Amin Safari

Iteration particle swarm optimization procedure for economic load dispatch with generator constraints

In this paper, iteration particle swarm optimization (IPSO) has been applied to determine the feasible optimal solution of the economic load dispatch (ELD) problem considering various generator constraints. Many realistic constraints, such as ramp rate limits, generation limitation, prohibited operating zone, transmission loss and nonlinear cost functions are all considered for practical operation. The performance of the classical particle swarm optimization (CPSO) greatly depends on its parameters, and it often suffers the problem of being trapped in local optima. A new index named, Iteration Best, is incorporated in CPSO to enrich the searching behavior, solution quality and to avoid being trapped into local optimum. Two test power systems, including 6 and 15 unit generating, are applied to compare the performance of the proposed algorithm with PSO, chaotic PSO, hybrid GAPSO, self organizing hierarchical PSO (SOH_PSO) methods. The numerical results affirmed the robustness and proficiency of proposed approach over other existing methods.

Controller Design of STATCOM for Power System Stability Improvement Using Honey Bee Mating Optimization

Damping of low frequency electromechanical oscillations is very important for a safe system operation. The fast acting, of a static synchronous compensator (STATCOM) which is capable of improving both steady state and dynamic performance permits newer approaches to system stabilization. This paper presents a novel methodology for tuning STATCOM based damping controller in order to enhance the damping of system low frequency oscillations. The design of STATCOM parameters are considered an optimization problem according to the time domain-based objective function solved by a Honey Bee Mating Optimization (HBMO) algorithm that has a strong ability to find the most optimistic results. To validate the results accuracy, a comparison with Genetic Algorithm (GA) has been made. The effectiveness of the proposed controller is demonstrated through nonlinear time-domain simulation and some performance indices studies over a wide range of loading conditions. The simulation study shows that the designed controller by HBMO performs better than GA in finding the solution. Moreover, the system performance analysis under different operating conditions shows that the φ based controller is superior to the C based controller.

A PSO Procedure for a Coordinated Tuning of Power System Stabilizers for Multiple Operating Conditions

The problem of coordinated tuning stabilizers in multi-machine power systems is formulated here as a sequence ofoptimization problems. The design problem of stabilizers is converted to a nonlinear optimization problem with a multiobjectivefitness function. The proposed method employs particle swarm optimization (PSO), an algorithm to searchfor optimal parameter settings of a widely used conventional fixed-structure lead-lag power system stabilizers(CPSSs). One of the main advantages of the proposed approach is its robustness to the initial parameter settings. Inaddition, the quality of the optimal solution does not rely on the initial guess. The robustness and performance of thenewly designed controllers is evaluated in a large sixteen-machine power system subjected to different loadingconditions in comparison with the genetic algorithm (GA) based PSSs design. The superiority of the controllerdesigned is demonstrated through the nonlinear time-domain simulation and some performance indices studies. Theresults analysis reveals that the tuned PSSs with proposed objective function has an excellent capability in dampingpower system low-frequency oscillations.

Optimal tuning of Power System Stabilizers in a multi-machine system using firefly algorithm

One of the most important characteristics of power systems as dynamic plants is maintaining their stability when subjected to disturbances. Power System Stabilizers (PSSs) are the most used devices to damp Low Frequency Oscillations (LFO) and enhance power system dynamic stability due to their flexibility, easy implementation and low cost. This paper presents a novel approach for designing PSSs to improve damping of power system low frequency oscillations under dynamic disturbances. This problem is formulated as a multi-objective optimization problem with the aim of tuning the PSSs parameters in the case of eigenvalues analysis and nonlinear time-domain simulation. The Firefly (FF) Algorithm which has been found robust in solving these kinds of optimization problems is selected as a tool to find the optimum solution. Simulations are executed on the New England- New York sixteen-machine power system under different operating conditions. Results obtained from this method are presented and compared with the those using Particle Swarm Optimization (PSO) method. At last, for better deduction, comparisons are done through some performance indices. Results confirm better performance of the designed PSSs based on the proposed method in amending damping torque and system oscillations stability.

Robust PWMSC Damping Controller Tuning on the Augmented Lagrangian PSO Algorithm

The paper introduces a new flexible alternating current transmission systems (FACTS) controller based on pulse width modulated series compensator (PWMSC) for damping inter-area oscillations in power systems. The PWMSC can modulate the impedance of a transmission line through the variation of the duty cycle of AC link. The main purpose of this work is to verify the capability of the PWMSC to mitigate low frequency oscillations. For this reason, a novel current injection model of PWMSC is proposed and incorporated in the system model. This study proposes a novel tuning strategy for robust PWMSC damping controller based on the augmented Lagrangian particle swarm optimization (ALPSO) satisfying the multiple H∞ performance criteria. Proposed method does not need any conservative assumption unlike the conventional techniques, and often enables us to find the desired parameters of controller just by solving the constrained optimization problem in a straightforward way. In the paper, a verification of the designed controller by means of digital simulations of single machine and four-machine power systems is presented. The net results show that the proposed controller improves the stability of both test systems significantly in a number of fault cases at different levels of power flow in tie-line.

Nonlinear Time Response Optimization using Imperialist Competitive Algorithm for Tuning Robust Power System Stabilizers

Abstract In this paper, a new approach based on Imperialist Competitive Algorithm (ICA) is proposed to tune the optimal parameters of the Power System Stabilizers (PSSs) to damp the low-frequency oscillations in a multi-machine power system. The paper uses the ICA to address PSSs design problem so as to overcome the deficiency of traditional derivative-based methods and other heuristic algorithms. The main objective of this procedure is to simultaneously optimize parameters of those PSSs having fixed parameters in coping with the complex nonlinear natures of the power system. The robustness and efficiency of the newly designed stabilizers is evaluated in a New England-New York sixteen-machine power system subjected to the different operating conditions and different types of disturbances in comparison with the genetic algorithm and linear matrix inequality based PSSs design methods. The superiority of the proposed stabilizers is demonstrated through the nonlinear simulation and some dynamic performance indices studies. The results analysis reveals that the tuned ICA-PSSs have an excellent capability in damping of low frequency oscillations.

PWMSC Controller Design for Damping Electromechanical Oscillations

Pulse Width modulated based Series Compensator (PWMSC), a newly FACTS device, can modulate the impedance of a transmission line through the variation of the duty cycle of a train of pulses with fixed frequency, resulting in improvement of system performance. In this study, a current injection model of PWMSC is proposed and incorporated in the transmission system model. The purpose of the work reported in this paper is to design an oscillation damping controller for PWMSC to damp low frequency oscillations. We have used the residue method to the linearized equations of the power system for multiple operating conditions and obtained a generalized form which is suitable for different damping controller input-output channels and therefore suitable for different control devices. The case study results show that the proposed controller is very effective to mitigate the power system critical modes of oscillation.

A Novel Current Injection Model of GCSC for Control and Damping of Power System Oscillations

The paper proposes the theory and the modeling technique of the new invention of the flexible AC transmission system (FACTS) device, i.e., Gate controlled series capacitor (GCSC) for power flow control of power transmission lines and damping of low-frequency oscillations. In this study, a current injection model of the GCSC is used for studying the effect of the GCSC on the low-frequency oscillations, which is incorporated in the transmission system model. To be sure of optimal adjustment of the applied damping controller, the particle swarm optimization algorithm is employed as an efficient heuristic optimizer to And out the near global optimum set of the damping controller parameters. The proposed model is applied to a damping controller design of a multi-machine power system. Detailed simulations are carried out with MATLAB/SIMULINK environment and the effect of the GCSC-based damping controller and the current injection model over the system stability is studied.