CN-121984211-A - Electric power engineering detection method and system based on smart grid

CN121984211ACN 121984211 ACN121984211 ACN 121984211ACN-121984211-A

Abstract

The invention relates to the technical field of power engineering detection and provides a power engineering detection method and system based on a smart grid, wherein the method comprises the steps of acquiring operation parameter information of a power component of the power grid and environment information of an environment where the power component is located; the method comprises the steps of continuously analyzing operation parameter information to obtain a continuous variation trend of the operation parameter, determining expected influence of environmental factors on the operation parameter according to the environmental information, comparing the continuous variation trend of the operation parameter with the expected influence, judging that physical degradation exists in an electric power component to finish electric power engineering detection when the continuous variation trend of the operation parameter exceeds the expected influence, generating a physical degradation early warning signal when the operation parameter does not exceed a preset traditional warning range, and adjusting an early warning threshold of the electric power component according to the early warning signal to realize continuous optimization of the early warning threshold. The invention has the effect of improving the accuracy and the reliability of the detection of the power engineering.

Inventors

CHENG XIAOFEI
HU RUI
WEI SHILEI
Mo Wangyi
Ji Peichen
LI JIAN
LI YUAN
QIN LIUYUN
ZENG JINFU

Assignees

南方电网互联网服务有限公司

Dates

Publication Date: 20260505
Application Date: 20251208

Claims (10)

1. The utility model provides a power engineering detection method based on smart power grids, which is characterized by comprising the following steps: Acquiring operation parameter information of a power grid power component and environment information of an environment where the power component is located; Continuously analyzing the operation parameter information to obtain a continuous variation trend of the operation parameter; determining the expected influence of environmental factors on the operation parameters according to the environmental information; comparing the continuous variation trend of the operation parameters with the expected influence, and judging that the physical degradation exists in the power component when the continuous variation trend of the operation parameters exceeds the expected influence so as to finish the power engineering detection; And when the operation parameters do not exceed the preset traditional warning range, generating the physical degradation early warning signal, and adjusting the early warning threshold of the power component according to the early warning signal so as to realize continuous optimization of the early warning threshold.
2. The smart grid-based power engineering detection method according to claim 1, wherein the step of comparing the continuous variation trend of the operation parameter with the expected influence, and determining that there is physical degradation of the power component when the continuous variation trend of the operation parameter exceeds the expected influence, to complete the power engineering detection comprises: Continuously monitoring a deviation between a continuously changing trend of the operating parameter and the expected impact; When the deviation presents continuous consistent systematic deviation within preset time under the condition that the pre-warning signal of the physical degradation is not triggered, incremental adjustment is carried out on the environmental response coefficient in the environmental influence rule, and the expected influence of the adjusted environmental factors is obtained; Comparing the continuous trend of the operating parameter with the expected influence of the adjusted environmental factor, and determining that there is physical degradation of the electrical component when the continuous trend of the operating parameter exceeds the expected influence of the adjusted environmental factor.
3. The smart grid-based power engineering detection method according to claim 2, wherein when the deviation presents a continuously consistent systematic deviation within a preset time without triggering the pre-warning signal of physical degradation, the step of incrementally adjusting an environmental response coefficient in an environmental impact rule to obtain an expected impact of the adjusted environmental factor comprises: Acquiring a plurality of environmental factor information of the environment where the power component is located; dividing a plurality of environment modes according to the environment factor information; presetting a set of environmental impact rules for each environmental mode; Continuously monitoring a deviation between a continuously changing trend of the operating parameter and an expected influence of an environmental factor in the current environmental mode; When the deviation presents continuous consistent systematic deviation within preset time under the condition that the pre-warning signal of the physical degradation is not triggered, identifying environmental factors which are dominant and influence in the current environmental mode; and performing incremental adjustment on response coefficients related to the environmental factors of the dominant influence in the environmental influence rules corresponding to the current environmental mode according to the environmental factors of the dominant influence to obtain the expected influence of the adjusted environmental factors.
4. The smart grid-based power engineering detection method according to claim 3, wherein the step of incrementally adjusting a response coefficient associated with the dominant environmental factor in the environmental impact rule corresponding to the current environmental pattern according to the dominant environmental factor to obtain the expected impact of the adjusted environmental factor comprises: Continuously monitoring a deviation between a continuously changing trend of the operating parameter and an expected influence of an environmental factor in the current environmental mode; when the deviation shows continuous consistent systematic deviation within preset time under the condition that the pre-warning signal of the physical degradation is not triggered, starting a dynamic dominant factor recognition program; in the dynamic dominant factor identification program, according to the sensitivity of each environmental factor to the influence of the operation parameters in the current environment mode and the contribution degree of each environmental factor in the current deviation formation, evaluating and determining an environmental factor set which has dominant influence on the change of the operation parameters at the current moment; and performing incremental adjustment on response coefficients related to environmental factors in the environmental factor set in an environmental impact rule corresponding to the current environmental mode according to the environmental factor set with dominant impact to obtain the expected impact of the adjusted environmental factors.
5. The smart grid-based power engineering detection method according to claim 1, wherein the step of generating the early warning signal of physical degradation and adjusting the early warning threshold of the power component according to the early warning signal to achieve continuous optimization of the early warning threshold when the operation parameter does not exceed the preset conventional warning range comprises: Generating a data packet of an early warning signal when the physical degradation of the power grid power component is judged and the corresponding operation parameter is within a preset traditional warning range; based on a data packet of an early warning signal, current load information of a power grid and environment information of a power component, adjusting an early warning threshold corresponding to the power component of the power grid, and adjusting an original early warning threshold from a first early warning threshold to a second early warning threshold, wherein the second early warning threshold is positioned in a preset traditional warning range and is lower than the warning upper limit of the traditional warning range; and writing the second early warning threshold value into an early warning threshold value library, and executing early warning judgment based on the early warning threshold value updated to the second early warning threshold value when the operation parameter information of the power grid power component is detected subsequently, so as to realize continuous optimization of the early warning threshold value.
6. The smart grid-based power engineering detection method according to claim 4, wherein the step of incrementally adjusting, according to the dominant-influence environmental factor set, a response coefficient associated with an environmental factor in the environmental factor set in an environmental influence rule corresponding to a current environmental pattern, to obtain an expected influence of the adjusted environmental factor includes: continuously evaluating the magnitude and the change rate of the deviation between the continuous change trend of the operation parameter and the expected influence of the environmental factors in the current environmental mode; When the deviation shows continuous consistent systematic deviation within preset time under the condition that the pre-warning signal of the physical degradation is not triggered, calculating an adjustment step length according to the magnitude and change rate of the deviation and the sensitivity of each environmental factor to the influence of the operation parameters in the current environmental mode; And according to the adjustment step length, performing incremental adjustment on response coefficients related to the dominant environmental factor set in the environmental impact rules corresponding to the current environmental mode.
7. The smart grid-based power engineering detection method according to claim 6, wherein the step of calculating the adjustment step size according to the magnitude and the change rate of the deviation and the sensitivity of each environmental factor to the influence of the operation parameter in the current environmental mode comprises: calculating the instantaneous sensitivity of each environmental factor to the influence of the operation parameters in the current environmental mode in real time according to the operation parameter information and the plurality of environmental factor information; And calculating an adjustment step according to the magnitude and the change rate of the deviation and the instantaneous sensitivity.
8. The smart grid-based power engineering detection method according to claim 7, wherein the step of calculating the instantaneous sensitivity of each environmental factor to the influence of the operating parameter in the current environmental mode in real time according to the operating parameter information and the plurality of environmental factor information comprises: Extracting the characteristics of the operation parameter information to obtain first characteristic information representing the microstructure change inside the power component; Extracting the characteristics of the environmental factor information to obtain second characteristic information representing the influence of the environmental factor on the operation parameters; comparing the first characteristic information with the second characteristic information, and judging that the power component has abnormal sensitivity to the environmental factors when specific association exists between the first characteristic information and the second characteristic information; and taking the abnormal sensitivity as a degradation early warning auxiliary index of the power component, and calculating the instantaneous sensitivity of each environmental factor to the influence of the operation parameters in the current environmental mode in real time according to the abnormal sensitivity.
9. The smart grid-based power engineering inspection method of claim 8, wherein the step of performing feature extraction on the operating parameter information to obtain first feature information characterizing a microstructure change inside the power component comprises: Identifying a specific frequency component or a time sequence mode existing in the operation parameters according to the operation parameter information; Filtering the operation parameter information to separate noise interference in a specific frequency component or time sequence mode; amplifying the specific frequency component or time sequence mode after filtering; and extracting the specific frequency component or the time sequence mode subjected to the amplification processing as first characteristic information for representing the internal microstructure change of the power component.
10. A smart grid-based power engineering detection system for performing smart grid-based power engineering detection, comprising: The information data acquisition module is used for acquiring operation parameter information of the power grid power component and environment information of the environment where the power component is located; the change trend acquisition module is used for continuously analyzing the operation parameter information to acquire a continuous change trend of the operation parameter; the expected influence determining module is used for determining the expected influence of the environmental factors on the operation parameters according to the environmental information; The physical degradation judging module is used for comparing the continuous change trend of the operation parameters with the expected influence, and judging that the power component is physically degraded when the continuous change trend of the operation parameters exceeds the expected influence so as to finish power engineering detection; And the early warning signal generation module is used for generating the early warning signal of the physical degradation when the operation parameters do not exceed the preset traditional warning range, and adjusting the early warning threshold value of the power component according to the early warning signal so as to realize the continuous optimization of the early warning threshold value.

Description

Electric power engineering detection method and system based on smart grid Technical Field The invention relates to the technical field of power engineering detection, in particular to a power engineering detection method and system based on a smart grid. Background In modern power engineering, the stable operation and construction efficiency of power transmission and transformation equipment are ensured, and the real-time and accurate detection of the operation states of the power transmission and transformation equipment is not needed. For this reason, the smart grid-based power engineering detection method and system are widely adopted. The core of these systems is their fault determination logic, which, at the beginning of the design, relies mainly on statistical analysis of large amounts of past operational data, in particular for specific power line segments and equipment types, such as high voltage cable junctions, insulators, etc., to establish their operational characteristics. This logic defaults that these critical components should remain relatively stable within normal operating ranges, and its determination is based primarily on pre-set fixed guard lines and statistical anomalies. However, in practical power engineering environments, particularly for those power components that are used for long periods of time or that operate under specific climatic conditions, their materials may undergo a natural, slow physical aging process. Such gradual degradation often results in subtle, cumulative changes in operating parameters that are difficult for existing systems to accurately identify and distinguish from normal external environmental fluctuations, thereby affecting timely and accurate fault pre-warning. For example, the metal material in the connection point of the power cable may gradually generate micro cracks due to various factors such as thermal expansion and contraction, micro vibration, etc., so that the resistance at the time of contact is gradually increased, and the insulator material may gradually decrease the insulation performance due to molecular chain breakage caused by ultraviolet irradiation, moisture erosion, etc. These changes are not abrupt faults, but rather cumulative, slightly occurring physical degradations that are difficult to immediately find by conventional visual inspection or simple resistance testing. In view of the above, there is a need in the art for improvements. Disclosure of Invention The application discloses a smart grid-based power engineering detection method and a smart grid-based power engineering detection system, and aims to solve the problems that the conventional power engineering detection system is limited in the aspect of identifying progressive physical degradation of power components and the conventional early warning mechanism cannot effectively distinguish benign environmental changes from malignant degradation trends. The technical scheme of the application is as follows: in a first aspect, the application discloses a smart grid-based power engineering detection method, which comprises the following steps: Acquiring operation parameter information of a power grid power component and environment information of an environment where the power component is located; Continuously analyzing the operation parameter information to obtain a continuous variation trend of the operation parameter; determining the expected influence of environmental factors on the operation parameters according to the environmental information; Comparing the continuous variation trend of the operation parameters with the expected influence, and judging that the physical degradation exists in the power component when the continuous variation trend of the operation parameters exceeds the expected influence so as to finish the detection of the power engineering; and when the operation parameters do not exceed the preset traditional warning range, generating a physical degradation early warning signal, and adjusting an early warning threshold of the power component according to the early warning signal so as to realize continuous optimization of the early warning threshold. According to the technical scheme, the early physical degradation of the power component can be effectively identified, the early warning can be generated even if the operation parameters do not reach the traditional warning range, and the defect that the degradation trend is misjudged as normal change by the existing system is overcome by continuously optimizing the early warning threshold, so that the timeliness and the accuracy of the early warning are improved. Further, comparing the continuous variation trend of the operation parameter with the expected influence, and when the continuous variation trend of the operation parameter exceeds the expected influence, determining that there is physical degradation of the electric power component to complete the electric power engineering detection includes: