Method for solving protection maloperation caused by abnormal large number based on floating threshold

Abstract

The invention provides a method for solving protection maloperation caused by an abnormal large number based on a floating threshold. The method comprises the following steps of: calculating a variable quantity of a current sampling value, calculating the floating threshold for the obtained variable quantity, comparing the current variable quantity with a starting constant value added with the floating threshold, if the current variable quantity is greater than the value and a certain point number is satisfied, determining that an abnormal large number exists, and after the protection meets an action condition, adopting long delay greater than an algorithm requirement to avoid misoperation, otherwise, adopting short delay to quickly remove the fault after the protection meets the action condition. According to the method, the continuous abnormal large number and the fault can be well distinguished, the data window of the method is short, the action speed during the fault cannot be sacrificed, and the problem that the continuous abnormal large number causes protection misoperation or slows down the fault action speed, which puzzles the power system industry, is solved. When protection conditions are met, variable time delay is adopted, normal protection action can not be affected, and correct action can be achieved even if an abnormal large number exists in a fault.

Description

technical field [0001] The invention belongs to the technical field of electric power systems, and relates to a method based on floating thresholds to solve protection maloperation caused by abnormally large numbers. Background technique [0002] When struck by lightning or other disturbances, the electrical signal of the power system will generate abnormally large numbers, which will cause the protection device to malfunction, and it is difficult to distinguish the abnormal sampling value of the electrical quantity from the normal sampling value when the fault occurs under a short data window. At present, there are some judgments on the abnormal point data of the sampling value, but all of them have defects: [0003] 1) For example, the 3-point continuous effective discriminant method with time delay can only be applied to such Figure 4 Validity of sampled values ​​for the finite discontinuity shown in (a), but for Figure 4 (b) or Figure 4 It is not applicable to occasio...

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Problems solved by technology

[0003] 1) For example, the 3-point continuous effective discriminant method with time delay can only be applied to such Figure 4 Validity of sampled values ​​for the finite discontinuity shown in (a), but for Figure 4 (b) or Figure 4 It is not applicable to occasions with multiple discontinuities shown in (c); or the data window requires a long time and poor real-time performance, which cannot be applied to fast protection;

[0004] 2) There is also a difference algorithm that uses the comparison of before and after values, but in the case of multiple discontinuities, it is also impossible to distinguish

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