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Relevant bibliographies by topics / Electrical energy usage

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Academic literature on the topic 'Electrical energy usage'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 May 2022

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Journal articles on the topic "Electrical energy usage"

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J. W. Slocombe, A. M. Feyerherm, and L. E. Stetson. "Electrical Energy Usage on Kansas Grain Farms." Applied Engineering in Agriculture 8, no. 2 (1992): 263–66. http://dx.doi.org/10.13031/2013.26063.

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Thoma, Mark. "Electrical energy usage over the business cycle." Energy Economics 26, no. 3 (May 2004): 463–85. http://dx.doi.org/10.1016/j.eneco.2004.04.006.

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Ritchie, Michael J., Jacobus A. A. Engelbrecht, and Marthinus J. Booysen. "Practically-Achievable Energy Savings with the Optimal Control of Stratified Water Heaters with Predicted Usage." Energies 14, no. 7 (April 1, 2021): 1963. http://dx.doi.org/10.3390/en14071963.

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Residential water heaters use a substantial amount of electrical energy and contribute to 25% of the energy usage in the residential sector. This raises concern for users in countries with flat rate electricity fees and where fossil fuels are used for electricity generation. Demand side management of tanked water heaters is well suited for energy-focused load reduction strategies. We propose a strategy for providing an electric water heater (EWH) with the optimal temperature planning to reduce the overall electrical energy usage while satisfying the comfort of the user. A probabilistic hot water usage model is used to predict the hot water usage behaviour for the A*-based optimisation algorithm, which accounts for water stratification in the tank. A temperature feedback controller with novel temperature and energy-correcting capabilities provides robustness to prediction errors. Three optimal control strategies are presented and compared to a baseline strategy with the thermostat always on: The first ensures temperature-matched water usages, the second ensures energy-matched water usages, and the third is a variation of the second that provides Legionella prevention. Results were obtained for 77 water heaters, each one simulated for four weeks. The median energy savings for predicted usage were 2.2% for the temperature-matched strategy, and 9.6% for both of the energy-matched strategies. We also compare the practical energy savings to the ideal scenario where the optimal scheduling has perfect foreknowledge of hot water usages, and the temperature and energy-matched strategies had a 4.1 and 11.0 percentage point decrease from the ideal energy savings.

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Hashim, Noorazuan Md, Muhammad Khaidir Bin Azmi, and Yaakob Mohd Jani. "Understanding Trend and Variation of Electrical Energy usage Among Students in the National University of Malaysia." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 31–35. http://dx.doi.org/10.31142/ijtsrd21586.

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Muyunda, C., and F. Mwale. "Electrical energy usage at Konkola Division, Zambian Copper Belt." Mine Water and the Environment 13, no. 2 (June 1994): 33–39. http://dx.doi.org/10.1007/bf02915538.

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Ruli A. Siregar, Riki, Hengki Sikumbang, Iriansyah BM Sangadji, and Indrianto. "KWh Meter Smart Card Model Token For Electrical Energy Monitoring." MATEC Web of Conferences 218 (2018): 03002. http://dx.doi.org/10.1051/matecconf/201821803002.

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This research Producer Electric meter Appliance model base on smart card kWh (kilo Watt hour). The card power meter Is use to calculate the prepaid electricity meter using the 20-digit voucher number as a charging medium. Utilizing a smart card, the token number in the prepaid electricity meter can help reduce the error rate when entering the token number, the model destination is created. Hardware design and with apps to detect how much energy is used to store basic data to help view history of usage. Using smart cards and microcontrollers in apps that come from a usage history in the Pulse usage category will help users know their usage in efficient, normal, and wasteful categories. The results of this research is a meter model with credit card for charging pulses, and data processing applications as devices that can be used for various electricity consumption. The information system is used as a model validation with pulse input that provides information about the use of electrical energy and as a determinant to save the time and time required to make optimal energy

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Herpendi, Herpendi, Veri Julianto, Khairul Anwar Hafizd, and Rabini Sayyidati. "IOT Based Smart Lamp for Efficient Usage of Electrical Energy." Logic : Jurnal Rancang Bangun dan Teknologi 19, no. 2 (July 29, 2019): 54. http://dx.doi.org/10.31940/logic.v19i2.1277.

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The government is proclaiming the electrical energy saving campaign in order to raise the people’s awareness of its importance. The Ministry of Energy and Mineral Resources (ESDM Ministry) of the Republic of Indonesia stated that a year of energy saving equals to the amount of saving Rp43.000.000.000.000,00 (forty three trillion rupiah) of money, which is also equal to a construction of electric steam power plant with the capacity of 3.500 megawatts (MW). One of the programs that has been encouraged by the government is the 'turn off the light' campaign. Turning off lights is a simple but often neglected thing. Apart from the limited awareness to save the energy for a better future, people are often too busy to do it. In 2015, Taruna built an Arduino Micro-controller based light control system using Android smartphone to provide ease, specifically for physically disabled and elderly. The shortcomings of this system are that the lights cannot be turned on and off automatically (smart) with timer and it can only be controlled at close range (bluetooth). Development of technology with the internet guide can easily help human, and thus, this research aims to improve the system with the time control (timer) and close range control (bluetooth) as well as the long range using SMS and internet. The system is built with the prototype model that incude the communication, fast planning, fast prototype designing and building, system submission and feedback. The result of this system building is that the light can be controlled using bluetooth and also provide a faster response time; less than a second (as well as the timer). The light can also be controlled from a long range using the internet connection, giving a response time between 14 to 17 seconds. When a light control command occurs, the SMS notification is sent to the cell phone of the user. Using this system, the light can be controlled correctly in order to conveniently give the user effectivity and efficiency in electrical energy usage.

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Asri, Yessy, Dwina Kuswardani, Efy Yosrita, and Ferdinand Hendrik Wullur. "Clusterization of customer energy usage to detect power shrinkage in an effort to increase the efficiency of electric energy consumption." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (April 1, 2021): 10. http://dx.doi.org/10.11591/ijeecs.v22.i1.pp10-17.

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<span>Automatic meter reading (AMR) is a reading system result the measurement of electrical energy consumen, both locally and remotely. The problems faced is the high non-technical shrinkage of AMR customers due to installation, maintenance errors as well as dishonest actions some consumers, this has a major influence on electrical power losses. PT. PLN Disjaya currently faces difficulties having to choose which customers should be checked first, so the field can only find a little damage. The K-means method based on historical electric power usage and determine the most optimal number of groups the davies-bouldin index (DBI) method. Based on the results of testing with 2-6 sets of clusters, the cluster set results are the most optimal is set cluster 4 because it has the smallest DBI value 0.893. The set of 4 clusters has the best performance in data grouping of historical power usage of AMR customers the business class, each centroid of each cluster is used as an attribute and value of the AMR customer power usage business chart. The testing phase is customers who categorized as customers with un-normal usage electricity power. The test is, by determining the distance data testing each centroid in the cluster 4 set.</span>

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D.A., Darshan, Sumith L.V., K. Sowjanya Reddy, K. Rasagnya, and Trupti V. N. "A STUDY OF ENERGY FLOW AT AN ELECTRICAL SUBSTATION THROUGH ENERGY AUDIT." International Journal of Research -GRANTHAALAYAH 5, no. 4RACEEE (April 30, 2017): 161–65. http://dx.doi.org/10.29121/granthaalayah.v5.i4raceee.2017.3339.

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This paper deals with the study of energy flow in a 220/ 66 kV substation. This study emphasizes on energy conservation by reducing power losses. Saving energy is the primary and overwhelming motivating factor for making energy improvements. Energy conservation can increase the environmental quality and higher the savings. Energy conservation lowers the energy costs by preventing future resource depletion (renewable energy source). Utilizing the electric power in the proper manner without wastage is the most important thing to consider. The main objectives are accumulating data at various energy points, identifying energy losses and critical junctions, enabling energy conservation and cost savings. Planning the use of electrical power in the most judicious way such that the usage as well as its wastage is minimized. For this purpose a energy management technique called energy audit is adopted. Energy auditing is required to determine the energy flows through various electrical installations such as feeders, transformers, substations in an electrical network system.

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Limpraptono, Fransiscus Yudi, Eko Nurcahyo, Mochammad Ibrahim Ashari, Erkata Yandri, and Yahya Jani. "Design of Power Monitoring and Electrical Control Systems to Support Energy Conservation." Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences 58, S (October 11, 2021): 1–7. http://dx.doi.org/10.53560/ppasa(58-sp1)726.

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The increasing demand for electrical energy and the decreasing supply of fossil fuels in recent years have increased the cost of electrical energy. So that the culture of saving electrical energy is a habit that must be cultivated in the community. On the other hand, energy-saving behavior cannot be realized massively without a support system that can control energy use. With these concerns, it is necessary to develop a method that encourages a culture of saving electrical energy. This paper proposes a system that supports active energy efficiency methods that can support an energy-efficient culture. This system is an electric power monitoring system that is integrated with a smart electrical panel that continuously monitors the use of electrical energy and can control electrical loads automatically, record electricity usage, provide comprehensive reports and analyze energy usage. The method used to carry out this research is research and development. This research has produced a prototype of electrical power control and monitoring system that has a smart panel based on a raspberry PI 3 and PZEM-004t power energy meter. The monitoring system performs and executes automatic control of electrical loads. The system can also provide reports in the form of data monitoring in daily, weekly, monthly or annual period. From the test results, it can be concluded that the system can work well. This research is expected to contribute to providing a system that can support government efforts in saving energy.

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Dissertations / Theses on the topic "Electrical energy usage"

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Kournetas, Nicholas George. "The use of oxygen to decrease electrical energy usage in the electric arc furnace." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0003/MQ34148.pdf.

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Chanda, Soumendu. "Powertrain Sizing and Energy Usage Adaptation Strategy for Plug-in Hybrid Electric Vehicles." University of Akron / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=akron1208385855.

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Johansson, Kevin, and Christoffer Eklund. "A comparison of energy usage between LoRa 433Mhz and LoRa 868MHz." Thesis, Jönköping University, JTH, Avdelningen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-54161.

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The number of devices connected to the internet is constantly increasing and therefore putting more weight on the importance of low energy usage. LoRa which is the physical part of the LoRaWAN communication protocol that this paper focuses on is popular in the area of IoT because of its low energy usage. The purpose of this paper was to find out how the energy usage differentiate between two of the most commonly used LoRa frequencies 433MHz and 868MHz. LoRa is often used with battery driven components within IoT such as temperature or humidity sensors. It is of great importance to keep the maintenance cost for these devices to a minimum. And it is therefore important to find the most energy efficient solutions for communication between LoRa components. To get an answer from the purpose of this paper, two questions were formulated, and they were in turn answered by using an experimental research method. For the experiment, two devices were set up using: one transmitter combined with a current sensor and one receiver, both of which were capable of using either LoRa 433MHz or 868MHz. The experiment was then conducted by transmitting 1000 packages for every DR and both of the frequencies. The results were analysed in an empirical quantitative way which showed that the higher frequency of 868MHz consumed more energy in all of the experiments. One discovery that was quite interesting was that the difference could be mitigated by using different data rates. The result in this paper is intended to increase the knowledge regarding LoRa and its energy usage. This papers result can be used as a reference when choosing between what frequency and data rate to use when working with LoRa.

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Chenailler, Hervé. "L'efficacité d'usage énergétique : pour une meilleure gestion de l'énergie électrique intégrant l'usager dans les bâtiments." Phd thesis, Université de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00771667.

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La consommation énergétique, et en particulier électrique, des bâtiments est grandement influencée par le comportement de ses usagers. L'analyse de l'usage électrique au travers d'un retour d'expérience réalisé sur une plateforme bâtiment-test nous a permis d'identifier qu'il pouvait exister différentes formes de satisfactions des usagers remettant en question la notion même d'efficacité énergétique d'un bâtiment. Afin de pouvoir intégrer l'acteur humain dans la conception de systèmes complexes bâtiment, nous proposons de définir la notion d'efficacité énergétique d'usage (EUE). Cette notion repose en particulier sur la satisfaction des usagers vis à vis d'un service que l'on a pu décomposer et quantifier au travers de fonctions de satisfaction rationnelles et sensibles. Le but de cette proposition est la construction d'un diagramme de compromis Coût / Satisfaction qui se positionne à la fois comme un outil effectif d'aide à la décision pour la conception de systèmes énergétiques du bâtiment intégrant l'usager et comme outil d'aide à la sobriété énergétique.

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Катюха, Ігор Анатолійович. "Прогнозні моделі електричних навантажень розподільчих мереж в умовах невизначеності вихідної інформації." Thesis, Таврійський державний агротехнологічний університет, 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/31033.

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Дисертація на здобуття наукового ступеня кандидата технічних наук за спеціальністю 05.14.02 «Електричні станції, мережі і системи» (141 Електроенергетика, електротехніка та електромеханіка). – Таврійський державний агротехнологічний університет МОН України, Мелітополь. – Національний технічний університет «Харківський політехнічний інститут» МОН України, Харків, 2017. Дисертаційна робота присвячена розв’язанню актуальної науково- прикладної задачі розроблення сучасного науково- методичного апарату прогнозу споживання електричної енергії в умовах невизначеності, що враховує можливості інформаційного забезпечення автоматизованих систем комерційного обліку електроенергії та особливості окремих споживачів і має на меті підвищення ефективності використання та збереження електричної енергії. Вдосконалено метод нечіткого регресійного аналізу для побудови довгострокових прогнозних моделей електричних навантажень в розподільчих мережах. Враховано паритетну участь двох критеріїв ефективності нечітких моделей: ступіня сумісності та ступіня нечіткості при побудові прогнозних моделей. Розроблено метод корекції довгострокових прогнозних моделей для короткострокового прогнозу. Запропоновано підхід до побудови виду прогнозних моделей при будь-яких типах навантажень. Аналітично встановлено зв'язок нечітких показників точності прогнозу з відносною середньомодульною похибкою. Розроблену методику апробовано при розробці прогнозних моделей електричного навантаження ряду споживачів з різними типами графіків навантаження. Основні результати дисертації знайшли практичне застосування у вигляді програмно-апаратного комплексу для автоматизації процесу довгострокового та II оперативного прогнозування електричних навантажень електроспоживачів, що може інтегруватись інформаційно в автоматизовану систему обліку електроенергії, а також при оперативному керуванні режимами розподільчих мереж. Внаслідок проведення дослідження за темою дисертаційної роботи одержані такі наукові результати: – удосконалено метод отримання прогнозних моделей електричних навантажень, який відрізняється шляхом побудови критерію ступеню сумісності нечіткої регресії на основі перетину нечітких чисел, який дає можливість розкрити невизначеність вихідних даних та підвищити якість прогнозу електричних навантажень. – вперше запропоновано метод уніфікації виду прогнозних моделей, який відрізняється тим, що в добовому графіку електроспоживання виділено функціональні ділянки, з роздільним використанням для них нечіткого регресійного аналізу, завдяки чому можна отримати вид прогнозних моделей при будь-яких навантаженнях. – вперше запропоновано метод підвищення адекватності моделей, отриманих на базі нечіткого регресійного аналізу, який відрізняється паритетним врахуванням ступеню сумісності та ступеню нечіткості опису, що дозволить зробити прогноз електричних навантажень більш якісним. – вперше аналітично визначено метод визначення ефективності прогнозу електроспоживання в електричних мережах, який дозволяє виконувати порівняльний аналіз нечітких регресійних моделей прогнозу з моделями, отриманими іншими методами. Практичне значення одержаних результатів для електроенергетичної галузі полягає в розробленій методики прогнозування електроспоживання на базі нечіткого регресійного аналізу, що включає принципи побудови прогнозних моделей, алгоритмічне забезпечення, а також програмне забезпечення, реалізоване у зручній для інтегрування в АСКОЕ формі. Результати досліджень впроваджені та підтверджені відповідними актами: III – ПП «Молокозавод-ОЛКОМ» щодо аналізу електроспоживання та оперативного керування з метою зменшення втрат енергії в мережі внутрішньозаводського електропостачання . – у навчальному процесі основні результати роботи включені у відповідні дисципліни – «Практична інженерна підготовка» та «Інженерна діяльність» за спеціальністю: 8.10010101 – Енергетика сільськогосподарського виробництва. – Приазовським РЕМ ВАТ «Запоріжжяобленерго» використаний апаратно-програмний комплекс для процесу довгострокового та короткострокового прогнозування електричних навантажень та оперативного керування режимами розподільчих мереж. Основні наукові положення за матеріалами дисертаційної роботи опубліковані у 15 друкованих працях, з них: 9 статей у наукових фахових виданнях України (5 – у виданнях, включених до міжнародних наукометричних баз, 1 ¬– у виданні з індексом SCORUS), 6 – у матеріалах конференцій та семінарів. Дисертаційна робота складається зі вступу, анотації, чотирьох розділів,ї висновків, списку використаних джерел та додатків. Загальний обсяг дисертації складає 190 стор., серед них: 18 рисунки по тексту, 20 таблиць по тексту, список використаних джерел містить 115 найменувань на 12 сторінках, додатки на 19 сторінках.
The thesis for getting scientific degree of the Candidate of technical science on the specialty 05.14.02 «Electric power stations, network and system» (141 Electrical energetics, electrical engineering and electromechanics). – Tavricheskiy State Agrotechnology University, Melitopol, Ukraine National Technical University «Kharkiv Polytechnic Institute» MES of Ukraine, Kharkiv, 2017. The dissertation devoted to solving actual scientific and technical problem of development of modern science and analytical tools forecast electricity consumption in the face of uncertainty, taking into account the possibility of information support automated systems of commercial accounting of electric power and features of individual consumers and aims to increase efficiency and save electricity. Improved method of fuzzy regression analysis to build long–term forecasting models of electric loads in distribution networks. Included balanced participation of two performance criteria fuzzy models: the degree of combination and degree of fuzziness when building predictive models. The method of correction term predictive models for short–term forecast. An approach to building the type of predictive models in any type of stress. Analytical contacted fuzzy indicators forecast accuracy Mean absolute percentage error. The technique was tested in the development of predictive models of electric load number of consumers with different types of load charts. The main results of the dissertation found practical application in the form of hardware and software to automate the process of long–term and operational forecasting electricity consumers of electrical loads that can integrate information into an automated accounting system of electricity, as well as operational management mode of distribution networks. VII As a result of the research on the theme of the thesis, the following scientific results were obtained: - the method for obtaining predictive models of electrical loads is improved, which is distinguished by constructing a fuzzy regression compatibility criterion based on the intersection of fuzzy numbers, which makes it possible to uncover the uncertainty of the output data and improve the quality of the prediction of electrical loads. - for the first time the method of unification of the type of forecasting models is proposed, which differs in the fact that in the daily schedule of electricity consumption allocated functional areas, with the separate use for them of fuzzy regression analysis, which allows you to get the kind of forecast models at all loads. - for the first time the method of increasing the adequacy of models obtained on the basis of fuzzy regression analysis, which differs from the parity considering the degree of compatibility and the degree of fuzzy description, which will make prediction of electrical loads more qualitative. - for the first time an analytical method for determining the efficiency of the forecast of electricity consumption in electric networks is determined, which allows to perform a comparative analysis of fuzzy regression models of the forecast with models obtained by other methods. The practical significance of the obtained results of work for the electric power industrylies in the developed method of forecasting electricity consumption based on fuzzy regression analysis, which includes the principles of constructing predictive models, algorithmic support, as well as software implemented in a convenient for integration in AMSCA form. The research results are implemented and confirmed by the relevant acts: - PE "Molokozavod-OLKOM" for the analysis of electricity consumption and operational control in order to reduce energy losses in the network of intra-electric power supply. VIII - in the educational process, the main results of the work are included in the relevant disciplines - "Practical engineering training" and "Engineering activities" in the specialty: 8.10010101 - Power engineering of agricultural production. - Azov REM OJSC "Zaporizhiaoblenergo" used a hardware and software complex for the process of long-term and short-term prediction of electrical loads and operational control of the modes of distribution networks. The basic scientific positions on the materials of the dissertation work are published in 15 printed works, including 9 articles in the scientific professional editions of Ukraine (5 in the publications included in the international science-computer bases, 1 ¬ in the edition with the index SCORUS), 6 in the materials of the conferences and workshops. Thesis consists of introduction, abstract, four sections, conclusions, list of used sources and applications. The total volume of the dissertation is 190 pages, among them: 18 figures in the text, 20 tables in the text, the list of used sources contains 115 titles in 12 pages, applications in 19 pages.

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Катюха, Ігор Анатолійович. "Прогнозні моделі електричних навантажень розподільчих мереж в умовах невизначеності вихідної інформації." Thesis, НТУ "ХПІ", 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/31032.

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Дисертація на здобуття наукового ступеня кандидата технічних наук за спеціальністю 05.14.02 – електричні станції, системи та мережі. – Таврійський державний агротехнологічний університет, Мелітополь, 2017. Дисертаційна робота присвячена розв’язанню актуальної науково-прикладної задачі розроблення сучасного науково-методичного апарату прогнозу споживання електричної енергії в умовах невизначеності, що враховує можливості інформаційного забезпечення автоматизованих систем комерційного обліку електроенергії та особливості окремих споживачів і має на меті підвищення ефективності використання та збереженняелектричної енергії. Вдосконалено метод нечіткого регресійного аналізу для побудови довгострокових прогнозних моделей електричних навантажень в розподільчих мережах. Враховано паритетну участь двох критеріїв ефективності нечітких моделей: степені суміщення та степені нечіткості при побудові прогнозних моделей. Розроблено метод корекції довгострокових прогнозних моделей для короткострокового прогнозу. Запропоновано підхід до побудови виду прогнозних моделей при будь-яких типах навантажень. Аналітично встановлено зв'язок нечітких показників точності прогнозу з відносною середньомодульною похибкою. Розроблену методику апробовано при розробці прогнозних моделей електричного навантаження ряду споживачів з різними типами графіків навантаження. Основні результати дисертації знайшли практичне застосування у вигляді програмно-апаратного комплексу для автоматизації процесу довгострокового та оперативного прогнозування електричних навантажень електроспоживачів, що може інтегруватись інформаційно в автоматизовану систему обліку електроенергії, а також при оперативному керуванні режимами розподільчих мереж.
Dissertation for scientific degree of candidate of technical sciences, specialty 05.14.02 – electric power stations, networks and systems. – Tavricheskiy State Agrotechnology University, Melitopol, 2017. The dissertation devoted to solving actual scientific and technical problem of development of modern science and analytical tools forecast electricity consumption in the face of uncertainty, taking into account the possibility of information support automated systems of commercial accounting of electric power and features of individual consumers and aims to increase efficiency and save electricity. Improved method of fuzzy regression analysis to build long–term forecasting models of electric loads in distribution networks. Included balanced participation of two performance criteria fuzzy models: the degree of combination and degree of fuzziness when building predictive models. The method of correction term predictive models for short–term forecast. An approach to building the type of predictive models in any type of stress. Analytical contacted fuzzy indicators forecast accuracy Mean absolute percentage error. The technique was tested in the development of predictive models of electric load number of consumers with different types of load charts. The main results of the dissertation found practical application in the form of hardware and software to automate the process of long–term and operational forecasting electricity consumers of electrical loads that can integrate information into an automated accounting system of electricity, as well as operational management mode of distribution networks.

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Guo, Feng. "Integrating Retired Electric Vehicle Batteries with Photovoltaics in Microgrids." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1408969201.

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Lu, Bin. "Energy Usage Evaluation and Condition Monitoring for Electric Machines using Wireless Sensor Networks." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14152.

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Energy usage evaluation and condition monitoring for electric machines are important in industry for overall energy savings. Traditionally these functions are realized only for large motors in wired systems formed by communication cables and various types of sensors. The unique characteristics of the wireless sensor networks (WSN) make them the ideal wireless structure for low-cost energy management in industrial plants. This work focuses on developing nonintrusive motor-efficiency-estimation methods, which are essential in the wireless motor-energy-management systems in a WSN architecture that is capable of improving overall energy savings in U.S. industry. This work starts with an investigation of existing motor-efficiency-evaluation methods. Based on the findings, a general approach of developing nonintrusive efficiency-estimation methods is proposed, incorporating sensorless rotor-speed detection, stator-resistance estimation, and loss estimation techniques. Following this approach, two new methods are proposed for estimating the efficiencies of in-service induction motors, using air-gap torque estimation and a modified induction motor equivalent circuit, respectively. The experimental results show that both methods achieve accurate efficiency estimates within ¡À2-3% errors under normal load conditions, using only a few cycles of input voltages and currents. The analytical results obtained from error analysis agree well with the experimental results. Using the proposed efficiency-estimation methods, a closed-loop motor-energy-management scheme for industrial plants with a WSN architecture is proposed. Besides the energy-usage-evaluation algorithms, this scheme also incorporates various sensorless current-based motor-condition-monitoring algorithms. A uniform data interface is defined to seamlessly integrate these energy-evaluation and condition-monitoring algorithms. Prototype wireless sensor devices are designed and implemented to satisfy the specific needs of motor energy management. A WSN test bed is implemented. The applicability of the proposed scheme is validated from the experimental results using multiple motors with different physical configurations under various load conditions. To demonstrate the validity of the measured and estimated motor efficiencies in the experiments presented in this work, an in-depth error analysis on motor efficiency measurement and estimation is conducted, using maximum error estimation, worst-case error estimation, and realistic error estimation techniques. The conclusions, contributions, and recommendations are summarized at the end.

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Yakkali, Sai Santosh. "Decomposing Residential Monthly Electric Utility Bill Into HVAC Energy Use Using Machine Learning." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin155437406441298.

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Da, Silva David. "Analyse de la flexibilité des usages électriques résidentiels : application aux usages thermiques." Phd thesis, École Nationale Supérieure des Mines de Paris, 2011. http://pastel.archives-ouvertes.fr/pastel-00678316.

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Au-delà de l'augmentation de la consommation de l'électricité, on observe dans le même temps que les consommations pendant les périodes de pointe deviennent de plus en plus fréquentes et de plus forte intensité. Pour faire face à cette problématique, la présente thèse exploite la flexibilité que peuvent apportée au système électrique les différents usages électriques résidentiels Dans un premier temps, le potentiel des différents équipements pour la gestion de la demande est évalué en termes d'impact sur la consommation et d'appels de puissance caractéristiques de chaque équipement. Dans un deuxième temps, une méthodologie basée sur un langage graphique est proposée pour repérer les possibles stratégies de contrôle. Cette méthodologie va permettre de définir l'ensemble des stratégies de contrôle applicables à un équipement et de voir de quelle façon un équipement ordinaire peut être modifié pour devenir " intelligent " (" Smart Appliance "). Ensuite, une méthodologie est développée pour analyser les différents impacts (positifs et négatifs) selon deux objectifs différents: le contrôle à distance et le contrôle en fonction de tarifs. Cette méthodologie permet de caractériser les effets positifs résultants de l'application d'une stratégie de contrôle donnée, en termes de puissance et énergie, mais aussi ses effets négatifs, les impacts sur le confort thermique et le possible recouvrement par le bâtiment ou l'équipement de l'énergie qu'il n'a pas consommée (cas des usages thermiques). Enfin, cette méthodologie est appliqué à plus grande l'échelle (plusieurs bâtiments) pour quantifier la flexibilité apportée au réseau. Les contrôles seront analysés du point de vue du réseau électrique mais aussi du point de vue du consommateur (par l'intermédiaire des gains ou pertes monétaires et de confort).

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Books on the topic "Electrical energy usage"

1

Kournetas, Nicholas George. The use of oxygen to decrease electrical energy useage in the electric Arc furnace. Ottawa: National Library of Canada, 1998.

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Pennsylvania Public Utility Commission. Bureau of Consumer Services. Low income usage reduction program (LIURP): Historical report and program analysis. Harrisburg, Pa: The Commission, 1994.

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Inc, Quantum Consulting, Southern California Edison Company, and Electric Power Research Institute, eds. Residential energy usage comparison: Findings. Palo Alto, CA: The Institute, 1991.

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Book chapters on the topic "Electrical energy usage"

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Shah, Yatish T. "Modular Systems for Energy Usage in Computer and Electrical/Electronic Applications." In Modular Systems for Energy Usage Management, 217–57. Boca Raton : CRC Press, [2020] | Series: Sustainable energy: CRC Press, 2020. http://dx.doi.org/10.1201/9780367822392-5.

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Utlu, Zafer, and Hasan Saygin. "Examination of Energy Usage of Electrical House Applications in Terms of Energy Efficiency." In Renewable Energy in the Service of Mankind Vol II, 277–89. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18215-5_25.

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Bandaru, Gidean, and Puneet Paneri. "Global System of Record and Framework to Preserve Energy-Usage Data with Blockchain." In Lecture Notes in Electrical Engineering, 83–90. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1299-2_8.

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Milev, George, Amin Al-Habaibeh, and Daniel Shin. "Impact of Replacing Conventional Cars with Electric Vehicles on UK Electricity Grid and Carbon Emissions." In Springer Proceedings in Energy, 199–206. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63916-7_25.

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AbstractThis paper estimated the effect of electric vehicle transition on UK road and how it impacts on electricity supply and the reduction of carbon emissions. It used a scenario in which all cars that utilise internal combustion engines will be replaced by EVs in the UK. The methodology is based on speculating the future number of EVs in Great Britain, which helped in estimating the amount of additional electricity usage that would be required for the scenario. The results revealed that approximately 81 TWh of additional electricity must be produced annually to compensate for such expansion of EV. With that increase in electricity generation, the levels of carbon emissions from the electrical grid will rise slightly, by about 8.6 million tonnes of carbon dioxide per year. Given that combustion vehicles contribute to about 42% of the carbon emissions from the transport sector in the UK, it is concluded that the total amount of CO2 in the country will decrease by approximately 12% of all cars with internal combustion engines are replaced by electric vehicles.

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Asha, N., and G. Raghavendra Rao. "Energy-Efficiency Driven Strategy for Resource Aggregation Based on Future Resource-Usage Inference in a Cloud Computing Environment." In Lecture Notes in Electrical Engineering, 143–51. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3125-5_16.

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Saqib, Mohd, Sanjeev Anand Sahu, Mohd Sakib, and Essam A. Al-Ammar. "Machine Learning-Based Day-Ahead Market Energy Usage Bidding for Smart Microgrids." In Electric Vehicle Integration in a Smart Microgrid Environment, 249–66. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9780367423926-10.

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van Montfort, Kees, Halldora Thorsdottir, and René Bohnsack. "Optimizing Resource Usage in an Unobtrusive Way Through Smart Aggregation: The Case of Electric Vehicle Charging in Amsterdam." In Regulations in the Energy Industry, 243–61. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-32296-0_13.

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Leahu, Cristian-Ioan, Sebastian Radu, Stelian Tarulescu, and Radu Tarulescu. "Usage of Electric Motors/Generators for Engines Supercharging in Order to Increase the Efficiency of Exhaust Gas Energy Recovery." In Proceedings of the 4th International Congress of Automotive and Transport Engineering (AMMA 2018), 550–57. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94409-8_64.

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"Storage and Usage of Energy." In Technologies for Electrical Power Conversion, Efficiency, and Distribution, 10–31. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-647-6.ch002.

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A necessity to store energy in purpose to use it later in time arises in different occasions. For example, in uninterruptible power supplies systems examined in Chapter 10, stored energy is required when a drop off of the electrical network system happens. In systems used to obtain energy from renewable sources examined in Chapter 9, the necessity to store energy also arises. This is explained by the fact that energy is not always possible to be consumed at the moment of its generation and of the same quantity. For example, the periods of strong sun lightening or strong wind may not coincide with the periods of maximum consumption.

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"Generator Modeling Practices for Renewable Energy Implementation." In Business Strategies for Electrical Infrastructure Engineering, 89–118. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2839-7.ch004.

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In order to integrate a renewable energy resource into the current electrical grid infrastructure, a comprehensive assessment of the demand-side usage patterns is compulsory. It includes such economic variables as tourism within the area, fuel usage, industrial/agricultural output, labor productivity, employment by sector, household income, and the electricity prices by group. A few of the key metrics as inputs for the integrated resource planning are described in this chapter. A thorough assessment and detailed analysis is also required for each generator request to investigate the proposed electrical impact on the grid.

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Conference papers on the topic "Electrical energy usage"

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Yang, Zhihan, Nigel Goddard, Lynda Webb, and Huiwei Chen. "Electrical Appliance Usage Timeline Data Visualization." In e-Energy '21: The Twelfth ACM International Conference on Future Energy Systems. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3447555.3466637.

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Bhagwandin, Devika, Vrijesh Tripathi, and Patrick Hosein. "Association Rule Mining of Household Electrical Energy Usage." In the 2017 International Conference. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3089871.3089888.

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Oliveira, D. Q., A. C. Zambroni de Souza, A. B. Almeida, M. V. Santos, B. I. L. Lopes, and D. Marujo. "Microgrid management in emergency scenarios for smart electrical energy usage." In 2015 IEEE Eindhoven PowerTech. IEEE, 2015. http://dx.doi.org/10.1109/ptc.2015.7232309.

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Barmayoon, M. H., M. Fotuhi-Firuzabad, A. Rajabi-Ghahnavieh, and M. Moeini-Aghtaie. "An investigation on the role of energy storage usage in residential energy hubs." In 2015 23rd Iranian Conference on Electrical Engineering (ICEE). IEEE, 2015. http://dx.doi.org/10.1109/iraniancee.2015.7146481.

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Aikema, David, and Rob Simmonds. "Electrical cost savings and clean energy usage potential for HPC workloads." In 2011 IEEE International Symposium on Sustainable Systems and Technology (ISSST). IEEE, 2011. http://dx.doi.org/10.1109/issst.2011.5936911.

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Cruz Martins, D., R. Demonti, and I. Barbi. "Usage of the solar energy from the photovoltaic panels for the generation of electrical energy." In 21st International Telecommunications Energy Conference. INTELEC '99 (Cat. No.99CH37007). IEEE, 1999. http://dx.doi.org/10.1109/intlec.1999.794089.

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Veremiichuk, Yurii, Olena Yarmoliuk, Ivan Prytyskach, and Vitalii Opryshko. "Modeling energy hub operating modes with demand side management usage." In 2018 International Conference and Exposition on Electrical And Power Engineering (EPE). IEEE, 2018. http://dx.doi.org/10.1109/icepe.2018.8559639.

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Pholboon, Seksak, Mark Sumner, and Petros Kounnos. "Adaptive power flow control for reducing peak demand and maximizing renewable energy usage." In 2017 International Electrical Engineering Congress (iEECON). IEEE, 2017. http://dx.doi.org/10.1109/ieecon.2017.8075737.

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Ntsaluba, Sula B. K., Maria Michael, Solathiso Shasha, and Isaac Dlamini. "Electrical Energy Usage Analysis for all Residences of a South African Academic Institution." In 2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC). IEEE, 2018. http://dx.doi.org/10.1109/iconic.2018.8601093.

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Bentley, Peter J., Soo Ling Lim, Shrey Jindal, and Sid Narang. "Generating Synthetic Energy Usage Data to Enable Machine Learning for Sustainable Accommodation." In 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME). IEEE, 2021. http://dx.doi.org/10.1109/iceccme52200.2021.9591016.

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Reports on the topic "Electrical energy usage"

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de Boer, Jan, Nikodem Derengowski, Marc Fontoynont, Daniel Neves Pimenta, Per Reinhold, and Robert Weitlaner. Standardisation issues related to lighting and daylighting control systems. Edited by Marc Fontoynont. IEA SHC Task 61, October 2021. http://dx.doi.org/10.18777/ieashc-task61-2021-0011.

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Even though there are existing codes and standards regarding daylighting and electric lighting controls, they have to be constantly reviewed and updated, as the technology is growing rapidly - and so do the users’ expectations. That is, in both efficiency of buildings in terms of sustainability and energy usage (utilizing advanced sensor-based systems), and also in the need for high quality of lighting at the workplaces.

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