A distribution network reconfiguration method based on immune binary particle swarm optimization algorithm

Abstract

The invention discloses a distribution network reconfiguration method based on an immune binary particle swarm algorithm. Includes such steps as simplifying distribution network, numbering nodes, branches and switches, analyzing distribution network topology by using depth-first search method, calculating distribution network power flow by using forward-backward substitution method to obtain linepower flow and loss; 2) aim at minimizing that network los in normal operation of the distribution system, establishing a distribution network reconfiguration model and determining a fitness function;3) that immune binary particle swarm algorithm is implemented, the state of the connection switch in the distribution network is taken as a control variable to code, the initialization of the population is completed, the affinity, the concentration and the selection probability of the particles are calculate, and the global optimal solution is outputted. The invention improves the speed of the distribution network reconfiguration, prevents the problem of premature convergence, and improves the searching ability of the algorithm in the whole solution space.

Description

technical field [0001] The invention relates to a power grid reconfiguration method, in particular to a distribution network reconfiguration method based on an immune binary particle swarm algorithm. Background technique [0002] Distribution network reconfiguration refers to optimizing the distribution network operation structure by changing the switch state in the network under the premise of meeting the basic requirements of line voltage, current and grid radial operation, so as to reduce network loss, balance load, eliminate Overload, improve power supply reliability and other purposes. As an effective means of distribution network optimization, distribution network reconfiguration can be used not only as a tool for network planning, but also as a tool for real-time control. In the current situation of rapid economic development and increasingly tense power supply, through the reconstruction of power distribution network, the potential of the existing distribution netwo...

AI Technical Summary

Problems solved by technology

The traditional mathematical optimization algorithm is relatively mature, and can obtain a global optimal solution that does not depend on the initial structure of the distribution network. However, the mathematical optimization technology belongs to the "greedy" search algorithm, which takes a long time to calculate and cannot handle complex large-scale power systems.

The calculation of the optimal flow mode algorithm is relatively large, and all the tie switches are closed at the beginning so that there are multiple ring networks in the network at the same time. When solving the optimal flow, the currents of each ring network affect each other, and the order of opening the switches also has a great influence on the result.

The switch exchange algorithm can only consider the operation of a pair of switches at a time, which cannot guarantee the global optimality, and the reconstruction result is affected by the initial structure

However, other artificial intelligence algorithms are more dependent on the structure and operation mode of the power system distribution network, and the amount of calculation is relatively large, resulting in poor algorithm performance.

Images