A5049303518- Water resources management and optimization
- Electric Power System Optimization
- Water Systems and Optimization
- Water-Energy-Food Nexus Studies
- Smart Grid Energy Management
- Energy Load and Power Forecasting
- Hydrological Forecasting Using AI
- Optimal Power Flow Distribution
- Hydrology and Watershed Management Studies
- Integrated Energy Systems Optimization
- Flood Risk Assessment and Management
- Power Systems and Renewable Energy
- Smart Grid and Power Systems
- Reservoir Engineering and Simulation Methods
- Advanced Computational Techniques and Applications
- Distributed and Parallel Computing Systems
- Power System Optimization and Stability
- Machine Learning and ELM
- Grey System Theory Applications
- Power Systems and Technologies
- Cloud Computing and Resource Management
- Transportation Planning and Optimization
- Advanced Algorithms and Applications
- Advanced Sensor and Control Systems
- Power System Reliability and Maintenance
Dalian University of Technology
2015-2024
Dalian National Laboratory for Clean Energy
2023
Dalian Ocean University
2018-2021
Wuhan Ship Development & Design Institute
2017
Comillas Pontifical University
2017
University of Illinois Urbana-Champaign
2017
University of Hong Kong
2017
University of Castilla-La Mancha
2017
University of Southern California
2017
Wrocław University of Science and Technology
2017
Abstract Accurate time- and site-specific forecasts of streamflow reservoir inflow are important in effective hydropower management scheduling. Traditionally, autoregressive moving-average (ARMA) models have been used modelling water resource time series as a standard representation stochastic series. Recently, artificial neural network (ANN) approaches proven to be efficient when applied hydrological prediction. In this paper, the support vector machine (SVM) is presented promising method...
Abstract: This study presents an optimization model for a bus network design based on the coarse‐grain parallel ant colony algorithm (CPACA). It aims to maximize number of direct travelers per unit length, that is, traveler density, subject route length and nonlinear rate constraints (ratio shortest road distance between origin destination). CPACA is new optimal (1) develops strategy update increased pheromone, called Ant‐Weight, by which path‐searching activities ants are adjusted objective...
Operation rule plays an important role in the scientific management of hydropower reservoirs, because a scientifically sound operating can help operators make approximately optimal decision with limited runoff prediction information. In past decades, various effective methods have been developed by researchers all over world, but there are few publications evaluating performances different deriving reservoir operation rule. To achieve satisfying scheduling process triggered streamflow data,...
Accurate hydrologic time-series prediction plays an important role in modern water resource planning, supply management, environmental protection, and power system operation. In general, single-layer feedforward networks (SLFNs) can provide satisfactory forecasting results, but classical gradient-based learning algorithms are time consuming easily trapped into local optimums. As a new training method for SLFNs, extreme machine (ELM) has faster speed stronger nonlinear mapping than...
A batch of huge hydropower plants with multiple vibration zones have been developed in China. These varying net head, i.e., head-sensitive, seriously challenge the hydro unit commitment (HUC). This paper presents a MILP model for HUC head-sensitive reservoir and zones. The focus study is mainly on two head related constraints, namely performance curves constraints are linearized through use binary 0-1 integer variables. practical behavior demonstrated using real-world case studies. results...
Accurate annual runoff prediction plays an important role in modern water resources planning and management. Here, a hybrid model using evolutionary extreme learning machine variational mode decomposition (VMD) is developed to forecast time series. In the proposed method, VMD method first used decompose original streamflow into series of disjoint subcomponents; second, each subcomponent forecasted by constructing appropriate while gravitational search algorithm adopted tune parameters;...