Power generation efficiency and resources saving of the hydropower industry using the extended data based convolutional neural network DOI
Jiajun Huang,

Peihao Zheng,

Xuan Hu

и другие.

Renewable Energy, Год журнала: 2025, Номер unknown, С. 122541 - 122541

Опубликована: Янв. 1, 2025

Язык: Английский

A novel method based on time series ensemble model for hourly photovoltaic power prediction DOI

Zenan Xiao,

Xiaoqiao Huang, Jun Liu

и другие.

Energy, Год журнала: 2023, Номер 276, С. 127542 - 127542

Опубликована: Апрель 20, 2023

Язык: Английский

Процитировано

45
A new paradigm based on Wasserstein Generative Adversarial Network and time-series graph for integrated energy system forecasting DOI
Zhirui Tian, Mei Gai

Energy Conversion and Management, Год журнала: 2025, Номер 326, С. 119484 - 119484

Опубликована: Янв. 13, 2025

Язык: Английский

Процитировано

2
An ensemble model for monthly runoff prediction using least squares support vector machine based on variational modal decomposition with dung beetle optimization algorithm and error correction strategy DOI
Dongmei Xu, Zong Li, Wenchuan Wang

и другие.

Journal of Hydrology, Год журнала: 2023, Номер 629, С. 130558 - 130558

Опубликована: Дек. 7, 2023

Язык: Английский

Процитировано

39
A 3D ConvLSTM-CNN network based on multi-channel color extraction for ultra-short-term solar irradiance forecasting DOI
Xiaoqiao Huang, Jun Liu,

Shaozhen Xu

и другие.

Energy, Год журнала: 2023, Номер 272, С. 127140 - 127140

Опубликована: Март 8, 2023

Язык: Английский

Процитировано

31
Novel optimization approach for realized volatility forecast of stock price index based on deep reinforcement learning model DOI Open Access
Yuanyuan Yu, Yu Lin,

Xianping Hou

и другие.

Expert Systems with Applications, Год журнала: 2023, Номер 233, С. 120880 - 120880

Опубликована: Июнь 22, 2023

Язык: Английский

Процитировано

27
An interpretable horizontal federated deep learning approach to improve short-term solar irradiance forecasting DOI

Zenan Xiao,

Bixuan Gao, Xiaoqiao Huang

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер 436, С. 140585 - 140585

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

12
A coupled framework for power load forecasting with Gaussian implicit spatio temporal block and attention mechanisms network DOI
Dezhi Liu, Xuan Lin,

Hanyang Liu

и другие.

Computers & Electrical Engineering, Год журнала: 2025, Номер 123, С. 110263 - 110263

Опубликована: Март 20, 2025

Язык: Английский

Процитировано

1
Week-ahead hourly solar irradiation forecasting method based on ICEEMDAN and TimesNet networks DOI

He Zhao,

Xiaoqiao Huang,

Zenan Xiao

и другие.

Renewable Energy, Год журнала: 2023, Номер 220, С. 119706 - 119706

Опубликована: Ноя. 25, 2023

Язык: Английский

Процитировано

19
A comprehensive approach for PV wind forecasting by using a hyperparameter tuned GCVCNN-MRNN deep learning model DOI
Adeel Feroz Mirza, Majad Mansoor, Muhammad Usman

и другие.

Energy, Год журнала: 2023, Номер 283, С. 129189 - 129189

Опубликована: Сен. 25, 2023

Язык: Английский

Процитировано

18
Recent Trends and Issues of Energy Management Systems Using Machine Learning DOI Creative Commons
Seongwoo Lee, Joonho Seon,

Byung-Sun Hwang

и другие.

Energies, Год журнала: 2024, Номер 17(3), С. 624 - 624

Опубликована: Янв. 27, 2024

Energy management systems (EMSs) are regarded as essential components within smart grids. In pursuit of efficiency, reliability, stability, and sustainability, an integrated EMS empowered by machine learning (ML) has been addressed a promising solution. A comprehensive review current literature trends conducted with focus on key areas, such distributed energy resources, information systems, storage trading risk demand-side grid automation, self-healing systems. The application ML in is discussed, highlighting enhancements data analytics, improvements system facilitation efficient distribution optimization flow. Moreover, architectural frameworks, operational constraints, challenging issues ML-based explored focusing its effectiveness, suitability. This paper intended to provide valuable insights into the future EMS.

Язык: Английский

Процитировано

8