Ground wire deicing control method and system based on distributed energy collection

Abstract

The invention discloses a ground wire deicing control method and system based on distributed energy harvesting, and relates to the technical field of ground wire deicing, and the method comprises the following steps: collecting total energy; obtaining icing influence data, and constructing an icing influence model based on a bp neural network according to the icing influence data; according to the ground wire icing rate and the total energy, obtaining relational data between the corresponding unit ground wire icing thickness and the energy consumed by deicing, and obtaining a constraint condition of the deicing frequency; removing a plurality of different deicing frequencies based on the constraint conditions of the deicing frequencies, obtaining the output of the icing influence model under the remaining deicing frequencies, constructing an output set, and performing data analysis to obtain the optimal deicing frequency; by accurately controlling the relation between the deicing frequency and the deicing energy, the problems of electric power facility damage and potential safety hazards caused by excessive deicing are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of ground wire deicing, and more specifically, to a ground wire deicing control method and system based on distributed energy harvesting. Background Art

[0002] In the power system, the icing problem of transmission lines has always been a severe challenge. Especially in winter, long-term low temperatures, rain, snow and freezing weather will cause thick ice to form on the surface of the transmission lines, which will not only significantly reduce the mechanical and electrical performance of the transmission lines, but also cause line overload, frequent ice flashes caused by icing of insulator strings, and transmission line dancing and damage to power equipment, which seriously threatens the safe operation of the power system.

[0003] With the advancement of science and technology, a ground wire de-icing control method based on distributed energy harvesting has emerged. This method uses the current or voltage induced by the ground wire itself as an energy source, and converts the energy in the ground wire into electrical energy through a distributed energy harvesting device, such as an electromagnetic power-taking device, and stores it in an energy storage capacitor. When de-icing is required, the energy storage capacitor discharges through the electromagnetic pulse coil to generate a pulse magnetic field, which generates a repulsive force between the electromagnetic pulse coil and the ground wire, so that the surface of the ground wire produces an amplitude and high acceleration movement within the elastic deformation range, achieving the effect of breaking the ice.

[0004] The above disclosed technical solutions have at least the following technical problems: The traditional ground wire deicing control method based on distributed energy harvesting cannot accurately control the relationship between deicing frequency and deicing energy during the deicing process, resulting in damage to power facilities and safety hazards caused by excessive deicing.

[0005] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a ground wire de-icing control method and system based on distributed energy harvesting, which obtains energy predictions of different distributed energy harvesting methods, and establishes a ground wire icing rate model and an icing influence model respectively, so as to solve the problems mentioned in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions: A ground wire deicing control method based on distributed energy collection includes obtaining a distributed energy collection method, predicting different distributed energy collection methods, and obtaining the total energy collected; obtaining ground wire icing rate influence data of a test area, and constructing a ground wire icing rate model based on a polynomial fitting method according to the ground wire icing rate influence data to obtain the ground wire icing rate; obtaining icing influence data, and constructing an icing influence model based on a BP neural network according to the icing influence data; obtaining relationship data between the corresponding unit ground wire icing thickness and the energy consumed for deicing according to the ground wire icing rate and the total energy, and obtaining the constraint conditions of the deicing frequency; eliminating several different deicing frequencies based on the constraint conditions of the deicing frequency, obtaining the output of the icing influence model under the remaining deicing frequencies, constructing an output set, and performing data analysis to obtain the optimal deicing frequency.

[0008] In a preferred embodiment, the ice coating influence data includes an electrical performance influence coefficient, and the steps for obtaining the electrical performance influence coefficient are as follows: prepare multiple groups of ice cubes coated on the ground wire to be tested, debug the test environment, and use a conductivity instrument to measure the conductivity of the ice cubes to be tested at different temperatures and the same humidity and at the same temperature and different humidity; according to the relationship data between humidity and conductivity and between temperature and conductivity, the humidity influence coefficient and the temperature influence coefficient are obtained based on linear regression analysis; obtain the type of insulating material in the ground wire to be tested and the rated voltage of the ground wire to be tested, prepare a group of identical insulating materials to be tested, conduct electrical experiments on the materials to be tested, and connect the red and black measuring wires of the insulation resistance meter to the ground wire to be tested, respectively. The two terminal positions of the ground wire material; applying a stable voltage to the material to be tested and the voltage is greater than the rated voltage of the ground wire, waiting for a period of time until the discharge phenomenon of the insulating electrode is stable, and then obtaining the insulation resistance value and the test voltage; obtaining the cross-sectional area of ​​the ground wire material to be tested, and calculating the insulation coefficient of the ground wire material based on the insulation resistance value, the test voltage and the cross-sectional area of ​​the ground wire material based on a preset insulation coefficient formula of the ground wire material; obtaining the thickness of the ice layer of the ground wire to be tested and the density of the ice, and calculating the electrical performance influence coefficient based on the preset electrical performance influence coefficient formula according to the conductivity of the ice, the humidity influence coefficient, the temperature influence coefficient, the insulation coefficient of the ground wire material, the thickness of the ice layer of the ground wire and the density of the ice.

[0009] In a preferred embodiment, the ice coverage influence data includes a mechanical strength influence coefficient, and the steps for obtaining the mechanical strength influence coefficient are as follows: obtain a ground wire to be tested, apply a load to the ground wire to be tested, until cracks appear in the ground wire and stop, and perform a tensile test on the ground wire under different load conditions, and record the elastic modulus of the ground wire under different load conditions; obtain the load coefficient based on linear analysis according to the relationship data between the ground wire load and the elastic modulus; obtain the annual average wind speed and wind speed distribution according to the historical meteorological data of the area to be tested, and obtain the wind speed at different heights based on the CFD model according to the geographical conditions of the area to be tested, and the geographical conditions include whether there are mountains and urban layout; according to The windward area of ​​the ground line is obtained according to the wind direction angle, that is, the area affected by wind force; the air density, wind speed, dynamic viscosity of air and characteristic length of the object in the measured area are obtained, the characteristic length of the object includes the width and thickness of the ice layer, and the air resistance coefficient is obtained based on the Reynolds number formula; the additional load caused by wind is calculated based on the air resistance coefficient, wind speed and the area affected by wind force based on the preset formula of additional load caused by wind force to obtain the additional load caused by wind; the thickness of ice layer and the density of ice covering the ground line are obtained, and the mechanical strength influence coefficient is calculated based on the preset formula of mechanical strength influence coefficient according to the load coefficient, additional load caused by wind force, thickness of ice layer and density of ice covering the ground line.

[0010] In a preferred embodiment, the steps for obtaining the ground ice coverage rate are as follows: obtaining historical meteorological data and corresponding ground ice coverage data of the area to be measured, and using the least squares method to obtain a constant coefficient, wherein the ground ice coverage data include temperature, humidity, wind speed, and the angle between the wind direction and the ground; calculating based on the ground ice coverage data of the area to be measured based on a preset ground ice coverage rate formula to obtain the ground ice coverage rate; obtaining parameter estimates for future unit time based on the parameters in the ground ice coverage rate formula based on a time series method, and inputting the obtained parameter estimates into the ground ice coverage rate formula to obtain the ground ice coverage rate for future unit time.

[0011] In a preferred embodiment, the relationship data between the corresponding unit ground wire ice coating thickness and the energy consumed for de-icing is obtained based on the ground wire ice coating rate and the total energy, and the constraint conditions for the de-icing frequency are obtained, which are specifically as follows: the total ground wire ice coating thickness per unit time is obtained based on the ground wire ice coating rate, and the total ground wire ice coating thickness is divided by the single de-icing thickness to obtain the de-icing frequency per unit time, and the de-icing frequency is greater than 1 and the single de-icing thickness is not higher than the total ice coating thickness per unit time.

[0012] In a preferred embodiment, the constraint condition based on the de-icing frequency is used to eliminate several different de-icing frequencies, obtain the output of the icing influence model under the remaining de-icing frequencies, construct an output set, and perform data analysis to obtain the optimal de-icing frequency, specifically as follows: multiply the de-icing frequency by the energy consumed in a single de-icing to obtain the total de-icing energy consumption, and eliminate the data with the total de-icing energy consumption higher than the total energy collected per unit time; divide the remaining data by the total ice thickness per unit time by the single de-icing thickness to obtain the remaining de-icing frequency data set; input the remaining de-icing frequency data into the icing influence model for output, construct an output set, and perform data analysis to obtain the highest output result, thereby obtaining the optimal de-icing frequency.

[0013] The system of the ground wire deicing control method based on distributed energy collection is characterized in that it includes an energy prediction module, a ground wire ice coating rate calculation module, a data collection module, an extraction constraint condition module and a data output module, and there are connections between the modules; the energy prediction module is used to obtain the distributed energy collection mode, predict different distributed energy collection modes, and obtain the total energy collected; the ground wire ice coating rate calculation module is used to obtain the ground wire ice coating rate influence data of the test area, and construct the ground wire ice coating rate model based on the polynomial fitting method according to the ground wire ice coating rate influence data to obtain the ground wire ice coating rate; the data collection module is used to obtain the ice coating influence data, and construct the ice coating influence model based on the bp neural network according to the ice coating influence data; the extraction constraint condition module is used to obtain the relationship data between the corresponding unit ground wire ice coating thickness and the energy consumed for deicing according to the ground wire ice coating rate and the total energy, and obtain the constraint condition of the deicing frequency; the data output module is used to eliminate several different deicing frequencies based on the constraint condition of the deicing frequency, obtain the output of the ice coating influence model under the remaining deicing frequencies, construct an output set, and perform data analysis to obtain the optimal deicing frequency.

[0014] Technical effects and advantages of the ground wire deicing control method and system based on distributed energy harvesting of the present invention: 1. The present invention can accurately calculate the deicing energy consumption of the ground line by obtaining energy predictions of different distributed energy collection methods and combining the optimization of the ground line ice coverage rate and deicing frequency. This control method can ensure the rationality of the deicing frequency, that is, by limiting the relationship between the deicing frequency and the actual energy collection capacity, unnecessary excessive deicing is avoided, thereby improving energy utilization efficiency. This optimization scheme can ensure that energy waste is reduced while ensuring the deicing effect.

[0015] 2. The present invention uses advanced data processing technologies such as polynomial fitting and BP neural network to establish ground wire ice coverage rate model and ice coverage impact model respectively. By combining historical meteorological data and measured data, it can accurately predict the ice coverage rate and electrical performance, mechanical strength and other aspects of the ground wire under different environmental conditions. Through the prediction of these models, more accurate input data can be provided for deicing strategies, improving the scientificity and accuracy of deicing operations.

[0016] 3. The present invention ensures that the energy consumption of deicing operation does not exceed the actual energy supply capacity of the distributed energy collection system by analyzing the relationship between the energy consumed by deicing and energy collection. By reasonably controlling the deicing frequency, excessive deicing is avoided when energy is short, thereby reducing energy waste and reducing the cost of the deicing process. In addition, by optimizing the selection of deicing frequency, inefficient multiple deicing is avoided, further improving energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a structural schematic diagram of a ground wire deicing control method based on distributed energy harvesting of the present invention.

[0018] Figure 2 The system structure diagram of a ground wire deicing control method based on distributed energy harvesting of the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Embodiment 1, Figure 1 The present invention provides a ground wire deicing control method based on distributed energy harvesting, which includes the following steps: S1, obtaining a distributed energy collection method, predicting different distributed energy collection methods, and obtaining the total collected energy.

[0021] In this embodiment, the distributed energy collection method is obtained, and different distributed energy collection methods are predicted to obtain the total energy collected, as follows: The distributed energy collection method includes photovoltaic energy collection, vibration energy collection and electromagnetic energy collection.

[0022] Vibration energy harvesting: Vibration energy is a ubiquitous energy source in the environment, especially in the ocean, bridges, and transportation. Through specific devices, such as vibration energy harvesters, these distributed vibration energies can be converted into electrical energy. This method has the advantages of being green, environmentally friendly, and sustainable, and can meet the needs of some electronic devices that require long-term maintenance-free operation. For example, vibration energy harvesting technology has been applied in bridge health monitoring systems and ocean monitoring buoys.

[0023] Photovoltaic energy harvesting: Photovoltaic energy harvesting is a technology that uses solar energy to convert into electrical energy. It is based on the photovoltaic effect and directly converts sunlight into electrical energy through photovoltaic cells. Photovoltaic cells are usually made of semiconductor materials. When sunlight shines on the surface of the cell, photons excite electrons in the semiconductor to form an electric current. This technology has the advantages of being clean, renewable, and pollution-free, and is an important part of the renewable energy field. Photovoltaic energy harvesting is widely used in households, industries, agriculture and other fields to provide green and sustainable energy for power systems.

[0024] Electromagnetic energy harvesting: Electromagnetic energy harvesting is a technology that uses the energy of electromagnetic waves to convert into electrical energy. It uses the principles of electromagnetic induction and electromagnetic radiation to convert electromagnetic waves into electrical energy to provide power for electronic devices. Electromagnetic energy harvesting technology has the advantages of easy operation, safety, and environmental protection, and can be applied to smart homes, smart vehicles and other fields. By collecting electromagnetic wave energy in the environment, electromagnetic energy harvesting technology can provide power support for these devices. This technology has broad application prospects and is one of the important development directions in the field of clean energy in the future. With the continuous advancement of technology, the efficiency of electromagnetic energy harvesting will continue to improve, providing green and sustainable energy for more fields.

[0025] The prediction of different distributed energy harvesting methods is as follows: The historical collection data of different distributed energy collection methods are obtained, and the energy collected by different distributed energy collection methods is predicted based on the time series method to obtain the total energy estimated for the next day.

[0026] S2, obtaining the ground line ice coverage rate influence data of the area to be measured, constructing a ground line ice coverage rate model based on the ground line ice coverage rate influence data based on a polynomial fitting method, and obtaining the ground line ice coverage rate.

[0027] In this embodiment, the ground line ice coverage rate influence data of the measured area is obtained, and a ground line ice coverage rate model is constructed based on the polynomial fitting method according to the ground line ice coverage rate influence data to obtain the ground line ice coverage rate, which is specifically as follows: The steps for obtaining the ground line ice coverage rate are as follows: Obtain historical meteorological data of the area to be tested and corresponding ground line ice coverage data, wherein the ground line ice coverage data includes temperature, humidity, wind speed, and the angle between the wind direction and the ground line, and obtain a constant coefficient using the least squares method; The temperature, humidity, wind speed, and the angle between the wind direction and the ground line of the area to be measured are obtained, and the ground line ice coverage rate is calculated based on the preset ground line ice coverage rate formula according to the temperature, humidity, wind speed, constant coefficient, and the angle between the wind direction and the ground line of the area to be measured; According to the parameters in the ground line ice coverage rate formula, a parameter estimation per unit time in the future is obtained based on a time series method, and the obtained parameter estimation is input into the ground line ice coverage rate formula to obtain the ground line ice coverage rate per unit time in the future.

[0028] The calculation formula of the ground line ice coverage rate is as follows:

[0029] In the formula, is the ground ice coverage rate, is a constant coefficient, is the temperature, is humidity, is the wind speed, It is the angle between the wind direction and the ground.

[0030] S3, obtaining ice impact data, and constructing an ice impact model based on the BP neural network according to the ice impact data; In this embodiment, the icing influence data is obtained, and an icing influence model is constructed based on the bp neural network according to the icing influence data, as follows: The ice coverage impact data includes an electrical performance impact coefficient and a mechanical strength impact coefficient; The electrical performance impact coefficient is an indicator used to quantify the degree of impact of ice on the electrical performance of the ground wire. It takes into account multiple factors such as the thickness, conductivity, density of the ice layer, and the insulation coefficient of the ground wire material. Under extreme climatic conditions, the accumulation of ice may pose a threat to the stability and safety of the power transmission system, reduce the insulation performance of the wires, increase the risk of electrical failures, and may even lead to an increase in deicing current. The electrical performance impact coefficient combines these complex physical factors into a single value through a mathematical model, making it easier for engineers to evaluate and predict the electrical performance of the ground wire.

[0031] The steps for obtaining the electrical performance influence coefficient are as follows: Prepare multiple groups of ice cubes covered on the ground wires to be tested, debug the test environment, and use a conductivity instrument to measure the conductivity of the ice cubes to be tested at different temperatures and the same humidity and at the same temperature and different humidity; According to the relationship data between humidity and conductivity and between temperature and conductivity, the humidity influence coefficient and temperature influence coefficient are obtained based on linear regression analysis; Obtain the type of insulating material in the ground wire to be tested and the rated voltage of the ground wire to be tested, prepare a group of identical insulating materials to be tested, conduct electrical experiments on the materials to be tested, and connect the red and black measuring wires of the insulation resistance meter to the two terminal positions of the ground wire material to be tested respectively; Apply a stable voltage greater than the rated voltage of the ground wire to the material to be tested, wait for a period of time until the discharge phenomenon of the insulating electrode stabilizes, and then obtain the insulation resistance value and test voltage; Obtaining the cross-sectional area of ​​the ground wire material to be tested, and calculating the insulation coefficient of the ground wire material based on a preset insulation coefficient formula of the ground wire material according to the insulation resistance value, the test voltage and the cross-sectional area of ​​the ground wire material; The thickness of the ice layer of the ground wire to be tested and the density of the ice are obtained, and the electrical performance influence coefficient is calculated based on a preset electrical performance influence coefficient formula according to the conductivity of the ice, the humidity influence coefficient, the temperature influence coefficient, the insulation coefficient of the ground wire material, the thickness of the ice layer of the ground wire and the density of the ice to obtain the electrical performance influence coefficient.

[0032] The calculation formula of the electrical performance influence coefficient is as follows:

[0033] The calculation formula of the insulation coefficient of the ground wire material is as follows:

[0034] In the formula, is the electrical performance influence coefficient, is the thickness of the ice layer, is the conductivity of the ice layer, is the density of ice, is the insulation coefficient of the ground wire material, is the temperature influence coefficient, is the humidity influence coefficient, is the insulation resistance value, is the cross-sectional area of ​​the ground wire material, is the test voltage.

[0035] The reason for selecting the ice cubes covering the ground wire to be tested is: Generally speaking, the conductivity of pure water ice (without impurities) is low, while the conductivity of ice containing salt or other impurities is high.

[0036] It should be noted that the smaller the value of the electrical performance impact coefficient, the greater the impact of the ice layer on the electrical performance of the ground wire, and additional measures may need to be taken to ensure the stable operation of the power system.

[0037] Mechanical strength influence coefficient is a key indicator used to quantify the impact of ice and wind on the mechanical strength and structural safety of ground wires. In power systems, ground wires not only have the task of transmitting current, but also have to withstand various challenges from the natural environment, of which ice and wind are the two main factors. Ice increases the gravity load on the ground wire, while wind may further aggravate this load, causing vibration, deformation, or even damage to the ground wire.

[0038] The steps for obtaining the mechanical strength influence coefficient are as follows: Obtain a ground wire to be tested, apply a load to the ground wire to be tested until cracks appear on the ground wire and the ground wire stops cracking, and perform a tensile test on the ground wire under different load states, and record the elastic modulus of the ground wire under different load states; The load factor is obtained based on linear analysis according to the relationship data between the ground wire load and the elastic modulus; According to the historical meteorological data of the area to be tested, the annual average wind speed and wind speed distribution are obtained, and according to the geographical conditions of the area to be tested, the wind speed at different heights is obtained based on the CFD model, and the geographical conditions include whether there are mountains and urban layout; Obtain the windward area of ​​the ground line according to the wind direction angle, that is, the area where the wind acts; Obtain the air density, wind speed, dynamic viscosity of the air and characteristic length of the object in the test area, wherein the characteristic length of the object includes the width and thickness of the ice layer, and calculate based on the Reynolds number formula to obtain the air resistance coefficient; The additional load caused by wind is calculated based on the preset additional load formula caused by wind according to the air resistance coefficient, wind speed and the area where wind acts, to obtain the additional load caused by wind; The thickness of the ice layer and the density of the ice covering the ground wire are obtained, and the mechanical strength influence coefficient is calculated based on a preset mechanical strength influence coefficient formula according to the load factor, the additional load caused by wind, the thickness of the ice layer and the density of the ice covering the ground wire.

[0039] The calculation formula of the mechanical strength influence coefficient is as follows:

[0040] The calculation formula of the additional load caused by wind force is as follows:

[0041] The calculation formula of the Reynolds number is as follows:

[0042] In the formula, is the mechanical strength influence coefficient, is the load factor, is the additional load caused by wind, is the thickness of the ice layer, is the density of ice, is the air resistance coefficient, is the area over which the wind acts, is the wind speed, is the characteristic length of the object, including the width and thickness of the ice layer, is the dynamic viscosity of air.

[0043] CFD model, or computational fluid dynamics model, is a mathematical model used to simulate and analyze physical phenomena such as fluid flow and heat conduction. It is based on the basic principles of fluid mechanics, heat transfer and control theory, and uses computer technology and numerical methods, such as finite difference method, finite element method, finite volume method, etc., to convert physical phenomena such as fluid movement and heat transfer into discrete mathematical equations, and solve these equations by computer to obtain the discrete distribution of the flow field of fluid flow in a continuous area, thereby approximately simulating the fluid flow.

[0044] It should be noted that the mechanical strength influence coefficient evaluates the comprehensive impact of these factors on the mechanical strength of the ground wire by comprehensively considering the mass of the ice layer (determined by the thickness of the ice layer and the density of the ice) and the additional load caused by wind. The load coefficient reflects the ability of the ground wire itself to withstand additional loads. The smaller the coefficient value, the greater the impact of ice and wind on the mechanical load of the ground wire, and the higher the risk of damage to the ground wire. Therefore, the mechanical strength influence coefficient is an important indicator for evaluating the ability of the ground wire to operate safely under extreme weather conditions.

[0045] The calculation formula of the ice coverage impact model is as follows:

[0046] In the formula, is the icing influence coefficient, is the electrical performance influence coefficient, is the mechanical strength influence coefficient.

[0047] It should be noted that the higher the icing impact coefficient, the smaller the impact of the mass of the ice layer and the external wind on the mechanical load of the ground wire. The ground wire structure can withstand greater pressure and maintain stable operation. The impact on the electrical performance of the ground wire is smaller, the risk of electrical failure is lower, and the conductivity and insulation of the ground wire remain good. The lower the icing impact coefficient, the greater the impact of the ice layer thickness and wind force. The ground wire may face a larger mechanical load and is prone to damage or vibration. The ice layer has a greater impact on the electrical performance of the ground wire, which may increase the probability of electrical failures. Especially when the ice layer thickness increases, the insulation of the ground wire will significantly decrease, increasing the risk of electrical short circuit or failure.

[0048] S4, according to the ground line ice coating rate and the total energy, obtain the relationship data between the corresponding single ground line ice coating thickness and the energy consumed by deicing, and obtain the constraint condition of the deicing frequency.

[0049] In this embodiment, the relationship data between the corresponding unit ground line ice thickness and the energy consumed for deicing is obtained according to the ground line ice coating rate and the total energy, and the constraint conditions of the deicing frequency are obtained, which are specifically as follows: The total ice thickness of the ground wire per unit time is obtained according to the ground wire ice coating rate, and the deicing frequency per unit time is obtained by dividing the total ice thickness of the ground wire by the single deicing thickness. The deicing frequency is greater than 1 and the single deicing thickness is not higher than the total ice thickness per unit time.

[0050] S5, based on the constraints of the deicing frequency, several different deicing frequencies are eliminated, the output of the icing influence model under the remaining deicing frequencies is obtained, an output set is constructed, and data analysis is performed to obtain the optimal deicing frequency.

[0051] In this embodiment, the constraint condition based on the deicing frequency is used to eliminate several different deicing frequencies, obtain the output of the icing influence model under the remaining deicing frequencies, construct an output set, and perform data analysis to obtain the optimal deicing frequency, as follows: The deicing frequency is multiplied by the energy consumed by a single deicing operation to obtain the total deicing energy consumption, and data whose total deicing energy consumption is higher than the total energy collected per unit time are eliminated; The remaining data is obtained by dividing the total ice thickness per unit time by the single deicing thickness to obtain the remaining deicing frequency data set; The remaining de-icing frequency data is input into the icing influence model for output, an output set is constructed, and data analysis is performed to obtain the highest output result, thereby obtaining the optimal de-icing frequency.

[0052] Embodiment 2, Figure 2 A system of a ground wire deicing control method based on distributed energy collection is provided, comprising an energy prediction module, a ground wire ice coverage rate calculation module, a data collection module, a constraint condition extraction module and a data output module, and there are connections between the modules; An energy prediction module is used to obtain distributed energy collection methods, predict different distributed energy collection methods, and obtain the total energy collected; The ground wire ice coverage rate calculation module is used to obtain the ground wire ice coverage rate influence data of the area to be tested, and to construct a ground wire ice coverage rate model based on the polynomial fitting method according to the ground wire ice coverage rate influence data to obtain the ground wire ice coverage rate; A data acquisition module is used to obtain ice impact data, and to construct an ice impact model based on the BP neural network according to the ice impact data; A constraint extraction module is used to obtain the relationship data between the corresponding unit ground line ice thickness and the energy consumed by deicing according to the ground line ice coating rate and the total energy, and obtain the constraint condition of the deicing frequency; The data output module is used to eliminate several different deicing frequencies based on the constraints of the deicing frequency, obtain the output of the icing influence model under the remaining deicing frequencies, construct an output set, and perform data analysis to obtain the optimal deicing frequency.

[0053] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0054] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0055] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0056] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0057] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0058] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A ground wire deicing control method based on distributed energy harvesting, characterized in that: The steps include: Obtain distributed energy collection methods, predict different distributed energy collection methods, and obtain the total energy collected; Obtain the ground wire ice coverage rate influence data of the area to be tested, and construct a ground wire ice coverage rate model based on the polynomial fitting method according to the ground wire ice coverage rate influence data to obtain the ground wire ice coverage rate; Acquire ice impact data, and construct an ice impact model based on the bp neural network according to the ice impact data; According to the ground line ice coating rate and the total energy, the relationship data between the corresponding unit ground line ice coating thickness and the energy consumed by deicing are obtained to obtain the constraint condition of the deicing frequency; Based on the constraints of deicing frequency, several different deicing frequencies are eliminated, the output of the icing influence model under the remaining deicing frequencies is obtained, the output set is constructed, and data analysis is performed to obtain the optimal deicing frequency.

2. The ground wire deicing control method based on distributed energy harvesting according to claim 1 is characterized in that: The ice coverage impact data includes an electrical performance impact coefficient, and the steps for obtaining the electrical performance impact coefficient are as follows: Prepare multiple groups of ice cubes covered on the ground wires to be tested, debug the test environment, and use a conductivity instrument to measure the conductivity of the ice cubes to be tested at different temperatures and the same humidity and at the same temperature and different humidity; According to the relationship data between humidity and conductivity and between temperature and conductivity, the humidity influence coefficient and temperature influence coefficient are obtained based on linear regression analysis; Obtain the type of insulating material in the ground wire to be tested and the rated voltage of the ground wire to be tested, prepare a group of identical insulating materials to be tested, conduct electrical experiments on the materials to be tested, and connect the red and black measuring wires of the insulation resistance meter to the two terminal positions of the ground wire material to be tested respectively; Apply a stable voltage greater than the rated voltage of the ground wire to the material to be tested, wait for a period of time until the discharge phenomenon of the insulating electrode stabilizes, and then obtain the insulation resistance value and test voltage; Obtaining the cross-sectional area of ​​the ground wire material to be tested, and calculating the insulation coefficient of the ground wire material based on a preset insulation coefficient formula of the ground wire material according to the insulation resistance value, the test voltage and the cross-sectional area of ​​the ground wire material; The thickness of the ice layer of the ground wire to be tested and the density of the ice are obtained, and the electrical performance influence coefficient is calculated based on a preset electrical performance influence coefficient formula according to the conductivity of the ice, the humidity influence coefficient, the temperature influence coefficient, the insulation coefficient of the ground wire material, the thickness of the ice layer of the ground wire and the density of the ice to obtain the electrical performance influence coefficient.

3. The ground wire deicing control method based on distributed energy harvesting according to claim 2 is characterized in that: The ice coverage influence data includes a mechanical strength influence coefficient, and the steps for obtaining the mechanical strength influence coefficient are as follows: Obtain a ground wire to be tested, apply a load to the ground wire to be tested until cracks appear on the ground wire and the ground wire stops cracking, and perform a tensile test on the ground wire under different load states, and record the elastic modulus of the ground wire under different load states; The load factor is obtained based on linear analysis according to the relationship data between the ground wire load and the elastic modulus; According to the historical meteorological data of the area to be tested, the annual average wind speed and wind speed distribution are obtained, and according to the geographical conditions of the area to be tested, the wind speed at different heights is obtained based on the CFD model, and the geographical conditions include whether there are mountains and urban layout; Obtain the windward area of ​​the ground line according to the wind direction angle, that is, the area where the wind acts; Obtain the air density, wind speed, dynamic viscosity of the air and characteristic length of the object in the test area, wherein the characteristic length of the object includes the width and thickness of the ice layer, and calculate based on the Reynolds number formula to obtain the air resistance coefficient; The additional load caused by wind is calculated based on the preset additional load formula caused by wind according to the air resistance coefficient, wind speed and the area where wind acts, to obtain the additional load caused by wind; The thickness of the ice layer and the density of the ice covering the ground wire are obtained, and the mechanical strength influence coefficient is calculated based on a preset mechanical strength influence coefficient formula according to the load factor, the additional load caused by wind, the thickness of the ice layer and the density of the ice covering the ground wire.

4. The ground wire deicing control method based on distributed energy harvesting according to claim 3 is characterized in that: The steps for obtaining the ground line ice coverage rate are as follows: Obtain historical meteorological data of the area to be tested and corresponding ground line ice coverage data, and obtain a constant coefficient using the least square method, wherein the ground line ice coverage data includes temperature, humidity, wind speed, and the angle between the wind direction and the ground line; According to the ground wire ice coverage data of the area to be tested, the ground wire ice coverage rate is calculated based on the preset ground wire ice coverage rate formula; According to the parameters in the ground line ice coverage rate formula, a parameter estimation for a future unit time is obtained based on a time series method, and the obtained parameter estimation is input into the ground line ice coverage rate formula to obtain the ground line ice coverage rate for a future unit time.

5. The ground wire deicing control method based on distributed energy harvesting according to claim 4 is characterized in that: According to the ground line ice coating rate and the total energy, the relationship data between the corresponding unit ground line ice coating thickness and the energy consumed by deicing is obtained to obtain the constraint conditions of the deicing frequency, which are specifically as follows: The total ice thickness of the ground wire per unit time is obtained according to the ground wire ice coverage rate, and the deicing frequency per unit time is obtained by dividing the total ice thickness of the ground wire by the single deicing thickness. The deicing frequency is greater than 1 and the single deicing thickness is not higher than the total ice thickness per unit time.

6. The ground wire deicing control method based on distributed energy harvesting according to claim 5 is characterized in that: The constraint condition based on the deicing frequency is used to eliminate several different deicing frequencies, obtain the output of the icing influence model under the remaining deicing frequencies, construct an output set, and perform data analysis to obtain the optimal deicing frequency, as follows: The deicing frequency is multiplied by the energy consumed by a single deicing operation to obtain the total deicing energy consumption, and data whose total deicing energy consumption is higher than the total energy collected per unit time are eliminated; The remaining data is obtained by dividing the total ice thickness per unit time by the single deicing thickness to obtain the remaining deicing frequency data set; The remaining de-icing frequency data is input into the icing influence model for output, an output set is constructed, and data analysis is performed to obtain the highest output result, thereby obtaining the optimal de-icing frequency.

7. The ground wire deicing control method based on distributed energy harvesting according to claim 6 is characterized in that: The calculation formula of the electrical performance influence coefficient is as follows: The calculation formula of the insulation coefficient of the ground wire material is as follows: In the formula, is the electrical performance influence coefficient, is the thickness of the ice layer, is the conductivity of the ice layer, is the density of ice, is the insulation coefficient of the ground wire material, is the temperature influence coefficient, is the humidity influence coefficient, is the insulation resistance value, is the cross-sectional area of ​​the ground wire material, is the test voltage.

8. The ground wire deicing control method based on distributed energy harvesting according to claim 7 is characterized in that: The calculation formula of the mechanical strength influence coefficient is as follows: The calculation formula of the additional load caused by wind force is as follows: The calculation formula of the Reynolds number is as follows: In the formula, is the mechanical strength influence coefficient, is the load factor, is the additional load caused by wind, is the thickness of the ice layer, is the density of ice, is the air resistance coefficient, is the area over which the wind acts, is the wind speed, is the characteristic length of the object, including the width and thickness of the ice layer, is the dynamic viscosity of air.

9. The ground wire deicing control method based on distributed energy harvesting according to claim 8, characterized in that: The calculation formula of the ground line ice coverage rate is as follows: In the formula, is the ground ice coverage rate, is a constant coefficient, is the temperature, is humidity, is the wind speed, It is the angle between the wind direction and the ground.

10. A system using the ground wire deicing control method based on distributed energy harvesting as claimed in any one of claims 1 to 9, characterized in that: It includes an energy prediction module, a ground line ice coverage rate calculation module, a data acquisition module, a constraint condition extraction module and a data output module, and there are connections between the modules; An energy prediction module is used to obtain distributed energy collection methods, predict different distributed energy collection methods, and obtain the total energy collected; The ground wire ice coverage rate calculation module is used to obtain the ground wire ice coverage rate influence data of the area to be tested, and to construct a ground wire ice coverage rate model based on the polynomial fitting method according to the ground wire ice coverage rate influence data to obtain the ground wire ice coverage rate; A data acquisition module is used to obtain ice impact data, and to construct an ice impact model based on the BP neural network according to the ice impact data; A constraint condition extraction module is used to obtain the relationship data between the corresponding unit ground line ice thickness and the energy consumed by deicing according to the ground line ice coating rate and the total energy, and obtain the constraint condition of the deicing frequency; The data output module is used to eliminate several different deicing frequencies based on the constraints of the deicing frequency, obtain the output of the icing influence model under the remaining deicing frequencies, construct an output set, and perform data analysis to obtain the optimal deicing frequency.

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