Evaluation method for carbon emission reduction of medium-deep geothermal heating system and related device

Abstract

The invention discloses a method and related device for evaluating carbon emission reduction of a medium-deep geothermal heating system, and the method comprises the steps: building a geothermal well source side heating capability model based on the fluid mechanics and engineering thermodynamics theory, and dividing the load side heating demand scale according to the heating load index and the building area; according to the geothermal well source side heating capacity model and the load side heating demand scale, a multi-parameter combination feasible solution is screened, operation energy consumption and carbon emission calculation is carried out, and economical efficiency evaluation and input-output comprehensive evaluation are carried out; and optimizing different system configuration schemes according to economic evaluation and input-output comprehensive evaluation results. According to the method, the geothermal well parameters and the system operation strategy are collaboratively optimized, the principle of'demand setting by supply ', the multi-parameter combination screening mechanism and the comprehensive carbon emission reduction goodness index are organically combined, and collaborative optimization of geothermal well source side parameters and heating system configuration is achieved.

Description

Technical Field

[0001] This invention belongs to the field of energy-saving technology and relates to an evaluation method and related device for carbon emission reduction in medium-deep geothermal heating systems. Background Technology

[0002] Against the backdrop of global climate change and energy structure transformation, the decarbonization of building heating systems has become a key link in achieving the "dual carbon" goal. Statistics show that building energy consumption accounts for more than 40% of global final energy consumption, with heating energy consumption exceeding 50%. Traditional heating methods, primarily based on fossil fuels, not only face challenges to energy supply security, but their high carbon emissions also make it difficult to meet increasingly stringent environmental policy requirements. As a form of energy with abundant reserves and clean, renewable energy, hydrothermal medium-deep geothermal energy shows broad application prospects in the field of district heating.

[0003] Currently, carbon emission reduction evaluation methods for hydrothermal medium-deep geothermal heating systems can be mainly divided into two categories: local evaluation based on a single parameter and comprehensive evaluation based on system configuration. Local evaluation based on a single parameter mainly analyzes specific parameters (such as geothermal well outlet water temperature or production / injection flow rate), using traditional thermodynamic models or numerical simulation methods. However, such methods only focus on the impact of a single parameter on carbon emissions, failing to consider the coupling relationship between multiple parameters such as well depth, geothermal gradient, and outlet water flow rate, as well as the synergistic effect of different system configurations such as direct and indirect heating. This leads to biases in the assessment of the overall carbon emission reduction potential of the system, thus limiting its application in guiding engineering practice. The other type is comprehensive evaluation based on system configuration. Although it treats the system as a whole, existing methods mostly focus on resource assessment or energy efficiency analysis of a single heating mode, lacking a comprehensive evaluation framework that can systematically quantify the carbon emission reduction benefits of different configuration schemes under the coupling effect of multiple parameters and comprehensively consider both economic and environmental benefits.

[0004] Therefore, accurate assessment of the carbon reduction benefits of hydrothermal medium-deep geothermal heating systems is a crucial issue in the low-carbon transition of building energy. Traditional methods often overlook the impact of multi-parameter synergy and various configuration options, resulting in the inaccurate quantification and comparison of the system's carbon reduction potential. With the development of system analysis theory and comprehensive evaluation methods, there is an urgent need to construct new methods that can integrate multi-parameter variations, cover different system configurations, and achieve a comprehensive quantitative evaluation of carbon reduction benefits and economic efficiency to support the optimized design and low-carbon operation of such systems. Summary of the Invention

[0005] The purpose of this invention is to provide a method and related apparatus for evaluating carbon emission reduction in medium-deep geothermal heating systems, thereby solving the problem that carbon emission reduction potential cannot be accurately quantified and compared in the prior art.

[0006] To achieve the above objectives, the present invention employs the following technical solution: An evaluation method for carbon emission reduction in medium-deep geothermal heating systems includes: Based on fluid mechanics and engineering thermodynamics, a source-side heating capacity model of geothermal wells is constructed, and the load-side heating demand scale is divided according to the heating load index and building area. Based on the source-side heating capacity model of geothermal wells and the scale of heating demand on the load side, we screened feasible solutions with multiple parameter combinations, carried out calculations on operating energy consumption and carbon emissions, and conducted economic evaluation and comprehensive input-output evaluation. Based on the results of economic evaluation and comprehensive input-output evaluation, different system configuration schemes are selected for optimization.

[0007] Furthermore, in the geothermal well source-side heating capacity model, the method for calculating the outlet water temperature is as follows:

[0008] in, Let be the average annual surface temperature of a certain region. For geothermal gradient, For the depth of the well, Temperature changes are caused by heat loss in the wellbore.

[0009] Furthermore, the screening process for feasible solutions with multiple parameter combinations includes: Based on the geothermal well parameters and load-side heating scale in the geothermal well source-side heating capacity model, a mapping relationship between parameter combinations and heating capacity is established. Through the supply-demand matching principle and multi-dimensional parameter constraints, a feasible configuration scheme that meets the system operation requirements is initially selected from all possible parameter combinations.

[0010] Furthermore, operating energy consumption includes the power consumption of variable frequency water pumps, the power consumption of heat pumps, and natural gas consumption; The power consumption of the variable frequency water pump is:

[0011] in, The power consumption of the variable frequency water pumps in each section. This represents the actual power consumption of the variable frequency water pumps in each load rate range. The time percentage for each load factor interval. Total heating duration; The power consumption of the heat pump is:

[0012] in, The power consumption of the heat pumps in each area, This represents the actual power consumption of the heat pump in each load rate range. The time percentage for each load factor interval. Total heating duration; Natural gas consumption is:

[0013] in, For the efficiency of gas-fired boilers, It is a low-calorific-value natural gas. Total heating load.

[0014] Furthermore, the calculation of carbon emissions includes carbon emissions from the operation of gas-fired boilers for heating and carbon emissions from hydrothermal heating systems; The carbon emissions from gas-fired boiler heating operation are:

[0015] in, As a carbon emission factor for natural gas, This refers to natural gas consumption. The carbon emission intensity of a gas-fired boiler heating system is:

[0016] in, The carbon emissions from the operation of the water pumps in the heating system are represented by A, where A is the building area under heating. The carbon emission intensity of hydrothermal heating systems is:

[0017] in, As a carbon emission factor for electricity, The power consumption of the variable frequency water pump This refers to the power consumption of the heat pump.

[0018] Furthermore, the comprehensive carbon emission reduction excellence index is used for economic evaluation and input-output comprehensive evaluation. The calculation method for the comprehensive carbon emission reduction excellence is as follows:

[0019]

[0020] in, For the first The cost per unit area of ​​the heating system with this configuration. Carbon emission intensity of hydrothermal heating systems Carbon emission intensity of gas-fired boiler heating systems.

[0021] Furthermore, the method for optimizing different system configuration schemes is as follows: Based on the economic evaluation and the comprehensive input-output evaluation results, and according to the overall carbon emission reduction advantages, the feasible configurations are ranked and compared to select the optimal system parameter combination and operation mode.

[0022] An evaluation system for carbon emission reduction in a medium-deep geothermal heating system includes: The planning module is used to construct a source-side heating capacity model of geothermal wells based on fluid mechanics and engineering thermodynamics theories, and to divide the load-side heating demand scale according to heating load indicators and building area. The calculation module is used to screen feasible solutions with multiple parameter combinations based on the source-side heating capacity model of geothermal wells and the scale of heating demand on the load side, to carry out calculations of operating energy consumption and carbon emissions, and to conduct economic evaluation and comprehensive input-output evaluation. The optimization module is used to select the best system configuration scheme based on the results of economic evaluation and comprehensive input-output evaluation.

[0023] A terminal device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method.

[0024] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method.

[0025] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a method for evaluating carbon emission reduction in medium-deep geothermal heating systems. Based on fluid mechanics and engineering thermodynamics theories, a source-side heating capacity model is constructed for medium-deep geothermal wells according to different parameter combinations. The source-side heating capacity is calculated, and the load-side heating demand scale is divided according to heating load indicators and building area. Then, based on the source-side heating capacity model and the load-side heating demand scale, the source-side capacity and load demand are matched according to the principle of "supply-driven demand," and feasible system configuration schemes under multiple parameter combinations are screened to ensure the rationality of the evaluation basis. Secondly, a comprehensive evaluation system covering energy intensity, carbon emission intensity, and economic indicators is established. Operating energy consumption and carbon emission calculations are performed, and economic evaluation and comprehensive input-output evaluation are conducted to achieve synergistic quantification of multi-dimensional performance. An innovative comprehensive input-output carbon emission reduction excellence index is proposed to achieve integrated evaluation of carbon emission reduction benefits and economic costs. Finally, based on the results of the economic evaluation and comprehensive input-output evaluation, different system configuration schemes are optimized. This invention, through theoretical analysis, clarifies the coupling relationship between multiple parameters such as geothermal well depth, geothermal gradient, and outflow rate, and their impact on system performance. It constructs a system-level carbon reduction evaluation framework that includes source-side heating capacity calculation, operational energy consumption and carbon emission modeling, and economic evaluation. A method for quantifying the carbon reduction potential of medium-deep geothermal well heating systems based on multi-parameter combination and comprehensive evaluation significantly improves the accuracy and practicality of low-carbon performance assessment for geothermal heating systems. This invention is the first to construct a carbon reduction evaluation system encompassing the coupling of multiple parameters such as well depth, geothermal gradient, and outflow rate. By synergistically optimizing geothermal well parameters and system operation strategies, it organically combines the "supply-driven demand" principle, multi-parameter combination screening mechanism, and comprehensive carbon reduction excellence index, achieving synergistic optimization of geothermal well source-side parameters and heating system configuration. While ensuring heating demand is met, through system matching and parameter optimization, it significantly improves the system's energy efficiency and carbon reduction benefits, providing a systematic solution for the low-carbon design of regional centralized heating systems.

[0026] Furthermore, through practical case studies in the Guanzhong Plain of Shaanxi Province, the heating capacity under 27 parameter combinations was systematically evaluated. Optimal configurations were then developed for different heating scales, clarifying the significant differences in carbon emission reduction benefits between direct and indirect heating modes. The results show that this invention can effectively identify the optimal low-carbon configuration for different heating scales, reducing the carbon emission intensity of geothermal heating systems to 1.08–3.03 kg CO2 / (m²). 2 •a) Carbon emission reduction intensity reaches 7.69~9.66 kg CO2 / m 2The direct heating mode significantly outperforms the indirect heating mode in both energy efficiency and carbon emission reduction, achieving an optimal carbon emission reduction value of 33.79 kg CO2 / 1000 yuan. This effectively solves the problems of inaccurate parameter matching and the mismatch between system configuration economy and carbon emission reduction benefits in traditional designs, providing theoretical support for the selection of heating modes in practical engineering. Compared with traditional single-parameter or single-mode evaluation methods, the method proposed in this invention significantly improves system energy efficiency and enhances the flexibility and adaptability of system design, demonstrating clear advantages in terms of systematicity, accuracy, and engineering guidance. Therefore, this invention can provide a scientific basis for the optimized design, low-carbon operation, and policy formulation of hydrothermal medium-deep geothermal heating systems, and has significant application value in promoting the transformation of building heating energy structure.

[0027] Furthermore, this invention innovatively proposes a comprehensive carbon emission reduction excellence index, which takes into account equipment energy consumption, carbon emission intensity, and economic efficiency, and realizes a comprehensive quantitative evaluation of carbon emission reduction benefits and investment costs, providing a clear multi-objective decision-making basis for system optimization.

[0028] Furthermore, by establishing a calculation model for the heating capacity of geothermal well source side, the influence of parameters such as well depth, geothermal gradient, and flow rate on the outlet water temperature and heating capacity is accurately reflected, making the system design more in line with actual geothermal resource conditions.

[0029] Furthermore, by using gas-fired boiler heating systems as the carbon emission benchmark, the carbon reduction potential of geothermal heating systems was clarified, enhancing the comparability and persuasiveness of the evaluation system. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart of an evaluation method for carbon emission reduction in a medium-deep geothermal heating system according to the present invention.

[0032] Figure 2 This is a schematic diagram of the hydrothermal medium-deep geothermal direct heating system of the present invention.

[0033] Figure 3 This is a schematic diagram of the hydrothermal medium-deep geothermal indirect heating system of the present invention.

[0034] Figure 4 This is a graph showing the total energy consumption results for different system configurations in Embodiment 1 of the present invention.

[0035] Figure 5 This is a diagram showing the total cost of the heating system configuration for each system in Embodiment 1 of the present invention.

[0036] Figure 6 This is a graph showing the carbon emissions during the heating season for each system configuration with different heating scales in Embodiment 1 of the present invention.

[0037] Figure 7 This is a diagram showing the carbon emission reduction intensity of different heating scale systems in Embodiment 1 of the present invention.

[0038] Figure 8 This is a schematic diagram of the carbon emission reduction evaluation system of the deep geothermal heating system in a preferred embodiment of the present invention.

[0039] Figure 9 This is a schematic diagram of the electronic device structure according to a preferred embodiment of the present invention. Detailed Implementation

[0040] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0041] Obviously, the described embodiments are only some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0042] It should be noted that the terminals involved in the embodiments of this application may include, but are not limited to, mobile phones, personal digital assistants (PDAs), wireless handheld devices, tablet computers, personal computers (PCs), MP3 players, MP4 players, wearable devices (e.g., smart glasses, smartwatches, smart bracelets), smart home devices, and other smart devices.

[0043] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0044] The present invention will now be described in further detail with reference to the accompanying drawings: This invention proposes a method for quantifying the carbon reduction potential of medium-deep geothermal well heating systems based on multi-parameter combination and systematic comprehensive evaluation. This method leverages the significant advantages of different system configurations and comprehensive evaluation in energy system analysis, utilizing variations in multiple geothermal well parameters, to achieve parallel evaluation of carbon reduction benefits under different configuration schemes through multi-level parameter combinations. This method significantly improves the accuracy and practicality of low-carbon performance evaluation for geothermal heating systems.

[0045] This invention systematically designs and implements a comprehensive carbon emission reduction evaluation process based on multi-parameter coupled analysis. The entire process consists of multiple evaluation modules, including source-side heating capacity calculation, supply-demand matching initial screening, energy consumption and carbon emission modeling, economic evaluation, and comprehensive carbon emission reduction excellence calculation. First, the source-side heating capacity is calculated based on different parameter combinations of medium-deep geothermal wells. Second, based on the principle of "supply-driven demand," source-side capacity and load demand are matched, and feasible system configuration schemes under multiple parameter combinations are screened to ensure the rationality of the evaluation basis. Finally, a comprehensive evaluation system covering energy intensity, carbon emission intensity, and economic indicators is established to achieve synergistic quantification of multi-dimensional performance. An innovative input-output comprehensive carbon emission reduction excellence index is proposed to achieve integrated evaluation of carbon emission reduction benefits and economic costs. This invention breaks through the limitations of traditional single-parameter evaluation, realizing the synergistic quantification of energy consumption, carbon emissions, and economic efficiency. Matching energy supply capacity and load demand based on the principle of "supply-driven demand" ensures engineering applicability and provides a quantitative basis for low-carbon decision-making. By using a parallel evaluation process, scenarios with multiple parameter combinations can be handled efficiently, significantly shortening the analysis cycle.

[0046] See Figure 1 This invention provides a method for evaluating carbon emission reduction in medium-deep geothermal heating systems, mainly comprising six steps: constructing a source-side heating capacity model of geothermal wells, classifying the scale of load-side heating demand, screening feasible solutions with multi-parameter combinations, calculating operational energy consumption and carbon emissions, conducting economic evaluation and comprehensive input-output evaluation, and finally optimizing different system configuration schemes. Specifically, it includes the following steps: Step 1: Construct a geothermal well source-side heating capacity model. Constructing a geothermal well source-side heating capacity model refers to the process of determining the heat output capacity of the extraction and reinjection system by selecting key parameters such as well depth, geothermal gradient, and water flow rate, and then calculating the wellhead outlet water temperature and reinjection temperature using empirical formulas, based on fluid mechanics and engineering thermodynamics theories. The approximate formula for calculating the outlet water temperature based on well depth, geothermal gradient, and water flow rate is as follows: (1) In the formula, The average annual surface temperature of a certain region is expressed in °C. The geothermal gradient is expressed in °C / hm². Let the well depth be m; Temperature changes caused by heat loss in the wellbore are typically 2-5°C and are negatively correlated with flow rate.

[0047] This process utilizes the principles of thermodynamic equilibrium and heat transfer to establish a calculation framework for source-side heating capacity, providing fundamental data for subsequent system configuration and carbon emission reduction assessment. During modeling, wellhead temperature and flow rate, as core input parameters, jointly determine the source-side heating potential, while the selection of reinjection temperature directly affects system energy efficiency and sustainability. See the schematic diagram of a medium-deep geothermal heating system. Figure 2 and Figure 3 However, due to the wide range of parameters in geothermal wells, significant coupling effects from multiple factors, and the involvement of nonlinear heat loss and geological uncertainties, the modeling process requires handling multivariate collaborative analysis and parameter sensitivity assessment. Therefore, the parameter combination screening and "supply-demand-based" matching mechanism adopted in this study can effectively improve the practicality and engineering applicability of the model.

[0048] Step 2: Determine the scale of heating demand on the load side. Determining the scale of heating demand on the load side refers to the process of determining heating load indicators based on building type, usage function, and regional climate characteristics, and then classifying the heat load demand corresponding to different building areas. This process, through load calculation and scale grouping, achieves precise matching of supply and demand under the principle of "supply determines demand," avoiding problems such as "over-engineered systems" or insufficient capacity in system configuration. In the delineation process, the heating load indicator and building area jointly determine the total heat demand on the load side, and the classification result directly relates to the selection range of subsequent system configurations. For example, dividing the heating demand scale into 5 levels, covering building areas of 60,000 to 180,000 square meters, corresponds to design heat loads of 1800 to 5400 kW. However, due to diverse building usage patterns and dynamic changes in outdoor weather conditions, the actual heat load fluctuates in time and space, and the delineation process needs to consider both typicality and representativeness. Therefore, using an arithmetic progression classification and load interval mapping method can enhance the systematicity and applicability of the delineation results.

[0049] Step 3: Screening Feasible Solutions with Multi-Parameter Combinations. Screening feasible solutions with multi-parameter combinations refers to the process of initially selecting feasible configuration schemes that meet the system's operational requirements from all possible parameter combinations under given geothermal well parameter variation ranges and load-side heating scale conditions, through supply-demand matching principles and multi-dimensional parameter constraints. This process establishes a mapping relationship between parameter combinations and heating capacity, and conducts preliminary screening based on the principles of "supply-demand matching, avoiding redundancy, and ensuring diversity," providing a candidate solution set for subsequent detailed evaluation. During the screening process, the interactive influence of parameters such as well depth, flow rate, geothermal gradient, and reinjection temperature jointly determines the structural characteristics of feasible solutions. For example, based on 27 multi-parameter combinations, multiple initial feasible solutions were screened for five heating scales, and a symbolic representation was used for system identification. However, due to the large number of parameter combinations and diverse constraints, the screening process needs to strike a balance between computational efficiency and solution set quality. Therefore, introducing preliminary selection rules and structural solution expression methods can significantly improve the logical clarity and operability of the screening process.

[0050] Step 4: Conduct operational energy consumption calculations and carbon emission reduction assessments. This step involves establishing energy consumption models for key equipment such as variable frequency water pumps and heat pump units for each feasible system configuration, calculating the total electricity consumption during the heating season based on partial load operating characteristics and time distribution, and further evaluating carbon emission reductions.

[0051] According to the similarity law of fluid mechanics, the power consumed by a water pump is... (The sentence is incomplete and requires more context to translate accurately.) It can be derived from its frequency Approximate calculation of the relationship: (2) In the formula, This is the rated power of the water pump, in kW; The rated operating frequency of the water pump is 50Hz.

[0052] Assuming the heating system operates under constant temperature difference control, the heating partial load rate is... The relationship with the frequency ratio is: (3) In the formula, For dynamic heating load, kW; The corresponding water flow rate (m) during heating system operation. 3 / h.

[0053] Assuming the lower limit frequency of the variable frequency water pump is 35Hz, the actual operating frequency of the water pump is... Determined by the following formula: (4) Assuming the total heating season duration is The hourly partial load ranges are defined as follows: t1 for ΔPLR1 = 100%~75%, t2 for ΔPLR2 = 75%~50%, t3 for ΔPLR3 = 50%~25%, and t4 for ΔPLR4 = 25%~0%. Therefore, the actual power consumption of the variable frequency pumps in each range is... The total power consumption of the variable frequency water pump can be calculated using formula (2). It can be calculated using the following formula: (5) In the formula, The power consumption of the variable frequency water pumps in each section is given in kWh.

[0054] For heat pump units, the rated heating capacity Rated operating conditions Assuming that the inlet and outlet temperatures of the water flow in the condenser and evaporator remain basically constant during heat pump heating, the change in the heating capacity of the heat pump mainly depends on the water flow rate. From formula (3), we know that... Relationship with flow rate, actual operating conditions Correction coefficient The following formula can be used to fit the data based on the heat pump manufacturer's data or actual operating data: (6) In the formula, a0, a1, and a2 are fitting coefficients.

[0055] Assuming the total heating duration during the heating season is [duration missing] The time percentages for partial load ranges are as follows: t1 = 100%~75%, t2 = 75%~50%, t3 = 50%~25%, and t4 = 25%~0%. Therefore, the actual power consumption of the heat pump in each range is... The calculation formula is: (7) In the formula, dynamic heating load The average heating load of the interval can be taken as the actual value; the actual value of the heat pump The average value of its interval can be taken; heating partial load rate It can be taken as the average value of the load factor of the interval.

[0056] Total power consumption of heat pump It can be calculated using the following formula: (8) In the formula, The heat pump power consumption for each zone is expressed in kWh.

[0057] During the calculation process, the equipment partial load performance correction, frequency control strategy and operating time distribution jointly determine the total energy consumption level of the system, while the electricity carbon factor is directly related to the carbon emission results.

[0058] This invention selects a gas-fired boiler heating system as the carbon emission comparison benchmark. Assuming the heating target and heating terminal are the same, the energy-consuming equipment in this heating system is mainly a variable frequency water pump and a gas-fired boiler. The power consumption of the variable frequency water pump can be calculated using formulas (2) to (5). The total heating load is... It can be calculated using the following formula: (9) Natural gas consumption Calculation formula: (10) In the formula, For the efficiency of the gas-fired boiler, take 0.9; The lower calorific value of natural gas is taken as 9.77 kWh / m³. 3 .

[0059] Carbon emissions from gas-fired boiler heating operation : (11) In the formula, The carbon emission factor for natural gas is taken as 2.16 kgCO2 / m³. 3 .

[0060] Carbon emission intensity of gas boiler heating systems (kgCO2 / m 2 ): (12) In the formula, Carbon emissions from the operation of the heating system's water pumps, expressed in kgCO2; A represents the heating building area, expressed in m². 2 .

[0061] Carbon emission intensity of hydrothermal heating systems (kgCO2 / m 2 ): (13) In the formula, The carbon emission factor for the Northwest Power Grid is taken as 0.583 kgCO2 / kWh.

[0062] Based on the above formula, it can be calculated that different system configurations... The hydrothermal carbon emission intensity is Compared to the baseline scenario for carbon emission intensity, the [missing information] Carbon emission reduction effect of hydrothermal medium-deep geothermal heating system under this configuration (kgCO2 / m 2 )for: (14) Step 5 involves conducting an economic evaluation and a comprehensive input-output evaluation. This step involves combining market price information and system configuration parameters to estimate the initial investment cost of each feasible scheme, and further constructing a comprehensive carbon emission reduction excellence index. This process comprehensively considers carbon emission reduction benefits and unit investment costs, achieving a synergistic evaluation of economic and environmental benefits. Let the estimated first step... The cost per unit area of ​​the heating system configured in this system is (yuan / m) 2 ), then the first The overall carbon emission reduction efficiency of a hydrothermal medium-deep geothermal heating system under this system configuration (kgCO2 / thousand yuan) is: (15) Step 6 involves optimizing different system configurations. Based on the overall carbon emission reduction efficiency score, system configurations are ranked from highest to lowest efficiency. This process, after evaluating energy consumption, carbon emissions, and economic viability, ranks and compares feasible configurations based on indicators such as system energy efficiency, carbon emission reduction intensity, unit cost, and overall carbon emission reduction efficiency, ultimately recommending the optimal system parameter combination and operating mode. However, due to potential constraints in actual engineering projects, such as regional policies, user needs, or technological limitations, the optimization results need to be adapted to specific scenarios. Therefore, providing multi-indicator ranking and parameter impact analysis can offer flexible and systematic decision support for engineering design and operation optimization.

[0063] The present invention will be further described in detail below through specific embodiments: Example 1: This embodiment selects a real hydrothermal medium-deep geothermal well in Xianyang area of ​​Guanzhong, Shaanxi Province as the research object to verify the comprehensive evaluation method of carbon emission reduction of heating system by combining multiple parameters of medium-deep geothermal wells. The well depth in this embodiment is 2000~3000 meters, the geothermal gradient is 2.6~3.2℃ / 100m, and the water flow rate is 45~105m3 / h. The purpose is to test the ability of the carbon emission reduction quantification method of this application to solve practical problems in medium-deep geothermal well heating systems. The changes of multiple parameters of the geothermal well in this embodiment are shown in Table 1.

[0064] Table 1. Changes in key operating parameters of geothermal wells

[0065] Using formula (1), the wellhead water temperature for 27 different scenarios can be calculated. Based on the three temperature ranges: >76℃, 65~76℃, and <65℃, and adhering to the principle of efficient geothermal energy utilization, the reinjection water temperature is defined as 40℃, 30℃, and 25℃ respectively. For example... Figure 2 and Figure 3 As shown, the corresponding heating modes are ModeⅠ and ModeⅡ, respectively. Let their COP=5 and COP=4.3. According to the first law of thermodynamics, the heating capacity of the load side of the machine room can be calculated, as shown in Tables 2 to 4.

[0066] Table 2. Source-side heating capacity for cases 1-9 at a well depth of 2000 meters.

[0067] Table 3. Source-side heating capacity for cases 10-18 at a well depth of 2500 meters.

[0068] Table 4. Source-side heating capacity for cases 19-27 at a well depth of 3000 meters.

[0069] To meet the heating demand on the load side, the heating load index is set at 30W / m². 2 The heating building area is 60,000 / 90,000 / 120,000 / 150,000 / 180,000 m² 2 The corresponding heating load requirements are 1800 / 2700 / 3600 / 4500 / 5400 kW. The load-side heating capacity ranges from 1895 to 5764 kW, meaning the load-side heating capacity can meet the heating needs of buildings with a floor area of ​​approximately 65,000 to 195,000 m². 2 Therefore, the heating demand on the load side is divided into five levels: 60,000 m² 2 (1800kW), 90,000m 2 (2700kW), 120,000m 2 (3600kW), 150,000m 2 (4500kW), 180,000m 2 (5400kW). Five different heating scales were set up for multi-scenario analysis to verify the applicability and stability of the present invention under different load demands. The optimization results have good engineering reference value.

[0070] The variations in the multi-parameter combinations of the injection and extraction well groups result in 27 scenarios. Each combination corresponds to a heating capacity on the load side of the machine room, and each combination also constructs a hydrothermal medium-deep geothermal heating system configuration. When the scale of heating demand on the load side is different, this study proposes the following initial selection principles for the feasible solutions of the multi-parameter combinations: (1) the principle of supply and demand matching to avoid the phenomenon of "overkill"; (2) the principle of selecting parameters with multiple dimensions of influence to ensure the diversity of the initial feasible solutions. Based on these principles, the initial feasible solutions of the multi-parameter combinations for different heating demand scales are shown in Table 5.

[0071] Table 5 Initial feasible solutions for multi-parameter combinations of well groups with different heating demand scales.

[0072] The parameter structure of the multi-parameter combined solution is S ijk m (H i ,L ij ,T g ijk / T h m The subscript i represents well depth, j represents water flow rate, k represents geothermal gradient, and the superscript m represents heating mode. H i (i=1,2,3) represent well depths of 2 / 2.5 / 3 km respectively; L ij (i=1,2,3;j=1,2,3) represents 9 different flow rates m at 3 different well depths. 3 / h;T g ijk (i=1,2,3;j=1,2,3;k=1,2,3) represent the outlet water temperature (°C) of 27 water production wells under different well depth / flow rate / geothermal gradient conditions; T h m (m=1,2,3) represent different heating modes (direct heating mode I, indirect heating modes II-a and II-b), with corresponding reinjection water temperatures of 40 / 30 / 25℃ respectively. For example, this corresponds to a heating demand of 60,000 m³. 2 The initial feasible solutions for the multi-parameter combination are: S1113, S1123, S1213, S1223, S1132, and so on.

[0073] As shown in Table 5, different heating scales correspond to different feasible solutions, which in turn correspond to different system configurations. For ease of explanation, the different system configurations for different heating scales are represented by the symbols HSXSCY, where X=1,2,3,4,5 represent the five heating scales in sequence, and Y=1,2,3,4,5 represent the corresponding five system configurations in sequence. For example, a heating demand scale of 60,000 m³... 2There are 5 initial feasible solutions with multiple parameter combinations, corresponding to 5 system configurations, which can be represented as HS1SC1, HS1SC2, HS1SC3, HS1SC4, and HS1SC5, respectively. The others follow the same pattern and will not be elaborated further.

[0074] 1. Energy consumption calculation and optimal solution selection The total heating season duration for residential buildings in Xianyang is 120 × 24 = 2880 hours. The empirical values ​​for the time percentages of the heating load factor ΔPLR1 to ΔPLR4 are 0.2 / 0.3 / 0.3 / 0.2, respectively. The energy consumption of each variable frequency water pump during the heating season can be calculated based on the performance parameters of each pump using formulas (2) to (5). The energy consumption of the heat pump unit during the heating season can be calculated based on the performance parameters of the heat pump using formulas (6) to (8). The total energy consumption results for different system configurations are as follows: Figure 4 As shown.

[0075] from Figure 4 The total power consumption analysis shows that higher well water flow and temperature are beneficial to improving the overall energy efficiency of the heating system, specifically manifested in a reduction in total power consumption. Under the same well water flow conditions, the higher the well water temperature, the more obvious the system's energy efficiency advantage. Furthermore, when there is a significant surplus of heating capacity on the load side, appropriately increasing the reinjection water temperature also helps improve system energy efficiency. Comparison of different heating modes reveals that the energy efficiency of the direct heating mode is significantly higher than that of the indirect heating mode. Therefore, the energy efficiency ranking of each system configuration from best to worst is as follows: HS1SC4>HS1SC5>HS1SC2>HS1SC3>HS1SC1; HS2SC5>HS2SC3>HS2SC4>HS2SC1>HS2SC2; HS3SC5>HS3SC3>HS3SC4>HS3SC2>HS3SC1; HS4SC5>HS4SC4>HS4SC3>HS4SC2>HS4SC1; HS5SC4>HS5SC3>HS5SC2>HS5SC1.

[0076] 2. Economic evaluation and optimal solution selection Based on the system selection calculation results and market price information, the cost of various system configurations for different heating scales can be obtained. Figure 5It can be seen that the unit area cost of each system configuration can be calculated, so their economic advantages are ranked as follows: HS1SC1>HS1SC2>HS1SC5>HS1SC3>HS1SC4; HS2SC3>HS2SC1>HS2SC2>HS2SC4>HS2SC5; HS3SC1>HS3SC2>HS3SC3>HS3SC4>HS3SC5; HS4SC1>HS4SC2>HS4SC3>HS4SC5>HS4SC4; HS5SC3>HS5SC1>HS5SC4>HS5SC2.

[0077] 3. Carbon emission reduction assessment and optimal solution selection (1) Benchmark carbon emissions For gas boiler heating systems, the carbon emissions of the gas boiler and heating circulation variable frequency water pump are calculated using formulas (2)~(5) and (9)~(12). The calculation results are summarized in Table 6.

[0078] Table 6 Comparison Benchmark (Gas-fired Boiler Heating System): Carbon Emissions and Emission Intensity During Heating Season for Different Heating Scales

[0079] (2) Carbon emissions and emission reductions of medium-deep geothermal heating systems For hydrothermal medium-deep geothermal heating systems, based on energy consumption calculations and baseline carbon emission calculations, the carbon emissions and carbon reduction intensity of each system configuration with different heating scales can be calculated using formulas (13) and (14). Figure 6 and Figure 7 It is evident that the ranking of carbon emission reduction intensity of various system configurations for different heating scales is completely consistent with their corresponding energy efficiency ranking.

[0080] 4. Comprehensive evaluation of carbon emission reduction based on input and output based on Figure 5 System cost data and Figure 7 The carbon emission reduction intensity data in the data were used to calculate the comprehensive carbon emission reduction of the input and output of the hydrothermal medium-deep geothermal heating system using formula (15), as shown in Table 7.

[0081] Table 7. Overall Carbon Emission Reduction of Hydrothermal Medium-Deep Geothermal Heating System (Input and Output)

[0082] As shown in Table 7, the ranking of the overall carbon emission reduction efficiency of each system configuration is as follows: HS1SC5>HS1SC2>HS1SC4>HS1SC1>HS1SC3; HS2SC3>HS2SC1>HS2SC5>HS2SC4>HS2SC2; HS3SC3>HS3SC2>HS3SC5>HS3SC1>HS3SC4; HS4SC5>HS4SC3>HS4SC4>HS4SC2>HS4SC1; HS5SC3>HS5SC4>HS5SC1>HS5SC2.

[0083] In summary, all experimental results indicate that the dominant influencing factor on system energy efficiency is water intake temperature, system cost is mainly controlled by well depth, and the overall input-output carbon emission reduction is influenced by parameters such as water intake temperature and well depth. Through the study of this embodiment, the system energy efficiency COP ranges from 8.71 to 24.4, with an average value of 15.24; the carbon emission intensity CIWHS is 1.08 to 3.03 kgCO2 / (m²). 2 •a), with an average value of 1.84 kg CO2 / (m 2 a) Carbon emission reduction intensity CI is 7.69~9.66 kg CO2 / m 2 The average value is 8.90 kg CO2 / m³. 2 The system cost is CIVEST 286~399 RMB / m². 2 The average price is 324.27 yuan / m². 2 The input-output integrated carbon emission reduction (CCERI) ranged from 21.41 to 33.79 kg CO2 / thousand yuan, with an average of 27.71 kg CO2 / thousand yuan. Significant differences existed in system energy efficiency and input-output integrated carbon emission reduction under different heating modes: the average COP for direct heating mode I was 23.45, while for indirect heating modes II-a and II-b it was 14.72 and 12.17, respectively; the average CCERI for mode I was 31.48 kg CO2 / thousand yuan, while for modes II-a and II-b it was 28.12 kg CO2 / thousand yuan and 24.88 kg CO2 / thousand yuan, respectively.

[0084] Example 2: This invention also provides an evaluation system for carbon emission reduction in medium-deep geothermal heating systems, such as... Figure 8 As shown, the system includes: a planning module, a calculation module, and an optimization module.

[0085] The planning module is used to construct a source-side heating capacity model of geothermal wells based on fluid mechanics and engineering thermodynamics theories, and to divide the load-side heating demand scale according to heating load indicators and building area. The calculation module is used to screen feasible solutions with multiple parameter combinations based on the source-side heating capacity model of geothermal wells and the scale of heating demand on the load side, to carry out calculations of operating energy consumption and carbon emissions, and to conduct economic evaluation and comprehensive input-output evaluation. The optimization module is used to select the best system configuration scheme based on the results of economic evaluation and comprehensive input-output evaluation.

[0086] It is understood that the carbon emission reduction evaluation system for medium-deep geothermal heating systems provided by this invention corresponds to the carbon emission reduction evaluation methods for medium-deep geothermal heating systems provided in the foregoing embodiments. The relevant technical features of the carbon emission reduction evaluation system for medium-deep geothermal heating systems can be referred to the relevant technical features of the carbon emission reduction evaluation methods for medium-deep geothermal heating systems, and will not be repeated here.

[0087] Another object of the present invention is to provide an electronic device, such as... Figure 9 As shown, it includes a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor performing the steps of the carbon emission reduction evaluation method for the medium-deep geothermal heating system.

[0088] The evaluation method for carbon emission reduction of the medium-deep geothermal heating system includes the following steps: Based on fluid mechanics and engineering thermodynamics, a source-side heating capacity model of geothermal wells is constructed, and the load-side heating demand scale is divided according to the heating load index and building area. Based on the source-side heating capacity model of geothermal wells and the scale of heating demand on the load side, we screened feasible solutions with multiple parameter combinations, carried out calculations on operating energy consumption and carbon emissions, and conducted economic evaluation and comprehensive input-output evaluation. Based on the results of economic evaluation and comprehensive input-output evaluation, different system configuration schemes are selected for optimization.

[0089] A fourth objective of this invention is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the carbon emission reduction evaluation method for the medium-deep geothermal heating system.

[0090] The evaluation method for carbon emission reduction of the medium-deep geothermal heating system includes the following steps: Based on fluid mechanics and engineering thermodynamics, a source-side heating capacity model of geothermal wells is constructed, and the load-side heating demand scale is divided according to the heating load index and building area. Based on the source-side heating capacity model of geothermal wells and the scale of heating demand on the load side, we screened feasible solutions with multiple parameter combinations, carried out calculations on operating energy consumption and carbon emissions, and conducted economic evaluation and comprehensive input-output evaluation. Based on the results of economic evaluation and comprehensive input-output evaluation, different system configuration schemes are selected for optimization.

[0091] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0092] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0093] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0094] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for evaluating carbon emission reduction in a medium-deep geothermal heating system, characterized in that, include: Based on fluid mechanics and engineering thermodynamics, a source-side heating capacity model of geothermal wells is constructed, and the load-side heating demand scale is divided according to the heating load index and building area. Based on the source-side heating capacity model of geothermal wells and the scale of heating demand on the load side, we screened feasible solutions with multiple parameter combinations, carried out calculations on operating energy consumption and carbon emissions, and conducted economic evaluation and comprehensive input-output evaluation. Based on the results of economic evaluation and comprehensive input-output evaluation, different system configuration schemes are selected for optimization.

2. The evaluation method for carbon emission reduction in a medium-deep geothermal heating system according to claim 1, characterized in that, In the geothermal well source-side heating capacity model, the method for calculating the outlet water temperature is as follows: in, Let be the average annual surface temperature of a certain region. For geothermal gradient, For the depth of the well, Temperature changes are caused by heat loss in the wellbore.

3. The evaluation method for carbon emission reduction in a medium-deep geothermal heating system according to claim 1, characterized in that, The process of selecting feasible solutions with multiple parameters includes: Based on the geothermal well parameters and load-side heating scale in the geothermal well source-side heating capacity model, a mapping relationship between parameter combinations and heating capacity is established. Through the supply-demand matching principle and multi-dimensional parameter constraints, a feasible configuration scheme that meets the system operation requirements is initially selected from all possible parameter combinations.

4. The evaluation method for carbon emission reduction in a medium-deep geothermal heating system according to claim 1, characterized in that, Operating energy consumption includes the power consumption of variable frequency water pumps, the power consumption of heat pumps, and natural gas consumption; The power consumption of the variable frequency water pump is: in, The power consumption of the variable frequency water pumps in each section. This represents the actual power consumption of the variable frequency water pumps in each load rate range. The time percentage for each load factor range. This refers to the total duration of heating. The power consumption of the heat pump is: in, The power consumption of the heat pumps in each area, This represents the actual power consumption of the heat pump in each load rate range. The time percentage for each load factor range. This refers to the total duration of heating. Natural gas consumption is: in, For the efficiency of gas-fired boilers, It is a low-calorific-value natural gas. Total heating load.

5. The evaluation method for carbon emission reduction in a medium-deep geothermal heating system according to claim 1, characterized in that, The calculation of carbon emissions includes carbon emissions from the operation of gas-fired boilers for heating and carbon emissions from hydrothermal heating systems; The carbon emissions from gas-fired boiler heating operation are: in, As a carbon emission factor for natural gas, This refers to natural gas consumption. The carbon emission intensity of a gas-fired boiler heating system is: in, The carbon emissions from the operation of the water pumps in the heating system are represented by A, where A is the building area under heating. The carbon emission intensity of hydrothermal heating systems is: in, As a carbon emission factor for electricity, The power consumption of the variable frequency water pump This refers to the power consumption of the heat pump.

6. The evaluation method for carbon emission reduction in a medium-deep geothermal heating system according to claim 1, characterized in that, The comprehensive carbon emission reduction excellence index is used for economic evaluation and input-output comprehensive evaluation. The calculation method for the comprehensive carbon emission reduction excellence is as follows: in, For the first The cost per unit area of ​​the heating system with this configuration. Carbon emission intensity of hydrothermal heating systems Carbon emission intensity of gas-fired boiler heating systems.

7. The evaluation method for carbon emission reduction in a medium-deep geothermal heating system according to claim 1, characterized in that, The method for optimizing different system configuration schemes is as follows: Based on the economic evaluation and the comprehensive input-output evaluation results, and according to the overall carbon emission reduction advantages, the feasible configurations are ranked and compared to select the optimal system parameter combination and operation mode.

8. An evaluation system for carbon emission reduction in a medium-deep geothermal heating system, characterized in that, include: The planning module is used to construct a source-side heating capacity model of geothermal wells based on fluid mechanics and engineering thermodynamics theories, and to divide the load-side heating demand scale according to heating load indicators and building area. The calculation module is used to screen feasible solutions with multiple parameter combinations based on the source-side heating capacity model of geothermal wells and the scale of heating demand on the load side, to carry out calculations of operating energy consumption and carbon emissions, and to conduct economic evaluation and comprehensive input-output evaluation. The optimization module is used to select the best system configuration scheme based on the results of economic evaluation and comprehensive input-output evaluation.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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