Reactive power optimization method and system for distribution network

Abstract

The invention relates to a reactive optimization method and system of a distribution network. The method comprises: a high-dimensional random matrix is established based on a distribution network and a covariance matrix of the high-dimensional random matrix is calculated; a spectral distribution circular ring is constructed based on the covariance matrix and a to-be-measured matrix in the spectral distribution circular ring is determined; and on the basis of the to-be-measured matrix, a reactive power compensation point and a reactive power compensation capacity of the distribution network are determined. Because of introduction of the high-dimensional random matrix theory into the reactive power compensation analysis of the distribution network, a novel analysis method is provided for reactive power compensation of the distribution network.

Description

technical field [0001] The invention relates to the technical field of distribution network operation, in particular to a reactive power optimization method and system for a distribution network. Background technique [0002] Reactive power optimization can improve voltage quality and reduce network loss. It uses reactive power compensation or regulating equipment as a control method, and belongs to nonlinear programming problems. The traditional voltage and reactive power optimization mainly has the following problems: [0003] 1) Due to the hierarchical management of the power grid, there is a problem of repetitive construction of reactive power. At the same time, due to its cumbersome operation, it not only increases the cost of electricity, but also causes the problems of large investment in multi-level equipment, low utilization rate and poor comprehensive effect; 2) Existing reactive power compensation strategies are often limited to local reactive power compensation,...

AI Technical Summary

Problems solved by technology

Especially for the global optimization of reactive power, if all nodes are taken into account when optimizing reactive power in the whole network, the scope is too large, the optimization speed is slow, and the ideal effect cannot be achieved

The traditional reactive power optimization method has been studied and applied for many years, but it often requires certain assumptions, and it is easy to fall into the local optimum, and it is difficult to obtain the global optimal solution

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