Power transmission line real-time capacity increasing adjusting method and system based on multi-field coupling

Abstract

The invention relates to the technical field of power transmission line control, in particular to a power transmission line real-time capacity-increasing adjusting method and system based on multi-field coupling, and the method comprises the steps: collecting line parameters for a to-be-adjusted line, and calculating AC resistance, conductor sag and line current-carrying capacity as modeling evaluation parameters; performing risk assessment on the to-be-adjusted line to obtain risk assessment parameters; and determining and executing a hierarchical control strategy according to the risk assessment parameters. Aiming at the problem that the line capacity expansion method in the prior art is implemented only according to a single variable and is low in accuracy, a to-be-adjusted line is comprehensively calculated from three angles of an electromagnetic field, a temperature field and a mechanical field to obtain alternating-current resistance, conductor sag and line current-carrying capacity as modeling evaluation parameters; and then multi-field coupling dynamic risk assessment is carried out on the to-be-adjusted line according to the modeling assessment parameters, so that a more accurate risk assessment process is realized, a corresponding risk level is determined and related processing is carried out, and the assessment accuracy is improved.

Description

Technical Field

[0001] This invention relates to the field of power transmission line control technology, specifically to a method and system for real-time capacity expansion regulation of power transmission lines based on multi-field coupling. Background Technology

[0002] Transmission control refers to the process of allocating various parameters according to the operating conditions of the transmission lines in a high-voltage transmission system. Since transmission line capacity is affected by various environmental parameters—for example, higher ambient temperatures narrow the permissible operating temperature range and reduce usable line capacity—incorrect estimation of line capacity can lead to a significant reduction in economic efficiency. Therefore, accurate estimation and timely control of various parameters during transmission are essential. The stable operation of existing power systems relies on the precise control of transmission line capacity by power system dispatchers. However, traditional power system operation methods typically use transmission line thermal ratings based on static environmental conditions, which do not fully utilize the capacity margins in the actual operating environment. With the digital development of power systems, more efficient utilization of existing transmission network resources has become an urgent need. In recent years, Dynamic Line Rating (DLR) technology has gained widespread attention because it can adjust according to real-time environmental conditions, ensuring that transmission lines operate close to their maximum limits. In particular, by combining regional meteorological conditions, DLR technology has significant advantages in improving transmission line operating efficiency and ensuring safe and stable operation.

[0003] For example, patent document CN202310371831.9 discloses a method for increasing the capacity of a power transmission line. A DC transmission system is installed between two AC systems to increase the transmission line capacity. The DC transmission system includes a first converter station connected to a first AC system, a second converter station connected to a second AC system, and the transmission line requiring capacity increase. The first and second converter stations are connected through the transmission line. A three-pole structure can be achieved with a single converter, effectively reducing the number of converters used and lowering overall costs while also reducing the difficulty of coordination and control, thus promoting the application of AC-to-DC conversion technology.

[0004] For example, patent document CN201410487200.4 discloses a dynamic capacity expansion monitoring system and method for transmission lines. This system monitors transmission lines in real time, acquires monitoring data to calculate the safe operating current carrying capacity of the transmission lines, and determines whether the transmission lines can be expanded based on the safe operating current carrying capacity. If so, it extracts preset capacity expansion information and expands the capacity of the transmission lines accordingly. During capacity expansion, the system calculates the conductor sag data of the transmission lines based on the monitoring data and sends the monitoring data and conductor sag data to the application terminal for display. Because it allows for real-time data acquisition and monitoring of transmission lines, and real-time monitoring of conductor sag data during capacity expansion, it comprehensively considers the impact of various important factors on the safe operation of transmission lines, thus improving safety.

[0005] However, the inventors discovered that existing dynamic capacity expansion technologies are mostly based on a single thermodynamic model, estimating current carrying capacity through simplified methods such as wind speed and preset environmental parameters, which makes it difficult to accurately reflect the true state of the conductor under the coupling effect of multiple physical fields. Summary of the Invention

[0006] To address the aforementioned problems in the existing technology, a real-time capacity expansion regulation method for transmission lines based on multi-field coupling is provided.

[0007] On the other hand, a real-time capacity expansion and regulation system for transmission lines is also provided for implementing the above methods.

[0008] The specific technical solution is as follows:

[0009] A method for real-time capacity expansion regulation of transmission lines based on multi-field coupling, comprising:

[0010] Step S1: Collect line parameters for the line to be adjusted and calculate AC resistance, conductor sag and line current carrying capacity as modeling and evaluation parameters.

[0011] Step S2: Based on the modeling and evaluation parameters, perform a risk assessment on the line to be adjusted to obtain risk assessment parameters;

[0012] Step S3: Determine and implement the graded control strategy according to the risk assessment parameters.

[0013] On the other hand, in step S1, the method for generating the modeling evaluation parameters includes:

[0014] First, the AC resistance and the conductor sag are calculated based on the line parameters.

[0015] The method for generating the AC resistance includes:

[0016] R ac =R 20 [1+α20 (T avg -20)](1+k s )

[0017] In the formula: R 20 The DC resistance value of the circuit to be adjusted at an ambient temperature of 20°C is expressed in Ω / m.

[0018] α 20 The temperature coefficient of the conductor material of the circuit to be adjusted is given when the ambient temperature is 20°C.

[0019] T avg The average conductor temperature of the circuit to be adjusted is currently [value missing].

[0020] k s The skin effect coefficient of the circuit to be adjusted;

[0021] The method for generating the conductor sag includes:

[0022]

[0023] In the formula:

[0024] f (m2y) The sag of the conductor;

[0025] σ 01 The stress at the lowest point of the sag of the line to be adjusted in the initial state;

[0026] σ 02 The stress at the lowest point of the sag of the line to be adjusted in the current state;

[0027] γ1 is the weight-wind pressure ratio of the line to be adjusted in the initial state;

[0028] γ2 is the weight-wind pressure ratio of the line to be adjusted under the current condition;

[0029] T1 is the conductor temperature of the circuit to be adjusted in the initial state;

[0030] T2 is the conductor temperature of the circuit to be adjusted in the current state;

[0031] η1 is the wind deflection angle of the line to be adjusted in the initial state;

[0032] η2 is the wind deflection angle of the line to be adjusted in the current state;

[0033] l represents the span between the two ends of the line to be adjusted;

[0034] β is the elevation difference angle between the two ends of the line to be adjusted;

[0035] α is the coefficient of thermal expansion of the circuit to be adjusted;

[0036] E is the elastic coefficient of the circuit to be adjusted;

[0037] Then, the line current carrying capacity is generated based on the line parameters and the AC resistance;

[0038] The method for generating the line carrying capacity includes:

[0039] I 2 R+Q s =Q c +Q r

[0040] In the formula: I is the current carrying capacity of the conductor;

[0041] R is the AC resistance;

[0042] Q s The solar heat absorption per unit length of the line to be adjusted under the current state;

[0043] Q c For convective heat dissipation per unit length of the circuit to be adjusted in the current state;

[0044] Q r This refers to the radiative heat dissipation per unit length of the circuit to be adjusted in the current state.

[0045] On the other hand, step S2 includes:

[0046] Step S21: Quantify the modeling and evaluation parameters to obtain the quantified parameters;

[0047] Step S22: Compare each of the quantification parameters with the corresponding risk interval to obtain the parameter comparison results;

[0048] Step S23: Generate the risk assessment parameters based on the parameter comparison results.

[0049] On the other hand, step S3 includes:

[0050] Step S31: Match the risk assessment parameters with the preset level rules to determine whether capacity expansion is possible;

[0051] If so, proceed to step S32;

[0052] If not, proceed to step S33;

[0053] Step S32: Expand the capacity of the line to be adjusted according to the modeling and evaluation parameters, and configure the corresponding derating rules;

[0054] Step S33: Reduce the capacity of the line to be adjusted according to the modeling and evaluation parameters and set the monitoring method.

[0055] On the other hand, step S32 includes:

[0056] Step S321: Generate dynamic capacity limits based on the modeling and evaluation parameters;

[0057] Step S322: Configure monitoring rules according to the risk assessment parameters;

[0058] Step S323: Construct the monitoring method according to the modeling and evaluation parameters.

[0059] A real-time capacity expansion and regulation system for transmission lines based on multi-field coupling is used to implement the above-mentioned real-time capacity expansion and regulation method for transmission lines.

[0060] The real-time capacity expansion and adjustment system for transmission lines includes:

[0061] The modeling module collects line parameters for the line to be adjusted and calculates AC resistance, conductor sag and line current carrying capacity as modeling and evaluation parameters.

[0062] An evaluation module, which is connected to the modeling module;

[0063] The evaluation module performs a risk assessment on the line to be adjusted based on the modeling evaluation parameters to obtain risk assessment parameters.

[0064] A control module, which is connected to the evaluation module;

[0065] The control module determines and executes a tiered control strategy based on the risk assessment parameters.

[0066] On the other hand, the modeling module includes:

[0067] A conductor sag calculation module, which calculates the conductor sag based on the line parameters;

[0068] A resistance calculation module, which calculates the AC resistance based on the line parameters;

[0069] A current carrying capacity calculation module, wherein the current carrying capacity calculation module is connected to the resistance calculation module;

[0070] The current carrying capacity calculation module generates the line current carrying capacity based on the line parameters and the AC resistance.

[0071] On the other hand, the modeling module includes:

[0072] A quantization module, which performs quantization parameter calculations on the modeling and evaluation parameters to obtain quantization parameters;

[0073] A comparison module, which is connected to the quantization module;

[0074] The comparison module compares each quantification parameter with its corresponding risk range to obtain the parameter comparison result.

[0075] A risk assessment module is connected to the comparison module;

[0076] The risk assessment module generates the risk assessment parameters based on the comparison results of the parameters.

[0077] On the other hand, the control module includes:

[0078] A matching module, which matches the risk assessment parameters with preset level rules to determine whether expansion is possible;

[0079] A first adjustment module, which is connected to the matching module;

[0080] When expansion is possible, the first adjustment module expands the capacity of the line to be adjusted according to the modeling and evaluation parameters, and configures the corresponding derating rules.

[0081] A second adjustment module is connected to the first adjustment module;

[0082] The second adjustment module reduces the capacity of the line to be adjusted according to the modeling and evaluation parameters and sets the monitoring mode.

[0083] On the other hand, the second adjustment module includes:

[0084] A limit configuration module, which generates a dynamic capacity limit based on the modeling and evaluation parameters;

[0085] The rule configuration module configures monitoring rules according to the risk assessment parameters;

[0086] The monitoring configuration module constructs the monitoring method according to the modeling and evaluation parameters.

[0087] The above technical solution has the following advantages or beneficial effects:

[0088] To address the issue of low accuracy in existing line expansion methods that rely on a single variable, this solution employs a comprehensive calculation approach, considering electromagnetic, temperature, and mechanical fields to obtain AC resistance, conductor sag, and line current carrying capacity as modeling and evaluation parameters. Then, a dynamic risk assessment involving multi-field coupling is performed on these parameters, resulting in a more accurate risk assessment process. This process determines the corresponding risk level and performs relevant processing, thereby improving the accuracy of the assessment. Attached Figure Description

[0089] Embodiments of the invention will be described more fully with reference to the accompanying drawings. However, the drawings are for illustration and explanation only and do not constitute a limitation on the scope of the invention.

[0090] Figure 1 This is an overall schematic diagram of an embodiment of the present invention;

[0091] Figure 2 This is a schematic diagram of step S2 in an embodiment of the present invention;

[0092] Figure 3 This is a schematic diagram of step S3 in an embodiment of the present invention;

[0093] Figure 4 This is a schematic diagram of step S32 in an embodiment of the present invention;

[0094] Figure 5 This is a schematic diagram of the system in an embodiment of the present invention;

[0095] Figure 6 This is a schematic diagram of the modeling module in an embodiment of the present invention;

[0096] Figure 7 This is a schematic diagram of the evaluation module in an embodiment of the present invention;

[0097] Figure 8 This is a schematic diagram of the control module in an embodiment of the present invention;

[0098] Figure 9 This is a schematic diagram of the second adjustment module in an embodiment of the present invention. Detailed Implementation

[0099] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0100] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0101] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but this is not intended to limit the scope of the invention.

[0102] This invention includes:

[0103] A method for real-time capacity expansion regulation of transmission lines based on multi-field coupling, such as... Figure 1 As shown, it includes:

[0104] Step S1: Collect line parameters for the line to be adjusted and calculate AC resistance, conductor sag and line current carrying capacity as modeling and evaluation parameters.

[0105] Step S2: Based on the modeling and evaluation parameters, conduct a risk assessment of the line to be regulated to obtain the risk assessment parameters;

[0106] Step S3: Determine and implement the tiered control strategy based on the risk assessment parameters.

[0107] Specifically, addressing the issue of low accuracy in existing line expansion methods that rely on a single variable, this solution performs comprehensive calculations from three perspectives—electromagnetic field, temperature field, and mechanical field—to obtain AC resistance, conductor sag, and line current carrying capacity as modeling and evaluation parameters. Then, based on these parameters, a dynamic risk assessment of the line under adjustment is conducted using multi-field coupling, thereby achieving a more accurate risk assessment process, determining the corresponding risk level, and performing relevant processing, thus improving the accuracy of the assessment.

[0108] During implementation, multi-parameter intelligent sensing terminals are first deployed on transmission lines and towers, integrating meteorological monitoring units, distributed contact temperature sensors, conductor deformation monitoring modules, alternating magnetic field monitoring units, and edge computing nodes to monitor in real time information such as conductor operating current, conductor temperature, ambient temperature, solar radiation intensity, and wind speed. At the same time, these signals are collected and uploaded to the system's main station via 5G or 4G LTE networks.

[0109] Then, the backend system acquires multi-dimensional data such as transmission line current, temperature, and environmental parameters in real time. Based on a digital twin engine, it constructs a dynamic coupling model of electromagnetic field, temperature field, and stress field, and achieves real-time operating condition analysis through multi-resolution collaborative calculation. Under the premise of ensuring line life and operational safety, the system provides dynamic thermal stability limit values ​​and safe operating time predictions for daily power grid dispatch management, operation mode optimization, and emergency plan revision.

[0110] In one embodiment, the method for generating modeling evaluation parameters in step S1 includes:

[0111] First, the AC resistance and conductor sag are calculated based on the line parameters.

[0112] Methods for generating AC resistance include:

[0113] R ac =R 20 [1+α 20 (T avg -20)](1+k s )

[0114] In the formula: R 20 The value of the DC resistance of the circuit to be adjusted is given at an ambient temperature of 20℃, in Ω / m.

[0115] α 20 The temperature coefficient of the conductor material of the circuit to be adjusted at an ambient temperature of 20℃;

[0116] T avg The average conductor temperature of the circuit to be adjusted is currently being measured.

[0117] k s The skin effect coefficient of the circuit to be adjusted;

[0118] Methods for generating conductor sag include:

[0119]

[0120] In the formula:

[0121] f (m2y) For conductor sag;

[0122] σ 01 The stress at the lowest point of the sag of the line to be adjusted in the initial state;

[0123] σ 02 The stress at the lowest point of the sag of the line to be adjusted under the current condition;

[0124] γ1 is the weight-wind pressure ratio of the line to be adjusted in the initial state;

[0125] γ2 is the self-weight-wind pressure ratio of the line to be adjusted under the current condition;

[0126] T1 represents the initial conductor temperature of the circuit to be adjusted.

[0127] T2 represents the conductor temperature of the circuit to be adjusted in the current state.

[0128] η1 is the wind deflection angle of the line to be adjusted in the initial state;

[0129] η2 is the wind deflection angle of the line to be adjusted under the current condition;

[0130] l represents the span between the two ends of the line to be adjusted;

[0131] β is the elevation difference angle between the two ends of the line to be adjusted;

[0132] α is the coefficient of thermal expansion of the circuit to be adjusted;

[0133] E is the elasticity coefficient of the line to be adjusted;

[0134] Then, the line current carrying capacity is generated based on the line parameters and AC resistance; the methods for generating the line current carrying capacity include:

[0135] I 2 R+Q s =Q c +Q r

[0136] In the formula: I is the current carrying capacity of the conductor;

[0137] R is the AC resistance;

[0138] Q s The solar heat absorption per unit length of the line to be adjusted under the current condition;

[0139] Q c For convective heat dissipation per unit length of the circuit to be adjusted in the current state;

[0140] Q r This refers to the radiative heat dissipation per unit length of the circuit to be adjusted under the current condition.

[0141] Specifically, in view of the problem that the existing line expansion methods only rely on a single variable and have low accuracy, this embodiment performs comprehensive calculations from three perspectives—electromagnetic field, temperature field, and mechanical field—for the line to be adjusted.

[0142] Specifically, regarding electromagnetic fields, the main consideration is the change in AC resistance caused by the temperature change of the conductor in the online state. Therefore, the conductor temperature coefficient is combined to measure the AC resistance of the conductor at a specific temperature. At the same time, considering the skin effect of AC current, a skin effect coefficient is also added to achieve accurate measurement.

[0143] For mechanical fields, the main focus is on measuring the changes in conductor sag under the influence of temperature and wind deflection when the conductors are overhead. Specifically, for the line to be adjusted, calculations are performed segment by segment based on the line between overhead towers.

[0144] For each segment, the span between the two ends, the elevation difference angle between the two ends, the coefficient of thermal expansion, and the elastic coefficient were pre-collected. The initial state of the conductor was determined by the temperature and stress at the end of the initial construction phase, while the parameters measured in real-time during the evaluation phase were used as the parameters for the current state. After calculating the stress at the lowest point of the sag of the line to be adjusted under the current state using the above equations, the conductor sag was then calculated to determine whether the conductor's condition was normal.

[0145] For the temperature field, the AC resistance is first calculated, and then the solar heat absorption, convection heat dissipation and radiation heat dissipation per unit length are collected simultaneously. When the conductor temperature of the circuit to be regulated tends to a steady state, the corresponding AC resistance is calculated.

[0146] Based on the calculation of the above parameters, a better characterization of the circuit to be adjusted was achieved.

[0147] In one embodiment, such as Figure 2 As shown, step S2 includes:

[0148] Step S21: Quantify the modeling and evaluation parameters to obtain the quantified parameters;

[0149] Step S22: Compare each quantification parameter with its corresponding risk interval to obtain the parameter comparison results;

[0150] Step S23: Generate risk assessment parameters based on the parameter comparison results.

[0151] Specifically, to achieve better risk assessment results, in this embodiment, each modeling and assessment parameter is first quantified to obtain a quantified parameter, including quantifying the conductor temperature (Tc) based on the temperature field, and calculating the safe time (t) in combination with the conductor temperature (Tc). safe The real-time current carrying capacity ratio (IR) is calculated by combining electromagnetic field, which is the ratio of real-time current to rated allowable current carrying capacity. At the same time, the sag margin (SM) is further calculated based on the conductor sag.

[0152] Then, each quantification parameter is compared with its corresponding risk range to obtain the parameter comparison results.

[0153] For example, under a pre-defined low-risk condition, Tc≤70℃, t safe >60 minutes, SM≥20%, and all indicators meet the safety threshold;

[0154] Under medium-risk conditions, any indicator that exceeds the low-risk threshold but does not reach the high-risk critical value includes 70℃ < Tc < 80℃ and 30 minutes ≤ t safe ≤60 minutes, 125%≤IR≤155%, 10%≤SM≤20%, or both indicators are in the medium risk range;

[0155] Under high-risk conditions, any indicator reaching a critical threshold, including Tc > 80℃, t safe <30 minutes, IR>155%, SM<10%, or two medium-risk indicators accompanied by Tc>75℃ or SM<15%.

[0156] After comparison, corresponding risk assessment parameters are generated based on the comparison results of the parameters that triggered the exceedance.

[0157] In one embodiment, such as Figure 3 As shown, step S3 includes:

[0158] Step S31: Match the risk assessment parameters with the preset level rules to determine whether capacity expansion is possible;

[0159] If so, proceed to step S32;

[0160] If not, proceed to step S33;

[0161] Step S32: Expand the capacity of the line to be adjusted according to the modeling and evaluation parameters, and configure the corresponding derating rules;

[0162] Step S33: Reduce the capacity of the line to be regulated according to the modeling and evaluation parameters and set the monitoring method.

[0163] Specifically, in order to achieve a better evaluation process, in this embodiment, after the risk assessment parameters are constructed, they are matched with preset level rules to determine whether expansion is possible.

[0164] Specifically, different rules are configured according to different risk levels. Expansion can only be carried out under low-risk conditions, while traffic should be limited under medium- and high-risk conditions. Medium and high risks correspond to different levels of traffic limitation and handling methods.

[0165] For example, in low-risk situations, the system prioritizes economy, allowing the load capacity to be increased to 90% of the dynamic limit, extending the monitoring cycle to 15 minutes, and generating a capacity increase suggestion curve for the next 4 hours. At the same time, it sets a mandatory load reduction rule when the ambient temperature exceeds 35°C or the wind speed is below 1 m / s.

[0166] In the case of medium risk, the load capacity is immediately limited to 85% of the dynamic limit. The parameters are checked every 5 minutes and real-time sag monitoring is started. If the sag margin is less than 15%, the load is reduced to 80%. At the same time, alternative solutions of maintaining the current load capacity or reducing the load for safety are provided.

[0167] In cases of high risk, the load will be forcibly reduced to 70% of the dynamic limit or 90% of the static limit, and load transfer to backup lines, manual on-site inspection, or cooling measures will be implemented. A red alert will also be sent to the dispatch terminal in real time.

[0168] After all strategies are executed, dynamic parameter calibration and historical case matching optimization are automatically triggered. Through closed-loop feedback, the model accuracy and response efficiency are continuously improved, ensuring the safe capacity expansion of transmission lines under complex operating conditions.

[0169] In one embodiment, such as Figure 4 As shown, step S32 includes:

[0170] Step S321: Generate dynamic capacity limits based on modeling and evaluation parameters;

[0171] Step S322: Configure monitoring rules according to risk assessment parameters;

[0172] Step S323: Construct a monitoring method based on the modeling and evaluation parameters.

[0173] A real-time capacity expansion and regulation system for transmission lines based on multi-field coupling is used to implement the above-mentioned real-time capacity expansion and regulation method for transmission lines.

[0174] like Figure 5 As shown, the real-time capacity expansion and regulation system for transmission lines includes:

[0175] Modeling Module 1 collects line parameters for the line to be adjusted and calculates AC resistance, conductor sag and line current carrying capacity as modeling and evaluation parameters.

[0176] Evaluation module 2 is connected to modeling module 1;

[0177] Evaluation module 2 performs a risk assessment on the line to be regulated based on the modeling evaluation parameters to obtain risk assessment parameters;

[0178] Control module 3 is connected to evaluation module 2;

[0179] Control module 3 determines and executes a tiered control strategy based on risk assessment parameters.

[0180] Specifically, addressing the issue of low accuracy in existing line expansion methods that rely on a single variable, this solution performs comprehensive calculations from three perspectives—electromagnetic field, temperature field, and mechanical field—to obtain AC resistance, conductor sag, and line current carrying capacity as modeling and evaluation parameters. Then, based on these parameters, a dynamic risk assessment of the line under adjustment is conducted using multi-field coupling, thereby achieving a more accurate risk assessment process, determining the corresponding risk level, and performing relevant processing, thus improving the accuracy of the assessment.

[0181] In one embodiment, such as Figure 6 As shown, modeling module 1 includes:

[0182] Conductor sag calculation module 11 calculates conductor sag based on line parameters;

[0183] Resistance calculation module 12 calculates AC resistance based on line parameters;

[0184] Current carrying capacity calculation module 13 is connected to resistance calculation module 12;

[0185] The current carrying capacity calculation module 13 generates the line current carrying capacity based on line parameters and AC resistance. Specifically, to achieve better risk assessment results, in this embodiment, each modeling and assessment parameter is first quantified to obtain quantified parameters, including quantifying the conductor temperature (Tc) based on the temperature field, and calculating the safe time (t) in combination with the conductor temperature (Tc). safe The real-time current carrying capacity ratio (IR) is calculated by combining electromagnetic field, which is the ratio of real-time current to rated allowable current carrying capacity. At the same time, the sag margin (SM) is further calculated based on the conductor sag.

[0186] Then, each quantification parameter is compared with its corresponding risk range to obtain the parameter comparison results.

[0187] In one embodiment, such as Figure 7 As shown, evaluation module 2 includes:

[0188] Quantization module 21 calculates the quantization parameters of the modeling evaluation parameters to obtain the quantization parameters;

[0189] Comparison module 22, which is connected to quantization module 21;

[0190] The comparison module 22 compares each quantified parameter with its corresponding risk range to obtain the parameter comparison results;

[0191] Risk assessment module 23, which is connected to comparison module 22;

[0192] The risk assessment module 23 generates risk assessment parameters based on the parameter comparison results.

[0193] Specifically, to achieve better risk assessment results, in this embodiment, each modeling and assessment parameter is first quantified to obtain a quantified parameter, including quantifying the conductor temperature (Tc) based on the temperature field, and calculating the safe time (t) in combination with the conductor temperature (Tc). safe The real-time current carrying capacity ratio (IR) is calculated by combining electromagnetic field, which is the ratio of real-time current to rated allowable current carrying capacity. At the same time, the sag margin (SM) is further calculated based on the conductor sag.

[0194] Then, each quantification parameter is compared with its corresponding risk range to obtain the parameter comparison results.

[0195] For example, under a pre-defined low-risk condition, Tc≤70℃, t safe >60 minutes, SM≥20%, and all indicators meet the safety threshold;

[0196] Under medium-risk conditions, any indicator that exceeds the low-risk threshold but does not reach the high-risk critical value includes 70℃ < Tc < 80℃ and 30 minutes ≤ t safe ≤60 minutes, 125%≤IR≤155%, 10%≤SM≤20%, or both indicators are in the medium risk range;

[0197] Under high-risk conditions, any indicator reaching a critical threshold, including Tc > 80℃, t safe <30 minutes, IR>155%, SM<10%, or two medium-risk indicators accompanied by Tc>75℃ or SM<15%.

[0198] After comparison, corresponding risk assessment parameters are generated based on the comparison results of the parameters that triggered the exceedance.

[0199] In one embodiment, such as Figure 8 As shown, control module 3 includes:

[0200] Matching module 31 matches risk assessment parameters with preset level rules to determine whether expansion is possible.

[0201] First adjustment module 32, first adjustment module 32 is connected to matching module 31;

[0202] When expansion is possible, the first adjustment module 32 expands the capacity of the line to be adjusted according to the modeling and evaluation parameters, and configures the corresponding reduction rules.

[0203] The second adjustment module 33 is connected to the first adjustment module 32;

[0204] The second regulation module 33 reduces the capacity of the line to be regulated according to the modeling and evaluation parameters and sets the monitoring mode.

[0205] Specifically, in order to achieve a better evaluation process, in this embodiment, after the risk assessment parameters are constructed, they are matched with preset level rules to determine whether expansion is possible.

[0206] Specifically, different rules are configured according to different risk levels. Expansion can only be carried out under low-risk conditions, while traffic should be limited under medium- and high-risk conditions. Medium and high risks correspond to different levels of traffic limitation and handling methods.

[0207] For example, in low-risk situations, the system prioritizes economy, allowing the load capacity to be increased to 90% of the dynamic limit, extending the monitoring cycle to 15 minutes, and generating a capacity increase suggestion curve for the next 4 hours. At the same time, it sets a mandatory load reduction rule when the ambient temperature exceeds 35°C or the wind speed is below 1 m / s.

[0208] In the case of medium risk, the load capacity is immediately limited to 85% of the dynamic limit. The parameters are checked every 5 minutes and real-time sag monitoring is started. If the sag margin is less than 15%, the load is reduced to 80%. At the same time, alternative solutions of maintaining the current load capacity or reducing the load for safety are provided.

[0209] In cases of high risk, the load will be forcibly reduced to 70% of the dynamic limit or 90% of the static limit, and load transfer to backup lines, manual on-site inspection, or cooling measures will be implemented. A red alert will also be sent to the dispatch terminal in real time.

[0210] In one embodiment, such as Figure 9 As shown, the second adjustment module 33 includes:

[0211] The limit configuration module 331 generates a dynamic limit for carrying capacity based on the modeling and evaluation parameters;

[0212] Rule configuration module 332 configures monitoring rules according to risk assessment parameters;

[0213] The monitoring configuration module 333 constructs a monitoring method based on the modeling and evaluation parameters.

[0214] The above are merely preferred embodiments of the present invention and are not intended to limit the implementation methods and protection scope of the present invention. Those skilled in the art should recognize that any equivalent substitutions and obvious changes made based on the description and illustrations of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for real-time capacity expansion and regulation of transmission lines based on multi-field coupling, characterized in that, include: Step S1: Collect line parameters for the line to be adjusted and calculate AC resistance, conductor sag and line current carrying capacity as modeling and evaluation parameters. Step S2: Based on the modeling and evaluation parameters, perform a risk assessment on the line to be adjusted to obtain risk assessment parameters; Step S3: Determine and implement the graded control strategy according to the risk assessment parameters.

2. The real-time capacity expansion and adjustment method for transmission lines according to claim 1, characterized in that, In step S1, the method for generating the modeling and evaluation parameters includes: First, the AC resistance and the conductor sag are calculated based on the line parameters. The method for generating the AC resistance includes: R ac =R 20 [1+a 20 (T avg -20)](1+k s ) In the formula: R 20 The DC resistance value of the circuit to be adjusted at an ambient temperature of 20°C is expressed in Ω / m. α 20 The temperature coefficient of the conductor material of the circuit to be adjusted is given when the ambient temperature is 20°C. T avg The average conductor temperature of the circuit to be adjusted is currently [value missing]. k s The skin effect coefficient of the circuit to be adjusted; The method for generating the conductor sag includes: In the formula: f (m2y) The sag of the conductor; σ 01 The stress at the lowest point of the sag of the line to be adjusted in the initial state; σ 02 The stress at the lowest point of the sag of the line to be adjusted in the current state; γ1 is the weight-wind pressure ratio of the line to be adjusted in the initial state; γ2 is the weight-wind pressure ratio of the line to be adjusted under the current condition; T1 is the conductor temperature of the circuit to be adjusted in the initial state; T2 is the conductor temperature of the circuit to be adjusted in the current state; η1 is the wind deflection angle of the line to be adjusted in the initial state; η2 is the wind deflection angle of the line to be adjusted in the current state; l represents the span between the two ends of the line to be adjusted; β is the elevation difference angle between the two ends of the line to be adjusted; α is the coefficient of thermal expansion of the circuit to be adjusted; E is the elastic coefficient of the circuit to be adjusted; Then, the line current carrying capacity is generated based on the line parameters and the AC resistance; The method for generating the line carrying capacity includes: I 2 R+Q s =Q c +Q r In the formula: I is the current carrying capacity of the conductor; R is the AC resistance; Q s The solar heat absorption per unit length of the line to be adjusted under the current state; Q c For convective heat dissipation per unit length of the circuit to be adjusted in the current state; Q r This refers to the radiative heat dissipation per unit length of the circuit to be adjusted in the current state.

3. The real-time capacity expansion and adjustment method for transmission lines according to claim 1, characterized in that, Step S2 includes: Step S21: Quantify the modeling and evaluation parameters to obtain the quantified parameters; Step S22: Compare each of the quantification parameters with the corresponding risk interval to obtain the parameter comparison results; Step S23: Generate the risk assessment parameters based on the parameter comparison results.

4. The real-time capacity expansion and adjustment method for transmission lines according to claim 1, characterized in that, Step S3 includes: Step S31: Match the risk assessment parameters with the preset level rules to determine whether capacity expansion is possible; If so, proceed to step S32; If not, proceed to step S33; Step S32: Expand the capacity of the line to be adjusted according to the modeling and evaluation parameters, and configure the corresponding derating rules; Step S33: Reduce the capacity of the line to be adjusted according to the modeling and evaluation parameters and set the monitoring method.

5. The real-time capacity expansion and adjustment method for transmission lines according to claim 4, characterized in that, Step S32 includes: Step S321: Generate dynamic capacity limits based on the modeling and evaluation parameters; Step S322: Configure monitoring rules according to the risk assessment parameters; Step S323: Construct the monitoring method according to the modeling and evaluation parameters.

6. A real-time capacity expansion and regulation system for transmission lines based on multi-field coupling, characterized in that, Used to implement the real-time capacity expansion and adjustment method for transmission lines as described in any one of claims 1-5; The real-time capacity expansion and adjustment system for transmission lines includes: The modeling module collects line parameters for the line to be adjusted and calculates AC resistance, conductor sag and line current carrying capacity as modeling and evaluation parameters. An evaluation module, which is connected to the modeling module; The evaluation module performs a risk assessment on the line to be adjusted based on the modeling evaluation parameters to obtain risk assessment parameters. A control module, which is connected to the evaluation module; The control module determines and executes a tiered control strategy based on the risk assessment parameters.

7. The real-time capacity expansion and regulation system for transmission lines according to claim 6, characterized in that, The modeling module includes: A conductor sag calculation module, which calculates the conductor sag based on the line parameters; A resistance calculation module, which calculates the AC resistance based on the line parameters; A current carrying capacity calculation module, wherein the current carrying capacity calculation module is connected to the resistance calculation module; The current carrying capacity calculation module generates the line current carrying capacity based on the line parameters and the AC resistance.

8. The real-time capacity expansion and regulation system for transmission lines according to claim 6, characterized in that, The evaluation module includes: A quantization module, which performs quantization parameter calculations on the modeling and evaluation parameters to obtain quantization parameters; A comparison module, which is connected to the quantization module; The comparison module compares each quantification parameter with its corresponding risk range to obtain the parameter comparison result. A risk assessment module is connected to the comparison module; The risk assessment module generates the risk assessment parameters based on the comparison results of the parameters.

9. The real-time capacity expansion and regulation system for transmission lines according to claim 6, characterized in that, The control module includes: A matching module, which matches the risk assessment parameters with preset level rules to determine whether expansion is possible; A first adjustment module, which is connected to the matching module; When expansion is possible, the first adjustment module expands the capacity of the line to be adjusted according to the modeling and evaluation parameters, and configures the corresponding derating rules. A second adjustment module is connected to the first adjustment module; The second adjustment module reduces the capacity of the line to be adjusted according to the modeling and evaluation parameters and sets the monitoring mode.

10. The real-time capacity expansion and regulation system for transmission lines according to claim 9, characterized in that, The second adjustment module includes: A limit configuration module, which generates a dynamic capacity limit based on the modeling and evaluation parameters; The rule configuration module configures monitoring rules according to the risk assessment parameters; The monitoring configuration module constructs the monitoring method according to the modeling and evaluation parameters.

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