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A low-voltage distribution network topology identification method and system based on logistic regression

A low-voltage distribution network and logistic regression technology, applied in character and pattern recognition, electrical components, circuit devices, etc., can solve the problems of complex wiring, frequent update of distribution network, and difficulty in realizing topology identification of distribution network. The effect of short running time, increased topology identification difficulty, and high accuracy

Active Publication Date: 2021-12-10
ELECTRIC POWER RES INST OF STATE GRID ZHEJIANG ELECTRIC POWER COMAPNY +3
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Problems solved by technology

[0004] Problems in the existing research: most of the research on power system topology is limited to the identification of transmission network topology errors and the detection of topology changes. However, the current distribution network is frequently updated and the wiring is complex. With the development of smart grids, Massive data in each link of the distribution network makes it difficult to realize the topology identification of the distribution network

Method used

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  • A low-voltage distribution network topology identification method and system based on logistic regression
  • A low-voltage distribution network topology identification method and system based on logistic regression
  • A low-voltage distribution network topology identification method and system based on logistic regression

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Embodiment 1

[0054] This embodiment provides a low-voltage distribution network topology identification method based on the logistic regression method, the flow chart of which is as follows figure 1 As shown, the steps it adopts are as follows:

[0055] Step (1): Collect time-series voltage amplitude information of users in the low-voltage distribution station area as data for identifying the topology of the low-voltage distribution station area, and the corresponding time-series historical topology structure as a label.

[0056] The voltage of each node is measured regularly by the smart meter, and the historical time series value of the voltage of each node is obtained.

[0057] Time-series voltage amplitude measurements of users in low-voltage distribution stations: {z 1 ,z 2 ,...,z k ,...,z Q}, Q represents the length of the time series, z k Represents a vector of voltage measurements under a time series.

[0058] The time series historical topology of collecting historical data:...

Embodiment 2

[0087] The present embodiment provides a low-voltage distribution network topology identification system based on a logistic regression method, which includes:

[0088] Data acquisition module: collect the time series voltage amplitude information of users in the low-voltage distribution station area as the data to identify the topology of the low-voltage distribution station area, and the corresponding time-series historical topology structure as the label;

[0089] Model generation module: training regression method to generate regression model;

[0090] Historical data acquisition module: use the time series historical voltage measurement values ​​of historical data to obtain a set of most similar historical data through the nearest neighbor algorithm

[0091] Topology prediction module: the historical data Put it into the already trained regression model for prediction, and get the optimal topological structure of the low-voltage distribution station area.

[0092] In...

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Abstract

The invention discloses a low-voltage distribution network topology identification method and system based on a logic regression method. With the penetration of distributed energy, the power energy system puts forward higher requirements for fast and accurate online data analysis tools. The technical solution adopted by the low-voltage distribution network topology identification method of the present invention is as follows: first, collect the time-series voltage amplitude information of the users in the low-voltage distribution network area; secondly, train the historical data to obtain the classification model of the topology; The neighbor algorithm obtains a group of the most similar historical data, and finally puts it into the trained regression model for prediction to complete the topology identification of the low-voltage distribution station area. The invention can better cope with the transformation of the electric power industry model from the traditional physical model-based monitoring system structure to the data-driven resource management model, and breaks the current situation that the existing monitoring structure-based model requires large-scale and complex modeling and consumes a lot of time.

Description

technical field [0001] The invention belongs to the field of distribution network topology identification and relates to a low-voltage distribution network topology identification method and system based on a logic regression method. Background technique [0002] Power network analysis and optimization problems are the basis of power system control, operation and planning. In recent years, a large proportion of renewable energy has been connected to the grid on a large scale, and its power generation output has strong randomness, which puts forward higher requirements for the analysis and optimization of power system uncertainty. The penetration of distributed energy, energy storage, electric vehicles and other equipment in the terminal distribution network is gradually increasing, making the analysis and control of the distribution network more complicated. These factors bring challenges to power network analysis and optimization problems. [0003] On the other hand, data...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/00H02J3/38G06K9/62
CPCH02J3/00H02J3/381H02J2203/20H02J2300/20G06F18/2411G06F18/214
Inventor 张弛周金辉赵健邵先军童力江航陈蕾谢琳王凯赵启承王子凌陈超
Owner ELECTRIC POWER RES INST OF STATE GRID ZHEJIANG ELECTRIC POWER COMAPNY
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