit on Ownership and Usage of Electrical Appliances), one has a rough idea of the daily load shape curves by appliance. However, the curves obtained this way tend to be a little inaccurate, as they are generated by the consumer survey information of usage of the equipments, which tend to be imprecise information. Despite its inaccuracy, the energy audits (PPHs) are a simple and cheap way to understand equipment ownership and consumption habits of the residential consumers of such a large country as Brazil. In this work, it presented a statistical-based model that allows a better calibration of the load shape curve for appliances for residential consumers using information from two sources: PPHs and household measurements through specific devices that provide real-time measures of the total consumption. Two methodologies using linear regression were tested, one considering a two parameter linear model and another one considering only the slope parameter. It is shown that the latter produced better results.     

Economical and environmental impact of room air conditioners energy labels in Malaysia

The usage of residential electrical appliances for the last two decades has increased rapidly in Malaysia together with the increasing income per capita. Like other developing countries with hot and humid climates, Malaysia has been experiencing dramatic growth in the number of use of air conditioners, and the usage will be higher in the future. In order to reduce energy consumption in the residential sector, the Department of Electricity and Gas Supply considers implementing energy labels for room air conditioners sometime in the coming year. This study attempts to calculate the economical and environmental impact of implementing this program in Malaysia. The study found the savings has exceeded the investment cost and the program has reduced the emissions caused by burning fossil fuel.     

城市住宅结构及耗能设备节能潜力的调查分析

于2007年9月对中国七个典型城市住宅的住宅结构、主要耗能设备、生活方式、舒适性及空气品质和能源使用情况等方面进行了详细的问卷调查,本文分析了住宅结构和主要耗能设备两方面的情况,从而得知户型过大,围护结构保温性能差,住户节能意识不高等已成为实现我国建筑节能必须解决的问题。     

Prediction of greenhouse gas reduction potential in Japanese residential sector by residential energy end-use model

A model is developed that simulates nationwide energy consumption of the residential sector by considering the diversity of household and building types. Since this model can simulate the energy consumption for each household and building category by dynamic energy use based on the schedule of the occupants’ activities and a heating and cooling load calculation model, various kinds of energy-saving policies can be evaluated with considerable accuracy. In addition, the average energy efficiency of major electric appliances used in the residential sector and the percentages of housing insulation levels of existing houses is predicted by the “stock transition model.” In this paper, energy consumption and CO₂ emissions in the Japanese residential sector until 2025 are predicted. For example, as a business – as-usual (BAU) case, CO₂ emissions will be reduced by 7% from the 1990 level. Also evaluated are mitigation measures such as the energy efficiency standard for home electric appliances, thermal insulation code, reduction of standby power, high-efficiency water heaters, energy-efficient behavior of occupants, and dissemination of photovoltaic panels.     

Modeling of the appliance,lighting, and space-cooling energy consumptions in the residential sector using neural networks

Two methods are currently used to model residential energy consumption at the national or regional level: the engineering method and the conditional demand analysis method. Another potentially feasible method to model residential energy consumption is the neural network (NN) method. Using the NN method, it is possible to determine causal relationships amongst a large number of parameters, such as occur in the energy consumption patterns in the residential sector. A review of the published literature indicates that the NN method has not been used or tested for housing-sector energy consumption modeling. A NN based energy consumption model is being developed for the Canadian residential sector. This paper presents the NN methodology used in developing the appliances, lighting, and space-cooling component of the model, the accuracy of its predictions, and some sample results.