Abstract: This paper demonstrates dynamic performance evaluation of load frequency control (LFC) with different intelligent techniques. All non-linearities and physical constraints have been considered in simulation studies such as governor dead band (GDB), generation rate constraint (GRC) and boiler dynamics. The conventional integral time absolute error has been considered as objective function. The design problem is formulated as an optimisation problem and particle swarm optimisation (PSO), bacterial foraging optimisation algorithm (BFOA) and differential evolution (DE) are employed to search optimal controller parameters. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic control (FLC) for the same interconnected power system. The comparison is done using various performance measures like overshoot, undershoot, settling time and standard error criteria of frequency and tie-line power deviation following a step load perturbation (SLP). It is noticed that, the dynamic performance of proposed controller is better than FLC. Further, robustness analysis is carried out by varying the time constants of speed governor, turbine, tie-line power in the range of +40% to -40% to demonstrate the robustness of the proposed DE optimized PID controller.
Abstract: This paper represents performance of particle swarm
optimisation (PSO) algorithm based integral (I) controller and
proportional-integral controller (PI) for interconnected hydro-thermal
automatic generation control (AGC) with generation rate constraint
(GRC) and Thyristor controlled phase shifter (TCPS) in series with
tie line. The control strategy of TCPS provides active control of
system frequency. Conventional objective function integral square
error (ISE) and another objective function considering square of
derivative of change in frequencies of both areas and change in tie
line power are considered. The aim of designing the objective
function is to suppress oscillation in frequency deviations and change
in tie line power oscillation. The controller parameters are searched
by PSO algorithm by minimising the objective functions. The
dynamic performance of the controllers I and PI, for both the
objective functions, are compared with conventionally optimized I
controller.
Abstract: This paper presents a differential evolution algorithm to design a robust PI and PID controllers for Load Frequency Control (LFC) of nonlinear interconnected power systems considering the boiler dynamics, Governor Dead Band (GDB), Generation Rate Constraint (GRC). Differential evolution algorithm is employed to search for the optimal controller parameters. The proposed method easily copes of with nonlinear constraints. Further the proposed controller is simple, effective and can ensure the desirable overall system performance. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic controller for the same power systems. The comparison is done using various performance measures like overshoot, settling time and standard error criteria of frequency and tie-line power deviation following a 1% step load perturbation in hydro area. It is noticed that, the dynamic performance of proposed controller is better than fuzzy logic controller. Furthermore, it is also seen that the proposed system is robust and is not affected by change in the system parameters.