Artificial neural network–aided technique for low voltage ride-through wind turbines for controlling the dynamic behavior under different load conditions. Issue 4 (August 2019)
- Record Type:
- Journal Article
- Title:
- Artificial neural network–aided technique for low voltage ride-through wind turbines for controlling the dynamic behavior under different load conditions. Issue 4 (August 2019)
- Main Title:
- Artificial neural network–aided technique for low voltage ride-through wind turbines for controlling the dynamic behavior under different load conditions
- Authors:
- Salah Saidi, Abdelaziz
Helmy, Walid - Abstract:
- At the level of the electrical distribution networks with wind generation, the disturbances may influence the voltage stability, particularly during low voltage ride-through wind turbine. This research is concerned with studying the effect of implementing different controllers and load types on the low voltage ride-through dynamic recovery performance during disturbances. A conventional proportional–integral–derivative controller is compared with the artificial neural network–based one. The controller construction and its gain are proposed for each type of controller and the impact of each controller on the dynamic behavior of the low voltage ride-through is investigated thoroughly under various operating conditions. Also, the dynamic performance of wind generators is examined with low voltage ride through and different dynamic load models. Both, dynamic induction motor load and composed static and exponential recovery load models are considered. In case of dynamic induction motor load, the effect of the inertia constant has been studied under two types of controllers. The overall system model is simulated using PSAT/MATLAB software in such a way that it can be suited for modeling of voltage controller and loads configurations. The low voltage ride-through performance has been changed with different controllers and load types.
- Is Part Of:
- Wind engineering. Volume 43:Issue 4(2019)
- Journal:
- Wind engineering
- Issue:
- Volume 43:Issue 4(2019)
- Issue Display:
- Volume 43, Issue 4 (2019)
- Year:
- 2019
- Volume:
- 43
- Issue:
- 4
- Issue Sort Value:
- 2019-0043-0004-0000
- Page Start:
- 420
- Page End:
- 440
- Publication Date:
- 2019-08
- Subjects:
- Doubly fed induction generator wind turbine -- low voltage ride-through -- static and dynamic loads -- exponential recovery load model -- proportional–integral–derivative controller -- artificial neural network–based controller
Wind-pressure -- Periodicals
Winds -- Periodicals
Wind power -- Periodicals
Engineering meteorology -- Periodicals
Pression du vent
Vents
Énergie éolienne
Météorologie appliquée
Engineering meteorology
Wind power
Wind-pressure
Winds
Periodicals
621.4505 - Journal URLs:
- http://wie.sagepub.com/ ↗
http://multi-science.metapress.com/content/121513 ↗
http://www.ingentaconnect.com ↗
http://www.multi-science.co.uk/ ↗ - DOI:
- 10.1177/0309524X18791387 ↗
- Languages:
- English
- ISSNs:
- 0309-524X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11541.xml