.png){kind=icon}
Return
Optimal power flow using Teaching-Learning-Based Optimization technique
.png){kind=icon}
PRE
AI
DOI：10.1016/j.epsr.2014.03.032.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Teaching-Learning-Based Optimization is a rising star among metaheuristic techniques with highly competitive performances. This technique is based on the influence of a teacher on learners. In this paper, the Teaching-Learning-Based Optimization technique is used to solve the optimal power flow problem. In order to show the effectiveness of the proposed method, it has been applied to the standard IEEE 30-bus and IEEE 118-bus test systems for different objectives that reflect the performances of the power system. Furthermore, the obtained results using the proposed technique have been compared to those obtained using other techniques reported in the literature. The obtained results and the comparison with other techniques indicate that the Teaching-Learning-Based Optimization technique provides effective and robust high-quality solution when solving the optimal power flow problem with different complexities. (C) 2014 Elsevier B.V. All rights reserved.
Keywords:
Teaching-Learning-Based Optimization
Metaheuristic
Optimal power flow
Power system optimization
Voltage profile
Voltage stability
Journal
IF:
4.2
Papers:
1.1W
Citations:
2.2W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveModified differential evolution algorithm for optimal power flow with non-smooth cost functions
PREAI
ShareSaveShareSave
ShareSaveShareSave
View more