Journal articles: 'Electric household appliances'

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Won, An Na, and Won Hwa Hong. "A Survey on Ownership of Home Appliances and Electric Energy Consumption Status According to the Number of Household Member." Applied Mechanics and Materials 672-674 (October 2014): 2165–68. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.2165.

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With increasing trend of nuclear family, modern society is also showing a gradual increase in single households. Increase in single household leads to increased use of home appliances. Accordingly, the aim of this study was to examine ownership of electric home appliances (home appliance products that use electricity) and energy consumption status and to obtain implications for energy conservation.A survey was conducted / analyzed on 2,250 households, and the following results were obtained. First, ratio of home appliance ownership and number of appliances per household member were examined. Average number of home appliances was 10.6 for single households, 13.8 for 2-person households and 17.5 for households with 6 persons or more. Second, electric rate was found to be 46,000 won for single households and 114,000 won for households with 6 persons or more. Electric rate per member of household was rapidly reduced from <single household> to <4-person household>, showing about 50% conservation. In other words, increase in single households is regarded to have great impact on increase in energy consumption.

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Zhang, Ying, Bo Yin, Yanping Cong, and Zehua Du. "Multi-State Household Appliance Identification Based on Convolutional Neural Networks and Clustering." Energies 13, no. 4 (February 11, 2020): 792. http://dx.doi.org/10.3390/en13040792.

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Non-intrusive load monitoring, a convenient way to discern the energy consumption of a house, has been studied extensively. However, most research works have been carried out based on a hypothetical condition that each electric appliance has only one running state. This leads to low identification accuracy for multi-state electric appliances. To deal with this problem, a method for identifying the type and state of electric appliances based on a power time series is proposed in this paper. First, to identify the type of appliance, a convolutional neural network model was constructed that incorporated residual modules. Then, a k-means clustering algorithm was applied to calculate the number of states of the appliance. Finally, in order to identify the states of the appliances, different k-means clustering models were established for different multi-state electric appliances. Experimental results show effectiveness of the proposed method in identifying both the type and the running state of electric appliances.

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Toropov, Alexey. "Axiological distribution of the limited electric power of the household." E3S Web of Conferences 431 (2023): 02009. http://dx.doi.org/10.1051/e3sconf/202343102009.

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The structure of household electricity consumption depends on multiple factors. The operation of household electrical networks is possible within the allocated power limit and is restricted by the installed automatic disconnection devices of the power supply network. In conditions of limited allocated electrical power, comfortable living is not possible without prioritized power redistribution. A six-level hierarchical system of electrical power distribution for households has been proposed, incorporating variable priorities. By employing prioritized disconnection principles for groups of electrical appliances, the disconnection of limited household power supply can be avoided while maintaining maximum comfort. The proposed electrical connection scheme for household electrical equipment includes priority relays, time relays, and devices for remote disconnection of secondary appliances. When using heat pumps and heat accumulators for heating systems, a limit of 15 kWh is sufficient for comfortable use of any standard electrical appliances in households with an area of up to 150 square meters.

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Taik, Salma, and Bálint Kiss. "Household electricity usage optimization using MPC and mixed integer programming." Pollack Periodica 15, no. 1 (April 2020): 136–47. http://dx.doi.org/10.1556/606.2020.15.1.13.

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Abstract This paper discusses the control of the electric energy consumption in a household equipped with smart devices. The household consumption pattern is the result of a two-level optimization framework. The scheduling of the electric appliances is determined by the first optimization, receiving Time of Use tariffs proposed by the utility company. The scheduler considers the consumer's preferences on the powering on for each appliance. Secondly a model predictive controller is developed to control the electric heating system based on energy constraints resulting from the appliance scheduling. Simulations show the energy efficiency and an optimized electricity cost of the strategy proposed.

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Msimbe, Hamisi, Daniel Wilson, Juma Salim, Florian Rwegoshora, Dr Ramadhan Sinde, and Prof Michael kisangiri. "Development of IoT-Based System for Monitoring Electrical Energy Consumption of the Smart and Rental Houses in Tanzania." International Journal of Advances in Scientific Research and Engineering 08, no. 08 (2022): 01–10. http://dx.doi.org/10.31695/ijasre.2022.8.8.1.

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Electricity has a significant impact on human productivity when using a variety of electrical appliances in households. Appliances hooked into the electric network are now causing an increase in electric energy usage in rental homes hence the increases in the user's electricity expenses. Some tenants consume high electrical energy compared to others due to the electrical meters cannot determine the amount of usage by each tenant in the house, all tenants contribute the same universal payment which is not realistic. To offset these costs, a monitoring system for electric energy consumption based on each appliance in a household is formulated, allowing customers to see how much money and energy they are wasting. Different studies have thus far proposed monitoring electric energy consumption in households. However, most of the solutions did not consider the electric energy consumption of individual appliances which is a main problem for the end-users. This paper presents an Internet of Things-based system to provide information to the users through an application on their daily consumption usage updates whether they are online with the presence of a Wi-Fi module. The system has a backup battery to allow giving information in case the power supply is off. Moreover, our system is designed to monitor the real-time energy consumption of individual appliances. Our results show that 90% of end-users that observed the implemented system are capable of monitoring daily electrical consumption hence tenants can put a good budget on their purchase of electrical units.

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Gubernskiy, Yu D., Mikhail E. Goshin, N. V. Kalinina, and I. M. Banin. "Hygienic aspects of electromagnetic pollution of indoor environment." Hygiene and sanitation 95, no. 4 (October 28, 2019): 329–35. http://dx.doi.org/10.18821/0016-9900-2016-95-4-329-335.

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There is presented an overview of studies devoted to the assessment of 50 Hz electromagnetic the radiations in the indoor environment and their impact on the human body. The classification of household appliances depending on their location has been proposed. The levels of intensity of electric and magnetic fields generated by power-frequency (50 Hz) current from a variety of household appliances have been determined. The ranking of household appliances in dependence on the intensity of electromagnetic the radiations has been made. There was performed an estimation of the intensity of electromagnetic fields in dependence on the regimen of the usage of appliances.

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Ueno, Kiyoshi. "Recycling and Eco-Design of Household Electric Appliances." Waste Management Research 15, no. 3 (2004): 115–22. http://dx.doi.org/10.3985/wmr.15.115.

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Cao, Ruobing. "Comparative Analysis of Investment Value in Chinese Household Appliance Industry." Highlights in Business, Economics and Management 13 (May 29, 2023): 192–97. http://dx.doi.org/10.54097/hbem.v13i.8814.

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As an important part of the consumption field, household appliances play a key role in China's economic growth. After 30 years of development, China's home appliance industry has made remarkable achievements and occupies an important position in the world's home appliance industry. It has become the largest manufacturing base and consumer market of home appliances in the world, leading international counterparts in cost and quality, with obvious advantages. There is no doubt that the value of an investment in China's home appliance industry is also growing. Therefore, this paper adopts appropriate evaluation methods to study the investment value of three major home appliance companies in China -- Haier Zhijia, Gree Electric, and Changhong Meiling, so that the majority of investors can realize their investment value, and at the same time, it also contributes its own strength to guide investors to make rational value investment and promote the healthy development of Chinese capital market. This paper compares and analyzes their investment value from three aspects: risk ratio, profitability ratio, and market value ratio. Based on the analysis, the conclusion of this paper is that these three companies are basically excellent, have broad investment value, and Haier Zhijia has the most development prospects.

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Chatzigeorgiou, Ioanna-M., Christos Diou, Kyriakos C. Chatzidimitriou, and Georgios T. Andreou. "Demand Response Alert Service Based on Appliance Modeling." Energies 14, no. 10 (May 20, 2021): 2953. http://dx.doi.org/10.3390/en14102953.

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Demand response has been widely developed during recent years to increase efficiency and decrease the cost in the electric power sector by shifting energy use, smoothening the load curve, and thus ensuring benefits for all participating parties. This paper introduces a Demand Response Alert Service (DRAS) that can optimize the interaction between the energy industry parties and end users by sending the minimum number of relatable alerts to satisfy the transformation of the load curve. The service creates appliance models for certain deferrable appliances based on past-usage measurements and prioritizes households according to the probability of the use of their appliances. Several variations of the appliance model are examined with respect to the probabilistic association of appliance usage on different days. The service is evaluated for a peak-shaving scenario when either one or more appliances per household are involved. The results demonstrate a significant improvement compared to a random selection of end users, thus promising increased participation and engagement. Indicatively, in terms of the Area Under the Curve (AUC) index, the proposed method achieves, in all the studied scenarios, an improvement ranging between 41.33% and 64.64% compared to the baseline scenario. In terms of the F1 score index, the respective improvement reaches up to 221.05%.

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Gara, Evita, and Claudio Rochas. "Simulation of the Stock of Electric Appliances and Calculation of Standby Losses for Latvia." Scientific Journal of Riga Technical University. Environmental and Climate Technologies 5, no. -1 (January 1, 2010): 35–41. http://dx.doi.org/10.2478/v10145-010-0032-5.

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Simulation of the Stock of Electric Appliances and Calculation of Standby Losses for Latvia Standby losses in households are discussed in this paper. As there was no information on the total volume of standby losses in Latvia, the objective of the study was to calculate: the percentage from the household total electricity bill that goes to standby losses; what are the total costs for these losses; and how much CO2 is produced to generate the amount of electricity that is needed to cover these standby losses. All calculations were conducted for one and for all households in Latvia and the results of one household were compared with an average European household. Finally, the savings potential that can be obtained implementing the Eco-design Directive and other political instruments was examined.

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Ozughalu, Uche M. "Patterns and Determinants of Households' Energy Choices for Cooking as Well as Their Implications for Poverty Eradication in Nigeria." Journal of Developing Areas 57, no. 4 (September 2023): 175–99. http://dx.doi.org/10.1353/jda.2023.a908652.

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ABSTRACT: Adequate access to environmentally-friendly energy sources is crucial for addressing the problems of environmental degradation and adverse climate change as well as other developmental challenges. The literature on the patterns and determinants of households' energy choices for cooking is very scanty. Essentially, the scanty literature, in general, did not adequately cater for household composition and economies of scale in household consumption as well as give adequate consideration to the impact of ownership of education/entertainment appliances and means of communication by households on households' energy choices for cooking. It is very important to utilize adult equivalence scales and estimate of economies of scales in household consumption in the analysis of household consumption in order to make such analysis highly robust. It is also very important to include ownership of education/entertainment appliances and means of communication in the analysis of households' energy choices for cooking because they (the appliances and means of communication) are expected to provide adequate awareness on the harmful effects of dirty energy sources and such awareness can influence households' energy choices. Furthermore, none of the studies in the scanty literature discussed the major implications for poverty eradication of the patterns and determinants of households' energy choices for cooking. This study adequately addressed the highlighted research gaps. The study analyzed the patterns and determinants of households' energy choices for cooking in Nigeria and discussed their implications for poverty eradication in the country using, among other things, descriptive statistics and multinomial logistic regression technique. The study was based on a nationally representative survey data, obtained from the National Bureau of Statistics. The study found that the patterns of households' energy choices for cooking in Nigeria exhibit the operation of energy ladder hypothesis. The study also found that increased educational level of household head, ownership of electric food preservation appliance by household and satisfactory housing condition are among the factors that increase the likelihoods of the uses of transition fuels and very clean energy sources as well as reduce the likelihood of the use of traditional biomass fuels. Adequate measures should therefore be put in place to sufficiently increase households' incomes and guarantee optimal access to environmentally-friendly energy sources for cooking in the country; this will pave the way for poverty eradication in the country.

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Binish Naz. "Configuration-Free Systems for WiFi Sensing based Smart Home using the Smart Remote Controller." Lahore Garrison University Research Journal of Computer Science and Information Technology 5, no. 1 (February 9, 2021): 79–86. http://dx.doi.org/10.54692/lgurjcsit.2021.0501179.

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The Smart Home invention offers us extreme supervision over our home by automating the lighting structure, the dimming, the screens, electric machines, the sound and safety frames. Main technologies that provide connectivity to smart home facilities, WiFi is one of them. In traditional households, where the household appliances will increase, the remote controls to manage them and the interference between them will also increase. This makes the system configuration dependent and troublesome for users to manage them that increases their burden. Recently, some systems were developed to manage multiple household appliances through one interface. However, the matter is once the dataset will increases the interface gets sophisticated and every home appliance or controller wants a special device to connect with it. In this paper, we introduced FreeGesture in the DeepRemote controller, which is a gesture recognition scheme without a device that uses preferred computer vision algorithms, particularly deep learning, to recognize numerous devices and manage them via IR or network. It simplifies deployment and makes systems without configuration. We are going to consider it as “Smart Remote” in this article. Smart Remote consists of four buttons, a camera, an Inertial Measurement Unit (IMU), a WiFi component, an Infrared (IR) transceiver, and a speaker. The popularity accuracy of smart Remote for 5 varieties of home appliances from completely different places is hyperbolic from 81.07% to 95.8%.

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Seva Bala Sundaram, Mithila, ChiaKwang Tan, Jeyraj Selvaraj, and Ab Halim Abu Bakar. "Energy Savings for Various Residential Appliances and Distribution Networks in a Malaysian Scenario." Energies 16, no. 13 (June 23, 2023): 4902. http://dx.doi.org/10.3390/en16134902.

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This paper presents a detailed study of the energy savings that can be achieved through residential appliances by implementing conservation voltage reduction (CVR). The computed energy savings are derived from the ZIP coefficients of a load model (static) under varying voltage conditions that represent the power consumed by each appliance tested. Multiple studies have shown energy savings at the substation level but not at the level of a specific residence and appliance; hence, the latter is the focus of this analysis. The appliances are determined based on the type of heating and cooling loads, and the daily duration of use for each appliance, which contributes to the total monthly consumption that is billed for a household are included in this study. Energy savings in Malaysia has been a focus of many current studies, and this study is the first attempt to achieve energy savings through the implementation of CVR. No published work has compared individual appliances that truly benefits from CVR, and this is addressed in this study. The main contribution of this study is that it provides very detailed and measured data that are used to analyze and generate energy savings for very specific residential appliances intended to meet every 1% voltage drop. The load model is developed for the common household appliances in Malaysia, and then a voltage reduction study is applied to the appliances as well as the Malaysian distribution networks. Here, we also provide insight for performing voltage reduction at an electric vehicle (EV) charging station in Malaysia. The results of this study should serve as a foundation for all practicing utilities engineers to address the issue of CVR in Malaysia. The CVR factors for residential, commercial, and industrial networks in Malaysia are also published in this paper.

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Yoshida, Aya, Panate Manomivibool, Tomohiro Tasaki, and Pattayaporn Unroj. "Qualitative Study on Electricity Consumption of Urban and Rural Households in Chiang Rai, Thailand, with a Focus on Ownership and Use of Air Conditioners." Sustainability 12, no. 14 (July 18, 2020): 5796. http://dx.doi.org/10.3390/su12145796.

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This study investigated the differences in household energy consumption between urban and rural households in northern Thailand, with a particular focus on air-conditioner ownership and use. In-depth visits to 32 households in Chiang Rai were undertaken in 2016 and 2017. The data collection covered six aspects: household attributes, ownership of electric appliances, use of air conditioners (ACs), intentions to conserve electricity, desire to purchase electric appliances in the future, and prospects for a future lifestyle. Traditional stilt houses can still be found in rural areas, but ACs have been introduced as rural houses have modernized. The typical period of AC use in rural areas was 2 to 4 months during summer. In urban households, ACs were used for a longer period, from 3 to 12 months each year. In addition, rural households usually used ACs for only a few hours each day before sleeping, whereas urban households often used them while they slept and some used them throughout the day. Households with children and grandchildren tended to use the AC for longer periods. These results suggest that promotion of environmentally friendly lifestyles for younger adults to control overuse of ACs would be key to reducing energy consumption in the future.

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Han, Jun, Zhenjian Xie, and Chao Cai. "Multi-level Topology and Dynamic Power Sharing of Household DC Distribution System." Journal of Physics: Conference Series 2465, no. 1 (March 1, 2023): 012020. http://dx.doi.org/10.1088/1742-6596/2465/1/012020.

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Abstract With the popularity of electronic information products and the gradual adoption of DC speed control in electric household appliances, more and more household appliances are equipped with rectifiers or inverters. Moreover, household rooftop PV, wind turbines and energy storage devices also output electric energy in the form of DC. This paper presents a topology of household DC distribution system, which not only improves the reliability of power supply from the power consumption mode, reduces the loss in the process of power form conversion, but also provides users with safer voltage level and more reasonable fault protection. On this basis, this paper proposes an instantaneous power sharing scheme based on droop control, which enables each power module of the system to achieve steady-state and dynamic power sharing.

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Liu, Lin, Xin Yang, Han Huang, and Shiyan Hu. "Smart Home Scheduling for Cost Reduction and Its Implementation on FPGA." Journal of Circuits, Systems and Computers 24, no. 04 (March 4, 2015): 1550044. http://dx.doi.org/10.1142/s0218126615500449.

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In a typical smart home scenario, various household appliances of a residential user such as washing machine and plug-in hybrid electric vehicle (PHEV) are connected via a home area network. Household appliances can be automatically scheduled by a central controller for satisfying the timing and energy constraints. It enables the reduction of monetary cost of electricity consumption and the peak energy load of the home system. On the other hand, the prevailing household appliances usually offer multiple discrete power levels. However, the existing smart home scheduling controllers can only handle the continuous power levels, while makes them unsuitable for prevailing household appliances. In this paper, a dynamic programming-based scheduling technique is proposed and implemented on FPGA to schedule household appliances with discrete power levels. It features a solution pruning technique, which can largely improve the time complexity. A case study which constitutes ten household appliances is performed. The experimental results demonstrate that our technique can reduce the monetary cost by 39.3% on weekday and 27.2% on weekend, respectively, comparing to the traditional scheduling. For energy consumption balancing, it shows that the peak to average ratio (PAR) of the energy consumption is reduced by 43.6% on weekday and 24.0% on weekend, respectively.

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Li, Bo, Min Cao, Peng Fei Huang, Zhi Zhou Bi, Yuan Qiang Xiao, Can Mei Hong, Tao Xie, et al. "Characteristic Study on Carrier Communication Device Noise of Low Voltage Power Lines Based on UPS." Applied Mechanics and Materials 599-601 (August 2014): 1429–34. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.1429.

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Low-voltage power lines are not designed to transmit communication data; it is not ideal channel characteristics using power line as a data communication medium, especially the noise generated by the several of household electrical appliances will have a significant impact on the power line communication system. First, low-voltage power line carrier communication and channel noise characteristics are analyzed, and based on pure electricity environment UPS, the experimental results obtained with different electric appliances for data processing, and analyze the impact of the electric appliances noise on the power line carrier communication.

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Kotani, Hitomu, and Kazuyoshi Nakano. "How a Household Survived a Natural Hazard-Triggered Blackout with Photovoltaic and Battery Energy System: A Report of 2018 Hokkaido Eastern Iburi Earthquake in Japan." Journal of Disaster Research 18, no. 3 (April 1, 2023): 280–86. http://dx.doi.org/10.20965/jdr.2023.p0280.

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Energy-generating and storage systems, such as photovoltaic (PV) panels and energy storage batteries in homes, are becoming increasingly popular in the context of decarbonization. The systems are also expected to increase household resilience to natural hazard-triggered blackouts. However, how these systems contribute to the use of electrical appliances in households in actual cases is not sufficiently known. Therefore, this report aims to describe the activities that a household with an energy-generating and storage system could undertake during a natural hazard-triggered blackout. We focused on the blackout triggered by the 2018 Hokkaido Eastern Iburi Earthquake (approximately 2.95 million households lost power) and conducted an interview with a household living in a detached all-electric house with a PV and battery system. The results showed that the household lived without inconveniences during the blackout due to the power supply from the installed system, despite the weather. They charged cell phones and used a television, refrigerator, microwave oven, cooking heater, and bath. Moreover, the household’s electricity was also supplied to other households. These results clarified the actual benefit of enhancing household and community resilience of the systems. The results will aid household decision-making for the installation and governmental consideration of subsidies.

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Kaur, Jasmeet, and Anju Bala. "Predicting power for home appliances based on climatic conditions." International Journal of Energy Sector Management 13, no. 3 (September 2, 2019): 610–29. http://dx.doi.org/10.1108/ijesm-04-2018-0012.

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Purpose Power management in households has become the periodic issue for electric suppliers and household occupants. The number of electronic appliances is increasing day by day in every home with upcoming technology. So, it is becoming difficult for the energy suppliers to predict the power consumption for households at the appliance level. Power consumption in households depends on various factors such as building types, demographics, weather conditions and behavioral aspect. An uncertainty related to the usage of appliances in homes makes the prediction of power difficult. Hence, there is a need to study the usage patterns of the households appliances for predicting the power effectively. Design/methodology/approach Principal component analysis was performed for dimensionality reduction and for finding the hidden patterns to provide data in clusters. Then, these clusters were further being integrated with climate variables such as temperature, visibility and humidity. Finally, power has been predicted according to climate using regression-based machine learning models. Findings Power prediction was done based on different climatic conditions for electronic appliances in the residential sector. Different machine learning algorithms were implemented, and the result was compared with the existing work. Social implications This will benefit the society as a whole as it will help to reduce the power consumption and the electricity bills of the house. It will also be helpful in the reduction of the greenhouse gas emission. Originality/value The proposed work has been compared with the existing work to validate the current work. The work will be useful to energy suppliers as it will help them to predict the next day power supply to the households. It will be useful for the occupants of the households to complete their daily activities without any hindrance.

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TAKEMOTO, Shizuo, Masayoshi KUBO, and Ichiro UEDA. "A Study on Illegal Abandonment of Used Household Electric Appliances." Journal of Japan Institute of Navigation 109 (2003): 247–56. http://dx.doi.org/10.9749/jin.109.247.

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Jin, Hyun Joung, Jeong In Kim, Eun Young You, and Seo Hwa Park. "Estimation of Potential Supply of Offset from Household Electric Appliances." Environmental and Resource Economics Review 24, no. 3 (September 30, 2015): 463–88. http://dx.doi.org/10.15266/kerea.2015.24.3.463.

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Levin, N., V. Pugachev, J. Dirba, and L. Lavrinovicha. "Physical and Technical Energy Problems." Latvian Journal of Physics and Technical Sciences 50, no. 3 (June 1, 2013): 3–11. http://dx.doi.org/10.2478/lpts-2013-0015.

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The paper presents an overview of brushless electric motors used in hand electric tools and household appliances. Analysis of the motor types has shown that synchronous reluctance motors are the most reliable for lowpower drives of such tools and appliances due to their simple design, long service life and low cost of production. Solutions are proposed for significant decrease in the quadrature-axis magnetic flux of the synchronous reluctance motor. The motors are shown to develop the specific electromagnetic torque up to 0.35÷0.4 Nm/kg.

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Cerna, Fernando V., Mahdi Pourakbari-Kasmaei, Luizalba S. S. Pinheiro, Ehsan Naderi, Matti Lehtonen, and Javier Contreras. "Intelligent Energy Management in a Prosumer Community Considering the Load Factor Enhancement." Energies 14, no. 12 (June 18, 2021): 3624. http://dx.doi.org/10.3390/en14123624.

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In prosumers’ communities, the use of storage batteries (SBs) as support for photovoltaic (PV) sources combined with coordination in household appliances usage guarantees several gains. Although these technologies increase the reliability of the electricity supply, the large-scale use of home appliances in periods of lower solar radiation and low electricity tariff can impair the performance of the electrical system. The appearance of new consumption peaks can lead to disturbances. Moreover, the repetition of these events in the short term can cause rapid fatigue of the assets. To address these concerns, this research proposes a mixed-integer linear programming (MILP) model aiming at the optimal operation of the SBs and the appliance usage of each prosumer, as well as a PV plant within a community to achieve the maximum load factor (LF) increase. Constraints related to the household appliances, including the electric vehicle (EV), shared PV plant, and the SBs, are considered. Uncertainties in consumption habits are simulated using a Monte Carlo algorithm. The proposed model was solved using the CPLEX solver. The effectiveness of our proposed model is evaluated with/without the LF improvement. Results corroborate the efficient performance of the proposed tool. Financial benefits are obtained for both prosumers and the energy company.

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Ma, Mei, Bin Huang, Bin Wang, Jian Chen, and Lida Liao. "Development of an Energy-Efficient Smart Socket Based on STM32F103." Applied Sciences 8, no. 11 (November 17, 2018): 2276. http://dx.doi.org/10.3390/app8112276.

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Many efforts have recently been dedicated to developing smart sockets that seek to provide insights into the reduction of standby energy waste coupled to electric appliances. However, not all technical solutions consider the techno-economic benefits in the development. This research presents a hardware solution based on STM32F103 (STM32F103 devices use the Cortex-M3 core, with a maximum CPU speed of 72 MHz) for the development of an energy-efficient smart socket to address the standby energy waste of household electric appliances and associated economic losses. Input-output analysis on monitored voltage and current was employed to assess the performance and examine the precision of the developed system. As it was targeted at facilitating easier operation, the smart socket was developed to be compatible with other remote controllers of household electric appliances. Experimental results indicated that the developed system could measure voltage values accurately to avoid overvoltage for security protection. The measuring unit could monitor current values with high precision to support the energy-saving control. A functional testing was conducted on the prototypes with a lifecycle assessment employed to validate the economic attractiveness of the developed system. Results indicated that the system is user friendly and cost-effective as no extra wiring required and network environment independent. Indeed, indirect fruits, such as lifespan extension and safety enhancement, could also be achieved for appliances.

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Jiang, Wenqian, Bo Liu, Zhou Yang, Hanju Cai, Xiuqing Lin, and Da Xu. "Non-Intrusive Arc Fault Detection and Localization Method Based on the Mann–Kendall Test and Current Decomposition." Energies 16, no. 10 (May 9, 2023): 3988. http://dx.doi.org/10.3390/en16103988.

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In recent years, electrical fires caused by arc faults have been increasing, seriously affecting the safety of people’s lives and property. Considering the complex arc fault characteristics of actual low-voltage users, the non-intrusive arc fault detection and localization method is studied. First, the characteristics of arc current waveforms are analyzed, and event detection based on the Mann–Kendall Test is performed for the difference between the current waveforms of two adjacent cycles, rather than using the current waveforms directly. Then, the current waveforms of the two segments are calculated via subtraction to obtain the current waveform of the electric appliances causing the event. A current feature parameter database of the normal and arc currents is constructed via harmonic analysis, and a multi-appliance current decomposition model considering the sparse operation characteristics of appliances is established; thus, the arc localization problem is transformed into an optimization problem. Finally, a genetic algorithm is used to optimize the differential current decomposition results, and then, locate the arc fault. A household arc fault simulation experiment is carried out for the common electric appliances of actual low-voltage users. The experimental results show that the proposed non-intrusive arc fault detection and localization method is effective.

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Toropov, Alexey. "The system of priority distribution of the allocated limited electrical capacity of the household." E3S Web of Conferences 389 (2023): 01058. http://dx.doi.org/10.1051/e3sconf/202338901058.

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The structure of household electricity consumption is dependent on many factors, such as time, climate, territorial, historical, social, age, gender, and political factors. Operation of the power grid of households is possible within the allocated power limit and is limited by the devices installed for automatic disconnection of the power supply network. A 6-level hierarchical, with alternating precedence, system of electric power distribution for households is proposed. The highest (first) level is urgent needs and without which in the modern world it is impossible to exist. The second refers to devices to ensure the physiological and social needs of a person, the third is large household appliances. The fourth and fifth levels of the pyramid of household electricity consumption are related to heat supply systems and the concept of thermal inertia of buildings. The sixth is the devices of the lowest priority, supplied with energy according to the residual principle. An example is charging an electric car. The proposed method of distribution of electrical power allows to ensure comfortable living in the household while limiting the total power of the allocated electrical energy.

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Tri Atmaja, Sigit, and Abdul Halim. "Steady State Modification Method Based On Backpropagation Neural Network For Non-Intrusive Load Monitoring (NILM)." MATEC Web of Conferences 218 (2018): 02013. http://dx.doi.org/10.1051/matecconf/201821802013.

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Household electric power sector is highlighted as one of significant contributors to national energy consumption. To reduce electric energy usage in this sector, a technique called Non-Intrusive Load Monitoring (NILM) has been developed recently. NILM is a load disaggregating and monitoring tool that can be used to identify the daily usage behavior of individual electric appliance. Different to conventional method, NILM promises the reduction of sensor deployment significantly. NILM commonly uses either transient or steady state signal. Based on load/appliance signal condition, many NILM’s research results have been published. In this paper, steady state modification method of backpropagation neural network (NN) is applied for developing NILM. We use steady state signal to disaggregate the sum of load power signal. In the proposed method, NN is explored for feature extraction of electric power consumption of individual appliance. The presented method is powerful for load power signal which has almost same value. To verify the effectiveness of proposed method, data provided by tracebase.org has been used. The presented method can be applied for local data. It is obvious from simulation results that the proposed method could improve the recognition rate of appliances until 100 %.

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M. Trushina, Kira. "Some aspects of home ecology: measuring the level of EMF from household appliances." Ecology, Environment and Conservation 29, no. 04 (2023): 1461–64. http://dx.doi.org/10.53550/eec.2023.v29i04.001.

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The results of domestic and foreign studies clearly indicate the high biological activity of EMF. In a residential environment, a person is exposed to electromagnetic fields from a variety of sources. The purpose of this work was to determine the level of EMF near various household appliances and develop appropriate safety recommendations. To achieve the goal, the following tasks were set: to measure the levels of electric field strength, the level of magnetic induction, to determine the distances to the devices at which the threshold values of EMF are not exceeded. Measurements of the intensity of electric and magnetic fields of industrial frequency 50 Hz were carried out from sources located in residential premises; a total of 26 EMI sources were examined. almost all household appliances are EMF sources, and some devices both in operation and in standby mode exceed the maximum permissible values of electric field strength and magnetic induction, indicated in GOST R 54148-2010 and San PiN 2.1.2.1002-00 (E = 25 V/m, V = 250 nT). The greatest concern is the proximity of the human body with such devices as a slow cooker, a vacuum cleaner, a radio receiver and a hair dryer. For example, the highest values of the electric field strength were noted for a bread maker, and magnetic induction for a vacuum cleaner. Based on the data obtained, it can be concluded that for the safe use of household appliances, it is desirable to be located at least 50 cm away from them. Devices that are not in use at the current time must be disconnected from the electrical network.

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Rossit, Diego G., Segio Nesmachnow, Jamal Toutouh, and Francisco Luna. "Scheduling deferrable electric appliances in smart homes: a bi-objective stochastic optimization approach." Mathematical Biosciences and Engineering 19, no. 1 (2022): 34–65. http://dx.doi.org/10.3934/mbe.2022002.

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<abstract><p>In the last decades, cities have increased the number of activities and services that depends on an efficient and reliable electricity service. In particular, households have had a sustained increase of electricity consumption to perform many residential activities. Thus, providing efficient methods to enhance the decision making processes in demand-side management is crucial for achieving a more sustainable usage of the available resources. In this line of work, this article presents an optimization model to schedule deferrable appliances in households, which simultaneously optimize two conflicting objectives: the minimization of the cost of electricity bill and the maximization of users satisfaction with the consumed energy. Since users satisfaction is based on human preferences, it is subjected to a great variability and, thus, stochastic resolution methods have to be applied to solve the proposed model. In turn, a maximum allowable power consumption value is included as constraint, to account for the maximum power contracted for each household or building. Two different algorithms are proposed: a simulation-optimization approach and a greedy heuristic. Both methods are evaluated over problem instances based on real-world data, accounting for different household types. The obtained results show the competitiveness of the proposed approach, which are able to compute different compromising solutions accounting for the trade-off between these two conflicting optimization criteria in reasonable computing times. The simulation-optimization obtains better solutions, outperforming and dominating the greedy heuristic in all considered scenarios.</p></abstract>

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Grabchikov, S. S., E. A. Grabchikova, A. P. Drapezo, T. I. Zubar, M. I. Panasyuk, O. D. Kanafyev, A. V. Losev, A. V. Trukhanov, and V. M. Fedosyuk. "The problem of protecting a person from the effects of low-frequency electromagnetic fields in modern society. Possible ways to solve it." Proceedings of the National Academy of Sciences of Belarus. Physical-technical series 69, no. 2 (July 9, 2024): 114–28. http://dx.doi.org/10.29235/1561-8358-2024-69-2-114-128.

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The paper considers the problem of the impact of low-frequency electromagnetic fields (EMF) generated by electric vehicles (EV) and household appliances on humans in modern society. The data on the effect of EMF on human health and regulatory documents establishing requirements for electromagnetic safety are presented. The method of electromagnetic shielding and materials for the implementation of this method are considered as a promising method for solving the problem. The levels of electromagnetic radiation from a number of EV and household electrical appliances have been experimentally measured. The efficiency of electromagnetic shielding of materials based on single-layer coatings of Ni80Fe20 alloys, multilayer film structures Ni80Fe20/Cu and amorphous metal alloys AMAG172 has been estimated using a computational method. It is shown that electromagnetic screens based on these materials significantly reduce the levels of exposure to EMF of EV and household electrical appliances on humans, which allows us to approach the hygienic standards recommended by doctors and meet the requirements of regulatory documents on remote control.

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Murata, Hiroshi, Takashi Onoda, Katsuhisa Yoshimoto, Yukio Nakano, and Syuhei Kondo. "Non-Intrusive Electric Appliances Load Monitoring System-Experiment for Real Household-." IEEJ Transactions on Electronics, Information and Systems 124, no. 9 (2004): 1874–80. http://dx.doi.org/10.1541/ieejeiss.124.1874.

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Wu, Yu Chi, Meng Jen Chen, Hsien Min Liao, Bo Huei Yang, and Jing Yuan Lin. "Standby-Energy-Saving Socket." Applied Mechanics and Materials 563 (May 2014): 356–61. http://dx.doi.org/10.4028/www.scientific.net/amm.563.356.

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Most home electric appliances have standby energy waste when they are at idle mode. This standby energy is about 3% to 11% of total household electricity consumption. For several millions of households in Taiwan, this standby energy would cause billion dollars of waste per year. Therefore, in this paper we propose a standby-energy-saving socket using a microcontroller unit (MCU) to reduce the standby-energy waste. The user can start up this standby-energy-saving socket to supply power to appliances through the appliances infrared remote control or the button on the socket. When the appliances enter into the standby mode, the current sensor in the socket automatically detects it and the MCU turns off the power through a relay to reduce the standby power to zero. Based on the test, the MCU in the proposed standby-energy-saving socket only consumes about 3 mW when the socket is at sleep mode, 6 mW at working mode. The cost of this proposed socket is $9. The standby-energy saving tested on a PC is reduced by 99.93%.

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Martand Prata, Et al. "Analysis of PFC Buck-Boost Converter Fed PMBLDC Motor Drive Systems." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 8 (August 31, 2023): 560–68. http://dx.doi.org/10.17762/ijritcc.v11i8.10056.

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Electric motors influence almost every aspect of modern life. Refrigerators, vacuum cleaners, air conditioners, fans, computer hard drives, automatic vehicle windows, & a number of other household products & devices employ electric motors to convert electrical energy into usable mechanical energy. Electric motors power a wide range of industrial processes in addition to powering residential appliances. Brushless DC (BLDC) motor drives have grown in popularity in recent years due to their suitability for a wide range of low and medium power applications such as household appliances, medical equipment, position actuators, Heating, Ventilation, and Air Conditioning (HVAC), motion control, and transportation. These drives have great efficiency, dependability, durability, and outstanding performance across a wide range of speed control. The BLDC motor cannot be connected directly to the supply and must be driven by a drive consisting of VSI controlled by an electronic commutation system. Harmonics are introduced into the main power supply and power factor issue by the electronic commutation system and rectification procedure. Power Factor Correction (PFC) converters are used to improve the power quality and power factor of the alternating current mains.

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El Makroum, Reda, Ahmed Khallaayoun, Rachid Lghoul, Kedar Mehta, and Wilfried Zörner. "Home Energy Management System Based on Genetic Algorithm for Load Scheduling: A Case Study Based on Real Life Consumption Data." Energies 16, no. 6 (March 14, 2023): 2698. http://dx.doi.org/10.3390/en16062698.

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This paper proposes a home energy management system able to achieve optimized load scheduling for the operation of appliances within a given household. The system, based on the genetic algorithm, provides recommendations for the user to improve the way the energy needs of the home are handled. These recommendations not only take into account the dynamic pricing of electricity, but also the optimization for solar energy usage as well as user comfort. Historical data regarding the times at which the appliances have been used is leveraged through a statistical method to integrate the user’s preference into the algorithm. Based on real life appliance consumption data collected from a household in Morocco, three scenarios are established to assess the performance of the proposed system with each scenario having different parameters. Running the scenarios on the developed MATLAB script shows a cost saving of up to 63.48% as compared to a base scenario for a specific day. These results demonstrate that significant cost saving can be achieved while maintaining user comfort. The addition of supplementary shiftable loads (i.e., an electric vehicle) to the household as well as the limitations of such home energy management systems are discussed. The main contribution of this paper is the real data and including the user comfort as a metric in in the home energy management scheme.

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Ashley, Steven. "Energy-Efficient Appliances." Mechanical Engineering 120, no. 03 (March 1, 1998): 94–97. http://dx.doi.org/10.1115/1.1998-mar-6.

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Washing machines and other household devices are being redesigned for greater efficiency. Key to creating an energy-efficient washer is to cut the use of water, because 85 to 90 percent of the energy used in washers goes to heating the water. This is typically accomplished by a front-loading unit with a tub that rotates around a horizontal axis. Studies by Electric Power Research Institute (EPRI), Palo Aldo, CA, show that horizontal-axis machines use about one-third less water and two-thirds less energy than the vertical-axis machines that have captured almost the entire U.S. market. Maytag Laundry Appliances Research and Development’s new front-loading Neptune washer features a horizontal-axis tub that is angled up 15 degrees to improve visibility and access. Rather than agitating wash loads in a full tub of water like standard top loaders, the Neptune washer substitutes a clothes-dryer-like tumbling action that dunks fabrics in a smaller volume of water.

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Zhang, Ai Rong, and Jin Lan Zhang. "The Building of Home Automation Electricity Distribution System Based on PLC." Advanced Materials Research 442 (January 2012): 407–11. http://dx.doi.org/10.4028/www.scientific.net/amr.442.407.

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Home automation is a common area of interest the researchers and engineers work, of course, the consumer. Today, intelligent household system is commonly found in many homes in many countries around the world. This system not only provides a high level of control household appliances, also should try to reduce the waste electricity. Electric power communication (PLC) is a kind of common technology used in home automation system, household electric wire reuse for communication. But the current system puts forward the shortcomings of the need to improve. We introduced the design a new generation of intelligent household system that will give consumers with a huge characteristics and businessman. The main characteristics of the system are based on the Internet control, logging-facilities.

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Saban Selim Seker, Osman Cerezci, Muhammet Fatih Bayindir, and Ozlem Simsek. "Electromagnetic High-Frequency Transients Measurements of Some Household Devices." Emerging Science Innovation 2 (January 29, 2024): 19–25. http://dx.doi.org/10.46604/emsi.2023.12005.

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Voltage Transients are generated in power lines and emit both low-frequency electromagnetic fields and radio-frequency radiation. This study aims to highlight its existence and detrimental effects on human health. A comprehensive literature review is presented, encompassing studies by multiple authors exploring the topic of dirty electricity, its impact on well-being, and preventative measures. The electromagnetic spectrum analysis and measurements of both electric and magnetic fields are performed on various household appliances such as hair dryers, old televisions, blenders, heaters, toasters, vacuum cleaners, and microwaves. The findings indicates that microwaves and compact fluorescent lamps (CFL) bulbs exhibit similar spectral characteristics, with high-frequency voltage transients primarily originating from these two devices. Conversely, other appliances do not generate significant high-frequency voltage transients (HFVT). Overall, dirty electricity poses a substantial risk to human health and necessitates attention to minimize its adverse consequences.

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Shin, Hyunkyung, and Zong Geem. "Optimal Design of a Residential Photovoltaic Renewable System in South Korea." Applied Sciences 9, no. 6 (March 18, 2019): 1138. http://dx.doi.org/10.3390/app9061138.

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An optimal design model for residential photovoltaic (PV) systems in South Korea was proposed. In the optimization formulation, the objective function is composed of three costs, including the monthly electricity bill, the PV system construction cost (including the government’s subsidy), and the PV system maintenance cost. Here, because the monthly electricity bill is not differentiable (it is a stepped piecewise linear function), it cannot be solved by using traditional gradient-based approaches. For details considering the residential electric consumption in a typical Korean household, consumption was broken down into four types (year-round electric appliances, seasonal electric appliances, lighting appliances, and stand-by power). For details considering the degree of PV generation, a monthly generation dataset with different PV tilt angles was analyzed. The optimal design model was able to obtain a global design solution (PV tilt angle and PV size) without being trapped in local optima. We hope that this kind of practical approach will be more frequently applied to real-world designs in residential PV systems in South Korea and other countries.

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Imahori, Yoko, and Tohru Morioka. "Field Work of Leasing for Household Electric Appliances towards Cycle-oriented Society." ENVIRONMENTAL SYSTEMS RESEARCH 31 (2003): 343–49. http://dx.doi.org/10.2208/proer.31.343.

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YAMASAKI, Hiroki, Yugo YAMAMOTO, Noboru YOSHIDA, and Tohru MORIOKA. "ESTABLISHING AND APPLYING EVALUATION CRITERIA FOR PARTS-REUSABILITY OF ELECTRIC HOUSEHOLD APPLIANCES." ENVIRONMENTAL SYSTEMS RESEARCH 33 (2005): 267–73. http://dx.doi.org/10.2208/proer.33.267.

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Du, Shengli, Mingchao Li, Shuai Han, Jonathan Shi, and Heng Li. "Multi-Pattern Data Mining and Recognition of Primary Electric Appliances from Single Non-Intrusive Load Monitoring Data." Energies 12, no. 6 (March 14, 2019): 992. http://dx.doi.org/10.3390/en12060992.

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The electric power industry is an essential part of the energy industry as it strengthens the monitoring and control management of household electricity for the construction of an economic power system. In this paper, a non-intrusive affinity propagation (AP) clustering algorithm is improved according to the factor graph model and the belief propagation theory. The energy data of non-intrusive monitoring consists of the actual energy consumption data of each electronic appliance. The experimental results show that this improved algorithm identifies the basic and combined class of home appliances. According to the possibility of conversion between different classes, the combination of classes is broken down into different basic classes. This method provides the basis for power management companies to allocate electricity scientifically and rationally.

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Hu, Yu-Chen, Yu-Hsiu Lin, and Harinahalli Lokesh Gururaj. "Partitional Clustering-Hybridized Neuro-Fuzzy Classification Evolved through Parallel Evolutionary Computing and Applied to Energy Decomposition for Demand-Side Management in a Smart Home." Processes 9, no. 9 (August 29, 2021): 1539. http://dx.doi.org/10.3390/pr9091539.

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The key advantage of smart meters over rotating-disc meters is their ability to transmit electric energy consumption data to power utilities’ remote data centers. Besides enabling the automated collection of consumers’ electric energy consumption data for billing purposes, data gathered by smart meters and analyzed through Artificial Intelligence (AI) make the realization of consumer-centric use cases possible. A smart meter installed in a domestic sector of an electrical grid and used for the realization of consumer-centric use cases is located at the entry point of a household/building’s electrical grid connection and can gather composite/circuit-level electric energy consumption data. However, it is not able to decompose its measured circuit-level electric energy consumption into appliance-level electric energy consumption. In this research, we present an AI model, a neuro-fuzzy classifier integrated with partitional clustering and metaheuristically optimized through parallel-computing-accelerated evolutionary computing, that performs energy decomposition on smart meter data in residential demand-side management, where a publicly available UK-DALE (UK Domestic Appliance-Level Electricity) dataset is used to experimentally test the presented model to classify the On/Off status of monitored electrical appliances. As shown in this research, the presented AI model is effective at providing energy decomposition for domestic consumers. Further, energy decomposition can be provided for industrial as well as commercial consumers.

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Endres, Kirsten W. "Plugged into the Good Life: Living Electrically through the Ages in Urban Vietnam." positions 32, no. 1 (November 28, 2023): 27–47. http://dx.doi.org/10.1215/10679847-10889934.

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Abstract With Vietnam's countrywide electrification rate approaching 100 percent, electricity has become ever more indispensable and essential to the quality of everyday life. The steady upsurge in household electricity consumption over the past years has been driven by a growing technification of the domestic sphere. Modern households are increasingly equipped with a variety of electric appliances that not only provide convenience and comfort but also serve as markers of social distinction. This essay explores the history of domestic electrification and people's aspirations to live electrically in urban Vietnam, from the colonial era until today. Inspired by recent advances in the anthropology of electricity, it investigates the meanings that people have attributed to electric home appliances through the ages and asks if, how, and why some of these have come to define what it means to live a good life. In the current era, however, living electrically has also come to reflect a global sense of “cruel optimism” in which people become increasingly attached to certain understandings of what constitutes a good life that are unsustainable in the long run, and detrimental to their well-being.

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Teixeira, Cristiano André, Ana Paula Melo, Michele Fossati, and Roberto Lamberts. "Bottom-up modelling of electricity end-use consumption of the residential sector in Brazil." Ambiente Construído 22, no. 3 (September 2022): 113–31. http://dx.doi.org/10.1590/s1678-86212022000300611.

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Abstract Electricity consumption in the residential sector in Brazil has been increasing annually despite efforts to promote the energy efficiency of household appliances. One of the main goals for achieving more energy efficiency in dwellings is understanding its energy end uses. In this context, this paper presents a bottom-up model developed to analyse regional and national electricity end uses in the residential sector in Brazil based on a recent survey on Ownership of Appliances and Consumption Habits. The percentages of total electricity consumption associated with nine appliances (light bulbs, refrigerators, freezers, televisions, showers, microwaves, washing machines, fans, and air conditioners) were estimated. The values were obtained using the software EnergyPlus for air conditioners and electricity consumption equations for the other eight appliances. Results show that the proposed model gives reasonable estimates of electricity consumption, which were close to the values expected for most appliances. Regionally, the appliances for which ownership and pattern of use are influenced by the climate (electric showers, fans, and air conditioners) obtained the most significant variation in the percentage of electricity consumption.

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Codispoti, Jackson, Atieh R. Khamesi, Nelson Penn, Simone Silvestri, and Eura Shin. "Learning from Non-experts: An Interactive and Adaptive Learning Approach for Appliance Recognition in Smart Homes." ACM Transactions on Cyber-Physical Systems 6, no. 2 (April 30, 2022): 1–22. http://dx.doi.org/10.1145/3491241.

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With the acceleration of Information and Communication Technologies and the Internet-of-Things paradigm, smart residential environments , also known as smart homes , are becoming increasingly common. These environments have significant potential for the development of intelligent energy management systems and have therefore attracted significant attention from both academia and industry. An enabling building block for these systems is the ability of obtaining energy consumption at the appliance-level. This information is usually inferred from electric signals data (e.g., current) collected by a smart meter or a smart outlet, a problem known as appliance recognition . Several previous approaches for appliance recognition have proposed load disaggregation techniques for smart meter data. However, these approaches are often very inaccurate for low consumption and multi-state appliances. Recently, Machine Learning (ML) techniques have been proposed for appliance recognition. These approaches are mainly based on passive MLs, thus requiring pre-labeled data to be trained. This makes such approaches unable to rapidly adapt to the constantly changing availability and heterogeneity of appliances on the market. In a home setting scenario, it is natural to consider the involvement of users in the labeling process, as appliances’ electric signatures are collected. This type of learning falls into the category of Stream-based Active Learning (SAL). SAL has been mainly investigated assuming the presence of an expert , always available and willing to label the collected samples. Nevertheless, a home user may lack such availability, and in general present a more erratic and user-dependent behavior. In this article, we develop a SAL algorithm, called K -Active-Neighbors (KAN), for the problem of household appliance recognition. Differently from previous approaches, KAN jointly learns the user behavior and the appliance signatures. KAN dynamically adjusts the querying strategy to increase accuracy by considering the user availability as well as the quality of the collected signatures. Such quality is defined as a combination of informativeness , representativeness , and confidence score of the signature compared to the current knowledge. To test KAN versus state-of-the-art approaches, we use real appliance data collected by a low-cost Arduino-based smart outlet as well as the ECO smart home dataset. Furthermore, we use a real dataset to model user behavior. Results show that KAN is able to achieve high accuracy with minimal data, i.e., signatures of short length and collected at low frequency.

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Hirota, Izuo, Hidekazu Yamashita, Hideki Omori, and Mutsuo Nakaoka. "Historical Review of Electric Household Appliances using induction-Heating and Future Challenging Trends." IEEJ Transactions on Fundamentals and Materials 124, no. 8 (2004): 713–19. http://dx.doi.org/10.1541/ieejfms.124.713.

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Austin, Lydia. "Magnetic and electric field strengths of high voltage power lines and household appliances." Physics Education 32, no. 2 (March 1997): 108–10. http://dx.doi.org/10.1088/0031-9120/32/2/019.

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Sánchez-Jacob, Eduardo, Andrés González-García, Javier Mazorra, Pedro Ciller, Julio Lumbreras, and José Ignacio Pérez-Arriaga. "Joint Optimal Planning of Electricity and Modern Energy Cooking Services Access in Nyagatare." Energies 14, no. 14 (July 6, 2021): 4093. http://dx.doi.org/10.3390/en14144093.

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In 2019, there were 759 million people globally without access to electricity and 2.6 billion people lacked access to clean cooking. Cooking with electricity could contribute to achieving universal access to energy by 2030. This paper uses geospatially-based techniques—a computer model named REM, for Reference Electrification Model—to show the impact of integrating electric cooking into electrification planning. Three household scenarios were analyzed: one for providing basic electricity access with no electric cooking; another for cooking with electricity; and the third for cooking half of the meals with electricity and half with another fuel, with a clean stacking process. Results of the application of REM to the three scenarios were obtained for the Nyagatare District, Rwanda. The case study showed that electric cooking substantially changes the mix of technologies and the total cost of the least-cost electrification plan. It also showed that electric cooking can be cost competitive compared to LPG and charcoal in grid-connected households and can reduce greenhouse emissions. Stacking with energy-efficient electric appliances provides most of the benefits of full electric cooking at a lower cost and is a pathway worthy of further consideration.

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Shams Ashkezari, Leila, Marco Succetti, Rémi Jabœuf, Paolo Tosco, and Morris Brenna. "Are Commercial EV Chargers Ready to Aid with Household Power Consumption?" Electronics 12, no. 9 (April 29, 2023): 2065. http://dx.doi.org/10.3390/electronics12092065.

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The transportation industry now accounts for approximately a quarter of worldwide energy-related direct CO2 emissions, and governments all around the globe have committed to converting their fossil-fuel vehicles to zero-emission ones by adopting electric vehicles. Current electric vehicles (EV) can store approximately 18 to 100 kWh of energy, which may be employed not only for commuting but also for other purposes such as delivering energy to households (V2H) or buildings (V2B), as well as offering ancillary services to the power grid (V2G). In this study, a real test setting including a trending bidirectional charger, an EV, a PV simulator, and household appliances are utilized to evaluate the performance of various V2H components and to learn about the concerns that may arise during V2H operation. The results of the tests on the bidirectional EV charger are presented in this paper. Although the results of the tests on the charger installed in the house are not satisfactory and consistent to the project’s goal, they are released in order to aid future studies in better understanding the true challenges of commercial bidirectional chargers.

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Kim, Hyungbae, and Kyoung Duck Ryu. ""Design development of Small-sized household appliances using electric fan - Focused on Smart home service for single household"." Journal of Industrial Design Studies 48 (June 30, 2019): 1–10. http://dx.doi.org/10.37254/ids.2019.06.48.01.01.

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Journal articles on the topic 'Electric household appliances'

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