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FACTS Devices to Enhance Total Transfer Capability Using Evolutionary Programming

version 1.0.0.0 (205 KB) by INDRA(INDRANIL SAAKI)
indranil saaki

35 Downloads

Updated 01 May 2018

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Improving of ATC is an important issue in the current de-regulated environment of power systems. The Available Transfer Capability (ATC) of a transmission network is the unutilized transfer capabilities of a transmission network for the transfer of power for further commercial activity, over and above already committed usage. Power transactions between a specific seller bus/area and a buyer bus/area can be committed only when sufficient ATC is available. Transmission system operators (TSOs) are encouraged to use the existing facilities more effectively to enhance the ATC margin. ATC can be limited usually by heavily loaded circuits and buses with relatively low voltages. It is well known that FACTS technology can control voltage magnitude, phase angle and circuit reactance. Using these devices may redistribute the load flow, regulating bus voltages. Therefore, it is worthwhile to investigate the impact of FACTS controllers on the ATC. In this thesis focuses on the evaluation of the impact of TCSC and SVC as FACTS devices on ATC and its enhancement during with and without line outage cases. In a competitive (deregulated) power market, optimal the location of these devices and their control can significantly affect the operation of the system and will be very important for ISO.
In this project, the use of TCSC and SVC to maximize Available Transfer Capability (ATC) generally defined as the maximum power transfer transaction between a specific power-seller and a power-buyer in a network during normal and contingency cases. In this project, ATC is computed using Continuous Power Flow (CPF) method considering both line thermal limit as well as bus voltage limits. Real-code Genetic Algorithm is used as the optimization tool to determine the location as well as the controlling parameter of TCSC or SVC simultaneously. The performance of the Real-code Genetic Algorithm has been tested on IEEE 14-Bus System and IEEE 30-Bus Reliability Test System.

Comments and Ratings (6)

ASHOK KUMAR

For Latest Simulation Projects,Please Contact http://asokatechnologies.in/

Riski Yan

Jigar Sarda

Sir where is the code of ATC enhancement using GA and PSO is available?

pradeep

Thank you sir provide open plateform Dear sir if possible please send Harmonic load flow upload on mathworks else send me pkjmtech@gmail.com

Updates

1.0.0.0

.

1.0.0.0

updated with Genetic Algorithm and particle swarm optimization techniques

1.0.0.0

updated with Genetic Algorithm and particle swarm optimization techniques

MATLAB Release Compatibility
Created with R2009b
Compatible with any release
Platform Compatibility
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