Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Oscar De Somer"'
Autor:
Milo Broekmans, Dominic Ectors, Ana Soares, Jan Goyvaerts, Dennis van Goch, Filip Aben, Koen Vanthournout, Fred Spiessens, Oscar De Somer
Publikováno v:
IEEE Transactions on Power Systems. 34:4119-4127
This paper presents results from a field test that uses a method for transactive control based on dual decomposition. The proposed approach is used to activate flexibility at the residential level to resolve any forecasted bottlenecks and power surpl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e9cca9a06159645342ba2bff538a0b8
https://doi.org/10.1109/tpwrs.2018.2809440
https://doi.org/10.1109/tpwrs.2018.2809440
Using reinforcement learning for maximizing residential self-consumption – Results from a field test
Publikováno v:
Energy and Buildings. 207:109608
This paper presents the results from a real residential field test in which one of the objectives was to maximize the instantaneous self-consumption of the local photovoltaic production. The field test was part of the REnnovates project and was condu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d92659605da972daca8fb7de6623195
https://doi.org/10.1016/j.enbuild.2019.109608
https://doi.org/10.1016/j.enbuild.2019.109608
Publikováno v:
ISGT Europe
This paper demonstrates a data-driven control approach for demand response in real-life residential buildings. The objective is to optimally schedule the heating cycles of the Domestic Hot Water (DHW) buffer to maximize the self-consumption of the lo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3080708f9eea5a467330c7c25bccc189
http://arxiv.org/abs/1703.05486
http://arxiv.org/abs/1703.05486
Autor:
Dirk Vanhoudt, Davy Geysen, Oscar De Somer, Christian Johansson, Markus Bergkvist, Niklas Lavesson
Publikováno v:
Energy Procedia
Heat demand forecasting is in one form or another an integrated part of most optimisation solutions for district heating and cooling (DHC). Since DHC systems are demand driven, the ability to forecast this behaviour becomes an important part of most
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec68b1f0ddc0a9a4ba7fce4c9edee07c