Distributed multi-agent Load Frequency Control for a Large-scale Power System Optimized by Grey Wolf Optimizer

Document Type : Research paper


1 Electrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran

2 Department of Technical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran


This paper aims to design an optimal distributed multi-agent controller for load frequency control and optimal power flow purposes. The controller parameters are optimized using Grey Wolf Optimization (GWO) algorithm. The designed optimal distributed controller is employed for load frequency control in the IEEE 30-bus test system with six generators. The controller of each generator is considered as one agent. The controllers of agents are implemented in a distributed manner that is control rule of each agent depends on the agents’ own state and the states of their neighbors. Three other types of controllers including centralized controller, decentralized controller, and optimal centralized controller are considered for comparison. The performances of decentralized and distributed controllers are compared with two centralized controllers. In the optimal centralized controller and optimal distributed controller, the objective function is considered to achieve the objective of load frequency control as well as minimize power generation. Simulation results using MATLAB/SIMULINK show that although there is no global information of system in the optimal distributed controller, it has suitably reduced the frequency deviation. Meanwhile the power is optimally generated in the three scenarios of load increasing, load reduction and generator outage.


Main Subjects

[1]     G. Gross, and J. W. Lee “Analysis of load frequency control performance assessment criteria,” IEEE Trans. Power Syst., vol. 16, no. 3, pp. 520-525, 2001.
[2]     S. Satyanarayana, R. K. Sharma, A. Mukta, and S. A. Kumar, “Automatic Generation control in power plant using PID, PSS and fuzzy-PID controller,” Smart Electr. Grid, pp. 1-8, 2014.
[3]     O. Abedinia, N. Amjady, A. Ghasemi, and H. Shayeghi “Multi-stage fuzzy load frequency control based on multi-objective harmony search algorithm in deregulated environment,” J. Oper. Autom.  Power Eng., vol. 1, no. 1, pp. 63-73, 2013.
[4]     M. Andreasson, H. Sandberg, D. Dimarogonas, and K. Johansson, “Distributed Integral Action: Stability Analysis and Frequency Control of Power Systems,” 51st IEEE Conf. Decis. Control, pp. 2077- 2083, 2012.
[5]     E. Planas, A. Gil-de-Muro, J. Andreu, I. Kortabarria, and I. Martinez de Alegria, “General aspects, hierarchical controls and droop methods in micro grids: a review,” Renew. Sustain. Energy Rev., pp. 147-159, 2013.
[6]     A. Del Barrio, S. Memik, M. Molina, J. Mendias, and R. Hermida, “A Distributed controller for Managing Speculative Functional Units in High Level Synthesis,” IEEE Trans.-Aided Des. Integr. Circuits Syst., vol. 30, pp. 350-363, 2011.
[7]     F. Katiraei, M. Iravani, and P. Lehn “Micro-grid autonomous operation during and subsequent to islanding process,” IEEE Trans. Power Delivery, vol. 20, no. 1, pp. 248-257, 2005.
[8]     F. Liu, Y. H. Song, J. Ma, S. Mei, and Q. Lu, “Optimal load-frequency control in restructured power systems. Generation,” IEE Proc.-Gener., Transm. Distrib., vol. 150, no. 1, pp. 87-95, 2003.
[9]     J. Machowski, J. W. Bialek, and J. R. Bumby “Power system dynamics: stability and control,” Wiley, 2008.
[10]  N. Senroy, G. T. Heydt, and V. Vittal “Decision tree assisted controlled islanding,” IEEE Trans.  Power Syst., vol. 21, no. 4, pp. 1790-1797, 2006.
[11]  B. Yang, V. Vittal, and G.T Heydt “Slow-coherency-based controlled islanding: A demonstration of the approach on the august 14, 2003 blackout scenario,” IEEE Trans. Power Syst., vol. 21, no. 4, pp. 1840-1847, 2006.
[12]  Momoh JA, Zhu JZ “Improved interior point method for OPF problems,” IEEE Trans.  Power Syst., vol. 14, no. 3, pp. 1114-1120, 1999.
[13]  K. Abaci and V. Yamacli “Differential search algorithm for solving multi-objective optimal power flow problem,” Int. J. Electr. Power Energy Sys., vol. 79, pp. 1-10, 2016.
[14]  S. Surender Reddy and C. Srinivasa Rathnam “Optimal Power Flow using Glowworm Swarm Optimization,” Int. J. Electr. Power Energy Syst., vol. 80, pp. 128-139, 2016.
[15]  S. Derafshi Beigvand, and H. Abdi “Optimal power flow in the smart grid using direct load control program,” J. Oper. Autom. Power Eng., vol. 3, no. 2, pp. 102-115, 2015.
[16]  R. Sahu, S. Panda, and U. Rout, “DE optimized parallel 2-DOF PID controller for load frequency control of power system with governor dead-band nonlinearity,” Int. J. Electr. Power Energy Syst., vol. 49, pp. 19-33, 2013.
[17]  S. Mirjalili, S. Mirjalili, and A. Lewis “Grey Wolf Optimizer,” Adv. Eng. Software, vol. 69, pp. 46-61, 2014.
[18]  Y. Sharma, and L. Saikia, “Automatic generation control of a multi-area ST-Thermal power system using Grey Wolf Optimizer algorithm based classical controllers,” Int. J. Electr. Power Energy Syst., vol. 73, pp. 853-862, 2015.
[19]  M. Andreasson, D. Dimarogonas, H. Sandberg, and K. Johansson “Distributed Control of Networked Dynamical Systems: Static Feedback, Integral Action and Consensus,” IEEE Trans. Autom. Control, vol. 59, no. 7, pp. 1750-1764, 2014.
[20]  M. Andreasson, “Control of Multi-Agent Systems with Applications to Distributed Frequency Control Power Systems,” [Thesis]. Stockholm:  KTH R. Inst. Technol., 2013.