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Power system stabilizers have been widely used in generation systems to enhance the transient stability of the power system. Low frequency oscillation may occur as a result of excitation system which exerts a phase lag. Conventional power system stabilizers using a lead-lag controller have been used in utility for decades. Proper tunning of the parameters of stabilizer is essential for effectiveness...
This paper presents a study of tuning the existing power system stabilizers (PSSs) of the Saudi Electricity Company (SEC) power system and its effect on increasing the power transfer limit of the interconnection between Eastern Operating Area (SECE-OA) and Central Operating Area (SEC-COA). This work is also investigating the optimal location of installing additional power system stabilizers (PSSs)...
In this paper, a complementary damping controller is presented for the Static Synchronous Series Compensator (SSSC). Power system stability improvement by SSSC-based damping controller and Power System Stabilizers (PSSs) thoroughly scrutinized. The Genetic Algorithm (GA) due to its being immediately perceptive, ease of performing, and the ability to impressively solve the highly non-linear objective...
In this paper, a neural networks (NN) based adaptive sliding mode controller (SMC) is introduced. The selection of SMC feedback gains is normally based on one operating point and thus the performance of the controller away from the design operating point is, of necessity, a compromise. The adaptive SMC is proposed to overcome the limitations imposed on the effectiveness of the SMC under different...
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 Power System Stabilizer (PSS) tuning procedure based on a Parallel Genetic Algorithm (PGA). The procedure is applied to the simultaneous tuning of 61 PSSs, using their actual models in the entire Brazilian Interconnected Power System (BIPS) modeled with 3849 buses. Heavy, median and light loading conditions were considered during the tuning process, to ensure control robustness...
This paper discusses the design of Power System Stabilizers (PSSs) using an Adaptive Mutation Breeder Genetic Algorithm (BGA) and Population Based Incremental Learning (PBIL). BGA is a new form of evolutionary algorithm. It uses the same idea of survival of the fittest like the Genetic Algorithms, however unlike GA; BGA uses the concept of artificial breeding, whereby the offspring takes the best...
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...
Power system stability improvement by means of instantaneous coordinated design of typical power system stabilizers (PSSs) and flexible ac transmission systems power oscillation damping (FACTS POD) controller is comprehensively investigated in this paper. The controller gains are optimized instantaneously using real-coded genetic algorithm (RCGA) to achieve a total optimal damping behavior. Simulation...
This paper discusses the design and implementation of power system stabilizers based on newly introduced evolutionary algorithms, namely the population- based incremental learning (PBIL) and the breeder genetic algorithm (BGA) with adaptive mutation. The designed PSSs were implemented on a power system experimental setup and the experimental results are presented in this paper. A conventional power...
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, we investigate the ability of improved version of Strength Pareto Evolutionary Algorithm, namely SPEA2, as a multi-objective Algorithm. This algorithm is applied to design two power system stabilizers (PSSs) coordinately for multi-machine power system to damp the inter-area oscillation. To fulfill this desire, the parameters of the PSSs are coordinately determined by SPEA2 using two...
Wide-area controllers have been proposed to enhance the dynamic performance of large interconnected power systems. The time delay existing in the data communication may be a detriment to wide area control system stability. This paper analyzes the effect of time delay on the additional interarea damping control (AIADC) design of PSS. The AIADC is proposed for generators' excitation controllers and...
This paper presents an adaptive fuzzy logic power system stabilizer (FLPSS). A two-stage technology of FLPSS adaptation is considered taking into account real conditions in a bulk electric power system. A genetic algorithm (GA) is applied for tuning parameters of FLPSS. An artificial neural network (ANN) is used on-line to adapt the FLPSS to changes in operating conditions
Power system stability enhancement via coordinated design of power system stabilizers (PSSs) and STATCOM-based damping stabilizers is thoroughly investigated in this paper. This study presents a singular value decomposition (SVD) based approach to assess and measure the controllability of the poorly damped electromechanical modes by different control inputs. The coordination among the proposed damping...
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