Rabindra Kumar Sahu

Application of Firefly Algorithm for Load Frequency Control of Multi-area Interconnected Power System

Abstract—In this article, a firefly algorithm is proposed for load frequency control of multi-area power systems. Initially a two equal area non-reheat thermal system is considered and the optimum gains of the proportional integral/proportional integral derivative controller are optimized employing the firefly algorithm technique. The superiority of the proposed approach is demonstrated by comparing the results with some recently published techniques such as genetic algorithm, bacteria foraging optimization algorithm, differential evolution, particle swarm optimization, hybrid bacteria foraging optimization algorithm-particle swarm optimization, and Ziegler–Nichols-based controllers for the same interconnected power system. Further, the proposed approach is extended to a three-unequal-area thermal system considering generation rate constraint and governor dead-band. Investigations reveal on comparison that proportional integral derivative controller provides much better response compared to integral and proportional integral controllers. Additionally, robustness analysis is carried out by varying the operating load condition and time constants of speed governor, turbine, and inertia constant in the range of +50 to –50% from their nominal values as well as the size and position of step load perturbation to demonstrate the robustness of the proposed firefly algorithm optimized proportional integral derivative controller.

A novel hybrid gravitational search and pattern search algorithm for load frequency control of nonlinear power system

Selection of objective function and controller structure is vital for controller design.An objective function using ITAE, damping ratio and settling times is proposed.The concept is applied to design an hGSA-PS-based PI/PID controller for LFC.Nonlinear interconnected power system model with GRC, GDB and time delay is considered. In this paper, a hybrid gravitational search algorithm (GSA) and pattern search (PS) technique is proposed for load frequency control (LFC) of multi-area power system. Initially, various conventional error criterions are considered, the PI controller parameters for a two-area power system are optimized employing GSA and the effect of objective function on system performance is analyzed. Then GSA control parameters are tuned by carrying out multiple runs of algorithm for each control parameter variation. After that PS is employed to fine tune the best solution provided by GSA. Further, modifications in the objective function and controller structure are introduced and the controller parameters are optimized employing the proposed hybrid GSA and PS (hGSA-PS) approach. The superiority of the proposed approach is demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as firefly algorithm (FA), differential evolution (DE), bacteria foraging optimization algorithm (BFOA), particle swarm optimization (PSO), hybrid BFOA-PSO, NSGA-II and genetic algorithm (GA) for the same interconnected power system. Additionally, sensitivity analysis is performed by varying the system parameters and operating load conditions from their nominal values. Also, the proposed approach is extended to two-area reheat thermal power system by considering the physical constraints such as reheat turbine, generation rate constraint (GRC) and governor dead band (GDB) nonlinearity. Finally, to demonstrate the ability of the proposed algorithm to cope with nonlinear and unequal interconnected areas with different controller coefficients, the study is extended to a nonlinear three unequal area power system and the controller parameters of each area are optimized using proposed hGSA-PS technique.

Design and analysis of tilt integral derivative controller with filter for load frequency control of multi-area interconnected power systems.

In this paper, a novel Tilt Integral Derivative controller with Filter (TIDF) is proposed for Load Frequency Control (LFC) of multi-area power systems. Initially, a two-area power system is considered and the parameters of the TIDF controller are optimized using Differential Evolution (DE) algorithm employing an Integral of Time multiplied Absolute Error (ITAE) criterion. The superiority of the proposed approach is demonstrated by comparing the results with some recently published heuristic approaches such as Firefly Algorithm (FA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) optimized PID controllers for the same interconnected power system. Investigations reveal that proposed TIDF controllers provide better dynamic response compared to PID controller in terms of minimum undershoots and settling times of frequency as well as tie-line power deviations following a disturbance. The proposed approach is also extended to two widely used three area test systems considering nonlinearities such as Generation Rate Constraint (GRC) and Governor Dead Band (GDB). To improve the performance of the system, a Thyristor Controlled Series Compensator (TCSC) is also considered and the performance of TIDF controller in presence of TCSC is investigated. It is observed that system performance improves with the inclusion of TCSC. Finally, sensitivity analysis is carried out to test the robustness of the proposed controller by varying the system parameters, operating condition and load pattern. It is observed that the proposed controllers are robust and perform satisfactorily with variations in operating condition, system parameters and load pattern.

Application of Firefly Algorithm for AGC Under Deregulated Power System

In this paper, Proportional–Integral–Derivative controller with derivative Filter (PIDF) is proposed for Automatic Generation Control (AGC) problem of four area reheat thermal power systems under deregulated environment by considering the physical constraints such as Generation Rate Constraint (GRC) and Governor Dead Band (GDB) nonlinearity. The system is investigated in all possible scenarios under deregulated environment. The gains of the controllers are optimized using an Integral of Time multiplied by Absolute value of Error (ITAE) criterion employing of Firefly Algorithm (FA).The performance of some diverse classical controllers such as Integral (I), Proportional–Integral (PI) and PIDF controllers are compared under poolco based scenario. Simulation results reveal that the performance of the system is better with PIDF controller compared to others.

Gravitational Search Algorithm based Automatic Generation Control for interconnected power system

This paper presents the design and performance analysis of Gravitational Search Algorithm (GSA) based Proportional-Integral (PI) controller for Automatic Generation Control (AGC) of an interconnected power system. A two area non-reheat thermal system equipped with PI controllers which is widely used in literature is considered for the design and analysis purpose. The design problem is formulated as an optimization problem and GSA is employed to search for optimal controller parameters. Three different objective functions using Integral Time multiply Absolute Error (ITAE), damping ratio of dominant eigen values and settling times of frequency and tie line power deviations with appropriate weight coefficients are derived in order to increase the performance of the controller. The superiority of the proposed GSA optimized PI controller is demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as Bacteria Foraging Optimization Algorithm (BFOA) and Genetic Algorithm (GA) based PI controller for the same interconnected power system. It is observed that the dynamic performance of GSA optimized PI controller is better than BFOA and GA optimized PI controllers.

Multi-objective optimization technique for TCSC-based supplementary damping controller design

Design of an optimal controller requires optimization of multiple performance measures that are often noncommensurable and competing with each other. Design of such a controller is indeed a multi-objective optimization problem. Being a population based approach; Genetic Algorithm (GA) is well suited to solve multi-objective optimization problems. This paper investigates the application of GA-based multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based supplementary damping controller. The design objective is to improve the power system stability with minimum control effort. The proposed technique is applied to generate Pareto set of global optimal solutions to the given multi-objective optimization problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.

Modelling, simulation and optimal design of a TCSC-based controller in a power system

This paper presents a MATLAB/Simulink-based modelling and simulation of a power system installed with a thyristor controlled series compensator (TCSC)-based controller which is suitable for carrying out power system stability studies. The synchronous generator is represented by one field circuit and one equivalent damper on q-axis known as the Model 1.1, so that the impact of TCSC on power system stability can be more reasonably evaluated. Further, a TCSC-based controller has been designed for improving the system damping. The design problem of the proposed controller is formulated as an optimisation problem and differential evolution (DE) optimisation technique is employed to search for the optimal controller parameters. A detailed analysis on the selection of control signals, both local (line current) and remote (speed deviation) signals, on the effectiveness of the TCSC controller is carried out and simulation results are presented.

Sensitivity Analysis of Load-Frequency Control of Power System Using Gravitational Search Algorithm

This paper investigates the sensitivity analysis of load-frequency control for multi area power system based Proportional Integral Derivative controller with derivative Filter (PIDF) by Gravitational Search algorithm (GSA). At first, a two area non reheat thermal system without physical constraints is considered. A modified objective function which includes ITAE, damping ratio of dominant eigenvalues, settling times of frequency and peak overshoots with appropriate weight coefficients is proposed. Further, the proposed objective function is extended to a more realistic power system model by considering the physical constraints such as reheat turbine, Generation Rate Constraint (GRC) and Governor Dead Band nonlinearity. Finally the robustness of the system is verified, with operating load condition and time constants of speed governor, turbine, tie-line power are changed from their nominal values in the range of +50% to -50% in steps of 25%. It is observed that the proposed controllers are robust and perform satisfactorily for a wide range of the system parameters and operating load conditions.

Application of Search Group Algorithm for Automatic Generation Control of Interconnected Power System

A novel search group algorithm (SGA) technique with PID controller is proposed for an application toward multi-area interconnected power system-based automatic generation control (AGC). A reheat thermal power system over three unequal areas is considered. The system includes the nonlinearity parameters such as GRC and GDB. The supremacy of SGA tuned PID controller is projected with a comparative empirical result over recently published firefly algorithm (FA) optimized technique tuned PID controller for the similar multi-area power system which is interconnected. Simulation study confirms that the proposed SGA technique is better as compare to FA technique for the system.

Firefly algorithm optimised PID controller for automatic generation control with redox flow battery

In this article, firefly algorithm-based proportional-integral-derivative controller is employed for the best solution of automatic generation control problem. Initially, a multi-area multi-source system having thermal, hydro and nuclear generating units in each area are considered for analysis purpose with all the probable physical constraints such as boiler dynamics, governor dead band and generation rate constraint. To show the supremacy of proposed FA optimised PID controller, the results are compared with integral and proportional-integral controller for the same power system employing integral time multiplied absolute error as an objective function. Further, to improve the dynamic responses of the system, an energy storage device, redox flow battery is installed in each area. From the simulation results, it is examined that the FA optimised PID controller with RFBs provided the best results compared to others. Finally, to study the robustness of the proposed controller is investigated over a wide variation of system parameters (−25% to +25%) and loading condition. For superior investigation, the proposed method is also investigated by applying random step load and sinusoidal disturbances.