Non-signal injection type user transformer topological relation identification method based on genetic algorithm

A genetic algorithm and relationship identification technology, applied in the field of non-signal injection household variable topology relationship identification, can solve the problems of inability to automatically update and identify, cumbersome work, and long time.

Pending Publication Date: 2020-12-25
江苏其厚智能电气设备有限公司 +1
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Problems solved by technology

[0007] The current identification of the low-voltage power distribution topology in the station area is based on an intrusive method, which requires manual participation, cumbersome work, long time, a

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  • Non-signal injection type user transformer topological relation identification method based on genetic algorithm
  • Non-signal injection type user transformer topological relation identification method based on genetic algorithm
  • Non-signal injection type user transformer topological relation identification method based on genetic algorithm

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[0079]The technical solution of the present invention will be described in detail below with the accompanying drawings, but the protection scope of the present invention is not limited to the embodiments.

[0080]The present invention uses the station area data collected by the actual operating system as a sample to build a station area model that conforms to the nature of the low-voltage distribution station area. Based on Kirchhoff’s law, it is based on the active power of the low-voltage station area under normal conditions. Relations, using artificial neural network algorithms, genetic algorithms and other artificial intelligence optimization inference algorithms to find the optimal topological connection relationship from a large number of analysis samples, and verify it through actual conditions.

[0081]The main technical route includes the following two methods:

[0082]1) Neural network

[0083]Based on the output of the power distribution side and the actual use of the active power da...

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Abstract

The invention discloses a non-signal injection type user transformer topological relation identification method based on a genetic algorithm. The method comprises the steps: obtaining effective data after data cleaning and screening according to electrical quantity data information, returning the effective data to a storage list TValidDataSet, and randomly generating an M*N initialization chromosome population data matrix Pop_data according to the effective data; entering a loop process; calling a fitness function; calling a selection function, a crossover function and a variation function ofthe genetic algorithm to obtain updated NewPopdata and chromosomes containing Pop_num optimal selection results; setting a premature condition, and entering a reset function call of the genetic algorithm; and obtaining a final NewPopdata, and obtaining a judgment result of each row corresponding to each household meter through the mapping relationship. According to the method, the problem of topology identification of a low-voltage transformer area can be solved by utilizing the data of an existing acquisition system, namely other equipment systems do not need to be installed.

Description

technical field [0001] The invention relates to the technical field of distribution network topology identification, in particular to a genetic algorithm-based non-signal injection type household transformer topology relationship identification method. Background technique [0002] At present, there are mainly the following traditional ways to distinguish the household-variable topology relationship in the low-voltage station area: [0003] 1. Line inspection method: For the power supply of users in the station area, the overhead line method is used. The traditional line inspection method starts from the outlet of the lower live wire of the user's meter box, traces the inspection line along the lower live line, and reaches the outlet end of the distribution transformer. Draw the wiring diagram and record the nameplate parameters and serial numbers of the equipment. The characteristics of this method are: heavy workload and low efficiency. Once the user changes the line or i...

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Application Information

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IPC IPC(8): G06N3/12G06N3/04G06Q50/06
CPCG06N3/126G06Q50/06G06N3/045
Inventor 徐文孙大璟唐明群葛善虎高尚源
Owner 江苏其厚智能电气设备有限公司
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