A Method for Optimizing the Diameter of Heating Pipe Networks Based on an Improved Economic Evaluation Index System

Abstract

This application discloses a method for optimizing the pipe diameter design of heating pipe networks based on an improved economic evaluation index system. The steps include: obtaining the topology of the heating pipe network, constructing a sample space of pipe diameter combinations according to constraints, and selecting several pipe diameter combination samples; obtaining the design and operation parameters of the heating pipe network, calculating economic sub-indicators and normalizing them; calculating the weights of each economic sub-indicator based on the pipe diameter combination samples using the entropy weight method; determining whether the weight values ​​are independent of the sample size; if not, increasing the sample size and recalculating the weights; if so, establishing an improved economic evaluation index system for the heating pipe network based on the weight values; and using an optimization algorithm to find the optimal pipe diameter combination design scheme for the heating pipe network according to the improved economic evaluation index system. This application solves the problem of traditional pipe diameter optimization design failing to consider the differences in the degree of influence of each economic sub-indicator on pipe diameter design, resulting in a lack of balance between the importance of sub-indicators, and helps to obtain a more reasonable pipe diameter optimization design scheme.

Description

Technical Field

[0001] This invention belongs to the field of urban centralized heating energy efficiency improvement technology, and in particular relates to a heating network pipe diameter optimization design method based on an improved economic evaluation index system. Background Technology

[0002] The investment cost of the primary heating network accounts for a dominant position in the total investment cost of the entire urban centralized heating system. The length and diameter of each pipe in the network are the decisive factors affecting this investment cost. Furthermore, pipe length and diameter significantly influence heat loss and pump energy consumption. When designing a heating network, the network topology is largely determined by urban heating planning, resulting in limited room for optimizing pipe lengths. Therefore, optimizing pipe diameter becomes a key factor affecting the economic benefits and energy efficiency of the heating network and the entire centralized heating system.

[0003] Pipeline investment cost and operating energy consumption are key aspects of pipe diameter optimization design, as they are mutually influential and restrictive: as the pipe diameter increases, pipeline investment increases while operating energy consumption decreases; conversely, as the pipe diameter decreases, pipeline investment decreases while operating energy consumption increases. Therefore, for all pipe diameter combinations within the network, there exists an optimal pipe diameter design scheme that simultaneously optimizes both pipeline investment and operating energy consumption. The "Design Code for Urban Heating Pipelines" (CJJ 34-2010) provides an engineering design method for pipe diameter: for the main pipeline, the pipe diameter is determined using economic friction resistance (economic friction resistance is a recommended value for optimal pipeline design friction resistance based on design, construction, and operation experience, taking into account pipeline investment, operating power consumption, and heat loss costs). Based on the recommended economic friction resistance range and the design flow rate of each main pipeline segment, the pipe diameter is determined from the hydraulic calculation table of the heating network. For branch lines and trunk lines of the heating network, the diameter is determined based on the aforementioned determined friction resistance of each main pipeline segment and... The pressure loss of the main pipeline is calculated based on the total equivalent length (pipe segment length + local resistance equivalent length). Then, according to the principle of node balance, the available pressure difference of each branch line is determined. Based on the available pressure difference and the design flow rate of each pipe segment, the pipe diameter can be determined from the hydraulic calculation table of the heating network. Considering hydraulic stability and other issues, the standard stipulates that the flow velocity of the heating medium in the branch lines should not exceed 3.5 m / s, and the specific friction resistance of the branch lines should not exceed 300 Pa / m. The specific friction resistance of a branch line connecting to a heating station can exceed 300 Pa / m. Although the above engineering design method implicitly includes an optimization process, within the range of specific friction resistance recommended by the standard, the hydraulic calculation table of the heating network usually offers several pipe diameter specifications to choose from. Considering the mutual influence and constraints between the investment cost and operating energy consumption of the pipeline network under different pipe diameters, it is impossible to directly select the pipe diameter with the best overall performance from the candidate specifications. Therefore, it is urgent to develop a pipe diameter optimization design method for heating pipeline networks to provide a theoretical basis for simultaneously reducing pipeline network investment costs and operating energy consumption.

[0004] Traditional pipe diameter optimization design methods mostly consider economic benefits, using economic sub-indicators such as annual equivalent investment cost, annual operating cost, and annual heat loss cost as optimization targets, or directly adding up the sub-indicators to obtain the annual equivalent cost as a comprehensive evaluation index for pipe diameter design. However, simply adding up the various economic sub-indicators means that each sub-indicator plays the same role in the comprehensive evaluation, without considering the objective differences in the degree of influence of different sub-indicators on pipe diameter design. This results in a lack of balance among the sub-indicators in the comprehensive evaluation index, making it impossible to objectively evaluate the comprehensive economic performance of the pipeline network. Consequently, the pipe diameter optimization design of heating pipeline networks lacks a scientifically reasonable optimization objective. Summary of the Invention

[0005] This invention addresses the shortcomings of existing pipe diameter optimization design methods by proposing a pipe diameter optimization design method for heating pipe networks based on an improved economic evaluation index system. This method fully considers the varying degrees of influence of different economic sub-indicators on pipe network construction costs, and combines a pipe network diameter combination sample construction method with the entropy weight method to quantify these differences, thereby establishing an improved comprehensive economic evaluation index system as the optimization target for pipe network diameter design.

[0006] The present invention solves the technical problems of existing pipe diameter optimization design methods through the following technical solutions.

[0007] This invention provides a method for optimizing the design of heating network pipe diameter based on an improved economic evaluation index system, comprising the following steps:

[0008] Obtain the topology of the heating network, construct a sample space of pipe diameter combinations according to constraints, and select several pipe diameter combination samples from the sample space.

[0009] Obtain the design and operation parameters of the heating network, and calculate the economic sub-indices of the pipe diameter combination sample;

[0010] The aforementioned economic sub-indicators are normalized.

[0011] The entropy weight method is applied to calculate the weight values ​​of each economic sub-index in the pipe diameter optimization design based on the pipe diameter combination sample.

[0012] Determine whether the weight value is independent of the number of pipe diameter combination samples. If the weight value still depends on the number of pipe diameter combination samples, increase the number of pipe diameter combination samples and recalculate the weight value until the weight value no longer changes with the increase of the number of pipe diameter combination samples.

[0013] An economic evaluation index system for improving heating pipe networks is established based on the aforementioned weight values.

[0014] Based on the improved economic evaluation index system, an optimization algorithm is used to find the optimal pipe diameter combination design scheme for the heating network.

[0015] In one possible implementation, the constraints include pipe diameter range, upstream and downstream pipe diameter constraints, heating medium flow rate, and pipe segment specific friction.

[0016] In one possible implementation, the economic sub-indicators of the heating network include annual equivalent investment costs and annual operating costs; for heating network pipe diameter combination i, its economic sub-indicator j is calculated and expressed as:

[0017] x ij (i = 1, 2, ..., m; j = 1, 2).

[0018] In one possible implementation, the normalization process for the economic sub-indicators is performed using the range method, and the calculation formula is as follows:

[0019]

[0020] In the formula, maxx j minx represents the maximum value of the economic sub-index j among all pipe diameter combinations. j This represents the minimum value of the economic sub-index j among all pipe diameter combinations.

[0021] In one possible implementation, the application of the entropy weight method to calculate the weight values ​​of each of the economic sub-indicators in the pipe diameter optimization design based on the pipe diameter combination sample includes:

[0022] The contribution of the pipe diameter sample combination to each of the aforementioned economic sub-indicators is calculated using the following formula:

[0023]

[0024] The information entropy of each of the aforementioned economic sub-indicators is calculated using the following formula:

[0025]

[0026] The weight values ​​of each of the aforementioned economic sub-indicators are calculated using the following formula:

[0027]

[0028] Among them, P ij e represents the contribution of pipe diameter combination sample i to the economic sub-index j. j ω represents the information entropy of the economic sub-indicator j. j This represents the weight value of the economic performance sub-indicator j.

[0029] In one possible implementation, the strategy for setting the number of pipe diameter combination samples includes:

[0030] From the sample space, a number of S pipe diameter combination samples are initially selected, and the weight values ​​of each of the economic sub-indicators are calculated.

[0031] The number of pipe diameter combination samples is multiplied by 2S, 4S, 8S, 16S, ..., and the weight values ​​of each economic sub-indicator are repeatedly calculated until the weight values ​​are independent of the number of pipe diameter combination samples.

[0032] In one possible implementation, the criterion for determining that the weight value is independent of the number of pipe diameter combination samples includes: the relative error between two consecutive weight values ​​satisfies the following formula:

[0033] δ=|(ω j,k -ω j,k-1 ) / ω j,k-1 |<10 -3 (k = 2, 3, 4, ...)

[0034] In the formula, k represents the number of times the weight value is repeatedly calculated; ω j,k ω represents the weight value of the economic sub-indicator j in the k-th calculation; j,k-1 This represents the weight value of the economic sub-indicator j in the (k-1)th calculation.

[0035] In one possible implementation, establishing an economic evaluation index system for heating network improvement based on the weighted values ​​includes: calculating the comprehensive evaluation score of the heating network pipe diameter combination using the following formula:

[0036]

[0037] In the formula, P ij ω represents the contribution of pipe diameter combination sample i to the economic sub-index j. j The value represents the weight of the economic sub-indicator j. i This represents the overall evaluation score of pipe diameter combination sample i.

[0038] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0039] This invention provides a method for optimizing the pipe diameter of heating networks based on an improved economic evaluation index system. This method can allocate weights according to the degree of influence of economic sub-indicators on pipe diameter design, so as to take into account the differences in their influence on pipe diameter design. This solves the problem of neglecting the differences in the degree of influence of each sub-indicator on pipe diameter design in traditional pipe diameter optimization design, which leads to the lack of weighting of sub-indicators. This helps to obtain a more reasonable pipe diameter optimization design scheme. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments of the present invention or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 A flowchart of a heating network pipe diameter optimization design method based on an improved economic evaluation index system provided in an embodiment of the present invention;

[0042] Figure 2 A diagram illustrating the process by which the weight values ​​gradually stabilize as the number of pipe diameter combination samples increases, as provided in this embodiment of the invention.

[0043] Figure 3 A flowchart of an algorithm for finding the optimal pipe diameter combination for a heating network using a genetic algorithm, provided in an embodiment of the present invention;

[0044] Figure 4 This is a diagram illustrating the iterative process of an algorithm using a genetic algorithm to find the optimal pipe diameter combination for a heating network, as provided in an embodiment of the present invention.

[0045] Figure 5 A statistical comparison chart of the pipe diameter selection length in the pipe diameter optimization design scheme based on traditional and improved economic evaluation index systems provided in the embodiments of the present invention.

[0046] Figure 6A The pipe diameter and pressure drop diagram of the most unfavorable branch and its various pipe sections in the pipe diameter optimization design scheme based on the traditional economic evaluation index system provided in the embodiments of the present invention;

[0047] Figure 6B The pipe diameter and pressure drop diagram of the most unfavorable branch and its various pipe sections in the pipe diameter optimization design scheme based on the improved economic evaluation index system provided in the embodiments of the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0049] In a specific example, this application focuses on optimizing the pipe diameter design of a heating network with an already completed pipe layout. Embodiments of this invention provide a method for optimizing the pipe diameter of a heating network based on an improved economic evaluation index system, such as... Figure 1 As shown, the method includes:

[0050] Step S101: Obtain the topology of the heating network, construct a sample space of pipe diameter combinations according to the constraints, and select several pipe diameter combination samples from it.

[0051] Step S102: Obtain the design and operation parameters of the heating network and calculate the economic sub-indices of the pipe diameter combination sample;

[0052] Step S103: Normalize the economic sub-indicators.

[0053] Step S104: Apply the entropy weight method to calculate the weight values ​​of each economic sub-index in the pipe diameter optimization design based on the pipe diameter combination sample;

[0054] Step S105: Determine whether the weight value is independent of the number of pipe diameter combination samples. If the determination result is yes, proceed to step S107; if the determination result is no, proceed to steps S106, S102, S103, S104 and S105.

[0055] Step S106: Increase the number of pipe diameter combination samples.

[0056] Step S107: Establish an economic evaluation index system for improving the heating network based on weight values.

[0057] Step S108: Based on the improved economic evaluation index system, use the optimization algorithm to find the optimal pipe diameter combination design scheme for the heating network.

[0058] In step S101, the constraints selected for pipe diameter optimization design in this application are as follows:

[0059] (1) Pipe diameter specifications: Based on the "Municipal Engineering Investment Estimation Index" compiled by the Ministry of Construction of the People's Republic of China, and combined with the supply and demand of steel pipe market and the load demand of heat users, this application selects 19 discrete pipe diameter specifications, including DN50, DN65, DN80, DN100, DN125, DN150, DN200, DN250, DN300, DN350, DN400, DN450, DN500, DN600, DN700, DN800, DN900, DN1000, and DN1200.

[0060] (2) Pipe diameter constraints of upstream and downstream sections: In actual heating networks, the pipe diameter of the downstream section should not be greater than that of the upstream section, that is, the pipe diameter of each section should meet the following requirement: d i ≥d j , where d i Indicates the pipe diameter of the upstream section, d j This indicates the diameter of the downstream pipe section.

[0061] (3) Heating medium flow velocity: According to the industry standard of the People's Republic of China "Design Code for Urban Heating Pipeline Network", the flow velocity of the heating medium in the main line and branch line of the hot water heating network should not exceed 3.5m / s.

[0062] (4) Specific friction resistance of pipe sections: The "Code for Design of Urban Heating Pipeline Networks" stipulates that the economic specific friction resistance should be used when determining the diameter of the main pipeline of the hot water heating network. The value of the economic specific friction resistance should be calculated and determined according to the specific conditions of the project. The specific friction resistance of the main pipeline can be 30Pa / m to 70Pa / m. The specific friction resistance of the branch pipeline should not be greater than 300Pa / m, and the specific friction resistance of the branch pipeline connecting a heating station can be greater than 300Pa / m.

[0063] Of course, other engineering issues that pipe diameter optimization designers are concerned with can also be used as constraints. The combination of these constraints with pipe diameter optimization design ensures the engineering applicability of the pipe diameter design results.

[0064] In step S102, this application selects the annual equivalent investment cost and annual operating cost as economic sub-indicators for pipe diameter optimization design. Of course, other economic sub-indicators that pipe diameter optimization designers are concerned with can also be included in the evaluation scope. The calculation process of the indicators is as follows:

[0065] Annual deferred investment cost C1 is the cost that is calculated by converting the total initial investment in the heating network to the annual cost. The formula is as follows:

[0066] C1 = X t ·C cap ,

[0067] In the formula, C cap It is the total initial investment; the investment recovery factor X tDefined as the ratio of the annual return to the initial investment, under compound interest conditions, within the designed payback period; total initial investment C cap The calculation formula is as follows:

[0068]

[0069] In the formula, f(d) i ) indicates that the pipe diameter is d i The cost per unit length of steel pipe (raw material cost plus laying cost), l i This represents the length of each section of steel pipe in the heating network. Investment recovery factor X t The calculation formula is as follows:

[0070]

[0071] In the formula, i represents the bank interest rate, and n represents the design service life of the heating network.

[0072] Annual operating cost C2 is the total cost incurred by the heating network for a full year. To simplify the calculation, maintenance and depreciation costs are ignored, and the electricity cost of the circulating water pumps is used as the annual operating cost of the heating network. The calculation formula is as follows:

[0073]

[0074] In the formula, P represents the pressure drop of the most unfavorable branch, Q represents the flow rate of the circulating water pump, η represents the efficiency of the circulating water pump, hour represents the number of operating hours of the circulating water pump in a day, day represents the number of operating days of the circulating water pump in a year, and price represents the electricity price for industrial use. The most unfavorable branch refers to the path in the heating network with the largest pressure drop between the heat source and the heat user. Its pressure drop P is obtained by summing the pressure drops of all pipe sections on the most unfavorable branch, and the calculation formula is as follows:

[0075]

[0076] In the formula, ΔP represents the pressure drop in the pipe section, including the friction loss ΔP. y Local resistance loss ΔP j and the drag loss ΔP caused by the height difference g The calculation formula is as follows:

[0077] ΔP=ΔP y +ΔP j +ΔP g .

[0078] For typical heating network systems, there is almost no height difference, therefore ΔP can be ignored. g The formula for calculating friction loss is as follows:

[0079] ΔPy =R m ·l,

[0080] In the formula, R m The local drag coefficient (specific friction) can be calculated using Darcy's formula:

[0081]

[0082] In the formula, λ represents the frictional resistance coefficient, ν represents the flow velocity of the heating medium in the pipe section, and R s The hydraulic radius of a pipe section, which is the ratio of its cross-sectional area to its wetted perimeter, is calculated using the following formula:

[0083]

[0084] In the formula, D represents the inner diameter of the pipe section. The formula for calculating the frictional resistance coefficient λ depends on the magnitude of the Reynolds number Re in the flow inside the pipe:

[0085]

[0086] In the formula, K represents the absolute roughness of the pipe material, which is usually taken as 0.5 mm for outdoor pipe networks. The formula for calculating the flow velocity v of the heating medium is:

[0087]

[0088] In the formula, Q represents the volumetric flow rate of each pipe section, which can be calculated based on the design heat load of the heating network and the supply and return water temperatures.

[0089]

[0090] In the formula, E represents the design heat load; c represents the specific heat of the heat transfer medium, and the specific heat of water is 4187 J / (kg·℃); t g With t h These represent the supply water temperature and the return water temperature, respectively.

[0091] According to the "Design Code for Urban Heating Pipeline Networks", the ratio of local resistance loss to friction loss in hot water pipelines can be represented by α. Therefore, the formula for calculating the pressure drop in a pipe section can be written as:

[0092] ΔP=ΔP y (1+α)

[0093] For the pipe diameter combination sample mentioned in step S101, its annual equivalent investment cost and annual operating cost can be calculated according to the above process and expressed as follows:

[0094] x ij (i = 1, 2, ..., m; j = 1, 2)

[0095] In step S103, the economic sub-indicator data are normalized. The data normalization method proposed in this application is the range method; however, Z-score standardization, sigmoid function, and other normalization methods can also be used. It is easy to see that annual discounted investment costs and annual operating costs are both cost indicators. The calculation formula for cost indicators using the range method is as follows:

[0096]

[0097] In the formula, maxx j minx represents the maximum value of the economic sub-index j among all pipe diameter combinations. j This represents the minimum value of the economic sub-index j among all pipe diameter combinations.

[0098] In step S104, the entropy weight method is applied to calculate the weight values ​​of annual equivalent investment cost and annual operating cost in pipe diameter optimization design based on the pipe diameter combination sample. The weight value calculation process includes:

[0099] The contribution of pipe diameter combination samples to each economic sub-indicator is calculated using the following formula:

[0100]

[0101] The information entropy of each economic sub-indicator is calculated using the following formula:

[0102]

[0103] The weight values ​​of each economic sub-indicator are calculated using the following formula:

[0104]

[0105] Among them, P ij e represents the contribution of pipe diameter combination sample i to the economic sub-index j. j ω represents the information entropy of the economic sub-indicator j. j This represents the weight value of the economic performance sub-indicator j.

[0106] In step S105, the criteria for determining that the weight values ​​are independent of the number of pipe diameter combination samples include: the relative error between two consecutive weight values ​​satisfies:

[0107] δ=|(ω j,k -ω j,k-1 ) / ω j,k-1 |<10 -3 (k = 2, 3, 4, ...)

[0108] In the formula, k represents the number of times the weight value is repeatedly calculated; ω j,kω represents the weight value of the economic sub-indicator j in the k-th calculation; j,k-1 This represents the weight value of the economic sub-indicator j in the (k-1)th calculation.

[0109] The purpose of setting this criterion is to ensure that the sample size in the sample space is sufficient and includes all characteristics of the heating pipe network diameter combinations. The process of the indicator weights gradually stabilizing as the sample size increases is shown in... Figure 2 In the study, the weights of the annual equivalent investment cost and the annual operating cost remained stable at 0.29 and 0.71, respectively. This result indicates that, in this embodiment of the invention, the annual operating cost has a greater impact on pipe diameter optimization design than the annual equivalent investment cost.

[0110] In step S106, the strategy for setting the number of pipe diameter combination samples includes:

[0111] From the sample space, a number of S pipe diameter combination samples are initially selected, and the weight values ​​of each of the economic sub-indicators are calculated.

[0112] The number of pipe diameter combination samples is multiplied by 2S, 4S, 8S, 16S, ..., and the weight values ​​of each economic sub-indicator are repeatedly calculated until the weight values ​​are independent of the number of pipe diameter combination samples.

[0113] In step S107, an economic evaluation index system for improving the heating network is established based on numerically stable index weights. For a certain pipe diameter combination in the heating network, its comprehensive evaluation score can be calculated using the following formula:

[0114]

[0115] In the formula, P ij ω represents the contribution of pipe diameter combination sample i to the economic sub-index j. j The value represents the weight of the economic sub-indicator j. i This represents the overall evaluation score of pipe diameter combination sample i.

[0116] In step S108, an optimization algorithm is used to find the optimal pipe diameter combination scheme for the heating network. A specific optimization algorithm proposed in this application is a genetic algorithm. Of course, particle swarm optimization algorithms, simulated annealing algorithms, etc., can also be used as optimization algorithms here.

[0117] Genetic algorithms are used to find the optimal pipe diameter combination scheme for heating pipe networks, such as... Figure 3 As shown, the optimization process includes steps S301 to S307:

[0118] Step S301: Input the topology and calculation parameters of the heating network to be designed;

[0119] Step S302: Define design variables, fitness function, constraints and termination conditions, and generate the initial population;

[0120] Step S303: Perform crossover and mutation operations on the individuals in the population to obtain the offspring population, and merge it with the parent population;

[0121] Step S304: Calculate the fitness of individuals in the population;

[0122] Step S305: Determine whether to terminate the calculation based on the preset termination condition; if the determination result is yes, then terminate the calculation and execute step S307; if the determination result is no, then continue to execute S306, S303, S304 and S305.

[0123] Step S306: Select individuals with high fitness to form the parent population;

[0124] Step S307: Output the optimal pipe diameter combination.

[0125] In step S302, the design variable is the pipe diameter. Unlike conventional variables, the pipe diameter is not continuous but discrete. The fitness function is set to the improved economic evaluation index system established in this invention. The higher the comprehensive evaluation score of the pipe diameter combination, the greater its fitness value.

[0126] The termination condition for the genetic algorithm proposed in this application is set as follows:

[0127]

[0128] In the formula, value max,gen This represents the comprehensive evaluation score of the optimal pipe diameter combination for a certain generation of the population. When the optimization process meets the above termination condition, the optimal pipe diameter combination for that iteration layer is output, which is the pipe diameter optimization design result.

[0129] The iterative process of using a genetic algorithm to find the optimal pipe diameter combination for a heating network is as follows: Figure 4 As shown, the algorithm converged successfully, yielding the optimal pipe diameter combination design scheme.

[0130] In the pipe diameter optimization design scheme based on traditional and improved economic evaluation index systems provided in this invention embodiment, the statistical comparison of the overall pipe diameter selection length is as follows: Figure 5 As shown in the figure. In the pipe diameter optimization design scheme based on the traditional economic evaluation index system, the pipe diameter and pressure drop of the most unfavorable branch and its various pipe sections are as follows. Figure 6A As shown; in the pipe diameter optimization design scheme based on the improved economic evaluation index system, the pipe diameter and pressure drop of the most unfavorable branch and its various pipe sections are as follows: Figure 6BAs shown. Due to the difference in weight values, the optimization design method provided in this embodiment of the invention tends to minimize annual operating costs while minimizing the increase in annual depreciated investment costs. Therefore, the overall pipe diameter distribution of the design scheme shows an increasing trend.

[0131] In this application, the entropy weight method is applied to calculate the weight of economic sub-indicators in pipe diameter optimization design. To obtain weight calculation results that do not change with the increase of sample size, a sample space of pipe diameter combinations is constructed, and several pipe diameter combination samples are selected. By repeatedly doubling the sample size, it is ensured that the sample size is sufficient and includes all characteristics of the pipe diameter combinations of the heating network, so that the calculated weight values ​​gradually tend to stabilize. The above weight calculation process allocates weights according to the role of economic sub-indicators in pipe diameter optimization design, taking into account the objective differences in their importance, effectively improving the problem of the lack of weighting of sub-indicators in traditional pipe diameter optimization design, and obtaining a more reasonable pipe diameter design scheme. In addition, pipe diameter optimization designers can adjust the composition of economic sub-indicators and constraints according to needs to solve pipe diameter optimization design problems with a wider range of network scales and more complex engineering design requirements.

[0132] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of this application.

Claims

1. A method for optimizing the pipe diameter of a heating pipe network based on an improved economic evaluation index system, characterized by: obtaining the topological structure of the heating pipe network, constructing a sample space of pipe diameter combinations of the heating pipe network according to constraint conditions, and selecting a plurality of pipe diameter combination samples from the sample space; obtaining the design and operation parameters of the heating pipe network, and calculating the economic sub-indexes of the pipe diameter combination samples; normalizing the economic sub-indexes; applying an entropy weight method to calculate the weight values of the economic sub-indexes in the pipe diameter optimization design based on the pipe diameter combination samples; determining whether the weight values are independent of the number of pipe diameter combination samples; if the weight values still depend on the number of pipe diameter combination samples, increasing the number of pipe diameter combination samples and recalculating the weight values until the weight values do not change with the increase in the number of pipe diameter combination samples; establishing an improved economic evaluation index system for the heating pipe network based on the weight values; finding the optimal pipe diameter combination design scheme of the heating pipe network using an optimization algorithm according to the improved economic evaluation index system; the setting strategy for the number of pipe diameter combination samples includes: initially selecting S pipe diameter combination samples from the sample space, and calculating the weight values of the economic sub-indexes; multiplying the number of pipe diameter combination samples by 2S, 4S, 8S, 16S, …, and repeatedly calculating the weight values of the economic sub-indexes until the weight values are independent of the number of pipe diameter combination samples; the judgment basis that the weight values have reached independence from the number of pipe diameter combination samples includes that the relative error of the weight values of two adjacent times satisfies the following formula: δ = |(ω j,k - ω j,k-1 ) / ω j,k-1 | < 10 -3 , k = 2, 3, 4,... where k represents the number of times the weight value is calculated repeatedly; ω j,k represents the weight value of the economic sub-index j calculated for the kth time; ω j,k-1 represents the weight value of the economic sub-index j calculated for the (k-1)th time.

2. The heat supply network pipe diameter optimization design method based on the improved economic evaluation index system according to claim 1, characterized in that, the constraint conditions include the range of pipe diameter specifications, the constraint of upstream and downstream pipe diameters, the flow rate of the heating medium, and the specific frictional resistance of the pipe section.

3. The heat supply network pipe diameter optimization design method based on the improved economic evaluation index system according to claim 1, characterized in that, The economic sub-indexes of the heating pipe network include the annual equivalent investment cost and the annual operation cost; for the pipe diameter combination i of the heating pipe network, the economic sub-index j is calculated and expressed as: x ij i = 1,2,...,m; j = 1,2.

4. The heat supply network pipe diameter optimization design method based on the improved economic evaluation index system according to claim 1, characterized in that, The normalization of the economic sub-indexes is performed using the range method, and the calculation formula is as follows: where max x j represents the maximum value of the economic sub-indicator j in all pipe diameter combination samples, min x j represents the minimum value of the economic sub-indicator j in all pipe diameter combination samples.

5. The heat supply network pipe diameter optimization design method based on the improved economic evaluation index system according to claim 4, characterized in that, The application of the entropy weight method to calculate the weight values of the economic sub-indexes in the pipe diameter optimization design based on the pipe diameter combination samples includes: calculating the contribution of the pipe diameter combination samples to each economic sub-index, and the calculation formula is as follows: calculating the information entropy of each economic sub-index, and the calculation formula is as follows: calculating the weight values of each economic sub-index, and the calculation formula is as follows: Wherein, P ij Contribution degree of pipe diameter combination sample i to economic sub-index j, e j Information entropy of economic sub-index j, ω j Weight value of economic sub-index j.

6. The heat supply network pipe diameter optimization design method based on the improved economic evaluation index system according to claim 1, characterized in that, The establishment of the improved economic evaluation index system for the heating pipe network based on the weight values includes calculating the comprehensive evaluation score of the pipe diameter combination of the heating pipe network by the following formula: In the formula, P ij represents the contribution degree of the pipe diameter combination sample i to the economic sub-index j, ω j represents the weight value of the economic sub-index j, value i represents the comprehensive evaluation score of the pipe diameter combination sample i.

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