Abstract
AbstractA new intelligent Automatic Generation Control (AGC) scheme based on Evolutionary Algorithms (EAs) and Fuzzy Logic concept is developed for a multi-area power system. EAs i.e. Genetic Algorithm–Simulated Annealing (GA–SA) are used to optimize the gains of Fuzzy Logic Algorithm (FLA)-based AGC regulators for interconnected power systems. The multi-area power system model has three different types of plants i.e. reheat, non-reheat and hydro and are interconnected via Extra High Voltage Alternate Current transmission links. The dynamic model of the system is developed considering one of the most important Governor Dead Band (GDB) non-linearity. The designed AGC regulators are implemented in the wake of 1% load perturbation in one of the control areas and the dynamic response plots are obtained for various system states. The investigations carried out in the study reveal that the system dynamic performance with hybrid GA–SA-tuned Fuzzy technique (GASATF)-based AGC controller is appreciably superior as...
Highlights
The growth of large interconnected power system is to minimize the occurrence of the black outs and providing an increasing power interchange among distinct system under the huge interconnected electric networks
The power system model under investigation is simulated on MATLAB/SIMULINK platform to carry out investigations with GASA-tuned Fuzzy Logic Controller (FLC) for the Automatic Generation Control (AGC) scheme
The proposed controller resulted in the response plots with less settling time, minimum peak overshoot and under shoot as compared to those obtained with IC and FLCbased AGC schemes
Summary
The growth of large interconnected power system is to minimize the occurrence of the black outs and providing an increasing power interchange among distinct system under the huge interconnected electric networks. The design of optimal AGC scheme for a three-area interconnected power system is investigated with three diverse controller’s i.e. classical integral control, FLA and GASA-tuned FLC controllers. A hybrid GASATF technique constitutes GA and SA approach to determine output fitness function from the fuzzy Mamdani algorithm This is used as the input for GA–SA technique to design the optimal gains for AGC scheme. The designed AGC scheme yielded ameliorated system dynamic performance under various operating conditions of a three-area interconnected hydro-thermal power systems with and without considering Governor Dead Band (GDB). The main objective was to minimize the ACEi augmented with penalty terms corresponding to transient response specifications in the system frequency and tie-line power flows These two disturbances yield the error for the AGC systems. Step 9: Reschedule step for every child; go to step
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