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In this article, the assessment of new coordinated design of power system stabilizers (PSSs) and static var compensator (SVC) in a multimachine power system via statistical method is proposed. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is handled as an optimization problem. The bacterial swarming optimization (BSO), which synergistically couples the bacterial...
This manuscript presents an analysis of the dynamic performance of a multimachine power system in the presence of device Flexible AC Transmission Systems (FACTS) acting in conjunction with robust controllers. Model Power Sensitivity (PSM) is used to represent the multimachine power system. The design of the controllers Power System Stabilizers (PSS) and Power Oscillation Damping (POD) is performed...
This paper presents a new coordinated control scheme based on wide-area signals to coordinate local controllers The coordinated controller transmits the supplementary signals to the local controllers. The proposed scheme uses the energy function based on Lyapunov's stability theory for modeling a coordinated controller. In this study, the coordinated controller which is installed at system control...
A genetic algorithm based optimization technique for optimum design of power system damping controller in a multi-machine power system has been developed. In this technique, the genetic algorithm involves an objective function that is based on the integral of squared-time- squared-error criterion. Parameters of the power system stabilizers are tuned via simulation experiments based on a non-linear...
This paper presents a global tuning procedure for FACTS power oscillation damping (POD) and power system stabilizers (PSSs) in a multi-machine power system using real coded genetic algorithm. The stabilizer's gains are obtained through the minimization of an objective function based on the damping ratio. The proposed controllers were simultaneously designed and they have provided a coordinated control...
The effect of learning rate (LR) on the performance of a newly introduced evolutionary algorithm called population-based incremental learning (PBIL) is investigated in this paper. PBIL is a technique that combines a simple genetic algorithm (GA) with competitive learning (CL). Although CL is often studied in the context of artificial neural networks (ANNs), it plays a vital role in PBIL in that the...
In this paper, a multiobjective design of the multi-machine power system stabilizers (PSSs) using chaotic optimization Algorithm (COA) is proposed. COA, which have the features of easy implementation, short execution time and robust mechanisms of escaping from local optimum, is a promising tool for engineering applications. The PSSs parameters tuning problem is converted to an optimization problem...
In this paper, an improved Takagi-Sugeno fuzzy logic PSS is proposed with a novel automatic design method called CDCARLA. As an optimal control system, the proposed PSS can be designed for optimizing any reasonable objective function based on any desired technical requirements. As another advantage of the proposed method, it needs no information about the dynamical model of the power system. And as...
This paper describes nonlinear parameter estimation of non-smooth nonlinear device by using a feed-forward neural network (FFNN) embedded in a hybrid system modeling. The hybrid systems are modeled by the differential-algebraic-impulsive-switched (DAIS) structure. In a switched linear hybrid system, the FFNN is applied to identify full dynamics of an objective function J formed by the states. Moreover,...
This paper focuses on the systematic optimal tuning of a power system stabilizer (PSS), which can improve the system damping performance immediately following a large disturbance. As the PSS consists of both linear parameters, such as the gain and time constant, and non-smooth nonlinear parameters, such as saturation limits of the PSS, two methods are applied to achieve optimal tuning of all parameters...
Power system stabilizers (PSSs) provide stabilizing control signals to excitation systems to damp out inter-area and intra-area oscillations. The PSS must be optimally tuned to accommodate the variations in the system dynamics. Designing multiple optimal PSSs is a challenging task for researchers. This paper presents the comparison between two bio-inspired algorithms: a small population based particle...
Power system stabilizers (PSSs) are used to generate supplementary control signals to excitation systems in order to damp out local and inter-area oscillations. In this paper, a modified particle swarm optimization (PSO) algorithm with a small population is presented for the design of optimal PSSs. The small population based PSO (SPPSO) is used to determine the optimal parameters of several PSSs simultaneously...
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