Machine learning-based hybrid demand-side controller for renewable energy management

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

Piezoelectric energy harvester converting wind aerodynamic energy into electrical energy for microelectronic application.

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.