Power transmission line dynamic current-carrying capacity prediction method based on grid weather forecast

Abstract

The invention relates to a power transmission line dynamic current-carrying capacity prediction method based on grid weather forecast, and the method comprises the steps: selecting a calculation representative point on a power transmission line at an interval of 1 km, and selecting a weather grid point closest to the calculation representative point for pairing; using the weather forecast model to output weather numerical forecast weather grid point data, and mapping the weather grid point data into corresponding environment forecast values of the representative points of the power transmission line; and calculating the maximum current-carrying capacity of the whole power transmission line in the future 1-24 hours by using a heat balance equation. According to the invention, the environment temperature and wind speed forecast values of the whole power transmission line can be formed without increasing hardware environment monitoring stations; the meteorological grid point forecast value is mapped to a plurality of calculation representative points of the long-distance power transmission line, so that the calculation result can reflect the environmental condition of the whole line more accurately; and the maximum current-carrying capacity of the power transmission line in the specific time in the future is calculated by using the heat balance equation, so that the calculation accuracy and practicability are improved.

Description

Technical Field

[0001] The invention relates to the technical field of electric power systems, and in particular to a method for predicting dynamic current carrying capacity of power transmission lines based on grid meteorological forecasts. Background Art

[0002] Transmission lines are an important part of the power system. Their main function is to efficiently and safely transmit the electricity generated by power stations to the load center. The design and operation of transmission lines must take into account their thermal load limits, which refers to the maximum current that the conductor can safely transmit without exceeding the maximum allowable temperature of the conductor (usually 70°C), that is, the dynamic current carrying capacity. The dynamic current carrying capacity is affected by a variety of environmental factors, including ambient temperature, wind speed, wind direction, etc. These factors will cause changes in the convection and radiation heat dissipation capacity of the conductor, thereby affecting its current carrying capacity. Traditional transmission line current carrying capacity calculation methods are mainly based on empirical formulas and standards, such as GB50545-2010 and IEEE738-2006 standards. These methods usually assume that environmental conditions are stable and rely on idealized environmental parameters, using idealized points as representatives of the current ambient temperature and wind speed of the entire line. However, the actual transmission line corridor environment is diverse, and the line passes through different terrain and climate regions, resulting in significant changes in environmental conditions along the length of the line. In addition, existing calculation methods are often lagging and only applicable to extremely short time scales, and cannot provide predictions of future environmental changes, which limits their application in actual power dispatching.

[0003] In recent years, with the development of smart grid technology, higher requirements have been put forward for the dynamic current carrying capacity calculation of transmission lines. Power system operators need more accurate and real-time data to optimize grid operation and dispatching strategies and improve the economic benefits and reliability of the grid. In addition, the frequent occurrence of extreme climate events also poses challenges to the safe operation of transmission lines, requiring more effective prediction and response measures. Although some studies have tried to use real-time environmental monitoring data to improve the accuracy of current carrying capacity calculation, these methods have limitations. First, the transmission line corridors are usually long and the environmental conditions vary complexly. It is difficult to fully reflect the environmental conditions of the entire line by relying on data from a small number of monitoring points. Secondly, the acquisition cost of real-time monitoring data is high and difficult to achieve in some remote areas. Finally, even with real-time data, the existing calculation methods cannot provide sufficient foresight, and it is difficult for dispatchers to make the best dispatching decisions within a limited time.

[0004] Therefore, it is necessary to develop a new method that can provide accurate predictions of future environmental conditions of transmission lines without increasing the cost of additional hardware monitoring, and calculate the maximum current carrying capacity of the lines based on this, which will help power system operators to better plan and dispatch power grids, improve the utilization efficiency of transmission lines, and ensure the safe and stable operation of the power grid. Summary of the invention

[0005] In order to solve the problem that the existing technology does not take into account the environmental diversity of actual lines, it is necessary to add micro-meteorological online monitoring devices on the lines, which consumes manpower and material resources. The purpose of the present invention is to provide a method for predicting the dynamic current carrying capacity of transmission lines based on grid meteorological forecasts, which can form the ambient temperature and wind speed forecast values ​​of the entire transmission line without adding hardware environmental monitoring stations, provide more comprehensive and forward-looking environmental data for the transmission lines, and improve the accuracy and practicality of calculations.

[0006] To achieve the above object, the present invention adopts the following technical solution: a method for predicting the dynamic current carrying capacity of a transmission line based on grid weather forecast, the method comprising the following steps in order:

[0007] (1) Select a representative calculation point every 1 km on the transmission line, and select the meteorological grid point closest to the representative calculation point for pairing;

[0008] (2) using a weather forecast model to output weather grid point data for numerical weather forecasting, wherein the weather grid point data refers to the ambient temperature and wind speed in the area along the transmission line within the next 1 to 24 hours;

[0009] (3) Mapping the meteorological grid point data to the environmental forecast values ​​of the corresponding transmission line representative points;

[0010] (4) Based on the environmental forecast values, use the heat balance equation to calculate the maximum current carrying capacity of the entire transmission line within the next 1 to 24 hours.

[0011] The step (1) specifically refers to: selecting a representative calculation point every 1 km on the transmission line, obtaining the coordinate value of the representative calculation point, and in addition, obtaining the coordinate values ​​of all meteorological grid points, calculating the distance between each meteorological grid point and the representative calculation point, selecting the meteorological grid point closest to the representative calculation point for pairing, and each representative calculation point is paired with a meteorological grid point.

[0012] The step (4) specifically refers to:

[0013] The heat balance equation is based on the following formula:

[0014] W R +W F =W S +I 2 R T

[0015] Where W R is the radiation heat dissipation, W F For convection cooling, W S As the sunlight absorbs heat, R Tis the AC resistance of the conductor at the working temperature; after the above formula is transformed, the calculation formula for the current carrying capacity is obtained as follows:

[0016]

[0017] W R , W F , W S The calculation formulas are:

[0018] W R =πDεS[(T P +273) 4 -(T A +273) 4 ]

[0019]

[0020] W s =αJD

[0021] Where D is the wire diameter; ε is the wire surface radiation heat dissipation coefficient; S is the Stefan-Boltzmann constant, which is 5.67*10 -8 W / m 2 ; T P is the allowable surface temperature of the conductor, which is 70°C; T A is the ambient temperature; v is the wind speed perpendicular to the conductor; α is the heat absorption coefficient of the conductor surface; J is the sunlight intensity received by the conductor;

[0022] Substitute the environmental forecast value of each calculated representative point at the future time t into the heat balance equation, 1≤t≤24 and t is an integer, and obtain the maximum current-carrying capacity of each calculated representative point at the time t. Compare the maximum current-carrying capacity calculated by all the calculated representative points, and select the smallest maximum current-carrying capacity value as the maximum current-carrying capacity of the entire transmission line at the time t, so as to obtain the maximum current-carrying capacity sequence of the entire transmission line in the future 1 to 24 hours.

[0023] It can be seen from the above technical scheme that the beneficial effects of the present invention are: first, the present invention utilizes grid meteorological numerical forecasting technology instead of relying solely on current measured values, and can form the ambient temperature and wind speed forecast values ​​of the entire transmission line without adding hardware environment monitoring stations, thereby providing more comprehensive and forward-looking environmental data for the transmission line; second, the present invention maps the meteorological grid point forecast values ​​to multiple representative calculation points of the long-distance transmission line, so that the calculation results can more accurately reflect the environmental conditions of the entire line; third, the present invention combines meteorological forecast data and uses the heat balance equation to calculate the maximum current carrying capacity of the transmission line within a specific time in the future, thereby improving the accuracy and practicality of the calculation; fourth, the calculation results provide the maximum current carrying capacity forecast value of the line within the next 1 to 24 hours, with a smaller prediction time granularity and a longer prediction period, providing sufficient time for power grid dispatchers to complete the optimization scheduling plan and safety verification; fifth, the present invention is applicable to large-scale cross-regional power grids, which helps to achieve optimized scheduling of power grids and improve the economic benefits of power grids. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic diagram of the meteorological grid forecast and meteorological grid point information in the present invention;

[0025] Figure 2 A schematic diagram of the mapping and pairing of the transmission line calculation representative points and the meteorological grid points in the present invention;

[0026] Figure 3 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0027] like Figure 3 As shown, a method for predicting dynamic current carrying capacity of a transmission line based on grid weather forecast comprises the following steps in order:

[0028] (1) Select a representative calculation point every 1 km on the transmission line, and select the meteorological grid point closest to the representative calculation point for pairing;

[0029] (2) using a weather forecast model to output weather grid point data for numerical weather forecasting, wherein the weather grid point data refers to the ambient temperature and wind speed in the area along the transmission line within the next 1 to 24 hours;

[0030] (3) Mapping the meteorological grid point data to the environmental forecast values ​​of the corresponding transmission line representative points;

[0031] (4) Based on the environmental forecast value, the maximum current carrying capacity of the entire transmission line in the next 1 to 24 hours is calculated using the heat balance equation. The method for calculating the current carrying capacity is based on the concept of thermal balance, that is, when the conductor reaches its maximum safe operating temperature, the heat generated inside the conductor and the heat dissipated to the outside are in equilibrium. In this state, the maximum current that the conductor can withstand is its rated current carrying capacity. In actual operation, the reasons for the heat generated by the conductor include the Joule heating effect when the current passes through the conductor resistance and solar radiation, while the heat is dissipated mainly through radiation and convection.

[0032] The step (1) specifically refers to: selecting a calculation representative point every 1 km on the transmission line, obtaining the coordinate value of the calculation representative point, and obtaining the coordinate values ​​of all meteorological grid points, calculating the distance between each meteorological grid point and the calculation representative point, and selecting the meteorological grid point closest to the calculation representative point for pairing. Each calculation representative point is paired with a meteorological grid point. The pairing mapping is shown in the figure below: Figure 2 shown.

[0033] The meteorological department first releases a grid meteorological numerical forecast for the area where the transmission line is located. Meteorological grid forecast is a method that divides the forecast area into a number of meteorological grid points and provides predicted values ​​of meteorological parameters at each meteorological grid point. This forecasting method can provide spatially continuous and detailed meteorological information, which is especially important for fields that require precise geographic location meteorological data. Meteorological grid forecasts can provide forecast products with different spatial resolutions, such as grid spacings of 1 km, 5 km, and 10 km. In the present invention, these numerical forecast products are provided with a meteorological grid point accuracy of 1 km×1 km, including meteorological parameters in the next 1 to 24 hours, such as temperature, wind speed, etc. The schematic diagram of the meteorological numerical forecast grid and forecast information is shown in the figure. Figure 1 shown.

[0034] The step (4) specifically refers to:

[0035] The heat balance equation is based on the following formula:

[0036] W R +W F =W S +I 2 R T

[0037] Where W R is the radiation heat dissipation, W F For convection cooling, W S As the sunlight absorbs heat, R T is the AC resistance of the conductor at the working temperature; after the above formula is transformed, the calculation formula for the current carrying capacity is obtained as follows:

[0038]

[0039] W R , W F , W S The calculation formulas are:

[0040] W R =πDεS[(T P +273) 4 -(T A +273) 4 ]

[0041]

[0042] W s =αJD

[0043] Where D is the conductor diameter; ε is the conductor surface radiation heat dissipation coefficient, which is 0.23~0.43 for new transmission lines and 0.9~0.95 for old transmission lines. Here, new transmission lines refer to those with a short service time, and old transmission lines refer to those with a long service time; S is the Stefan-Boltzmann constant, which is 5.67*10 -8 W / m 2 ; T P is the allowable surface temperature of the conductor, which is 70°C; T A is the ambient temperature; v is the wind speed perpendicular to the conductor; α is the heat absorption coefficient of the conductor surface, which is 0.35-0.46 for new conductors and 0.9-0.95 for old conductors; J is the sunlight intensity on the conductor, which is usually 1000W / m on sunny days. 2 .

[0044] Substitute the environmental forecast value of each calculated representative point at the future time t into the heat balance equation, 1≤t≤24 and t is an integer, and obtain the maximum current-carrying capacity of each calculated representative point at the time t. Compare the maximum current-carrying capacity calculated by all the calculated representative points, and select the smallest maximum current-carrying capacity value as the maximum current-carrying capacity of the entire transmission line at the time t, so as to obtain the maximum current-carrying capacity sequence of the entire transmission line in the future 1 to 24 hours.

[0045] like Figure 3 As shown, the specific implementation process of the transmission line current carrying capacity prediction of the present invention is as follows:

[0046] (1) Select the location coordinates of a tower every 1 km on the line as the representative calculation point, with a total of N representative calculation points;

[0047] (2) Input the location coordinates of the meteorological grid points in the entire region;

[0048] (3) Pair each tower representative point with the nearest meteorological grid point;

[0049] (4) Select the forecast time point t = 1h;

[0050] (5) Input the weather forecast values ​​of the meteorological grid points in the entire region at time t;

[0051] (6) Using the meteorological forecast values ​​of the paired meteorological grid points as the environmental forecast values ​​for the representative points;

[0052] (7) Obtain the environmental forecast value of the representative point of the entire line calculation at time t;

[0053] (8) Calculate the dynamic current carrying capacity of the representative points of the entire line based on the environmental forecast value and heat balance equation of the representative points;

[0054] (9) Take the minimum current carrying capacity among the N calculated representative points of the entire line as the maximum current carrying capacity of the line at time t and store it;

[0055] (10) Determine whether the forecast time point t is greater than 24h. If t is greater than 24, end the process and output the line maximum current carrying capacity sequence from 1 to 24h; if t is less than or equal to 24, set t=t+1 and jump to step (5).

[0056] With the continuous update of new meteorological data, the predicted current carrying capacity of the transmission line can be updated in real time. Dispatchers can adjust the dispatching strategy based on the latest forecast data to cope with the impact of environmental changes on the operation of the power grid.

[0057] For large-scale cross-regional power grids, the present invention can be extended to the entire power grid to provide comprehensive data support for the optimization and dispatching of the power grid. By integrating meteorological data and transmission line information from multiple regions, the dynamic current carrying capacity of the entire power grid can be predicted and monitored.

[0058] In summary, the present invention can effectively improve the prediction accuracy of the dynamic current carrying capacity of the transmission line and provide a scientific basis for the optimal dispatch of the power system. In addition, the present invention also has a smaller prediction time granularity and a longer forecast period, is suitable for large-scale cross-regional power grids, and has significant economic and social benefits.

Claims

1. A method for predicting the dynamic current carrying capacity of a power transmission line based on grid weather forecast, characterized in that: The method comprises the following steps in order: (1) Select a representative calculation point every 1 km on the transmission line, and select the meteorological grid point closest to the representative calculation point for pairing; (2) using a weather forecast model to output weather grid point data for numerical weather forecasting, wherein the weather grid point data refers to the ambient temperature and wind speed in the area along the transmission line within the next 1 to 24 hours; (3) Mapping the meteorological grid point data to the environmental forecast values ​​of the corresponding transmission line representative points; (4) Based on the environmental forecast values, use the heat balance equation to calculate the maximum current carrying capacity of the entire transmission line within the next 1 to 24 hours.

2. The method for predicting the dynamic current carrying capacity of a power transmission line based on grid weather forecast according to claim 1 is characterized in that: The step (1) specifically refers to: selecting a representative calculation point every 1 km on the transmission line, obtaining the coordinate value of the representative calculation point, and in addition, obtaining the coordinate values ​​of all meteorological grid points, calculating the distance between each meteorological grid point and the representative calculation point, selecting the meteorological grid point closest to the representative calculation point for pairing, and each representative calculation point is paired with a meteorological grid point.

3. The method for predicting the dynamic current carrying capacity of a power transmission line based on grid weather forecast according to claim 1 is characterized in that: The step (4) specifically refers to: The heat balance equation is based on the following formula: W R +W F =W S +I 2 R T Where W R is the radiation heat dissipation, W F For convection cooling, W S As the sunlight absorbs heat, R T is the AC resistance of the wire at the operating temperature; After the above formula is transformed, the calculation formula for the current carrying capacity is obtained as follows: W R , W F , W S The calculation formulas are: W R =πDεS[(T P +273) 4 -(T A +273) 4 ] IN s =αJD Where D is the wire diameter; ε is the wire surface radiation heat dissipation coefficient; S is the Stefan-Boltzmann constant, which is 5.67*10 -8 W / m 2 ; T P is the allowable surface temperature of the conductor, which is 70°C; T A is the ambient temperature; v is the wind speed perpendicular to the conductor; α is the heat absorption coefficient of the conductor surface; J is the sunlight intensity received by the conductor; Substitute the environmental forecast value of each calculated representative point at the future time t into the heat balance equation, 1≤t≤24 and t is an integer, and obtain the maximum current-carrying capacity of each calculated representative point at the time t. Compare the maximum current-carrying capacity calculated by all the calculated representative points, and select the smallest maximum current-carrying capacity value as the maximum current-carrying capacity of the entire transmission line at the time t, so as to obtain the maximum current-carrying capacity sequence of the entire transmission line in the future 1 to 24 hours.

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