An Optimal LFC in Two-Area Power Systems Using

a Meta-heuristic Optimization Algorithm

Lec. Dr. Mushtaq N. Ahmed

In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. This meta-heuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters (????????,????????) automatically. The developed controller (HS-PI) with LFC loop is very important to minimize the system frequency and keep the system power is maintained at scheduled values under sudden loads changes. Integral absolute error (IAE) is used as an objective function to enhance the overall system performance in terms of settling time, maximum deviation, and peak time. The two-area power systems and developed controller are modeled using MATLAB software (Simulink/Code). As a result, the developed control algorithm (HS-PI) is more robustness and efficient as compared to PSO-PI control algorithm under same operation conditions. 

REFERENCES

[1] J. Venkatachalam, et al., “A Particle Swarm Optimization Algorithm for Automatic Generation Control of Two Area Interconnected Power System,” International Journal of Engineering Research & Technology, vol/issue: 2(6), 2013.

[2] M. Najeeb, et al., “PID Parameters Improvement for AGC in Three Parallel Connected power Systems,” The National Conference for Postgraduate Research, Universiti Malaysia Pahang, vol. P075. pp. 544-551, 2016.

[3] Ibraheem, et al., “Recent philosophies of automatic generation control strategies in power systems,” IEEE Transactions on Power Systems, vol/issue: 20(1), pp. 346–357, 2005.

[4] G. A. Salman, “Automatic Generation Control in Multi Area Interconnected Power System Using PID Controller Based on GA and PSO,” Second Engineering Scientific Conference, College of Engineering, University of Diyala, pp. 297-310, 2015.

[5] J. Venkatachalam, et al., “Automatic generation control of two area interconnected power system using particle swarm optimization,” Journal of Electrical and Electronics Engineering, vol/issue: 6(1), pp. 28-36, 2013.

[6] S. Prakash, et al., “Load frequency control of three area interconnected hydro-thermal reheat power system using artificial intelligence and PI controllers,” International Journal of Engineering, Science and Technology, vol/issue: 4(1), pp. 23-37, 2011.

[7] J. G. Ziegler and N. B. Nichols, “Optimum settings for automatic controllers,” Transactions of the ASME, vol/issue: 64(8), pp. 759/768–759/768, 1942.

[8] T. C. Yang, et al., “Decentralized Power System load frequency control beyond the limit of diagonal dominance,” International Journal of Electrical Power & Energy Systems, vol/issue: 24(3), pp. 173-184, 2002.

[9] V. Donde, et al., “Simulation and Optimization in an AGC System after Deregulation,” IEEE Transactions on Power Systems, vol/issue: 16(3), pp. 481–489, 2001.

[10] C. H. Liang, et al., “Study of Differential Evolution for Optimal Reactive Power Dispatch,” IET Generation Transmission and Distribution, vol/issue: 1(2), pp. 253-260, 2007.

[11] L. X. Long, et al., “A Bacterial Foraging Global Optimization Algorithm Based On the Particle Swarm Optimization,” IEEE International Conference on Intelligent Computing and Intelligent Systems, vol. 2, pp. 22-27, 2010.

[12] A. M. Jadhav, et al., “Performance Verification of PID Controller in an Interconnected Power System Using Particle Swarm Optimization,” 2nd International Conference on Advances in Energy Engineering (ICAEE), Energy Procedia, vol. 14, pp. 2075-2080, 2012.

[13] A. J. Sharmili, et al., “Particle Swarm Optimization based PID controller for two area Load Frequency Control System,” International Journal of Engineering Research and General Science, vol/issue: 3(2), pp. 772-778, 2015.

[14] R. Chaudhary, et al., “A Novel Approach to PID Controller Design for Improvement of Transient Stability and Voltage Regulation of Nonlinear Power System,” International Journal of Electrical and Computer Engineering (IJECE), vol/issue: 6(5), pp. 2225-2238, 2016.

[15] N. R. Raju, et al., “Robustness Study of Fractional Order PID Controller Optimized by Particle Swarm Optimization in AVR System,” International Journal of Electrical and Computer Engineering (IJECE), vol/issue: 6(5), pp. 2033-2040, 2016.

[16] M. Dorigo, et al., “Ant Colony optimization: artificial ants as a computational intelligence technique,” IEEE Computational Intelligence Magazine, vol/issue: 1(4), pp. 28-39, 2007.

[17] V. Jain, et al., “Modeling and simulation of Load Frequency Control in Automatic Generation Control using Genetic Algorithms Technique,” International Journal of Innovative Science, Engineering & Technology, vol/issue: 1(8), pp. 356-362, 2014.

[18] G. Konar, et al., “Two Area Load Frequency Control Using GA Tuned PID Controller in Deregulated Environment,” Proceedings of the International Multi Conference of Engineers and Computer Scientists, vol. 2, pp. 1-6, 2014.

[19] M. M. Ismail, et al., “Load Frequency Control Adaptation Using Artificial Intelligent Techniques for One and Two Different Areas Power System,” International Journal of Control, Automation and Systems, vol/issue: 1(1), pp. 12- 23, 2012.

[20] Ganesh V., et al., “LQR Based Load Frequency Controller for Two Area Power System,” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol/issue: 1(4), pp. 262-269, 2012.

[21] M. Shahooth, et al., “An optimized PID parameters for LFC in interconnected power systems using MLSL optimization algorithm,” ARPN Journal of Engineering and Applied Sciences, vol/issue: 11(19), pp. 11770-11781, 2016.

[22] M. Hojabri, et al., “An Overview on Microgrid Control Strategies,” International Journal of Engineering and Advanced Technology, vol/issue: 4(5), pp. 93-98, 2015.

[23] Z. W. Geen, et al., “A New Heuristic Optimization Algorithm: Harmony Search,” Simulation, vol. 76, pp. 60- 69, 2001.

[24] H. Daniyal, et al., “An Efficient Control Implementation for Voltage Source Inverter based Harmony Search Algorithm,” International Journal of Power Electronics and Drive Systems, vol/issue: 8(1), pp. 279-289, 2017.

[25] M. Mansor, et al., “An Intelligent Voltage Controller for a PV Inverter System using Simulated Annealing Algorithm-based PI Tuning Approach,” Journal of Engineering and Applied Sciences, vol/issue: 12(3), pp. 660-669, 2017.