Optimum tuning of Unified Power Flow Controller via Ant Colony Optimization technique

Hamid, Zulkiffli Abdul; Musirin, Ismail; Othman, Mahmoud M.; Khalil, Munirah

doi:10.1109/peoco.2010.5559166

Cited by 5 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the recent past, a enormous count of academics have put a variety of different optimization algorithms through their paces in an effort to reduce power system issues utilizing FACTS. Utilizing metaheuristic optimization algorithms such as DE [15], [18], PSO [7], [11], GA [7], [19], Evolutionary programming [17], and ACO [20] is the strategy that is going to prove to be the most effective when dealing with issues of this kind. ACO has the benefit, in compared to the other meta-heuristic algorithms, that if the input varies rapidly, it can run constantly and familiarize to the variations in actual time.…”

Section: Introductionmentioning

confidence: 99%

Optimal Location Settings for UPFC Using Ant Colony Optimization for Improving Power System Security Under Single Contingencies

Raavi,

Medala

2023

International Transactions on Electrical Engineering and Comput

View full text Add to dashboard Cite

Devices referred to as FACTS are utilized extensively in the process of making power system more secure. The UPFC, which contains both shunt and series correction, is one of the FACTS devices that is considered to be among the most successful. The placement of the FACTS device and the values that are selected for its parameters both have a role in determining how successful the device is in reducing security risks. In this study, the ACO approach is presented as a means of optimally positioning UPFC in order to improve the consistency of the power system in the occurrence of single contingencies, also known as an N-1 contingency. In order to guarantee the integrity of the system, the simulation is run on test systems based on the IEEE 6 bus and the IEEE 14 bus, taking into account line overloads and voltage destructions on the bus. This strategy has a two-pronged approach. In the beginning, a N-1 contingency test is carried out based on the severity ranking, and after that, an ACO algorithm is used to install UPFC in the ideal location in order to reduce the severity. In order to further verify the suggested method, the results are matched with the traditional NLP-IP method. This comparison reveals that the new strategy is better in terms of assuring the safety of power systems.

show abstract