In this paper, an efficient and reliable evolutionary-based approach is employed to solve the optimal power flow (OPF) problem. This approach utilizes the global and local exploration capabilities of particle swarm optimization (PSO) to search for optimal setting of control variables for the OPF which is formulated as a nonlinear constrained objective optimization problem with both equality and inequality constraints. To illustrate how the proposed method has an efficient role, the standard IEEE 30-bus power system is studied and the PSO is used to minimize each of the total fuel cost, system power loss and voltage deviations. Two different types of FACTS devices are embedded with the test system, SVC and STATCOM, to achieve the objectives functions under certain constraints. The results show the effectiveness of STATCOM with optimal settings over the SVC with same conditions.
Saad, E., Amer, R. A., & Morsy, G. A. (2013). Optimal Power Flow Control Based Shunt FACTS Devices Using PSO Algorithm. ERJ. Engineering Research Journal, 36(4), 347-356. doi: 10.21608/erjm.2013.67072
MLA
Ekramy Saad; R. A. Amer; G. A. Morsy. "Optimal Power Flow Control Based Shunt FACTS Devices Using PSO Algorithm". ERJ. Engineering Research Journal, 36, 4, 2013, 347-356. doi: 10.21608/erjm.2013.67072
HARVARD
Saad, E., Amer, R. A., Morsy, G. A. (2013). 'Optimal Power Flow Control Based Shunt FACTS Devices Using PSO Algorithm', ERJ. Engineering Research Journal, 36(4), pp. 347-356. doi: 10.21608/erjm.2013.67072
VANCOUVER
Saad, E., Amer, R. A., Morsy, G. A. Optimal Power Flow Control Based Shunt FACTS Devices Using PSO Algorithm. ERJ. Engineering Research Journal, 2013; 36(4): 347-356. doi: 10.21608/erjm.2013.67072