Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Padmanabhan, Sanjeevikumar"'
Autor:
Shiladitya Acharya, Sabbir Ahmed, Bittab Biswas, Sukanta Bose, Susanta Chakraborty, Partha Chaudhuri, Amit Kumar Das, Gourab Das, Poonam B. Dhabai, Pijush Dutta, Gaurav Dwivedi, Adarsh Gaurav, Heba Ahmed Hassan, M. Shahidul Islam, Md. Mehedi Islam, Bhola Jha, M. Shamim Kaiser, Ramani Kannan, Nishant Raj Kapoor, Sujeet Kesharvani, Mohammad Khoobani, Aman Kumar, Anuj Kumar, Krishna Kumar, Narendra Kumar, Yatindra Kumar, Jia Liu, Siva Ramakrishna Madeti, Santanu Maity, Madhurima Majumder, Nabin Chandra Mandal, Anupam Nandi, Morteza Azimi Nasab, Kamaraj Nithyanandhan, Biplab Pal, Manoj Kumar Panda, Tamalika Panda, Md. Sazzadur Rahman, Sourav Sadhukhan, Hiranmay Saha, Gaurav Saini, R.P. Saini, Tina Samavat, Padmanabhan Sanjeevikumar, Sakshi Sarathe, Samir Settoul, Rachna Shah, Neeraj Tiwari, Mohammad Zand, Mohamed Zellagui, Yuekuan Zhou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76eba5099d5146326e1658985acd7325
https://doi.org/10.1016/b978-0-323-91228-0.09992-4
https://doi.org/10.1016/b978-0-323-91228-0.09992-4
Autor:
Padmanabhan Sanjeevikumar, Tina Samavat, Morteza Azimi Nasab, Mohammad Zand, Mohammad Khoobani
Publikováno v:
Padmanaban, S, Samavat, T, Nasab, M A, Zand, M & Khoobani, M 2022, Machine learning-based hybrid demand-side controller for renewable energy management . in K Kumar, R S Rao, O Kaiwartya, M S Kaiser & S Padmanaban (eds), Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies . Elsevier, Amsterdam, pp. 291-307 . https://doi.org/10.1016/B978-0-323-91228-0.00003-3
In power systems, maintaining the equivalency of supply and demand is the fundamental rule for a reliable power generator system to feed consumers consistently. This is the energy management (EM) desired goal, which has become an important field of i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa7afb78f1b7844c2ff046fc289dfd6e
https://pure.au.dk/portal/da/publications/machine-learningbased-hybrid-demandside-controller-for-renewable-energy-management(d175b6ae-29e0-4bf8-9535-e05b9bb6aded).html
https://pure.au.dk/portal/da/publications/machine-learningbased-hybrid-demandside-controller-for-renewable-energy-management(d175b6ae-29e0-4bf8-9535-e05b9bb6aded).html
Akademický článek
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Autor:
R, Sitharthan1 sithukky@gmail.com, S, Yuvaraj2, Padmanabhan, Sanjeevikumar3, Holm‐Nielsen, Jens Bo3, M, Sujith4, M, Rajesh5, N, Prabaharan6, K, vengatesan5
Publikováno v:
IET Renewable Power Generation (Wiley-Blackwell). Jul2021, Vol. 15 Issue 9, p1968-1975. 8p.
Publikováno v:
2015 IEEE International Conference on Signal Processing, Informatics, Communication & Energy Systems (SPICES); 2015, p1-7, 7p
Publikováno v:
2015 International Conference on Signal Processing, Computing & Control (ISPCC); 2015, piv-xii, 9p
Publikováno v:
2013 IEEE International Conference on Signal Processing, Computing & Control (ISPCC); 2013, p1-8, 8p
Publikováno v:
International Conference on Renewable Energies for Developing Countries 2014; 2014, p1-3, 3p
Publikováno v:
2013 IEEE 7th International Power Engineering & Optimization Conference (PEOCO); 2013, p6-7, 2p
Autor:
Krishna Kumar, Ram Shringar Rao, Omprakash Kaiwartya, Shamim Kaiser, Sanjeevikumar Padmanaban
Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload ene