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pro vyhledávání: '"Liisberg, Jon"'
Detecting behind-the-meter (BTM) equipment and major appliances at the residential level and tracking their changes in real time is important for aggregators and traditional electricity utilities. In our previous work, we developed a systematic solut
Externí odkaz:
http://arxiv.org/abs/2401.03352
Autor:
Yuan, Rui, Pourmousavi, S. Ali, Soong, Wen L., Black, Andrew J., Liisberg, Jon A. R., Lemos-Vinasco, Julian
Many smart grid applications involve data mining, clustering, classification, identification, and anomaly detection, among others. These applications primarily depend on the measurement of similarity, which is the distance between different time seri
Externí odkaz:
http://arxiv.org/abs/2310.12399
Autor:
Dinh, Nam Trong, Karimi-Arpanahi, Sahand, Pourmousavi, S. Ali, Guo, Mingyu, Lemos-Vinasco, Julian, Liisberg, Jon A. R.
Optimal battery sizing studies tend to overly simplify the practical aspects of battery operation within the battery sizing framework. Such assumptions may lead to a suboptimal battery capacity, resulting in significant financial losses for a battery
Externí odkaz:
http://arxiv.org/abs/2310.02494
Autor:
Dinh, Nam Trong, Karimi-Arpanahi, Sahand, Yuan, Rui, Pourmousavi, S. Ali, Guo, Mingyu, Liisberg, Jon A. R., Lemos-Vinasco, Julian
Demand response (DR) plays a critical role in ensuring efficient electricity consumption and optimal use of network assets. Yet, existing DR models often overlook a crucial element, the irrational behaviour of electricity end users. In this work, we
Externí odkaz:
http://arxiv.org/abs/2309.09012
Most literature surrounding optimal bidding strategies for aggregators in European day-ahead market (DAM) considers only hourly orders. While other order types (e.g., block orders) may better represent the temporal characteristics of certain sources
Externí odkaz:
http://arxiv.org/abs/2208.12431
Autor:
Bacher, Peder, Bergsteinsson, Hjörleifur G., Frölke, Linde, Sørensen, Mikkel L., Lemos-Vinasco, Julian, Liisberg, Jon, Møller, Jan Kloppenborg, Nielsen, Henrik Aalborg, Madsen, Henrik
Publikováno v:
The R Journal, 15/1 (2023) 172-194
Systems that rely on forecasts to make decisions, e.g. control or energy trading systems, require frequent updates of the forecasts. Usually, the forecasts are updated whenever new observations become available, hence in an online setting. We present
Externí odkaz:
http://arxiv.org/abs/2109.12915
Publikováno v:
Engineering Applicationsof Artificial Intelligence (2022) 105588
Modern power systems are experiencing the challenge of high uncertainty with the increasing penetration of renewable energy resources and the electrification of heating systems. In this paradigm shift, understanding electricity users' demand is of ut
Externí odkaz:
http://arxiv.org/abs/2109.13732
Autor:
Yuan, Rui, Pourmousavi, S. Ali, Soong, Wen L., Black, Andrew J., Liisberg, Jon A.R., Lemos-Vinasco, Julian
Publikováno v:
In Cell Reports Physical Science 21 February 2024 5(2)
Akademický článek
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Publikováno v:
In Engineering Applications of Artificial Intelligence January 2023 117 Part A