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The rapid growth of distributed energy resources integrated in distribution systems leads to an increasing need of continuously and automatically changing the system topology to realize the economic operation of distribution networks. This paper proposes an optimization model of dynamic reconfiguration for distribution networks based on a new method of time series analysis. Equivalent daily curve considering time‐varying nature of distributed generator and load demands is divided by an improved fuzzy C‐means clustering algorithm, where the indicator of section function is set to find the optimal reconfiguration time intervals. The uncertainty of distributed generator outputs and load demands is described by the interval algorithm. Then the affine Taylor expansion is adopted to solve the interval power flow equations. The reconfiguration optimization model is solved with decimal particle swarm optimization algorithm based on loop search. The optimal dynamic reconfiguration of a modified 70‐bus test system with distributed generators is carried out and the simulation results demonstrate the effectiveness and superiority of the proposed method. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Seismic activities show a space-time symmetry in some research. They have been recently studied using complex network theory. Earthquake network similarity is studied by us from seismic catalogs in the same region for a given period of time. In this paper, we first calculate the distance between feature vectors which represent the topological properties of different networks. A hierarchical clustering of earthquake networks in the same region is shown by using this method. It is found that similar networks are not the networks of adjacent years but those with decades time difference. To study the period of similar earthquake networks in the same region, we use wavelet analysis to obtain the possible periods at different time scales of the regions of the world, California and Japan. It is found that some of the possible periods are consistent with the results which have been already found by seismologists. The study of similar seismic activities from the perspective of the complex network will help seismologists to study the law of earthquake occurrence in a new way, which may provide possible research thinking for earthquake prediction. [ABSTRACT FROM AUTHOR]