Relevant bibliographies by topics / Electricity appliances

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Electricity appliances'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Electricity appliances"

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Morvai, Peter, Miroslav Žitňák, and Stanislav Paulovič. "Rationalization of Electricity Consumption in Househ Olds." Acta Technologica Agriculturae 21, no. 2 (June 1, 2018): 69–74. http://dx.doi.org/10.2478/ata-2018-0013.

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Abstract With rationalization of electricity consumption, it is possible to obtain savings of electric energy in households, as well as financing and capital input for the electricity production. Rational use of appliances in the best operating modes can reduce the final consumption of electricity, representing a positive impact on improving the environment quality. The main objective of this paper was to measure the electricity consumption of appliances in various operating modes. The measured values from two energy suppliers were recorded and processed in tables and figures, from which we created a table of the financial costs necessary for operation of appliances in different modes. For the calculation of annual electricity consumption and electricity prices, an application allowing selection of individual products from suppliers with current electricity prices was designed. According to the tables of electricity prices, various modes of appliance operation allow the selection of the most preferred mode for appliance operation based on the lowest price, rational consumption and energy costs. The aim of the paper is to demonstrate the consumption and costs of operating appliances in certain operating modes, standby modes and their efficient use or functionally similar appliances for reduction of electricity consumption in households.
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Aqilah, Naja, Sheikh Ahmad Zaki Shaikh Salim, Aya Hagishima, Nelidya Md Yusoff, and Fitri Yakub. "Time series data measurement on electricity consumption for selected domestic appliances in typical terrace house of Malaysia." Bulletin of Electrical Engineering and Informatics 8, no. 3 (September 1, 2019): 1144–53. http://dx.doi.org/10.11591/eei.v8i3.1601.

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This paper describes the pattern of electricity consumption from total and selected domestic appliances at a typical terrace house in Malaysia. The measured appliances can be classified into four groups on the basis of pattern of use which are ‘standby’ (TV), ‘active’ (massage chair, charger of hand phone, laptop and power bank, washing machine, air-conditioners, iron, standing fan, shower heaters, rice cooker, toaster, microwave), ‘cold’ (refrigerator) and ‘cold and hot’ (water dispenser). The major contribution of monthly electricity consumption comes from ‘cold’ appliances that consume 118.8 kWh/month followed by ‘active’ appliances that consume 87.8 kWh/month and ‘cold and hot’ appliance with 52.5 kWh/month. ‘Standby’ appliances shown a small contribution to the total electricity with 0.9 kWh/month. The amount of energy consumed depends on time-of-use, power characteristics of particular appliances as well as occupancy period.
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Dzobo, O., and Y. Sun. "Optimal Power Control Strategy of a Hybrid Energy System Considering Demand Response Strategy and Customer Interruption Cost." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 12, no. 1 (January 10, 2019): 20–29. http://dx.doi.org/10.2174/2352096511666180312142859.

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Background: The integration of distributed renewable energy sources into the conventional power system network has created opportunities for electricity customers to reduce their electricity cost. This paper investigates the optimal power scheduling of a hybrid energy system connected to the grid in the presence of demand response strategy and inconvenience cost. Methods: A new proposed method of calculating the inconvenience cost which is dependent on total home appliance load, Customer Interruption Cost (CIC) and delay time operation of home appliances is proposed. The hybrid energy system consists of solar photovoltaic (PV) module and battery bank storage system. The home appliance scheduling is formulated as a non-convex mixed integer programming with a binary decision variable to switch ON/OFF the home appliances. The optimization objective is to minimize both the total daily electricity cost and inconvenience cost of a residential customer with different time-shiftable, power shiftable home appliances and customer time preference constraints. Results: The results show that it is important to schedule home appliances and include their inconvenience cost so that home appliances are not only shifted to the lower electricity tariff periods but can also start at their customer preferred operation times. Conclusion: The results also show that the hybrid energy system is able to cater for all the energy requirements of home appliances during the day, reducing power demand from the grid by a significant percentage and thus, relieve the power system network and afford electricity consumers significant monetary savings.
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Apaydin-Özkan, Hanife. "An Appliance Scheduling System for Residential Energy Management." Sensors 21, no. 9 (May 10, 2021): 3287. http://dx.doi.org/10.3390/s21093287.

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In this work, an Appliance Scheduling-based Residential Energy Management System (AS-REMS) for reducing electricity cost and avoiding peak demand while keeping user comfort is presented. In AS-REMS, based on the effects of starting times of appliances on user comfort and the user attendance during their operations, appliances are divided into two classes in terms of controllability: MC-controllable (allowed to be scheduled by the Main Controller) and user-controllable (allowed to be scheduled only by a user). Use of all appliances are monitored in the considered home for a while for recording users’ appliance usage preferences and habits on each day of the week. Then, for each MC-controllable appliance, preferred starting times are determined and prioritized according to the recorded user preferences on similar days. When scheduling, assigned priorities of starting times of these appliances are considered for maintaining user comfort, while the tariff rate is considered for reducing electricity cost. Moreover, expected power consumptions of user-controllable appliances corresponding to the recorded user habits and power consumptions of MC-controllable appliances corresponding to the assigned starting times are considered for avoiding peak demand. The corresponding scheduling problem is solved by Brute-Force Closest Pair method. AS-REMS reduces the peak demand levels by 45% and the electricity costs by 39.6%, while provides the highest level of user comfort by 88%. Thus, users’ appliance usage preferences are sustained at a lower cost while their comfort is kept impressively.
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Vardhan, Pola Adithya. "Automated Electricity Control." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 20, 2021): 1408–15. http://dx.doi.org/10.22214/ijraset.2021.35264.

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Automated Electricity control with Arduino is a circuit used to achieve three tasks I.e., 1) to accurately count the number of students in a room, 2) to display The total number of people in the room on the LCD 16X2 module, And 3) to automatically turn off the electric appliances in some regions in the room where no people are there, we divide the the room in to n number of regions ,when a person enters into region 1, then the appliances in those area only turned on , when he moves from this region to another region the appliances in the first region will turned off automatically, thus the regions in which people are present only uses the electricity the unnecessary wastage of electricity would be drastically decreased, this could be implemented in big shopping malls and function halls, seminar halls etc.. when everyone leaves the room all the electric appliances will be turned off automatically. The microcontroller performs the task and receives signals from sensors, and these sensors are controlled by software stored on the EEPROM of the Arduino. this project will help reduce energy losses. This project can be implemented in a wide range of applications , where the area of rooms are very big and the electric appliance are arranged every corner of the room which is contributing of lot of electricity wastage.for Example At my university, I discovered that the lights and fans turn on even when no one is in the room. To avoid all these situations, this project was developed. When everyone leaves the room, the counter is reset to zero, turning off all lights and fans. You can avoid proxy attendance by cross-checking with the counter.
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Shewale, Amit, Anil Mokhade, Nitesh Funde, and Neeraj Dhanraj Bokde. "An Overview of Demand Response in Smart Grid and Optimization Techniques for Efficient Residential Appliance Scheduling Problem." Energies 13, no. 16 (August 18, 2020): 4266. http://dx.doi.org/10.3390/en13164266.

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Smart grid (SG) is a next-generation grid which is responsible for changing the lifestyle of modern society. It avoids the shortcomings of traditional grids by incorporating new technologies in the existing grids. In this paper, we have presented SG in detail with its features, advantages, and architecture. The demand side management techniques used in smart grid are also presented. With the wide usage of domestic appliances in homes, the residential users need to optimize the appliance scheduling strategies. These strategies require the consumer’s flexibility and awareness. Optimization of the power demand for home appliances is a challenge faced by both utility and consumers, particularly during peak hours when the consumption of electricity is on the higher side. Therefore, utility companies have introduced various time-varying incentives and dynamic pricing schemes that provides different rates of electricity at different times depending on consumption. The residential appliance scheduling problem (RASP) is the problem of scheduling appliances at appropriate periods considering the pricing schemes. The objectives of RASP are to minimize electricity cost (EC) of users, minimize the peak-to-average ratio (PAR), and improve the user satisfaction (US) level by minimizing waiting times for the appliances. Various methods have been studied for energy management in residential sectors which encourage the users to schedule their appliances efficiently. This paper aims to give an overview of optimization techniques for residential appliance scheduling. The reviewed studies are classified into classical techniques, heuristic approaches, and meta-heuristic algorithms. Based on this overview, the future research directions are proposed.
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Ryu, Do-Hyeon, Ryu-Hee Kim, Seung-Hyun Choi, Kwang-Jae Kim, Young Myoung Ko, Young-Jin Kim, Minseok Song, and Dong Gu Choi. "Utilizing Electricity Consumption Data to Assess the Noise Discomfort Caused by Electrical Appliances between Neighbors: A Case Study of a Campus Apartment Building." Sustainability 12, no. 20 (October 20, 2020): 8704. http://dx.doi.org/10.3390/su12208704.

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Real-time collection of household electricity consumption data has been facilitated by an advanced metering infrastructure. In recent studies, collected data have been processed to provide information on household appliance usage. The noise caused by electrical appliances from neighboring households constitutes a major issue, which is related to discomfort and even mental diseases. The assessment of noise discomfort using electricity consumption data has not been dealt with in the literature up to this day. In this study, a method that utilizes electricity consumption data for the assessment of noise discomfort levels caused by electrical appliances between neighboring households is proposed. This method is based on the differences in the usage time of electrical appliances in a collective residential building. The proposed method includes the following four steps: data collection and preprocessing, residential units clustering, noise discomfort modeling, and evaluation of noise discomfort. This method is demonstrated through a case study of a campus apartment building. Variations in the noise discomfort assessment model and measures for alleviating noise discomfort are also discussed. The proposed method can guide the application of electricity consumption data to the assessment and alleviation of noise discomfort from home appliances at an apartment building.
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Sena, Boni, Sheikh Ahmad Zaki, Hom Bahadur Rijal, Jorge Alfredo Ardila-Rey, Nelidya Md Yusoff, Fitri Yakub, Mohammad Kholid Ridwan, and Firdaus Muhammad-Sukki. "Determinant Factors of Electricity Consumption for a Malaysian Household Based on a Field Survey." Sustainability 13, no. 2 (January 15, 2021): 818. http://dx.doi.org/10.3390/su13020818.

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Electricity-saving strategies are an essential solution to overcoming increasing global CO2 emission and electricity consumption problems; therefore, the determinant factors of electricity consumption in households need to be assessed. Most previous studies were conducted in developed countries of subtropical regions that had different household characteristic factors from those in developing countries of tropical regions. A field survey was conducted on electricity consumption for Malaysian households to investigate the factors affecting electricity consumption that focused on technology perspective (building and appliance characteristics) and socio-economic perspective (socio-demographics and occupant behaviour). To analyse the determinant factors of electricity consumption, direct and indirect questionnaire surveys were conducted from November 2017 to January 2018 among 214 university students. Direct questionnaire surveys were performed in order to obtain general information that is easily answered by respondents. On the other hand, some questions such as electricity consumption and detailed information of appliances must be confirmed by the respondents’ parents or other household members through an indirect questionnaire survey. The results from multiple linear regression analyses of the survey responses showed that appliance characteristic factors were the main variables influencing electricity consumption and house characteristics were the least significant. Specifically, air conditioners, fluorescent lamps, and flat-screen TVs emerged as appliances with the most significant effect on electricity consumption. Occupant behaviour factors had a more significant influence than socio-demographic factors. The findings in this study can be used by policymakers to develop electricity-saving strategies in Malaysia.
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Gopi Krishna, P., K. Sreenivasa Ravi, R. Trinadh, K. Chandra Sekhar, and V. Ranjit Kumar. "Design and development of smart energy meter for effective use of electricity in IoT applications." International Journal of Engineering & Technology 7, no. 2.8 (March 19, 2018): 115. http://dx.doi.org/10.14419/ijet.v7i2.8.10342.

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IoT (Internet of things) has delivered a venerable progression and advancements in the automation of home environments. The home automation has changed the manual frame work into robotization by making the household appliances smart which plays vital role now and more in the coming future. By connecting the household appliances to the internet for remote supervision and controlling. For better results home automation is employed with energy management strategy for better fallouts. Many energy management systems are available which are having expensive cost but are not efficient. By equipping the energy meters to home appliances, the amount of energy consumed can be calculated by each appliance. Enhanced facilities are provided to the user in this system. The remote user can monitor the electrical appliances, can turn ON and OFF through the web page. Webcam is employed in the proposed system for better functionality and to enhance the security so that remote user can observe the living home environment. A specific threshold values are specified to electrical appliances which reduces the power consumption in an effective way. The appliances will turn OFF automatically when it reaches to the specified threshold value. The implement system uses a Raspberry Pi 3 which realizes the data received form the remote users and the webcam. The data is uploaded into the web sever through Raspberry Pi which act as central server and visualization of data will be done the user in the website. The proposed and implemented system performs the monitoring and controlling of electrical appliance dynamically with low cost and efficiently which reduce the power consumption.
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Jamil, Aqib, Turki Ali Alghamdi, Zahoor Ali Khan, Sakeena Javaid, Abdul Haseeb, Zahid Wadud, and Nadeem Javaid. "An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory." Sustainability 11, no. 22 (November 8, 2019): 6287. http://dx.doi.org/10.3390/su11226287.

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The feature of bidirectional communication in a smart grid involves the interaction between consumer and utility for optimizing the energy consumption of the users. For optimal management of the energy at the end user, several demand side management techniques are implemented. This work proposes a home energy management system, where consumption of household appliances is optimized using a hybrid technique. This technique is developed from cuckoo search algorithm and earthworm algorithm. However, there is a problem in such home energy management systems, that is, an uncertain behavior of the user that can lead to force start or stop of an appliance, deteriorating the purpose of scheduling of appliances. In order to solve this issue, coordination among appliances for rescheduling is incorporated in home energy management system using game theory. The appliances of the home are categorized in three different groups and their electricity cost is computed through the real-time pricing signals. Optimization schemes are implemented and their performance is scrutinized with and without coordination among the appliances. Simulation outcomes display that our proposed technique has minimized the total electricity cost by 50.6% as compared to unscheduled cost. Moreover, coordination among appliances has helped in increasing the user comfort by reducing the waiting time of appliances. The Shapley value has outperformed the Nash equilibrium and zero sum by achieving the maximum reduction in waiting time of appliances.
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Dissertations / Theses on the topic "Electricity appliances"

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Mansouri-Azar, Iman. "Energy consumptions and environmental impacts of household electrical appliances." Thesis, Cranfield University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336522.

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Wijaya, Muhammad Ery. "Electricity Saving Policy for Household in a Multicultural Society-Indonesia." Kyoto University, 2013. http://hdl.handle.net/2433/180444.

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Richardson, Ian. "Integrated high-resolution modelling of domestic electricity demand and low voltage electricity distribution networks." Thesis, Loughborough University, 2011. https://dspace.lboro.ac.uk/2134/7968.

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Assessing the impact of domestic low-carbon technologies on the electricity distribution network requires a detailed insight into the operation of networks and the power demands of consumers. When used on a wide-scale, low-carbon technologies, including domestic scale micro-generation, heat pumps, electric vehicles and flexible demand, will change the nature of domestic electricity use. In providing a basis for the quantification of the impact upon distribution networks, this thesis details the construction and use of a high-resolution integrated model that simulates both existing domestic electricity use and low voltage distribution networks. Electricity demand is modelled at the level of individual household appliances and is based upon surveyed occupant time-use data. This approach results in a simulation that exhibits realistic time-variant demand characteristics, in both individual dwellings, as well as, groups of dwellings together. Validation is performed against real domestic electricity use data, measured for this purpose, from dwellings in Loughborough in the East Midlands, UK. The low voltage distribution network is modelled using real network data, and the output of its simulation is validated against measured network voltages and power demands. The integrated model provides a highly detailed insight into the operation of networks at a one-minute resolution. This integrated model is the main output of this research, alongside published articles and a freely downloadable software implementation of the demand model.
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Mihirig, Ali Mohamed. "Transient stability analysis of multimachine power systems by catastrophe theory." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/29022.

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Transient stability analysis is an important part of power system planning and operation. For large power systems, such analysis is very demanding in computation time. On-line transient stability assessment will be necessary for secure and reliable operation of power systems in the near future because systems are operated close to their maximum limits. In the last two decades, a vast amount of research work has been done in the area of fast transient stability assessment by direct methods. The major difficulties associated with direct methods are the limitations in the power system model, determination of transient stability regions and adaptation to changes in operating conditions. In this thesis catastrophe theory is used to determine the transient stability regions. Taylor series expansion is used to find the energy balance equation in terms of clearing time and system transient parameters. The energy function is then put in the form of a catastrophe manifold from which the bifurcation set is extracted. The bifurcation set represents the transient stability region in terms of the power system transient parameters bounded by the transient stability limits. The transient stability regions determined are valid for any changes in loading conditions and fault location. The transient stability problem is dealt with in the two dimensions of transient stability limits and critical clearing times. Transient stability limits are given by the bifurcation set and the critical clearing times are calculated from the catastrophe manifold equation. The method achieves a breakthrough in the modelling problem because the effects of exciter response, flux decay and systems damping can all be included in the transient stability analysis. Numerical examples of one-machine infinite-bus and multi-machine power systems show very good agreement with the time solution in the practical range of first swing stability analysis. The method presented fulfills all requirements for on-line assessment of transient stability of power systems.
Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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Jossen, Quentin. "Unsupervised learning procedure for nonintrusive appliance load monitoring." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209369.

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There is a continuously growing amount of appliances and energy dependent services in households. To date, efforts have mostly focused on energy efficiency, however behavior changes are required for a more sustainable energy consumption. People therefore need to understand their consumption habits to be able to adapt them. Appliance-specific feedback is probably the most efficient way to impact behaviors, since people need to ‘see’ where their electricity goes. Smart meters, currently being extensively rolled out in Europe and in the U.S. are good potential candidates to provide end-users with

energy advice. The required functionalities must however be rapidly defined if they are expected to be integrated in the future massive roll out.

Nonintrusive appliance load monitoring aims to derive appliance-specific information from the aggregate electricity consumption. While techniques have been developed since the 80’s, those mainly address the identification of previously learned appliances, from a database. Building such a database is an intrusive and tedious process which should be avoided. Whereas most recent efforts have focused on unsupervised techniques to disambiguate energy consumption into individual appliances, they usually rely on prior information about measured appliances such as the number of appliances, the number of states in each appliance as well as the power they consume in each state. This information should ideally be learned from the data. This topic will be addressed in the present research.

This work will present a framework for unsupervised learning for nonintrusive appliance

load monitoring. It aims to discover information about appliances of a household solely from its aggregate consumption data, with neither prior information nor user intervention. The learning process can be segmented into five tasks: the detection of on/off switching, the extraction of individual load signatures, the identification of

recurrent signatures, the discovery of two-state electrical devices and, finally, the elaboration

of appliance models. The first four steps will be addressed in this paper.

The suite of algorithms proposed in this work allows to discover the set of two-states electrical loads from their aggregated consumption. This, along with the evaluation

of their operating sequences, is a prerequisite to learn appliance models from the data. Results show that loads consuming power down to some dozens of watts can be learned from the data. This should encourage future researchers to consider such an unsupervised learning.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

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FAGUNDES, WESLEY DE CASTRO. "ESTIMATION OF THE LOAD FACTOR (LF) AND THE DEMAND FACTOR (DF) OF ELECTRICITY CONSUMERS VIA MEASUREMENTS AND ELECTRICAL APPLIANCES OWNERSHIP AND USAGE SURVEYS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2011. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=18618@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
O objetivo desta dissertação é apresentar os conceitos de Fator de Carga (FC) e Fator de Demanda (FD) e verificar o quanto estas informações estão atualizadas para uso pelas concessionárias de energia elétrica. A motivação pelo estudo resultou do fato de o conhecimento e o gerenciamento desses índices proporciorem maior eficiência e segurança às instalações e equipamentos, além de permitir redução do custo da energia elétrica. A metodologia utilizada para o cálculo se baseia nos testes de Chauvenet, que permite determinar se um valor amostral (resultante de uma medição) é anômalo (outlier) em relação aos restantes valores da amostra, supondo-se que esta amostra é retirada de uma distribuição normal. Dentre os principais resultados destacam-se estimativas do Fator de Carga e Fator de Demanda, típicos para os diversos segmentos de clientes de uma empresa de distribuição de energia elétrica. Para se obter essas estimativas foi realizada uma pesquisa de campo permitindo o levantamento da potência instalada em clientes atendidos na alta e na baixa tensão. Em paralelo à pesquisa de campo, a concessionária de energia elétrica realizou medições de consumo e demanda junto a esses clientes. Como conclusão o trabalho confirma que as distribuidoras de energia elétrica não possuem acesso a um cadastro atualizado da potência instalada de seus consumidores. Faz-se necessário uma atualização mais dinâmica nas bases de dados disponíveis o que permitiria uma estimativa mais precisa dos fatores de carga e de demanda.
The aim of this work discusses basic concepts associated with the load factor (LF) and demand factor (DF) and the adequacy of their use by electricity utilities. The knowledge and management of these electrical parameters is rather important, as they contribute for the improvement of the efficiency and security of the system as a whole while promoting reduction on energy costs. The method used to estimate these quantities is based on the Chauvenet statistical tests capable to detect and remove possible discontinuity on the sample data observed to follow normal distribution. The LD and DF were estimated for various clusters of similar clients of a given distributing utility. Estimations were obtained through a survey involving clients of the selected utility to capture information on the end-users and their nominal power demanded at both, the low and high voltage levels. In parallel to the survey, the utility measured and monitored the energy consumption of the clients participating in the study. As a conclusion, the study revealed that the electricity utilities do not have access to update information (stratified by segments of clients) on the electrical parameters. A dynamic scheme to make available updated information related to load factor and demand factor proved to be extremely useful and is highly recommended.
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Ihbal, Abdel-Baset M. I. "Investigation of Energy Demand Modeling and Management for Local Communities. Investigation of the electricity demand modeling and management including consumption behaviour, dynamic tariffs, and use of renewable energy." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/5678.

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Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.
Libyan government
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Ihbal, Abdel-Baset Mostafa Imbarek. "Investigation of energy demand modeling and management for local communities : investigation of the electricity demand modeling and management including consumption behaviour, dynamic tariffs, and use of renewable energy." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/5678.

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Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.
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Kossmann, de Menezes Anna Carolina. "Improving predictions of operational energy performance through better estimates of small power consumption." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/13549.

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This Engineering Doctorate aims to understand the factors that generate variability in small power consumption in commercial office buildings in order to generate more representative, building specific estimates of energy consumption. Current energy modelling practices in England are heavily focussed on simplified calculations for compliance with Building Regulations, which exclude numerous sources of energy use such as small power. When considered, estimates of small power consumption are often based on historic benchmarks, which fail to capture the significant variability of this end-use, as well as the dynamic nature of office environments. Six interrelated studies are presented in this thesis resulting in three contributions to existing theory and practice. The first contribution consists of new monitored data of energy consumption and power demand profiles for individual small power equipment in use in contemporary office buildings. These were used to inform a critical review of existing benchmarks widely used by designers in the UK. In addition, monthly and annual small power consumption data for different tenants occupying similar buildings demonstrated variations of up to 73%. The second contribution consists of a cross-disciplinary investigation into the factors influencing small power consumption. A study based on the Theory of Planned Behaviour demonstrated that perceived behavioural control may account for 17% of the variation in electricity use by different tenants. A subsequent monitoring study at the equipment level identified that user attitudes and actions may have a greater impact on variations in energy consumption than job requirements or computer specification alone. The third contribution consists of two predictive models for estimating small power demand and energy consumption in office buildings. Outputs from both models were validated and demonstrated a good correlation between predictions and monitored data. This research also led to the development and publication of industry guidance on how to stimate operational energy use at the design stage.
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Bažant, Zdeněk. "Rodinný dům - aktivní uzel ve Smart Grid." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220943.

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This thesis deals with issues of smart houses and smart buildings. In the first part there is a research of possible systems installed in smart house. Each system is described from the perspective of its function and importance .The second part is focused on energy demands and where there is described European standard EN 15232 (Energy demand of building – influence of control automation and house management). In the practical part there was created scheme with devices which can be equipped smart houses with and their separation according to their relation to electricity. Each device is characterized by its electrical and nonelectrical parameters typical for family houses. Next part is about the proposal of prediction model of electricity consumption and generation. There are also stated quantities needed for prediction model and then method for prediction model realization.
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Books on the topic "Electricity appliances"

1

Bryant-Mole, Karen. Electricity. Oxford: Heinemann, 1996.

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Group, Great Britain Defence Estate Organisation (Works) Industrial. Electricity: MOD electricity safety rules and procedures. London: The Stationery Office, 1996.

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Dineen, Jacqueline. Electricity. Austin, Tex: Raintree Steck-Vaughn, 1995.

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Ollerenshaw, Chris. Electricity. Milwaukee: Gareth Stevens Pub., 1994.

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Bryant-Mole, Karen. Electricity. Crystal Lake, IL: Rigby Interactive Library, 1997.

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Raitt, Gordon. Electricity 2: Electromagnetism. Cambridge [Cambridgeshire]: Cambridge University Press, 1987.

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Exhibiting electricity. London: Institution of Electrical Engineers, 1997.

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The story behind electricity. London: Heinemann Library, 2009.

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Ford, R. A. Homemade lightning: Creative experiments in electricity. 3rd ed. New York: McGraw-Hill, 2002.

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Ford, R. A. Homemade lightning: Creative experiments in electricity. 2nd ed. New York: TAB Books, 1996.

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Book chapters on the topic "Electricity appliances"

1

Nakagami, Hidetoshi, Akio Tanaka, Chiharu Murakoshi, and Barbara Litt. "Stand-by Electricity Consumption in Japanese Houses." In Energy Efficiency in Household Appliances, 353–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60020-3_42.

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Nørgård, J. S., and A. Gydesen. "Energy Efficient Domestic Appliances — Analyses and Field Tests." In Integrated Electricity Resource Planning, 245–60. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1054-9_15.

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Abbate, G. P. "Technology Developments in Home Appliances." In Demand-Side Management and Electricity End-Use Efficiency, 435–48. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1403-2_27.

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Meier, Alan, and Wolfgang Huber. "Results from the investigations on leaking electricity in the USA." In Energy Efficiency in Household Appliances, 342–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60020-3_41.

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Sidler, Olivier. "End Use Measurement Campaigns of Electricity Specific Uses in the Residential Sector." In Energy Efficiency in Household Appliances, 158–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60020-3_20.

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Lipp, Judith. "The UK’S Green Electricity Market: Is it Sprouting?" In Energy Efficiency in Household Appliances and Lighting, 709–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56531-1_75.

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Procházka, Vladimír. "Household Electricity Consumption in the Czech Republic and Effective Ways to Influence it." In Energy Efficiency in Household Appliances, 447–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60020-3_53.

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Anglade, A., D. Beyrand, G. Burle, and J. Roturier. "In-House Measurements of the Electricity Consumption of Home Entertainment Appliances: the CEMEDA Collaboration." In Energy Efficiency in Household Appliances, 332–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60020-3_40.

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Predescu, Laurentia, and Oana Popescu. "Changing the Electricity Customer Mentality, Under Energy Market Liberalisation Circumstances." In Energy Efficiency in Household Appliances and Lighting, 498–507. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56531-1_55.

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Suozzo, Margaret, and Jennifer Thorne. "Leaking Electricity in the U.S.: Standby and Off-Mode Power Consumption in Consumer Electronics and Household Appliances." In Energy Efficiency in Household Appliances, 623–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60020-3_75.

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Conference papers on the topic "Electricity appliances"

1

Wang, Zhe, and Yang Li. "Electricity Forecasting Service for Appliances(EFSA)." In 2015 IEEE Student Conference on Research and Development (SCOReD). IEEE, 2015. http://dx.doi.org/10.1109/scored.2015.7449302.

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Ishii, Kentaro, Youichi Kamiyama, Wirawit Chaochaisit, Masahiko Inami, and Takeo Igarashi. "Delivering electricity to home appliances by mobile robots." In 2014 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2014. http://dx.doi.org/10.1109/icra.2014.6907800.

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Toader, Cornel, Petre Postolache, Nicolae Golovanov, Radu Porumb, Ion Mircea, and Paul-Mihai Mircea. "Power quality impact of energy-efficient electric domestic appliances." In 2014 International Conference on Applied and Theoretical Electricity (ICATE). IEEE, 2014. http://dx.doi.org/10.1109/icate.2014.6972627.

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Ellegård, Kajsa, Joakim Widen, and Katerina Vrotsou. "Appliances Facilitating Everyday Life - Electricity Use Derived from Daily Activities." In World Renewable Energy Congress – Sweden, 8–13 May, 2011, Linköping, Sweden. Linköping University Electronic Press, 2011. http://dx.doi.org/10.3384/ecp110571031.

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Paajanen, P., T. Kaipia, and J. Partanen. "DC supply of low-voltage electricity appliances in residential buildings." In 20th International Conference and Exhibition on Electricity Distribution (CIRED 2009). IET, 2009. http://dx.doi.org/10.1049/cp.2009.0925.

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Seljeseth, H., K. Sand, and K. E. Fossen. "Laboratory tests of electrical appliances immunity to voltage swells." In 20th International Conference and Exhibition on Electricity Distribution (CIRED 2009). IET, 2009. http://dx.doi.org/10.1049/cp.2009.0980.

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Chilukuri, M. V., Ming Yong Lee, and Yoke Yin Phang. "Voltage sag sensitivity of home appliances and office equipment." In 20th International Conference and Exhibition on Electricity Distribution (CIRED 2009). IET, 2009. http://dx.doi.org/10.1049/cp.2009.1096.

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Englert, Frank, Patrick Lieser, Alaa Alhamoud, Doreen Boehnstedt, and Ralf Steinmetz. "Electricity-Metering in a Connected World: Virtual Sensors for Estimating the Electricity Consumption of IoT Appliances." In 2015 3rd International Conference on Future Internet of Things and Cloud (FiCloud). IEEE, 2015. http://dx.doi.org/10.1109/ficloud.2015.38.

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Qi, Bing, Xiao-feng Zhang, Miao-xin Wang, and Dong-dong Wang. "Design of information interaction interface between electrical home appliances and smart grid." In 2012 China International Conference on Electricity Distribution (CICED). IEEE, 2012. http://dx.doi.org/10.1109/ciced.2012.6508646.

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Kardaras, G., A. Rossello-Busquet, V. B. Iversen, J. Soler, and L. Dittmann. "Regulating electricity demand peaks for home appliances using reversible fair scheduling." In 2010 IEEE 4th International Conference on Internet Multimedia Services Architecture and Application (IMSAA). IEEE, 2010. http://dx.doi.org/10.1109/imsaa.2010.5729405.

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Reports on the topic "Electricity appliances"

1

Leventis, Greg, Anand Gopal, Stephane de la Rue du Can, and Amol Phadke. Avoided electricity subsidy payments can finance substantial appliance efficiency incentive programs: Case study of Mexico. Office of Scientific and Technical Information (OSTI), March 2013. http://dx.doi.org/10.2172/1171613.

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