Cost optimization method and system for buried pipe system

Abstract

The invention discloses a cost optimization method and system for a buried pipe system, and relates to the technical field of buried pipe systems.The cost optimization method comprises the following steps that an optimization problem is solved, and a well track of a directional well group is obtained; a well group arrangement diagram is generated through the well track, and a buried pipe system numerical model is constructed based on the well group arrangement diagram; performing operation simulation on the numerical model of the buried pipe system, and determining the annual operation cost of the buried pipe system, the system operation cost of the whole life cycle and the average energy cost according to a simulation result; and correcting the initial investment cost, the annual operation cost, the system operation cost of the whole life cycle and the average energy cost according to the actual project condition. According to the method, efficient space utilization of the well group is achieved, and meanwhile the economical efficiency and the long-term stability of the system are improved by combining initial investment measurement and calculation, long-term operation parameter simulation and dynamic optimization of actual operation data.

Description

Technical Field

[0001] The present invention relates to the technical field of buried pipe systems, and particularly to a method and system for optimizing the cost of a buried pipe system. Background Art

[0002] With the growth of global energy demand, clean energy heating technology has become one of the important ways to solve the energy crisis. Among them, the buried pipe heating system has gradually become an important technical means in the fields of urban heating and industrial heating due to its characteristics of high efficiency, energy conservation, stable operation and environmental friendliness.

[0003] Traditional buried pipe systems usually adopt vertical well or horizontal well designs, which pose high requirements for the surface occupation area and construction conditions. However, with the advancement of urbanization, the available ground resources are decreasing day by day. Especially in densely populated urban areas, the problem of insufficient ground occupation area seriously restricts the application of traditional buried pipe heating systems. In addition, the heat recovery capacity of the rock and soil layer is limited. If the well group design of the heating system is unreasonable, it may lead to geothermal imbalance, thereby affecting the long-term operation efficiency of the system.

[0004] To solve these problems, directional well technology has been introduced into the design of buried pipe heating systems. By designing a reasonable wellbore trajectory (including the turning point, turning angle, well spacing and three-dimensional layout angle between wells), directional wells can not only effectively improve the space utilization rate of buried pipes, but also optimize the heat exchange efficiency and heat recovery capacity of the rock and soil layer. In addition, directional wells can achieve a larger-scale well group layout under limited surface occupation conditions, so as to meet the heating requirements of high-heat demand areas.

[0005] However, the design and optimization of existing directional well buried pipe heating systems still face many challenges. For example, how to accurately calculate the construction cost, operation and maintenance cost and the whole life cycle cost of the system (such as annual operation cost and average energy cost) during the system planning stage, and how to dynamically adjust the design parameters based on actual operation data to adapt to complex geological conditions and long-term operation requirements are still the difficulties and key points of the current technological development. Summary of the Invention

[0006] Based on the defects existing in the above-mentioned prior art, the present invention provides a method and system for optimizing the cost of a buried pipe system, and solves the existing problems.

[0007] The present invention adopts the following technical solutions:

[0008] In the first aspect, the present invention provides a method for optimizing the cost of a buried pipe system, including the following steps:

[0009] The optimization problem is constructed with the well spacing, inclination point and deviation azimuth of the directional well group as optimization variables, and the optimization objectives of maximizing the total heat collection capacity of the directional well group and minimizing the total investment cost.

[0010] Solve the optimization problem and obtain the wellbore trajectory of the directional well group;

[0011] Generate a well group layout diagram based on the wellbore trajectory, and construct a numerical model of the buried pipe system based on the well group layout diagram; collect the initial investment cost of the numerical model of the buried pipe system;

[0012] Conduct operational simulations on the buried pipe system numerical model and determine the annual operating cost, lifecycle system operating cost, and average energy cost of the buried pipe system based on the simulation results;

[0013] The initial investment cost, annual operating cost, system operating cost over the entire life cycle, and average energy cost are revised based on the actual project situation.

[0014] Preferably, the optimization objectives are specifically as follows:

[0015]

[0016] in,

[0017]

[0018] C i =C1×Kop+(L total -Kop)×y(d ij ,φ i );

[0019] Where f is the optimization target, Q total is the total heat production of the well group, C total is the total investment cost, Q i is the heat collection capacity of the i-th well, n is the number of wells in the well group, C i is the cost of the i-th well, L total is the total length of a single buried pipe, y(d ij ,φ i ) is the cost function of the directional part of the pipe length, C1 is the cost of the vertical part of the pipe length, d ij is the well spacing, Kop is the inclination point, φ i is the deflection azimuth.

[0020] Preferably, the optimization problem further includes the following constraints:

[0021] Well trajectories do not intersect;

[0022] The total heat production is not less than that of the vertical well group.

[0023] Preferably, solving the optimization problem to obtain the wellbore trajectories of the directional well group includes the following steps:

[0024] Randomly generate a plurality of individuals, and each individual needs to satisfy the constraint conditions. Each individual is an optimization variable;

[0025] Obtain the optimization objective value of each individual;

[0026] Perform crossover and mutation on the multiple individuals to obtain new individuals;

[0027] Obtain the optimization objective value of the new individuals;

[0028] Repeat the above crossover and mutation process until the maximum number of iterations;

[0029] Output the optimal individual, and generate the wellbore trajectories of the directional well group through the optimal individual.

[0030] Preferably, the initial investment cost includes geothermal well drilling cost, pipe material cost, and energy station construction cost.

[0031] In a second aspect, the present invention provides a cost optimization system for a buried pipe system, including:

[0032] A construction module, configured to construct an optimization problem with the well spacing, kick-off point, and deflection azimuth angle of the directional well group as optimization variables, and with maximizing the total heat collection capacity of the directional well group and minimizing the total investment cost as optimization objectives;

[0033] A solution module, configured to solve the optimization problem to obtain the wellbore trajectories of the directional well group;

[0034] An acquisition module, configured to generate a well group layout diagram through the wellbore trajectories, construct a numerical model of the buried pipe system based on the well group layout diagram; acquire the initial investment cost of the numerical model of the buried pipe system;

[0035] A simulation module, configured to perform operation simulation on the numerical model of the buried pipe system, and determine the annual operation cost, the system operation cost over the entire life cycle, and the average energy cost of the buried pipe system according to the simulation results;

[0036] A correction module, configured to correct the initial investment cost, the annual operation cost, the system operation cost over the entire life cycle, and the average energy cost according to the actual project situation.

[0037] Compared with the prior art, the above at least one technical solution adopted by the present invention can achieve the following beneficial effects:

[0038] The present invention first designs the wellbore trajectory of the directional well to achieve efficient spatial utilization of the well group. At the same time, by combining the initial investment calculation, long-term operation parameter simulation and dynamic optimization of actual operation data, the life-cycle cost is reduced, and the economy and long-term stability of the system are improved. This method is applicable to complex geological conditions and high heat demand scenarios, taking into account both the heating efficiency and the operation cost, and providing a comprehensive solution for the development of the buried pipe heating technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0040] Figure 1 It is a flowchart of a method for optimizing the cost of a buried pipe system according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0042] Based on the technical problems existing in the prior art, a design and optimization method for a buried pipe heating system based on directional well technology is developed, which can not only solve the problems of insufficient ground occupation and geothermal imbalance, but also significantly improve the economy and operation efficiency of the system, and has important research value and practical significance.

[0043] The present invention proposes a design and optimization method for a buried pipe heating system based on directional wells, aiming to solve the problem of low operation efficiency caused by insufficient surface occupation and limited geothermal recovery ability of traditional systems. By designing the wellbore trajectory (including the inflection point, inflection angle, well spacing and three-dimensional layout angle), the efficient spatial utilization of the well group is realized. At the same time, by combining the initial investment calculation, long-term operation parameter simulation and dynamic optimization of actual operation data, the life-cycle cost is reduced, and the economy and long-term stability of the system are improved. This method is applicable to complex geological conditions and high heat demand scenarios, taking into account both the heating efficiency and the operation cost, and providing a comprehensive solution for the development of the buried pipe heating technology.

[0044] S1: Taking the well spacing, kick-off point, and deflection azimuth angle of the directional well group as optimization variables, and maximizing the total heat collection capacity of the directional well group and minimizing the total investment cost as optimization objectives, an optimization problem is constructed.

[0045] Directional well trajectory design.

[0046] Based on the geothermal resource distribution and surface conditions, select a suitable layout (vertical well, directional well, fishbone well, or double-ring well, etc.) to ensure that the wellbore maximally covers the heat reservoir area and improves the heat collection efficiency.

[0047] Based on the following three main design variables, use genetic algorithm optimization to optimize the well spacing, kick-off point, and deflection azimuth angle. These variables together determine the wellbore trajectory and layout, thus affecting the heat collection efficiency and economy of the entire well group.

[0048] Well spacing d ij : The horizontal distance between two wells, which is crucial for ensuring heat collection efficiency and mutual interference between well groups. Too small a well spacing may lead to heat short-circuiting, while too large a well spacing may cause some wells to fail to fully cover the target heat reservoir. Optimizing the well spacing helps improve the heat collection effect.

[0049] Kick-off point Kop: The trajectory of a directional well consists of multiple straight-line segments, and the starting and ending angles of each segment are determined by the kick-off point. Reasonably setting the kick-off point helps ensure that the wellbore trajectory can effectively cover the underground heat reservoir while avoiding intersection or interference with other wellbore trajectories.

[0050] Deflection azimuth angle φ i : The horizontal offset direction of the wellbore. The deflection azimuth angle determines the orientation of the wellbore underground. By adjusting the deflection azimuth angle, the angle matching between the wellbore and the heat reservoir can be maximized, thus improving the heat collection capacity.

[0051] The objective function should comprehensively consider the following points:

[0052] Heat collection efficiency: The optimized well group design should maximize the total heat collection capacity of the well group to ensure that the heat energy collection of each well is effectively improved. The heat collection efficiency is not only related to the design variables of the wellbore (such as well spacing, kick-off point, and deflection azimuth angle), but also related to the distribution of the underground heat reservoir and resource utilization.

[0053] Economy: The optimization scheme needs to consider construction costs and operating costs. The costs should be balanced with the total heat collection of the well group to ensure that while maximizing heat collection, the costs are not too high.

[0054] Therefore, the optimization objective function can be expressed as:

[0055]

[0056] Among them,

[0057]

[0058] In the formula, Q total represents maximizing the total heat extraction sum of the well group (i.e., the total heat collection sum of all wells in the well group), and Q i is the heat collection capacity of the i-th well, and n is the number of wells in the well group. Q i is obtained through numerical simulation or corrected in combination with measured engineering. C total represents minimizing the total investment cost. On the premise of ensuring the heat collection benefit, the construction and operation costs should be reduced as much as possible. C i is the cost of the i-th well, including construction cost and operation cost.

[0059] C i = C1×Kop+(L total -Kop)×y(d ij , φ i );

[0060] Among them, L total is the total length of a single buried pipe, and y(d ij , φ i ) is the cost function of the extended meter length of the directional part, and C1 is the cost of the extended meter length of the vertical well part.

[0061] In addition to the objective function, the following several constraint conditions need to be considered in the optimization process:

[0062] Constraint 1: Well trajectories cannot intersect, and the well spacing is not less than the minimum requirement

[0063] Well trajectories do not intersect: In the optimization design, it must be ensured that the trajectories of any two wells do not intersect to avoid physical interference or heat short-circuit phenomena between wells.

[0064] Well spacing constraint: The distance between each well in the well group should meet the minimum well spacing requirement. This can ensure that the layout of the well group is not too dense and avoid mutual interference.

[0065] For any two wells i and j, the condition that the wellbore trajectories do not intersect must be satisfied, that is, the horizontal distance between the wells should be greater than or equal to the minimum well spacing:

[0066]

[0067] Constraint 2: The cost / heat extraction sum cannot be lower than that of the vertical well pipe group. This constraint ensures that the economy of the directional well group cannot be lower than the heat extraction effect of the vertical well pipe group under the same conditions.

[0068] The ratio of the total cost of the directional well group (including construction, operation, maintenance, etc.) to the total heat extraction benefit of the directional well group shall not be lower than the heat extraction sum / cost ratio of the straight well pipe group.

[0069]

[0070] Ensure that the ratio between the total heat collection and the total investment cost is not lower than a certain setting.

[0071] S2: Solve the optimization problem to obtain the wellbore trajectories of the directional well group.

[0072] Initialize the population: Randomly generate multiple initial solutions, each solution consisting of parameters such as the well spacing, kick-off point, and deflection azimuth angle of the well group.

[0073] Fitness evaluation: Each individual calculates its fitness according to the following indicators:

[0074] Total heat collection: Calculate the heat collection capacity of each well according to the design parameters (well spacing, kick-off point, deflection azimuth angle), and sum them to obtain the total heat collection capacity of the well group.

[0075] Investment cost: Calculate the total construction and operation costs of each design scheme.

[0076] Meet the constraint conditions: Check whether each scheme meets the constraint conditions of "non-intersecting well trajectories" and "minimum well spacing".

[0077] At the same time, the constraint conditions should be checked during the evaluation process. If the constraints are not met, the fitness should be adjusted or penalized.

[0078] Selection operation: According to the fitness, select suitable individuals for crossover and mutation to ensure that excellent design schemes can be retained for the next generation.

[0079] Crossover and mutation: The crossover operation combines the design variables of the parent individuals to generate new design schemes; the mutation operation randomly adjusts certain parameters to explore more solution spaces.

[0080] Termination condition: According to the preset termination condition (such as the maximum number of iterations or the fitness reaching the expectation), the genetic algorithm stops.

[0081] Output result: Output the optimal design scheme, including well spacing, kick-off point, deflection azimuth angle, economic analysis, and heat collection performance.

[0082] Comprehensively consider the balance between the total heat collection and the total investment cost. By introducing well spacing, kick-off point, and deflection azimuth angle as design variables, the genetic algorithm will effectively optimize the well group layout, improve the heat collection benefit, and consider economic constraints at the same time. The whole process will ensure the technical and economic feasibility of the well group.

[0083] S3: Generate a layout plan of the well group based on the wellbore trajectory, and construct a numerical model of the buried pipe system based on the layout plan of the well group; collect the initial investment cost of the numerical model of the buried pipe system.

[0084] Generate a layout plan of the well group, a wellbore parameter table and a construction guide document, and combine with thermal collection prediction to support precise construction and the efficiency and reliability of the later system operation.

[0085] The investment of the geothermal energy system consists of two parts: the initial investment and the operation cost.

[0086] The initial investment includes the drilling cost of geothermal wells, the cost of pipe materials and the construction cost of the energy station.

[0087] The drilling cost of geothermal wells includes multiple steps such as drilling, shaft protection, pipe lowering, and cementing. The specific cost depends on the soil type and well depth. The drilling depth and soil conditions directly affect the complexity and cost of drilling, so accurate calculation is required according to the local soil type.

[0088] The pipe materials mainly include the outer pipe and the inner pipe. The outer pipe usually selects N80 steel pipe, and the inner pipe is required to have pressure-bearing capacity and high temperature resistance. The costs of the outer pipe and the inner pipe are estimated respectively according to the material, market price and transportation cost, and finally the total cost of the pipe materials is obtained.

[0089] The construction cost of the energy station includes the cost of the ground heat pump station, including equipment purchase, installation and commissioning costs. The pipeline laying cost takes into account the connection between the heat pump station and the geothermal well and the construction cost of underground pipeline laying. At the same time, the purchase cost of the water pump also needs to be considered, and finally these costs are integrated into the investment of the heat pump station and the pipeline.

[0090] The operation cost includes components such as the power consumption of the water pump, the wages of workers for operation and maintenance, and the power consumption of the heat pump. The power consumption is determined by the flow resistance and the circulation flow rate. Combining with the efficiency and operation time of the water pump, the operation cost of the water pump is calculated. The wages of workers and the power consumption of the heat pump system also need to be comprehensively considered.

[0091] Determine the annual operation cost of the medium-deep directional buried pipe heating system according to the long-term operation parameters of the medium-deep directional buried pipe heating system.

[0092] Among them, the annual operation cost of the medium-deep directional buried pipe heating system includes the annual operation cost of the heat pump, the annual operation cost of the circulation water pump, and the annual equipment maintenance cost.

[0093] Determine the annual operation cost of the heat pump according to the long-term operation parameters of the medium-deep directional buried pipe heating system, including:

[0094] Determine the coefficient of performance of the heat pump according to the inlet temperature of the heat pump.

[0095] Determine the power consumption of the heat pump according to the coefficient of performance of the heat pump.

[0096] Determine the annual operating cost of the heat pump according to the power consumption of the heat pump and the electricity price.

[0097] Specifically, estimate the coefficient of performance COP of the heat pump according to the inlet water temperature:

[0098] COP = α + β×T in ;

[0099] where α and β are fixed coefficients related to the heat pump; T in is the inlet temperature of the heat pump; where T in is the outlet temperature of the heat exchanger obtained by simulating the long-term heat extraction condition of the heat exchanger, that is, the inlet temperature of the heat pump.

[0100] The electric power P of the heat pump ele is:

[0101]

[0102] where Q is the calibrated heat extraction power.

[0103] The power consumption Q of the heat pump ele is:

[0104]

[0105] where t is the system operation hours.

[0106] Then, according to the power consumption of the heat pump and the current local electricity price, the annual operating cost of the heat pump can be calculated.

[0107] Determine the annual operating cost of the circulating water pump according to the long-term operation parameters of the medium-deep directional ground-coupled heating system, including:

[0108] Determine the frictional resistance and local resistance of the heat extraction medium according to the operation parameters of the medium-deep directional ground-coupled heating system;

[0109] Determine the net power consumption of the circulating water pump according to the frictional resistance and local resistance;

[0110] Determine the annual operating cost of the circulating water pump according to the net power consumption of the circulating water pump and the electricity price.

[0111] Specifically, the frictional resistance h f is the loss that occurs when the circulating fluid is affected by fluid viscosity in the medium-deep directional ground-coupled heat exchanger and is:

[0112]

[0113] Among them, λ is the friction coefficient along the path; L is the length of the heat exchanger tube; d is the diameter of the directional tube; u is the average cross-sectional flow velocity; g is the acceleration due to gravity.

[0114] It can be understood that the heat exchanger includes two vertical tubes and an underground horizontal tube. The frictional resistance along the path of the medium-depth directional ground heat exchanger includes the sum of the frictional resistances of the two vertical tubes and the underground horizontal tube. In the above formula, if L is the total tube length of the three tubes, namely the two vertical tubes and the underground horizontal tube, then the calculated h f is the total frictional resistance along the path; if L is the tube length of any one section, then the total frictional resistance along the path is obtained by separately calculating the frictional resistances of the three tubes and then summing them up.

[0115] Among them,

[0116]

[0117] In the formula, K is the equivalent roughness; R e is the Reynolds number; ν is the dynamic viscosity of the circulating fluid.

[0118] The local resistance is generated at the elbow of the medium-depth directional ground heat exchanger by the circulating fluid, and can be estimated by taking 2% of the frictional resistance along the path.

[0119] The net power consumption (i.e., power) of the circulating water pump is the sum of the frictional resistance along the path and the local resistance of the medium-depth directional ground heat exchanger.

[0120] Finally, based on the net power consumption of the circulating water pump and the current local electricity price, the annual operating cost of the circulating water pump can be calculated.

[0121] S4: Thermodynamic simulation: Based on the initial design parameters, use a finite element analysis tool (such as ANSYS) to construct a geothermal heat extraction model and simulate the heat extraction capacity and heat interference of the well group.

[0122] Optimization of operating parameters: Evaluate the long-term operating parameters of the system (such as heat exchange efficiency, heat imbalance risk) by simulating different operating conditions (such as medium flow rate, well depth change).

[0123] Specifically, the model parameters obtained for the medium-depth directional ground heat supply system include geological parameters (such as geothermal gradient, specific heat capacity of different heat reservoirs), directional tube heat exchanger parameters (such as heat transfer coefficient of the heat exchanger, drilling diameter, etc.), circulating fluid flow velocity, circulating fluid mass flow rate (it can be understood that the circulating fluid mass flow rate can be directly obtained or can be converted according to the circulating fluid flow velocity), etc. Use the boundary condition of a fixed inlet temperature to evaluate the heat extraction power of the heat exchanger of the medium-depth directional ground heat supply system (or called the medium-depth directional ground heat exchanger or heat exchanger), simulate the medium-depth directional ground heat exchanger for one heating quarter, and obtain the calibrated heat extraction power Q of the heat exchanger:

[0124]

[0125] In the formula, c p is the specific heat capacity of the circulating fluid; q is the mass flow rate of the circulating fluid; Δt is the temperature difference between the inlet and outlet of the heat exchanger, where the temperature difference between the inlet and outlet is the difference between the outlet temperature and the fixed inlet temperature of the heat exchanger.

[0126] Taking the calibrated heat extraction power Q in a heating season as the boundary condition of the system, the long-term heat extraction operating condition of the heat exchanger is simulated with the calibrated heat extraction power to obtain the long-term operating parameters of the system, and the total heat extraction amount Q in the whole life cycle of the medium and deep directional buried pipe heating system is estimated TOTAL :

[0127]

[0128] where t is the operating hours of the system.

[0129] According to the calculated annual operating cost, the system operating cost in the whole life cycle of the medium and deep directional buried pipe heating system can be determined, including:

[0130] According to the annual operating cost, the preset system operating life, and the annual interest rate, the system operating cost in the whole life cycle of the medium and deep directional buried pipe heating system is determined.

[0131] Specifically, the system operating cost C in the whole life cycle of the medium and deep directional buried pipe heating system is calculated according to the life cycle cost model:

[0132]

[0133] where k is the preset system operating life (which can be set according to actual needs); r is the annual interest rate; c ann is the annual operating cost of the system, including the annual operating cost of the heat pump, the annual operating cost of the circulating water pump, and the annual equipment maintenance cost.

[0134] According to the system operating cost and the total heat extraction amount in the whole life cycle, the average energy cost is determined, including:

[0135] Determine the initial investment of the system;

[0136] According to the initial investment of the system, the system operating cost, and the total heat extraction amount, the average energy cost is determined.

[0137] Specifically, the average energy cost QAC of the geothermal system under the life cycle operation is calculated through the average energy cost model as:

[0138]

[0139] where C INIis the initial investment of the system; C is the operating cost of the system, and Q TOTAL is the total heat extraction of the system.

[0140] Among them, the initial investment of the system can include the drilling cost of the medium-deep geothermal well, the purchase cost of equipment, the installation and commissioning cost, the cost of machine room transformation, etc. The purchase cost of equipment includes, for example, the cost of medium-deep buried pipe materials, the cost of water pumps, the cost of heat pumps, etc.

[0141] The deeper the drilling depth and the longer the horizontal heat exchange section, the greater the heat extraction capacity of the medium-deep directional buried tube heat exchanger. However, at the same time, the power consumption of the heat pump and the water pump will also increase, resulting in an increase in the system operating cost. To more intuitively conduct a comprehensive economic comparison of the long-term operation process of the system, this application introduces the average energy cost index to evaluate the economy of the system. The meaning of the average energy cost index is the cost required for the unit heat obtained by the medium-deep directional buried tube heat exchanger. The smaller the average energy cost index, the smaller the cost required to extract the unit heat, and the better the economy of the medium-deep directional buried tube heating system.

[0142] A method for evaluating the economy of a medium-deep directional buried tube heating system further includes: estimating the investment return period of the medium-deep directional buried tube heating system, which may include:

[0143] Determining the annual income and cost within the preset system operation period;

[0144] Estimating the investment return period according to the annual income and cost within the preset system operation period.

[0145] Specifically, the calculation model of the investment return period (i.e., the net present value) NPV of the medium-deep directional buried tube heating system is:

[0146]

[0147] In the formula, C i is the income in the i-th year; C O is the cost in the i-th year; r is the annual interest rate; C INI is the initial investment of the system.

[0148] Among them, the income C i in the i-th year mainly includes the annual heating charge and the income brought by carbon emission reduction in the carbon trading market; the cost C O in the i-th year mainly includes the annual maintenance cost of the system, the annual operation cost of the system and the annual value of the initial investment cost.

[0149] This application introduces the net present value indicator (i.e., the investment return period). The significance of the net present value is the difference between the present value of the future annual income of the system and the present value of the future annual cost of the system calculated at the benchmark discount rate of the heating industry during the operation period of the medium-deep directional buried pipe heating system. The investment payback period of the system can be represented by the net present value indicator. When the net present value indicator starts to be greater than 0, the medium-deep directional buried pipe heating system will recover all the investments of the system and start to make a profit, thereby conducting an economic evaluation of the medium-deep directional buried pipe heating system.

[0150] S5: Project measurement and correction

[0151] Through the actual project operation data (such as heat output, energy consumption, maintenance cost, etc.) and user feedback, comprehensively understand the true performance of the system and provide basic data for model correction.

[0152] Compare and analyze the actual and model data

[0153] Compare the actual operation data with the predicted values of the initial model, identify the deviations of key parameters (such as investment cost, operation cost, system efficiency, etc.), and clarify the model elements that need to be adjusted. Focus on making adjustments to the well type design

[0154] Adjust the initial investment model

[0155] Revise the key parameters in the investment model (such as drilling cost, equipment cost, operation energy consumption), and improve the accuracy of investment calculation through calibration with actual data.

[0156] Optimize the statistical analysis model.

[0157] Update economic indicators such as the life cycle cost, unit heating cost, and investment payback period in the statistical analysis model to improve the prediction ability of long-term economy.

[0158] Establish a dynamic correction mechanism.

[0159] Implement a dynamic correction mechanism based on operation feedback. By continuously updating the model, make it adapt to the actual operation changes and provide a reliable reference for future similar projects.

[0160] The present invention realizes the efficient utilization of underground heat storage resources and the improvement of heat collection capacity by scientifically planning the layout form of well groups (such as directional wells, fishbone type, etc.).

[0161] Design the starting point, turning point, well depth, well spacing and three-dimensional trajectory parameters of the wellbore to ensure the reasonable layout of the well group, and avoid heat interference between wellbores and the increase of construction difficulty.

[0162] Calibrate the thermal parameters of the buried pipe group based on the actual operation feedback to improve the operation efficiency and long-term stability of the system.

[0163] Dynamically correct the initial investment and statistical model according to the actual project operation data, and optimize the life-cycle cost analysis and investment return prediction.

[0164] Establish a closed-loop optimization path from wellbore design to operation evaluation, and ensure the efficiency and economy of the geothermal heating system through technical feedback and model iteration.

[0165] Based on the same concept, the present invention also provides a cost optimization system for a buried pipe system, including a construction module, a solution module, a collection module, a simulation module, and a correction module.

[0166] The construction module is used to construct an optimization problem with the well spacing, kick-off point, and deflection azimuth angle of the directional well group as optimization variables, and with the maximization of the total heat collection capacity of the directional well group and the minimization of the total investment cost as optimization objectives.

[0167] The solution module is used to solve the optimization problem and obtain the wellbore trajectory of the directional well group.

[0168] The collection module is used to generate a well group layout diagram through the wellbore trajectory, construct a numerical model of the buried pipe system based on the well group layout diagram; collect the initial investment cost of the numerical model of the buried pipe system.

[0169] The simulation module is used to perform operation simulation on the numerical model of the buried pipe system, and determine the annual operation cost, the system operation cost over the entire life cycle, and the average energy cost of the buried pipe system according to the simulation results.

[0170] The correction module is used to correct the initial investment cost, annual operation cost, system operation cost over the entire life cycle, and average energy cost according to the actual project situation.

[0171] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concept. Therefore, the appended claims are intended to be construed as including the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0172] Obviously, those skilled in the art can make various changes and deformations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and deformations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and deformations.

Claims

1. A cost optimization method for a buried pipe system, characterized in that, It includes the following steps: Taking the well spacing, kick-off point and deflection azimuth angle of the directional well group as optimization variables, and taking maximizing the total heat collection capacity of the directional well group and minimizing the total investment cost as optimization objectives, an optimization problem is constructed; The optimization problem is solved to obtain the wellbore trajectories of the directional well group; A well group layout diagram is generated through the wellbore trajectories, and a numerical model of the buried pipe system is constructed based on the well group layout diagram; the initial investment cost of the buried pipe system numerical model is collected; The operation of the buried pipe system numerical model is simulated, and the annual operation cost, the system operation cost over the whole life cycle and the average energy cost of the buried pipe system are determined according to the simulation results; The initial investment cost, the annual operation cost, the system operation cost over the whole life cycle and the average energy cost are corrected according to the actual project situation.

2. The cost optimization method of a buried pipe system according to claim 1, characterized in that The specific optimization objectives are as follows: Among them, C i = C1 × Kop + (L total - Kop) × y(d ij , φ i ); In the formula, f is the optimization objective, Q total is the total heat extraction sum of the well group, C total is the total investment cost, Q i is the heat collection capacity of the i-th well, n is the number of wells in the well group, C i is the cost of the i-th well, L total is the total length of the main buried pipe per single well, y(d ij , φ i ) is the cost function of the length per meter of the directional part of the pipe, C1 is the cost per meter of the length of the vertical well part of the pipe, d ij is the well spacing, Kop is the kick-off point, φ i is the deviation azimuth angle.

3. The cost optimization method for a buried pipe system according to claim 1, characterized in that, The optimization problem also includes the following constraint conditions: The well trajectories do not intersect; The total heat extraction is not less than that of the vertical well group.

4. The cost optimization method for a buried pipe system according to claim 1, characterized in that The step of solving the optimization problem to obtain the wellbore trajectories of the directional well group includes the following steps: Multiple individuals are randomly generated, and each individual needs to meet the constraint conditions, and each individual is an optimization variable; The optimization objective values of each individual are obtained; The multiple individuals are crossed and mutated to obtain new individuals; The optimization objective values of the new individuals are obtained; Repeat the above crossing and mutation process until the maximum number of iterations; The optimal individual is output, and the wellbore trajectories of the directional well group are generated through the optimal individual.

5. The cost optimization method for a buried pipe system as claimed in claim 1, characterized in that The initial investment cost includes the geothermal well drilling cost, the pipe material cost and the energy station construction cost.

6. A cost optimization system for a buried pipe system, characterized in that, It includes: A construction module, which is used to construct an optimization problem by taking the well spacing, kick-off point and deflection azimuth angle of the directional well group as optimization variables and taking maximizing the total heat collection capacity of the directional well group and minimizing the total investment cost as optimization objectives; A solving module, which is used to solve the optimization problem to obtain the wellbore trajectories of the directional well group; A collection module, which is used to generate a well group layout diagram through the wellbore trajectories, construct a numerical model of the buried pipe system based on the well group layout diagram, and collect the initial investment cost of the buried pipe system numerical model; A simulation module, which is used to simulate the operation of the buried pipe system numerical model and determine the annual operation cost, the system operation cost over the whole life cycle and the average energy cost of the buried pipe system according to the simulation results; A correction module, which is used to correct the initial investment cost, the annual operation cost, the system operation cost over the whole life cycle and the average energy cost according to the actual project situation.

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