Voltage level uncertainty influence elastic network regression analysis method of power distribution network

Abstract

The invention discloses a voltage level uncertainty influence elastic network regression analysis method of a power distribution network. The method comprises the following steps of estimating a voltage expectation value of a node by a point estimation method; building a training sample required by an elastic network algorithm according to the expectation value; determining a leading influence source with the most influence on each node voltage and influence quantity of the leading influence source in each uncertainty source by elastic network regression analysis on the node voltage; building a node-uncertainty influence source correlation matrix according to uncertainty source probability distribution characteristic and a node voltage regression equation; introducing singular value decomposition to obtain an action mode of the uncertainty source on each node voltage and a corresponding node classification result. With the elastic network regression analysis method proposed by the invention, the uncertainty influence and the action mode of the uncertainty source such as a distributed power supply and a fluctuation load in the power distribution network on each node voltage can be quantitatively analyzed.

Description

technical field [0001] The invention relates to a regression analysis method for an elastic network affected by voltage level uncertainty of a distribution network, and belongs to the technical field of distribution network operation characteristic analysis. Background technique [0002] Accurate analysis of distribution system characteristics is an important prerequisite for active distribution network planning, operation and maintenance, and power management. The impact of determinism on the operation status of distribution network is also becoming more and more prominent. Indexes and analysis methods for a given operating point, such as sensitivity coefficients and distribution factors based on deterministic power flows, have been unable to meet the application requirements of the actual multi-working condition system. According to different modeling methods of uncertain factors such as power supply, load and components, scholars at home and abroad have successively prop...

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Problems solved by technology

When the distribution network contains many uncertain factors, the final output results of the above uncertainty analysis methods are all a certain distribution, which can only reflect the joint effect of multiple input random variables, but cannot accurately analyze the impact of each input random variable on the output random The degree of influence of the variable

[0003] Some scholars introduce affine operation into the interval power flow to take advantage of the simplicity of interval uncertainty modeling and overcome the conservatism of int...

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