Open AccessAn efficient transient stability‐constrained optimal power flow using biogeography‐based algorithm
Author(s) -
Bagde Bhushan Y.,
Umre Bhimrao S.,
Dhenuvakonda Koteswara Raju
Publication year - 2018
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2467
Subject(s) - transient (computer programming) , stability (learning theory) , electric power system , mathematical optimization , computer science , matlab , constraint (computer aided design) , power flow , optimization problem , power (physics) , algorithm , engineering , mathematics , physics , quantum mechanics , machine learning , operating system , mechanical engineering
Summary With deregulated regime for electricity market, utilities are being operated close to stability boundaries. Therefore, it has become necessary to secure power systems optimally when subjected to transient stability condition. Transient stability constrained optimal power flow (OPF) is a highly nonlinear, high‐dimension optimization problem and requires efficient methods to solve it. In this paper, transient stability constrained OPF problem is implemented by using biogeography‐based optimization algorithm, a recent evolutionary algorithm that searches for global optimum through migration and mutation of biological species distributed over geographical space and has shown promising results. The OPF model uses economic dispatch as objective function subjected to various constraints. Single machine equivalent, a hybrid method that combines time domain simulations and direct method, has been used to implement transient stability constraint. Tests on Western System Coordinating Council 3 machine, 9 bus system and New England 10 machine, 39 bus system demonstrate the effectiveness of the approach. The simulation results presented by using MATLAB are compared with recent findings that show that the proposed biogeography‐based optimization algorithm is capable of obtaining higher quality solutions.