A new modified TLBO algorithm for placement of AVRs in distribution system

Abstract

Automatic Voltage Regulators (AVRs) placement in the distribution system leads to many advantages for both utility and users. A modified teaching-learning-based-optimization (TLBO) algorithm for multi-objective siting and sizing of AVRs in distribution networks considering the existence of distributed generators (DGs) is investigated in this paper. Three objective functions, namely minimization of voltage deviation, electrical energy losses and energy generation cost are objective functions of the optimization problem. In the proposed algorithm, for enhancing the accuracy and convergence velocity of the original TLBO, both learner and teacher phases are improved. Furthermore, because objective functions are conflicting ones, a fuzzy clustering method is added to original TLBO. A 70-bus standard IEEE distribution network illustrates the superiority of the proposed algorithm in comparison with other evolutionary algorithms such as particle swarm optimization (PSO) algorithm, honey bee mating optimization (HBMO) algorithm, original TLBO, and genetic algorithm (GA) that shows the extraordinary of the proposed algorithm accuracy and convergence velocity.