A5065383812- Power System Optimization and Stability
- Cavitation Phenomena in Pumps
- Advanced Sensor and Control Systems
- Advanced Algorithms and Applications
- Machine Fault Diagnosis Techniques
- Water Systems and Optimization
- Microgrid Control and Optimization
- Fault Detection and Control Systems
- Power Systems and Renewable Energy
- Hydraulic and Pneumatic Systems
- Engineering Diagnostics and Reliability
- Energy Load and Power Forecasting
- Vibration and Dynamic Analysis
- Optimal Power Flow Distribution
- Electric Power System Optimization
- Geotechnical Engineering and Underground Structures
- Smart Grid and Power Systems
- Advanced Computational Techniques and Applications
- Integrated Energy Systems Optimization
- Hybrid Renewable Energy Systems
- Smart Grid Energy Management
- Industrial Technology and Control Systems
- High-Voltage Power Transmission Systems
- Power Systems and Technologies
- Gear and Bearing Dynamics Analysis
North China University of Water Resources and Electric Power
2022-2025
Southwest Petroleum University
2023-2024
Northwestern Polytechnical University
2006-2024
Hubei Provincial Water Resources and Hydropower Planning Survey and Design Institute
2024
Huazhong University of Science and Technology
2021-2023
Southwest Jiaotong University
2008-2022
Nanjing University of Aeronautics and Astronautics
2021
Ministry of Industry and Information Technology
2021
Beijing University of Chemical Technology
2021
Wuhan University
2005-2020
To deal with pattern synthesis of antenna arrays, a chaotic particle swarm optimization (CPSO) is presented to avoid the premature convergence.By fusing ergodic and stochastic chaos, novel algorithm explores global optimum comprehensive learning strategy.The searching region can be adjusted adaptively.To evaluate performance CPSO, several representative benchmark functions are minimized using various algorithms.Numerical results demonstrate that proposed approach improves significantly, in...
In order to enhance the overall power generation efficiency of cascade hydropower, it is essential conduct modelling optimization its in-plant operation. However, existing studies have devoted minimal attention detailed turbine operating performance curves within economic operation model. This represents a significant challenge practical application results. study presents refined model hydraulic curve, which was established by combining particle swarm (PSO) algorithm and backpropagation...
Parameter estimation is an important part in the modeling of a hydro-turbine regulation system (HTRS), and results determine final accuracy model. A normally non-minimum phase with strong nonlinearity time-varying parameters. For parameter such nonlinear system, heuristic algorithms are more advantageous than traditional mathematical methods. However, most heuristics based their improved versions not adaptive, which means that appropriate parameters algorithm need to be manually found keep...
To meet the needs of energy storage system configuration with distributed power supply and its operation in active distribution network (ADN), establish dynamics all-vanadium redox flow battery (BESS). On this basis, an ADN strategy is proposed to stabilise fluctuation system. The model optimising objectives such as fixed cost, operating direct economic benefit environmental BESS life cycle constructed, installation capacity, position are used decision variables, which solved by dynamic...
Deterioration trend prediction of hydropower units helps to detect abnormal conditions and can prevent early failures. The reliability accuracy the results are crucial ensure safe operation promote stable power system. In this paper, long short-term neural network (LSTM) is introduced, a comprehensive deterioration index (CDI) model based on time–frequency domain proposed, situation improved. Firstly, time–domain health (THM) constructed with back-propagation (BPNN) condition parameters...
Taking the full network observability of power system operation states and least number phasor measurement units (PMUs) as an objective function, improved optimal PMU placement algorithm is proposed. In this algorithm, genetic (GA) effectively combined with particle swarm optimization (PSO) to ensure that solution can be obtained. The cross aberrance operations in GA are used PMUs scheme decrease searching scope PSO method improve quality initial placement, thus solving process accelerated....
Abstract Fault diagnosis is an effective tool to ensure safe operation of machinery and avoid serious accidents. As most currently used fault methods usually employ mapping relationship established by training samples their labels achieve classification testing samples, it difficult for them under the condition incomplete sample types. In addition, previous studies focus on feature extraction single-channel vibration signal, which cannot get complete information. To solve above problems, a...
De-noising of signal processing is crucial for fault diagnosis in order to successfully conduct feature extraction and an efficient method accurate determination cause. In this paper, the empirical mode decomposition (EMD) thresholding-based de-noising probabilistic neural network (PNN) are respectively used vibration rotor compared with wavelet technology back propagation (BPNN). The results show that clear iterative EMD interval thresholding performs better than signal, avoids basis level....