Method for identifying power system core network based on cut constraint

Abstract

The invention discloses a method for identifying a power system core network based on cut constraint; a node current equation constraint based on a kirchhoff current law is established; in an inequality constraint, according to the actual situation, the reactive power is not considered, and the line current, which is not out of limit, is taken as a line power inequality constraint, and by taking the cut constraint as the connectedness constraint, a target function taking the economical efficiency and the power flow dielectric number as reference factors is solved; and correcting is carried outby the optimal power flow of OPF after a search net frame is obtained; and under the recognition method of the power system core network based on the cut constraint, the calculation method is more mature, and the result meets the requirements of actual systems.

Description

technical field [0001] The invention relates to the technical field of a modeling method for identification of a power system core backbone grid, in particular to an identification method for a power system core network based on cut constraints. Background technique [0002] The guaranteed bottom grid is the smallest grid to ensure the normal power supply of important loads under the condition of severe natural disasters, and it is also the basis for the gradual recovery of power supply after the disaster. It can be seen from this that the guaranteed bottom grid should firstly include important loads and important power supply nodes, and the scale of the grid should be as small as possible; secondly, the grid should try to include key lines that have a greater impact on system operation and recovery; On the basis of satisfying the safety operation constraints and topological connectivity constraints of the power grid, the guaranteed bottom grid should supply as much load as ...

AI Technical Summary

Problems solved by technology

[0004] The methods for calculating the bottom-guaranteed grid used in the above literatures all use artificial intelligence algorithms, which have problems such as uncertainty in calculation results, slow calculation speed, and poor robustness.

There is a huge flaw in solving the bottom-guaranteed grid search problem

In addition, in the model established in the above literature, there is no analytic constraint to guarantee the connectivity of the bottom grid

In addition, in the above literature, the search model of the bottom-guarantee grid established does not use the OPF optimal power flow for correction, so the optimization results cannot be more suitable for practical applications, and it is difficult to obtain a bottom-guaranteed grid with better economical efficiency.

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