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 considers the design of Dual Proportional-
Integral (DPI) Load Frequency Control (LFC), using gravitational
search algorithm (GSA). The design is carried out for nonlinear
hydrothermal power system where generation rate constraint (GRC)
and governor dead band are considered. Furthermore, time delays
imposed by governor-turbine, thermodynamic process, and
communication channels are investigated. GSA is utilized to search
for optimal controller parameters by minimizing a time-domain based
objective function. GSA-based DPI has been compared to Ziegler-
Nichols based PI, and Genetic Algorithm (GA) based PI controllers
in order to demonstrate the superior efficiency of the proposed
design. Simulation results are carried for a wide range of operating
conditions and system parameters variations.
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.
Abstract: In an interconnected power system, any sudden small
load perturbation in any of the interconnected areas causes the
deviation of the area frequencies, the tie line power and voltage
deviation at the generator terminals. This paper deals with the study
of performance of intelligent Fuzzy Logic controllers coupled with
Conventional Controllers (PI and PID) for Load Frequency Control.
For analysis, an isolated single area and interconnected two area
thermal power systems with and without generation rate constraints
(GRC) have been considered. The studies have been performed with
conventional PI and PID controllers and their performance has been
compared with intelligent fuzzy controllers. It can be demonstrated
that these controllers can successfully bring back the excursions in
area frequencies and tie line powers within acceptable limits in
smaller time periods and with lesser transients as compared to the
performance of conventional controllers under same load disturbance
conditions. The simulations in MATLAB have been used for
comparative studies.
Abstract: The optimal design of PI controller for Automatic Generation Control in two area is presented in this paper. The concept of Dual mode control is applied in the PI controller, such that the proportional mode is made active when the rate of change of the error is sufficiently larger than a specified limit otherwise switched to the integral mode. A digital simulation is used in conjunction with the Hooke-Jeeve’s optimization technique to determine the optimum parameters (individual gain of proportional and integral controller) of the PI controller. Integrated Square of the Error (ISE), Integrated Time multiplied by Absolute Error(ITAE) , and Integrated Absolute Error(IAE) performance indices are considered to measure the appropriateness of the designed controller. The proposed controller are tested for a two area single nonreheat thermal system considering the practical aspect of the problem such as Deadband and Generation Rate Constraint(GRC). Simulation results show that dual mode with optimized values of the gains improved the control performance than the commonly used Variable Structure .
Abstract: The design of Automatic Generation Control (AGC) system plays a vital role in automation of power system. This paper proposes Hybrid Neuro Fuzzy (HNF) approach for AGC of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The advantage of proposed controller is that it can handle the system non-linearities and at the same time the proposed approach is faster than conventional controllers. The performance of HNF controller has been compared with that of both conventional Proportional Integral (PI) controller as well as Fuzzy Logic Controller (FLC) both in the absence and presence of Generation Rate Constraint (GRC). System performance is examined considering disturbance in each area of interconnected power system.
Abstract: This paper is concerned with the application of small
rating Capacitive Energy Storage units for the improvement of
Automatic Generation Control of a multiunit multiarea power
system. Generation Rate Constraints are also considered in the
investigations. Integral Squared Error technique is used to obtain the
optimal integral gain settings by minimizing a quadratic performance
index. Simulation studies reveal that with CES units, the deviations
in area frequencies and inter-area tie-power are considerably
improved in terms of peak deviations and settling time as compared
to that obtained without CES units.