Geothermal heating project optimization sorting evaluation method, electronic equipment and medium

Abstract

The invention discloses a geothermal heating project optimization sorting evaluation method, electronic equipment and a medium. The method can comprise the steps that first-level indexes and second-level indexes are determined, and an index matrix of m heating projects is established; performing score assignment for the secondary indexes, and establishing an evaluation coefficient matrix of m heating projects; assigning the weights of the first-level indexes and the second-level indexes to obtain a weight matrix of the second-level indexes; according to the weight matrix and the evaluation coefficient matrix of the secondary indexes, comprehensive evaluation coefficients of the m heating projects are calculated and sorted, and an evaluation result is obtained. According to the method, the geothermal heating projects are optimally sorted and rapidly evaluated comprehensively and systematically, and a scientific basis is provided for investment decision-making of the geothermal heating projects.

Description

Technical Field

[0001] The present invention relates to the field of geothermal heating project evaluation, and more specifically, to a method, an electronic device and a medium for preferential ranking evaluation of geothermal heating projects. Background Art

[0002] During the utilization process of geothermal energy for heating, no pollutants such as carbon dioxide, sulfur dioxide, nitrogen oxides and dust are emitted, which has a significant effect on improving the natural environmental conditions and protecting the ecological environment, and plays an important role in helping to achieve the "dual carbon" goal.

[0003] Geothermal heating projects involve many and complex factors. How to select key factors and evaluation methods, and under a unified standard evaluation system, select projects efficiently, scientifically and based on evidence, effectively develop and utilize geothermal energy, and improve economic benefits. Therefore, a preferential analysis method for geothermal heating projects is needed.

[0004] Currently, the neutral evaluation method for geothermal heating projects mainly evaluates the economy. The consideration of resources and reinjection factors is relatively simple. Even for economic factors, it is also relatively general to evaluate with indicators such as internal rate of return and net present value. The heating fee collection rate, occupancy rate, energy-saving situation, etc. that actually affect the economic benefits of geothermal heating projects are not included in the evaluation index system, which will lead to discrepancies between the authenticity of the evaluation results and the coincidence rate with the actual situation, and affect the investment decision-making of geothermal heating projects.

[0005] Therefore, it is necessary to develop a method, an electronic device and a medium for preferential ranking evaluation of geothermal heating projects.

[0006] The information disclosed in the background art part of the present invention is only intended to deepen the understanding of the general background art of the present invention, and should not be regarded as an admission or any form of suggestion that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0007] The present invention provides a method, an electronic device and a medium for preferential ranking evaluation of geothermal heating projects, which comprehensively and systematically perform preferential ranking and rapid evaluation on geothermal heating projects, and provide a scientific basis for the investment decision-making of geothermal heating projects.

[0008] In a first aspect, an embodiment of the present disclosure provides a method for preferential ranking evaluation of geothermal heating projects, including:

[0009] Determine the primary indicators and secondary indicators, and establish an index matrix of m heating projects;

[0010] Score and assign values to the secondary indicators, and establish an evaluation coefficient matrix of m heating projects;

[0011] Assign weights to the first-level indicators and the second-level indicators to obtain the weight matrix of the second-level indicators;

[0012] Calculate the comprehensive evaluation coefficients of m heating projects according to the weight matrix of the second-level indicators and the evaluation coefficient matrix, and sort them to obtain the evaluation results.

[0013] Preferably, the first-level indicators include resource factors, reinjection factors, and economic factors; among them, the resource factors include heat reservoir type, caprock geothermal gradient, drilling depth, average single-well produced water temperature, average single-well produced water volume, and geothermal water salinity; the reinjection factors include formation pressure coefficient, heat reservoir fractures, formation sand production, geothermal water scaling, and reinjection difficulty; the economic factors include heating fee standards, supporting fee standards, water, electricity, and gas price policies, energy conservation conditions, energy consumption per unit area, occupancy rate, and heating fee collection rate.

[0014] Preferably, the index matrix is:

[0015]

[0016] Among them, A is the index matrix, and a ij is the index value of the jth second-level indicator of the ith heating project.

[0017] Preferably, the evaluation coefficient matrix is:

[0018]

[0019] Among them, C is the evaluation coefficient matrix, and c ij is the evaluation coefficient of the jth second-level indicator of the ith heating project.

[0020] Preferably, the weight matrix of the second-level indicators is:

[0021] R 1×n =[q1q 11 ... q1q 16 q2q 21 ... q2q 25 q3q 31 ... q3q 37

[0022] Among them, R 1×n is the weight matrix.

[0023] Preferably, calculating the comprehensive evaluation coefficients of m heating projects according to the weight matrix of the second-level indicators and the evaluation coefficient matrix includes:

[0024] Calculate the comprehensive evaluation coefficient matrix according to the weight matrix of the second-level indicators and the evaluation coefficient matrix; ​

[0025] Determine the comprehensive evaluation coefficients of m heating projects according to the comprehensive evaluation coefficient matrix.

[0026] Preferably, the comprehensive evaluation coefficient matrix is:

[0027] K=(k i ) 1×m =R×C T

[0028] where K is the comprehensive evaluation coefficient matrix, k i is the comprehensive evaluation coefficient of the i-th heating project, and C T is the transpose of the evaluation coefficient matrix.

[0029] Preferably, sort the heating projects according to the magnitudes of the comprehensive evaluation coefficients corresponding to the m heating projects.

[0030] In a second aspect, an embodiment of the present disclosure further provides an electronic device, which includes:

[0031] A memory storing executable instructions;

[0032] A processor that runs the executable instructions in the memory to implement the above-mentioned optimal sorting and evaluation method for geothermal heating projects.

[0033] In a third aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the above-mentioned optimal sorting and evaluation method for geothermal heating projects.

[0034] Its beneficial effects are as follows:

[0035] The present invention determines an evaluation index data system from numerous factors involved in geothermal heating projects. By establishing an evaluation coefficient matrix and a comprehensive weight matrix, calculating the comprehensive evaluation coefficient matrix, and quickly selecting optimal geothermal heating projects, the economic benefits of geothermal heating projects are improved.

[0036] The method and device of the present invention have other characteristics and advantages, which will be obvious from the accompanying drawings incorporated herein and the subsequent specific embodiments, or will be described in detail in the accompanying drawings incorporated herein and the subsequent specific embodiments. These drawings and specific embodiments are jointly used to explain the specific principles of the present invention. Description of the Drawings

[0037] By describing the exemplary embodiments of the present invention in more detail in conjunction with the accompanying drawings, the above-mentioned and other objects, features, and advantages of the present invention will become more obvious. Among them, in the exemplary embodiments of the present invention, the same reference numerals generally represent the same components.

[0038] Figure 1 Shows a schematic diagram of an evaluation index data system according to an embodiment of the present invention.

[0039] Figure 2 Shows a flowchart of the steps of a method for evaluating and ranking geothermal heating projects according to an embodiment of the present invention. Detailed implementation manners

[0040] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein.

[0041] The present invention provides a method for evaluating and ranking geothermal heating projects, including:

[0042] Determine the primary indicators and secondary indicators, and establish an index matrix for m heating projects;

[0043] Score and assign values for the secondary indicators, and establish an evaluation coefficient matrix for m heating projects;

[0044] Assign weights to the primary indicators and secondary indicators to obtain a weight matrix for the secondary indicators;

[0045] Calculate the comprehensive evaluation coefficients of m heating projects according to the weight matrix and evaluation coefficient matrix of the secondary indicators, and rank them to obtain the evaluation results.

[0046] In one example, the primary indicators include resource factors, reinjection factors, and economic factors; among them, the resource factors include heat reservoir type, caprock geothermal gradient, drilling depth, average single-well produced water temperature, average single-well produced water volume, and geothermal water salinity; the reinjection factors include formation pressure coefficient, heat reservoir fracture, formation sand production, geothermal water scaling, and reinjection difficulty; the economic factors include heating fee standard, supporting fee standard, water, electricity and gas price policy, energy conservation situation, energy consumption per unit area, occupancy rate, and heating fee collection rate.

[0047] In one example, the index matrix is:

[0048]

[0049] Among them, A is the index matrix, and a ij is the index value of the jth secondary indicator of the ith heating project.

[0050] In one example, the evaluation coefficient matrix is:

[0051]

[0052] Among them, C is the evaluation coefficient matrix, and cij is the evaluation coefficient of the j-th secondary index for the i-th heating project.

[0053] In one example, the weight matrix of the secondary indexes is:

[0054] R 1×n =[q1q 11 ... q1q 16 q2q 21 ... q2q 25 q3q 31 ... q3q 37

[0055] where R 1×n is the weight matrix.

[0056] In one example, calculating the comprehensive evaluation coefficients of m heating projects based on the weight matrix of the secondary indexes and the evaluation coefficient matrix includes:

[0057] Calculating the comprehensive evaluation coefficient matrix according to the weight matrix of the secondary indexes and the evaluation coefficient matrix;

[0058] Determining the comprehensive evaluation coefficients of m heating projects according to the comprehensive evaluation coefficient matrix.

[0059] In one example, the comprehensive evaluation coefficient matrix is:

[0060] K=(k i ) 1×m =R×C T

[0061] where K is the comprehensive evaluation coefficient matrix, k i is the comprehensive evaluation coefficient of the i-th heating project, and C T is the transpose of the evaluation coefficient matrix.

[0062] In one example, the heating projects are sorted according to the magnitudes of the comprehensive evaluation coefficients corresponding to the m heating projects.

[0063] Figure 1 shows a schematic diagram of an evaluation index data system according to an embodiment of the present invention.

[0064] Specifically, an evaluation index data system is established: The geothermal heating project involves many factors. According to the characteristics and natures of each factor, the evaluation indexes are classified into 3 primary indexes and 18 secondary indexes, such as Figure 1 ​As shown in the figure. The first-level indicators include 3 items: resource factors, reinjection factors, and economic factors. Among them, the resource factors include 6 secondary indicators: geothermal reservoir type, caprock geothermal gradient, drilling depth, average water temperature of single well production, average water production of single well, and geothermal water salinity; the reinjection factors include 5 secondary indicators: formation pressure coefficient, geothermal reservoir fracture, formation sand production, geothermal water scaling, and reinjection difficulty; the economic factors include 7 secondary indicators: heating fee standard, supporting fee standard, water, electricity and gas price policy, energy conservation situation, energy consumption per unit area, occupancy rate, and heating fee collection rate.

[0065] By collecting, sorting, and comprehensively analyzing the evaluation index data of geothermal heating projects, an evaluation index system for geothermal heating projects is established. Suppose m heating projects (samples) are evaluated, including n = 18 evaluation indicators, and the corresponding indicator values are a ij , i = 1, 2,..., m; j = 1, 2,..., n, and its indicator matrix A = (a ij ) m×n is:

[0066]

[0067] The indicator matrix can reflect data organization (set) and also conforms to the operation rules of matrix operations.

[0068] On the basis of comprehensively analyzing geological, reinjection, and economic factors, an evaluation standard for geothermal heating project indicators is established, as shown in Table 1. Each indicator corresponds to different evaluation coefficients according to different value-taking situations. To meet the requirements of data normalization, the evaluation coefficient assignment ∈ [0, 1]. Among the 18 selected evaluation indicators this time, 7 indicators such as geothermal reservoir type, geothermal reservoir fracture, formation sand production, geothermal water scaling, reinjection difficulty, water, electricity and gas price policy, and energy conservation situation are difficult to quantify. The indicator values are given qualitative descriptions, and the corresponding evaluation coefficients are given single values. For example, for formation sand production, it is given three types: no sand production or slight sand production, general sand production, and serious sand production, and the evaluation coefficients are assigned 1, 0.6, and 0.2 respectively; the other 11 indicators can be quantified, and the indicator values are given numerical values.

[0069]

[0070] Establish an indicator evaluation coefficient system: According to the indicator values in the evaluation indicator data system, assign evaluation coefficients corresponding to the indicator values according to the assignment rules of the indicator evaluation standard, and establish an indicator evaluation coefficient system corresponding to the evaluation indicator data system. During the assignment process, for interval data, linear interpolation is used for calculation; for single-value data, it can be directly used.

[0071] m heating projects (samples) include n = 18 evaluation indicators, and the corresponding evaluation coefficients for each indicator are c ij, where \(i = 1, 2, \ldots, m\); \(j = 1, 2, \ldots, n\), and the evaluation coefficient matrix \(C=(c ij ) m×n is:

[0072]

[0073] Establish an index weight system. The index weights are determined using the Delphi method. The Delphi method, also known as the expert survey method, has wide applications in various fields such as science and technology, economy, and social development. The greatest advantage of this type of method is its simplicity and intuitiveness. There is no need to establish a cumbersome mathematical model. Moreover, in the absence of information and historical statistical data, relying on the knowledge and experience of experts, through direct or simple calculations, a comprehensive analysis and research of the research object and its future state and development can be effectively predicted.

[0074] According to the principle of combining representativeness and authority, several experts with rich experience in the field of geothermal heating are selected. Based on the comparison of the relative importance of the same-level indicators, the weights of each indicator are determined. The higher the importance, the greater the weight. Among them, the sum of the weights of the first-level indicators is equal to 1, and the sum of the weights of the secondary indicators included in each first-level indicator is also equal to 1. After the experts give the weights of the first-level indicators and secondary indicators, their average values are taken as the final weight values. Finally, the product of the weight of the first-level indicator and its corresponding secondary indicator weight is taken as the comprehensive weight of the secondary indicator, as shown in Table 2.

[0075] Table 2 Weights of evaluation indicators determined by the Delphi method

[0076]

[0077]

[0078] Denote \(R 1×n as the comprehensive weight matrix of the secondary indicators, which is:

[0079] R 1×n =[q1q 11 ... q1q 16 q2q 21 ... q2q 25 q3q 31 ... q3q 37

[0080] Let the comprehensive evaluation coefficients corresponding to \(m\) heating projects be \(k i , where \(i = 1, 2, \ldots, m\), and the comprehensive evaluation coefficient matrix \(K=(k i ) 1×m is:

[0081] K=(k i ) 1×m ​= R × C T

[0082] Finally, according to the comprehensive evaluation coefficients k1, k2, ..., k m sort the relative advantages and disadvantages of the heating projects according to their magnitudes.

[0083] The present invention also provides an electronic device, which includes: a memory storing executable instructions; a processor that runs the executable instructions in the memory to implement the above-mentioned optimal sorting and evaluation method for geothermal heating projects.

[0084] The present invention also provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the above-mentioned optimal sorting and evaluation method for geothermal heating projects.

[0085] To facilitate understanding of the solutions and effects of the embodiments of the present invention, the following gives three specific application examples. Those skilled in the art should understand that this example is only for facilitating the understanding of the present invention, and any specific details are not intended to limit the present invention in any way.

[0086] Example 1

[0087] Figure 2 shows a flowchart of the steps of the optimal sorting and evaluation method for geothermal heating projects according to an embodiment of the present invention.

[0088] As Figure 2 shown, the optimal sorting and evaluation method for geothermal heating projects includes: Step 101, determining the primary indicators and secondary indicators, and establishing an index matrix for m heating projects; Step 102, performing score assignment for the secondary indicators to establish an evaluation coefficient matrix for m heating projects; Step 103, assigning weights to the primary indicators and secondary indicators to obtain a weight matrix for the secondary indicators; Step 104, calculating the comprehensive evaluation coefficients of m heating projects according to the weight matrix and evaluation coefficient matrix of the secondary indicators, and sorting to obtain an evaluation result.

[0089] Select 6 geothermal heating projects with typical representatives as empirical research cases, and the project numbers are Prog-1 - Prog-6 respectively. Among them, Prog-1 and Prog-4 are of the karst heat reservoir type, Prog-2 is of the fractured limestone heat reservoir type, and Prog-3, Prog-5 and Prog-6 are of the sandstone heat reservoir type. Through collection, collation and analysis, a value data system corresponding to these 6 projects and 18 indicators is established, as shown in Table 3, and this work is the basis of the research.

[0090]

[0091] According to the index evaluation criteria in Table 1, determine the evaluation coefficient values corresponding to each index in Table 3, and establish the index evaluation coefficient matrix C as follows:

[0092]

[0093] According to the format in Table 2, calculate the first-level index weights, second-level index weights, and comprehensive weights based on the scores given by multiple experts, and establish the evaluation index weight matrix R as follows:

[0094] R = [0.0756 0.063 0.0378 0.1176 0.1008 0.0252 0.033 0.033 0.0396 0.022 0.0924 0.0864 0.0576 0.036 0.0216 0.036 0.0612 0.0612]

[0095] Using the matrix multiplication function in Excel, establish the comprehensive evaluation coefficient matrix K as follows:

[0096] K = [0.8578 0.8339 0.8151 0.7951 0.8070 0.6633].

[0097] Then the project comprehensive evaluation coefficient result table is Table 4.

[0098] Table 4 Project Comprehensive Evaluation Coefficient Result Table

[0099] Project Number Prog-1 Prog-2 Prog-3 Prog-4 Prog-5 Prog-6 Comprehensive Evaluation Coefficient 0.8578 0.8339 0.8151 0.7951 0.8070 0.6633

[0100] As shown in Table 4, according to the size of the comprehensive evaluation coefficient, the projects are ranked from good to bad as Prog-1 > Prog-2 > Prog-3 > Prog-5 > Prog-4 > Prog-6. Among them, project Prog-1 is the best and project Prog-6 is the worst. Project Prog-1 has superior geological conditions and recharge conditions, manifested as well-developed karst, a geothermal gradient as high as 5.1 °C / 100m, a shallow heat reservoir depth, large water volume, high water temperature, well-developed heat reservoir fractures, good formation recharge, and high development and utilization value. Project Prog-6 is a sandstone heat reservoir with a low geothermal gradient (3.0 °C / 100m), low water temperature, small water volume, serious sand production in the formation, poor recharge, and although the heating fee standard and supporting fee standard are relatively high, the occupancy rate is low (34.4%), and overall the development and utilization value is poor.

[0101] Example 2

[0102] The present disclosure provides an electronic device, which includes: a memory storing executable instructions; a processor that runs the executable instructions in the memory to implement the above-mentioned optimal sorting and evaluation method for geothermal heating projects.

[0103] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0104] The memory is used to store non - transitory computer - readable instructions. Specifically, the memory may include one or more computer program products, and the computer program products may include various forms of computer - readable storage media, such as volatile memory and / or non - volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non - volatile memory may include, for example, read - only memory (ROM), hard disk, flash memory, etc.

[0105] The processor may be a central processing unit (CPU) or other forms of processing units with data - processing capabilities and / or instruction - execution capabilities, and may control other components in the electronic device to perform desired functions. In an embodiment of the present disclosure, the processor is used to run the computer - readable instructions stored in the memory.

[0106] Those skilled in the art should understand that, in order to solve the technical problem of how to obtain good user experience effects, this embodiment may also include well - known structures such as communication buses, interfaces, etc., and these well - known structures should also be included in the protection scope of the present disclosure.

[0107] For a detailed description of this embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, and details will not be repeated here.

[0108] Example 3

[0109] An embodiment of the present disclosure provides a computer - readable storage medium storing a computer program, and when the computer program is executed by a processor, the foregoing preferred - sorting evaluation method for geothermal heating projects is implemented.

[0110] A computer - readable storage medium according to an embodiment of the present disclosure stores non - transitory computer - readable instructions. When the non - transitory computer - readable instructions are run by a processor, all or part of the steps of the methods of the foregoing embodiments of the present disclosure are executed.

[0111] The foregoing computer - readable storage medium includes, but is not limited to: optical storage media (such as CD - ROM and DVD), magneto - optical storage media (such as MO), magnetic storage media (such as magnetic tapes or removable hard disks), media with built - in rewritable non - volatile memory (such as memory cards), and media with built - in ROM (such as ROM cartridges).

[0112] Those skilled in the art should understand that the purpose of the above description of the embodiments of the present invention is only to exemplarily illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any of the examples given.

[0113] The embodiments of the present invention have been described above. The above description is exemplary and not exhaustive, and is also not limited to the disclosed embodiments. Many modifications and variations are obvious to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for evaluating and ranking the preference of geothermal heating projects, characterized in that, Including: Determine the first-level indicators and the second-level indicators, and establish an indicator matrix for m heating projects; Assign scores to the second-level indicators to establish an evaluation coefficient matrix for m heating projects; Assign weights to the first-level indicators and the second-level indicators to obtain the weight matrix of the second-level indicators; According to the weight matrix of the second-level indicators and the evaluation coefficient matrix, calculate the comprehensive evaluation coefficients of m heating projects and sort them to obtain the evaluation results.

2. The preferred ranking evaluation method for geothermal heating projects according to claim 1, wherein The first-level indicators include resource factors, reinjection factors, and economic factors; among them, the resource factors include heat reservoir type, caprock geothermal gradient, drilling depth, average single-well produced water temperature, average single-well produced water volume, and geothermal water salinity; the reinjection factors include formation pressure coefficient, heat reservoir fracture, formation sand production, geothermal water scaling, and reinjection difficulty; the economic factors include heating fee standard, supporting fee standard, water, electricity and gas price policy, energy conservation situation, energy consumption per unit area, occupancy rate, and heating fee collection rate.

3. The geothermal heating project optimal ranking evaluation method according to claim 2, wherein, The indicator matrix is: Among them, A is the index matrix, and a ij is the index value of the j-th secondary index of the i-th heating project.

4. The preferred sorting and evaluation method for geothermal heating projects according to claim 2, wherein, The evaluation coefficient matrix is: Among them, C is the evaluation coefficient matrix, and c ij is the evaluation coefficient of the j-th secondary index of the i-th heating project.

5. The geothermal heating project optimal sorting and evaluation method according to claim 4, wherein, The weight matrix of the second-level indicators is: R 1×n = [q1q 11 ...q1q 16 q2q 21 ...q2q 25 q3q 31 ...q3q 37 ​ Among them, R 1×n is the weight matrix.

6. The method for evaluating the optimal ranking of a geothermal heating project according to claim 5, wherein, Calculating the comprehensive evaluation coefficients of m heating projects according to the weight matrix of the second-level indicators and the evaluation coefficient matrix includes: Calculate the comprehensive evaluation coefficient matrix according to the weight matrix of the second-level indicators and the evaluation coefficient matrix; Determine the comprehensive evaluation coefficients of m heating projects according to the comprehensive evaluation coefficient matrix.

7. The preferred ranking evaluation method for geothermal heating projects according to claim 6, wherein, The comprehensive evaluation coefficient matrix is: K=(k i ) 1×m =R×C T Among them, K is the comprehensive evaluation coefficient matrix, and k i is the comprehensive evaluation coefficient of the i-th heating project, and C T is the transpose of the evaluation coefficient matrix.

8. The preferred ranking evaluation method for geothermal heating projects according to claim 7, wherein, Sort the heating projects according to the magnitudes of the comprehensive evaluation coefficients corresponding to m heating projects.

9. An electronic device, characterized in that, The electronic device includes: A memory storing executable instructions; A processor that runs the executable instructions in the memory to implement the optimal sorting and evaluation method for geothermal heating projects according to any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the optimal sorting and evaluation method for geothermal heating projects according to any one of claims 1-8.

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