TY - GEN
T1 - Binary Bat Search Algorithm for Unit Commitment Problem in Power system
AU - Nidhi,
AU - Reddy, Srikanth
AU - Kumar, Rajesh
AU - Panigrahi, B. K.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - The unit commitment operation in power systems is a complex, non-linear, constrained optimization problem. The commitment and de-commitment decision presents a binary problem which needs discrete/binary optimization approaches. This paper presents a binary bat search algorithm (BBSA) to solve unit commitment (UC) problem. The bat search algorithm belongs to a meta heuristic class of optimization approaches inspired by natural echolocation behavior of bats. In order to solve binary UC problem, the real valued bat search process is mapped to binary search space using sigmoidal transformation function. The BBSA is then applied to test system with 10 thermal units. The effectiveness of the BBSA is verified against system dimension using test systems upto 100 units. Extensive numerical experiments are performed to test the effectiveness of BBSA and statistical analysis of simulation results are presented. The simulation results are presented, discussed and compared to various existing classical and heuristic approaches. The same demonstrate the superior performance of BBSA approach in solving UC problem.
AB - The unit commitment operation in power systems is a complex, non-linear, constrained optimization problem. The commitment and de-commitment decision presents a binary problem which needs discrete/binary optimization approaches. This paper presents a binary bat search algorithm (BBSA) to solve unit commitment (UC) problem. The bat search algorithm belongs to a meta heuristic class of optimization approaches inspired by natural echolocation behavior of bats. In order to solve binary UC problem, the real valued bat search process is mapped to binary search space using sigmoidal transformation function. The BBSA is then applied to test system with 10 thermal units. The effectiveness of the BBSA is verified against system dimension using test systems upto 100 units. Extensive numerical experiments are performed to test the effectiveness of BBSA and statistical analysis of simulation results are presented. The simulation results are presented, discussed and compared to various existing classical and heuristic approaches. The same demonstrate the superior performance of BBSA approach in solving UC problem.
KW - bat algorithm (BA)
KW - Binary Bat Search Algorithm (BBSA)
KW - heuristic optimization
KW - power system optimization
KW - unit commitment (UC)
UR - http://www.scopus.com/inward/record.url?scp=85055519468&partnerID=8YFLogxK
U2 - 10.1109/WIECON-ECE.2017.8468909
DO - 10.1109/WIECON-ECE.2017.8468909
M3 - Conference contribution
AN - SCOPUS:85055519468
T3 - WIECON-ECE 2017 - IEEE International WIE Conference on Electrical and Computer Engineering 2017
SP - 121
EP - 124
BT - WIECON-ECE 2017 - IEEE International WIE Conference on Electrical and Computer Engineering 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International WIE Conference on Electrical and Computer Engineering, WIECON-ECE 2017
Y2 - 18 December 2017 through 19 December 2017
ER -