A new Hybrid Evolutionary Algorithm for Distribution Network Reconfiguration Considering Wind and load uncertainty

Distribution Network Reconfiguration (DNR) must account uncertain behavior of loads and wind, when Wind Turbine Generators (WTG) supports a significant part of network. In this paper a new hybrid Bacterial Foraging and Differential Evolution (BF-DE) algorithm is considered for the DNR problem with minimum loss. In the BF-DE algorithm the DE algorithm is combined with the BF algorithm to improve the performance of BF. Indeed, the proposed algorithm is based on the evolutionary natures of BF and DE, to take their advantage of the compensatory property, and avoid their drawbacks. In addition, to cope with the uncertainty behavior of loads and wind, a stochastic model is presented to solve the DNR problem when the uncertainty related to wind and loads forecast is modeled in a stochastic framework on scenario approach basis. The proposed algorithm is tested on an 84-bus distribution test systems. The results of the simulation show the effectiveness of proposed algorithm

A new Hybrid Evolutionary Algorithm for Distribution Network Reconfiguration Considering Wind and load uncertainty Keywords:

Distribution Network Reconfiguration (DNR) , Wind Turbine Generators (WTG) , Bacterial foraging (BF) , Differential Evolution (DE).