Dynamic configuration of distribution network based on improved hierarchical clustering and GL-APSO algorithm - Yun WANG; Meiyun WANG; Jian ZHOU; Yuanyuan ZOU; Shaoyuan LI (智能科学与技术学报)
Aiming at the problem of dynamic reconfiguration of distribution network with distributed generation (DG), a dynamic distribution networks reconfiguration scheme considering the time-varying property of DG and distribution network load was proposed.Firstly, according to the comprehensive similarity between different periods based on both load characteristics and optimal network structure, an improved hierarchical clustering method was used to divide the reconstruction interval into segments.On this basis, the genetic learning adaptive particle swarm optimization algorithm was proposed to realize the dynamic reconstruction with minimum network loss.To tackle the shortcomings such as the lack of speed dynamic adjustment strategy and ease to fall into local optimum in basic particle swarm optimization algorithm, a genetic learning scheme based on the optimal position of individual particles was proposed to enhance diversity and improve global search ability.Adaptive inertia weight and acceleration coefficients were introduced to meet the optimization requirements of different periods.Finally, a simulation was carried out through the IEEE 33-bus distribution system as an example to verify the effectiveness and superiority of the proposed method.