DESIGN OF OPTIMAL LOCATION OF TCSC COMBINED SATCOM USING GRAVITATIONAL SEARCH, GREY WOLF AND FIREFLY OPTIMIZATION ALGORITHM
STATCOM(Static Synchronous Series Compensator) is a shunt connected reactive power compensation FACTS device. It can also be used to regulate active power if batteries are provided. It has faster rate of generation/ absorption of reactive power so as to maintain bus voltage. Generally, it consists of a coupling transformer, a voltage source inverter and a dc side capacitor. The optimal location of STATCOM is based on location of minimum power loss in the line and installation cost of STATCOM. The methodology is mathematically formulated based on installation cost of STATCOM and power loss in the line. The ability of STATCOM to provide shunt compensation in order to maintain bus voltage is exploited here.The criteria for optimal placement are following,
1.Installation cost of STATCOM &
2.Power losses in lines.
Thyristor-Controlled Series Compensation (TCSC) is used in power systems to dynamically control the reactance of a transmission line in order to provide sufficient load compensation. The benefits of TCSC are seen in its ability to control the amount of compensation of a transmission line, and in its ability to operate in different modes. These traits are very desirable since loads are constantly changing and cannot always be predicted. TCSC designs operate in the same way as Fixed Series Compensation, but provide variable control of the reactance absorbed by the capacitor device.
The main objective of this work is to determine the optimal location and the optimal parameter setting of the TCSC combined with SATCOM in the power network to minimize the loss of the power system and compare their performances. The design uses three optimization algorithm i.e. Gravitational Search Algorithm (GSA),Grey Wolf Algorithm(GWA) and Firefly Algorithm(FA). To show the validity of the proposed techniques and for comparison purposes, simulations are carried out on IEEE-57 bus power system. The results are presented in the simulation video demo as given below.
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Source: IEEE
Year:2015
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Author’s Name: Jie-Sheng Wang and Shu-Xia Li
Source: Scientific Reports
Year:2019
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Author’s Name: Sureshkumar Sudabattula and Kowsalya M
Source: Journal of Electrical Engineering
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SIMULATION VIDEO DEMO-FIREFLY ALGORITHM
SIMULATION VIDEO DEMO-GRAVITATIONAL SEARCH OPTIMIZATION ALGORITHM
SIMULATION VIDEO DEMO-GREY WOLF OPTIMIZATION ALGORITHM
SIMULATION VIDEO DEMO-3 OPTIMIZATION ALGORITHM
