An Adaptive Stabilizer for Thyristor Controlled Static Var Compensators for Power Systems

Sharaf,; Hill,

doi:10.1109/mper.1989.4310676

Cited by 3 publications

(2 citation statements)

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“…A hybrid Genetic Algorithmic approach with FACTS devices for optimal power flow is dealt in [13]. In [14] an adaptive stabilizer design for SVC control in power systems for either voltage regulation or controlling dynamic and transient performance under abnormal condition is discussed. Steady state firing angle model of SVC and TCSC for power flow solution were developed and discussed in [15].…”

Section: Introductionmentioning

confidence: 99%

Comparative study of GA & DE algorithm for the economic operation of a power system using FACTS devices

Bhattacharyya¹,

Gupta²,

Kumar³

2013

Archives of Electrical Engineering

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The problem of improving the voltage profile and reducing power loss in electrical networks must be solved in an optimal manner. This paper deals with comparative study of Genetic Algorithm (GA) and Differential Evolution (DE) based algorithm for the optimal allocation of multiple FACTS (Flexible AC Transmission System) devices in an interconnected power system for the economic operation as well as to enhance loadability of lines. Proper placement of FACTS devices like Static VAr Compensator (SVC), Thyristor Controlled Switched Capacitor (TCSC) and controlling reactive generations of the generators and transformer tap settings simultaneously improves the system performance greatly using the proposed approach. These GA & DE based methods are applied on standard IEEE 30 bus system. The system is reactively loaded starting from base to 200% of base load. FACTS devices are installed in the different locations of the power system and system performance is observed with and without FACTS devices. First, the locations, where the FACTS devices to be placed is determined by calculating active and reactive power flows in the lines. GA and DE based algorithm is then applied to find the amount of magnitudes of the FACTS devices. Finally the comparison between these two techniques for the placement of FACTS devices are presented. NomenclatureR Line -Resistance of line; X Line -Reactance of line; Z Line -Line Impedance; X ij -Reactance between i th & j th node; X TCSC -Reactance of TCSC; G TCSC -Real part of Admittance of TCSC; B TCSC -Imaginary part of Admittance of TCSC; r TCSC -Coefficient which represents the compensation degree of TCSC; X C -Capacitive reactance of SVC reactor bank; X L -Inductive reactance of SVC reactor bank; á -Firing angle of SVC; X SVC -Reactance of SVC; S -Operating range of FACTS devices; C TOTAL -Total cost of system operation; C 1 (E) -Cost due to energy loss; C 2 (F) -Total investment cost of the FACTS Devices; min ni p , max ni pLower and Upper limit of nodal active power in the i th bus respectively; P ni , Q niNodal active and reactive power output of the i th bus respectively; min ni Q , max ni Q -Lower and Upper limit of nodal reactive power in the i th bus respectively; min gi Q max gi Q -Lower and Upper limit of existing nodal reactive capacity in the i th bus respectively; Q gi -Output of existing nodal reactive capacity in the i th bus; P Gi , Q Gi -Active and Reactive power generation in the i th bus respectively; P Di , Q Di -Active and Reactive power consumed by load in the i th bus respectively; P i , Q i(inj) -Real and Unauthenticated Download Date | 8/24/15 11:50 AM

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Section: Introductionmentioning

confidence: 99%

Comparative study of GA & DE algorithm for the economic operation of a power system using FACTS devices

Bhattacharyya¹,

Gupta²,

Kumar³

2013

Archives of Electrical Engineering

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“…its variable degree of compensation that can be used in damping out low-frequency oscillations, controlling the power flow, etc. In [13] an adaptive stabilizer design for SVC control in power systems for either voltage regulation or controlling dynamic and transient performance under abnormal condition is discussed. Steady state firing angle model of SVC and TCSC for power flow solution were developed and discussed in [14].…”

Section: Introductionmentioning

confidence: 99%

Particle Swarm Intelligence based allocation of FACTS controller for the increased load ability of Power system

Bhattacharyya¹,

Goswami²,

Gupta³

2012

ijeei

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This paper presents Particle Swarm Optimization (PSO) based approach for the allocation & coordinated operation of multiple FACTS (Flexible AC Transmission System) devices for the economic operation as well as to increase power transfer capacity of an interconnected power system under different loading condition. The PSO based approach is applied on IEEE 30-bus system. The system is reactively loaded starting from base to 200 % of base load. FACTS devices are installed in the different locations of the power system and system performance is noticed with and without FACTS devices. First, the locations, where the FACTS devices to be placed is determined by calculating active and reactive power flows in the lines. A Particle Swarm Optimization based algorithm is then applied to find the amount of magnitudes of the FACTS devices. This Particle Swarm Optimization based approach for the placement of FACTS devices Yields promising result both in terms of performance and economy which is clearly observed from the result obtained.

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A variable structure VAR stabilizer for power system control

Dash

Sahoo

Doraiswami

1993

Electric Power Systems Research

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An Adaptive Stabilizer for Thyristor Controlled Static Var Compensators for Power Systems

Cited by 3 publications

References 0 publications

Comparative study of GA & DE algorithm for the economic operation of a power system using FACTS devices

Comparative study of GA & DE algorithm for the economic operation of a power system using FACTS devices

Particle Swarm Intelligence based allocation of FACTS controller for the increased load ability of Power system

A variable structure VAR stabilizer for power system control

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