Power grid line distribution point optimal configuration method based on ice suppression type phase-shifting transformer

Abstract

The invention relates to the field of power grid line stationing optimization, in particular to a power grid line stationing optimization configuration method based on an ice suppression type phase-shifting transformer. According to the scheme, the method comprises the following steps: performing easy icing area identification and point distribution configuration; collecting and preprocessing power grid data; constructing an icing risk map according to the collected power grid data; establishing a stationing optimization mathematical model according to the icing risk map, solving the stationing optimization mathematical model, and outputting the stationing position of the phase-shifting transformer; establishing a capacity optimization model, and solving the minimum capacity of the phase-shifting transformer; performing line stationing and multi-scene power flow simulation; and finally, the transmission capacity, the suppression effect and the influence of surrounding lines are evaluated. The method is suitable for winter power grid line distribution point optimal configuration.

Description

Technical Field

[0001] This invention relates to the field of power grid line layout optimization, specifically to a method for optimizing the configuration of power grid line layout based on an ice-suppressing phase-shifting transformer. Background Technology

[0002] The cold and damp winter climate in Central China makes power transmission lines prone to icing, which can lead to line galloping, flashovers, and even tower collapses and line breaks, causing widespread power outages. Traditional AC or DC de-icing technologies require power outages for operation, which are time-consuming, inefficient, and cannot meet the high requirements of modern power grids for continuous power supply.

[0003] Online icing suppression technologies based on the thermal effect of load current (such as using phase-shifting transformers to regulate power flow) have attracted attention because they do not require power outages. However, existing technologies suffer from problems such as insufficient model accuracy, coarse control strategies, and poor application performance in ultra-high voltage scenarios. Transmission line icing is a major hidden danger threatening the safe operation of the power grid. Utilizing phase-shifting transformers to regulate the power flow between parallel lines and achieving online icing suppression by increasing the Joule heat generated by the current in the icing line is an effective uninterrupted power supply solution. In recent years, phase-shifting transformers have been used for power flow regulation, but specific research and optimization design for icing suppression are still immature. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for optimizing the configuration of power grid lines based on anti-icing phase-shifting transformers, which greatly improves the icing suppression effect.

[0005] The present invention achieves the above objectives by adopting the following technical solution: The present invention provides a method for optimizing the configuration of power grid line layout based on an ice-suppressing phase-shifting transformer, comprising:

[0006] S1. Identification and deployment of easily icing areas;

[0007] S101, Power Grid Data Acquisition and Preprocessing;

[0008] Historical meteorological data, geographic information data, and line fault data of the power grid are collected. The historical meteorological data includes temperature, humidity, wind speed, and precipitation type. The geographic information data includes altitude and topography. The line faults include line faults caused by icing.

[0009] Collect power grid topology data, including line resistance, reactance parameters, and connection relationships between nodes;

[0010] The collected data is cleaned, normalized, and formatted to eliminate outliers.

[0011] S102. Construct an icing risk map based on the collected power grid data;

[0012] Clustering algorithms are used to calculate the similarity between meteorological and geographical data, and regions with similarity greater than a preset value are grouped into the same cluster.

[0013] The clustering results were overlaid with historical icing records for verification, and an icing risk index was calculated for each grid area using a weighted comprehensive evaluation method.

[0014] Finally, a risk map of power grid icing-prone areas is generated on the electronic map, with different colors used to visually display the risk level.

[0015] S103. Establish and solve a mathematical model for site optimization based on the icing risk map, and output the site locations of the phase-shifting transformers.

[0016] Using risk maps and power grid topology as input, a mathematical model for optimizing the placement of points is established. The objective function of the mathematical model for optimizing the placement of points is: to maximize the icing suppression coverage of all high-risk lines under the constraint of investment cost. The model constraints include: the placement points must be located at the hub nodes of the power grid, the placement points must be able to change the power flow of one or more high-risk lines, and the number of placement points is limited by the budget.

[0017] The mathematical model for optimizing the placement of phase-shifting transformers is solved using integer programming or a greedy algorithm, and a recommended set of placement locations is output.

[0018] S2. Establish a capacity optimization model and solve for the minimum capacity of the phase-shifting transformer;

[0019] The objective function is to minimize the phase-shifting transformer capacity S as the optimization variable;

[0020] Define the constraints:

[0021] Ice accretion risk constraints: Based on real-time or forecast meteorological data, determine the tidal flow range that needs to be controlled for the target line;

[0022] The suppression effect constraint takes the suppression effect as the degree of deviation of the line power flow from the critical power flow for icing, and quantifies it into a threshold that must be reached.

[0023] Power flow equation constraints;

[0024] Node voltage safety constraints;

[0025] Choose an optimization algorithm to find the minimum value of S among all possible capacities S that satisfy all constraints;

[0026] Finally, output the minimum capacity of the phase-shifting transformer.

[0027] S3. Perform route layout and multi-scenario power flow simulation;

[0028] Setting up the simulation environment:

[0029] In power system simulation software, a detailed power grid model including recommended site locations is established;

[0030] Insert a phase-shifting transformer model into the icing line in the detailed power grid model that includes the recommended placement locations, and set the capacity parameter of the phase-shifting transformer model to the calculated minimum capacity;

[0031] Perform multi-scenario simulations:

[0032] Light power flow scenario: Set the power generation and load data for light load in winter, perform power flow calculation, and record the power flow value of the target line under two conditions: no phase-shifting transformer in operation and phase-shifting transformer in operation.

[0033] Heavy power flow scenario: Set winter peak load data, perform power flow calculation, and record the power flow value of the target line under two conditions: no phase-shifting transformer in operation and phase-shifting transformer in operation;

[0034] Typical power flow scenario: Set typical daily load data, perform power flow calculation, and record the power flow value of the target line under two conditions: no phase-shifting transformer in operation and phase-shifting transformer in operation.

[0035] In each scenario, the phase angle of the phase-shifting transformer is adjusted, and the range of power flow variation in the target line is recorded.

[0036] S4. Evaluate the transmission capacity, suppression effect, and impact on surrounding lines;

[0037] Maximum transmission capacity analysis:

[0038] Obtain simulation results for multiple scenarios, and under the premise of ensuring system safety, obtain the maximum active power and maximum reactive power that the line can carry in multiple scenarios;

[0039] Quantification of inhibition effect:

[0040] Establish a mathematical model for icing growth. The inputs to the mathematical model for icing growth include environmental meteorological conditions and line current.

[0041] For each scenario, the power flow value of the target line under both the condition of no phase-shifting transformer and the condition of phase-shifting transformer is input into the icing growth mathematical model to calculate the simulated icing thickness and finally calculate the icing suppression effect.

[0042] Based on the recorded range of power flow changes in the target line, identify the target line for power flow transfer and calculate the change in the load rate of that target line.

[0043] The power flow shift is assessed and analyzed to determine whether it will cause any adjacent lines to overload or bring any adjacent lines closer to the icing critical state. Finally, new risk points brought about by the commissioning of the phase-shifting transformer are identified, and operational suggestions are provided to the operators.

[0044] The beneficial effects of this invention are as follows:

[0045] This invention establishes a deployment model by comprehensively analyzing icing-prone areas and line structures; proposes a minimum capacity design method for phase-shifting transformers that considers icing risk and suppression effect constraints; implements deployment on typical icing-prone lines and conducts multi-scenario power flow analysis; evaluates the active and reactive power transmission capacity and icing suppression effect of the lines under different power flow conditions; and explores the impact of adding phase-shifting transformers on the power flow of surrounding lines, greatly improving the icing suppression effect and achieving efficient, economical, and safe icing suppression. Attached Figure Description

[0046] Figure 1 This is a flowchart of a method for optimizing the layout of power grid lines based on an ice-suppressing phase-shifting transformer, provided by the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0048] This invention provides a method for optimizing the configuration of power grid lines based on anti-icing phase-shifting transformers, such as... Figure 1 As shown, it specifically includes:

[0049] S1. Identification and deployment of easily icing areas;

[0050] S101, Power Grid Data Acquisition and Preprocessing;

[0051] Historical meteorological data, geographic information data, and line fault data of the power grid are collected. The historical meteorological data includes temperature, humidity, wind speed, and precipitation type. The geographic information data includes altitude and topography. The line faults include line faults caused by icing.

[0052] Collect power grid topology data, including line resistance, reactance parameters, and connection relationships between nodes;

[0053] The collected data is cleaned, normalized, and formatted to eliminate outliers.

[0054] S102. Construct an icing risk map based on the collected power grid data;

[0055] Clustering algorithms are used to calculate the similarity between meteorological and geographical data, and regions with similarity greater than a preset value are grouped into the same cluster.

[0056] The clustering results were overlaid with historical icing records for verification, and an icing risk index was calculated for each grid area using a weighted comprehensive evaluation method.

[0057] Finally, a risk map of power grid icing-prone areas is generated on the electronic map, with different colors used to visually display the risk level.

[0058] S103. Establish and solve a mathematical model for site optimization based on the icing risk map, and output the site locations of the phase-shifting transformers.

[0059] Using risk maps and power grid topology as input, a mathematical model for optimizing the placement of points is established. The objective function of the mathematical model for optimizing the placement of points is: to maximize the icing suppression coverage of all high-risk lines under the constraint of investment cost. The model constraints include: the placement points must be located at the hub nodes of the power grid, the placement points must be able to change the power flow of one or more high-risk lines, and the number of placement points is limited by the budget.

[0060] The mathematical model for optimizing the placement of phase-shifting transformers is solved using integer programming or a greedy algorithm, and a recommended set of placement locations is output.

[0061] S2. Establish a capacity optimization model and solve for the minimum capacity of the phase-shifting transformer;

[0062] The objective function is to minimize the phase-shifting transformer capacity S as the optimization variable;

[0063] Define the constraints:

[0064] Ice accretion risk constraints: Based on real-time or forecast meteorological data, determine the tidal flow range that needs to be controlled for the target line;

[0065] The suppression effect constraint takes the suppression effect as the degree of deviation of the line power flow from the critical power flow for icing, and quantifies it into a threshold that must be reached.

[0066] Power flow equation constraints;

[0067] Node voltage safety constraints;

[0068] Choose an optimization algorithm to find the minimum value of S among all possible capacities S that satisfy all constraints;

[0069] Finally, output the minimum capacity of the phase-shifting transformer.

[0070] S3. Perform route layout and multi-scenario power flow simulation;

[0071] Setting up the simulation environment:

[0072] In power system simulation software, a detailed power grid model including recommended site locations is established;

[0073] Insert a phase-shifting transformer model into the icing line in the detailed power grid model that includes the recommended placement locations, and set the capacity parameter of the phase-shifting transformer model to the calculated minimum capacity;

[0074] Perform multi-scenario simulations:

[0075] Light power flow scenario: Set the power generation and load data for light load in winter, perform power flow calculation, and record the power flow value of the target line under two conditions: no phase-shifting transformer in operation and phase-shifting transformer in operation.

[0076] Heavy power flow scenario: Set winter peak load data, perform power flow calculation, and record the power flow value of the target line under two conditions: no phase-shifting transformer in operation and phase-shifting transformer in operation;

[0077] Typical power flow scenario: Set typical daily load data, perform power flow calculation, and record the power flow value of the target line under two conditions: no phase-shifting transformer in operation and phase-shifting transformer in operation.

[0078] In each scenario, the phase angle of the phase-shifting transformer is adjusted, and the range of power flow variation in the target line is recorded.

[0079] S4. Evaluation of transmission capacity and suppression effect;

[0080] Maximum transmission capacity analysis:

[0081] Obtain simulation results for multiple scenarios, and under the premise of ensuring system safety, obtain the maximum active power and maximum reactive power that the line can carry in multiple scenarios;

[0082] Quantification of inhibition effect:

[0083] Establish a mathematical model for icing growth. The inputs to the mathematical model for icing growth include environmental meteorological conditions and line current.

[0084] For each scenario, the power flow value of the target line under both the condition of no phase-shifting transformer and the condition of phase-shifting transformer is input into the icing growth mathematical model to calculate the simulated icing thickness and finally calculate the icing suppression effect.

[0085] S5. Conduct an impact assessment on surrounding lines.

[0086] Based on the recorded range of power flow changes in the target line, identify the target line for power flow transfer and calculate the change in the load rate of that target line.

[0087] The power flow shift is assessed and analyzed to determine whether it will cause any adjacent lines to overload or bring any adjacent lines closer to the icing critical state. Finally, new risk points brought about by the commissioning of the phase-shifting transformer are identified, and operational suggestions are provided to the operators.

[0088] The invention will be further described in detail below with reference to specific implementation examples.

[0089] This embodiment aims to suppress icing on power lines in the Central China power grid by deploying phase-shifting transformers. Its core lies in scientific site selection, precise capacity design, and comprehensive performance evaluation. The entire technical solution is coordinated and executed by a central control system (deployed on a dispatch server).

[0090] Overall data flow:

[0091] Data input: Historical meteorological data, line structure parameters, and real-time operation data flow from the power grid's data acquisition and monitoring control system and meteorological database to the central control system.

[0092] Data processing: The various modules within the central control system process and analyze the data in sequence.

[0093] Control output: The control system calculates the optimal location of the phase-shifting transformer and operating parameters (phase angle adjustment command).

[0094] Effect feedback: After the phase-shifting transformer executes the command, the new power grid operation data is collected and fed back to the evaluation system, forming a closed loop.

[0095] The entire solution is broken down into five core modules for detailed description below:

[0096] Module 1: Icing-prone Area Identification and Detection Module

[0097] Execution entity: Central control system (server side).

[0098] Execution sequence: The module for identifying and configuring icing-prone areas is executed during the planning phase or before the icing season, and is a prerequisite for all subsequent modules.

[0099] Application scenario: Disaster prevention planning for transmission lines in the Central China power grid during winter.

[0100] The detailed functions of the easy-to-ice area identification and deployment module are as follows:

[0101] Historical meteorological data (including temperature, humidity, wind speed, and precipitation type), geographic information data (altitude, topography), and line fault records (especially faults caused by icing) of the Central China Power Grid are retrieved from the database.

[0102] Read the power grid topology data, including the resistance and reactance parameters of the lines, as well as the connection relationships between nodes.

[0103] The collected data is cleaned, normalized, and formatted to eliminate outliers in preparation for analysis.

[0104] Construction of icing risk map:

[0105] Clustering algorithms (such as K-means) are used to group regions with high similarity between meteorological and geographical data into the same cluster. For example, areas with continuous low temperatures, high humidity, and medium to high wind speeds are identified as high-risk areas.

[0106] The clustering results were overlaid with historical icing records for verification, and an icing risk index was calculated for each grid area using a weighted comprehensive evaluation method.

[0107] Finally, a risk map of the icing-prone areas of the Central China power grid was generated on the electronic map, with different colors used to visually display the risk level.

[0108] Point placement optimization modeling and solution:

[0109] A mathematical model for site optimization is established using risk maps and power grid topology as inputs.

[0110] The objective function of the mathematical model for site optimization is: to maximize the icing suppression coverage of all high-risk lines under the constraint of investment cost.

[0111] The constraints include:

[0112] The deployment points must be located at key hub nodes of the power grid.

[0113] Once deployed, the points must be able to alter the flow of one or more high-risk routes.

[0114] The number of locations is limited by the budget.

[0115] The model is solved using integer programming or a greedy algorithm, and a recommended set of locations for phase-shifting transformers is output. For example, it is recommended to install one phase-shifting transformer between 500kV substations A and B.

[0116] Module 2: Minimum Capacity Design Module for Phase-Shifting Transformers

[0117] Execution entity: Central control system (server side).

[0118] Execution sequence: Executed after the site location is determined and before equipment selection.

[0119] Application scenario: Equipment procurement and capacity determination of phase-shifting transformers.

[0120] The detailed functions of the minimum capacity design module for phase-shifting transformers are as follows:

[0121] Constraint Quantification:

[0122] Icing risk constraints: Based on real-time or forecast meteorological data, determine the power flow range that needs to be controlled for the target line. For example, to prevent icing, the active power of line L needs to be increased to above the critical value P_min.

[0123] Suppression effect constraint: The suppression effect is defined as the degree of deviation of the line power flow from the critical power flow for icing, and it is quantified into a threshold that must be reached.

[0124] Capacity optimization model establishment and solution:

[0125] Establish a minimization objective function with the phase-shifting transformer capacity S as the optimization variable: Minimize(S).

[0126] The quantified risk and effect constraints, along with power flow equations and node voltage security constraints, are incorporated into the capacity optimization model.

[0127] Call an optimization solver (such as one based on genetic algorithms or linear programming) to solve the model. The solution process is to find the minimum value of S among all possible capacities that satisfy all constraints (i.e., ensure the suppression effect).

[0128] The minimum rated capacity of the output phase-shifting transformer.

[0129] Module 3: Typical Line Layout and Multi-Scenario Power Flow Simulation Module

[0130] Execution entity: Power flow calculation engine (server side) in the central control system.

[0131] Execution sequence: Used for scheme verification and simulation after capacity design is completed.

[0132] Application scenario: Simulation verification scenario before implementation of the solution.

[0133] The detailed functions of the typical line layout and multi-scenario power flow simulation module are as follows:

[0134] Simulation environment setup:

[0135] In power system simulation software, a detailed model of the Central China power grid, including recommended power grid locations, is established.

[0136] Insert a phase-shifting transformer model into the icing line in the model and set its capacity parameter to the minimum value calculated in Module 2.

[0137] Multi-scenario simulation execution:

[0138] Light power flow scenario: Set the generation and load data for light winter load, and perform power flow calculation. Record the power flow values ​​P_light and Q_light of the target line under two conditions: without phase-shifting transformer in operation and with phase-shifting transformer in operation (with an initial phase angle set).

[0139] Heavy load scenario: Set the winter peak load data, repeat the above process, and record P_heavy and Q_heavy.

[0140] Typical power flow scenario: Set typical daily load data, repeat the above process, and record P_normal and Q_normal.

[0141] In each scenario, the phase angle of the phase-shifting transformer was adjusted, and the variable range of the power flow of the target line was observed and recorded.

[0142] Module 4: Transmission Capacity and Suppression Effectiveness Evaluation Module

[0143] Execution entity: Central control system (server side).

[0144] Execution sequence: Executed immediately after the simulation results of Module 3.

[0145] Application scenario: Quantitative evaluation of solution effectiveness.

[0146] The detailed functions of the transmission capacity and suppression effect evaluation module are as follows:

[0147] Maximum transmission capacity analysis:

[0148] Read the simulation results from Module 3, and under the premise of ensuring system safety (voltage does not exceed limits and lines are not overloaded), find the maximum active power P_max and the maximum reactive power Q_max that the line can carry in three scenarios.

[0149] Quantification of inhibition effect:

[0150] An integrated mathematical model for icing growth is proposed, whose inputs include environmental meteorological conditions and line current (related to power flow P).

[0151] The construction principle of the mathematical model for ice growth is as follows:

[0152] According to the principles of fluid mechanics, the mass flux of supercooled water droplets trapped on a unit length of wire per unit time is... Represented as:

[0153]

[0154] In the formula, denoted as the characteristic diameter of the icing conductor as a function of time; w represents the liquid water content in the air; and v represents the wind speed.

[0155] in, The overall capture coefficient is defined by the following formula:

[0156]

[0157] In the formula, The probability of a water droplet hitting a wire is represented by the Stokes number and the Reynolds number. This represents the probability that a water droplet does not bounce after impact; for wet snow or freezing rain conditions, it is usually taken as 1. This characterizes the proportion of water that actually freezes into ice due to heat exchange limitations.

[0158] Based on the Messinger concept, a thermodynamic model of icing is established, and the energy conservation equation that the icing object must satisfy is determined:

[0159]

[0160] In the formula: Q J Joule heating is generated by the electric current; Q f The heat released when water freezes; Q k The energy converted from the kinetic energy of a water droplet impact; Q v The energy that generates heat through friction with air; Q c The energy dissipated by convection; Q e The energy dissipated through evaporation or sublimation; Q s The energy for sensible heat cooling; Q r Energy dissipated through radiation.

[0161]

[0162] in, The resistance is 20°C DC. The temperature coefficient of resistance. The core temperature of the conductor is approximated as the surface temperature of the conductor.

[0163]

[0164] in The latent heat of water freezing (334 kJ / kg).

[0165] Solving the above equations simultaneously, the freezing coefficient is:

[0166]

[0167] If calculated ≥1 indicates extremely strong cooling capacity; all captured water droplets freeze. (Correction) Let 1 be the value of ice and calculate the ice density using the Macklin formula:

[0168]

[0169] In the formula, A and B are empirical constants of 110 and 0.76, respectively. The density of pure ice is 917 kg / m³. 3 r is the droplet radius; v imp T represents the velocity of the water droplet hitting the wire. s This refers to the surface temperature covered by ice.

[0170] If the calculated 0 < < 1 indicates that the current generates Q. J Or, insufficient cooling due to ambient temperature may result in a water film on the surface. In this case, the ice density is high, and it is typically... .

[0171] like This indicates that Joule heating is sufficient to melt all water droplets, preventing the ice layer from growing.

[0172] Finally, based on the law of conservation of mass, the ice thickness is established. The differential equation over time. Assume the ice layer is uniformly distributed on the surface of the cylinder:

[0173]

[0174] Input current I and meteorological parameters, and obtain and Numerical integration is performed within the time step Δt to update the ice thickness at the next moment:

[0175]

[0176] Repeat the loop until the ice thickness reaches the preset time.

[0177] For each scenario, the power flow P_before when the phase-shifting transformer is not in operation and the power flow P_after after the phase-shifting transformer is in operation are respectively substituted into the icing model.

[0178] The simulated icing thickness was calculated, and the icing suppression effect was finally calculated, demonstrating the expected reduction rate of icing thickness by the phase-shifting transformer in different scenarios.

[0179] Module 5: Impact Assessment of Surrounding Lines

[0180] Execution entity: Central control system (server side).

[0181] Execution sequence: Executed in parallel with module four.

[0182] Application scenarios: Scenarios involving side effect evaluation of solutions and system security verification.

[0183] The detailed functions of the impact assessment module for surrounding lines are as follows:

[0184] Compare the power flow changes of adjacent lines around the circuit before and after the phase-shifting transformer in Module 3 is put into operation.

[0185] Identify which lines have experienced increased power flow (i.e., power flow shifts have occurred) and calculate the changes in their load rates.

[0186] Impact on report generation:

[0187] Assess whether these power flow shifts will cause any adjacent lines to become overloaded or bring them closer to icing criticality.

[0188] Finally, a comprehensive impact assessment was conducted to clearly identify the new risks that may arise from the installation of the phase-shifting transformer and to provide operational recommendations for operators.

[0189] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A method for optimizing the configuration of power grid lines based on anti-icing phase-shifting transformers, characterized in that, include: S1. Identification and deployment of easily icing areas; S101, Power Grid Data Acquisition and Preprocessing; S102. Construct an icing risk map based on the collected power grid data; S103. Establish and solve a mathematical model for site optimization based on the icing risk map, and output the site locations of the phase-shifting transformers. S2. Establish a capacity optimization model and solve for the minimum capacity of the phase-shifting transformer; S3. Perform route layout and multi-scenario power flow simulation; S4. Evaluate the transmission capacity, suppression effect, and impact on surrounding lines.

2. The method for optimizing the layout of power grid lines based on an ice-suppressing phase-shifting transformer according to claim 1, characterized in that, Step S101 specifically includes: Historical meteorological data, geographic information data, and line fault data of the power grid are collected. The historical meteorological data includes temperature, humidity, wind speed, and precipitation type. The geographic information data includes altitude and topography. The line faults include line faults caused by icing. Collect power grid topology data, including line resistance, reactance parameters, and connection relationships between nodes; The collected data is cleaned, normalized, and formatted to eliminate outliers.

3. The method for optimizing the layout of power grid lines based on an ice-suppressing phase-shifting transformer according to claim 2, characterized in that, Step S102 specifically includes: Clustering algorithms are used to calculate the similarity between meteorological and geographical data, and regions with similarity greater than a preset value are grouped into the same cluster. The clustering results were overlaid with historical icing records for verification, and an icing risk index was calculated for each grid area using a weighted comprehensive evaluation method. Finally, a risk map of power grid icing-prone areas is generated on the electronic map, with different colors used to visually display the risk level.

4. The method for optimizing the layout of power grid lines based on an ice-suppressing phase-shifting transformer according to claim 3, characterized in that, Step S103 specifically includes: Using risk maps and power grid topology as input, a mathematical model for optimizing the placement of points is established. The objective function of the mathematical model for optimizing the placement of points is: to maximize the icing suppression coverage of all high-risk lines under the constraint of investment cost. The model constraints include: the placement points must be located at the hub nodes of the power grid, the placement points must be able to change the power flow of one or more high-risk lines, and the number of placement points is limited by the budget. The mathematical model for optimizing the placement of phase-shifting transformers is solved using integer programming or a greedy algorithm, and a recommended set of placement locations is output.

5. The method for optimizing the layout of power grid lines based on an anti-icing phase-shifting transformer according to claim 1, characterized in that, Step S2 specifically includes: The objective function is to minimize the phase-shifting transformer capacity S as the optimization variable; Define the constraints: Ice accretion risk constraints: Based on real-time or forecast meteorological data, determine the tidal flow range that needs to be controlled for the target line; The suppression effect constraint takes the suppression effect as the degree of deviation of the line power flow from the critical power flow for icing, and quantifies it into a threshold that must be reached. Power flow equation constraints; Node voltage safety constraints; Choose an optimization algorithm to find the minimum value of S among all possible capacities S that satisfy all constraints; Finally, output the minimum capacity of the phase-shifting transformer.

6. The method for optimizing the layout of power grid lines based on an ice-suppressing phase-shifting transformer according to claim 1, characterized in that, Step S3 specifically includes: Setting up the simulation environment: In power system simulation software, a detailed power grid model including recommended site locations is established; Insert a phase-shifting transformer model into the icing line in the detailed power grid model that includes the recommended placement locations, and set the capacity parameter of the phase-shifting transformer model to the calculated minimum capacity; Perform multi-scenario simulations: Light power flow scenario: Set the power generation and load data for light load in winter, perform power flow calculation, and record the power flow value of the target line under two conditions: no phase-shifting transformer in operation and phase-shifting transformer in operation. Heavy power flow scenario: Set winter peak load data, perform power flow calculation, and record the power flow value of the target line under two conditions: no phase-shifting transformer in operation and phase-shifting transformer in operation; Typical power flow scenario: Set typical daily load data, perform power flow calculation, and record the power flow value of the target line under two conditions: no phase-shifting transformer in operation and phase-shifting transformer in operation. In each scenario, the phase angle of the phase-shifting transformer is adjusted, and the range of power flow variation in the target line is recorded.

7. The method for optimizing the layout of power grid lines based on an ice-suppressing phase-shifting transformer according to claim 1, characterized in that, Step S4 specifically includes the evaluation of transmission capacity and suppression effect: Maximum transmission capacity analysis: Obtain simulation results for multiple scenarios, and under the premise of ensuring system safety, obtain the maximum active power and maximum reactive power that the line can carry in multiple scenarios; Quantification of inhibition effect: Establish a mathematical model for icing growth. The inputs to the mathematical model for icing growth include environmental meteorological conditions and line current. For each scenario, the power flow value of the target line under both the condition of no phase-shifting transformer and the condition of phase-shifting transformer is input into the icing growth mathematical model to calculate the simulated icing thickness and finally calculate the icing suppression effect.

8. The method for optimizing the layout of power grid lines based on an ice-suppressing phase-shifting transformer according to claim 1, characterized in that, Step S4, specifically assessing the impact on surrounding lines, includes: Based on the recorded range of power flow changes in the target line, identify the target line for power flow transfer and calculate the change in the load rate of that target line. The power flow shift is assessed and analyzed to determine whether it will cause any adjacent lines to overload or bring any adjacent lines closer to the icing critical state. Finally, new risk points brought about by the commissioning of the phase-shifting transformer are identified, and operational suggestions are provided to the operators.

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