Wavelet neural network based on islanding detection via inverter‐based DG. Issue 2 (19th September 2014)
- Record Type:
- Journal Article
- Title:
- Wavelet neural network based on islanding detection via inverter‐based DG. Issue 2 (19th September 2014)
- Main Title:
- Wavelet neural network based on islanding detection via inverter‐based DG
- Authors:
- Mohammadi, Mohsen
Danandeh, Akbar
Nasir Aghdam, Hossein
Ojaroudi, Nasser - Abstract:
- Abstract : In this article, a passive neurowavelet based on islanding detection technique for grid‐connected inverter‐based distributed generation has been developed. Connecting distributed generator to the distribution network has many benefits such as increasing the capacity of the grid and enhancing the power quality. However, it gives rise to many problems. This is mainly due to the fact that distribution networks are designed without any generation units at that level. Hence, integrating distributed generators into the existing distribution network is not problem‐free. Unintentional islanding is one of the encountered problems. Islanding is the situation where the distribution system containing both distributed generator and loads is separated from the main grid as a result of many reasons such as electrical faults and their subsequent switching incidents, equipment failures, or preplanned switching events like maintenance. The proposed method utilizes and combines wavelet analysis and artificial neural network to detect islanding. Discrete wavelet transform is capable of decomposing the signals into different frequency bands. It can be utilized in extracting discriminative features from the acquired voltage signals. Passive schemes have a large nondetection zone (NDZ) and concern has been raised on active method due to its degrading power quality effect. The main emphasis of the proposed scheme is to reduce the NDZ to as close as possible and to keep the output powerAbstract : In this article, a passive neurowavelet based on islanding detection technique for grid‐connected inverter‐based distributed generation has been developed. Connecting distributed generator to the distribution network has many benefits such as increasing the capacity of the grid and enhancing the power quality. However, it gives rise to many problems. This is mainly due to the fact that distribution networks are designed without any generation units at that level. Hence, integrating distributed generators into the existing distribution network is not problem‐free. Unintentional islanding is one of the encountered problems. Islanding is the situation where the distribution system containing both distributed generator and loads is separated from the main grid as a result of many reasons such as electrical faults and their subsequent switching incidents, equipment failures, or preplanned switching events like maintenance. The proposed method utilizes and combines wavelet analysis and artificial neural network to detect islanding. Discrete wavelet transform is capable of decomposing the signals into different frequency bands. It can be utilized in extracting discriminative features from the acquired voltage signals. Passive schemes have a large nondetection zone (NDZ) and concern has been raised on active method due to its degrading power quality effect. The main emphasis of the proposed scheme is to reduce the NDZ to as close as possible and to keep the output power quality unchanged. The simulations results, performed by MATLAB/Simulink, shows that the proposed method has a small NDZ. Also, this method is capable of detecting islanding accurately within the minimum standard time. © 2014 Wiley Periodicals, Inc. Complexity 21: 309–324, 2015 … (more)
- Is Part Of:
- Complexity. Volume 21:Issue 2(2015)
- Journal:
- Complexity
- Issue:
- Volume 21:Issue 2(2015)
- Issue Display:
- Volume 21, Issue 2 (2015)
- Year:
- 2015
- Volume:
- 21
- Issue:
- 2
- Issue Sort Value:
- 2015-0021-0002-0000
- Page Start:
- 309
- Page End:
- 324
- Publication Date:
- 2014-09-19
- Subjects:
- islanding detection -- neurowavelet -- nondetection zone -- distributed generation
Chaotic behavior in systems -- Periodicals
Complexity (Philosophy) -- Periodicals
003 - Journal URLs:
- https://onlinelibrary.wiley.com/journal/10990526 ↗
http://onlinelibrary.wiley.com/ ↗
https://www.hindawi.com/journals/complexity/ ↗ - DOI:
- 10.1002/cplx.21606 ↗
- Languages:
- English
- ISSNs:
- 1076-2787
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3364.585500
British Library HMNTS - ELD Digital store - Ingest File:
- 4.xml