TY - JOUR
T1 - Improved tunicate swarm algorithm: solving the dynamic economic emission dispatch problems
AU - Li, Ling-Ling
AU - Liu, Zhi-Feng
AU - Tseng, Ming-Lang
AU - Zheng, Sheng-Jie
AU - Lim, Ming
PY - 2021/9
Y1 - 2021/9
N2 - This study proposes improved tunicate swarm algorithm (ITSA) for solving and optimizing the dynamic economic emission dispatch (DEED) problem. The DEED optimization target is to reduce the fuel cost and pollutant emission of the power system. In addition, DEED is a complex optimization problem and contains multiple optimization goals. To strengthen the ability of the ITSA algorithm for solving DEED, the tent mapping is employed to generate initial population for improving the directionality in the optimization process. Meanwhile, the gray wolf optimizer is used to generate the global search vector for improving global exploration ability, and the Levy flight is introduced to expand the search range. Three test systems containing 5, 10 and 15 generator units are employed to verify the solving performance of ITSA. The test results show that the ITSA algorithm can provide a competitive scheduling plan for test systems containing different units. ITSA proposed algorithm gives the optimal economic and environmental dynamic dispatch scheme for achieving more precise dispatch strategy.
AB - This study proposes improved tunicate swarm algorithm (ITSA) for solving and optimizing the dynamic economic emission dispatch (DEED) problem. The DEED optimization target is to reduce the fuel cost and pollutant emission of the power system. In addition, DEED is a complex optimization problem and contains multiple optimization goals. To strengthen the ability of the ITSA algorithm for solving DEED, the tent mapping is employed to generate initial population for improving the directionality in the optimization process. Meanwhile, the gray wolf optimizer is used to generate the global search vector for improving global exploration ability, and the Levy flight is introduced to expand the search range. Three test systems containing 5, 10 and 15 generator units are employed to verify the solving performance of ITSA. The test results show that the ITSA algorithm can provide a competitive scheduling plan for test systems containing different units. ITSA proposed algorithm gives the optimal economic and environmental dynamic dispatch scheme for achieving more precise dispatch strategy.
KW - Dynamic economic emission dispatch
KW - Fuel cost
KW - Improved tunicate swarm algorithm
KW - Power system
KW - Soft-computing
UR - http://www.scopus.com/inward/record.url?scp=85106913051&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2021.107504
DO - 10.1016/j.asoc.2021.107504
M3 - Article
SN - 1568-4946
VL - 108
JO - Applied Soft Computing
JF - Applied Soft Computing
M1 - 107504
ER -