Optimal recloser and autosectionalizer allocation for reliability improvement of distribution networks using HBB-BC algorithm

Optimal recloser and autosectionalizer allocation for reliability improvement of distribution networks using HBB-BC algorithm

Reliability improvement is one of the important goals for distribution companies. Use of automatic devices such as recloser and autosectionlizer (R AS) can reduce the amount of interrupted load during the faults and the restoration time. Determination of optimal location of these automatic devices is a combinational and complex problem. In this paper, a methodology based on cost/benefit analysis for optimal R AS allocation in distribution systems is proposed. The objective function is considered minimizing the costs of distribution system reliability with regard to the effect of load types and investment and maintenance costs of R ASs. Applied method for solving the problem is based on Hybrid Big Bang-Big Crunch (HBB-BC) algorithm and Monte Carlo simulation. The HBB-BC algorithm is an effective and powerful method that has high accuracy and fast convergence as well as its implementation is easy. In this algorithm PSO capacities and mutation operation are used to improve the exploration ability of the BB-BC algorithm and avoid local optimum. The proposed algorithm is tested on the real 28-bus distribution system in Qazvin, Iran. Simulation results indicate the efficient performance of the proposed algorithm.

Reliability improvement is one of the important goals for distribution companies. Use of automatic devices such as recloser and autosectionlizer (R AS) can reduce the amount of interrupted load during the faults and the restoration time. Determination of optimal location of these automatic devices is a combinational and complex problem. In this paper, a methodology based on cost/benefit analysis for optimal R AS allocation in distribution systems is proposed. The objective function is considered minimizing the costs of distribution system reliability with regard to the effect of load types and investment and maintenance costs of R ASs. Applied method for solving the problem is based on Hybrid Big Bang-Big Crunch (HBB-BC) algorithm and Monte Carlo simulation. The HBB-BC algorithm is an effective and powerful method that has high accuracy and fast convergence as well as its implementation is easy. In this algorithm PSO capacities and mutation operation are used to improve the exploration ability of the BB-BC algorithm and avoid local optimum. The proposed algorithm is tested on the real 28-bus distribution system in Qazvin, Iran. Simulation results indicate the efficient performance of the proposed algorithm.