Types Of Power System Stabilizers Research Articles

Genetic-TLBO Algorithm for Power System Stabilizer

Background: A large number of nature-based optimization methods have been proposed to use as efficient tools in scientific studies. Genetic Algorithm (GA), which operates based on human genetical evolution, has been an outstanding mostly used solver in a wide range of applications. This algorithm reflects the process of natural selection where the fittest individuals are selected for reproduction in order to produce offspring of the next generation. Initialization, selection, crossover, and mutation are the main parts of the GA population-based method which enables GA to have a prominent explorative feature. On the other hand, the Teaching Learning Based Optimization algorithm (TLBO) is of great performance during searching for the optimum solution among individuals. Therefore, it is expected that the combination of both algorithms in a certain logical way improves the optimization time. Objective: The study intends to determine ways of improving performance of the TLBO algorithm to solve a complex non-linear problem. Power system studies are one of the most complex problems for analysis. Therefore, a powerful heuristic optimization procedure would have a valuable contribution in solving such problems. In addition, the proposed heuristic algorithm will help scientists to apply the technique to their problems. Materials and Methods: According to the aforementioned explanation, a new efficient optimization approach is proposed which optimizes the parameters of multi-machine power system stabilizers (PSSs). The TLBO algorithm includes two different stages in its main structure, which are aptly called teacher and student stages. The student stage of TLBO is replaced by the genetic algorithm in order to improve the explorative feature of the main TLBO. The PSS parameters are obtained for four PSSs which are connected to four generators. Results: The performance of the proposed stabilizer is compared with other formerly designed stabilizers reported in the literature consisting of multi-band PSSs for two areas four-machine power system. Simulation results demonstrate the effectiveness and robustness of the proposed PSS in damping local and inter-area oscillation modes under various disturbances and confirm its superiority in comparison with the other types of PSSs. Conclusion: : A search heuristic method like the genetic algorithm can dramatically improve the performance of meta-heuristic optimization technique. In actuality, the TLBO as a meta-heuristic optimization technique suffers from a direct search of random solutions in its primary stage. Then, the TLBO relinquishes some parts of search space which may restrict the algorithm to find absolute maximums or minimums. In this condition, the GA with a great ability in searching the whole search space effectively improves the TLBO. According to the obtained results, the proposed algorithm, named Genetic-TLBO, obviates the conventional TLBO flaws successfully.

Simulation And Analysis of An Intelligent Power System Stabilizer Using Fuzzy Logic

The basic aim of the power system stabilizer is to damp the fluctuations that occur on the rotating axis of the synchronous generator that result from noise or disturbance on the power system. This is achieved by producing an appropriate damping torque for these fluctuations across the excitation circuit of the generator and for a wide range of operation conditions. The study describes the types of power system stabilizers and giving an mathematical model of the power system that consists of a synchronous machine connected to the infinite bus though transmission lines. This has been achieved by simulating the electric and mechanical equations of power systems and proposing a methodological approach to design a Fuzzy Logic Power System Stabilize (FPSS) relaying in the design on the (Matlab/Fuzzy logic toolbox).Speed deviation (Δω) and acceleration (∆ ) of the synchronous machine are chosen as the input signals to the fuzzy controller in order to achieve a good dynamic performance .The complete range for the variation of each of the two controller inputs is represented by a 7×7 decision table, i.e. 49 rules using proportional derivative like fuzzy logic. The power system (SMIB) was tested with the presence and absence of the excitation system, then (CPSS) was added, and then (FPSS).The simulation results of the proposed fuzzy logic on )SMIB( gave a better dynamic response, decreased the settling time and good performance of the stabilizer in damping the fluctuations that arise in the speed of rotation of the generator and its active power in various operating conditions when proposed (FPSS) is compared with conventional PSS. The simulation results proved the superior performance of the proposed (FPSS).

EFFICIENT POWER OSCILLATION DAMPING CONTROL BY ADAPTIVE NEURO FUZZY CONTROLLER BASED POWER SYSTEM STABILIZER

Low frequency Inter-area oscillations are undesirable which affects the goals of maximum power transfer and optimal power flow. Power system stabilizers can be added to the automatic voltage regulators on the generators to reduce the effect of low frequency inter area oscillation. Different types of power system stabilizers are developed to reduce low frequency inter area oscillations inter but the area is still open for the efficient power stabilizer, for handling the power oscillations without increasing the system controller complexity. This paper presents a way to improve the dynamic stability of interconnected power systems by damping of inter area oscillations in two area four machine power system by designing of Adaptive Neuro Fuzzy Inference System based controller. The implementation is done with the Simulink of MATLAB 2012(b).The obtained results shows that ANIFS-PSS is capable of damping power oscillations in multi area system.

A multiobjective tuning approach of power system stabilizers using particle swarm optimization

This work presents an optimal tuning approach of power system stabilizers (PSSs) using multiobjective particle swarm optimization. Two types of PSSs are investigated, the conventional speed-based PSS type and a dual-input PSS type that uses the accelerating power as an additional input. The tuning problem of these PSSs is formulated as a minimization problem of a vector objective function characterizing the damping and the transient performance of the closed-loop system. A 3-machine 9-bus power system example is considered, and the speed-constraine multiobjective particle swarm optimization algorithm is used to solve the optimization problem. The results show that trade-offs exist between the 2 objective functions of the problem, and that the best trade-off is obtained with the dual-input PSS. The performance of the resulting PSSs is illustrated through numerical simulations considering different scenarios.

Multi-band power system stabilizer design by using CPCE algorithm for multi-machine power system

Synchronous generators are generally equipped with power system stabilizers (PSS) to damp out low frequency oscillations. Among different types of PSSs it has been recently shown that the new advanced stabilizer, called multi-band PSS (MB-PSS), has a better performance to cope with all global, inter area and local modes. All different types of PSSs are mainly designed based on one operating point of the system using a linear model. However, power system is inherently nonlinear and its operating conditions frequently change and the PSS performance may deteriorate. This paper develops a new design for MB-PSS in which the parameters are tuned by using a new Meta-heuristic optimization algorithm based on the combination of culture algorithm, particle swarm optimization (PSO) and co-evolutionary algorithms. In this new culture-PSO-co evolutionary (CPCE) algorithm, the characteristics of all three mentioned algorithms are combined and a new strong optimization technique is obtained. The proposed MB-PSS is tested on a multi-machine power system and results are compared with PSO-based MB-PSS (PSO-MB-PSS) and conventional MB-PSS (C-MB-PSS). Simulation results confirm the effectiveness of the proposed optimization tuning method for improving the power system dynamic stability.

A Comparison between Conventional and Optimal Power System Stabilizers for a Single Machine to an Infinite Bus Power System

The excitation control of synchronous generator in a single machine to an infinite bus (SMIB) power system is very important to improve the stability modes of power system. In addition to the usual or conventional excitation control techniques and speed governors, other devices proved its effectiveness to enhance better system stability like power system stabilizers (PSS) and static VAR compensators (SVC). In this paper, the PSS is used as an additional device to improve the SMIB power system stability. Two out of different control strategies were used; a conventional control technique (PI controller) and a linear optimal controller (LOC). A comparison between both types of PSSs was stated. The contribution of this paper is the design and application of an optimal-PSS and a PI-PSS to a synchronous generator connected to an infinite bus power system. KeywordsSingle machine to an infinite bus, power system stabilizer, excitation control, PI controller, linear optimal controller.

Parameter optimization of multimachine power system conventional stabilizers using CDCARLA method

In this paper, a novel Combinatorial Discrete and Continuous Action Reinforcement Learning Automata (CDCARLA) based approach for optimal design of multimachine power system stabilizers (PSSs) is presented. The proposed CDCARLA based design approach is a combined procedure of two optimization stages in discrete and continuous spaces for fast convergence and high optimization efficiency. The potential of the proposed approach in seeking the optimal settings of the widely used conventional lead-lag PSSs’ parameters is investigated and assessed in multimachine power systems. The performance and robustness of the proposed CDCARLA based PSS is evaluated under different power system disturbances. The performance of the proposed stabilizer is also compared with other stabilizers reported in the literature including the multi-band PSSs for a two-area four-machine power system. Simulation results show the effectiveness and robustness of the proposed CDCARLA PSS in damping local and inter area oscillation modes under various disturbances, and confirm its superiority in comparison with other types of PSSs.

Comparison of power system stabilizers for damping local mode oscillations

The Bureau of Reclamation has examined the damping of local mode oscillations using three types of power system stabilizers (PSS): internal frequency; electrical power; and accelerating power. Comparisons of operating characteristics such as PSS output noise and sensitivity to load changes are also included. Results are based on the analysis of field test data and analog computer simulation, Methods that can be used at remote sites during PSS alignment tests have been employed. >