Power distribution network line fault risk day prediction method and system
A technology of line fault and prediction method, applied in fault location, fault detection according to conductor type, measurement of electricity, etc., can solve the problems of lack of judgment of distribution network and avoid risks, so as to ensure reliability, avoid faults, and ensure reliable power supply sexual effect
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Embodiment 1
[0044] figure 1 It is a flow chart of a distribution network line failure risk day prediction method of the present invention, such as figure 1 A method for predicting a distribution network line fault risk day provided by the present invention includes:
[0045] Obtain the external environment information of the area where the tested line is located on the forecast day, the load forecast data of the tested line on the forecast day, the operation and maintenance plan of the tested line on the forecast day, and the self-condition information of the tested line on the forecast day;
[0046] Input the external environment information of the area where the line under test is located on the forecast day, the load forecast data of the line under test on the forecast day, the operation and maintenance plan of the line under test on the forecast day, and the self-condition information of the line under test on the forecast day obtained above The pre-built line failure risk day predic...
Embodiment 2
[0068] Based on the same inventive concept, the present invention also provides a distribution network line failure risk day prediction system, which may include:
[0069] The acquisition module is used to obtain the external environment forecast information of the area where the line under test is located on the forecast day, the load forecast data of the line under test on the forecast day, the operation and maintenance plan of the line under test on the forecast day, and the self-condition information of the line under test;
[0070] The forecast module is used to collect the external environment forecast information of the area where the line under test is located on the forecast day, the load forecast data of the line under test on the forecast day, the operation and maintenance plan of the line under test on the forecast day, and the The self-condition information is input into the pre-built line failure risk daily prediction model to generate the predicted value of the f...
Embodiment 3
[0092] Aiming at a certain line in the distribution network, the present invention aims at predicting the probability of failure of the line on a certain day in the future.
[0093] First, based on historical information, a machine learning method is used to establish a day-to-day prediction model for the line failure risk.
[0094] (1) Determine the input and output of the model
[0095] Based on the main influencing factors that lead to the line fault, the input and output of the model are sorted out.
[0096] The input includes four major factors: the line's own condition, the actual power supply condition, the external environment, and the operation and maintenance condition.
[0097] The output is the probability of failure on the line for that day.
[0098] The status of the line itself includes: the average line loss rate, average capacity-load ratio, overload operation time, and fault frequency of the line within a certain period of time on the day;
[0099] The act...
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