A novel approach of PSS optimal parameter tuning in a multi-area power system using hybrid butterfly optimization algorithm- particle swarm optimization

Murali Krishna Gude () and Umme Salma ()
Additional contact information
Murali Krishna Gude: GIT, GITAM (Deemed to be University)
Umme Salma: GIT, GITAM (Deemed to be University)

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 5, No 38, 2619-2628

Abstract: Abstract The small-signal stability is the cause of concern for modern-day power engineers. These mostly go undetected at the sender end but causes voltage fluctuations at the receiver end/ distributor end. The main reason behind this instability is the continuously varying operating point of the power system. Due to this, many types of controllers are being used whose nature are non-linear in nature. Thus, their effectiveness and swiftness to tackle such small-signal instability depend merely on their parameters. To fulfil this demand, various hybrid methods are being utilized. In this article, a novel optimization algorithm, Hybrid Butterfly Optimization Algorithm—Particle Swarm Optimization (HBOAPSO), has been used to tune the parameters of the Power System Stabilizer (PSS) employed in the Two Area Four Machines system. The obtained performance of HBOAPSO-PSS is then compared to other metaheuristic methods. The HBOAPSO-PSS has shown promising results. This can also be observed by the convergence graph of the HBOAPSO with respect to iteration. The inability of BOA to maintain a balance between local and global optima is removed by hybridizing it with PSO.

Keywords: Power system stability; Butterfly optimization algorithm; Multi area power system (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s13198-022-01678-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:13:y:2022:i:5:d:10.1007_s13198-022-01678-2

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-022-01678-2

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().