A5015507984- Electric Power System Optimization
- Water resources management and optimization
- Smart Grid Energy Management
- Water-Energy-Food Nexus Studies
- Water Systems and Optimization
- Optimal Power Flow Distribution
- Hydrology and Watershed Management Studies
- Integrated Energy Systems Optimization
- Flood Risk Assessment and Management
- Power Systems and Renewable Energy
- Hydrological Forecasting Using AI
- Smart Grid and Power Systems
- Microgrid Control and Optimization
- Energy Load and Power Forecasting
- Geoscience and Mining Technology
- Energy and Environment Impacts
- High-Voltage Power Transmission Systems
- Power System Optimization and Stability
- Hybrid Renewable Energy Systems
- Emotion and Mood Recognition
- Reservoir Engineering and Simulation Methods
- Geomechanics and Mining Engineering
- Advanced Computational Techniques and Applications
- COVID-19 Clinical Research Studies
- Risk and Portfolio Optimization
Dalian University of Technology
2015-2024
Zhengzhou University
2024
Hohai University
2024
Northeast Electric Power University
2024
Central Queensland University
2024
Aalborg University
2024
University of Technology Sydney
2024
Arizona State University
2024
Shaanxi Normal University
2022-2024
Ministry of Education of the People's Republic of China
2022
Reservoir monthly inflow is rather important for the security of long-term reservoir operation and water resource management. The main goal present research to develop forecasting models inflow. In this paper, artificial neural networks (ANN) support vector machine (SVM) are two basic heuristic methods, genetic algorithm (GA) employed choose parameters SVM. When data series, both approaches inclined acquire relatively poor performances. Thus, based on thought refined prediction by model...
Abstract. Inflow forecasting plays an essential role in reservoir management and operation. The impacts of climate change human activities have made accurate inflow prediction increasingly difficult, especially for longer lead times. In this study, a new hybrid forecast framework – using the ERA-Interim reanalysis data set as input adopting gradient-boosting regression trees (GBRT) maximal information coefficient (MIC) is developed multistep-ahead daily forecasting. Firstly, provides more...
The irregular forbidden zone (FZ) is a common phenomenon with giant hydropower plants developed in the past two decades China. Irregular shapes of FZs significantly challenge hydro unit commitment (HUC). This paper proposes novel MILP based framework for HUC considering FZ related constraints including constraint, effects linearization errors both net head and output, crossing constraint. In framework, constraint handled by optimal convex partitioning algorithm structure-based formulation...