Performance improvement and control optimization in grid-integrated PV source with energy storage systems DOI

Lavanya Nandhyala,

Lalit Chandra Saikia,

Shinagam Rajshekar

et al.

Journal of Energy Storage, Journal Year: 2024, Volume and Issue: 103, P. 114517 - 114517

Published: Nov. 14, 2024

Language: Английский

Techno-economic analysis of a hybrid energy system for electrification using an off-grid solar/biogas/battery system employing HOMER: A case study in Vietnam DOI
Van Giao Nguyen, Prabhakar Sharma, Bhaskor Jyoti Bora

et al.

Process Safety and Environmental Protection, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 1, 2024

Language: Английский

Citations

10
A graph-factor-based random forest model for assessing and predicting carbon emission patterns - Pearl River Delta urban agglomeration DOI
Y.K. Ding, Yongping Li, Heran Zheng

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 469, P. 143220 - 143220

Published: July 20, 2024

Language: Английский

Citations

6
Improve energy conversion efficiency of μDMFC stack power system by optimal microscopic catalyst structures and power management DOI
Shuo Fang, Guowei Yang, Yuntao Liu

et al.

Energy, Journal Year: 2025, Volume and Issue: 315, P. 134361 - 134361

Published: Jan. 1, 2025

Language: Английский

Citations

0
Experimental simulation and analysis of Acacia Nilotica biomass gasification with XGBoost and SHapley Additive Explanations to determine the importance of key features DOI
Prabhu Paramasivam, Mansoor Alruqi, Ümit Ağbulut

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 136291 - 136291

Published: April 1, 2025

Language: Английский

Citations

0
Unlocking renewable energy potential: Harnessing machine learning and intelligent algorithms DOI Creative Commons
Thanh Tuan Le, Prabhu Paramasivam,

Elvis Adril

et al.

International Journal of Renewable Energy Development, Journal Year: 2024, Volume and Issue: 13(4), P. 783 - 813

Published: June 7, 2024

This review article examines the revolutionary possibilities of machine learning (ML) and intelligent algorithms for enabling renewable energy, with an emphasis on energy domains solar, wind, biofuel, biomass. Critical problems such as data variability, system inefficiencies, predictive maintenance are addressed by integration ML in systems. Machine improves solar irradiance prediction accuracy maximizes photovoltaic performance sector. help to generate electricity more reliably enhancing wind speed forecasts turbine efficiency. efficiency biofuel production optimizing feedstock selection, process parameters, yield forecasts. Similarly, models biomass provide effective thermal conversion procedures real-time management, guaranteeing increased operational stability. Even enormous advantages, quality, interpretability models, computing requirements, current systems still remain. Resolving these issues calls interdisciplinary cooperation, developments computer technology, encouraging legislative frameworks. study emphasizes vital role promoting sustainable efficient giving a thorough present applications highlighting continuing problems, outlining future prospects

Language: Английский

Citations

3
Performance improvement and control optimization in grid-integrated PV source with energy storage systems DOI

Lavanya Nandhyala,

Lalit Chandra Saikia,

Shinagam Rajshekar

et al.

Journal of Energy Storage, Journal Year: 2024, Volume and Issue: 103, P. 114517 - 114517

Published: Nov. 14, 2024

Language: Английский

Citations

1