Automatic Voltage Generation Control for Two Area Power System Based on Particle Swarm Optimization

2016 ◽  
Vol 2 (1) ◽  
pp. 132 ◽  
Author(s):  
Ali M. Ali ◽  
M.A. Ebrahim ◽  
M.A. Moustafa Hassan
Keyword(s):  
Power Systems ◽  
Power System ◽  
Pid Controller ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Voltage Regulator ◽  
Swarm Optimization ◽  
Self Tuning ◽  
Voltage Generation ◽  
Generation Control

<p>This article presentes a PID controller for two area power system equipped with both automatic generation control and automatic voltage regulator loops. The research has been done to control two area power systems with PSO optimized self-tuning PID controller. The comparison between different controllers and the suggested PSO based controller illustrates that the proposed controller can generate the best dynamic response for a step load change. For this purpose, MATLAB-Simulink software is used. The obtained results are promising.</p>

A Hybrid PSO-LEVY Flight Algorithm Based Fuzzy PID Controller for Automatic Generation Control of Multi Area Power Systems

2017 ◽  
Vol 6 (2) ◽  
pp. 42-63 ◽  
Author(s):  
Ajit Kumar Barisal ◽  
Tapas Kumar Panigrahi ◽  
Somanath Mishra
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Pid Controller ◽  
Particle Swarm ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Fuzzy Pid ◽  
Swarm Optimization ◽  
Fuzzy Pid Controller ◽  
Generation Control

This article presents a hybrid PSO with Levy flight algorithm (LFPSO) for optimization of the PID controllers and employed in automatic generation control (AGC) of nonlinear power system. The superiority of the proposed LFPSO approach has been demonstrated with comparing to recently published Lozi map-based chaotic optimization algorithm (LCOA) and Particle swarm optimization to solve load-frequency control (LFC) problem. It is found that the proposed LFPSO method has robust dynamic behavior in terms of settling times, overshoots and undershoots by varying the system parameters and loading conditions from their nominal values as well as size and locations of disturbance. Secondly, a three-area thermal power system is considered with nonlinear as Generation Rate Constraints (GRC) and outperforms to the results of Bacteria Foraging algorithm based integral controller as well as hybrid Differential Evolution and Particle Swarm Optimization based fuzzy PID controller for the similar power system. Finally, the proficiency of the proposed controller is also verified by random load patterns.

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