TY - GEN
T1 - FACTS devices allocation for preventive/corrective control against voltage collapse under deregulated power system
AU - Wibowo, Rony Seto
AU - Priyadi, Ardyono
AU - Soeprijanto, Adi
AU - Yorino, Naoto
PY - 2011
Y1 - 2011
N2 - In this paper, an approach for optimal allocation of flexible AC transmission system (FACTS) devices under deregulated power systems is presented. The approach considers system operation under normal and contingency states along with their related probabilities to occur. For each state, FACTS devices are optimally utilized to minimize operating cost. If a contingency occurs, preventive/corrective control strategy is applied to prevent voltage collapse as well as to relieve transmission congestion. During corrective control, fast control action is utilized while during preventive control, both fast and slow control actions are employed. The objective of normal state is to maximize social welfare while the objectives of contingency states are to maximize social welfare and to minimize compensations paid for generations re-scheduling and load shedding. The overall problem is formulated as a mixed integer nonlinear programming problem and is solved using hybrid Particle Swarm Optimization. The effectiveness of the proposed approach is demonstrated on modified IEEE 14 bus test system.
AB - In this paper, an approach for optimal allocation of flexible AC transmission system (FACTS) devices under deregulated power systems is presented. The approach considers system operation under normal and contingency states along with their related probabilities to occur. For each state, FACTS devices are optimally utilized to minimize operating cost. If a contingency occurs, preventive/corrective control strategy is applied to prevent voltage collapse as well as to relieve transmission congestion. During corrective control, fast control action is utilized while during preventive control, both fast and slow control actions are employed. The objective of normal state is to maximize social welfare while the objectives of contingency states are to maximize social welfare and to minimize compensations paid for generations re-scheduling and load shedding. The overall problem is formulated as a mixed integer nonlinear programming problem and is solved using hybrid Particle Swarm Optimization. The effectiveness of the proposed approach is demonstrated on modified IEEE 14 bus test system.
KW - FACTS devices allocation
KW - congestion relief
KW - control coordination
KW - expected security cost
KW - preventive/corrective control
KW - voltage stability
UR - http://www.scopus.com/inward/record.url?scp=84856888328&partnerID=8YFLogxK
U2 - 10.1109/TENCON.2011.6129244
DO - 10.1109/TENCON.2011.6129244
M3 - Conference contribution
AN - SCOPUS:84856888328
SN - 9781457702556
T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON
SP - 918
EP - 922
BT - TENCON 2011 - 2011 IEEE Region 10 Conference
T2 - 2011 IEEE Region 10 Conference: Trends and Development in Converging Technology Towards 2020, TENCON 2011
Y2 - 21 November 2011 through 24 November 2011
ER -