Application of Hybrid Differential Evolution–Grey Wolf Optimization Algorithm for Automatic Generation Control of a Multi-Source Interconnected Power System Using Optimal Fuzzy–PID Controller

2017 ◽  
Vol 45 (19) ◽  
pp. 2104-2117 ◽  
Author(s):  
Manoj Kumar Debnath ◽  
Ranjan Kumar Mallick ◽  
Binod Kumar Sahu
Keyword(s):  
Optimization Algorithm ◽  
Pid Controller ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Grey Wolf ◽  
Fuzzy Pid ◽  
Grey Wolf Optimization ◽  
Interconnected Power System ◽  
Fuzzy Pid Controller ◽  
Generation Control

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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