CN-122000918-A - Load section early warning method, equipment and medium

CN122000918ACN 122000918 ACN122000918 ACN 122000918ACN-122000918-A

Abstract

The application provides a load section early warning method, equipment and a medium, which relate to the technical field of data processing and comprise the steps of obtaining real-time load of a load section, determining whether early warning judgment on the load section is executed according to the real-time load, respectively determining a first time period and a second time period if the early warning judgment on the load section is executed, obtaining first integral data of active power of the load section in the first time period, obtaining second integral data of the active power of the load section in the second time period, determining a load rate predicted value of the load section according to the first integral data and the second integral data, triggering load section early warning if the load rate predicted value is larger than a preset load rate predicted threshold, and improving early warning efficiency and early warning accuracy.

Inventors

LUO SONGLIN
ZHOU JUAN
LI ZHISHAN
CHEN JINGHAO
WANG ZIWEN
CHEN ZHICHENG
ZHANG SHIBIN
HU RUNFENG
LIU SHUAN
YANG YANG

Assignees

广东电网有限责任公司东莞供电局

Dates

Publication Date: 20260508
Application Date: 20260112

Claims (10)

1. The load section early warning method is characterized by comprising the following steps of: acquiring real-time load of a load section; determining whether to execute early warning judgment on the load section according to the real-time load; If the early warning judgment aiming at the load section is determined to be executed, a first time period and a second time period are respectively determined, wherein the first time period is a time period with the current real-time load acquisition time point as an end point on the current day and the preset duration is traced forward, the second time period is a time period with the same time corresponding to the current real-time load acquisition time point as an end point on the previous day and the preset duration is traced forward; acquiring first integral data of active power of the load section in the first time period; acquiring second integral data of the active power of the load section in the second time period; determining a load factor predicted value of the load section according to the first integral data and the second integral data; and if the load rate predicted value is larger than a preset load rate predicted threshold value, triggering load section early warning.
2. The method of claim 1, wherein determining whether to perform an early warning determination for the load profile based on the real-time load comprises: Acquiring a preset load section limit value; calculating the real-time load rate of the load section according to the preset load section limit value and the real-time load; and if the real-time load rate is greater than or equal to a first load rate threshold value, determining to execute early warning judgment on the load section.
3. The method of claim 2, wherein the determining the load factor forecast value for the load profile from the first integral data and the second integral data comprises: determining a maximum load rate of a previous day of the load section; Calculating a difference between the first integral data and the second integral data; calculating the product of the preset load section limit value and the time length of the first time period; determining a load difference value predicted value according to the ratio of the difference value to the product; and determining the sum of the maximum load rate of the previous day and the load rate difference predictive value as the load rate predictive value of the load section.
4. A method according to claim 3, wherein said determining a maximum load rate of a previous day of said load profile comprises: acquiring load rate data of the load section on the previous day; determining a maximum power time point according to the load rate data; carrying out data mutation judgment on the maximum power time point; and if the maximum power time point is not the data abrupt change time point, determining that the first load rate corresponding to the maximum power time point is the maximum load rate of the previous day.
5. The method of claim 4, wherein the determining the data mutation at the maximum power point in time comprises: Acquiring a first load rate of the maximum power time point; Determining a first time point and a second time point adjacent to the maximum power time point; Respectively acquiring a second load rate at the first time point and a third load rate at the second time point; determining a first abrupt change judgment ratio according to the first load rate and the second load rate; Determining a second abrupt change judgment ratio according to the first load rate and the third load rate; Determining the larger one of the first mutation judgment ratio and the second mutation judgment ratio as a target mutation judgment ratio; and if the target mutation judgment ratio is not greater than a preset mutation judgment threshold, determining that the maximum power time point is not a data mutation time point.
6. The method according to any one of claims 1 to 5, further comprising, after triggering the load profile warning if the load factor predicted value is greater than a preset load factor predicted threshold: Acquiring load information of the load section; And sending the load information to a preset early warning database.
7. The method of claim 6, further comprising, after said sending said load information to a pre-set pre-alarm database: generating an early warning prompt interface according to the early warning database; And displaying the early warning prompt interface.
8. The utility model provides a load section early warning device which characterized in that includes: The first acquisition module is used for acquiring real-time load of the load section; the first determining module is used for determining whether to execute early warning judgment on the load section according to the real-time load; The second determining module is used for determining a first time period and a second time period respectively if the early warning judgment on the load section is determined to be executed, wherein the first time period is a time period of a preset duration traced forward by taking the current real-time load acquisition time point as an end point on the same day, and the second time period is a time period of the same duration traced forward by taking the same time corresponding to the current real-time load acquisition time point as an end point on the same day; the second acquisition module is used for acquiring first integral data of the active power of the load section in the first time period; The third acquisition module is used for acquiring second integral data of the active power of the load section in the second time period; the third determining module is used for determining a load rate predicted value of the load section according to the first integral data and the second integral data; and the early warning module is used for triggering load section early warning if the load rate predicted value is larger than a preset load rate predicted threshold value.
9. The load section early warning device is characterized by comprising a memory and a processor; The memory stores computer-executable instructions; The processor executing computer-executable instructions stored in the memory, causing the processor to perform the method of any one of claims 1-7.
10. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-7.

Description

Load section early warning method, equipment and medium Technical Field The present application relates to the field of data processing technologies, and in particular, to a method, an apparatus, and a medium for early warning of a load section. Background For the power grid, the principle of N-1 is required to be followed, namely, a single fault occurs, the load change is monitored in real time and the risk of out-of-limit is early-warned by setting a section limit value considering the overload capacity of equipment, so that stable power supply and stable system operation under the single fault are ensured, for example, the rated capacity of each main transformer is 240MVA, the power factor is 0.95, the transformer substation has 4 main transformers, and the overload capacity of the main transformer is 1.3 times. The load provided by 4 main transformers of the transformer substation needs to meet the principle of N-1 that the control section power=240×0.95×1.3 (4-1) =889 MW, if there are 1 power outage overhauls for 4 main transformers, the remaining 3 main transformers need to control the section=240×0.95×1.3×1.3 (3-1) =593 MW according to the principle of N-1. Therefore, in order to ensure the stable operation of the system, a more accurate load section early warning method is developed, and the method has an application prospect. In the prior art, a load section limit value is calculated based on an N-1 principle, real-time monitoring and early warning are implemented, and a regulating and controlling person controls the section within the limit value through means of load transfer, operation mode adjustment and the like. However, in the prior art, load section early warning depends on real-time monitoring and is easily interfered by factors such as power plant output, weather and the like, so that early warning is delayed when load mutation occurs, the regulation and control response is difficult to match with load climbing speed, section continuous out-of-limit is caused, grid fault risk is aggravated, the early warning threshold is reduced, but a large number of false alarms can be triggered due to non-critical fluctuation, invalid accounting and manpower consumption are caused, and the technical problems of low early warning efficiency and poor early warning accuracy exist. Disclosure of Invention The load section early warning method, the load section early warning equipment and the load section early warning medium are used for achieving the technical effects of improving early warning efficiency and early warning accuracy. In a first aspect, the present application provides a load section early warning method, including: acquiring real-time load of a load section; determining whether to execute early warning judgment on a load section according to the real-time load; If the early warning judgment of the load section is determined to be executed, a first time period and a second time period are respectively determined, wherein the first time period is a time period with the current real-time load acquisition time point as an end point and the preset duration is traced forward, the second time period is a time period with the same time corresponding to the current real-time load acquisition time point as an end point and the preset duration is traced forward; Acquiring first integral data of active power of a load section in a first time period; Acquiring second integral data of active power of a load section in a second time period; Determining a load factor predicted value of the load section according to the first integral data and the second integral data; And if the load rate predicted value is larger than the preset load rate predicted threshold value, triggering load section early warning. In one possible implementation manner, according to the real-time load, determining whether to execute early warning judgment on the load section includes: Acquiring a preset load section limit value; Calculating the real-time load rate of the load section according to the preset load section limit value and the real-time load; And if the real-time load rate is greater than or equal to the first load rate threshold value, determining to execute early warning judgment on the load section. In one possible embodiment, determining the load factor predicted value of the load section according to the first integral data and the second integral data includes: Determining the maximum load rate of the previous day of the load section; Calculating a difference between the first integral data and the second integral data; Calculating the product of the preset load section limit value and the time length of the first time period; Determining a load difference value predicted value according to the ratio of the difference value and the product; and determining the sum of the maximum load rate and the load rate difference predicted value of the previous day as the load rate predicted value of the load section. In one p