Active power distribution network fragile node identification method considering new energy influence

Abstract

The invention discloses an active power distribution network fragile node identification method considering new energy influence, which comprises the following steps: sampling a pre-constructed DG random output model and a load random model to obtain random output data of new energy and a load, determining random output matrixes according to the random output data, arranging the random output matrixes, and determining the fragile nodes of the active power distribution network according to the random output matrixes. Obtaining an arrangement matrix enabling the correlation of each random variable sampling value to tend to be minimum; inputting the data in the arrangement matrix into a pre-constructed node vulnerability index evaluation system model to obtain a node comprehensive vulnerability index; a three-parameter interval number sorting method based on a Boolean matrix is combined with a node comprehensive vulnerability index to identify vulnerable nodes. The method has the advantages that under the condition that new energy is accessed to the power distribution network, the vulnerable nodes in the power distribution network can be accurately and rapidly identified, the vulnerability of the power distribution network is effectively evaluated, a power grid operator can comprehensively and deeply master the safety condition of the power distribution network, and risks caused by the vulnerability are eliminated or alleviated.

Description

technical field [0001] The invention relates to an active distribution network vulnerable node identification method considering the impact of new energy, and belongs to the technical field of active distribution network vulnerable node identification. Background technique [0002] In recent years, there have been many blackouts in the domestic and foreign power systems, resulting in a lot of economic losses. The power outage in the U.S. and Canada in 2003 and the ice disaster in southern China in 2008 both caused large-scale and long-term power outages; on March 21, 2018, the Brazilian power grid caused a cascading failure due to the overload protection of circuit breakers, causing the northern and northeastern parts of the grid to fail. 14 states experienced widespread power outages. The occurrence of these power outages has attracted the attention of electric power workers. How to identify the risks of key equipment in the power system has become an important research co...

AI Technical Summary

Problems solved by technology

However, due to the unique randomness and volatility of new energy power sources, when the output of new energy power generation fluctuates, the power flow of the distribution network will also change accordingly, and the identification of vulnerable nodes in the power grid often depends on the results of the power flow. It is particularly urgent and important to accurately and quickly identify vulnerable nodes in the power grid

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