TY - JOUR ID - 3119 TI - Optimal Placement of Capacitor Banks Using a New Modified Version of Teaching-Learning- Based Optimization Algorithm JO - AUT Journal of Modeling and Simulation JA - MISCJ LA - en SN - 2588-2953 AU - Rahiminejad, A. AU - Foroughi Nematollahi, A. AU - Vahidi, B. AU - Shahrooyan, S. AD - Department of Electrical and Computer Science, Esfarayen University of Technology, Esfarayen, Iran AD - Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran AD - Department of English Literature, Hakim Sabzevari University, Sabzevar, Iran Y1 - 2018 PY - 2018 VL - 50 IS - 2 SP - 171 EP - 180 KW - Teaching-Learning-Based Optimi‌zation algorithm KW - capacitor placement KW - net saving maximization KW - system stability enhancement DO - 10.22060/miscj.2018.14594.5111 N2 - Meta-heuristics optimization methods are important techniques for optimal design of the engineering systems. Numerous Meta-heuristics methods, all inspired by different nature phenomena, have been introduced in the literature. A new modified version of Teaching-Learning-Based Optimization (TLBO) Algorithm is introduced in this paper. TLBO, as a parameter-free algorithm, is based on the learning procedure of students in a classroom. In the Conventional TLBO (CTLBO), the students enhance their grade in two phases known as teacher phase and student phase. In the former, the teacher tries to enhance the average of the class. In the latter, the students share their knowledge in the groups of two. In the proposed Modified TLBO (MTLBO), the students participate in the groups of several students and improve their knowledge based on the grade of these students. Participating in the meeting with more than two students increases the probability of enhancing the student marks. To testify the performance of the proposed algorithm, it is applied to the problem of optimal capacitor placement with the aim of annual net saving maximization and system stability enhancement. The test systems are 34-bus and 94- bus radial test systems. The comparison of the results with those from off-the-shelf algorithms clears the appropriate performance, fast convergence, and superiority of the proposed algorithm.  UR - https://miscj.aut.ac.ir/article_3119.html L1 - https://miscj.aut.ac.ir/article_3119_a2b6cac2525cb30e8e6f75ed47a8f4c1.pdf ER -