Optimal location and size determination of FACTS devices by using multiobjective optimal power flow

Malakar, Tanmoy; Sinha, Nilotpal; Goswami, S. K.; Saikia, Lalit Chandra

doi:10.1109/tencon.2010.5686706

Cited by 13 publications

(4 citation statements)

References 16 publications

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“…In the present work, the multi-objective function is formulated to find optimal location and size of SVC device by minimizing certain objective functions subject to satisfying some network constraints. The multi-objective functions can be written as in [18]:…”

Section: Problem Formulationmentioning

confidence: 99%

Application of Hybrid Psoga for Optimal Location of SVC to Improve Voltage Stability of Power System

Kalaivani¹,

Kamaraj²

2013

IJEEE

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Due to huge increase in power demand, modern power system networks are being operated under highly stressed conditions. This has resulted into the difficulty in meeting reactive power requirement and maintaining the bus voltage within acceptable limits. Voltage instability in the system occurs in the form of a progressive decay in voltage magnitude at some of the buses. The problems of voltage instability and voltage collapse are the major concerns in the operation of power system. It is very important to do the power system analysis with respect to voltage stability. Flexible AC Transmission System (FACTS) device in a power system improves the stability, enhances the voltage stability margin and reduces the power losses. Identification of location of FACTS device in the power system is very important task. Research is carried out to investigate application of Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and hybrid PSOGA to find optimal location and rated value of SVC device to minimize the voltage stability index, total power loss, load voltage deviation, cost of generation and cost of FACTS device to improve voltage stability in the power system. Optimal location and rated value of SVC device have been found for different loading scenario using PSO, GA and PSOGA. It is observed from the results that the voltages stability margin is improved, voltage profile of the power system is increased, load voltage deviation is reduced and real power losses also reduced by optimally locating SVC device in the power system. The proposed algorithm is verified with IEEE 14 bus and 30 bus power systems.

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Section: Problem Formulationmentioning

confidence: 99%

Application of Hybrid Psoga for Optimal Location of SVC to Improve Voltage Stability of Power System

Kalaivani¹,

Kamaraj²

2013

IJEEE

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“…1) whose output is adjusted to exchange capacitive or inductive current so as to maintain or control specific parameters of the electrical power system (typically bus voltage). It is modeled as an ideal reactive power injection at the load ends as in (Malakar et al, 2010).…”

Section: Mathematical Model Of Svcmentioning

confidence: 99%

Enhancement of Voltage Stability by Optimal Location of Static Var Compensator Using Genetic Algorithm and Particle Swarm Optimization

Nooritawat¹

2012

American Journal of Engineering and Applied Sciences

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Problem statement:Voltage instability and voltage collapse have been considered as a major threat to present power system networks due to their stressed operation. It is very important to do the power system analysis with respect to voltage stability. Approach: Flexible AC Transmission System (FACTS) is an alternating current transmission system incorporating power electronic-based and other static controllers to enhance controllability and increase power transfer capability. A FACTS device in a power system improves the voltage stability, reduces the power loss and also improves the load ability of the system. Results: This study investigates the application of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to find optimal location and rated value of Static Var Compensator (SVC) device to minimize the voltage stability index, total power loss, load voltage deviation, cost of generation and cost of FACTS devices to improve voltage stability in the power system. Optimal location and rated value of SVC device have been found in different loading scenario (115%, 125% and 150% of normal loading) using PSO and GA. Conclusion/Recommendations: It is observed from the results that the voltage stability margin is improved, the voltage profile of the power system is increased, load voltage deviation is reduced and real power losses also reduced by optimally locating SVC device in the power system. The proposed algorithm is verified with the IEEE 14 bus, IEEE 30 bus and IEEE 57 bus.

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“…The technique is applied to determine the optimal location and capacity of FACTS devices in power system. Two types of FACTS devices (TCSC and SVC) were modeled and analyzed to enhance the steady state performance of power system [31]. The residue factor is implemented for determining the optimal location of FACTs devices to damp power systems oscillations [32].…”

Section: Introductionmentioning

confidence: 99%

Optimal Number, Location And Sizing Of FACTS Devices For Optimal Power Flow Using Genetic Algorithm

2021

Aswan University Journal of Sciences and Technology

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This work applies genetic Algorithm to determine the optimal location, number, and sizing of Flexible AC Transmission Systems (FACTS) devices in power system to improve power system performance quality. The challenge in this study is considering a mixture of various objective functions, which are economic considerations as minimizing total generation cost and FACTS devices investment cost in addition to minimizing the system losses, holding voltage profile within acceptable limits, and considering minimization of reactive power flow on power system lines.The optimization process is developed without missing MVA line flow limits cost and insuring that iteration counter increases towards its final value at convergence. A good simulation results can be obtained by minimizing all the objective functions and satisfying all the constraints. Shunt and series types of FACTS devices (SVC and TCSC) had been introduced. All objective functions have been solved and simulated by controlling the active power of the generators and reactive power of shunt and series compensator with respect to GA parameters. An IEEE30 bus system is used to demonstrate the effectiveness of the proposed fitness function based on (BGA) as an optimization tool and yields efficiency in improvement of power system performances. The results indicate that the proposed optimization using several methods like Weighted Sum method and Penalty Function method are available for finding the best solution. That approach with careful adjustment of the weight and penalty coefficients is a powerful optimization, may yield better solutions to a set of engineering problems than those obtained using a single objective function.

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Optimal location and size determination of FACTS devices by using multiobjective optimal power flow

Cited by 13 publications

References 16 publications

Application of Hybrid Psoga for Optimal Location of SVC to Improve Voltage Stability of Power System

Application of Hybrid Psoga for Optimal Location of SVC to Improve Voltage Stability of Power System

Enhancement of Voltage Stability by Optimal Location of Static Var Compensator Using Genetic Algorithm and Particle Swarm Optimization

Optimal Number, Location And Sizing Of FACTS Devices For Optimal Power Flow Using Genetic Algorithm

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