Investigation of the impact of PSO, ABC, BFO and Cuckoo search optimization techniques on UPFC device for sustainable voltage stability margin improvement

被引:1
作者
Ndubuisi Hyginus Ikeli
Chinemezu Evans Ashigwuike
Ibitayo Isaac Alabi
机构
[1] University of Abuja,Department of Electrical and Electronics Engineering, Faculty of Engineering
[2] Transmission Company of Nigeria,Department of Electrical/Electronic Engineering, Faculty of Engineering
[3] Corporate Headquarters,undefined
[4] Nigerian Defence Academy,undefined
关键词
Artificial Bee Colony; Bacterial foraging optimization; Cuckoo search algorithm; Particle Swarm optimization; Voltage stability margin; UPFC;
D O I
10.1186/s43067-023-00095-0
中图分类号
学科分类号
摘要
This paper investigates the enhancement of voltage stability margin using Unified Power Flow Control (UPFC) device tuned with Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Bacterial Foraging Optimization (BFO) and Cuckoo Search techniques (CS) on Nigerian 330 kV 56-bus practical network. In order to have a voltage stable power system, it is good to keep voltages within the acceptable limits. This is achieved using continuation power flow embedded in Power System Analysis Toolbox (PSAT). The optimal location and tuning of the UPFC device is determined using line stability index and the met-heuristics techniques. The effects of UPFC and the proposed optimizing techniques on voltage stability margin are examined. The results so obtained for tuning PSO, ABC, BFO and Cuckoo Search with UPFC device are compared to know the technique that yields the best loading parameter for Nigerian 56- bus power system for voltage stability margin enhancement. It is found that UPFC tuned with Cuckoo Search outperforms the other techniques in terms of the increased loading parameter of the Nigerian power system with margin improvement of 86.6%, 90% and 88.6% for Adiabor (Bus 45), Jalingo (Bus 34) and Jos (Bus 13). The tuned UPFC device has proved beyond reasonable doubt that it can improve voltage stability margin of the entire Nigerian 330 kV Network as envisaged from results before and after optimization.
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