VoltaVistaMan: Energy Dynamics Intelligent Predictive Analysis Utilizing Bayesian Hyper-Tuned Neural Networks – A Case Study on Switzerland's National Electricity Demand DOI
Ashkan Safari, Hamed Kharrati, Afshin Rahimi

et al.

Published: June 17, 2024

Language: Английский

Carbon neutrality and hydrogen energy systems DOI
Solomon Evro, Babalola Aisosa Oni, Olusegun Stanley Tomomewo

et al.

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 78, P. 1449 - 1467

Published: July 5, 2024

Language: Английский

Citations

97
Exploring hydrogen energy systems: A comprehensive review of technologies, applications, prevailing trends, and associated challenges DOI
Muhammad Kamran, Marek Turzyński

Journal of Energy Storage, Journal Year: 2024, Volume and Issue: 96, P. 112601 - 112601

Published: June 28, 2024

Language: Английский

Citations

42
Overview of energy modeling requirements and tools for future smart energy systems DOI Creative Commons
Hassan Majidi-Gharehnaz, Mohammad Mohsen Hayati, Christian Breyer

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 212, P. 115367 - 115367

Published: Jan. 22, 2025

Language: Английский

Citations

1
Energy Intelligence: A Systematic Review of Artificial Intelligence for Energy Management DOI Creative Commons
Ashkan Safari, Mohammadreza Daneshvar, Amjad Anvari‐Moghaddam

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(23), P. 11112 - 11112

Published: Nov. 28, 2024

Artificial intelligence (AI) and machine learning (ML) can assist in the effective development of power system by improving reliability resilience. The rapid advancement AI ML is fundamentally transforming energy management systems (EMSs) across diverse industries, including areas such as prediction, fault detection, electricity markets, buildings, electric vehicles (EVs). Consequently, to form a complete resource for cognitive techniques, this review paper integrates findings from more than 200 scientific papers (45 reviews 155 research studies) addressing utilization EMSs its influence on sector. additionally investigates essential features smart grids, big data, their integration with EMS, emphasizing capacity improve efficiency reliability. Despite these advances, there are still additional challenges that remain, concerns regarding privacy integrating different systems, issues related scalability. finishes analyzing problems providing future perspectives ongoing use EMS.

Language: Английский

Citations

8
NeuroQuMan: quantum neural network-based consumer reaction time demand response predictive management DOI
Ashkan Safari, Mohammad Ali Badamchizadeh

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(30), P. 19121 - 19138

Published: Aug. 2, 2024

Language: Английский

Citations

2
FaultyVoltaMan: Ensemble Learning Model for Accurate Fault Detection and Classification of PV-Integrated Systems DOI
Ashkan Safari, Hamed Kharrati, Afshin Rahimi

et al.

Published: June 17, 2024

Language: Английский

Citations

1
A Survey on Wind Speed Forecasting in Smart Grids Using Deep Learning Algorithm Applications DOI

Hassan Majidi-Gharehnaz,

Mohammad Mohsen Hayati,

Reza Khalilzadeh

et al.

Published: April 23, 2024

Language: Английский

Citations

0
VoltaVistaMan: Energy Dynamics Intelligent Predictive Analysis Utilizing Bayesian Hyper-Tuned Neural Networks – A Case Study on Switzerland's National Electricity Demand DOI
Ashkan Safari, Hamed Kharrati, Afshin Rahimi

et al.

Published: June 17, 2024

Language: Английский

Citations

0