Showing papers by "Binod Kumar Sahu published in 2014"

Hybrid differential evolution particle swarm optimisation optimised fuzzy proportional–integral derivative controller for automatic generation control of interconnected power system

Abstract: A novel fuzzy proportional–integral derivative (PID) controller is proposed in this study for automatic generation control (AGC) of interconnected power systems. The optimum gains of the proposed fuzzy PID controller are optimised employing a hybrid differential evolution particle swarm optimisation (DEPSO) technique using an integral of time multiplied by absolute value of error criterion. The superiority of hybrid DEPSO algorithm over differential evolution and particle swarm optimisation (PSO) algorithm has also been demonstrated. The results are also compared with some recently published approaches such as artificial bee colony and PSO based proportional–integral/PID controllers for the same interconnected power systems. Furthermore, performance of the proposed system is analysed by varying the different parameters such as loading condition, system parameters and objective functions. It is observed that the optimum gains of the proposed fuzzy PID controller need not be reset even if the system is subjected to variation in loading condition and system parameters. Finally, the study is extended to a three area system considering generation rate constraint to demonstrate the ability of the proposed approach to cope with multiple interconnected systems. Comparison with previous AGC methods reported in the literature validates the significance of the proposed approach.

Tuning and Assessment of Proportional–Integral–Derivative Controller for an Automatic Voltage Regulator System Employing Local Unimodal Sampling Algorithm

Abstract: —This article presents an approach for obtaining proportional–integral–derivative controller parameters for an automatic voltage regulator system based on a local unimodal sampling optimization algorithm. A conventional integral time of squared error objective function and modified objective functions in terms of integral time of absolute error, integral of absolute error, integral of squared error, peak overshoot, and settling time with appropriate weighting factors are employed to tune the controller parameters. Different objective functions are employed to obtain optimized proportional–integral–derivative controller gains. Superiority of proposed technique over some recently published modern heuristic optimization techniques, such as artificial bee colony algorithm, particle swarm optimization algorithm, and differential evolution algorithm, for the same automatic voltage regulator system is demonstrated. Simulation results reveal that the proposed proportional–integral–derivative controlled au...

Automatic voltage regulator using TLBO algorithm optimized PID controller

Abstract: This paper deals with design and analysis of AVR using proportional-integral-derivative (PID) controller optimized by Teaching Learning Based Optimization (TLBO) algorithm The optimum gain of the controller for the proposed model is obtained with objective function as Integral Time Absolute Error (ITAE). The performance of the system is found to be better in every aspect in terms of the settling point, rise point & peak overshoot. By changing the different components of AVR (sensor, generator, exciter & amplifier) by ±50 % robustness analysis is performed.

Application of hybrid DEPSO algorithm to study the performance of different PID controller structures for automatic generation control of a two-area multi-units interconnected power system

Abstract: This paper deals with design and analysis of automatic generation control (AGC) of a two area four unit interconnected thermal power system. Three different structures of proportional integral-derivative (PID) controller are used to study the transient response of the proposed system. Areal consists of two thermal generating units with reheat turbines and area2 has two thermal generating units with non-reheat turbines. The gains of PID controllers are optimized by using a novel hybrid Differential Evolution-Particle Swarm Optimization (DEPSO) technique. Step load perturbation (SLP) of 1 % is applied in areal to study the performance of different structures of PID controllers. Finally it is observed that the 3rd PID controller configuration performs better than the other two.

Proper selection of different parameters of DE algorithm to study the dynamic performance of AGC in a two area hydrothermal system

Abstract: In this paper a novel attempt is made to select the proper strategy and the control parameters of differential evolution (DE) algorithm to design the gains of proportional-integral-derivative (PID) controllers for automatic generation control (AGC) of an interconnected two equal area hydrothermal system. The hydro area is equipped with a mechanical governor and the thermal area with a reheat turbine. The best strategy and proper values of control parameters of DE algorithm are determined by applying 1% SLP to thermal area. The PID controller gains are tuned using DE algorithm with the best strategy and control parameters. Finally the dynamic response of the proposed two area system is studied with optimum controller gains.

area multi-units interconnected power system Application of Hybrid DEPSO algorithm to study the performance of different PID controller structures for automatic generation control of a two-

Abstract: This paper deals with design and analysis of automatic generation control (AGC) of a two area four unit interconnected thermal power system. Three different structures of proportional integral- derivative (PID) controller are used to study the transient response of the proposed system. Area1 consists of two thermal generating units with reheat turbines and area2 has two thermal generating units with non-reheat turbines. The gains of PID controllers are optimized by using a novel hybrid Differential Evolution- Particle Swarm Optimization (DEPSO) technique. Step load perturbation (SLP) of 1 % is applied in area1 to study the performance of different structures of PID controllers. Finally it is observed that the 3 rd PID controller configuration