E-LIB Suche - Ergebnisse für: Ali Pourmousavi Kani, S

1

A comprehensive day-ahead scheduling strategy for electric ..:

Tookanlou, Mahsa Bagheri ; Ali Pourmousavi Kani, S. ; Marzband, Mousa
International Journal of Electrical Power & Energy Systems. 131 (2021) - p. 106912 , 2021

Link: https://doi.org/10.1016/..

2

A comprehensive day-ahead scheduling strategy for electric ..:

Bagheri Tookanlou, Mahsa ; Ali Pourmousavi Kani, S ; Marzband, Mousa
https://nrl.northumbria.ac.uk/id/eprint/45932/1/Paper1_International%20Journal%20of%20Electrical%20Power%20%26%20Energy%20Systems.pdf. , 2021

Link: https://nrl.northumbria...

3

Improving Predictability of Renewable Generation Through Op..:

Kani, S. Ali Pourmousavi ; Wild, Phil ; Saha, Tapan Kumar
IEEE Transactions on Sustainable Energy. 11 (2020) 1 - p. 37-47 , 2020

Link: https://doi.org/10.1109/..

4

Point-based and probabilistic electricity demand prediction..:

Ghimire, Sujan ; Deo, Ravinesh C. ; Ali Pourmousavi, S...
Engineering Applications of Artificial Intelligence. 135 (2024) - p. 108702 , 2024

Link: https://doi.org/10.1016/..

5

A data-driven approach to estimate battery cell temperature..:

Hasan, Md Mehedi ; Ali Pourmousavi, S. ; Jahanbani Ardakani, Ali.
Journal of Energy Storage. 32 (2020) - p. 101879 , 2020

Link: https://doi.org/10.1016/..

6

Very short-term wind speed prediction: A new artificial neu..:

Pourmousavi Kani, S.A. ; Ardehali, M.M.
Energy Conversion and Management. 52 (2011) 1 - p. 738-745 , 2011

Link: https://doi.org/10.1016/..

7

Battery Scheduling Optimisation in Energy and Ancillary Ser..:

, In: Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems,

Karimi-Arpanahi, Sahand ; Kani, Ali Pourmousavi ; Mahdavi, Nariman - p. 226-236 , 2024

Link: https://dl.acm.org/doi/1..

8

Investigation of Short-Term Intermittency in Solar Irradian..:

, In: 2022 32nd Australasian Universities Power Engineering Conference (AUPEC),

Yao, Yuan ; Ertugrul, Nesimi ; Kani, Ali Pourmousavi - p. 1-6 , 2022

Link: https://doi.org/10.1109/..

9

Behind-the-Meter Energy Flexibility Modelling for Aggregato..:

, In: 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe),

Blomgren, Emma M. V. ; Ebrahimy, Razgar ; Pourmousavi Kani, Ali... - p. 1-6 , 2021

Link: https://doi.org/10.1109/..

10

Modelling Irrational Behaviour of Residential End Users Usi..:

Dinh, Nam Trong ; Karimi-Arpanahi, Sahand ; Yuan, Rui...
IEEE Transactions on Smart Grid. , 2024

Link: https://doi.org/10.1109/..

11

Unleashing the benefits of smart grids by overcoming the ch..:

Yuan, Rui ; Pourmousavi, S. Ali ; Soong, Wen L....
Cell Reports Physical Science. 5 (2024) 2 - p. 101830 , 2024

Link: https://doi.org/10.1016/..

12

A probabilistic forecast methodology for volatile electrici..:

Cornell, Cameron ; Dinh, Nam Trong ; Pourmousavi, S. Ali
International Journal of Forecasting. , 2024

Link: https://doi.org/10.1016/..

13

Probabilistic-based electricity demand forecasting with hyb..:

Ghimire, Sujan ; Deo, Ravinesh C. ; Casillas-Pérez, David...
Engineering Applications of Artificial Intelligence. 132 (2024) - p. 107918 , 2024

Link: https://doi.org/10.1016/..

14

A new zero-dimensional dynamic model to study the capacity ..:

Wang, Hao ; Pourmousavi, S. Ali ; Li, Yifeng...
Journal of Power Sources. 603 (2024) - p. 234428 , 2024

Link: https://doi.org/10.1016/..

15

A three-layer joint distributionally robust chance-constrai..:

Bagheri Tookanlou, Mahsa ; Pourmousavi, S. Ali ; Marzband, Mousa
Applied Energy. 331 (2023) - p. 120402 , 2023

Link: https://doi.org/10.1016/..