Automatic generation control of a multi-area ST – Thermal power system using Grey Wolf Optimizer algorithm based classical controllers
[Display omitted] •Solar thermal power plant is incorporated for the first time in AGC.•Grey Wolf Optimizer algorithm for optimization of controller’s gains.•Performances of classical controllers (I, PI, and PID) are evaluated with SLP.•Comparison reveals that PID controller is best.•Sensitivity ana...
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| Veröffentlicht in: | International journal of electrical power & energy systems Jg. 73; S. 853 - 862 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier Ltd
01.12.2015
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| ISSN: | 0142-0615, 1879-3517 |
| Online-Zugang: | Volltext |
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| Abstract | [Display omitted]
•Solar thermal power plant is incorporated for the first time in AGC.•Grey Wolf Optimizer algorithm for optimization of controller’s gains.•Performances of classical controllers (I, PI, and PID) are evaluated with SLP.•Comparison reveals that PID controller is best.•Sensitivity analysis reveals the robustness of the optimum gains.
This paper present automatic generation control (AGC) of a three area thermal system incorporating solar thermal power plant (STPP) in one of the area. Single reheat turbine and appropriate generation rate constraints is provided in the conventional thermal system. The performances of integral (I), proportional plus integral (PI), and proportional plus integral plus derivative (PID) controller are evaluated in the system with and without incorporating STPP. A new computational evolutionary technique called grey wolf optimizer algorithm (GWO) is used for the optimization of secondary controller gains for first time in AGC. Investigations reveal that GWO optimized PID controller’s performance is better than others in terms of settling time, peak overshoot and magnitude of oscillations in the system with or without STPP. Sensitivity analysis reveals that that GWO optimized PID controller gains obtained in nominal conditions and parameters are healthy and not necessary to reset for large change in system conditions and parameters. |
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| AbstractList | [Display omitted]
•Solar thermal power plant is incorporated for the first time in AGC.•Grey Wolf Optimizer algorithm for optimization of controller’s gains.•Performances of classical controllers (I, PI, and PID) are evaluated with SLP.•Comparison reveals that PID controller is best.•Sensitivity analysis reveals the robustness of the optimum gains.
This paper present automatic generation control (AGC) of a three area thermal system incorporating solar thermal power plant (STPP) in one of the area. Single reheat turbine and appropriate generation rate constraints is provided in the conventional thermal system. The performances of integral (I), proportional plus integral (PI), and proportional plus integral plus derivative (PID) controller are evaluated in the system with and without incorporating STPP. A new computational evolutionary technique called grey wolf optimizer algorithm (GWO) is used for the optimization of secondary controller gains for first time in AGC. Investigations reveal that GWO optimized PID controller’s performance is better than others in terms of settling time, peak overshoot and magnitude of oscillations in the system with or without STPP. Sensitivity analysis reveals that that GWO optimized PID controller gains obtained in nominal conditions and parameters are healthy and not necessary to reset for large change in system conditions and parameters. |
| Author | Saikia, Lalit Chandra Sharma, Yatin |
| Author_xml | – sequence: 1 givenname: Yatin surname: Sharma fullname: Sharma, Yatin email: sharmayatin28@gmail.com – sequence: 2 givenname: Lalit Chandra surname: Saikia fullname: Saikia, Lalit Chandra email: lcsaikia@yahoo.com |
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