scholarly journals Intelligent Diagnosis Technology of Wind Turbine Drive System based on Neural Network

2021 ◽  
Vol 19 ◽  
pp. 289-296
Author(s):  
Wei Yang ◽  
Yi Chai ◽  
Jie Zheng ◽  
Jie Liu
Keyword(s):  
Neural Network ◽  
Power Generation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Power ◽  
Recognition Rate ◽  
Back Propagation ◽  
Wind Power Generation ◽  
Drive System ◽  
Turbine Drive

The seriousness of air pollution appears to be the importance of wind energy as a non-polluting energy source. Today, the use of wind power has become a trend for new countries to develop new energy sources. Wind turbines are the key equipment for converting wind energy into electrical energy, the quality of the state directly affects the efficiency of wind power generation. Therefore, how to effectively diagnose the wind turbine drive system is the guarantee of wind power generation. This paper establishes a fault diagnosis method for wind turbine drive based on vibration characteristics, by wavelet packet decomposition of vibration signals. The feature extraction is carried out and back propagation neural network is used for classification research. Finally, the simulation results show that the recognition rate is over 90%, which verify effectiveness of the proposed method.

scholarly journals Some Issues Related to Power Generation Using Wind Energy Conversion Systems: An Overview

2005 ◽  
Vol 3 (2) ◽  
Author(s):  
Dr. R. C. Bansal ◽  
Dr. Ahmed F Zobaa ◽  
Dr. R. K. Saket
Keyword(s):  
Power Generation ◽  
Wind Energy ◽  
Energy Conversion ◽  
Wind Turbine ◽  
Wind Power ◽  
Reactive Power ◽  
Wind Power Generation ◽  
Wind Energy Conversion ◽  
Wind Energy Conversion Systems ◽  
Energy Conversion Systems

Design and successful operation of wind energy conversion systems (WECs) is a very complex task and requires the skills of many interdisciplinary skills, e.g., civil, mechanical, electrical and electronics, geography, aerospace, environmental etc. Performance of WECs depends upon subsystems like wind turbine (aerodynamic), gears (mechanical), generator (electrical); whereas the availability of wind resources are governed by the climatic conditions of the region concerned for which wind survey is extremely important to exploit wind energy. This paper presents a number of issues related to the power generation from WECs e.g. factors affecting wind power, their classification, choice of generators, main design considerations in wind turbine design, problems related with grid connections, wind-diesel autonomous hybrid power systems, reactive power control of wind system, environmental aspects of power generation, economics of wind power generation, and latest trend of wind power generation from off shore sites.

scholarly journals Techno-economic analysis and modelling of the feasibility of wind energy in Kuwait

2022 ◽  
Vol 7 ◽  
pp. 9
Author(s):  
Seyed Amir Kaboli ◽  
Reyhaneh Nazmabadi
Keyword(s):  
Power Generation ◽  
Economic Analysis ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Power ◽  
Power Plants ◽  
Clean Energy ◽  
Wind Power Generation ◽  
Generation Capacity ◽  
The Impact

There continues to be significant attention and investment in wind power generation, which can supply a high percentage of the global demand for renewable energy if harvested efficiently. The research study is based on techno-economic analysis of the feasibility of implementing wind power generation in Kuwait with a power generation capacity of 105 MW based on 50 wind turbines, which has a major requirement for clean energy. The study focused on three main areas of analysis and numerical modeling using the RETScreen software tool. The first area involved evaluating the performance and efficacy of generating wind power by collecting, analyzing, and modeling data on observed wind levels, wind turbine operation, and wind power generation. The second area comprised an environmental impact review to assess the environmental benefits of implementing wind power. The third area involved economic analysis of installing wind power in Kuwait. The analysis was undertaken to assess the energy recovery time for wind energy and determine the mitigation of global warming and pollution levels, the decrease of toxic emissions, and any cost savings from implementing clean energy systems in Kuwait. Additionally, sensitivity analysis was undertaken to determine the impact of certain variables in the modeling process. The results are used to estimate that the energy price would be $0.053 per kWh for a power generation capacity of 105 MWh based on an initial cost of $168 million and O&M of $5 million for 214,000 MWh of electricity exported to the grid. Moreover, the wind turbine farm will potentially avoid the emission of approximately 1.8 million tonnes of carbon dioxide per year, thereby saving approximately $9 million over 20 years spent installing carbon capture systems for conventional power plants. The wind farm containing a simple wind turbine is estimated to have a payback period of 9.1 years.

scholarly journals Experiments and Simulation on a Late-Model Wind-Motor Hybrid Pumping Unit

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 994 ◽  
Author(s):  
Chunyou Zhang ◽  
Liang Wang ◽  
Hong Li
Keyword(s):  
Mathematical Model ◽  
Power Generation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Power ◽  
Wind Power Generation ◽  
Oil Fields ◽  
Power Generation Technology ◽  
Pumping Unit ◽  
Generation Technology

Many oil fields are full of wind energy. At present, wind power generation technology has catered to oil fields. A larger wind turbine is used to supply power to several pumping units. As a result of the structural characteristics of the pumping unit, the efficiency of the electromotor is very low, which leads to a reduction in the utilization rate of wind energy. At the same time, considering the high cost of large wind turbines, the energy saving effect is not obvious in practical applications. This paper proposes an energy supply model of a pumping unit driven by a small wind turbine and a new wind-motor hybrid structure. Instead of wind power generation technology, wind energy drives the pumping unit directly via a mechanical–hydraulic transmission system. This new mechanical-hydraulic system can optimize the power confluence of wind and electric power. To enhance the efficiency of the motor, a mathematical model and a test station were established. The correctness of the energy conservation method and the mathematical model was verified, and the performance of the wind-motor system was studied.

scholarly journals Techno-Economic Analysis and Modelling of the Feasibility of Wind Energy in Kuwait

2022 ◽  
Vol 4 (1) ◽  
pp. 14-34
Author(s):  
Ali M. H. A. Khajah ◽  
Simon P. Philbin
Keyword(s):  
Power Generation ◽  
Economic Analysis ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Power ◽  
Power Plants ◽  
Clean Energy ◽  
Wind Power Generation ◽  
Environmental Benefits ◽  
The Impact

There continues to be significant attention and investment in wind power generation, which can supply a high percentage of the global demand for renewable energy if harvested efficiently. The research study is based on a techno-economic analysis of the feasibility of implementing wind power generation in Kuwait for 105 MW of electricity generation based on 50 wind turbines, which is a major requirement for clean energy. The study focused on three main areas of analysis and numerical modelling using the RETScreen software tool. The first area involved evaluating the performance and efficacy of generating wind power by collecting, analysing, and modelling data on observed wind levels, wind turbine operation, and wind power generation. The second area comprised an environmental impact report to assess the environmental benefits of implementing wind power. The third area involved economic analysis of installing wind power in Kuwait. The analysis was undertaken to determine the energy recovery time for wind energy and determine the mitigation of global warming and pollution levels, the decrease of toxic emissions, and any cost savings from implementing clean energy systems in Kuwait. Additionally, sensitivity analysis was undertaken to determine the impact of certain variables in the modelling process. The results were used to estimate that the energy price would be $0.053 per kWh for a power generation capacity of 105 MWh based on an initial cost of US $168 million and O&M of $5 million for 214,000 MWh of electricity exported to the grid. Moreover, the wind turbine farm will potentially avoid the emission of approximately 1.8 million t of carbon dioxide per year, thereby saving about $9 million over 20 years spent through installing carbon capture systems for conventional power plants. The wind farm is estimated to have a payback time of 9.1 years.

Power Electronics for Grid Integration of Wind Power Generation System

2016 ◽  
Vol 9 ◽  
pp. 10 ◽  
Author(s):  
Michael S Okundamiya
Keyword(s):  
Power Generation ◽  
Wind Energy ◽  
Power Electronics ◽  
Wind Power ◽  
Renewable Energy Sources ◽  
Wind Power Generation ◽  
Generation System ◽  
Electricity Grid ◽  
Power Generation System ◽  
Promising Source

The rising demands for a sustainable energy system have stimulated global interests in renewable energy sources. Wind is the fastest growing and promising source of renewable power generation globally. The inclusion of wind power into the electric grid can severely impact the monetary cost, stability and quality of the grid network due to the erratic nature of wind. Power electronics technology can enable optimum performance of the wind power generation system, transferring suitable and applicable energy to the electricity grid. Power electronics can be used for smooth transfer of wind energy to electricity grid but the technology for wind turbines is influenced by the type of generator employed, the energy demand and the grid requirements. This paper investigates the constraints and standards of wind energy conversion technology and the enabling power electronic technology for integration to electricity grid.

scholarly journals Forecasting Wind Power Generation Using Artificial Neural Network: “Pawan Danawi”—A Case Study from Sri Lanka

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Amila T. Peiris ◽  
Jeevani Jayasinghe ◽  
Upaka Rathnayake
Keyword(s):  
Neural Network ◽  
Power Generation ◽  
Wind Power ◽  
Wind Farm ◽  
Mean Squared Error ◽  
Wind Power Generation ◽  
Training Algorithms ◽  
Training Algorithm ◽  
Squared Error ◽  
Ann Models

Wind power, as a renewable energy resource, has taken much attention of the energy authorities in many countries, as it is used as one of the major energy sources to satisfy the ever-increasing energy demand. However, careful attention is needed in identifying the wind power potential in a particular area due to climate changes. In this sense, forecasting both wind power generation and wind power potential is essential. This paper develops artificial neural network (ANN) models to forecast wind power generation in “Pawan Danawi”, a functioning wind farm in Sri Lanka. Wind speed, wind direction, and ambient temperature of the area were used as the independent variable matrices of the developed ANN models, while the generated wind power was used as the dependent variable. The models were tested with three training algorithms, namely, Levenberg-Marquardt (LM), Scaled Conjugate Gradient (SCG), and Bayesian Regularization (BR) training algorithms. In addition, the model was calibrated for five validation percentages (5% to 25% in 5% intervals) under each algorithm to identify the best training algorithm with the most suitable training and validation percentages. Mean squared error (MSE), coefficient of correlation (R), root mean squared error ratio (RSR), Nash number, and BIAS were used to evaluate the performance of the developed ANN models. Results revealed that all three training algorithms produce acceptable predictions for the power generation in the Pawan Danawi wind farm with R > 0.91, MSE < 0.22, and BIAS < 1. Among them, the LM training algorithm at 70% of training and 5% of validation percentages produces the best forecasting results. The developed models can be effectively used in the prediction of wind power at the Pawan Danawi wind farm. In addition, the models can be used with the projected climatic scenarios in predicting the future wind power harvest. Furthermore, the models can acceptably be used in similar environmental and climatic conditions to identify the wind power potential of the area.

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