Literatura académica sobre el tema "Electricity network peak demands"
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Artículos de revistas sobre el tema "Electricity network peak demands"
Rokamwar, Kaustubh. "Feed- Forward Neural Network based Day Ahead Nodal Pricing". International Journal for Research in Applied Science and Engineering Technology 9, n.º VII (15 de julio de 2021): 1029–33. http://dx.doi.org/10.22214/ijraset.2021.36352.
Texto completoMarwan, Marwan y Pirman Pirman. "Mitigating Electricity a Price Spike under Pre-Cooling Method". International Journal of Electrical and Computer Engineering (IJECE) 6, n.º 3 (1 de junio de 2016): 1281. http://dx.doi.org/10.11591/ijece.v6i3.9597.
Texto completoMarwan, Marwan y Pirman Pirman. "Mitigating Electricity a Price Spike under Pre-Cooling Method". International Journal of Electrical and Computer Engineering (IJECE) 6, n.º 3 (1 de junio de 2016): 1281. http://dx.doi.org/10.11591/ijece.v6i3.pp1281-1293.
Texto completoKim, Hyunsoo, Jiseok Jeong y Changwan Kim. "Daily Peak-Electricity-Demand Forecasting Based on Residual Long Short-Term Network". Mathematics 10, n.º 23 (28 de noviembre de 2022): 4486. http://dx.doi.org/10.3390/math10234486.
Texto completoIfaei, P., J. K. Park, T. Y. Woo, C. H. Jeong y C. K. Yoo. "Leveraging media for demand control in an optimal network of renewable microgrids with hydrogen facilities in South Korea". IOP Conference Series: Earth and Environmental Science 1372, n.º 1 (1 de julio de 2024): 012005. http://dx.doi.org/10.1088/1755-1315/1372/1/012005.
Texto completoGupta, Rajat y Sahar Zahiri. "Examining daily electricity demand and indoor temperature profiles in UK social housing flats retrofitted with heat pumps". IOP Conference Series: Earth and Environmental Science 1363, n.º 1 (1 de junio de 2024): 012093. http://dx.doi.org/10.1088/1755-1315/1363/1/012093.
Texto completoNafkha, Rafik, Tomasz Ząbkowski y Krzysztof Gajowniczek. "Deep Learning-Based Approaches to Optimize the Electricity Contract Capacity Problem for Commercial Customers". Energies 14, n.º 8 (14 de abril de 2021): 2181. http://dx.doi.org/10.3390/en14082181.
Texto completoDejvises, Jackravut. "Energy Storage System Sizing for Peak Shaving in Thailand". ECTI Transactions on Electrical Engineering, Electronics, and Communications 14, n.º 1 (30 de noviembre de 2015): 49–55. http://dx.doi.org/10.37936/ecti-eec.2016141.171094.
Texto completoKauko, Hanne, Daniel Rohde y Armin Hafner. "Local Heating Networks with Waste Heat Utilization: Low or Medium Temperature Supply?" Energies 13, n.º 4 (20 de febrero de 2020): 954. http://dx.doi.org/10.3390/en13040954.
Texto completoAmin, Adil, Wajahat Ullah Khan Tareen, Muhammad Usman, Haider Ali, Inam Bari, Ben Horan, Saad Mekhilef, Muhammad Asif, Saeed Ahmed y Anzar Mahmood. "A Review of Optimal Charging Strategy for Electric Vehicles under Dynamic Pricing Schemes in the Distribution Charging Network". Sustainability 12, n.º 23 (4 de diciembre de 2020): 10160. http://dx.doi.org/10.3390/su122310160.
Texto completoTesis sobre el tema "Electricity network peak demands"
Mullen, Christopher. "Interactions between demand side response, demand recovery, peak pricing and electricity distribution network capacity margins". Thesis, University of Newcastle upon Tyne, 2018. http://hdl.handle.net/10443/4170.
Texto completoMorris, Peter J. "Improved residential electricity demand management through analysis of the customer perspective". Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/83943/12/83943%28thesis%29.pdf.
Texto completoCARON, MATHIEU. "Long-term forecasting model for future electricity consumption in French non-interconnected territories". Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299457.
Texto completoI samband med utfasningen av fossila källor för elproduktion i franska icke-sammankopplade territorier är kunskapen om framtida elbehov, särskilt årlig förbrukning och topplast på lång sikt, avgörande för att utforma ny infrastruktur för förnybar energi. Hittills är dessa territorier, främst öar som ligger i Stilla havet och Indiska oceanen, beroende av anläggningar med fossila bränslen. Energipolitiken planerar att på bred front utveckla förnybar energi för att gå mot en koldioxidsnål elmix till 2028. Denna avhandling fokuserar på den långsiktiga prognosen för elbehov per timme. En metod är utvecklad för att utforma och välja en modell som kan passa korrekt historisk data och för att förutsäga framtida efterfrågan inom dessa specifika områden. Historiska data analyseras först genom en klusteranalys för att identifiera trender och mönster, baserat på en k-means klusteralgoritm. Specifika kalenderinmatningar utformas sedan för att beakta dessa första observationer. Externa inmatningar, såsom väderdata, ekonomiska och demografiska variabler, ingår också. Prognosalgoritmer väljs utifrån litteraturen och de testas och jämförs på olika inmatade dataset. Dessa inmatade dataset, förutom den nämnda kalenderdatan och externa variabler, innehåller olika antal fördröjda värden, från noll till tre. Kombinationen av modell och inmatat dataset som ger de mest exakta resultaten på testdvärdena väljs för att förutsäga framtida elbehov. Införandet av fördröjda värden leder till betydande förbättringar i exakthet. Även om gradientförstärkande regression har de lägsta felen kan den inte upptäcka toppar av elbehov korrekt. Tvärtom, visar artificiella neurala nätverk (ANN) en stor förmåga att passa historiska data och visar en god noggrannhet på testuppsättningen, liksom för förutsägelse av toppefterfrågan. En generaliserad tillsatsmodell, en relativt ny modell inom energiprognosfältet, ger lovande resultat eftersom dess prestanda ligger nära den för ANN och representerar en intressant modell för framtida forskning. Baserat på de framtida värdena på indata, prognostiserades elbehovet 2028 i Réunion med ANN. Elbehovet förväntas nå mer än 2,3 GWh och toppbehovet cirka 485 MW. Detta motsvarar en tillväxt på 12,7% respektive 14,6% jämfört med 2019 års nivåer.
Hadjipaschalis, Constantinos. "An investigation of artificial neural networks applied to monthly electricity peak demand and energy forecasting". Thesis, Imperial College London, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286627.
Texto completoPaisios, Andreas. "Profiling and disaggregation of electricity demands measured in MV distribution networks". Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28777.
Texto completoYen, Ta-Pin y 顏大濱. "The Optimal Capacity Investigate to Suppress the Peak Loading of Micro-Grid Network with both of Wind Power and Solar Energy Electricity Generation". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/54712163890968264113.
Texto completo和春技術學院
電機工程研究所
97
The load characteristics of micro-grids in various areas are comprised by the typical industrial, commercial, agricultural and residential customers. By summation the power consumption of each typical customer to form the micro-grid network such as the industry-oriented, commerce-oriented, agriculture-oriented, resident-oriented and mixed type micro-grids. To suppress peak demand the distributed power supply has proven to be the best practice for micro-grid. Whereas main system is consist of many sub-systems and the loadings of main systems can be further categorized by micro-grids. Once the peak demand of micro-grids is suppressed by the distributed power supply of renewable energy, in the same view of point, the peak demand of the main systems is suppressed too. It proposed two kind of renewable energy distribution generation system to parallel into the micro-grid network to supply the power with Tai-power at the same time. Therefore, that can suppressed peak load to investigate the optimal timing strategy of the industrial-oriented, commercial-oriented, agricultural-oriented, residential-oriented and hybrid five combination demands.
Capítulos de libros sobre el tema "Electricity network peak demands"
Gorges, Tobias, Claudia Weißmann y Sebastian Bothor. "Small Electric Vehicles (SEV)—Impacts of an Increasing SEV Fleet on the Electric Load and Grid". En Small Electric Vehicles, 115–25. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65843-4_9.
Texto completoPalmer, Graham. "Electricity Networks: Managing Peak Demand". En SpringerBriefs in Energy, 31–44. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02940-5_4.
Texto completoBalwant, Manoj Kumar, Sai Rohan Basa y Rajiv Misra. "Reducing Peak Electricity Demands of a Cluster of Buildings with Multi-Agent Reinforcement Learning". En Springer Proceedings in Mathematics & Statistics, 307–17. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-15175-0_25.
Texto completoMorgan, Roger. "Displacement of Conventional Domestic Energy Demands by Electricity: Implications for the Distribution Network". En Sustainability in Energy and Buildings, 149–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17387-5_16.
Texto completoTrenz, André, Christoph Hoffmann, Christopher Lange y Richard Öchsner. "Increasing Energy Efficiency and Flexibility by Forecasting Production Energy Demand Based on Machine Learning". En Lecture Notes in Mechanical Engineering, 449–56. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28839-5_50.
Texto completoMolla, Tesfahun. "Smart Home Energy Management System". En Research Anthology on Smart Grid and Microgrid Development, 1132–47. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-3666-0.ch051.
Texto completoMolla, Tesfahun. "Smart Home Energy Management System". En Handbook of Research on New Solutions and Technologies in Electrical Distribution Networks, 191–206. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1230-2.ch011.
Texto completoWang, Qing, Xiaohu Zhu y Xiaozhuang Zhou. "Two-Layer Optimal Dispatching Strategy of Distribution Network Considering Demand Side Load". En Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia231208.
Texto completoM., Maheswari y Gunasekharan S. "Operation and Control of Microgrid". En Handbook of Research on Smart Power System Operation and Control, 412–33. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8030-0.ch018.
Texto completoM., Maheswari y Gunasekharan S. "Operation and Control of Microgrid". En Research Anthology on Smart Grid and Microgrid Development, 1437–58. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-3666-0.ch065.
Texto completoActas de conferencias sobre el tema "Electricity network peak demands"
Heidar Esfehani, Hamidreza y Martin Kriegel. "Modeling and Analysis of Energy Load Management Using Advanced Off-Peak Controlled Heat Pump System With Thermal Storage Under Different Time and Weather Conditions". En ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-52957.
Texto completoBello, Olumide y Landon Onyebueke. "Optimization of Smart Grid Solar Energy Application". En ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-36791.
Texto completoLiang, Yongtu, Jing Gong, Zhengling Kang y Fafu Yang. "Research on Operation Optimization of Multi-Product Pipeline". En 2004 International Pipeline Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/ipc2004-0597.
Texto completoManoharan, Yogesh, Alexander Headley, Keith Olson, Laurence Sombardier y Benjamin Schenkman. "Energy Storage Versus Demand Side Management for Peak-Demand Reduction at the Hawaii Ocean Science and Technology Park". En ASME 2021 15th International Conference on Energy Sustainability collocated with the ASME 2021 Heat Transfer Summer Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/es2021-63799.
Texto completoGajowniczek, Krzysztof, Rafik Nafkha y Tomasz Ząbkowski. "Electricity peak demand classification with artificial neural networks". En 2017 Federated Conference on Computer Science and Information Systems. IEEE, 2017. http://dx.doi.org/10.15439/2017f168.
Texto completoNagah, Mostafa y Mohamed Shaaban. "A Transactive Energy Microgrid Model using Blockchains". En International Technical Postgraduate Conference 2022. AIJR Publisher, 2022. http://dx.doi.org/10.21467/proceedings.141.31.
Texto completoTong, Zheng, Xiaoqi Wang, Dingwei Weng, Chunming He, Rui Yang, Zhigang Zhang y Sun Qiang. "Unconventional Fields Recovery Enabled By Large-Scale Green Power Supply Based on Multi Micro-Grids and Energy Storage Sharing with National Data Centers". En SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/215407-ms.
Texto completoKhoir, Khoir Lazuardi, Ade Rafsanjani Ade y Widi Hernowo Widi. "Technical and Economic Analysis of Mini LNG from the Utilization of Gas Flare by Optimization of Liquefaction Process". En ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/210883-ms.
Texto completoWill, Adrian. "Autonomous demand-side management system for peak shaving and energy optimization in electricity distribution networks". En 2017 International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions) (ICTUS). IEEE, 2017. http://dx.doi.org/10.1109/ictus.2017.8285986.
Texto completoRistić, Leposava. "ENERGY OPTIMIZATION OF INDUSTRIAL PROCESSES THROUGH ADVANCED USE OF CONTROLLED ELECTRICAL DRIVES AND POWER ELECTRONICS". En IX Regional Conference Industrial Energy and Environmental Protection in the Countries of Southeast Europe, 340–70. Society of Thermal Engineers of Serbia,, 2024. http://dx.doi.org/10.46793/ieep24.340r.
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