Optimal tuning of PID controller parameters for AGC of a wind
Abstract
The interconnected power systems response control has become more challenging with the integration of wind energy due to the variable range of wind speed and power output. In addition to load perturbations, fluctuations in wind power can also impact system frequency. Therefore, enhancing current control strategies is essential to maintain the stability of the frequency in these complex power system scenarios. The Controller is tuned in three methods. The new tuning methods are introduced to the conventional proportional-integral and derivative controller such that the system gives best performance. These tuning methods are Genetic Algorithm (GA) and Harmony Search Algorithm (HSA) used to study the system performance in comparison between them on Time Domain Analysis. The system is also tested for its robustness in three cases as the nominal loads for both the areas and with the load disturbance and the controller by its gain variations. The system's results are acquired through the utilization of the MATLAB/Simulink software.
Downloads
References
M. L. Kothari, J. Nanda, D. P. Kothari and D. Das, "Discrete-mode automatic generation control of a two-area reheat thermal system with new area control error," in IEEE Transactions on Power Systems, vol. 4, no. 2, pp. 730-738, May 1989.
Nasiruddin, Ibraheem & Kumar, Prabhat & Kothari, D.P.. (2005). Recent Philosophies of Automatic Generation Control Strategies in Power Systems. Power Systems, IEEE Transactions on. 20. 346 - 357. 10.1109/TPWRS, April, 2004.
Saikia, Lalit & Nanda, Jayanarayan & Mishra, S.. (2011). Performance comparison of several classical controllers in AGC for multi-area interconnected thermal system. International Journal of Electrical Power & Energy Systems. 33. 394-401. 10.1016/j.ijepes, September, 2010.
Askarzadeh, Alireza. A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm. Computers & Structures. 169. 1-12. 10.1016/j.compstruc, March, 2016.
Hasanien, H.M. and El-Fergany, A.A. Symbiotic organisms search algorithm for automatic generation control of interconnected power systems including wind farms. IET Gener. Transm. Distrib., 11: 1692-1700, 2017.
Sahu, R. K., Panda, S., Rout, U. K., & Sahoo, D. K. Teaching learning-based optimization algorithm for automatic generation control of power system using 2-DOF PID controller. International Journal of Electrical Power and Energy Systems, 77, 287–301, 2016.
Askarzadeh, A. A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm. Computers and Structures, 169, 1–12, 2016.
Naidu, Karanam & Shaw, Binod. A new two-degree of freedom combined PID controller for automatic generation control of a wind integrated interconnected power system. Protection and Control of Modern Power Systems. 7. 10.1186/s41601-022-00241-2, October, 2022.
Nayak, J. R., Shaw, B., Sahu, B. K., & Naidu, K. A. Application of optimized adaptive crow search algorithm based two degrees of freedom optimal fuzzy PID controller for AGC system. Engineering Science and Technology, an International Journal, 2021.
H. R., M. Mirsalim, and G. B., ‘Application of Harmony Search Algorithm in Power Engineering’, Search Algorithms for Engineering Optimization. InTech, Feb. 13, 2013. doi: 10.5772/55509.
Baghaee, H. R., Mirsalim, M., & Gharehpetian, G. B. (2013). Application of harmony search algorithm in power engineering. In Search Algorithms for Engineering Optimization. IntechOpen.
Copyright (c) 2024 ITEGAM-JETIA
This work is licensed under a Creative Commons Attribution 4.0 International License.
