Zobrazeno 1 - 10
of 82
pro vyhledávání: '"Emanuele Ogliari"'
Autor:
Giampaolo Manzolini, Andrea Fusco, Domenico Gioffrè, Silvana Matrone, Riccardo Ramaschi, Marios Saleptsis, Riccardo Simonetti, Filip Sobic, Michael James Wood, Emanuele Ogliari, Sonia Leva
Publikováno v:
Forecasting, Vol 6, Iss 3, Pp 591-615 (2024)
The electrification of the transport sector together with large renewable energy deployment requires powerful tools to efficiently use energy assets and infrastructure. In this framework, the forecast of electric vehicle demand and solar photovoltaic
Externí odkaz:
https://doaj.org/article/95873e887af442439354fc265366a4be
Publikováno v:
IEEE Access, Vol 12, Pp 141580-141593 (2024)
Effective microgrid management necessitates sophisticated strategies to optimally balance grid components and minimize power exchanges with the main grid. Central to this challenge is the energy storage system, typically comprised of lithium-ion batt
Externí odkaz:
https://doaj.org/article/b7f1ee4159c74ba5931bf813798597f8
Publikováno v:
IEEE Access, Vol 12, Pp 80244-80254 (2024)
In this study, a novel Machine learning-based method for the joint State of Charge and State of Health estimation of Lithium Batteries that tackle real-world applications and with Bayesian Hyperparameter optimization is proposed. The estimated State
Externí odkaz:
https://doaj.org/article/99bc61926a65486bb80e3f470bc44d5f
Publikováno v:
IEEE Access, Vol 12, Pp 993-1004 (2024)
State of Charge (SOC) estimation is vital for battery management systems (BMS), impacting battery efficiency and lifespan. Accurate SOC estimation is challenging due to battery complexity and limited data for training Machine Learning based models. T
Externí odkaz:
https://doaj.org/article/7492e2b710eb445fbcf56bdf5d3d56ca
Publikováno v:
Forecasting, Vol 5, Iss 3, Pp 576-599 (2023)
In recent years, there has been a noticeable shift towards electric mobility and an increasing emphasis on integrating renewable energy sources. Consequently, batteries and their management have been prominent in this context. A vital aspect of the B
Externí odkaz:
https://doaj.org/article/1a3dc736896e4e959eacb78dc9ac6d36
Autor:
Michele Bellomo, Spyridon Giazitzis, Susheel Badha, Filippo Rosetti, Alberto Dolara, Emanuele Ogliari
Publikováno v:
Batteries, Vol 10, Iss 8, p 292 (2024)
This study presents methods to handle deep learning regressions with input and output sequences of different lengths. We discuss the Autoregressive one-step prediction framework and introduce an innovative one-time multi-step (OTMS) prediction approa
Externí odkaz:
https://doaj.org/article/5dc674f8748444338bbdfef00921d34b
Publikováno v:
Applied Sciences, Vol 14, Iss 13, p 5714 (2024)
To fully exploit the advantages of bifacial PV (bPV) modules and understand their performance under real-world conditions, a comprehensive investigation was conducted. It was focused on bPV installations with some mounting constraints, as in industri
Externí odkaz:
https://doaj.org/article/36603ca7f2ea476ba71c5a5f1bca6ed5
Publikováno v:
Forecasting, Vol 5, Iss 1, Pp 297-314 (2023)
Optimal behind-the-meter energy management often requires a day-ahead electric load forecast capable of learning non-linear and non-stationary patterns, due to the spatial disaggregation of loads and concept drift associated with time-varying physics
Externí odkaz:
https://doaj.org/article/748378d6fa2d43e5b03aad086347d934
Publikováno v:
IEEE Access, Vol 11, Pp 6273-6283 (2023)
The increasing adoption of electric vehicles poses new problems for the electrical distribution network. For this reason, proper electric vehicle forecasting will be of fundamental importance for a predictive energy management system, which could gre
Externí odkaz:
https://doaj.org/article/e1d53f962d944c5ea1e133cd8f0974ac
Publikováno v:
Forecasting, Vol 4, Iss 1, Pp 338-348 (2022)
This work proposes and evaluates a method for the nowcasting of solar irradiance variability in multiple time horizons, namely 5, 10, and 15 min ahead. The method is based on a Convolutional Neural Network structure that exploits infrared sky images
Externí odkaz:
https://doaj.org/article/cf09653da694495d946143abdfb22b74