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International Journal of Electrical Power and Machine Systems Review Article

Research on Synchronous Generators AC Excitation Regulation Control System

  1. Mansi Balram Handi Department of Electrical Engineering, Sanjivani College of Engineering, Kopargoan, Ahmadnagar
  2. P. S. Chobe Department of Electrical Engineering, Sanjivani College of Engineering, Kopargoan, Ahmadnagar
  3. D. B. Pardeshi Department of Electrical Engineering, Sanjivani College of Engineering, Kopargoan, Ahmadnagar

Abstract

Based on various methods to supply excitation power to the synchronous generator it is categorized in three different types of excitation systems for synchronous motor. The first one is DC excitation system, second is AC excitation system and third one is static excitation system. The increasing size of contemporary power systems ensures system dependability and stability. A better supply of power is vital and has a big influence on improving people's quality of life and economic growth. The AC excitation system is the primary subject of this study. Variable rotor speed is one of the great features of AC excited generator; it enhances power system stability and permits deep operation without step loss. AC excitation generators have independent features for adjusting speed, reactive power, and effective power in addition to variable speed and constant frequency power. Maximum dependability, operating flexibility, and outstanding adjustment performance may be achieved with AC excitation generators by utilizing high-performance variable frequency excitation power sources and suitable excitation control techniques. Synchronous generator functioning depends heavily on the excitation mechanism. The stability of the motor and power system are significantly increased by a well-designed excitation system, which also guarantees the generator's steady and dependable functioning.

Keywords

References (14)

  1. Bhoi SL, Shantilal Salve S, Kumar DV, Pardeshi DB, William P. Deployment of Slow power Hybrid Electric Vehicle based on Combustion Engine. 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC). 2022:231-235. doi:10.1109/icesc54411.2022.9885402
  2. Dhumane RA, Nikam TD, Hajare RN, Pardeshi DB, William P. Sustainable and Intelligent Control Strategies for Electric Vehicle Systems. 2023 2nd International Conference on Edge Computing and Applications (ICECAA). 2023:1551-1555. doi:10.1109/icecaa58104.2023.10212140
  3. Dahatonde S, Jape N, Hajare RN, Pardeshi DB, William P. Arduino Based Vehicle Overload Detection System for Prevention of Accidents Using ADC. 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA). 2023:1633-1636. doi:10.1109/icirca57980.2023.10220821
  4. Roham MN, Kadam RS, Hajare R, Pardeshi DB, William P. Hybrid Model for Vehicle Overload Detection System using Arduino Sensors. 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA). 2023:1431-1434. doi:10.1109/icirca57980.2023.10220870
  5. More AR, Shendkar OB, Pathak KG, Sanap PD, Pachore SN, William P. Survey on Framework for Governing Modern Cyber Attacks in Computer Network. 2023 4th International Conference on Computation, Automation and Knowledge Management (ICCAKM). 2023:01-06. doi:10.1109/iccakm58659.2023.10449582
  6. Nayak, C. ., William, P. ., Kumar, R. ., Deepak, A. ., Yadav, K. ., Rao, A. L. N. ., Srivastava, A. ., & Shrivastava, A. . (2024). Edge Cloud Server Deployment with Machine Learning for 6G Internet of Things. International Journal of Intelligent Systems and Applications in Engineering, 12(16s), 328 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4826
  7. Hegde, S. K. ., William, P. ., Basvant, M. S. ., Deepak, A. ., Badhoutiya, A. ., Rao, A. L. N. ., Srivastava, A. ., & Shrivastava, A. . (2024). Energy-Efficient Bio-Inspired Hybrid Deep Learning Model for Network Intrusion Detection Based on Intelligent Decision Making. International Journal of Intelligent Systems and Applications in Engineering, 12(16s), 306 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4823
  8. Gow and C. Manning, “Development of a photovoltaic array model for use in power-electronics simulation studies,” IEE Proc, Electric Power Appl., vol. 146, no. 2, pp. 193–200, Mar. 1999.
  9. Bellia, R.Youcef, Fatima,, “A detailed modeling of photovoltaic module using MATLAB –NRIAG Journal of astronomy and Geophysics, 2014.
  10. Yogeesh N, William P. Sensor-enabled biomedical decision support system using deep learning and fuzzy logic. Deep Learning Applications in Translational Bioinformatics. 2024:33-53. doi:10.1016/b978-0-443-22299-3.00003-7
  11. Warule AS, Barde VR, Barshile MK, Kambhire SV, Bibave RR, Pardeshi DB. Electric Reaping and Fertilizing Machine. 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA). 2023:1685-1691. doi:10.1109/icirca57980.2023.10220941
  12. Bibave R, Thokal P, Hajare R, Deulkar A, William P, Chandan AT. A Comparative Analysis of Single Phase to Three Phase Power Converter for Input Current THD Reduction. 2022 International Conference on Electronics and Renewable Systems (ICEARS). 2022:325-330. doi:10.1109/icears53579.2022.9752161
  13. Bibave R, Kulkarni V. A Novel Maximum Power Point Tracking Method for Wind Energy Conversion System: A Review. 2018 Internat2018 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)ional conference on computation of power, energy, Information and Communication (ICCPEIC). 2018:430-433. doi:10.1109/iccpeic.2018.8525198
  14. Bibave R, kulkarni V. Maximum Power Extraction from Wind Energy System by Using Perturbation and Observation Method. 2018 International Conference on Smart Electric Drives and Power System (ICSEDPS). 2018:105-110. doi:10.1109/icsedps.2018.8536033