TY - JOUR
T1 - Voltage stability index and APFC for performance improvement of modern power systems with intense renewables
AU - Singh, Pradeep
AU - Tiwari, Rajive
AU - Shah, Mukesh Kumar
AU - Niazi, Khaleequr Rahman
AU - Meena, Nand Kishor
AU - Ratra, Saurabh
N1 - This is an open access article published by the IET under the Creative Commons Attribution -NonCommercial License (http://creativecommons.org/licenses/by-nc/3.0/)
PY - 2019/7
Y1 - 2019/7
N2 - In this study, a newly developed amalgam power flow controller (APFC) is used for better controllability and voltage stability enhancement of modern power system with deep renewable penetration. A new voltage stability index is proposed to determine the potential site of APFC and then Grey Wolf optimisation based on fuzzy logic is adopted to determine the optimal parameter settings of the APFC. A quarter cosine and exponential fuzzy membership function have been used to find out membership value of diverse objectives. The multi-objective problem is formulated considering three different objectives of conflicting nature. The proposed optimisation framework is implemented on an IEEE benchmark system of 30 buses for different cases. The comparison of simulation results reveals the effectiveness of the proposed model.
AB - In this study, a newly developed amalgam power flow controller (APFC) is used for better controllability and voltage stability enhancement of modern power system with deep renewable penetration. A new voltage stability index is proposed to determine the potential site of APFC and then Grey Wolf optimisation based on fuzzy logic is adopted to determine the optimal parameter settings of the APFC. A quarter cosine and exponential fuzzy membership function have been used to find out membership value of diverse objectives. The multi-objective problem is formulated considering three different objectives of conflicting nature. The proposed optimisation framework is implemented on an IEEE benchmark system of 30 buses for different cases. The comparison of simulation results reveals the effectiveness of the proposed model.
UR - https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9375
U2 - 10.1049/joe.2018.9375
DO - 10.1049/joe.2018.9375
M3 - Conference article
SN - 2051-3305
VL - 2019
SP - 5187
EP - 5192
JO - The Journal of Engineering
JF - The Journal of Engineering
IS - 18
ER -