EPMITS: An Efficient Prediction Method Incorporating Trends and Shapes Features for Chemical Process Variables DOI

Yiming Bai,

Huawei Ye,

Jinsong Zhao

et al.

Computers & Chemical Engineering, Journal Year: 2024, Volume and Issue: 191, P. 108855 - 108855

Published: Aug. 24, 2024

Language: Английский

A spatial–temporal data-driven deep learning framework for enhancing ultra-short-term prediction of distributed photovoltaic power generation DOI Creative Commons
Gong Wang,

Shengyao Sun,

Siyuan Fan

et al.

International Journal of Electrical Power & Energy Systems, Journal Year: 2024, Volume and Issue: 160, P. 110125 - 110125

Published: July 11, 2024

Language: Английский

Citations

1
A Photovoltaic Fault Diagnosis Method Integrating Photovoltaic Power Prediction and EWMA Control Chart DOI Creative Commons
Jun Su,

Zhiyuan Zeng,

Chaolong Tang

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(17), P. 4263 - 4263

Published: Aug. 26, 2024

The inevitability of faults arises due to prolonged exposure photovoltaic (PV) power plants intricate environmental conditions. Therefore, fault diagnosis PV is crucial ensure the continuity and reliability generation. This paper proposes a method that integrates prediction an exponentially weighted moving average (EWMA) control chart. predicts based on meteorological factors using adaptive particle swarm algorithm-back propagation neural network (APSO-BPNN) model takes its error from actual value as quantity for EWMA chart then monitors values identify types. Finally, it verified by comparison with discrete rate (DR) analysis method. results showed coefficient determination proposed reached 0.98. Although DR can evaluate overall performance inverter faults, often fails point out specific location accurately. In contrast, monitor abnormal states such open short circuits accurately locate string where occurs.

Language: Английский

Citations

1
A new framework for ultra-short-term electricity load forecasting model using IVMD–SGMD two–layer decomposition and INGO–BiLSTM–TPA–TCN DOI

Xiwen Cui,

Xiaodan Zhang, Dongxiao Niu

et al.

Applied Soft Computing, Journal Year: 2024, Volume and Issue: 167, P. 112311 - 112311

Published: Oct. 10, 2024

Language: Английский

Citations

1
Cdte Pv Sustainability Study in China: Supply and Demand Perspective of Tellurium DOI
Bingchun Liu, Li Ming, Jiali Chen

et al.

Published: Jan. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Language: Английский

Citations

0
A coupled SWATPlus and BiLSTM tuning model for improved daily scale hydroclimate simulation in typical loess hilly areas of China DOI
Xianqi Zhang,

Jiawen Liu,

He Ren

et al.

Natural Hazards, Journal Year: 2024, Volume and Issue: unknown

Published: July 25, 2024

Language: Английский

Citations

0
Research on high precision online prediction of motion responses of a floating platform based on multi-mode fusion DOI
Jianwei Wang, Xiaofan Jin, Ze He

et al.

Applied Ocean Research, Journal Year: 2024, Volume and Issue: 151, P. 104150 - 104150

Published: Aug. 3, 2024

Language: Английский

Citations

0
EPMITS: An Efficient Prediction Method Incorporating Trends and Shapes Features for Chemical Process Variables DOI

Yiming Bai,

Huawei Ye,

Jinsong Zhao

et al.

Computers & Chemical Engineering, Journal Year: 2024, Volume and Issue: 191, P. 108855 - 108855

Published: Aug. 24, 2024

Language: Английский

Citations

0