Title
Solving optimal reactive power dispatch problem using a novel teaching-learning-based optimization algorithm.
Abstract
The paper presents a novel teaching–learning-based optimization (TLBO) algorithm, the Gaussian bare-bones TLBO (GBTLBO) algorithm, with its modified version (MGBTLBO) for the optimal reactive power dispatch (ORPD) problem with discrete and continuous control variables in the standard IEEE power systems for reduction in power transmission loss. The feasibility and performance of the GBTLBO and MGBTLBO algorithms are demonstrated for standard IEEE 14-bus and standard IEEE 30-bus systems. A comparison of simulation results reveals optimization efficacy of the GBTLBO and MGBTLBO algorithms over other well established other algorithms like bare-bones differential evolution (BBDE) and bare-bones particle swarm optimization (BBPSO) algorithm. Results for ORPD problem demonstrate superiority in terms of solution quality of the GBTLBO and MGBTLBO algorithms over original TLBO algorithm and other algorithm.
Year
DOI
Venue
2015
10.1016/j.engappai.2014.12.001
Engineering Applications of Artificial Intelligence
Keywords
DocType
Volume
Gaussian bare-bones teaching–learning-based optimization,Power systems,ORPD problem,Control variables
Journal
39
ISSN
Citations 
PageRank 
0952-1976
8
0.48
References 
Authors
18
5
Name
Order
Citations
PageRank
Mojtaba Ghasemi11015.83
Mahdi Taghizadeh2101.52
Sahand Ghavidel3976.13
Jamshid Aghaei45419.74
Abbas Abbasian5100.84