caa a22 4500 60616023X CHVBK 20210128100628.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00521-014-1791-x doi (NATIONALLICENCE)springer-10.1007/s00521-014-1791-x Rezaee Jordehi A. Department of Electrical Engineering, University Putra Malaysia (UPM), 43400, Serdang, Selangor, Malaysia aut Optimal setting of TCSCs in power systems using teaching-learning-based optimisation algorithm [Elektronische Daten] [A. Rezaee Jordehi] Teaching-learning-based optimisation (TLBO) is an emerging gradient-free optimisation algorithm inspired by interactions between students and teacher in classrooms. TLBO has no control parameter to be tuned by user. This property makes it popular in research community. It has been successfully applied to challenging optimisation problems in different areas. In this study, TLBO is assisted to find optimal setting of thyristor-controlled series compensators in electric power systems. The experiments have been done for both N-1 and N-2 line outage contingencies. The results show that TLBO performs well in solving this problem. The Natural Computing Applications Forum, 2014 Teaching-learning-based optimisation nationallicence FACTS allocation problem nationallicence Contingency nationallicence Neural Computing and Applications Springer London 26/5(2015-07-01), 1249-1256 0941-0643 26:5<1249 2015 26 521 https://doi.org/10.1007/s00521-014-1791-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1791-x text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Rezaee Jordehi A. Department of Electrical Engineering, University Putra Malaysia (UPM), 43400, Serdang, Selangor, Malaysia aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/5(2015-07-01), 1249-1256 0941-0643 26:5<1249 2015 26 521