Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Pourmousavi, S. Ali"'
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
The South Australia region of the Australian National Electricity Market (NEM) displays some of the highest levels of price volatility observed in modern electricity markets. This paper outlines an approach to probabilistic forecasting under these ex
Externí odkaz:
http://arxiv.org/abs/2311.07289
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
Energy usage optimal scheduling has attracted great attention in the power system community, where various methodologies have been proposed. However, in real-world applications, the optimal scheduling problems require reliable energy forecasting, whi
Externí odkaz:
http://arxiv.org/abs/2210.12990
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
Home energy management systems (HEMSs) are expected to become a crucial part of future smart grids. However, there is a limited number of studies that comprehensively assess the potential economic benefits of HEMS for consumers under real market cond
Externí odkaz:
http://arxiv.org/abs/2203.08639
Publikováno v:
In International Journal of Forecasting October-December 2024 40(4):1421-1437
A high number of electric vehicles (EVs) in the transportation sector necessitates an advanced scheduling framework for e-mobility ecosystem operation as a whole in order to overcome range anxiety and create a viable business model for charging stati
Externí odkaz:
http://arxiv.org/abs/2110.12123