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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Engineering Applications of Artificial Intelligence
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.