Jinghao Wang

Stipendiat
ved Institutt for elektrisk energi ved Norges teknisk-naturvitenskapelige universitet

Resultater Resultater

Exploring the application of machine-learning techniques in the next generation of long-term hydropower-thermal scheduling.

Wang, Jinghao; Yousefi, Mojtaba; Rajasekharan, Jayaprakash; Arghandeh, Reza; Farahmand, Hossein. 2024, IET Renewable Power Generation. NTNU, HVLVitenskapelig artikkel

TransNILM: A Transformer-based Deep Learning Model for Non-intrusive Load Monitoring.

XU, CHENG; Zhao, Meng; Zhang, Jianhua; Wang, Jinghao; Pan, Xueping; Liu, Xiufeng. 2022, IEEE Xplore Digital Library. TUT, DTU, HHU, NTNUVitenskapelig artikkel

Machine learning-based forepart block decomposition model as a precursor to the Scenario fan problem.

Wang, Jinghao. 2022, International Conference on Hydropower Scheduling in Competitive Electricity markets. NTNUFaglig foredrag

Short-term inflow forecasting in a dam-regulated river in Southwest Norway using causal variational mode decomposition.

Yousefi, Mojtaba; Wang, Jinghao; Høivik, Øivind Fandrem; Rajasekharan, Jayaprakash; Wierling, August Hubert; Farahmand, Hossein; Arghandeh, Reza. 2023, Scientific Reports. NTNU, LYSE, HVLVitenskapelig artikkel

Self-organizing maps for scenario reduction in long-term hydropower scheduling.

Wang, Jinghao; Yousefi, Mojtaba; Cheng, Xiaomei; Rajasekharan, Jayaprakash; Arghandeh, Reza; Pan, Xueping; Farahmand, Hossein. 2022, IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society. NTNU, HVLVitenskapelig foredrag

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