Open AccessApplication of chaotic whale optimisation algorithm for transient stability constrained optimal power flow
Author(s) -
Prasad Dharmbir,
Mukherjee Aparajita,
Shankar Gauri,
Mukherjee Vivekananda
Publication year - 2017
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2017.0015
Subject(s) - electric power system , power flow , transient (computer programming) , chaotic , mathematical optimization , computer science , stability (learning theory) , control theory (sociology) , algorithm , power (physics) , mathematics , physics , control (management) , quantum mechanics , artificial intelligence , machine learning , operating system
Chaotic whale optimisation algorithm (CWOA) is a metaheuristic real‐parameter optimisation algorithm. This study appears to be well capable of providing solution to the transient stability constrained optimal power flow (OPF) problem of power system. Basically, transient stability constrained OPF (TSCOPF) problem is the extended study of conventional OPF problem while additionally, considering transient stability constraints along with other previously considered equality and inequality constraints of the conventional OPF problem. Here, CWOA algorithm is validated by choosing two test power systems viz . (a) New England 10‐generator, 39‐bus and (b) 17‐generator, 162‐bus test systems. Considering multiple contingency cases, the main objective of the proposed algorithm is minimisation of the total fuel cost of these two test systems. Simulation test results, as obtained from the proposed CWOA, are compared to the results offered by some other evolutionary optimisation techniques surfaced in the recent state‐of‐the‐art literature. The results presented in this study indicate that the proposed algorithm shows its efficacy over other recently originated popular optimisation techniques (including basic WOA) in terms of extending potential of offering higher quality solutions, effectiveness and faster convergence speed.