Power Quality Monitoring in Wind Solar Hybrid System
By: Rathika, P
.
Contributor(s): Pram, Prasanna.
Publisher: New Delhi STM Journals 2018Edition: Vol 8 (1), Jan- April.Description: 16-23p.Subject(s): EXTC EngineeringOnline resources: Click here
In:
Journal of power electronics and power systemsSummary: development of new functionalities, solar and wind energy based hybrid systems are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting, is one of the most promising sources. Due to the development of modern power electronic devices, the power quality of wind solar hybrid system gets affected. Hence, due to the increasing usage of sensitive electronic equipments in wind solar hybrid system, power quality has become a major concern. Sag, swell and harmonics are the critical aspects of power quality issues. This project develops a method that can be able to provide the identification and detection of problems in power quality. This method is developed by discrete wavelet transform (DWT). The signal which is given is decomposed by using wavelet transformation. Thereby, using the wavelet coefficients, the features are extracted and the artificial neural network is developed which is used for classification of the power quality disturbances. The data required for training and testing to develop the neural network model is generated through simulation. This project demonstrates that each power quality disturbance has some unique deviations from the pure sine wave and it is adopted to provide a classification which is reliable to the type of disturbance. The combined wavelet transformation and ANN approach can be able to classify the power quality disturbances correctly.
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Articles Abstract Database
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School of Engineering & Technology Archieval Section | Not for loan | 2021-2021394 |
development of new functionalities, solar and wind energy based hybrid systems are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting, is one of the most promising sources. Due to the development of modern power electronic devices, the power quality of wind solar hybrid system gets affected. Hence, due to the increasing usage of sensitive electronic equipments in wind solar hybrid system, power quality has become a major concern. Sag, swell and harmonics are the critical aspects of power quality issues. This project develops a method that can be able to provide the identification and detection of problems in power quality. This method is developed by discrete wavelet transform (DWT). The signal which is given is decomposed by using wavelet transformation. Thereby, using the wavelet coefficients, the features are extracted and the artificial neural network is developed which is used for classification of the power quality disturbances. The data required for training and testing to develop the neural network model is generated through simulation. This project demonstrates that each power quality disturbance has some unique deviations from the pure sine wave and it is adopted to provide a classification which is reliable to the type of disturbance. The combined wavelet transformation and ANN approach can be able to classify the power quality disturbances correctly.
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