Transmission congestion management with integration of wind farm: a possible solution methodology for deregulated power market

Sadhan Gope (), A. K. Goswami () and P. K. Tiwari ()
Additional contact information
Sadhan Gope: Mizoram University
A. K. Goswami: National Institute of Technology Silchar
P. K. Tiwari: National Institute of Technology Silchar

International Journal of System Assurance Engineering and Management, 2020, vol. 11, issue 2, No 4, 287-296

Abstract: Abstract Congestion management (CM) work is a challenging task for researchers working in the field of power transmission sector. In this paper, an appreciable effort has been made to eliminate the line congestion by integrating wind farm in the system. To reschedule the conventional generators for achieving best optimal solution, moth flame optimization (MFO) algorithm is implemented here. Generator sensitivity factors and bus sensitivity factors are respectively used to reschedule the generators and to optimally locate the wind farm in deregulated power system. To test the performance and check the effectiveness of the proposed CM approach, modified IEEE 30 bus test system and modified 39 bus New England test system are used here. Further after obtained details results, the competitive performance of MFO algorithm is compared and verified with others optimization algorithms like artificial bee colony, firefly algorithm and ant lion optimizer algorithms in terms of rescheduling amount, rescheduling cost and active power losses.

Keywords: Wind farm; Moth flame optimization algorithm; Generator sensitivity factor; Bus sensitivity factor (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13198-019-00856-z 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:11:y:2020:i:2:d:10.1007_s13198-019-00856-z

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

DOI: 10.1007/s13198-019-00856-z

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 ().