An intelligent topology design method for middle-deep geothermal pipe group layout

Abstract

The application discloses an intelligent topological design method for a middle-deep geothermal pipe group layout, which comprises the following steps: obtaining geothermal geological parameters and geothermal indexes of a region to be designed, performing space division and constructing a geothermal balance evaluation index system, calculating a geothermal balance score of the region to be designed, obtaining historical data of a geothermal pipe group to construct a geothermal pipe group database, performing heat exchange simulation on a topological model of the geothermal pipe group to obtain a topological optimization coefficient, determining a topological design target function and a topological design constraint condition of the geothermal pipe group, performing multi-level matching to obtain a reference geothermal pipe group topological structure, and optimizing the reference geothermal pipe group topological structure according to the topological design target function of the geothermal pipe group to obtain an optimal geothermal pipe group topological structure. The method can significantly improve the extraction efficiency of geothermal energy and the economy of a geothermal system, and is of great significance to the intelligent development of the layout design of the geothermal pipe group.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of geothermal energy, in particular to an intelligent topology design method for middle-deep geothermal pipe group layout. BACKGROUND

[0002] With the increasing global energy demand and the growing emphasis on environmental protection, middle-deep geothermal energy as a renewable and clean energy, its efficient development and utilization has extremely key significance for realizing energy structure optimization and sustainable development. As the core facility of geothermal energy development, the reasonable layout design of middle-deep geothermal pipe group is directly related to the extraction efficiency of geothermal energy and the economy and stability of the whole system.

[0003] The traditional geothermal pipe group layout design method has many shortcomings: first, it lacks fine analysis and spatial differentiation of geothermal geological parameters, and cannot accurately evaluate the geothermal balance state of different regions, making it difficult to realize effective matching of geothermal pipe group layout and geological characteristics; second, it fails to fully utilize historical data, and lacks systematic summary and mining of the performance of geothermal pipe group under different working conditions, making it difficult to accurately design topology according to specific project requirements; finally, most of the existing design methods are based on single-objective optimization model, and it is difficult to realize globally optimal geothermal pipe group layout scheme under multi-objective constraint conditions. Therefore, the present application proposes an intelligent topology design method for middle-deep geothermal pipe group layout, which obtains the geothermal balance score of the designed region by spatial division of the designed region and construction of a geothermal balance evaluation index system, establishes a geothermal pipe group database using historical data to form a data-driven design reference benchmark, obtains topology optimization coefficients through heat exchange simulation to construct objective function and constraint conditions, and realizes rapid and accurate optimization of geothermal pipe group topology structure based on multi-level matching and multi-objective adaptive optimization algorithm. This technology breaks through the limitations of traditional design, significantly improves the scientificity and adaptability of geothermal pipe group layout, and has important practical value for promoting efficient development and utilization of middle-deep geothermal resources. SUMMARY

[0004] The purpose of the present application is to provide an intelligent topology design method for middle-deep geothermal pipe group layout.

[0005] To achieve the above purpose, the present application is implemented according to the following technical solutions:

[0006] The present application comprises the following steps:

[0007] Obtain the geothermal geological parameters and geothermal indicators of the designed region, divide the designed region according to the geothermal geological parameters, construct a geothermal balance evaluation index system, and calculate the geothermal balance score of the designed region according to the spatial division results, the geothermal indicators and the geothermal balance evaluation index system;

[0008] Obtaining geothermal pipe group historical data, calculating the geothermal balance historical score of the historical area, and constructing a geothermal pipe group database according to the geothermal balance historical score and the geothermal pipe group historical data; the geothermal pipe group historical data includes geothermal pipe group state historical data and geothermal pipe group topology historical structure;

[0009] Performing geothermal pipe group topology model heat exchange simulation to obtain a topology optimization coefficient, determining a geothermal pipe group topology design objective function according to the topology optimization coefficient, and determining a geothermal pipe group topology design constraint condition according to the geothermal index;

[0010] According to the geothermal pipe group topology design objective function, performing multi-objective adaptive full-area fast optimization on the reference geothermal pipe group topology structure to obtain an optimal geothermal pipe group topology structure.

[0011] According to the geothermal pipe group topology design objective function, performing multi-objective adaptive full-area fast optimization on the reference geothermal pipe group topology structure to obtain an optimal geothermal pipe group topology structure.

[0012] Further, the method for spatially dividing the area to be designed comprises:

[0013] Dividing the area to be designed into a plurality of horizontal regions by 10m*10m on a horizontal plane;

[0014] Dividing each horizontal region into longitudinal units every 500m along the depth direction, calculating the change coefficient of the geothermal geological parameters of each longitudinal unit and the corresponding dynamic threshold value, and the expression is:

[0015]

[0016]

[0017] wherein is the change coefficient of the geothermal geological parameters of the longitudinal unit in the horizontal region , includes permeability, thermal conductivity, porosity and ground temperature, is the maximum value of the geothermal geological parameters in the corresponding unit , is the minimum value of the geothermal geological parameters in the corresponding unit , is the average value of the geothermal geological parameters in the corresponding unit , is the dynamic threshold value of the change coefficient of the geothermal geological parameters of the longitudinal unit in the horizontal region , is the dynamic threshold value of the change coefficient of the geothermal geological parameters of the longitudinal unit in the horizontal region , is the dynamic threshold value of the change coefficient of the geothermal geological parameters of the longitudinal unit in the horizontal region , is the dynamic threshold value of the change coefficient of the geothermal geological parameters of the longitudinal unit in the horizontal region The standard threshold value of the coefficient of variation, is the depth coefficient, For horizontal area Inner longitudinal unit The average depth of is the maximum depth of the buried pipe;

[0018] When the coefficient of variation of any two geothermal geological parameters exceeds the corresponding threshold, the corresponding vertical unit is subdivided to obtain a vertical subunit, and the vertical subunit is defined as an evaluation area. Otherwise, the vertical unit does not need to be subdivided, and the corresponding vertical unit is defined as an evaluation area. The step of obtaining the vertical subunit is to select the extreme value point position of the coefficient of variation of the geothermal geological parameter as the subdivision position, and divide the vertical subunit with the subdivision position as the center. The expression is:

[0019]

[0020] in For horizontal area Inner longitudinal unit New subdivision location within;

[0021] Output the spatial division results according to all evaluation areas.

[0022] Furthermore, the method for calculating the geothermal balance score of the area to be designed includes the following steps:

[0023] Geothermal indicators are organized into an evaluation factor set. A bag-of-words model is used to obtain importance judgments between factors within the evaluation factor set. Values ​​are assigned based on the importance judgment results to obtain importance comparison scores. A judgment matrix is ​​constructed based on the importance comparison scores. The inconsistency of the judgment matrix is ​​verified and geothermal indicator weights are obtained. The geothermal indicators include the total amount of heat storage resources, the available amount of heat storage and its utilization efficiency, cross-seasonal heat storage and its utilization efficiency, and the heat storage flow field, temperature field, and pressure field.

[0024] The geothermal index is input into the membership function to obtain the geothermal index score. The geothermal balance score of the corresponding evaluation area is calculated according to the geothermal index score and the geothermal index weight. The geothermal balance score of the area to be designed is obtained by accumulating the geothermal balance scores of all evaluation areas.

[0025] Furthermore, the method for determining the geothermal pipe group topology design objective function and determining the geothermal pipe group topology design constraint conditions includes:

[0026] A geothermal pipe group topology model is constructed using historical data on the geothermal pipe group topology structure, and a heat exchange simulation is performed in combination with a primitive library to obtain a first simulated outlet water temperature. The geothermal pipe group topology model is optimized based on the deviation of the first simulated outlet water temperature and the historical outlet water temperature. The geothermal pipe group topology structure is changed based on a control variable method, and a heat exchange simulation is performed using the optimized heat pipe group topology model to obtain a second simulated outlet water temperature. The geothermal pipe group topology structure includes the shape and size of the buried pipes, the connection method, and the distance between the pipes.

[0027] The second simulated outlet water temperature is fitted with the topological structure of the geothermal pipe group to obtain a topological optimization coefficient; the topological optimization coefficient includes the maximum distance between pipes, the thermal attenuation influence coefficient of the connection method, and the standard buried pipe size;

[0028] The geothermal pipe group topology design objective function is determined based on the topology optimization coefficient and the geothermal pipe group topology structure. The expression is:

[0029]

[0030]

[0031]

[0032] in Design objective function for geothermal pipe cluster topology, Cost weight, is the energy weight, is the topological structure cost of the geothermal pipe group, including the pipe laying cost, station building cost and water pump operation cost, is the available amount of heat storage, is the utilization efficiency of available heat storage capacity, is the thermal attenuation rate of the geothermal pipe group topology, for Cost impact coefficient of pipeline connection method, for Thermal attenuation influence coefficient of pipeline connection method, is the area to be designed, is the distance between geothermal pipes, For size of The material cost of the buried pipe is for The construction cost of the pipeline connection method, is the construction cost of the station building for each geothermal pipe, is the cross-sectional area of ​​each buried pipe, is the flow rate of the buried pipe heat exchange fluid, is the water pump power consumption cost per unit flow rate of heat exchange fluid, is the maximum distance between tubes, It is the standard underground pipe size;

[0033] Determine the topological design constraints of the geothermal pipe group according to the geothermal index; the topological design constraints of the geothermal pipe group include density constraints, flow constraints and energy constraints, and the expression is:

[0034]

[0035] in The minimum heating area of ​​a single geothermal pipe is: is the minimum liquid flow rate of the geothermal pipe group, is the specific heat capacity of the heat exchange fluid.

[0036] Furthermore, the method for obtaining a reference geothermal pipe group topology structure includes:

[0037] Perform a primary match on the geothermal pipe group database according to the thermal balance score of the area to be designed, and select the geothermal pipe group historical data corresponding to the geothermal balance historical score with a deviation of within ±0.2 of the thermal balance score of the area to be designed as the primary matching result;

[0038] The comprehensive similarity of the characteristic vectors of the geothermal pipe group state data corresponding to the designed area and the historical data of the geothermal pipe group state corresponding to the primary matching result is calculated, and the geothermal pipe group topology historical structure corresponding to the primary matching result with the highest comprehensive similarity is taken as the reference geothermal pipe group topology structure; the geothermal pipe group state data includes regional location, average temperature during the regional heating season, total regional heat storage resources, available regional heat storage and utilization efficiency, and regional heat storage flow field, temperature field, and pressure field; the comprehensive similarity includes spatiotemporal overlap, cosine similarity, and Pearson correlation coefficient.

[0039] Furthermore, the method for obtaining the optimal geothermal pipe group topology structure includes:

[0040] The geothermal pipe group topology design objective function is used to perform multi-objective adaptive full-area rapid optimization of the reference geothermal pipe group topology structure. The specific steps include:

[0041] APSO is used to generate the initial particle swarm and calculate the objective function value of geothermal pipe group topology design;

[0042] Based on the initial particle swarm generated by APSO, non-dominated sorting is performed to select elite individuals to generate the initial population, and the population is crossover and mutation are performed to obtain a new population. The expression is:

[0043]

[0044]

[0045] in For solution The corresponding congestion level, is the number of terms in the objective function, For solution In the objective function The value in the item, is the new solution generated after crossover and mutation operations, To speak for my father, is the crossover rate, is the velocity term for particle swarm optimization, is the step length;

[0046] The particle positions corresponding to the reference geothermal pipe group topology structure are used as the optimal positions of the new population to perform APSO local search to update the particles and positions. The simulated annealing method is used to apply probabilistic perturbations to the global optimal solution to obtain a new population. The expression is:

[0047]

[0048]

[0049]

[0050]

[0051] in For the The particle speed, For the The particle speed, For the The particle location, For the The particle location, is the perturbation probability of simulated annealing, is the maximum inertia weight, is the minimum inertia weight, is the maximum number of iterations, 、 、 is the dynamic acceleration coefficient, 、 、 is the standard acceleration factor, is the decay rate, 、 、 is a random number in [0,1], is the regularization strength, For particles The individual historical optimal position of is the global historical optimal position of the group, For particles The optimal location in the neighborhood of is the objective function value of the new solution of the geothermal pipe group topology, is the objective function value of the old solution of the geothermal pipe group topology structure, is the initial temperature, is the temperature attenuation coefficient, Particles in the neighborhood location, For particles The neighborhood range of is the number of terms in the objective function, For solution In the objective function The value in the item;

[0052] The new population of NGSA-III operation and APSO operation is merged, and similarity screening is performed on the merged population to obtain similar solutions, retaining the solutions with high congestion and eliminating the rest of the similar solutions; the similarity screening conditions are:

[0053]

[0054] in is the distance threshold, Represents the solution 、 Euclidean distance in target space;

[0055] Repeat the above operation until the maximum number of iterations is reached, and the first three Pareto frontiers are output with the minimum geothermal pipe group topology design objective function as the optimization goal. The Pareto optimal solution is selected according to the designer's design focus, and the geothermal pipe group topology structure corresponding to the Pareto optimal solution is output as the optimal geothermal pipe group topology structure.

[0056] The beneficial effects of the present invention are:

[0057] The present invention is an intelligent topological design method for the layout of mid-deep geothermal pipe groups. Compared with the existing technology, the present invention has the following technical effects:

[0058] The present invention can improve the data preprocessing capability in the topological design of the layout of medium-deep geothermal pipe groups through the steps of space division, regional scoring, database construction, heat exchange simulation, parameter matching and parameter optimization, and can increase the speed of geothermal balance scoring in the area to be designed, thereby increasing the speed of determining the topological structure of the reference geothermal pipe group, thereby improving the efficiency and accuracy of the topological design of the layout of medium-deep geothermal pipe groups. Optimizing the topological design of the layout of medium-deep geothermal pipe groups can greatly save resources, improve work efficiency, and realize the intelligent topological design of the layout of medium-deep geothermal pipe groups, providing strong technical support and guarantee for the large-scale development and utilization of medium-deep geothermal energy, and is of great significance to promoting the technological progress and sustainable development of the geothermal energy development industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a flowchart of the steps of an intelligent topology design method for the layout of medium-deep geothermal pipe groups in the present invention. DETAILED DESCRIPTION

[0060] The present invention will be further described below through specific examples. The illustrative examples and descriptions of the present invention are used to explain the present invention but are not intended to limit the present invention.

[0061] The present invention provides an intelligent topology design method for the layout of a mid-deep geothermal pipe group, comprising the following steps:

[0062] like Figure 1 As shown, in this embodiment, the following steps are included:

[0063] Obtaining geothermal geological parameters and geothermal indicators of the area to be designed, spatially dividing the area to be designed according to the geothermal geological parameters, constructing a geothermal equilibrium evaluation index system, and calculating a geothermal equilibrium score for the area to be designed based on the spatial division results, the geothermal indicators, and the geothermal equilibrium evaluation index system;

[0064] Acquire historical data of geothermal pipe groups, calculate historical geothermal balance scores of historical areas, and construct a geothermal pipe group database based on the historical geothermal balance scores and the historical data of geothermal pipe groups; the historical data of geothermal pipe groups includes historical data of geothermal pipe group states and historical topological structures of geothermal pipe groups;

[0065] Performing a heat exchange simulation on a geothermal pipe group topology model to obtain a topology optimization coefficient, determining a geothermal pipe group topology design objective function based on the topology optimization coefficient, and determining a geothermal pipe group topology design constraint condition based on the geothermal index;

[0066] A reference geothermal pipe group topology is obtained by performing multi-level matching on the geothermal pipe group database according to the thermal balance score of the area to be designed and the geothermal pipe group status data;

[0067] According to the geothermal pipe group topology design objective function, the reference geothermal pipe group topology structure is subjected to multi-objective adaptive full-area rapid optimization to obtain the optimal geothermal pipe group topology structure.

[0068] In this embodiment, the method for spatially dividing the area to be designed includes:

[0069] Divide the area to be designed into a grid of 10m×10m on the horizontal plane to obtain multiple horizontal areas;

[0070] Each horizontal area is divided into vertical units at intervals of 500m along the depth direction. The geothermal geological parameter variation coefficient and the corresponding dynamic threshold of each vertical unit are calculated. The expression is:

[0071]

[0072]

[0073] in For horizontal area Inner longitudinal unit Geothermal geological parameters The coefficient of variation, Including permeability, thermal conductivity, porosity and ground temperature, is the geothermal geological parameter of the corresponding unit The maximum value of is the geothermal geological parameter of the corresponding unit The minimum value of is the geothermal geological parameter of the corresponding unit The mean of For horizontal area Inner longitudinal unit Geothermal geological parameters Dynamic threshold of the coefficient of variation, Geothermal geological parameters The standard threshold value of the coefficient of variation, is the depth coefficient, For horizontal area Inner longitudinal unit The average depth of is the maximum depth of the buried pipe;

[0074] When the coefficient of variation of any two geothermal geological parameters exceeds the corresponding threshold, the corresponding vertical unit is subdivided to obtain a vertical subunit, and the vertical subunit is defined as an evaluation area. Otherwise, the vertical unit does not need to be subdivided, and the corresponding vertical unit is defined as an evaluation area. The step of obtaining the vertical subunit is to select the extreme value point position of the coefficient of variation of the geothermal geological parameter as the subdivision position, and divide the vertical subunit with the subdivision position as the center. The expression is:

[0075]

[0076] in For horizontal area Inner longitudinal unit New subdivision location within;

[0077] Output spatial division results according to all evaluation areas;

[0078] In the actual evaluation, taking the topology design of a deep-seated geothermal pipe cluster at a certain location as an example, the design area is a 100m×30m rectangular area (divided horizontally into 10×3 grids, with a total of 30 horizontal areas, recorded as K1-K30), and the depth direction is 0-2000m (divided into four vertical units at 500m intervals, recorded as Z1-Z4, corresponding to the depth ranges: Z1=0-500m, Z2=500-1000m, Z3=1000-1500m, Z4=1500-2000m);

[0079] Taking the subdivision determination of K1Z3 unit (average depth 1250m) as an example, the depth coefficient , Maximum depth of buried pipe The maximum, minimum, and average values ​​of the permeability of the K1Z3 unit are 80mD, 10mD, and 45mD, respectively; the maximum, minimum, and average values ​​of the thermal conductivity are 5W / (m・K), 0.5W / (m・K), and 2.75W / (m・K), respectively; the standard threshold values ​​of the permeability variation coefficient and thermal conductivity variation coefficient are 0.8 and 1.2;

[0080] The permeability variation coefficient and thermal conductivity variation coefficient of the K1Z3 unit are calculated to be 1.555 and 1.636, respectively. The dynamic thresholds of the permeability variation coefficient and thermal conductivity variation coefficient are 0.8188 and 1.2282, respectively. Both the permeability variation coefficient and the thermal conductivity variation coefficient are greater than the corresponding dynamic thresholds, indicating that subdivision is required. The extreme value point of the geothermal geological parameter variation coefficient is calculated to be 1200m. The K1Z3 unit is subdivided into K1Z3-1 (depth 1000m-1200m) and K1Z3-2 (depth 1200-1500m).

[0081] Similarly, the design area is divided vertically to obtain 150 evaluation areas.

[0082] In this embodiment, the method for calculating the geothermal balance score of the area to be designed includes the following steps:

[0083] Geothermal indicators are organized into an evaluation factor set. A bag-of-words model is used to obtain importance judgments between factors within the evaluation factor set. Values ​​are assigned based on the importance judgment results to obtain importance comparison scores. A judgment matrix is ​​constructed based on the importance comparison scores. The inconsistency of the judgment matrix is ​​verified and geothermal indicator weights are obtained. The geothermal indicators include the total amount of heat storage resources, the available amount of heat storage and its utilization efficiency, cross-seasonal heat storage and its utilization efficiency, and the heat storage flow field, temperature field, and pressure field.

[0084] The geothermal index is input into the membership function to obtain the geothermal index score. The geothermal balance score of the corresponding evaluation area is calculated based on the geothermal index score and the geothermal index weight. The geothermal balance score of all evaluation areas is accumulated to obtain the geothermal balance score of the area to be designed.

[0085] In the actual evaluation, the importance judgments between factors include x and y are equally important, x is slightly more important than y, x is more important than y, x is obviously more important than y, and x is extremely important than y. The corresponding comparison scores G(x,y) are 1, 3, 5, 7, and 9 respectively. The corresponding scores G(y,x) are the inverse. According to the importance comparison scores, the judgment matrix of the factor set {total heat storage resources, available heat storage and its utilization efficiency, cross-seasonal heat storage and its utilization efficiency, heat storage flow field-temperature field-pressure field} is constructed :

[0086]

[0087] According to the characteristic equation Obtain The maximum eigenvalue of (in is the eigenvalue, is the unit matrix), calculate the consistency evaluation index , according to the consistency evaluation index Verify the random consistency ratio ,therefore The inconsistency is acceptable and based on The weights of the indicators of total heat storage resources, available heat storage and its utilization efficiency, cross-seasonal heat storage and its utilization efficiency, and heat storage flow field-temperature field-pressure field are determined to be 0.5222, 0.0781, 0.1998, and 0.1998;

[0088] Taking the geothermal balance score calculation of the evaluation area corresponding to the vertical unit Z3 in the K1 horizontal area as an example, the total heat storage resource of 8000MJ / m², the available heat storage of 5000MJ / m², the utilization efficiency of the available heat storage of 0.7, the cross-seasonal heat storage of 3000MJ / m², the cross-seasonal heat storage utilization efficiency of 0.6, the flow field uniformity of 0.8, the temperature stability of 0.7, and the pressure fluctuation of 0.9 are input into the membership function preset by the designer to obtain geothermal index scores of 8, 8.33, 7, 7.5, 6, 8, 7, and 9. After multiplying the geothermal index scores with the corresponding index weights, The cumulative geothermal balance score of the K1Z3 evaluation area is (8×0.5222)+[(8.33+7)×0.0781]+[(7.5+6)×0.1998]+[(8+7+9)×0.0666]=9.669. The cumulative geothermal balance scores of all evaluation areas are used to obtain a geothermal balance score of 348.084 for the area to be designed (first, calculate the thermal balance scores of multiple vertical evaluation areas in the same horizontal area as the thermal balance score of the horizontal area, and then accumulate the thermal balance scores of 30 horizontal areas to obtain the geothermal balance score of the area to be designed).

[0089] In this embodiment, the method for determining the geothermal pipe group topology design objective function and determining the geothermal pipe group topology design constraint conditions includes:

[0090] A geothermal pipe group topology model is constructed using historical data on the geothermal pipe group topology structure, and a heat exchange simulation is performed in combination with a primitive library to obtain a first simulated outlet water temperature. The geothermal pipe group topology model is optimized based on the deviation of the first simulated outlet water temperature and the historical outlet water temperature. The geothermal pipe group topology structure is changed based on a control variable method, and a heat exchange simulation is performed using the optimized heat pipe group topology model to obtain a second simulated outlet water temperature. The geothermal pipe group topology structure includes the shape and size of the buried pipes, the connection method, and the distance between the pipes.

[0091] The second simulated outlet water temperature is fitted with the topological structure of the geothermal pipe group to obtain a topological optimization coefficient; the topological optimization coefficient includes the maximum distance between pipes, the thermal attenuation influence coefficient of the connection method, and the standard buried pipe size;

[0092] The geothermal pipe group topology design objective function is determined based on the topology optimization coefficient and the geothermal pipe group topology structure. The expression is:

[0093]

[0094]

[0095]

[0096] in Design objective function for geothermal pipe cluster topology, Cost weight, is the energy weight, is the topological structure cost of the geothermal pipe group, including the pipe laying cost, station building cost and water pump operation cost, is the available amount of heat storage, is the utilization efficiency of available heat storage capacity, is the thermal attenuation rate of the geothermal pipe group topology, for Cost impact coefficient of pipeline connection method, for Thermal attenuation influence coefficient of pipeline connection method, is the area to be designed, is the distance between geothermal pipes, For size of The material cost of the buried pipe is for The construction cost of the pipeline connection method, is the construction cost of the station building for each geothermal pipe, is the cross-sectional area of ​​each buried pipe, is the flow rate of the buried pipe heat exchange fluid, is the water pump power consumption cost per unit flow rate of heat exchange fluid, is the maximum distance between tubes, It is the standard underground pipe size;

[0097] Determine the topological design constraints of the geothermal pipe group according to the geothermal index; the topological design constraints of the geothermal pipe group include density constraints, flow constraints and energy constraints, and the expression is:

[0098]

[0099] in The minimum heating area of ​​a single geothermal pipe is: is the minimum liquid flow rate of the geothermal pipe group, is the specific heat capacity of the heat exchange fluid;

[0100] In the actual evaluation, the second simulated outlet water temperature was fitted with the geothermal pipe group topology to obtain the topology optimization coefficients: the maximum pipe distance was 25m, the connection method thermal attenuation influence coefficient was 0.9 (the minimum value for straight-line connection), and the standard buried pipe size was 0.075m;

[0101] Take cost weight , energy weight , Cost impact coefficient of straight line connection method , thermal attenuation influence coefficient of straight line connection , construction cost of straight line connection Yuan / m, station building construction cost Yuan / root, unit flow rate of heat exchange fluid water pump power consumption cost Yuan / (m³ / h);

[0102] Take the minimum heating area of ​​a single geothermal pipe 20㎡, minimum liquid flow rate of geothermal pipe group m³ / h.

[0103] In this embodiment, the method for obtaining a reference geothermal pipe group topology structure includes:

[0104] Perform a primary match on the geothermal pipe group database according to the thermal balance score of the area to be designed, and select the geothermal pipe group historical data corresponding to the geothermal balance historical score with a deviation of within ±0.2 of the thermal balance score of the area to be designed as the primary matching result;

[0105] Calculate the comprehensive similarity of the characteristic vectors of the geothermal pipe group state data corresponding to the design area and the geothermal pipe group state historical data corresponding to the primary matching result, and take the geothermal pipe group topology historical structure corresponding to the primary matching result with the highest comprehensive similarity as the reference geothermal pipe group topology structure; the geothermal pipe group state data includes regional location, average temperature during the regional heating season, total regional heat storage resources, available regional heat storage and utilization efficiency, and regional heat storage flow field, temperature field, and pressure field; the comprehensive similarity includes spatiotemporal overlap, cosine similarity, and Pearson correlation coefficient;

[0106] In the actual evaluation, the thermal balance score of the design area was 785.2, and the status data (N30° / E120°, average temperature in the heating season of 5°C, total heat storage resources of 8000MJ / m², available heat storage of 5000MJ / m², utilization efficiency of available heat storage of 0.7, inter-seasonal heat storage of 3000MJ / m², inter-seasonal heat storage utilization efficiency of 0.6, flow field uniformity of 0.8, temperature stability of 0.7, pressure fluctuation of 0.9);

[0107] According to the thermal balance score of the area to be designed, the geothermal pipe group database is preliminarily matched, and 10 geothermal pipe group historical data corresponding to the geothermal balance historical scores of the area to be designed with a thermal balance score deviation within ±0.2 are obtained. The comprehensive similarity between the state data of the area to be designed and the state data of the matching results is calculated respectively = [time-space overlap * (0.5 * cosine similarity + 0.5 * Pearson correlation coefficient)], and the geothermal pipe group topology history structure corresponding to the primary matching result with the highest comprehensive similarity is selected as the reference geothermal pipe group topology structure (the distance between geothermal pipes is 0.5). m. Material cost Yuan / m, heat exchange fluid flow rate of circular pipe and buried pipe m / s, buried pipe size m).

[0108] In this embodiment, the method for obtaining the optimal geothermal pipe group topology includes:

[0109] The geothermal pipe group topology design objective function is used to perform multi-objective adaptive full-area rapid optimization of the reference geothermal pipe group topology structure. The specific steps include:

[0110] APSO is used to generate the initial particle swarm and calculate the objective function value of geothermal pipe group topology design;

[0111] Based on the initial particle swarm generated by APSO, non-dominated sorting is performed to select elite individuals to generate the initial population, and the population is crossover and mutation are performed to obtain a new population. The expression is:

[0112]

[0113]

[0114] in For solution The corresponding congestion level, is the number of terms in the objective function, For solution In the objective function The value in the item, is the new solution generated after crossover and mutation operations, To speak for my father, is the crossover rate, is the velocity term for particle swarm optimization, is the step length;

[0115] The particle positions corresponding to the reference geothermal pipe group topology structure are used as the optimal positions of the new population to perform APSO local search to update the particles and positions. The simulated annealing method is used to apply probabilistic perturbations to the global optimal solution to obtain a new population. The expression is:

[0116]

[0117]

[0118]

[0119]

[0120] in For the The particle speed, For the The particle speed, For the The particle location, For the The particle location, is the perturbation probability of simulated annealing, is the maximum inertia weight, is the minimum inertia weight, is the maximum number of iterations, 、 、 is the dynamic acceleration coefficient, 、 、 is the standard acceleration factor, is the decay rate, 、 、 is a random number in [0,1], is the regularization strength, For particles The individual historical optimal position of is the global historical optimal position of the group, For particles The optimal location in the neighborhood of is the objective function value of the new solution of the geothermal pipe group topology, is the objective function value of the old solution of the geothermal pipe group topology structure, is the initial temperature, is the temperature attenuation coefficient, Particles in the neighborhood location, For particles The neighborhood range of is the number of terms in the objective function, For solution In the objective function The value in the item;

[0121] The new population of NGSA-III operation and APSO operation is merged, and similarity screening is performed on the merged population to obtain similar solutions, retaining the solutions with high congestion and eliminating the rest of the similar solutions; the similarity screening conditions are:

[0122]

[0123] in is the distance threshold, Represents the solution 、 Euclidean distance in target space;

[0124] Repeat the above operation until the maximum number of iterations is reached, and the first three Pareto frontiers are output with the minimum geothermal pipe group topology design objective function as the optimization goal. The Pareto optimal solution is selected according to the designer's design focus, and the geothermal pipe group topology structure corresponding to the Pareto optimal solution is output as the optimal geothermal pipe group topology structure;

[0125] In the actual evaluation, the particle position corresponding to the reference geothermal pipe group topology structure is used as the optimal position of the new population to calculate the corresponding geothermal pipe group topology design objective function of 172,982.88, taking the maximum inertia weight. , minimum inertia weight , standard acceleration coefficients are 2 / 2 / 1.5, decay rate , regularization strength , the initial particle swarm size is 50, the maximum number of iterations , the number of objective function items is 4 (3 items for cost and 1 item for heat energy), cross rate , step length m, initial temperature ℃, temperature attenuation coefficient , neighborhood size = 0.1 population size, distance threshold 5% of the cost item / energy item;

[0126] Repeat the above operation until the maximum number of iterations is reached, and the top 3 solutions of the Pareto front are output. According to the designer's balanced design, the corresponding Pareto optimal solution (the corresponding geothermal pipe group topology design objective function value is 151200) and the corresponding optimal geothermal pipe group topology structure (the distance between geothermal pipes) are output. m. Material cost Yuan / m, heat exchange fluid flow rate of circular pipe and buried pipe m / s, buried pipe size m).

[0127] 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 scope of protection of the present invention.

Claims

1. An intelligent topology design method for the layout of mid-deep geothermal pipe groups, characterized in that: The following steps are involved: S1. Obtain geothermal geological parameters and geothermal indicators of the area to be designed, spatially divide the area to be designed according to the geothermal geological parameters, construct a geothermal balance evaluation index system, and calculate a geothermal balance score for the area to be designed based on the spatial division results, the geothermal indicators, and the geothermal balance evaluation index system; S2. Obtain historical data of geothermal pipe groups, calculate the geothermal balance history score of the historical area, and construct a geothermal pipe group database based on the geothermal balance history score and the geothermal pipe group historical data; The geothermal pipe group historical data includes geothermal pipe group status historical data and geothermal pipe group topology historical structure; S3. Performing a heat exchange simulation on a geothermal pipe group topology model to obtain a topology optimization coefficient, determining a geothermal pipe group topology design objective function based on the topology optimization coefficient, and determining a geothermal pipe group topology design constraint condition based on the geothermal index; S4. Perform multi-level matching with the geothermal pipe group database based on the thermal balance score of the area to be designed and the geothermal pipe group status data to obtain a reference geothermal pipe group topology structure; S5. Performing multi-objective adaptive full-area rapid optimization on the reference geothermal pipe group topology structure according to the geothermal pipe group topology design objective function to obtain an optimal geothermal pipe group topology structure; The method for spatially dividing the area to be designed includes: Divide the area to be designed into a grid of 10m×10m on the horizontal plane to obtain multiple horizontal areas; Each horizontal area is divided into vertical units at intervals of 500m along the depth direction. The geothermal geological parameter variation coefficient and the corresponding dynamic threshold of each vertical unit are calculated. The expression is: in is the variation coefficient of geothermal geological parameters g of the vertical unit z in the horizontal region k, g includes permeability, thermal conductivity, porosity and ground temperature, max[P g (k, z)] is the maximum value of the geothermal parameter g in the corresponding unit, min[P g (k,z)] is the minimum value of the geothermal parameter g in the corresponding unit, is the mean value of the geothermal geological parameter g in the corresponding unit, is the dynamic threshold of the coefficient of change of geothermal geological parameter g of vertical unit z in horizontal region k, θ g is the standard threshold value of the geothermal geological parameter g variation coefficient, μ is the depth coefficient, is the average depth of the longitudinal unit z in the horizontal region k, h max is the maximum depth of the buried pipe; When the coefficient of variation of any two geothermal geological parameters exceeds the corresponding threshold, the corresponding vertical unit is subdivided to obtain a vertical subunit, and the vertical subunit is defined as an evaluation area. Otherwise, the vertical unit does not need to be subdivided, and the corresponding vertical unit is defined as an evaluation area. The step of obtaining the vertical subunit is to select the extreme value point position of the coefficient of variation of the geothermal geological parameter as the subdivision position, and divide the vertical subunit with the subdivision position as the center. The expression is: in is the new subdivision position within the longitudinal unit z within the horizontal region k; Output the spatial division results according to all evaluation areas.

2. The intelligent topology design method for the layout of mid-deep geothermal pipe groups according to claim 1, characterized in that: The method for calculating the geothermal balance score of the area to be designed comprises the following steps: Geothermal indicators are organized into an evaluation factor set. A bag-of-words model is used to obtain importance judgments between factors within the evaluation factor set. Values ​​are assigned based on the importance judgment results to obtain importance comparison scores. A judgment matrix is ​​constructed based on the importance comparison scores. The inconsistency of the judgment matrix is ​​verified and geothermal indicator weights are obtained. The geothermal indicators include the total amount of heat storage resources, the available amount of heat storage and its utilization efficiency, cross-seasonal heat storage and its utilization efficiency, and the heat storage flow field, temperature field, and pressure field. The geothermal index is input into the membership function to obtain the geothermal index score. The geothermal balance score of the corresponding evaluation area is calculated according to the geothermal index score and the geothermal index weight. The geothermal balance score of the area to be designed is obtained by accumulating the geothermal balance scores of all evaluation areas.

3. The intelligent topology design method for the layout of mid-deep geothermal pipe groups according to claim 1 is characterized in that: The method for determining the geothermal pipe group topology design objective function and determining the geothermal pipe group topology design constraint conditions comprises the following steps: A geothermal pipe group topology model is constructed using historical data on the geothermal pipe group topology structure, and a heat exchange simulation is performed in combination with a primitive library to obtain a first simulated outlet water temperature. The geothermal pipe group topology model is optimized based on the deviation of the first simulated outlet water temperature and the historical outlet water temperature. The geothermal pipe group topology structure is changed based on a control variable method, and a heat exchange simulation is performed using the optimized heat pipe group topology model to obtain a second simulated outlet water temperature. The geothermal pipe group topology structure includes the shape and size of the buried pipes, the connection method, and the distance between the pipes. The second simulated outlet water temperature is fitted with the topological structure of the geothermal pipe group to obtain a topological optimization coefficient; the topological optimization coefficient includes the maximum distance between pipes, the thermal attenuation influence coefficient of the connection method, and the standard buried pipe size; The geothermal pipe group topology design objective function is determined based on the topology optimization coefficient and the geothermal pipe group topology structure. The expression is: Aim top =α·C total +β·Q avail ·r avail ·r decay Among them Aim top is the objective function for geothermal pipe group topology design, α is the cost weight, β is the energy weight, C total is the topological structure cost of the geothermal pipe group, including the pipe laying cost, station building cost and water pump operation cost, Q avail is the available amount of heat storage, ρ avail is the utilization efficiency of available heat storage, ρ decay is the thermal attenuation rate of the geothermal pipe group topology, δ j1 is the cost impact coefficient of the j pipeline connection method, δ j2 is the thermal attenuation influence coefficient of the j pipeline connection mode, A area is the area of ​​the area to be designed, d is the distance between the geothermal pipes, C i (r) is the material cost of the I-shaped buried pipe with size r, C j is the construction cost of the j pipeline connection method, C build is the construction cost of the station building for each geothermal pipe, A pipe is the cross-sectional area of ​​each buried pipe, v pipe is the flow rate of the buried pipe heat exchange fluid, C P is the water pump power consumption cost per unit flow rate of heat exchange fluid, d max is the maximum distance between tubes, r o It is the standard underground pipe size; Determine the topological design constraints of the geothermal pipe group according to the geothermal index; the topological design constraints of the geothermal pipe group include density constraints, flow constraints and energy constraints, and the expression is: Among them A sup Minimum heating area of ​​a single geothermal pipe, L sup is the minimum liquid flow rate of the geothermal pipe group, c liquid is the specific heat capacity of the heat exchange fluid.

4. The intelligent topology design method for the layout of mid-deep geothermal pipe groups according to claim 1, characterized in that: The method for obtaining a reference geothermal pipe group topology structure comprises: Perform a primary match on the geothermal pipe group database according to the thermal balance score of the area to be designed, and select the geothermal pipe group historical data corresponding to the geothermal balance historical score with a deviation of within ±0.2 of the thermal balance score of the area to be designed as the primary matching result; The comprehensive similarity of the characteristic vectors of the geothermal pipe group state data corresponding to the designed area and the historical data of the geothermal pipe group state corresponding to the primary matching result is calculated, and the geothermal pipe group topology historical structure corresponding to the primary matching result with the highest comprehensive similarity is taken as the reference geothermal pipe group topology structure; the geothermal pipe group state data includes regional location, average temperature during the regional heating season, total regional heat storage resources, available regional heat storage and utilization efficiency, and regional heat storage flow field, temperature field, and pressure field; the comprehensive similarity includes spatiotemporal overlap, cosine similarity, and Pearson correlation coefficient.

5. The intelligent topology design method for the layout of mid-deep geothermal pipe groups according to claim 1, characterized in that: The method for obtaining the optimal geothermal pipe group topology structure includes: The geothermal pipe group topology design objective function is used to perform multi-objective adaptive full-area rapid optimization of the reference geothermal pipe group topology structure. The specific steps include: APSO is used to generate the initial particle swarm and calculate the objective function value of geothermal pipe group topology design; Based on the initial particle swarm generated by APSO, non-dominated sorting is performed to select elite individuals to generate the initial population, and the population is crossover and mutation are performed to obtain a new population. The expression is: x new =x parent +η·(v PSO ·Δt) Where Crow(x i ) is the solution x i The corresponding congestion degree, M is the number of terms in the objective function, f m (x i+1 ) is the solution x i+1 The value in the objective function m term, x new is the new solution generated after crossover and mutation operations, x parent is the parent solution, η is the crossover rate, v PSO is the speed term of particle swarm optimization, Δt is the step size; The particle positions corresponding to the reference geothermal pipe group topology structure are used as the optimal positions of the new population to perform APSO local search to update the particles and positions. The simulated annealing method is used to apply probabilistic perturbations to the global optimal solution to obtain a new population. The expression is: in is the velocity of particle i at the k+1th iteration, is the velocity of particle i at the kth iteration, is the position of particle i at the k+1th iteration, is the position of particle i at the kth iteration, p accept is the perturbation probability of simulated annealing, w max is the maximum inertia weight, w min is the minimum inertia weight, K max is the maximum number of iterations, c1(k)=c 1,sta ·e -τk 、c2(k)=c 2,sta ·e -τk 、c3(k)=c 3,sta ·e -τk is the dynamic acceleration coefficient, c 1,sta 、c 2,sta 、c 3,sta is the standard acceleration coefficient, τ is the decay rate, r1, r2, r3 are random numbers in [0,1], λ is the regularization strength, pbest i is the individual best historical position of particle i, gbest is the global best historical position of the group, nbest i is the optimal location of particle i in the neighborhood, is the objective function value of the new solution of the geothermal pipe group topology, is the objective function value of the old solution of the geothermal pipe group topology structure, T0 is the initial temperature, γ is the temperature attenuation coefficient, and x j is the position of particle j in the neighborhood, Neigh(i) is the neighborhood range of particle i, M is the number of terms in the objective function, f m (x j ) is the solution x j The value in the objective function m term; The new population of NGSA-III operation and APSO operation is merged, and similarity screening is performed on the merged population to obtain similar solutions, retaining the solutions with high congestion and eliminating the rest of the similar solutions; the similarity screening conditions are: Where ∈ is the distance threshold, Represents the solution x a 、x a Euclidean distance in target space; Repeat the above operation until the maximum number of iterations is reached, and the first three Pareto frontiers are output with the minimum geothermal pipe group topology design objective function as the optimization goal. The Pareto optimal solution is selected according to the designer's design focus, and the geothermal pipe group topology structure corresponding to the Pareto optimal solution is output as the optimal geothermal pipe group topology structure.

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