Method and system for network reconfiguration in urban distribution network

Abstract

The present invention discloses a method and system for network reconfiguration in an urban distribution network. The method comprises: establishing multi-objective optimization functions of annual power shortage of the system, average power-off duration of the system, average power-off frequency of the system and minimal network loss of the urban distribution network; determining constraint conditions of the multi-objective optimization functions and the weight of each objective optimization function; setting an on-off initial value of the switch of each load node in the urban distribution network; according to the on-off initial value of the switch of each load node, the multi-objective optimization functions and the constraint conditions, using the multi-objective particle swarm optimization algorithm based on the decomposition and differential evolution to solve the multi-objective optimization functions; and according to the on and off of the switch of each load node in the urban distribution network corresponding to the weighted and minimum multi-objective optimization function solution, reconstructing the network in the urban distribution network. According to the method and system disclosed by the present invention, the network loss of the urban distribution network containing the distributed power supply and the automobile charging station can be optimized, the operation cost can be reduced, and the supply voltage quality of the urban distribution network can be improved at the same time.

Description

technical field [0001] The invention relates to the technical field of distribution network planning, in particular to a network reconfiguration method and system of an urban distribution network. Background technique [0002] In recent years, with the rapid development of the urban economy, the demand for electric energy has been on the rise, the power load has increased year by year, and the structure of the urban distribution network has become increasingly complex, causing the network loss of the urban distribution network to increase year by year. At the same time, in recent years, the power generation of various energy sources in my country is far from meeting people's demand for electricity. The phenomenon of power cuts is becoming more and more obvious, and the contradiction between supply and demand is becoming more and more serious. The impact on urban economic development and people's quality of life is increasing year by year. In order to solve the above problems...

AI Technical Summary

Problems solved by technology

However, the current methods of urban distribution network reconfiguration take relatively little consideration of new energy sources and new load access.

At the same time, there are certain problems in the current urban distribution network reconstruction algorithm. For example, the particle swarm algorithm based on binary codes is easy to fall into local convergence when analyzing the particle swarm, and produces a large number of infeasible solutions. The calculation is huge and time-consuming. There are very large limitations, and it is difficult to cope with the increasingly complex urban distribution network

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