Excitation Control Enhancement for the Synchronous Generator Using Effective Control Methodology.

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Bibliographic Details
Title: Excitation Control Enhancement for the Synchronous Generator Using Effective Control Methodology.
Authors: N. Jasim, Hawraa1,2 hawraa.jasim.iba9@atu.edu.iq, K. Abdalla, Kasim2
Source: Iraqi Journal for Electrical & Electronic Engineering. Jun2026, Vol. 22 Issue 1, p540-552. 13p.
Subjects: Synchronous generators, PID controllers, Artificial neural networks, Electric power system stability, Feedback control systems, Voltage control, Simulated annealing, Electric power systems
Abstract (English): In electrical power plants, the excitation control system is an important part of controlling the output voltage of the synchronous generators. The purpose of this paper is to utilize various methods of excitation control, such as Proportional-Integral-Derivative (PID), Simulated Annealing (SA), and Neural Network (NN) controllers. Each method is examined in terms of its effectiveness in enhancing system stability, reliability, and adaptability to varying operational conditions. The study simulates and optimizes a 2 MVA/400 V synchronous generator driven by a three-phase diesel engine with mechanical coupling and an exciter system. MATLAB 2021 is used to implement the Simulink model. The dynamic responses of field voltage and field current to load changes were analyzed for each control technique. Additionally, the performance of three-phase voltage and current for synchronous generator were examined over a 10-second timeframe. Our findings indicate that the PID controller offers straightforward implementation and reliable performance under varying conditions. The NN controller implementation is more similar to the PID response, and the SA controller demonstrates superior adaptability. The research underscores the potential of integrating these advanced control techniques in synchronous generators, paving the way for enhanced stability and reliability in modern electric power systems, with further implications for renewable energy integration. [ABSTRACT FROM AUTHOR]
Abstract (Arabic): يركز المقال على تحسين التحكم في الإثارة للمولدات المتزامنة من خلال مقارنة ثلاث منهجيات تحكم: المتحكم التناسبي-التكاملي-التفاضلي (PID)، والشبكة العصبية (NN)، ومتحكم التلدين المحاكى (SA). باستخدام برنامج MATLAB Simulink، تحاكي الدراسة مولدًا متزامنًا بقوة 2 ميجا فولت أمبير وجهد 400 فولت، يعمل بمحرك ديزل ثلاثي الطور مع اقتران ميكانيكي ونظام إثارة، حيث يتم تحليل الاستجابات الديناميكية لجهد التيار الميداني تحت تغيرات الحمل. تشير النتائج إلى أن متحكمي PID وNN يقدمان تنظيمًا موثوقًا للجهد مع استعادة مستقرة لجهد الطرف بعد الاضطرابات، في حين يظهر متحكم SA قدرة أكبر على التكيف لكنه يستغرق وقتًا أطول للاستقرار ويعطي سعة جهد طرف أقل. تسلط الدراسة الضوء على إمكانيات هذه التقنيات المتقدمة في تحسين الاستقرار والموثوقية في أنظمة الطاقة، مع تداعيات مهمة لدمجها مع مصادر الطاقة المتجددة. [Extracted from the article]
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Database: Engineering Source
Description
Abstract:In electrical power plants, the excitation control system is an important part of controlling the output voltage of the synchronous generators. The purpose of this paper is to utilize various methods of excitation control, such as Proportional-Integral-Derivative (PID), Simulated Annealing (SA), and Neural Network (NN) controllers. Each method is examined in terms of its effectiveness in enhancing system stability, reliability, and adaptability to varying operational conditions. The study simulates and optimizes a 2 MVA/400 V synchronous generator driven by a three-phase diesel engine with mechanical coupling and an exciter system. MATLAB 2021 is used to implement the Simulink model. The dynamic responses of field voltage and field current to load changes were analyzed for each control technique. Additionally, the performance of three-phase voltage and current for synchronous generator were examined over a 10-second timeframe. Our findings indicate that the PID controller offers straightforward implementation and reliable performance under varying conditions. The NN controller implementation is more similar to the PID response, and the SA controller demonstrates superior adaptability. The research underscores the potential of integrating these advanced control techniques in synchronous generators, paving the way for enhanced stability and reliability in modern electric power systems, with further implications for renewable energy integration. [ABSTRACT FROM AUTHOR]
ISSN:18145892
DOI:10.37917/ijeee.22.1.48