CN110232532B - Power grid overhaul index calculation method and system based on logistic regression - Google Patents
Power grid overhaul index calculation method and system based on logistic regression Download PDFInfo
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Abstract
The invention relates to the technical field of power transmission and distribution, and discloses a method and a system for calculating a power grid overhaul index based on logistic regression, which are used for realizing the calculation of the power grid overhaul index based on meteorological elements and providing a guarantee for reasonably arranging power grid overhaul; the method of the invention comprises the following steps: basic information of a transmission line to be overhauled is acquired, a basic database is established, and a weather database of the daily precipitation of the region where the transmission line to be overhauled is located is established; predicting the highest daily temperature, the relative humidity and the daily precipitation of seven days in the future of an area where the power transmission line to be overhauled is positioned by adopting a numerical mode; grid division is carried out on the region where the power transmission line to be overhauled is located according to longitude and latitude, and the region corresponds to the numerical mode result; defining a high temperature index, a precipitation index and an icing index, calculating to obtain a power grid overhaul probability according to the high temperature index, the precipitation index and the icing index, determining the power grid overhaul index according to the power grid overhaul probability, and judging whether overhaul is needed according to the power grid overhaul index.
Description
Technical Field
The invention relates to the technical field of power transmission and distribution, in particular to a method and a system for calculating a power grid overhaul index based on logistic regression.
Background
The distribution of the power transmission line is directly affected by natural environments such as strong wind, heavy rain, snow, lightning strike, heavy fog and the like, and simultaneously, geological disasters such as landslide, debris flow and the like caused by strong precipitation also cause harm to the safe and stable operation of the power grid. As a result, status maintenance of transmission lines becomes increasingly important. However, the current overhaul work of the power transmission equipment does not judge the actual running state of the equipment, but carries out periodical overhaul on the equipment completely according to the requirements of related regulations. When the weather factors such as thunderstorm and high temperature are encountered, the maintenance is inevitably stopped in consideration of personal safety, so that the maintenance task of the power transmission equipment cannot be completed on time, the waste of huge manpower, financial resources and material resources is caused, the health degree of the equipment cannot be guaranteed, and the reliability of power transmission is threatened.
Therefore, how to implement the calculation of the grid overhaul index based on the meteorological elements becomes an urgent problem to be solved.
Disclosure of Invention
The invention aims to provide a method and a system for calculating a power grid overhaul index based on logistic regression, which are used for realizing the calculation of the power grid overhaul index based on meteorological elements and providing a guarantee for reasonably arranging the power grid overhaul.
In order to achieve the above purpose, the invention provides a method for calculating a power grid overhaul index based on logistic regression, which comprises the following steps:
s1: acquiring basic information of a transmission line to be overhauled, establishing a basic database, and establishing a weather database of the daily precipitation of an area where the transmission line to be overhauled is located;
s2: predicting the highest daily temperature, the relative humidity and the daily precipitation of seven days in the future of the region where the power transmission line to be overhauled is located in a numerical mode, and outputting a prediction result by taking a grid as a unit;
s3: grid division is carried out on the region where the power transmission line to be overhauled is located according to longitude and latitude, and the divided grid requirements correspond to the grid predicted by the numerical mode;
s4: and defining a high temperature index, a precipitation index and an icing index of each grid according to the output result of the numerical mode prediction, calculating to obtain the grid overhaul probability in the grid according to the high temperature index, the precipitation index and the icing index, determining the grid overhaul index according to the grid overhaul probability, and judging whether the grid in the grid needs overhaul according to the grid overhaul index.
Preferably, in the step S3, the dividing precision of dividing the area where the power transmission line to be overhauled is located according to longitude and latitude is 0.25 ° x 0.25 °.
Preferably, the calculation formula of the high temperature index is:
in θ 1 Is of high temperature index, T max For the highest daily temperature in the grid, RH is the relative humidity in the grid.
Preferably, the precipitation index is calculated according to the following formula:
in θ 2 Rain3 is the precipitation index, and is the precipitation accumulation of three days before the forecast day.
Preferably, when the forecast day is the first day in the future, the first three-day precipitation accumulation Rain3 is the sum of the live day-by-day precipitation of the first two days of the current day and the 24-hour precipitation forecast of the current day;
when the forecast day is the next day in the future, the precipitation accumulation Rain3 of the first three days is the sum of the live day before the current day, the forecast precipitation of the current day and the 24-hour precipitation of the forecast future day;
when the forecast day is the third and later days in the future, the precipitation accumulation Rain3 of the first three days is the sum of the precipitation of 24 hours of the first three days of the forecast.
Preferably, the formula for calculating the ice coating index is:
in θ 3 For the icing index, ICE is the icing thickness.
Preferably, in the step S4, a calculation formula for calculating the grid overhaul probability is as follows:
wherein P is the power grid overhaul probability theta 0 For the control parameters, the calculation formula is:
preferably, in the step S4, the judging formula for judging whether the maintenance is required according to the power grid maintenance index is as follows:
wherein, I is a power grid overhaul index, and when the power grid overhaul index I=0, the power grid overhaul index is judged to be unsuitable for overhaul; when the grid overhaul index i=1, it is determined that overhaul is possible.
As a general technical idea, the present invention also provides a system for calculating a grid overhaul index based on logistic regression, which comprises a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.
The invention has the following beneficial effects:
the invention provides a method and a system for calculating a power grid overhaul index based on logistic regression, which are used for realizing the calculation of the power grid overhaul index based on meteorological elements and comprehensively reflecting the meteorological element states of power grid overhaul and provide a guarantee for reasonably arranging the power grid overhaul.
The invention will be described in further detail with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention. In the drawings:
fig. 1 is a flowchart of a method for calculating a grid overhaul index based on logistic regression according to a preferred embodiment of the present invention.
Detailed Description
Embodiments of the invention are described in detail below with reference to the attached drawings, but the invention can be implemented in a number of different ways, which are defined and covered by the claims.
Example 1
As shown in fig. 1, the embodiment provides a method for calculating a grid overhaul index based on logistic regression, which includes the following steps:
s1: basic information of a transmission line to be overhauled is acquired, a basic database is established, and a weather database of the daily precipitation of the region where the transmission line to be overhauled is located is established;
s2: predicting the highest daily temperature, the relative humidity and the daily precipitation of seven days in the future of an area where the power transmission line to be overhauled is positioned in a numerical mode, and outputting a prediction result by taking a grid as a unit;
s3: dividing the area of the transmission line to be overhauled into grids according to longitude and latitude, wherein the divided grids are required to correspond to the grids predicted by the numerical mode;
s4: and defining a high temperature index, a precipitation index and an icing index of each grid according to the output result of the numerical mode prediction, calculating to obtain the grid overhaul probability in the grid according to the high temperature index, the precipitation index and the icing index, determining the grid overhaul index according to the grid overhaul probability, and judging whether the grid in the grid needs overhaul according to the grid overhaul index.
When the prediction is performed using the numerical mode, the mode divides the area into grids, for example, 3km by 3km, in operation. To determine the weather element forecast of a section of the transmission line, it is necessary to know which part of the numerical forecast pattern results the section is located in. Therefore, when the area where the power transmission line to be overhauled is subjected to grid division according to longitude and latitude, the grid is required to correspond to the grid predicted by the numerical mode, the weather element prediction condition of the power transmission line in the grid can be accurately obtained, and the high temperature index, the rainfall index and the icing index in the grid can be conveniently determined.
According to the method for calculating the power grid overhaul index based on the logistic regression, the power grid overhaul index is calculated based on the meteorological elements, the meteorological element states of power grid overhaul are comprehensively reflected, and a guarantee is provided for reasonably arranging the power grid overhaul.
As a preferred embodiment of the present embodiment, the calculation of the numerical pattern is implemented using a mesoscale weather pattern (WRF).
Further, the area around the transmission line is subdivided into 0.25 degrees by 0.25 degrees according to longitude and latitude as a reference unit, and corresponds to a numerical mode result. Predicting the maximum daily temperature T according to the grid point position near the output power transmission line predicted by the numerical mode max The high temperature index is calculated at 38 ℃ with the relative humidity RH of 85%, and the calculation formula is as follows:
in θ 1 Is of high temperature index, T max For the highest daily temperature in the grid, RH is the relative humidity in the grid.
In this embodiment, the high temperature index θ is calculated 1 Is-0.5.
The accumulated precipitation amount of the grid point near the transmission line is 0 in three days, the future 7 days are expected to be mainly weather, the precipitation amount is 0, the precipitation index is calculated, and the calculation formula is as follows:
in θ 2 Rain3 is the precipitation index, and is the precipitation accumulation of three days before the forecast day. In this embodiment, the current day is the day of the report, that is, the day of the forecast, and the forecast day is the day on which the forecast result needs to be known.
In the present embodiment, precipitation index θ 2 Is 0.
And calculating an icing index when weather is good and icing is not present in the next 7 days of grid positions near the power transmission line, wherein a calculation formula is as follows:
in θ 3 For the icing index, ICE is the icing thickness.
In this embodiment, the icing index θ 3 Is 0.
In the present embodiment, due to θ 1 +θ 2 +θ 3 If = -0.5 < 0, there is a control parameter θ 0 Is 0, and p=0.38, grid overhaul index I (P<0.5 And) =0, so no service is recommended.
Example 2
In correspondence with the above method embodiment, the present embodiment provides a system for calculating a grid overhaul index based on logistic regression, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the above method when executing the computer program.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. The method for calculating the power grid overhaul index based on logistic regression is characterized by comprising the following steps of:
s1: acquiring basic information of a transmission line to be overhauled, establishing a basic database, and establishing a weather database of the daily precipitation of an area where the transmission line to be overhauled is located;
s2: predicting the highest daily temperature, the relative humidity and the daily precipitation of seven days in the future of the region where the power transmission line to be overhauled is located in a numerical mode, and outputting a prediction result by taking a grid as a unit;
s3: grid division is carried out on the region where the power transmission line to be overhauled is located according to longitude and latitude, and the divided grid requirements correspond to the grid predicted by the numerical mode;
s4: defining a high temperature index, a precipitation index and an icing index of each grid according to the output result of the numerical mode prediction, calculating to obtain the grid overhaul probability in the grid according to the high temperature index, the precipitation index and the icing index, determining the grid overhaul index according to the grid overhaul probability, and judging whether the grid in the grid needs overhaul according to the grid overhaul index;
wherein, the calculation formula of the high temperature index is:
in θ 1 Is of high temperature index, T max The highest daily temperature in the grid is represented by RH, and the relative humidity in the grid is represented by RH;
the precipitation index is calculated according to the following formula:
in θ 2 Rain3 is the precipitation index for forecasting precipitation accumulation of three days before the day;
the calculation formula of the icing index is as follows:
in θ 3 ICE is ICE thickness, which is the ICE coating index;
in the step S4, a calculation formula for calculating the power grid overhaul probability is as follows:
wherein P is the power grid overhaul probability theta 0 For the control parameters, the calculation formula is:
in θ 1 Is of high temperature index, theta 2 Index of precipitation, θ 3 Is ice coating index;
in the step S4, the judging formula for judging whether the maintenance is needed according to the power grid maintenance index is as follows:
wherein, I is a power grid overhaul index, P is power grid overhaul probability, and when the power grid overhaul index I=0, the power grid overhaul index is judged to be unsuitable for overhaul; when the grid overhaul index i=1, it is determined that overhaul is possible.
2. The method for calculating a grid overhaul index based on logistic regression according to claim 1, wherein in S3, the dividing precision of dividing the area where the power transmission line to be overhauled is located according to longitude and latitude is 0.25 degrees x 0.25 degrees.
3. The method for calculating a grid overhaul index based on logistic regression according to claim 1, wherein when the forecast day is the first day in the future, the first three days precipitation accumulation Rain3 is the sum of the first two days live day-by-day precipitation on the current day and the 24 hours precipitation forecasted on the current day;
when the forecast day is the next day in the future, the precipitation accumulation Rain3 of the first three days is the sum of the live day before the current day, the forecast precipitation of the current day and the 24-hour precipitation of the forecast future day;
when the forecast day is the third and later days in the future, the precipitation accumulation Rain3 of the first three days is the sum of the precipitation of 24 hours of the first three days of the forecast.
4. A logistic regression-based grid overhaul index calculation system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any one of the preceding claims 1 to 3 when executing the computer program.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0844421A (en) * | 1994-07-29 | 1996-02-16 | Toshiba Corp | Device for supporting maintenance and management of equipment |
| JP2014229001A (en) * | 2013-05-21 | 2014-12-08 | 株式会社東芝 | Facility utilization scheme determination method, facility utilization scheme determination apparatus, facility utilization scheme determination program, and facility utilization scheme determination system |
| KR101775065B1 (en) * | 2016-08-05 | 2017-09-06 | 주식회사 해줌 | Method, server and system for detecting abnormality of a power plant using solar energy |
| CN108596449A (en) * | 2018-04-09 | 2018-09-28 | 南京邮电大学 | It is a kind of to consider distribution network reliability prediction technique of the weather to distribution network failure impact probability |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105354640A (en) * | 2015-11-12 | 2016-02-24 | 国家电网公司 | Power grid equipment overhaul-oriented meteorological disaster forewarning model construction method |
| CN106384210B (en) * | 2016-10-28 | 2019-08-27 | 贵州电网有限责任公司贵阳供电局 | A kind of power transmission and transforming equipment maintenance prioritization method based on maintenance risk income |
| CN107271829A (en) * | 2017-05-09 | 2017-10-20 | 安徽继远软件有限公司 | A kind of controller switching equipment running state analysis method and device |
| CN107220905A (en) * | 2017-05-26 | 2017-09-29 | 国网甘肃省电力公司 | The distribution transformer running status method for prewarning risk that a kind of logic-based is returned |
| CN108375715B (en) * | 2018-03-08 | 2023-11-03 | 中国电力科学研究院有限公司 | Power distribution network line fault risk day prediction method and system |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0844421A (en) * | 1994-07-29 | 1996-02-16 | Toshiba Corp | Device for supporting maintenance and management of equipment |
| JP2014229001A (en) * | 2013-05-21 | 2014-12-08 | 株式会社東芝 | Facility utilization scheme determination method, facility utilization scheme determination apparatus, facility utilization scheme determination program, and facility utilization scheme determination system |
| KR101775065B1 (en) * | 2016-08-05 | 2017-09-06 | 주식회사 해줌 | Method, server and system for detecting abnormality of a power plant using solar energy |
| CN108596449A (en) * | 2018-04-09 | 2018-09-28 | 南京邮电大学 | It is a kind of to consider distribution network reliability prediction technique of the weather to distribution network failure impact probability |
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