Literatura científica selecionada sobre o tema "Electric power consumption"
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Artigos de revistas sobre o assunto "Electric power consumption"
Milivoj Mandić, Ivo Uglešić e Viktor Milardić. "ELECTRIC RAILWAY POWER CONSUMPTION". Journal of Energy - Energija 58, n.º 4 (16 de setembro de 2022): 384–407. http://dx.doi.org/10.37798/2009584306.
Texto completo da fonteHan, Oakyoung, e Jaehyoun Kim. "Uncertainty Analysis on Electric Power Consumption". Computers, Materials & Continua 68, n.º 2 (2021): 2621–32. http://dx.doi.org/10.32604/cmc.2021.014665.
Texto completo da fonteSablin, O. I. "THE ADDITIONAL PULSATION POWER LOSS IN POWER CHAINS OF XPS DC". Science and Transport Progress, n.º 18 (25 de outubro de 2007): 38–40. http://dx.doi.org/10.15802/stp2007/17437.
Texto completo da fonteNaumov, I. V., D. N. Karamov, A. N. Tretyakov, M. A. Yakupova e E. S. Fedorinova. "Asymmetric power consumption in rural electric networks". IOP Conference Series: Earth and Environmental Science 677, n.º 3 (1 de março de 2021): 032088. http://dx.doi.org/10.1088/1755-1315/677/3/032088.
Texto completo da fonteBeliaeva, Nataliia, Anton Petrochenkov e Korinna Bade. "Data Set Analysis of Electric Power Consumption". European Researcher 61, n.º 10-2 (15 de setembro de 2013): 2482–87. http://dx.doi.org/10.13187/er.2013.61.2482.
Texto completo da fonteN’Zué, Felix Fofana. "Is There a Relationship between CO2 Emissions by Sources, Electricity Consumption and Economic Growth in Côte d’Ivoire? Evidence from an ARDL Investigation". International Journal of Economics and Finance 14, n.º 7 (25 de junho de 2022): 28. http://dx.doi.org/10.5539/ijef.v14n7p28.
Texto completo da fonteKarpenko, Sergey, e Nadezhda Karpenko. "Analysis and modeling of regional electric power consumption subject to influence of external factors". Energy Safety and Energy Economy 3 (junho de 2021): 12–17. http://dx.doi.org/10.18635/2071-2219-2021-3-12-17.
Texto completo da fonteMacheso, Paul Stone, e Doreen Thotho. "ESP32 Based Electric Energy Consumption Meter". International Journal of Computer Communication and Informatics 4, n.º 1 (9 de maio de 2022): 23–35. http://dx.doi.org/10.34256/ijcci2213.
Texto completo da fonteHasan, Maha Yousif, e 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, n.º 1 (1 de janeiro de 2022): 68. http://dx.doi.org/10.11591/ijeecs.v25.i1.pp68-78.
Texto completo da fontePark, EungSuk, BoRam Kim, SooHyun Park e Daecheol Kim. "Analysis of the Effects of the Home Energy Management System from an Open Innovation Perspective". Journal of Open Innovation: Technology, Market, and Complexity 4, n.º 3 (3 de agosto de 2018): 31. http://dx.doi.org/10.3390/joitmc4030031.
Texto completo da fonteTeses / dissertações sobre o assunto "Electric power consumption"
Mangisa, Siphumlile. "Statistical analysis of electricity demand profiles". Thesis, Nelson Mandela Metropolitan University, 2013. http://hdl.handle.net/10948/d1011548.
Texto completo da fonteModlin, 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.
Texto completo da fonteHuss, William Reed. "Load forecasting for electric utilities /". The Ohio State University, 1985. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487263399023837.
Texto completo da fonteLai, 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.
Texto completo da fonteSi, 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.
Texto completo da fonteChawdhry, 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.
Texto completo da fonteChiu, 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.
Texto completo da fonteIncludes bibliographical references (leaves 33-35). Also available in electronic version. Access restricted to campus users.
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.
Texto completo da fonteTitle from document title page. Document formatted into pages; contains viii, 75 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 74-75).
Doorduin, Riaan. "Electricity theft detection on a low voltage reticulation environment". Thesis, Stellenbosch : University of Stellenbosch, 2004. http://hdl.handle.net/10019.1/16310.
Texto completo da fonteENGLISH 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.
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.
Texto completo da fonteCataloged 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.
Livros sobre o assunto "Electric power consumption"
Arthur Andersen & Co., Andersen Consulting e Cambridge Energy Research Associates, eds. European electric power trends. Cambridge, Mass., USA: Cambridge Energy Research Associates, 1991.
Encontre o texto completo da fonteNational Association of Regulatory Utility Commissioners., ed. Electric power technology. Washington, D.C: National Association of Regulatory Utility Commissioners, 1990.
Encontre o texto completo da fonteEstomin, Steven. Forecasted electric power demands for the Potomac Electric Power Company. [Annapolis, Md.]: The Program, 1988.
Encontre o texto completo da fonteMunasinghe, Mohan. Electric power economics: Selected works. London: Butterworths, 1990.
Encontre o texto completo da fonteGroup, Energy Research, ed. Electric power for industrialisation in developing countries. Place of publication not identified]: [publisher not identified], 1985.
Encontre o texto completo da fonteStump, Lisa, Parveen Baig e Leslie Cleveland. Facts concerning the consumption and production of electric power in Iowa. Editado por Iowa Utilities Board. Des Moines, Iowa: Iowa Utilities Board, Dept. of Commerce, 2000.
Encontre o texto completo da fonteAlagh, Yoginder K. Power economics in Gujarat. New Delhi: Har-Anand Publications, 1998.
Encontre o texto completo da fonteUnited States. Bonneville Power Administration., ed. Puget Sound area electric reliability plan. Portland, Or: The Administration, 1991.
Encontre o texto completo da fonteWillis, H. Lee. Spatial electric load forecasting. 2a ed. New York: Marcel Dekker, 2002.
Encontre o texto completo da fonteʻAbduh, Saʻīd Aḥmad. Jughrāfīyat al-ṭāqah al-kahrabāʼīyah fī al-minṭaqah al-janūbīyah bi-al-Mamlakah al-ʻArabīyah al-Saʻūdīyah. [Cairo: s.n.], 1985.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Electric power consumption"
Stütz, Sebastian, Andreas Gade e 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.
Texto completo da fonteSeliverstova, Anastasiya V., Darya A. Pavlova, Slavik A. Tonoyan e 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.
Texto completo da fontePanchal, R., e 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.
Texto completo da fonteKovan, Ibrahim, e 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.
Texto completo da fonteJing, Feng, e 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.
Texto completo da fonteIstomin, Stanislav, e 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.
Texto completo da fontede Queiroz, Alynne C. S., e 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.
Texto completo da fonteCzachórski, Tadeusz, Erol Gelenbe, Godlove Suila Kuaban e 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.
Texto completo da fonteGoolak, Sergey, Borys Liubarskyi, Svitlana Sapronova, Viktor Tkachenko e 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.
Texto completo da fonteFong, Simon, Meng Yuen, Raymond K. Wong, Wei Song e 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.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Electric power consumption"
Brandstetter, Pavel, Jan Vanek e 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.
Texto completo da fonteCoban, Hasan Huseyin, Mohit Bajaj, Vojtech Blazek, Francisco Jurado e 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.
Texto completo da fonteKott, 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.
Texto completo da fonteCherkassky, Vladimir, Sohini Roy Chowdhury, Volker Landenberger, Saurabh Tewari e 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.
Texto completo da fonteHobby, 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.
Texto completo da fonteMurata, H., e 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.
Texto completo da fonteVitaliy, Kuznetsov, Tryputen Nikolay e 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.
Texto completo da fonteJiang, Jingfei, Bo Bao, Fanzhuo Meng, Yifan Ma, Hui Zhang, Yucheng Jin, Fengwen Pan e 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.
Texto completo da fonteZihan, Wang, Shao Enze, Wang Can, Xu Xiao, Du Xianbo, Zhong Chunlin, Zou Lei, Chen GuoLin e 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.
Texto completo da fonteDamianakis, Nikolaos, Gautham Chandra Ram Mouli e 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.
Texto completo da fonteRelatórios de organizações sobre o assunto "Electric power consumption"
Boero, Riccardo. Electric Power Consumption Coefficients for U.S. Industries: Regional Estimation and Analysis. Office of Scientific and Technical Information (OSTI), julho de 2017. http://dx.doi.org/10.2172/1372806.
Texto completo da fonteMai, Trieu T., Paige Jadun, Jeffrey S. Logan, Colin A. McMillan, Matteo Muratori, Daniel C. Steinberg, Laura J. Vimmerstedt, Benjamin Haley, Ryan Jones e Brent Nelson. Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States. Office of Scientific and Technical Information (OSTI), junho de 2018. http://dx.doi.org/10.2172/1459351.
Texto completo da fonteLi, Yan, Yuhao Luo e Xin Lu. PHEV Energy Management Optimization Based on Multi-Island Genetic Algorithm. SAE International, março de 2022. http://dx.doi.org/10.4271/2022-01-0739.
Texto completo da fonteDhammi, Rimmi, Marcus Jones, Shweta Varadarajan, Conor Baverstock, Steve Chege e James Zihni. ACA105 Motorcade - Analysis toolkit for monitoring trials of zero emission vehicles. TRL, janeiro de 2024. http://dx.doi.org/10.58446/omcq1828.
Texto completo da fontePenetrante, B. M., M. C. Hsiao e 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), fevereiro de 1996. http://dx.doi.org/10.2172/231371.
Texto completo da fonteHaddad, J., L. A. Horta Nogueira, Germano Lambert-Torres e L. E. Borges da Silva. Energy Efficiency and Smart Grids for Low Carbon and Green Growth in Brazil: Knowledge Sharing Forum on Development Experiences: Comparative Experiences of Korea and Latin America and the Caribbean. Inter-American Development Bank, junho de 2015. http://dx.doi.org/10.18235/0007001.
Texto completo da fonteGolovacheva, Larissa. Integration modules for electronic systems. Intellectual Archive, abril de 2024. http://dx.doi.org/10.32370/iaj.3067.
Texto completo da fonteGummow. L51908 AC Grounding Effects on Cathodic Protection Performance in Pipeline Stations.pdf. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), dezembro de 2001. http://dx.doi.org/10.55274/r0010269.
Texto completo da fonteHall e Brown. PR-343-14607-R01 Miniaturized Gas Chromatography and Gas Quality Sensor. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), fevereiro de 2015. http://dx.doi.org/10.55274/r0010558.
Texto completo da fonteComparative 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, março de 2022. http://dx.doi.org/10.4271/2022-01-0740.
Texto completo da fonte