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Zeitschriftenartikel zum Thema "Electric power consumption":
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Milivoj Mandić, Ivo Uglešić und Viktor Milardić. „ELECTRIC RAILWAY POWER CONSUMPTION“. Journal of Energy - Energija 58, Nr. 4 (16.09.2022): 384–407. http://dx.doi.org/10.37798/2009584306.
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The electric railways is a specific consumer of the electric power system. For the purpose of using electric energy rationally and making adequate savings, efforts are made to optimize electric energy consumption of electric trains and other electric railway facilities. The work shows the train movement simulation algorithm which serves to determine primarily the mechanical and then also the electric power required for traction. The sections of the electrified tracks are supplied from the electric traction substation (TS) and, for the requirements of the electric traction calculation, an electric network is formed. Based on the maximum time table for a certain time period, calculation is done of the electric circumstances; electricity, voltage, electric power, as well as the total consumed electric energy. For the determination of the electric energy supply of the traction unit, movement resistances of the certain train on each section need to be calculated. Input data necessary for such a calculation are the tracks profile parameters, planned movement speeds on certain sections, and the properties of the train and the locomotive. Besides the train movement simulation model, the article also shows the analysis of impact factors on the electric energy consumption for the electromotor train which travels the Croatian suburban rails. The results are obtained by the train movement simulation algorithm, by virtue of which the locations of trains are calculated, as well as their mechanical and electric powers necessary for traction. The particular example of the supply of the existing SS serves for comparing the results obtained by electric traction calculation and measurement. Some of the results are given of the electric traction simulation for the Zaprešić SS at the supply of the suburban Podsused factory − Samobor − Bregana which is planned for construction.
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Hasan, Maha Yousif, und Dheyaa Jasim Kadhim. „A new smart approach of an efficient energy consumption management by using a machine-learning technique“. Indonesian Journal of Electrical Engineering and Computer Science 25, Nr. 1 (01.01.2022): 68. http://dx.doi.org/10.11591/ijeecs.v25.i1.pp68-78.
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Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is satisfied. It divides the measured data for actual power (A_p ) of the electrical model into two portions: the training portion is selected for different maximum actual powers, and the validation portion is determined based on the minimum output power consumption and then used for comparison with the actual required input power. Simulation results show the energy expenditure problem can be solved with good accuracy in energy consumption by reducing the maximum rate (A_p ) in a given time (24) hours for a single house, as well as electricity’s bill cost, is reduced.
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KOTYSH, Andrii, Ivan SAVELENKO und Kateryna PETROVA. „THE EXCESSIVE TECHNICAL LOSSES OF ELECTRICITY IN ELECTRICAL SYSTEMS OF POWER CONSUMPTION“. Herald of Khmelnytskyi National University. Technical sciences 315, Nr. 6 (29.12.2022): 69–73. http://dx.doi.org/10.31891/2307-5732-2022-315-6(2)-69-73.
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Reducing electricity losses in electrical networks is a complex complex problem that requires significant capital investments necessary for optimizing the development of electrical networks, improving the electricity accounting system, introducing new information technologies in marketing activities and managing network modes, training personnel and equipping them with means of testing measuring devices etc. In reality, in recent years, in connection with the inclusion of normative losses in the tariff for electric energy transmission services, a dangerous trend of adapting these norms to actual losses has emerged. The article analyzes the occurrence of power losses in electrical engineering systems and electrical networks of various voltage classes. Special attention is paid to the so-called excess losses, which are not taken into account during design and operation. These losses occur in insulators, linear fittings, current-limiting reactors, electricity meters, windings of current and voltage transformers, etc. Excessive losses of electricity in electric networks are direct financial losses of electric power companies. Savings from reducing losses could be directed to technical re-equipment of networks; staff salary increase; improvement of the organization of electricity transmission and distribution; increasing the reliability and quality of electricity supply to consumers. Unaccounted losses reach approximately 1% of the total amount. This fact must be taken into account. Because currently we are talking about millions of losses.
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Arlenny. „The Design of Portable Battery Charging Devices Using Motorcycle Wheel Round“. International Journal of Electrical, Energy and Power System Engineering 2, Nr. 2 (18.06.2019): 16–19. http://dx.doi.org/10.31258/ijeepse.2.2.16-19.
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This research aims to the development of reader equipment as well as control the load limitation of electric power using Atmega 8535 microcontroller. In the development of equipment of reading and controlling electrical energy consumptions, the modified KWH (Kilo Watt Hour) meter was used by placing the optocoupler sensor as the enumerator indicator the electric power consumption on the disc. Atmega 8535 microcontroller was used to control and limitation of the electric power consumption. In this research, the measuring and control system was developed to record the amount of electrical power load used, and it can be used as an alternative to the current divider for the achievement of the efficiency of practical electrical energy consumption. The results of the measurement comparison between the measured load and the output load tended to be stable with an average percentage error of 6.3%, and it was still below the optimum threshold value of the error factor, which around 10%. Therefore, results of testing developed equipment KWH digital meter using Atmega 8535 microcontroller that was produced a good performance.
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Han, Oakyoung, und Jaehyoun Kim. „Uncertainty Analysis on Electric Power Consumption“. Computers, Materials & Continua 68, Nr. 2 (2021): 2621–32. http://dx.doi.org/10.32604/cmc.2021.014665.
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Karpenko, S. M., N. V. Karpenko und G. Y. Bezginov. „Forecasting of power consumption at mining enterprises using statistical methods“. Mining Industry Journal (Gornay Promishlennost), Nr. 1/2022 (15.03.2022): 82–88. http://dx.doi.org/10.30686/1609-9192-2022-1-82-88.
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Forecasting of electric power consumption with due account of assessed impact of various factors helps to make efficient technical and managerial decisions to optimize the electric power consumption processes, including preparation of bids for the wholesale electric power and capacity market. The article uses multivariate methods of statistical analysis and econometric methods based on time series analysis for model designing. The paper presents the results of developing the following models: a multifactor model of electrical power consumption using the regression analysis, the Principal Component Method with the assessment of the impact of production factors on electrical power consumption using elasticity coefficients, as well as the energy saving factor based on a variable structure model; trend additive and multiplicative forecast models of electrical consumption that take into account the seasonality factor, models with a change in trends, a linear dynamic model of electrical power consumption that takes into account the production output; a forecast adaptive polynomial model of electrical power consumption as well as the Winters model. The developed forecast models have a sufficiently high accuracy (accuracy of the MAPE was below 7%). The choice of the model type to forecast the electrical power consumption depends on the quantitative and qualitative characteristics of the time series, the structural relation between the series, the purpose and objectives of the modeling. In order to enhance the accuracy of the forecast it is required to regularly refine the model and adjust it to the actual situation with the due account of new factors and production trends while building different versions of scenarios and combined forecast models of electrical power consumption
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Rajamoorthy, Yogambigai, Ooi Bee Chen und Subramaniam Munusamy. „Evidence of Electricity Consumption Lead Climate Change in Malaysia“. Jurnal Kejuruteraan si1, Nr. 6 (30.11.2018): 49–58. http://dx.doi.org/10.17576/jkukm-2018-si1(6)-07.
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The consumption of electricity in Malaysia increase in demand as one of the driving forces of economic development. The main source of electric power generation in Malaysia depends on fossil fuels which lead to air pollution currently and a shortage of natural resources (fossil) in the future if this method continues. Moreover, this will cause a serious problem such as sustainability of energy choice and will harm the environment. This study investigates the relationship between climate variables and electric power consumption in Malaysia. The important climate variables included such as average temperature, average rainfall, forest area, carbon dioxide emission and arable land over a period of 1991 to 2015. Augmented Dickey-Fuller unit root test shows that average rainfall, average temperature, and electrical power consumption stationary at their level. However, forest area, carbon dioxide emission, and arable land stationary after first differences. The result of this study indicates that electric power consumption has a long-run relationship between average temperature and average rainfall. This indicates that electric power consumption has an impact on climate change in Malaysia. These studies also find evidence that unidirectional causality between electric power consumption and climate factors. Overall, the wise consumption of electricity and adopting renewable energy to generate electricity will reduce carbon emission in Malaysia.
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Naumov, I. V., D. N. Karamov, A. N. Tretyakov, M. A. Yakupova und E. S. Fedorinova. „Asymmetric power consumption in rural electric networks“. IOP Conference Series: Earth and Environmental Science 677, Nr. 3 (01.03.2021): 032088. http://dx.doi.org/10.1088/1755-1315/677/3/032088.
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Beliaeva, Nataliia, Anton Petrochenkov und Korinna Bade. „Data Set Analysis of Electric Power Consumption“. European Researcher 61, Nr. 10-2 (15.09.2013): 2482–87. http://dx.doi.org/10.13187/er.2013.61.2482.
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Sablin, O. I. „THE ADDITIONAL PULSATION POWER LOSS IN POWER CHAINS OF XPS DC“. Science and Transport Progress, Nr. 18 (25.10.2007): 38–40. http://dx.doi.org/10.15802/stp2007/17437.
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Results of researches are stated in article specifying on consumption of inactive jet capacity by the electric rolling stock of a direct current. It is shown, that this consumption brings to additional loss of electric power.
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An electricity demand profile is a graph showing the amount of electricity used by customers over a unit of time. It shows the variation in electricity demand versus time. In the demand profiles, the shape of the graph is of utmost importance. The variations in demand profiles are caused by many factors, such as economic and en- vironmental factors. These variations may also be due to changes in the electricity use behaviours of electricity users. This study seeks to model daily profiles of energy demand in South Africa with a model which is a composition of two de Moivre type models. The model has seven parameters, each with a natural interpretation (one parameter representing minimum demand in a day, two parameters representing the time of morning and afternoon peaks, two parameters representing the shape of each peak, and two parameters representing the total energy per peak). With the help of this model, we trace change in the demand profile over a number of years. The proposed model will be helpful for short to long term electricity demand forecasting.
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Modlin, Danny Robert. „Utilizing time series analysis to forecast long-term electrical consumption /“. Electronic version (PDF), 2006. http://dl.uncw.edu/etd/2006/modlind/dannymodlin.pdf.
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Huss, William Reed. „Load forecasting for electric utilities /“. The Ohio State University, 1985. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487263399023837.
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Lai, Chiu-cheong. „Electricity use and its conservation potential in the commercial sector : a case study in Hong Kong /“. [Hong Kong : University of Hong Kong], 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13498423.
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Chawdhry, P. K. „Identification of boiler-turbine systems in electric power stations“. Thesis, Queen's University Belfast, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.372987.
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Si, Yau-li. „Forecasts of electricity demand and their implication for energy developments in Hong Kong“. [Hong Kong : University of Hong Kong], 1990. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13009102.
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Chiu, Yuk Ha. „A cross-country empirical study on electricity demand /“. View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?ECON%202004%20CHIU.
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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004. Includes bibliographical references (leaves 33-35). Also available in electronic version. Access restricted to campus users.
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Gopalakrishnan, Chandra. „Effectiveness of electrical demand reduction strategies“. Morgantown, W. Va. : [West Virginia University Libraries], 2004. https://etd.wvu.edu/etd/controller.jsp?moduleName=documentdata&jsp%5FetdId=3776.
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Thesis (M.S.)--West Virginia University, 2004. Title from document title page. Document formatted into pages; contains viii, 75 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 74-75).
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Doorduin, Riaan. „Electricity theft detection on a low voltage reticulation environment“. Thesis, Stellenbosch : University of Stellenbosch, 2004. http://hdl.handle.net/10019.1/16310.
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Thesis (MScIng)--University of Stellenbosch, 2004. ENGLISH ABSTRACT: Electricity theft in South Africa has become a major problem. This led to several developments
from both industries and research institutes to counter these actions. Since equipment is already
installed and major capital has been invested to provide electricity for a broad spectrum
of consumers, the challenge is to find a low cost solution harnessing current investments and
technology to detect electricity theft more accurately.
This thesis investigates into the electricity theft topic. Two different methods, Time Domain
Pulse Reflectometry and a data driven platform based on the Theory of Constraints philosophy,
were investigated to provide means to detect and determine the impact of illegal electricity
usage. Both methods required detailed designs to conduct preliminary proof of concept tests in
a laboratory environment.
These methods are evaluated against their economical viability, possible practical implications
and applications. This thesis presents a practical approach to electricity theft detection
and provides the basic tools for management of this ever-increasing problem. AFRIKAANSE OPSOMMING: Suid Afrika se elektrisiteit diefstal statistiek het die afgelope jare skrikwekkend gegroei. Dit het
die industrie genoop om baie meer navorsing in die area te doen. Met reeds gevestigde toerusting
en tegnologie om di´e energie medium so effektief moontlik te versprei, is die uitdaging juis
om ’n ekonomiese oplossing te vind om reeds beskikbare tegnologie¨e meer doeltreffend aan te
wend.
Die doel van die tesis is om die gebied van elektrisiteit diefstal na te vors. Twee verskillende
metodes is ondersoek, naamlik Tydgebied-pulse-reflektometrie en ’n informasie gebaseerde
stelsel wat op die Randvoorwaarde Teorie gebaseer is, om effektief die omvang van elektrisiteit
diefstal in ’n mikro, asook makro omgewing te bepaal. Die twee metodes is in ’n beheerde
omgewing getoets sodat die konsepte wat ontwikkel is bewys kon word.
Die metodes is ge-evalueer in terme van die ekonomiese lewensvatbaarheid daarvan met inagneming
van die praktiese implikasies. Die tesis bied bestuur die nodige kennis om elektrisiteit
diefstal in die praktyk doeltreffend die hok mee te slaan.
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Sarris, Emmanouil. „Naval ship propulsion and electric power systems selection for optimal fuel consumption“. Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68573.
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Thesis (Nav. E.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (S.M. in Engineering and Management)--Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. [100]-102). Although propulsion and electric power systems selection is an important part of naval ship design, respective decisions often have to be made without detailed ship knowledge (resistance, propulsors, etc.). Propulsion and electric power systems have always had to satisfy speed and ship-service power requirements. Nowadays, increasing fuel costs are moving such decisions towards more fuel-efficient solutions. Unlike commercial ships, naval ships operate in a variety of speeds and electric loads, making fuel consumption optimization challenging. This thesis develops a flexible decision support tool in Matlab® environment, which identifies the propulsion and ship-service power generation systems configuration that minimizes fuel consumption for any ship based on its operating profile. Mechanical-driven propulsion systems with or without propulsion derived ship-service power generation, separate ship-service systems and integrated power systems are analyzed. Modeling includes hull resistance using the Holtrop-Mennen method requiring only basic hull geometry information, propeller efficiencies using the Wageningen B series and transmission and prime movers fuel efficiencies. Propulsion and ship-service power generation systems configuration is optimized using the genetic algorithm. US Navy's Advanced Surface Ship Evaluation Tool (ASSET) model for the DDG-51 Flight I destroyer was used for modeling validation. Optimal fuel consumption results are compared against the existing configuration for the DDG-51 Flight I destroyer using a representative operating profile. by Emmanouil Sarris. S.M.in Engineering and Management Nav.E.
Arthur Andersen & Co., Andersen Consulting und Cambridge Energy Research Associates, Hrsg. European electric power trends. Cambridge, Mass., USA: Cambridge Energy Research Associates, 1991.
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National Association of Regulatory Utility Commissioners., Hrsg. Electric power technology. Washington, D.C: National Association of Regulatory Utility Commissioners, 1990.
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Stump, Lisa, Parveen Baig und Leslie Cleveland. Facts concerning the consumption and production of electric power in Iowa. Herausgegeben von Iowa Utilities Board. Des Moines, Iowa: Iowa Utilities Board, Dept. of Commerce, 2000.
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Zipper, Carl E. Assessment of Virginia coalfield region capability to support an electric power generation industry. Blacksburg, Va: Virginia Center for Coal and Energy Research, Virginia Polytechnic and State Iniversity, 1994.
Stütz, Sebastian, Andreas Gade und Daniela Kirsch. „Promoting Zero-Emission Urban Logistics: Efficient Use of Electric Trucks Through Intelligent Range Estimation“. In iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, 91–102. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92096-8_8.
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AbstractCritical success factors for the efficient use of electric trucks are the operational range and the total costs of ownership. For both range and efficient use, power consumption is the key factor. Increasing precision in forecasting power consumption and, hence, maximum range will pave the way for efficient vehicle deployment. However, not only electric trucks are scarce, but also is knowledge with respect to what these vehicles are actually technically capable of. Therefore, this article focuses on power consumption and range of electric vehicles. Following a discussion on how current research handles the mileage of electric vehicles, the article illustrates how to find simple yet robust and precise models to predict power consumption and range by using basic parameters from transport planning only. In the paper, we argue that the precision of range and consumption estimates can be substantially improved compared to common approaches which usually posit a proportional relationship between energy consumption and travel distance and require substantial safety buffers.
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Seliverstova, Anastasiya V., Darya A. Pavlova, Slavik A. Tonoyan und Yuriy E. Gapanyuk. „The Time Series Forecasting of the Company’s Electric Power Consumption“. In Advances in Neural Computation, Machine Learning, and Cognitive Research II, 210–15. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01328-8_24.
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Panchal, R., und B. Kumar. „Forecasting industrial electric power consumption using regression based predictive model“. In Recent Trends in Communication and Electronics, 135–39. London: CRC Press, 2021. http://dx.doi.org/10.1201/9781003193838-26.
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Kovan, Ibrahim, und Stefan Twieg. „Forecasting the Energy Consumption Impact of Electric Vehicles by Means of Machine Learning Approaches“. In Electric Transportation Systems in Smart Power Grids, 43–70. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003293989-3.
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Jing, Feng, und Pan Anding. „The Effect of Guangzhou’s Temperature Change to the Electric Power Consumption“. In Advances in Intelligent and Soft Computing, 439–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25349-2_58.
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Istomin, Stanislav, und Maxim Bobrov. „The Organization of Adaptive Control, Forecasting and Management of Electric Power Consumption of Electric Rolling Stock“. In Lecture Notes in Networks and Systems, 1521–30. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11058-0_154.
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de Queiroz, Alynne C. S., und José Alfredo F. Costa. „Behavior Pattern Recognition in Electric Power Consumption Series Using Data Mining Tools“. In Intelligent Data Engineering and Automated Learning - IDEAL 2012, 522–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32639-4_64.
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Goolak, Sergey, Borys Liubarskyi, Svitlana Sapronova, Viktor Tkachenko und Ievgen Riabov. „Determination of the Power Factor of Electric Rolling Stock of Alternating Current Consumption“. In TRANSBALTICA XII: Transportation Science and Technology, 243–52. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94774-3_24.
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Czachórski, Tadeusz, Erol Gelenbe, Godlove Suila Kuaban und Dariusz Marek. „Optimizing Energy Usage for an Electric Drone“. In Communications in Computer and Information Science, 61–75. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09357-9_6.
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AbstractUnmanned Aerial Vehicles (UAVs) are rapidly gaining popularity in a wide variety of applications, e.g., agriculture, health care, environmental management, supply chains, law enforcement, surveillance, and photography. Dones are often powered by batteries, making energy a critical resource that must be optimised during the mission of the drone. The duration of a done’s mission depends on the amount of energy required to perform some manoeuvering actions (takeoff, level flight, hovering, and landing), the energy required to power the ICT modules in the drone, the drone’s speed, payload, and the wind. In this paper, we present a model that minimizes the energy consumption of a low power drone and maximizes the time required to completely drain the drone’s battery and ensure the safe landing of the drone.
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Fong, Simon, Meng Yuen, Raymond K. Wong, Wei Song und Kyungeun Cho. „Real-Time Stream Mining Electric Power Consumption Data Using Hoeffding Tree with Shadow Features“. In Advanced Data Mining and Applications, 775–87. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49586-6_56.
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Konferenzberichte zum Thema "Electric power consumption":
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Brandstetter, Pavel, Jan Vanek und Tomas Verner. „Electric vehicle energy consumption monitoring“. In 2014 15th International Scientific Conference on Electric Power Engineering (EPE). IEEE, 2014. http://dx.doi.org/10.1109/epe.2014.6839444.
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Coban, Hasan Huseyin, Mohit Bajaj, Vojtech Blazek, Francisco Jurado und Salah Kamel. „Forecasting Energy Consumption of Electric Vehicles“. In 2023 5th Global Power, Energy and Communication Conference (GPECOM). IEEE, 2023. http://dx.doi.org/10.1109/gpecom58364.2023.10175761.
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Kott, M. „The electricity consumption in polish households“. In 2015 Modern Electric Power Systems (MEPS). IEEE, 2015. http://dx.doi.org/10.1109/meps.2015.7477166.
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Cherkassky, Vladimir, Sohini Roy Chowdhury, Volker Landenberger, Saurabh Tewari und Paul Bursch. „Prediction of electric power consumption for commercial buildings“. In 2011 International Joint Conference on Neural Networks (IJCNN 2011 - San Jose). IEEE, 2011. http://dx.doi.org/10.1109/ijcnn.2011.6033285.
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Hobby, John D. „Constructing Demand Response Models for Electric Power Consumption“. In 2010 1st IEEE International Conference on Smart Grid Communications (SmartGridComm). IEEE, 2010. http://dx.doi.org/10.1109/smartgrid.2010.5622075.
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Murata, H., und T. Onoda. „Estimation of power consumption for household electric appliances“. In 9th International Conference on Neural Information Processing. IEEE, 2002. http://dx.doi.org/10.1109/iconip.2002.1201903.
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Vitaliy, Kuznetsov, Tryputen Nikolay und Kuznetsova Yevheniia. „Evaluating the Effect of Electric Power Quality upon the Efficiency of Electric Power Consumption“. In 2019 IEEE 2nd Ukraine Conference on Electrical and Computer Engineering (UKRCON). IEEE, 2019. http://dx.doi.org/10.1109/ukrcon.2019.8879841.
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Jiang, Jingfei, Bo Bao, Fanzhuo Meng, Yifan Ma, Hui Zhang, Yucheng Jin, Fengwen Pan und Xinmei Yuan. „Probabilistic Energy Consumption Estimation for Electric Buses“. In 2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES). IEEE, 2022. http://dx.doi.org/10.1109/spies55999.2022.10082616.
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Zihan, Wang, Shao Enze, Wang Can, Xu Xiao, Du Xianbo, Zhong Chunlin, Zou Lei, Chen GuoLin und Fang Chao. „LSTM-Based Method for Electric Consumption Outlier Detection“. In 2021 IEEE Sustainable Power and Energy Conference (iSPEC). IEEE, 2021. http://dx.doi.org/10.1109/ispec53008.2021.9735594.
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Damianakis, Nikolaos, Gautham Chandra Ram Mouli und Pavol Bauer. „Risk-averse Estimation of Electric Heat Pump Power Consumption“. In 2023 IEEE 17th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG). IEEE, 2023. http://dx.doi.org/10.1109/cpe-powereng58103.2023.10227424.
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Berichte der Organisationen zum Thema "Electric power consumption":
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Boero, Riccardo. Electric Power Consumption Coefficients for U.S. Industries: Regional Estimation and Analysis. Office of Scientific and Technical Information (OSTI), Juli 2017. http://dx.doi.org/10.2172/1372806.
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Mai, Trieu T., Paige Jadun, Jeffrey S. Logan, Colin A. McMillan, Matteo Muratori, Daniel C. Steinberg, Laura J. Vimmerstedt, Benjamin Haley, Ryan Jones und Brent Nelson. Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States. Office of Scientific and Technical Information (OSTI), Juni 2018. http://dx.doi.org/10.2172/1459351.
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Li, Yan, Yuhao Luo und Xin Lu. PHEV Energy Management Optimization Based on Multi-Island Genetic Algorithm. SAE International, März 2022. http://dx.doi.org/10.4271/2022-01-0739.
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The plug-in hybrid electric vehicle (PHEV) gradually moves into the mainstream market with its excellent power and energy consumption control, and has become the research target of many researchers. The energy management strategy of plug-in hybrid vehicles is more complicated than conventional gasoline vehicles. Therefore, there are still many problems to be solved in terms of power source distribution and energy saving and emission reduction. This research proposes a new solution and realizes it through simulation optimization, which improves the energy consumption and emission problems of PHEV to a certain extent. First, on the basis that MATLAB software has completed the modeling of the key components of the vehicle, the fuzzy controller of the vehicle is established considering the principle of the joint control of the engine and the electric motor. Afterwards, based on the Isight and ADVISOR co-simulation platform, with the goal of ensuring certain dynamic performance and optimal fuel economy of the vehicle, the multi-island genetic algorithm is used to optimize the parameters of the membership function of the fuzzy control strategy to overcome it to a certain extent. The disadvantages of selecting parameters based on experience are compensated for, and the efficiency and feasibility of fuzzy control are improved. Finally, the PHEV vehicle model simulation comparison was carried out under the UDDS working condition through ADVISOR software. The optimization results show that while ensuring the required power performance, the vehicle fuzzy controller after parameter optimization using the multi-island genetic algorithm is more efficient, which can significantly reduce vehicle fuel consumption and improve exhaust emissions.
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Penetrante, B. M., M. C. Hsiao und J. N. Bardsley. Power consumption and byproducts in electron beam and electrical discharge processing of volatile organic compounds. Office of Scientific and Technical Information (OSTI), Februar 1996. http://dx.doi.org/10.2172/231371.
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Gummow. L51908 AC Grounding Effects on Cathodic Protection Performance in Pipeline Stations.pdf. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), Dezember 2001. http://dx.doi.org/10.55274/r0010269.
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Most AC powered equipment at pipeline stations and at motorized valve sites isrequired, by code, to be electrically grounded to one or more ground electrodes. These grounding systems are normally electrically bonded to the AC power distribution grid, which can be quite extensive. Piping, either intentionally or inadvertently, is often connected to the AC electrical grounding grid in pipeline stations. Grounding grid conductors are usually bare and composed of copper or tinned copper, and ground rod materials can consist of a wide variety of metals such as copper-clad steel, carbon steel, stainless steel, galvanized steel, and galvanic anode alloys of zinc and magnesium. The interconnection of these grounding materials to the piping can increase the current requirements of the cathodic protection system, distort the current distribution pattern and complicate the accurate measurement of the pipe potentials. Benefit: The primary objective of this research project was to assess the impact of various types of grounding materials on the performance and testing of cathodic protection systems. The two major issues in this regard were the effects on current requirements and the accuracy of pipe-to-soil potential measurements. In addition, some related issues investigated as follows:the electrical resistance of each groundrod-to-earth was to be measured to determine whether or not there were any changes in the resistance-to-earth as a result cathodic polarization;the potential of galvanized steel was to be measured with increasing zinc consumption to determine if there is a well defined relationship between potential and zinc consumption; the National Electrical Code (NEC) was to be reviewed with respect to the insertion of AC coupling/DC isolating devices in series between the piping and the electrical grounding network. The results of this investigation were intended toprovide information to design more effective cathodic protection facilities for piping in pipeline stations having electrical grounding systems, anddetermine whether or not the resistance of the electrical grounding system increases as a result of receiving cathodic protection, andrecommend pipe-to-soil potential survey techniques to maximize measurement accuracy in the presence of an AC grounding grid, andevaluate the use of DC isolators/AC couplers to interconnect the piping to either the secondary or primary AC grounding system.
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Hall und Brown. PR-343-14607-R01 Miniaturized Gas Chromatography and Gas Quality Sensor. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), Februar 2015. http://dx.doi.org/10.55274/r0010558.
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In natural gas transmission and distribution, many metering stations utilize gas chromatography to ensure the gas complies with the pipeline�s gas quality tariff provisions and to determine the chemical energy content of the gas for billing purposes. It is also used as a check on the operation of gas ultrasonic flowmeters through a calculation of the speed of sound in the gas. Because of limitations on existing gas chromatographs (GC�s), including high installed cost, analysis time, carrier gas consumption and others, there is a desire to consider alternate technologies for natural gas analysis. PRCI has sponsored a study of technologies that utilize the variation in absorption/scattering of optical wavelengths by different molecules. The purpose of this study is to extend that study to the use of additional technologies, such as MEMS (Micro-Electro-Mechanical Systems). This is not a new approach, but recent advancements offer a greater possibility of achievement of the desired goals than in the past. This study reviewed and evaluated work in process with MEMS technology to provide a smaller, less ex-pensive, lower-power and faster GC that can be utilized in a Class 1 Division 2 area. Developments at both commercial firms and in university MEMS research programs have been included. Since there have been several programs to evaluate �energy meters� that attempt to measure gas quality by calculating the BTU content of a gas sample, this study focused on micro-GC�s that can make a much more precise measurement of gas quality.
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Comparative Analysis on Fuel Consumption Between Two Online Strategies for P2 Hybrid Electric Vehicles: Adaptive-RuleBased (A-RB) vs Adaptive-Equivalent Consumption Minimization Strategy (A-ECMS). SAE International, März 2022. http://dx.doi.org/10.4271/2022-01-0740.
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Hybrid electric vehicles (HEVs) represent one of the main technological options for reducing vehicle CO2 emissions, helping car manufacturers (OEMs) to meet the stricter targets which are set by the European Green Deal for new passenger cars at 80 g CO2/km by 2025. The optimal power-split between the internal combustion engine (ICE) and the electric motor is a challenge since it depends on many unpredictable variables. In fact, HEV improvements in fuel economy and emissions strongly depend on the energy management strategy (EMS) on-board of the vehicle. Dynamic Programming approach (DP), direct methods and Pontryagin’s minimum principle (PMP) are some of the most used methodologies to optimize the HEV power-split. In this paper two online strategies are evaluated: an Adaptive-RuleBased (A-RB) and an Adaptive-Equivalent Consumption Minimization Strategy (A-ECMS). At first, a description of the P2 HEV model is made. Second, the two sub-optimal strategies are described in detail and then implemented on the HEV model to derive the fuel-optimal control strategy managing the power split between the thermal and electric engine to satisfy the driver's power request, including the engine on/off operating mode and the best gear selection. Finally, the two proposed strategies are tested on different driving cycles and then compared to other commercial strategies available in literature, such as the Equivalent Consumption Minimization Strategy (ECMS) and a RuleBased (RB) strategy. The results show that the A-ECMS is more conservative in terms of state of charge (SoC) compared to the A-RB. In fact, in the A-ECMS the SoC is always within the admissible range with considerable margin from the upper and lower limits for tested cycles, while in the A-RB a deep discharge of the battery is allowed. This behavior leads to a better fuel consumption of the A-RB compared to the A-ECMS, both in the WLTC and in the FTP-75 cycle.
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Development of an Adaptive Efficient Thermal/Electric Skipping Control Strategy Applied to a Parallel Plug-in Hybrid Electric Vehicle. SAE International, März 2022. http://dx.doi.org/10.4271/2022-01-0737.
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In recent years automobile manufacturers focused on an increasing degree of electrification of the powertrains with the aim to reduce pollutants and CO2 emissions. Despite more complex design processes and control strategies, these powertrains offer improved fuel exploitation compared to conventional vehicles thanks to intelligent energy management. A simulation study is here presented aiming at developing a new control strategy for a P3 parallel plug-in hybrid electric vehicle. The simulation model is implemented using vehicle modeling and simulation toolboxes in MATLAB/Simulink. The proposed control strategy is based on an alternative utilization of the electric motor and thermal engine to satisfy the vehicle power demand at the wheels (Efficient Thermal/Electric Skipping Strategy - ETESS). The choice between the two units is realized through a comparison between two equivalent fuel rates, one related to the thermal engine and the other related to the electric consumption. An adaptive function is introduced to develop a charge-blended control strategy. The novel adaptive control strategy (A-ETESS) is applied to estimate fuel consumption along different driving cycles. The control algorithm is implemented on a dedicated microcontroller unit performing a Processor-In-the-Loop (PIL) simulation. To demonstrate the reliability and effectiveness of the A-ETESS, the same adaptive function is built on the Equivalent Consumption Minimization Strategy (ECMS). The PIL results showed that the proposed strategy ensures a fuel economy similar to ECMS (worse of about 2% on average) and a computational effort reduced by 99% on average. This last feature reveals the potential for real-time on-vehicle applications.
