CN111079808A - Rapid gust prediction method and system based on weather classification - Google Patents
Rapid gust prediction method and system based on weather classification Download PDFInfo
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Abstract
本发明公开了一种基于天气分型的阵风快速预测方法及系统，该方法包括：获取待预测区域的过去一段时间的平均风数据，包括平均风的分段时间内的最多阵风风向及分段时间内的平均风速的数据；对平均风数据进行降维处理，获得多个平均风要素；对平均风要素进行聚类分析获得多个聚类，作为多个天气分型；采用阵风模型对多个天气分型进行训练，得到不同的天气分型下阵风预测模型；对待预测区域的未来一段时间的平均风进行预测，并计算预测结果的天气分型，采用对应的天气分型的阵风预测模型预测阵风的风速。本发明能够基于已有数值模式的平均风预测结果，对阵风快速进行预测。
The invention discloses a method and system for rapid gust prediction based on weather classification. The method includes: acquiring the average wind data of the area to be predicted in the past period of time, including the most gust wind direction and the segment within the segment time of the average wind. The average wind speed data in time; the dimensionality reduction of the average wind data is performed to obtain multiple average wind elements; the cluster analysis of the average wind elements is performed to obtain multiple clusters as multiple weather classifications; the gust model is used to Train each weather type to obtain gust prediction models under different weather types; forecast the average wind in the area to be forecasted for a period of time in the future, calculate the weather type of the forecast result, and use the gust prediction model of the corresponding weather type Predict the wind speed of gusts. The invention can quickly predict the gust of wind based on the average wind prediction result of the existing numerical model.
Description
Technical Field
The invention relates to the technical field of power grid protection, in particular to a method and a system for rapidly predicting gust based on weather typing.
Background
The Chinese region is wide, disastrous gusts often occur, and accidents such as tower collapse, disconnection, windage yaw flashover, insulator string separation, hardware breakage and the like of the power transmission line are often caused. Therefore, the accurate prediction of the wind speed and the wind direction of the gust has great significance for deploying the disaster prevention and relief equipment of the power grid in advance.
However, the current meteorological model can only output average wind, and the numerical value is smaller than the size of gust. Otherwise, the calculation amount is large, and the service requirement is difficult to adapt.
Therefore, it is necessary to research a method and a system for fast predicting gust.
Disclosure of Invention
The invention provides a method and a system for rapidly predicting gust based on weather typing, which are used for solving the technical problem that the gust can not be accurately predicted because the current meteorological model only can output average wind.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
a gust rapid prediction method based on weather typing comprises the following steps:
acquiring average wind data of a region to be predicted in the past period of time, wherein the average wind data comprises the maximum gust wind direction in the sectional time of the average wind and the average wind speed data in the sectional time;
carrying out dimensionality reduction on the average wind data to obtain a plurality of average wind elements;
carrying out cluster analysis on the average wind factor to obtain a plurality of clusters as a plurality of weather types;
training a plurality of weather patterns by using a gust model to obtain gust prediction models under different weather patterns;
and predicting the average wind of a future period of time of the area to be predicted, calculating the weather typing of the prediction result, and predicting the wind speed of the gust by adopting a gust prediction model of the corresponding weather typing.
Preferably, the gust model is:
wherein A and n are parameters to be fitted, UmIs mean wind, UgIs a gust of wind.
Preferably, a satisfies:
G＝AUn；
wherein G is the gust coefficient, and:
preferably, the average wind is an average wind of several minutes, hours or days.
The present invention also provides a computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any of the methods described above when executing the computer program.
The invention has the following beneficial effects:
1. the method and the system for rapidly predicting the gust based on the weather typing have simple and convenient calculation process and can rapidly predict the gust based on the average wind prediction result of the existing numerical mode. The method is good in universality and can be suitable for calculating gust prediction in different areas.
2. By adopting the calculation result of the invention, line operation and maintenance personnel can be helped to deploy equipment for preventing wind deflection tripping, flashover and the like in time in areas with large gust wind speed, and the safe and stable operation of a power grid is ensured.
In addition to the objects, features and advantages described above, other objects, features and advantages of the present invention are also provided. The present invention will be described in further detail below with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a flow chart of a method for rapidly predicting gust based on weather typing according to a preferred embodiment of the present invention.
Detailed Description
The embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways as defined and covered by the claims.
Referring to fig. 1, the method for rapidly predicting gust based on weather typing of the present invention includes the following steps:
s1: average wind (average wind is preferably average wind of a plurality of minutes, hours or days) data of a past period of the area to be predicted are obtained, and the average wind data comprise the wind direction of the maximum gust in the segmented time of the average wind and the average wind speed in the segmented time. Typically, the average wind data includes a 10 minute average wind speed and a maximum wind direction over 10 minutes;
s2: and carrying out dimensionality reduction on the average wind data to obtain a plurality of average wind elements. The mean wind may preferably be subjected to a dimensionality reduction process by principal component analysis:
the mean wind data constitutes a data set X, principal component analysis is performed on X to obtain q principal components, the corresponding contribution ratios are each denoted as λ i (i is 1, …, q), λ i is arranged in an ascending (descending) order, and the first m principal components are selected such that:
the average wind element after the dimensionality reduction treatment can be represented as X'.
S3: and (3) carrying out cluster analysis on the average wind factor (for example, selecting an unsupervised learning method in machine learning to carry out cluster analysis on X', wherein the cluster method can preferably adopt K-means, fuzzy C cluster, hierarchical cluster and the like, such as cluster analysis of Ward method) to obtain d clusters as a plurality of weather types (each cluster result reflects different weather types).
S4: and training a plurality of weather types by adopting a gust model to obtain gust prediction models under different weather types. The method specifically comprises the following steps:
defining the gust coefficient G as:
wherein, UmIs mean wind, UgIs a gust of wind. Since G decreases with increasing U, the present embodiment preferably uses an exponential function for the fitting, namely:
G＝AUn
taking logarithm on two sides, then:
logG＝logA+nlogU
therefore, the values of A and n (A and n are parameters to be fitted) can be obtained by the least square method. Thus, a gust model can be obtained:
and respectively training the weather classifications corresponding to the d clusters to obtain gust prediction models under different weather classifications.
S5: and predicting the average wind of the area to be predicted in the future period of time (for example, predicting the average wind of 1-7 days in the future by a meteorological numerical mode), calculating the weather type of the prediction result (preferably, judging the weather type of 1-7 days in the future according to the Euclidean distance between the predicted wind field and the d clustering centers), and predicting the wind speed of the gust by adopting a corresponding gust prediction model of the weather type.
The present invention also provides a computer system, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the above-mentioned implementation methods when executing the computer program.
In conclusion, the method can be used for rapidly predicting the gust based on the average wind prediction result of the existing numerical mode. The wind drift prevention device can help line operation and maintenance personnel to deploy equipment for preventing wind drift tripping, flashover and the like in time in areas with large gust wind speed, and the safe and stable operation of a power grid is guaranteed.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
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