An artificial neural network based power system stabilizer for multi-machine power system
Joint Authors
al-Razzaz, Z. S.
Abd al-Hamid, M.
Source
The Arabian Journal for Science and Engineering. Section B, Engineering
Issue
Vol. 26, Issue 1B (30 Apr. 2001), pp.29-41, 13 p.
Publisher
King Fahd University of Petroleum and Minerals
Publication Date
2001-04-30
Country of Publication
Saudi Arabia
No. of Pages
13
Main Subjects
Topics
Abstract AR
تم في هذا البحث اقتراح و بناء مقرر لأنظمة القدرة الكهربية باستخدام الشبكات العصبية.
و قد اخذ في الاعتبار التغير في أحوال الشبكة و كذلك التغير في نوعية الحمل الكهربي.
استخدم مقرر الأنظمة لزيادة اضمحلال الذبذبات الكهربية التي تنتج عن أي اضطراب في النظام.
و من عيوب استخدام مقرر ذي مكونات ثابتة أنه لا يعطي تأثيرا جيدا عند استخدامه في أحوال تختلف عن التي تم بناؤه عندها.
و لذلك يمتاز المقرر المقترح بتغير قيم مكوناته عند التغير في أحوال الشبكة مما يعطي درجة أداء افصل من سابقه.
و لقد تم اختبار المقرر باستخدام أحوال أخرى لم تدخل في عملية بنائه و قد أعطى نتائج جيدة.
و تم اختبار المقرر المقترح علم شبكة كهربية تحضي مولدات متعددة و أعطى نتائج جيدة.
Abstract EN
An adaptive power system stabilizer (PSS) over a wide range of operating conditions and typical local load models is proposed, using an artificial neural network ANN.
The PSS with fixed parameters, which improves the power system damping for one operating point, may become unsatisfactory for another one especially for a wide range of operating conditions and load models.
To improve the damping of the system over a wide range of operating conditions, it is desirable to adapt the parameters of the PSS in real time, based on operating points and load models.
In order to do this, on-line measurement of operating points and load model parameters are chosen as the input signals to the neural network.
The outputs of the neural network are the desired parameters of the PSS.
The neural network, once trained by a set of input-output patterns in the training set, can yield proper PSS parameters under any operating conditions and local load model.
Simulation results show that the tuning parameters of the PSS using the ANN approach can provide better damping than a fixed-parameters PSS over a wide range of operating points and typical load models.
The proposed PSS is implemented for a multi-machine system.
American Psychological Association (APA)
al-Razzaz, Z. S.& Abd al-Hamid, M.. 2001. An artificial neural network based power system stabilizer for multi-machine power system. The Arabian Journal for Science and Engineering. Section B, Engineering،Vol. 26, no. 1B, pp.29-41.
https://search.emarefa.net/detail/BIM-390076
Modern Language Association (MLA)
al-Razzaz, Z. S.& Abd al-Hamid, M.. An artificial neural network based power system stabilizer for multi-machine power system. The Arabian Journal for Science and Engineering. Section B, Engineering Vol. 26, no. 1B (Apr. 2001), pp.29-41.
https://search.emarefa.net/detail/BIM-390076
American Medical Association (AMA)
al-Razzaz, Z. S.& Abd al-Hamid, M.. An artificial neural network based power system stabilizer for multi-machine power system. The Arabian Journal for Science and Engineering. Section B, Engineering. 2001. Vol. 26, no. 1B, pp.29-41.
https://search.emarefa.net/detail/BIM-390076
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 40
Record ID
BIM-390076