Optimal Number, Location And Sizing Of FACTS Devices For Optimal Power Flow Using Genetic Algorithm | ||||
| Aswan University Journal of Sciences and Technology | ||||
| Volume 1, Issue 1, June 2021, Page 55-73 PDF (1.67 MB) | ||||
| Document Type: Original papers | ||||
| DOI: 10.21608/aujst.2021.226478 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Al-Attar Mohamed  1; Ahmed Aljaafary2; Yahia Mohamed3
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| 1Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan, Egypt | ||||
| 2Electrical Engineering Department, Faculty of Engineering, Minia University, Minia, Egypt | ||||
| 3Electrical Engineering Department, Faculty of Engineering, Minia University, Minia, Egypt | ||||
| Abstract | ||||
| 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. | ||||
| Keywords | ||||
| Binary genetic Algorithm (BGA); optimal power flow (OPF); Flexible AC Transmission systems (FACTS) | ||||
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