Grounding resistance regulation method and system based on multi-objective optimization algorithm in permafrost region

Abstract

The application provides a permafrost region grounding resistance regulation method and system based on a multi-objective optimization algorithm, and belongs to the technical field of permafrost region grounding engineering. The method comprises the following steps: collecting project information; adopting a real number coding mode to map an engineering construction scheme and a later regulation scheme into an individual coding vector; setting an engineering boundary condition and a logical relationship between parameters in the individual coding vector; setting a hard constraint condition and an optimization objective function, and screening out invalid solutions; calculating a Pareto front solution set through a multi-objective optimization algorithm; arranging the Pareto front solution set, constructing an evaluation matrix, and calculating a weight vector of the optimization objective through an entropy weight method; weighting the Pareto front solution set evaluation matrix and the weight vector to form a final evaluation vector, and taking a scheme corresponding to a factor with the largest weight value as a recommended engineering scheme; and laying a grounding system according to the recommended engineering scheme, and dynamically regulating the grounding system by real-time detection of soil parameters.

Description

Technical Field

[0001] This invention belongs to the field of grounding engineering technology in permafrost areas, specifically relating to a method and system for grounding resistance control in permafrost areas based on a multi-objective optimization algorithm. Background Technology

[0002] The soil in high-altitude permafrost regions exhibits significant changes in physical properties across different seasons. Prolonged exposure to low temperatures leads to the formation of a permafrost layer, causing a sharp increase in resistivity. This seasonal soil electrical characteristic poses a severe challenge to the design and stable operation of grounding systems. Existing technologies optimize grounding performance using auxiliary resistance-reducing materials such as porous conductive materials and electrolyte solutions. However, these materials can only passively adapt to the permafrost environment and cannot cope with the extreme climatic changes of the plateau. Porous conductive materials cannot prevent secondary freezing of the grounding layer soil during winter, resulting in grounding resistance far exceeding the safety threshold. Electrolyte solutions are easily leached away by rainwater; blindly pursuing resistance reduction can significantly increase construction costs. Excessive use of electrolyte solutions can also accelerate the corrosion of metal grounding electrodes and cause soil salinization. Furthermore, the difficulty of excavating permafrost hinders construction progress and reduces efficiency. Currently, there is a lack of seasonal optimization strategies for construction in permafrost regions.

[0003] Chinese invention patent application CN116542014A discloses an optimization design method for the grounding resistance of transmission line towers based on particle swarm optimization (PSO) algorithm. The method uses PSO to generate a random initial particle swarm. During iteration, the position and velocity of the particle swarm are updated based on the historical best values ​​and positions of the particles, thereby finding the global optimal solution. This global optimal solution is then transformed into soil resistivity classification and grounding resistance values ​​as an optimized design scheme for the grounding resistance. This approach can reduce the cost of grounding resistance while ensuring that the tripping rate of the transmission line meets requirements. However, this application does not consider the multi-objective collaborative balance of engineering projects in permafrost areas, making it difficult to meet the needs of grounding systems in permafrost regions.

[0004] Chinese invention patent application CN120414195A discloses a method, application, and grounding grid structure for grounding grid resistance reduction engineering in plateau permafrost areas. Through the innovative application of liquid flexible resistance reduction materials and precise targeted optimization strategies, it achieves an organic unity of high-efficiency resistance reduction, extreme environment adaptability, construction flexibility, and economic benefits, effectively solving the safety hazards caused by the high resistivity of grounding grids in plateau permafrost areas. However, this application mainly focuses on the analysis and optimization of the grounding grid leakage distribution of liquid flexible resistance reduction materials, and does not involve the active control of grounding resistance. Summary of the Invention

[0005] To address the problems in the prior art, this invention proposes a grounding resistance control method and system for permafrost regions based on a multi-objective optimization algorithm. By constructing a multi-objective optimization algorithm adapted to grounding projects in permafrost regions, the cost is optimized to the minimum while meeting the grounding resistivity standards for permafrost regions. At the same time, the electrolyte output is actively controlled to avoid soil salinization, extend the effective period of resistance reduction, and reduce the maintenance frequency.

[0006] The technical solution of the present invention is as follows: In a first aspect, the present invention provides a method for regulating grounding resistance in permafrost areas based on a multi-objective optimization algorithm, comprising the following steps: Collect information on engineering projects, including engineering technical requirements, meteorological conditions, site conditions, and construction conditions; Using real number encoding, the engineering construction plan and the post-construction control plan are mapped to individual encoding vectors, and the individual encoding vectors are used as the search individuals for the multi-objective optimization algorithm; Set engineering boundary conditions and logical relationships between parameters in the individual encoding vector; Set hard constraints and objective functions for the optimization algorithm, and eliminate invalid solutions based on the hard constraints; The Pareto front solution set is obtained by iteratively calculating the individual encoding vectors using a multi-objective optimization algorithm. All Pareto front solutions are organized, an evaluation matrix is ​​constructed, and the entropy weight method is used to calculate the weights of the optimization objectives to obtain a weight vector. The final evaluation vector is formed by weighting the Pareto front solution set evaluation matrix and the weight vector. The solution corresponding to the factor with the largest weight in the final evaluation vector is taken as the recommended engineering solution. The grounding system is laid according to the recommended engineering plan, and the grounding system is dynamically adjusted by monitoring soil parameters in real time.

[0007] Furthermore, the individual encoding vector X = [x1, x2, x3, x4, x5, x6, x7, x8]; x1 is the burial depth of the grounding electrode; x2 is the burial area of ​​the grounding electrode; x3 is the material and layout of the grounding electrode; x4 is the type of electrolyte; x5 is the initial amount of electrolyte added; x6 is the dynamic adjustment threshold of the electrolyte; x7 is the start and end time of construction; x8 is the configuration of construction labor and materials. x3, x4, and x7 are discrete parameters that are converted into real numbers through numerical mapping. In the multi-objective optimization process, the principle of integer mapping invariance is adopted to perform crossover and mutation operations.

[0008] Furthermore, the construction start and end times x7 are mapped using the start date sequence number, and the boundary values ​​for the construction period are set to [T0, T0+T]. constructionT0 is the date when the grounding system construction began, T construction The time required for construction; Set the earliest construction date T to avoid the freezing period. ready and the latest deadline T end T ready >0, and satisfy T0≥T ready and T ready +T construction <T end At the same time, a tolerance range of preset days is introduced for the construction period.

[0009] Furthermore, the hard constraints include a first constraint, a second constraint, and a third constraint; The first constraint is R ≤ R design R is the grounding resistance of the engineering scheme. design This refers to the design requirement value for grounding resistance; The second constraint is [T] ready , T ready +T construction ]∩[T frozen-s , T frozen-e ]=ø,T ready The earliest construction date, T construction For the time required for construction, T frozen-s T represents the start time of the permafrost period. frozen-e This refers to the end of the permafrost period; The third constraint is E≤E standard E represents the environmental indicators for the electrolyte and supporting environmental protection measures in the engineering scheme, including heavy metal residues, soil pollution index, and groundwater impact. standard To meet environmental standards; An engineering solution that does not meet any of the hard constraints will be deemed an invalid solution.

[0010] Furthermore, the optimization objective function takes cost minimization as its objective, and the objective function is: C = min(C1 + C2 + C3); Where C represents the total project cost; C1 represents the electrolyte procurement cost; C2 represents the direct construction cost; and C3 represents the electrolyte dynamic control cost.

[0011] Furthermore, the evaluation matrix B=(b) of the Pareto front solution set ij ) w×n w is the number of Pareto front solutions, and n is the number of optimization objectives; Optimization targets include grounding resistance b i1 Construction cycle redundancy b i2 Environmental protection indicators b i3 and comprehensive costs bi4 ; After constructing the evaluation matrix B, it is normalized to form the matrix nsga. ij Expressed as a formula: .

[0012] Furthermore, the construction cycle margin b i2 Expressed as a formula: b i2 =e i / (T frozen-s -T ready ); e i =T frozen-s -(T ready +T construction-i ); Among them, e i T is the time interval between the end of construction and the start of the frozen soil period. construction-i The construction time required for the i-th Pareto solution; T frozen-s T is the start time of the permafrost period. ready The earliest construction date.

[0013] Furthermore, the entropy weight method is used to calculate the weights of the optimization objectives, and an expert evaluation matrix U=(u ij ) n×m n is the target number, and m is the number of experts conducting the human evaluation; The calculation of the weight vector specifically includes: The expert evaluation matrix U is normalized to form a standardized evaluation matrix P=(p ij ) n×m The normalization process is expressed by the formula: ; Among them, min(u j ) represents the minimum importance score for the j-th expert; max(u j ) represents the highest importance score for the j-th expert; Find the information entropy of matrix P, forming the information entropy vector Q=q. i Expressed as a formula: ; ; Calculate the weight vector H=h based on the information entropy vector. i Expressed as a formula: .

[0014] Secondly, this invention provides a grounding resistance control system for permafrost areas based on a multi-objective optimization algorithm, the system comprising: The grounding electrode module includes a horizontal grounding electrode and a vertical grounding electrode, wherein the horizontal grounding electrode and the vertical grounding electrode are hollow grounding electrodes used for conveying water and electrolyte liquid; The real-time soil parameter monitoring module is used to monitor soil temperature, moisture content, salinity, and resistivity. The data communication transmission module is used to collect soil parameters and upload them to the cloud data server via GPRS wireless communication; The intelligent management platform for the grounding system generates dynamic control commands by executing multi-objective optimization algorithms through the data processing unit and combining them with the actual soil and climate conditions of the environment. The electrolyte dynamic dosing module executes dynamic control commands to adjust the discharge volume of water or electrolyte solution; The system power supply module provides power to the system.

[0015] Furthermore, the grounding electrode is made of porous graphite material; the electrolyte solution is made of calcium magnesium acetate.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention constructs a multi-objective optimization algorithm adapted to grounding engineering in permafrost areas. Under the premise of meeting the grounding resistivity standard in permafrost areas, it optimizes the early engineering cost and the later system control cost to the minimum. The grounding grid is laid by assembling prefabricated grounding bodies and installing distributed soil sensors attached to the grounding bodies to collect soil parameters in real time and dynamically control the replenishment of electrolytes. Active regulation of electrolyte output can prevent excessive electrolyte solution from causing soil salinization and aggravating corrosion of metal grounding bodies. Weather monitoring can reduce the amount of electrolyte lost through leaching with rainwater, while also extending the effective period of resistance reduction and reducing maintenance frequency. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a method for regulating grounding resistance in permafrost regions based on a multi-objective optimization algorithm. Figure 2 This is a graph showing the relationship between soil temperature and time during the soil freezing process. Figure 3 This is a schematic diagram of a grounding resistance control system for permafrost regions based on a multi-objective optimization algorithm. Figure 4 This is a diagram of a grounding resistance control system architecture for permafrost regions based on a multi-objective optimization algorithm. Detailed Implementation

[0018] 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 a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0019] Example 1 This embodiment provides a method for controlling grounding resistance in permafrost areas based on a multi-objective optimization algorithm, such as... Figure 1 As shown, it includes the following steps: S1. Gather project information for solution development, including: Engineering technical requirements should clearly define engineering needs, including grounding resistance requirements, step voltage requirements, contact potential requirements, construction period, and project milestone plans. Meteorological conditions, including rainfall data, historical permafrost depth, historical permafrost temperature, and historical soil salinity in the project area; Site conditions, clearly defining the scope of the construction site and the geological conditions within that area; Construction conditions, including construction window period, construction labor costs, construction machinery costs, grounding material parameters, and grounding material prices; S2. Using real-number encoding, each complete engineering construction plan and post-construction control plan is mapped to an individual encoding vector. This individual encoding vector is compatible with NSGA-III genetic operations and fully covers the engineering parameters. Specifically, the mapping to individual encoding vectors is as follows: The individual encoding vector X = [x1, x2, x3, x4, x5, x6, x7, x8] has the following specific meanings for each parameter: x1 is the burial depth of the grounding electrode. This parameter is a continuous real number and is constrained by the electrolyte optimization effect and the depth of frozen soil. It is a core engineering parameter. x2 represents the buried area of ​​the grounding electrode. This parameter is a continuous real number and is constrained by the area that can be used to install the grounding electrode. It is a core engineering parameter. x3 represents the material and arrangement of the grounding electrode. This parameter maps discrete parameters to real numbers and relates to the grounding resistance compliance and direct construction costs. x4 represents the electrolyte type. This parameter maps discrete parameters to real numbers and relates them to environmental compliance and costs. x5 represents the initial amount of electrolyte added. This parameter is a continuous real number and is associated with the optimization of soil secondary freezing temperature and the achievement of grounding resistance standards. x6 is the electrolyte dynamic adjustment threshold. This parameter is a continuous real number, including the lower limit of water content and the upper limit of salinity, and is associated with the feasibility of active regulation. x7 represents the start and end times of construction. This parameter maps discrete parameters to real numbers and is used to determine whether to avoid the freezing period. x8 represents the construction labor and material configuration. This parameter can be a continuous or discrete real number and is associated with the total construction cost. S3. Set reasonable engineering boundary conditions and logical relationships for each parameter of the individual encoding vector in step S2. The specific construction of the parameter association logic is as follows: S31, The boundary value of the grounding electrode burial depth x1 is set as follows: H max This is the maximum excavation depth for the construction equipment. This represents the critical depth for initial soil freezing. During the calculation process, adjustments are needed depending on the composition of each soil layer and the amount of electrolyte added. The corrected formula is as follows: ; in, To correct the critical depth of soil freezing before; x5 represents the corrected critical depth for soil freezing; k1 is the electrolyte correction coefficient; x5 is the initial amount of electrolyte added. The electrolyte correction factor k1 is calculated based on the salinity profile added as needed. Appropriate salinity profiles are selected according to different soil layers to reduce invalid solutions. The laying depth should not be less than 0.8m below the normal laying depth; The relationship between soil temperature and depth can be approximated as follows: as depth increases arithmetically, the amplitude decreases geometrically until the isothermal layer. Therefore, by combining soil materials and using the function of resistivity with temperature and depth, the corresponding temperature at each depth of the soil at a certain time of the year can be predicted. S32, The boundary value of the grounding electrode burial area x2 is set to [S0, S... max ], S max S0 represents the maximum area that can be obtained for grounding under the project conditions, and is the area of ​​the grounding grid under the condition that the grounding device is normally laid at a depth of 0.8m without the influence of frost. The calculation method is as follows: The formula for calculating the grounding resistance of a composite grounding electrode with a horizontal grounding electrode and a closed main edge in uniform soil is as follows: ; ; ; ; in, The grounding resistance of a grounding grid with an arbitrary shaped edge; The grounding resistance of the equivalent square grounding grid; This is the shape correction factor; SThe total area of ​​the grounding grid; This refers to the total length of the outer edge of the grounding grid; Soil resistivity; L This is the total length of the horizontal grounding electrode; The burial depth of the horizontal grounding electrode; The diameter or equivalent diameter of the horizontal grounding electrode; This is the burial depth correction factor; S33, Grounding electrode material and layout form x3: In order to avoid compatibility issues in the genetic operation and to facilitate the reverse mapping of subsequent results into engineering terms, different grounding electrode materials and layout forms are converted into real numbers through explicit numerical mapping. The specific conversion relationship is shown in Table 1.

[0020] S34 and electrolyte type x4 are also converted into real numbers through numerical mapping, and the conversion relationship is shown in Table 2.

[0021] S35, Initial electrolyte addition amount x5 is based on the initial freezing temperature T of the frozen soil. f and the secondary freezing temperature T s Calculate the amount to add, such as Figure 2 As shown, the soil freezing process can be described as follows: In stage AB, as the freezing time increases, the soil temperature gradually decreases to the supercooled temperature, but the water does not freeze. This is because freezing of water in the soil requires the formation of crystallization centers dominated by soil particles, which requires a temperature lower than the freezing temperature. Stage BC is the abrupt change stage, where water in the soil forms ice crystals around the crystallization centers. Stage CD is the equilibrium stage, and the corresponding temperature is called the soil freezing temperature T. f The first freezing temperature, or E, marks the initial freezing point, where free water in the soil begins to freeze, releasing latent heat during the phase transition. The DE segment represents the cooling stage, where the soil temperature continues to decrease. After point E, only a small amount of bound water remains unfrozen. Bound water is formed by the attraction of water near soil particles to the electrostatic forces on the particle surfaces. During freezing, it must overcome not only the attraction between water molecules but also the molecular attraction on the soil particle surfaces, resulting in an even lower freezing temperature. When a sharp drop in the unfrozen water content occurs, the corresponding temperature is called the second freezing temperature, T. s The higher the soil moisture content, the higher the T f and T s The higher the temperature, the higher the salt content. f and T s The lower; The boundary value of the initial electrolyte addition amount x5 is set as follows: , The original salinity of the soil, S maxTo determine the maximum soil salinity under environmental restrictions, the electrolyte addition amount is related to x1, x2, x3, and x4, determined by a preset function. The relationship, expressed as a formula, is as follows: ; Among them, C a The addition amount is a positive coefficient; S36, Electrolyte Dynamic Adjustment Threshold x6 is a numerical range for dynamically controlling the amount of electrolyte liquid added based on the water content and salinity data collected by the soil sensor and combined with real-time meteorological data prediction. This reduces waste caused by the loss of electrolyte liquid due to excessive addition at one time. It can also be intelligently controlled according to meteorological conditions to avoid adding electrolyte before rainfall or adding electrolyte before a significant drop in temperature. The electrolyte dynamic addition system can be implemented by setting up a buried dosing system to avoid the problem of ground liquid freezing due to low temperature. The dosing system can be powered by electricity from thermal power plants, substations, new energy stations, or independent photovoltaic charging systems. The electrolyte liquid is transported through a hollow grounding electrode and discharged through the discharge ports at each connection point of the grounding device. Sensors are installed at the discharge ports to upload the detection data to the cloud in real time and feed it back to the host, or the data can be transmitted through a General Packet Radio Service (GPRS) network. The amount of electrolyte liquid added is dynamically adjusted according to the feedback results. S37. The construction start and end times x7 are mapped using the start date sequence number. The first day after the contract takes effect is numbered 1, and subsequent dates are numbered sequentially. The boundary value of the construction period is set as [T0, T0+T]. construction T0 represents the date the grounding single-phase construction began relative to the first day the contract took effect. construction T is the total time required for the entire grounding single-phase construction. construction Related to x1, x2, and x3, expressed by the formula: ; Wherein, k2 is a positive coefficient for the burial depth of the grounding electrode; k3 is a positive coefficient for the burial area of ​​the grounding electrode; k4 is a positive coefficient for the material and arrangement of the grounding electrode; C t It is a positive coefficient for construction duration; T ready The earliest construction date, T ready >0, and T0 is not less than T ready T end The contract deadline is T. ready +T construction <T end When determining whether the construction period coincides with the frozen soil period, a preset number of days of tolerance is set. S38, the boundary values ​​for construction labor and material allocation x8 are set to [M0, M... maxM0 represents the minimum required construction labor and material configuration under unconstrained conditions. max To determine the maximum manpower and material allocation for the construction site that can accommodate the largest working area, x8 is related to x1, x2, x4, and x7, and is determined through a preset function. The relationship, expressed as a formula, is as follows: ; Among them, C m Positive coefficients should be allocated to construction labor and materials; S4. Set hard constraints and optimization objective functions for the optimization algorithm to ensure that the solution output by the algorithm meets the engineering baseline requirements and has optimization value; The hard constraints include a first constraint, a second constraint, and a third constraint, where the first constraint is R ≤ R. design R is the grounding resistance of the engineering scheme. design This refers to the design requirement value for grounding resistance; The second constraint is [T] ready , T ready +T construction ]∩[T frozen-s , T frozen-e ]=ø,T ready The earliest construction date, T construction For the time required for construction, T frozen-s T represents the start time of the permafrost period. frozen-e This refers to the end of the permafrost period; The third constraint is E≤E standard E represents the environmental indicators for the electrolyte and supporting environmental protection measures in the engineering scheme, including heavy metal residues, soil pollution index, and groundwater impact. standard To meet environmental standards; If an engineering solution fails to meet any of the hard constraints, it will be deemed an invalid solution and eliminated to improve algorithm efficiency. The core optimization objective of the aforementioned objective function is cost minimization. All parameters in the individual encoding vector that affect cost are incorporated into the cost calculation model. The objective function is: C = min(C1 + C2 + C3); Where C represents the total project cost; C1 represents the electrolyte procurement cost; C2 represents the direct construction cost; and C3 represents the electrolyte dynamic control cost. Electrolyte procurement cost C1 is positively correlated with electrolyte type and initial electrolyte addition amount; direct construction cost C2 is positively correlated with grounding electrode burial depth, grounding electrode burial area, grounding electrode material and layout, construction start and end time, construction labor and material configuration; electrolyte dynamic control cost C3 is related to electrolyte dynamic adjustment threshold, soil monitoring frequency and electrolyte liquid replenishment amount. S5. The NSGA-III algorithm is used to perform multi-objective optimization calculations on the parameters in the individual encoding vector, and the Pareto front solution set is obtained by iterative search. Preferably, the population size for multi-objective optimization computation is set to 50-100, the number of iterations is 100-200, the crossover probability is set to 0.7-0.9, the mutation probability is set to 0.01-0.05, and the number of iterations does not exceed 500. Preferably, the crossover and variation operations of grounding electrode material and layout, electrolyte type and construction start and end time adopt the principle of integer mapping invariance to avoid invalid coding; S6. Process the Pareto front solution set, organize all Pareto front solutions, and form a matrix B based on the number of optimization objectives, B=(b ij ) w×n w is the number of Pareto front solutions, and n is the number of optimization objectives; Preferably, the optimization objectives specifically include four types: grounding resistance, construction cycle redundancy, environmental protection indicators, and comprehensive costs. The elements of these four optimization objectives in matrix B are processed, specifically including: Grounding resistance R is within the allowable value R design As the baseline value, b i1 =1-R i / R design R i Let be the grounding resistance value of the i-th Pareto solution; To avoid the freezing period, a construction cycle redundancy is set at a time interval e between the end of construction and the start of the freezing period. i Expressed as a formula: e i =T frozen-s -(T ready +T construction-i ); Among them, T construction-i The construction time required for the i-th Pareto solution; b i2 =e i / (T frozen-s -T ready ); e i The larger b i2 The larger the value, the greater the safety margin during construction; Element b of environmental protection indicators i3 =1-E i / E standard E i For the i-th Pareto solution, the environmental indicator is... Element b of comprehensive cost i4 Expressed as a formula: ; in, Let i' be the i'th type of project cost; N is the number of project cost types. Normalize matrix B to form matrix nsga ij Expressed as a formula: ; S7. Weight each objective using the entropy weighting method. Since the solution set obtained by the NSGA-III algorithm is not unique, an evaluation system is needed to determine the engineering solution. The three constraint objectives under hard constraints and one optimization objective of the optimization function are manually evaluated. The importance of each objective is scored according to a pre-defined scaling method, forming an expert evaluation matrix U=(u ij ) n×m n is the target number, and m is the number of experts conducting the human evaluation; The expert evaluation matrix U is normalized to form a standardized evaluation matrix P=(p ij ) n×m The normalization process is expressed by the formula: ; Among them, min(u j ) represents the minimum importance score for the j-th expert; max(u j ) represents the highest importance score for the j-th expert; Find the information entropy of matrix P, forming the information entropy vector Q=q. i Expressed as a formula: ; ; When t ij When q = 0, define q at this time. i =0; Calculate the weight vector H=h based on the information entropy vector. i Expressed as a formula: ; S8. Normalize the Pareto front solution set obtained in step S6 to the matrix nsga. ij and the weight vector h obtained in step S7 i The weighted averages form the final evaluation vector S, expressed by the formula: S=s i =nsga ij ·h i ; The factor s with the largest weight in the final evaluation vector S i The corresponding solution is the recommended engineering solution; S9. Lay the grounding system according to the recommended engineering plan. After the construction is completed, monitor the soil parameters in real time, compare them with the calculation results of the multi-objective optimization algorithm, generate control instructions for the grounding system, and realize the optimized operation of the grounding system.

[0022] Example 2 This embodiment provides a grounding resistance control system for permafrost areas based on a multi-objective optimization algorithm, such as... Figure 3 and Figure 4 As shown, the system includes: The grounding electrode module includes a horizontal grounding electrode and a vertical grounding electrode, wherein the horizontal grounding electrode and the vertical grounding electrode are hollow grounding electrodes used for conveying water and electrolyte liquid; The real-time soil parameter monitoring module is used to monitor soil temperature, moisture content, salinity, and resistivity. The data communication transmission module is used to collect soil parameters and upload them to the cloud data server via GPRS wireless communication; The intelligent management platform for the grounding system generates dynamic control commands by executing multi-objective optimization algorithms through the data processing unit and combining them with the actual soil and climate conditions of the environment. The electrolyte dynamic dosing module executes dynamic control commands to adjust the discharge volume of water or electrolyte solution; The system power supply module provides power to the system.

[0023] Preferably, the grounding electrode is made of porous graphite material. Porous graphite material not only increases the conductive interface, but also serves as a storage carrier for electrolyte liquid. The slow-release effect of porous graphite material can release electrolyte slowly, prolong the resistance reduction period, and reduce the maintenance frequency. The electrolyte solution uses calcium magnesium acetate, which can prevent soil salinization and reduce the corrosion rate of metal grounding bodies, reducing it by more than 60% compared to traditional resistance-reducing agents.

[0024] Preferably, the power source is electricity from thermal power plants, substations, new energy stations, or independently installed small-scale photovoltaic charging systems.

[0025] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structure made using the contents of the present invention specification and drawings, or directly or indirectly applied to other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for regulating grounding resistance in permafrost areas based on a multi-objective optimization algorithm, characterized in that, Includes the following steps: Collect information on engineering projects, including engineering technical requirements, meteorological conditions, site conditions, and construction conditions; Using real number encoding, the engineering construction plan and the post-construction control plan are mapped to individual encoding vectors, and the individual encoding vectors are used as the search individuals for the multi-objective optimization algorithm; Set engineering boundary conditions and logical relationships between parameters in the individual encoding vector; Set hard constraints and objective functions for the optimization algorithm, and eliminate invalid solutions based on the hard constraints; The Pareto front solution set is obtained by iteratively calculating the individual encoding vectors using a multi-objective optimization algorithm. All Pareto front solutions are organized, an evaluation matrix is ​​constructed, and the entropy weight method is used to calculate the weights of the optimization objectives to obtain a weight vector. The final evaluation vector is formed by weighting the Pareto front solution set evaluation matrix and the weight vector. The solution corresponding to the factor with the largest weight in the final evaluation vector is taken as the recommended engineering solution. The grounding system is laid according to the recommended engineering plan, and the grounding system is dynamically adjusted by monitoring soil parameters in real time.

2. A method for regulating grounding resistance in permafrost areas based on a multi-objective optimization algorithm according to claim 1, characterized in that, The individual encoding vector X = [x1, x2, x3, x4, x5, x6, x7, x8]; x1 is the burial depth of the grounding electrode; x2 is the burial area of ​​the grounding electrode; x3 is the material and layout of the grounding electrode; x4 is the type of electrolyte; x5 is the initial amount of electrolyte added; x6 is the dynamic adjustment threshold of the electrolyte; x7 is the start and end time of construction; x8 is the configuration of construction labor and materials. x3, x4, and x7 are discrete parameters that are converted into real numbers through numerical mapping. In the multi-objective optimization process, the principle of integer mapping invariance is adopted to perform crossover and mutation operations.

3. A method for regulating grounding resistance in permafrost areas based on a multi-objective optimization algorithm according to claim 2, characterized in that, The construction start and end times x7 are mapped using the start date sequence number, and the boundary values ​​for the construction period are set to [T0, T0+T]. construction T0 is the date when the grounding system construction began, T construction The time required for construction; Set the earliest construction date T to avoid the freezing period. ready and the latest deadline T end T ready >0, and satisfy T0≥T ready and T ready +T construction <T end At the same time, a tolerance range of preset days is introduced for the construction period.

4. The method for regulating grounding resistance in permafrost areas based on a multi-objective optimization algorithm according to claim 1, characterized in that, The hard constraints include a first constraint, a second constraint, and a third constraint; The first constraint is R ≤ R design R is the grounding resistance of the engineering scheme. design This refers to the design requirement value for grounding resistance; The second constraint is [T] ready , T ready +T construction ]∩[T frozen-s , T frozen-e ]=ø,T ready The earliest construction date, T construction For the time required for construction, T frozen-s T represents the start time of the permafrost period. frozen-e This refers to the end of the permafrost period; The third constraint is E≤E standard E represents the environmental indicators for the electrolyte and supporting environmental protection measures in the engineering scheme, including heavy metal residues, soil pollution index, and groundwater impact. standard To meet environmental standards; An engineering solution that does not meet any of the hard constraints will be deemed an invalid solution.

5. A method for regulating grounding resistance in permafrost areas based on a multi-objective optimization algorithm according to claim 1, characterized in that, The optimization objective function aims to minimize cost, and the objective function is as follows: C = min(C1 + C2 + C3); Where C represents the total project cost; C1 represents the electrolyte procurement cost; C2 represents the direct construction cost; and C3 represents the electrolyte dynamic control cost.

6. A method for regulating grounding resistance in permafrost areas based on a multi-objective optimization algorithm according to claim 1, characterized in that, The evaluation matrix B=(b) of the Pareto front solution set ij ) w×n w is the number of Pareto front solutions, and n is the number of optimization objectives; Optimization targets include grounding resistance b i1 Construction cycle redundancy b i2 Environmental protection indicators b i3 and comprehensive costs b i4 ; After constructing the evaluation matrix B, it is normalized to form the matrix nsga. ij Expressed as a formula: 。 7. A method for regulating grounding resistance in permafrost areas based on a multi-objective optimization algorithm according to claim 6, characterized in that, The construction period margin b i2 Expressed as a formula: b i2 =e i / (T frozen-s -T ready ); e i =T frozen-s -(T ready +T construction-i ); Among them, e i T is the time interval between the end of construction and the start of the frozen soil period. construction-i The construction time required for the i-th Pareto solution; T frozen-s T is the start time of the permafrost period. ready The earliest construction date.

8. A method for regulating grounding resistance in permafrost areas based on a multi-objective optimization algorithm according to claim 1, characterized in that, The entropy weight method is used to calculate the importance of the optimization objective, and an expert evaluation matrix U=(u) is formed by human evaluation of the optimization objective. ij ) n×m n is the target number, and m is the number of experts conducting the human evaluation; The calculation of the weight vector specifically includes: The expert evaluation matrix U is normalized to form a standardized evaluation matrix P=(p ij ) n×m The normalization process is expressed by the formula: ； Among them, min(u j ) represents the minimum importance score for the j-th expert; max(u j ) represents the highest importance score for the j-th expert; Find the information entropy of matrix P, forming the information entropy vector Q=q. i Expressed as a formula: ； ； Calculate the weight vector H=h based on the information entropy vector. i Expressed as a formula: 。 9. A grounding resistance control system for permafrost areas based on a multi-objective optimization algorithm, characterized in that, The system includes: The grounding electrode module includes a horizontal grounding electrode and a vertical grounding electrode, wherein the horizontal grounding electrode and the vertical grounding electrode are hollow grounding electrodes used for conveying water and electrolyte liquid; The real-time soil parameter monitoring module is used to monitor soil temperature, moisture content, salinity, and resistivity. The data communication transmission module is used to collect soil parameters and upload them to the cloud data server via GPRS wireless communication; The intelligent management platform for the grounding system generates dynamic control commands by executing multi-objective optimization algorithms through the data processing unit and combining them with the actual soil and climate conditions of the environment. The electrolyte dynamic dosing module executes dynamic control commands to adjust the discharge volume of water or electrolyte solution; The system power supply module provides power to the system.

10. The grounding resistance control system for permafrost areas based on a multi-objective optimization algorithm according to claim 9, characterized in that, The grounding electrode is made of porous graphite material; The electrolyte solution is calcium magnesium acetate.

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