Аннотация
The Distribution Network Reconfiguration (DNR) problem is one of the important problems in the operation of distribution networks, which modifies the topology structure and improves the network performance by changing the state of the network switches.In this study, an optimization model is presented to solve the DNR problem with the aim of reducing active power losses.In this model, the objective function is defined based on minimizing line losses and the main constraints include maintaining the radial structure, full network connectivity, permissible bus voltage limits, and line current limitation.To solve this problem, an improved version of the Teaching-Learning-Based Optimization (TLBO) algorithm is introduced.The main innovation of this method is the simultaneous modification of the Teacher phase and the Learner phase.In the Teacher phase, a disturbance term with binary probability is added to the update equation to increase the search ability of the algorithm.Also, in the Learner phase, a new mechanism for knowledge transfer among students is proposed, which enhances the learning process and creates a better balance between exploration and exploitation.The performance of the proposed method is evaluated on the standard IEEE 33bus network.The simulation results show that the proposed algorithm determines the optimal network arrangement with open keys 7, 10, 14, 32, and 37.In this case, the active power losses are reduced from 208.4591 kW to 139.6552 kW, which is equivalent to 33.0059 percent loss reduction.Also, the minimum network voltage is increased from 0.9107 p.u to 0.9423 p.u and the Voltage Deviation (VD) value is reduced from 1.6606 to 1.1173.Furthermore, the convergence curve shows that the improved version of TLBO converges to a stable solution at a reasonable speed.The findings of this study show that the proposed method is able to effectively reduce power losses while maintaining network operation constraints and simultaneously improve the quality of the voltage profile; therefore, this method can be used as an efficient tool for solving Distribution Network Reconfiguration problems in radial distribution networks.