Load forecasting model considering dynamic coupling relationships using structured dynamic-inner latent variables and broad learning system DOI
Ziwen Gu,

Yatao Shen,

Zijian Wang

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 133, P. 108180 - 108180

Published: March 11, 2024

Language: Английский

Binary firefly algorithm based reconfiguration for maximum power extraction under partial shading and machine learning approach for fault detection in solar PV arrays DOI

S. Saravanan,

R. Senthil Kumar,

P. Balakumar

et al.

Applied Soft Computing, Journal Year: 2024, Volume and Issue: 154, P. 111318 - 111318

Published: Feb. 2, 2024

Language: Английский

Citations

17
A review of the photothermal-photovoltaic energy supply system for building in solar energy enrichment zones DOI
Baichao Wang, Yanfeng Liu, Dengjia Wang

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 191, P. 114100 - 114100

Published: Dec. 3, 2023

Language: Английский

Citations

37
Enhanced solar photovoltaic power prediction using diverse machine learning algorithms with hyperparameter optimization DOI
Muhammad Faizan Tahir, Muhammad Zain Yousaf, Anthony Tzes

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 200, P. 114581 - 114581

Published: May 22, 2024

Language: Английский

Citations

13
Multi-time scale optimization study of integrated energy system considering dynamic energy hub and dual demand response DOI
Guanxiong Wang, Chongchao Pan, Wei Wu

et al.

Sustainable Energy Grids and Networks, Journal Year: 2024, Volume and Issue: 38, P. 101286 - 101286

Published: Feb. 3, 2024

Language: Английский

Citations

10
Optimal power management of a stand-alone hybrid energy management system: Hydro-photovoltaic-fuel cell DOI Creative Commons

M. Mossa Al-Sawalha,

Humaira Yasmin, Shakoor Muhammad

et al.

Ain Shams Engineering Journal, Journal Year: 2024, Volume and Issue: unknown, P. 103089 - 103089

Published: Oct. 1, 2024

Language: Английский

Citations

9
VAEneu: a new avenue for VAE application on probabilistic forecasting DOI Creative Commons
Alireza Koochali,

Ensiye Tahaei,

Andreas Dengel

et al.

Applied Intelligence, Journal Year: 2025, Volume and Issue: 55(6)

Published: Feb. 27, 2025

Language: Английский

Citations

1
Hybrid Machine learning models for PV output prediction: Harnessing Random Forest and LSTM-RNN for sustainable energy management in aquaponic system DOI

Tresna Dewi,

Elsa Nurul Mardiyati,

Pola Risma

et al.

Energy Conversion and Management, Journal Year: 2025, Volume and Issue: 330, P. 119663 - 119663

Published: March 1, 2025

Language: Английский

Citations

1
Thermo-kinetic behaviour of green synthesized nanomaterial enhanced organic phase change material: Model fitting approach DOI

B. Kalidasan,

A.K. Pandey, Belqasem Aljafari

et al.

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 348, P. 119439 - 119439

Published: Oct. 25, 2023

Language: Английский

Citations

18
Multi-objective sustainability optimization of a solar-based integrated energy system DOI

Zepeng Han,

Wei Han,

Yiyin Ye

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 202, P. 114679 - 114679

Published: June 28, 2024

Language: Английский

Citations

8
Multi-objective optimal sizing and design of renewable and diesel-based autonomous microgrids with hydrogen storage considering economic, environmental, and social uncertainties DOI Creative Commons
Oladimeji Lawrence Oyewole, Nnamdi Nwulu, Ewaoche John Okampo

et al.

Renewable Energy, Journal Year: 2024, Volume and Issue: 231, P. 120987 - 120987

Published: July 16, 2024

The multifaceted nature of human society necessitates the consideration various indicators when planning and designing energy systems. success systems is contingent on their ability to reliably meet demands while satisfying different objectives that align with societal needs. This paper presents multi-objective optimal design configuration hydrogen-storage-based microgrids electric load in remote regions considering economic, environmental social uncertainties. A comprehensive Mixed Integer Linear Programming (MILP) was adopted model microgrid consisting renewable (RES), hydrogen storage system (HESS), battery (BESS), diesel generator (DG). Advanced Interactive Multidimensional Modelling System (AIMMS) used perform deterministic robust optimisation special cost-greenhouse emissions minisation employment generation maximisation. study further performs a comparative analysis between hydrogen-based lithium-ion battery-based terms key objectives. In overall performance, photovoltaic (PV), wind turbine (WT), fuel cell (FC), electrolyser (EL) low-pressure tank (LPT) outplays other configurations considered total job factor, levelised cost electricity, penetration carbon emission reduction capability. Considering both solutions configuration, electricity ranges 0.131 0.169 $/kWh, lifetime varies from $2,002,100 $6,784,740, provision factor 0.339 0.447. Nevertheless, there need for investment its continued technological market penetration. good basis adoption

Language: Английский

Citations

8