Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Roope Sarala"'
Autor:
Jussi Kiljander, Roope Sarala, Jari Rehu, Daniel Pakkala, Pekka Paakkonen, Janne Takalo-Mattila, Klaus Kansala
Publikováno v:
IEEE Access, Vol 9, Pp 40755-40767 (2021)
Optimal management of demand-side flexibility in buildings is important for properly integrating large amounts of intermittent generation from windmills and photovoltaics. This paper proposes a novel Energy Management Agent (EMA) concept that can opt
Externí odkaz:
https://doaj.org/article/cba330657f8643a8a6a088b6f6b73c68
Publikováno v:
Future Internet, Vol 13, Iss 1, p 5 (2020)
The current approaches for energy consumption optimisation in buildings are mainly reactive or focus on scheduling of daily/weekly operation modes in heating. Machine Learning (ML)-based advanced control methods have been demonstrated to improve ener
Externí odkaz:
https://doaj.org/article/5aa252e76e4c439e8f6f71787cf36f25
Autor:
Marc-Oliver Pahl, Josef Schindler, Erkin Kirdan, Christian Lubben, Arpit Bajpai, Hanne Siikavirta, Satu Paiho, Jussi Numminen, Thomas Weisshaupt, Markus Duchon, Lars Wustrich, Jussi Kiljander, Roope Sarala, Olli Kilkki
Publikováno v:
Paiho, S, Kiljander, J, Sarala, R, Siikavirta, H, Kilkki, O, Bajpai, A, Duchon, M, Pahl, M-O, Wüstrich, L, Lübben, C, Kirdan, E, Schindler, J, Numminen, J & Weisshaupt, T 2021, ' Towards cross-commodity energy-sharing communities – A review of the market, regulatory, and technical situation ', Renewable and Sustainable Energy Reviews, vol. 151, 111568 . https://doi.org/10.1016/j.rser.2021.111568
Meeting the energy goals of the European Union requires new ways of managing energy. Decentralized energy management, cross-commodity energy production and usage optimization are promising means. Future neighbourhoods will include multiple forms of e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fb7d9b1d36d40b42eab98fb2703c5d7
https://cris.vtt.fi/ws/files/52267437/1_s2.0_S1364032121008467_main.pdf
https://cris.vtt.fi/ws/files/52267437/1_s2.0_S1364032121008467_main.pdf
Publikováno v:
Pääkkönen, P, Pakkala, D, Kiljander, J & Sarala, R 2021, ' Architecture for Enabling Edge Inference via Model Transfer from Cloud Domain in a Kubernetes Environment ', Future Internet, vol. 13, no. 1, 5, pp. 1-24 . https://doi.org/10.3390/fi13010005
Future Internet
Volume 13
Issue 1
Future Internet, Vol 13, Iss 5, p 5 (2021)
Future Internet
Volume 13
Issue 1
Future Internet, Vol 13, Iss 5, p 5 (2021)
The current approaches for energy consumption optimisation in buildings are mainly reactive or focus on scheduling of daily/weekly operation modes in heating. Machine Learning (ML)-based advanced control methods have been demonstrated to improve ener
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c87bd8ad11b9836598455fc5efe77863
https://cris.vtt.fi/en/publications/8d8344d4-7e2f-4af4-8f96-b955ccb61376
https://cris.vtt.fi/en/publications/8d8344d4-7e2f-4af4-8f96-b955ccb61376