scholarly journals Performance Assessment of Fuzzy Logic Power System Stabilizer on North Benghazi Power Plant

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
T. Hussein ◽  
A. Shamekh
Keyword(s):  
Fuzzy Logic ◽  
Power Plant ◽  
Power System ◽  
Optimization Technique ◽  
Operating Conditions ◽  
Power System Stabilizer ◽  
Particle Swarm Optimization Technique ◽  
System Output ◽  
System Stabilizer ◽  
One Machine

Fuzzy logic design has been implemented online to tune the power system stabilizer gain (KPSS). To assess the performance of the proposed technique, Benghazi North Power Plant (BNPP), at eastern Libyan network, has been utilized as a power system stabilizer (PSS) benchmark. The design considers different operating conditions and large disturbance. A selection of fuzzy rules is derived by means of system output power to tune KPSS, whereas Particle Swarm Optimization technique (PSO) is exploited to calculate the PSS parameters offline according to real-time measurements of the considered plant. Several simulation scenarios have been conducted to show the effectiveness of the proposed PSS in damping of local and interarea modes of oscillation of one-machine infinite-bus system. The study also contains comparison between the proposed technique and conventional PSS (CPSS).

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

2020 ◽  
Vol 27 (4) ◽  
pp. 70-86
Author(s):  
firas AlDurze ◽  
sura Abdullah
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Synchronous Machine ◽  
Operating Conditions ◽  
Superior Performance ◽  
Power System Stabilizer ◽  
Operation Conditions ◽  
Wide Range ◽  
Simulation Results ◽  
System Stabilizer

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 (∆ώ) 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).

Optimal design of multi-machine power system stabilizer using robust ant colony optimization technique

2011 ◽  
Vol 34 (7) ◽  
pp. 829-840 ◽  
Author(s):  
M Mary Linda ◽  
N Kesavan Nair
Keyword(s):  
Power Systems ◽  
Power System ◽  
Ant Colony Optimization ◽  
Optimization Technique ◽  
Operating Conditions ◽  
Ant Colony ◽  
Fine Tuning ◽  
Power System Stabilizer ◽  
System Stabilizer ◽  
Genetic Local Search

In this paper, a multi-objective design of the multi-machine Power System Stabilizer (PSS) using Ant Colony Optimization (ACO) is proposed. The fine tuning of PSS parameters problem is converted to an optimization problem that is resolved by an ACO-based dominant metaheuristic technique. The strength of the proposed ACO-based PSS is tested on two different multi-machine power systems under diverse operating conditions. The outcomes of the proposed ACOPSS are compared with the Conventional PSS, Genetic Local Search-based PSS, Chaotic Optimization-based PSS and Particle Swarm Optimization-based PSS (PSOPSS). From the simulation results it can be inferred that the ACOPSS reduces the settling time and maximum overshoot more than the other techniques.

Tuning of Power System Stabilizer (Unitrol D) in Benghazi North Power Plant

2013 ◽  
Vol 2 (2) ◽  
pp. 32-43 ◽  
Author(s):  
Tawfiq H. Elmenfy
Keyword(s):  
Power Systems ◽  
Power System ◽  
Power Plants ◽  
Optimization Technique ◽  
System Stability ◽  
Power System Stabilizer ◽  
Power System Stabilizers ◽  
Particle Swarm Optimization Technique ◽  
Matlab Package ◽  
System Stabilizer

The use of power system stabilizers (PSSs) to damp power system swing mode of oscillations is of practical important. The authors purpose is to retune the power system stabilizer (PSS1A) parameters in Unitrol D produced by ABB– was installed in 1995 in Benghazi North Power Plants (BNPPs) at General Electricity Company of Libya (GECOL). Power systems are steadily growing with larger capacity, so the optimal values of the power system stabilizer (PSS1A) parameters should be retuned. A particle swarm optimization technique (PSO) is used to determine the parameters of the PSS off-line. The objective is to damp the local and inter-area modes of oscillations that occur following power system disturbances. The retuned power system stabilizer (PSS1A) can cope with large disturbance at different operating points and has an enhanced power system stability, The MATLAB package with SIMULINK is used for the design and simulations.

A Simple Design Approach for Excitation Controller and Power System Stabilizer

2010 ◽  
Author(s):  
G. Fusco ◽  
M. Russo
Keyword(s):  
Power System ◽  
Transient Stability ◽  
Short Circuit ◽  
Design Procedure ◽  
Voltage Regulation ◽  
Operating Conditions ◽  
Power System Stabilizer ◽  
Simple Design ◽  
Wide Range ◽  
System Stabilizer

This paper proposes a simple design procedure to solve the problem of controlling generator transient stability following large disturbances in power systems. A state-feedback excitation controller and power system stabilizer are designed to guarantee robustness against uncertainty in the system parameters. These controllers ensure satisfactory swing damping and quick decay of the voltage regulation error over a wide range of operating conditions. The controller performance is evaluated in a case study in which a three-phase short-circuit fault near the generator terminals in a four-bus power system is simulated.

Robust adaptive fuzzy logic power system stabilizer

2009 ◽  
Vol 36 (10) ◽  
pp. 12104-12112 ◽  
Author(s):  
T. Hussein ◽  
M.S. Saad ◽  
A.L. Elshafei ◽  
A. Bahgat
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Power System Stabilizer ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Logic ◽  
Robust Adaptive ◽  
System Stabilizer

scholarly journals Dynamic Stability and Analysis of SMIB system with FLC Based PSS including Load Damping Parameter Sensitivity

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Jagadeesh Pothula ◽  
Ch. Durga Prasad ◽  
M. Sai Veerraju
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Dynamic Analysis ◽  
Single Machine ◽  
Fuzzy Logic Controller ◽  
Parameter Sensitivity ◽  
Power System Stabilizer ◽  
Pid Controllers ◽  
Damping Parameter ◽  
System Stabilizer

This paper studies Dynamic Analysis and Stability of Single machine connected to infinite bus (SMIB) with power system stabilizer (PSS) in presence of Fuzzy logic controller (FLC) including load damping parameter sensitivity. Here PSS is modeled using fuzzy logic controller and the response is compared with the responses of the system in presence of conventional PI, PID controllers including load damping parameters sensitivity. In case of FLC based PSS the responses are compared different load damping parameters. Matlab-Simulink is used to test the results.

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