Investigation to effects of TCSC and STATCOM on optimal power flow problem with CEPSO algorithm
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Abstract (EN)
In Today's modern power systems, providing reliable energy, improving operational efficiency and making correct investment plans have become almost impossible due to problems such as increasing population and energy demand, unbalanced and inefficient usage of transmission assets, economic bottlenecek, geopolitics of energy, integration of the intermittent renewable energy resources, complex communication and automation infrastructures required for smart grid concept, and increasing environmental concern. Using optimal power flow solutions and power electronic based Flexible Alternating Current Systems (FACTS) in power system studies make it available to get a highly reliable and predicatble system operated almost at it's maximum capacity and to make correct and efficient investment preferences. In this study, chaos embdedded particle swarm optimization algorithm was used for the minimization of active power losses and voltage profile improvement problems. The developed algorithm was tested first in standart IEEE 5 bus test system and then in IEEE 30 bus test systems, respectively. Some other objection functions of optimal power flow problem such as fuel cost minimization, volatge stability enhancement and reactive power losses minimization were carried out through the developed optimization algorithm. To achieve better results for the selected objection function in the optimization studies, for reducing active power losses in both IEEE 5 and IEEE 30 bus systems ,a series FACTS device, thyristor controlled series capacitor (TCSC) and for improving voltage profilein the system, a shunt FACTS device, static synchronous compensator (STATCOM) were used The obtained results were presented comparatively.
Author
İsmail Hakan Dağhan
Institution
Fırat University
Elektrik Tesisleri Bilim Dalı
How to Cite
İsmail Hakan Dağhan (Doctorate thesis). Investigation to effects of TCSC and STATCOM on optimal power flow problem with CEPSO algorithm, 2023, Fırat University.
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