Determination Method, Device, Readable Medium and Electronic Device for Steam Pipe Network Structure

Abstract

The present invention discloses a method, device, readable medium and electronic device for determining a steam pipe network structure. The method includes: constructing an optimization model of the steam pipe network according to road network data and user load data in the area to be provided with the steam pipe network; performing convex relaxation processing on the optimization model of the steam pipe network to obtain the processed optimization model of the steam pipe network; performing decomposition and coordination on the processed optimization model of the steam pipe network to determine the main problem of the optimization of the steam pipe network and the sub-problem of the optimization of the steam pipe network; and determining the steam pipe network structure corresponding to the solution of the optimization model of the steam pipe network according to the main problem of the optimization of the steam pipe network and the sub-problem of the optimization of the steam pipe network. The technical solution provided by the present invention sequentially performs convex relaxation processing and decomposition and coordination processing on the constructed optimization model of the steam pipe network to ensure that the determined steam pipe network structure is more reasonable, and the steam pipe network structure can reduce energy loss, improve energy utilization efficiency, and is beneficial to improving the energy efficiency and economic performance of the energy station.

Description

Technical Field

[0001] The present invention relates to the field of energy, and particularly to a method, device, readable medium and electronic device for determining the structure of a steam pipe network. Background Art

[0002] The steam pipe network is a key transmission channel for transporting the steam from the energy station to the steam users. The structure of the steam pipe network has an important impact on the energy efficiency and economic performance of the energy station.

[0003] Currently, the structure of the steam pipe network is mostly designed by designers, which makes the structure of the steam pipe network directly related to the experience and level of the designers. There may be a situation where the structure design of the steam pipe network is unreasonable. An unreasonably structured steam pipe network will have a large amount of energy loss during the pipe network transportation process, resulting in a low operating efficiency of the steam pipe network, seriously affecting the energy efficiency of the energy station. Therefore, determining a reasonable structure of the steam pipe network is of great significance for reducing the energy loss of the steam pipe network and improving the energy utilization efficiency. Summary of the Invention

[0004] The present invention provides a method, device, readable medium and electronic device for determining the structure of a steam pipe network. By considering the road network characteristics and user load characteristics, a steam pipe network optimization model is constructed, and further convex relaxation processing and decomposition and coordination processing are performed on the steam pipe network optimization model to determine the optimal solution of the relatively accurate steam pipe network optimization model, so that the structure of the steam pipe network determined according to the optimal solution is more reasonable, effectively reducing the energy loss of the steam pipe network and improving the energy utilization efficiency, which is beneficial to the improvement of the energy efficiency and economic performance of the energy station.

[0005] In a first aspect, the present invention provides a method for determining the structure of a steam pipe network, including:

[0006] Constructing a steam pipe network optimization model according to the road network data and user load data in the area to be designed of the steam pipe network;

[0007] Performing convex relaxation processing on the steam pipe network optimization model to obtain the processed steam pipe network optimization model;

[0008] Performing decomposition and coordination on the processed steam pipe network optimization model to determine the steam pipe network optimization main problem and the steam pipe network optimization sub-problem;

[0009] Determining the steam pipe network structure corresponding to the solution of the steam pipe network optimization model according to the steam pipe network optimization main problem and the steam pipe network optimization sub-problem.

[0010] Preferably,

[0011] The steam pipe network optimization model includes an objective function for minimizing the total planning cost;

[0012] The specific formula of the objective function is as follows:

[0013] minC = C v + C O ;

[0014] Wherein, C represents the total planning cost; C v represents the average annual pipe network investment cost; C O represents the pipe loss cost.

[0015] Preferably,

[0016] The specific formula of the average annual pipe network investment cost is as follows:

[0017]

[0018] Wherein, d ij represents the pipe diameter level of the connecting pipe ij between road network node i and road network node j, which is an integer variable, and 0 ≤ d ij ≤ MaxDia, where MaxDia is the maximum pipe diameter level; p represents the unit price of the pipe; L represents the pipe life; r represents the residual value rate; arcs represents the set of connectable pipes ij in the road network; D ij represents the length between pipes ij;

[0019] The specific formula of the pipe loss cost is as follows:

[0020]

[0021] Wherein, G ij represents the steam flow of pipe ij; λ represents the friction factor along the length; ρ represents the fluid density.

[0022] Preferably,

[0023] The steam pipe network optimization model further includes constraint conditions;

[0024] The constraint conditions include:

[0025] Pipe section connection and pipe diameter relationship constraints, and the specific formula is as follows:

[0026]

[0027] Wherein, x ij represents whether pipe ij is connected, which is an integer variable, 1 means connected, and 0 means not connected;

[0028] Energy station capacity constraints, and the specific formula is as follows:

[0029]

[0030] Among them, IES_cap_0 represents the maximum steam capacity of the energy station; I 0 represents the set of nodes connected to the energy station at node 0; G 0j represents the steam flow rate of pipeline 0j with the energy station node as the first segment;

[0031] Pipeline quantity constraint, the specific formula is as follows:

[0032]

[0033] Among them, MaxL represents the maximum number of pipelines at the energy station outlet;

[0034] Node pipeline inflow quantity constraint, the specific formula is as follows:

[0035]

[0036] Among them, N represents the set of all nodes, including the energy station node and the plot nodes; I j represents the set of nodes connected to node j;

[0037] Pipe segment flow rate constraint, the specific formula is as follows:

[0038]

[0039] Pipe segment pressure loss and flow rate, pipe diameter coupling constraint, the specific formula is as follows:

[0040]

[0041] Among them, P i represents the pressure at node i; P j represents the pressure at node j;

[0042] Plot node inflow pipeline quantity constraint, the specific formula is as follows:

[0043]

[0044] Among them, B k represents the set of nodes belonging to plot k; Block represents the set of plots;

[0045] Plot pressure constraint, the specific formula is as follows:

[0046]

[0047] Among them, Pk represents the lower limit of the pressure of plot k;

[0048] Plot flow rate balance constraint, the specific formula is as follows:

[0049]

[0050] Among them, G k,load represents the load of plot k;

[0051] The node pressure constraint, and the specific formula is as follows:

[0052]

[0053] The routing node flow balance constraint, and the specific formula is as follows:

[0054]

[0055] Among them, N net represents the set of routing nodes, excluding the energy station node and the plot node.

[0056] Preferably,

[0057] Performing convex relaxation processing on the steam pipe network optimization model to obtain the processed steam pipe network optimization model, including:

[0058] Equivalently relaxing the coupling constraint formula of pipe section pressure loss with flow rate and pipe diameter to:

[0059]

[0060] Taking ifx ij >0 for conversion to obtain the converted coupling constraint of pipe section pressure loss with flow rate and pipe diameter:

[0061] x ij ≤Big_M*v ij ;

[0062]

[0063] Among them, Big_M represents the introduced large number; v ij represents the introduced integer variable, v ij ∈{0,1};

[0064] According to the objective function, the pipe section connection and pipe diameter relationship constraint, the energy station capacity constraint, the pipeline quantity constraint, the node pipeline inflow quantity constraint, the pipe section flow constraint, the converted coupling constraint of pipe section pressure loss with flow rate and pipe diameter, the plot node inflow pipeline quantity constraint, the plot pressure constraint, the plot flow balance constraint, the node pressure constraint, and the routing node flow balance constraint, determine the processed steam pipe network optimization model.

[0065] Preferably,

[0066] The steam pipeline network optimization sub-problem includes:

[0067]

[0068]

[0069] Among them, represents the integer variable calculated by the steam pipeline network optimization main problem; s.t. represents the constraint condition.

[0070] Preferably,

[0071] The steam pipeline network optimization main problem includes:

[0072] minz;

[0073]

[0074] Among them, z represents the newly introduced variable to be solved as the objective of the steam pipeline network optimization main problem.

[0075] In a second aspect, the present invention provides a device for determining the structure of a steam pipeline network, including:

[0076] A model construction module, configured to construct a steam pipeline network optimization model according to the road network data and user load data in the area to be designed of the steam pipeline network;

[0077] A model processing module, which performs convex relaxation processing on the steam pipeline network optimization model to obtain the processed steam pipeline network optimization model;

[0078] A model decomposition module, configured to decompose and coordinate the processed steam pipeline network optimization model to determine the steam pipeline network optimization main problem and the steam pipeline network optimization sub-problem;

[0079] A structure determination module, configured to determine the steam pipeline network structure corresponding to the solution of the steam pipeline network optimization model according to the steam pipeline network optimization main problem and the steam pipeline network optimization sub-problem.

[0080] In a third aspect, the present invention provides a readable medium, including execution instructions. When the processor of an electronic device executes the execution instructions, the electronic device executes the method according to any one of the first aspects.

[0081] In a fourth aspect, the present invention provides an electronic device, including a processor and a memory storing execution instructions. When the processor executes the execution instructions stored in the memory, the processor executes the method according to any one of the first aspects.

[0082] The present invention provides a method, apparatus, readable medium, and electronic device for determining a steam pipe network structure. By determining the road network data and user load data within the area to be equipped with a steam pipe network, a steam pipe network optimization model is constructed. To ensure obtaining the optimal solution of the steam pipe network optimization model, convex relaxation processing is performed on the steam pipe network optimization model to obtain the processed steam pipe network optimization model. Further, decomposition and coordination are performed on the processed steam pipe network optimization model to determine the main steam pipe network optimization problem and the sub-steam pipe network optimization problem. Then, based on the main steam pipe network optimization problem and the sub-steam pipe network optimization problem, the optimal solution of the steam pipe network optimization model is determined, and the corresponding steam pipe network structure is determined according to the optimal solution. The method for determining the steam pipe network structure provided by the present invention considers the characteristics of the road network and user loads, and through convex relaxation processing and decomposition and coordination processing of the constructed steam pipe network optimization model, ensures the accuracy of the determined optimal solution of the steam pipe network optimization model, thereby making the steam pipe network structure corresponding to the optimal solution more reasonable, effectively reducing the energy loss of the steam pipe network, improving the energy utilization efficiency, and being beneficial to the improvement of the energy efficiency and economic performance of the energy station. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0084] Figure 1 It is a flowchart of a method for determining a steam pipe network structure provided in an embodiment of the present invention;

[0085] Figure 2 It is a schematic structural diagram of an apparatus for determining a steam pipe network structure provided in an embodiment of the present invention;

[0086] Figure 3 It is a schematic structural diagram of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0087] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions of the present invention in conjunction with specific embodiments and the corresponding drawings. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0088] As Figure 1As shown in the figure, an embodiment of the present invention provides a method for determining a steam pipe network structure, the method comprising:

[0089] Step 101, constructing an optimization model of the steam pipe network according to road network data and user load data in the area to be provided with the steam pipe network;

[0090] Step 102, performing convex relaxation processing on the optimization model of the steam pipe network to obtain the processed optimization model of the steam pipe network;

[0091] Step 103, performing decomposition and coordination on the processed optimization model of the steam pipe network to determine the main problem of the optimization of the steam pipe network and the sub-problem of the optimization of the steam pipe network;

[0092] Step 104, determining the steam pipe network structure corresponding to the solution of the optimization model of the steam pipe network according to the main problem of the optimization of the steam pipe network and the sub-problem of the optimization of the steam pipe network.

[0093] As Figure 1 shown in the embodiment, by determining the road network data and user load data in the area to be provided with the steam pipe network, an optimization model of the steam pipe network is constructed. In order to ensure that the optimal solution of the optimization model of the steam pipe network can be obtained, convex relaxation processing is performed on the optimization model of the steam pipe network to obtain the processed optimization model of the steam pipe network. Further, decomposition and coordination are performed on the processed optimization model of the steam pipe network to determine the main problem of the optimization of the steam pipe network and the sub-problem of the optimization of the steam pipe network. Then, according to the main problem of the optimization of the steam pipe network and the sub-problem of the optimization of the steam pipe network, the optimal solution of the optimization model of the steam pipe network is determined, and the corresponding steam pipe network structure is determined according to the optimal solution. The method for determining the steam pipe network structure provided by the present invention takes into account the road network characteristics and user load characteristics, and through convex relaxation processing and decomposition and coordination processing on the constructed optimization model of the steam pipe network, ensures the accuracy of the optimal solution of the determined optimization model of the steam pipe network, so that the steam pipe network structure corresponding to the optimal solution is more reasonable, effectively reduces the energy loss of the steam pipe network, improves the energy utilization efficiency, and is beneficial to the improvement of the energy efficiency and economic performance of the energy station.

[0094] Specifically, the road network data may include the coordinates of energy stations, the coordinates of road network nodes, and the coordinates of the center points of plots, that is, the road network data can reflect the road network characteristics of the area where the steam pipeline network is to be set and the distribution characteristics of functional plots; the user load data includes user steam parameters, flow data, and pressure data, that is, the user load data can reflect the load characteristics of users, so that the steam pipeline network optimization model constructed based on the road network data and the user load data can better reflect the situation of the area where the steam pipeline network is to be set. Therefore, the steam pipeline network structure determined according to the steam pipeline network optimization model is more reasonable. It should be noted that the area where the steam pipeline network is to be set mentioned in this embodiment may be an area where no steam pipeline network has been laid, or an area where part of the steam pipeline network has been laid. Of course, it may also be an area where the steam pipeline network has been laid and the laid steam pipeline network needs to be optimized. This embodiment does not make any limitations in this regard.

[0095] In an embodiment of the present invention, the steam pipeline network optimization model includes an objective function for minimizing the total planning cost; the specific formula of the objective function is shown in the following formula (1):

[0096] minC = C v + C O ; (1)

[0097] Wherein, C represents the total planning cost; C v represents the annual average pipeline network investment cost; C O represents the pipeline loss cost.

[0098] In the above embodiment, the objective function is obtained by comprehensively considering the annual average pipeline network investment cost and the pipeline loss cost. Taking the minimum value of the sum of the annual average pipeline network investment cost and the pipeline loss cost as the objective function, the steam pipeline network structure determined by using this objective function can effectively improve the economy of the energy station.

[0099] Specifically, the formula of the annual average pipeline network investment cost is shown in the following formula (2):

[0100]

[0101] Wherein, d ij represents the pipe diameter level of the connecting pipeline ij between road network node i and road network node j, which is an integer variable, and 0 ≤ d ij ≤ MaxDia, MaxDia is the maximum pipe diameter level; p represents the unit price of the pipeline; L represents the pipeline life; r represents the residual value rate; arcs represents the set of connectable pipelines ij in the road network; D ij represents the length between pipelines ij;

[0102] The formula of the pipeline loss cost is shown in the following formula (3):

[0103]

[0104] Among them, G ij represents the steam flow rate of pipeline ij; λ represents the friction factor along the path; ρ represents the fluid density.

[0105] In Equation (2), the pipeline loss cost can be regarded as the pressure loss cost, which is mainly related to the pipe diameter and flow velocity, etc. It can be seen from Equations (1), (2) and (3) that the objective function is a function of the connection path level and steam flow rate of the steam pipe network. By solving this objective function, the steam pipe network structure with the minimum total planning cost can be determined.

[0106] In an embodiment of the present invention, the steam pipe network optimization model further includes constraint conditions;

[0107] The constraint conditions include:

[0108] Pipe section connection and pipe diameter relationship constraint, as shown in Equation (4) below:

[0109]

[0110] Among them, x ij represents whether pipeline ij is connected, which is an integer variable, 1 means connected, and 0 means not connected;

[0111] Equation (4) means that even if nodes i and j are connected, the pipe diameter level of pipeline ij should be less than the maximum pipe diameter level. In Equation (4), because 0 ≤ d ij ≤ MaxDia, so when nodes i and j are connected, x ij = 1, that is, MaxDia >> d ij ; when nodes i and j are not connected, at this time x ij = 0, because nodes i and j are not connected, there is no pipe diameter level of the connected pipeline ij, that is, d ij is 0 at this time. Therefore, there are constraint conditions for pipe section connection and pipe diameter as shown in Equation (4).

[0112] Energy station capacity constraint, as shown in Equation (5) below:

[0113]

[0114] Among them, IES_cap_0 represents the maximum steam capacity of the energy station; I 0 represents the set of nodes connected to the energy station of node 0; G 0j represents the steam flow rate of pipeline 0j with the energy station node as the first section;

[0115] Equation (5) indicates that the steam flow rate flowing out of Node 0 through pipeline 0j is less than the maximum steam capacity of the energy station at Node 0. Since the steam pipe network transports the steam from the energy station to users, the total steam flow rate flowing out of the energy station must be less than or equal to the maximum steam capacity, thus there is the constraint condition shown in Equation (5).

[0116] The pipeline quantity constraint is shown in the following Equation (6):

[0117]

[0118] where MaxL represents the maximum number of pipelines at the outlet of the energy station;

[0119] Equation (6) indicates that the number of pipelines connected to the energy station is less than or equal to the maximum number of pipelines at the outlet of the energy station. The energy station is Node 0, and I 0 represents the set of nodes connected to Node 0. However, there is a maximum limit on the number of pipelines at the outlet of the energy station. Therefore, the number of pipelines connected to Node 0 must be within this maximum limit range, thus there is the constraint condition shown in Equation (6).

[0120] The node pipeline inflow quantity constraint is shown in the following Equation (7):

[0121]

[0122] where N represents the set of all nodes, including the energy station node and the plot nodes; I j represents the set of nodes connected to Node j;

[0123] Equation (7) indicates that for Node j, it can be connected to Node i or not. However, if it is connected, there is only one Node i that can be connected to Node j.

[0124] The pipeline segment flow rate constraint is shown in the following Equation (8):

[0125]

[0126] Equation (8) is used to limit the variable range and can accelerate the solution speed of the steam pipe network optimization model.

[0127] The pipeline segment pressure loss and flow rate, pipe diameter coupling constraint is shown in the following Equation (9):

[0128]

[0129] where P i represents the pressure at Node i; P j represents the pressure at Node j;

[0130] As shown in Equation (9), when nodes i and j are connected, it represents the relationship between the pressure loss of pipeline ij and the flow velocity and pipe diameter.

[0131] The constraint on the number of pipelines flowing into the plot nodes is as shown in Equation (10) below:

[0132]

[0133] where B k represents the set of nodes belonging to plot k; Block represents the set of plots;

[0134] Equation (10) means that for all nodes j in plot k, considering the nodes i connected to node j at the same time, the cumulative connection between the two is less than or equal to 1, so as to achieve the purpose that there is at most one input pipeline connecting plot k.

[0135] The plot pressure constraint is as shown in Equation (11) below:

[0136]

[0137] where P k represents the lower limit of the pressure of plot k;

[0138] Equation (11) means that when node i belongs to plot k, the pressure corresponding to node i should be greater than or equal to the lower limit of the pressure of plot k.

[0139] The plot flow balance constraint is as shown in Equation (12) below:

[0140]

[0141] where G k,load represents the load of plot k;

[0142] Equation (12) means that the difference between the total steam flow into plot k and the total steam flow out of plot k is not less than the load of plot k.

[0143] The node pressure constraint is as shown in Equation (13) below:

[0144]

[0145] Equation (13) means that when there is a connection between node i and node j, the pressure of node j should be less than or equal to 1000, that is, when x ij = 1, P j ≤1000, when x ij = 0, P j = 0.

[0146] The routing node flow balance constraint is as shown in Equation (14) below:

[0147]

[0148] Among them, N net represents the set of routing nodes, excluding the energy station nodes and plot nodes.

[0149] Equation (14) indicates that the total steam flow rate flowing into the routing node is equal to the total steam flow rate flowing out of the routing node, where the routing node refers to the node that transports steam from the energy station node to the plot node.

[0150] The steam pipe network optimization model is composed of Equations (1)-(14). This steam pipe network optimization model fully considers various possible constraint conditions to ensure the rationality and accuracy of the optimal solution of the finally obtained steam pipe network optimization model, and is more in line with the actual situation in the area where the steam pipe network is to be set up.

[0151] In Equations (1)-(14), due to the existence of Equation (9), the obtained steam pipe network optimization model is non-convex, and this steam pipe network optimization model is a mixed-integer non-linear programming problem. Therefore, in order to obtain the optimal solution of this steam pipe network optimization model, convex relaxation processing needs to be performed on the steam pipe network optimization model. In an embodiment of the present invention, the convex relaxation processing of the steam pipe network optimization model to obtain the processed steam pipe network optimization model includes: equivalently relaxing the coupling constraint formula of the pipe section pressure loss with the flow rate and pipe diameter to:

[0152]

[0153] Convert Equation (15) to obtain the converted coupling constraint of the pipe section pressure loss with the flow rate and pipe diameter:

[0154]

[0155] Among them, Big_M represents the introduced larger number; v ij represents the introduced integer variable, v ij ∈{0,1};

[0156] According to the objective function, the pipe section connection and pipe diameter relationship constraints, the energy station capacity constraints, the pipeline quantity constraints, the node pipeline inflow quantity constraints, the pipe section flow rate constraints, the converted coupling constraint of the pipe section pressure loss with the flow rate and pipe diameter, the plot node inflow pipeline quantity constraints, the plot pressure constraints, the plot flow rate balance constraints, the node pressure constraints, and the routing node flow rate balance constraints, determine the processed steam pipe network optimization model.

[0157] In the above embodiment, because x ijSince it is a 0, 1 variable, Equation (9) can be equivalently relaxed to Equation (15), and the constraint conditions are reconstructed using the Big-M method to obtain the transformed pipe section pressure loss and flow rate, pipe diameter coupling constraint shown in Equation (16). The processed steam pipe network optimization model is composed of Equations (1)-(8), (10)-(14), and (16), and there is an optimal solution for the processed steam pipe network optimization model.

[0158] In an embodiment of the present invention, the optimal solution of the steam pipe network optimization model is determined by generalized Benders decomposition. The steam pipe network optimization model is decomposed into a steam pipe network optimization master problem and a steam pipe network optimization subproblem using the generalized Benders decomposition principle. Specifically,

[0159] The steam pipe network optimization subproblem includes:

[0160]

[0161]

[0162] Among them, represents the integer variable calculated by the steam pipe network optimization master problem; s.t. represents the constraint condition. That is, in the steam pipe network optimization subproblem is no longer a variable, but the value calculated by the steam pipe network optimization master problem in the previous iteration process.

[0163] The steam pipe network optimization master problem includes:

[0164] minz;

[0165]

[0166] Among them, z represents the newly introduced variable to be solved as the objective of the steam pipe network optimization master problem.

[0167] In the above embodiment, the steam pipe network optimization model is decomposed into a steam pipe network optimization master problem and a steam pipe network optimization subproblem, and the steam pipe network optimization master problem and the steam pipe network optimization subproblem are alternately iteratively solved to achieve the purpose of solving the steam pipe network optimization model.

[0168] In a possible implementation manner, after determining the steam pipe network optimization master problem and the steam pipe network optimization subproblem, the following steps are used to solve the steam pipe network optimization model:

[0169] Step 1, initialization.

[0170] Input various parameters, set the upper bound LB and the lower bound UB, initially set the iteration number t = 1 and the algorithm maximum error tolerance ε, and at x ij and d ijGiven an initial value in the feasible region.

[0171] Step 2, Solve the steam pipeline network sub-problem

[0172] If there is a feasible solution, i.e., m can be obtained t (m corresponds to G in this embodiment ij and P i ) and the dual variable λ t (Lagrange multiplier), then construct a feasible cut and feed it back to the master problem:

[0173]

[0174] where L() represents the Lagrangian function, and y corresponds to x in this embodiment ij and d ij , then represents the integer variable solution obtained from the steam pipeline network optimization master problem corresponding to in this embodiment;

[0175] If there is no feasible solution, then introduce a slack variable to construct a slack sub-problem:

[0176] mins t

[0177]

[0178] where s t represents the introduced slack variable, and g() represents the function on the left side of the inequality constraint;

[0179] According to m calculated from the slack sub-problem t and the dual variable λ t construct an infeasible cut and feed it back to the steam pipeline network optimization master problem:

[0180]

[0181] Step 3, Convergence check.

[0182] Use the optimal value of the steam pipeline network optimization sub-problem to update the upper bound LB, and check whether the difference between the updated upper bound LB and the lower bound UB is greater than the set error tolerance ε. If so, continue with Step 4; otherwise, terminate the operation and output the current solution as the optimal solution.

[0183] Step 4, Solve the steam pipeline network master problem

[0184] Add the feasible cut or infeasible cut returned by the steam pipeline network optimization sub-problem to the steam pipeline network optimization master problem for recalculation, and calculate the new x ij and d ijvalues, update the lower bound UB according to the z value optimized by the main steam pipe network, let t = t + 1, return to step 2 to recalculate, that is, enter the next iteration, until the convergence determination condition in step 3 is satisfied, then the algorithm terminates, determine the optimal solution, and determine the connection mode, pipe diameter level, steam flow rate and pressure of the road network nodes according to the optimal solution, so as to determine the steam pipe network structure. The determined steam pipe network structure is reasonable, which can effectively reduce the energy loss of the steam pipe network and improve the energy utilization efficiency.

[0185] Based on the same inventive concept as the above method, as Figure 2 shown, an embodiment of the present invention provides a device for determining a steam pipe network structure, including:

[0186] A model construction module 201, configured to construct an optimization model of the steam pipe network according to the road network data and user load data in the area to be set up of the steam pipe network;

[0187] A model processing module 202, which performs convex relaxation processing on the optimization model of the steam pipe network to obtain the processed optimization model of the steam pipe network;

[0188] A model decomposition module 203, configured to decompose and coordinate the processed optimization model of the steam pipe network to determine the main problem of the steam pipe network optimization and the sub-problem of the steam pipe network optimization;

[0189] A structure determination module 204, configured to determine the steam pipe network structure corresponding to the solution of the optimization model of the steam pipe network according to the main problem of the steam pipe network optimization and the sub-problem of the steam pipe network optimization.

[0190] Figure 3It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. At the hardware level, the electronic device includes a processor 301 and a memory 302 storing execution instructions. Optionally, it further includes an internal bus 303 and a network interface 304. Among them, the memory 302 may include a memory 3021, such as a high-speed random access memory (Random-Access Memory, RAM), and may also include a non-volatile memory 3022 (non-volatile memory), such as at least one disk memory, etc.; the processor 301, the network interface 304, and the memory 302 can be interconnected through the internal bus 303, and the internal bus 303 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc.; the internal bus 303 can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 3 only a bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus. Of course, the electronic device may also include other hardware required for other services. When the processor 301 executes the execution instructions stored in the memory 302, the processor 301 executes the method in any one of the embodiments of the present invention and is at least used to execute as Figure 1 the method shown.

[0191] In a possible implementation manner, the processor reads the corresponding execution instructions from the non-volatile memory into the memory and then runs, or can also obtain the corresponding execution instructions from other devices to form a determining device for a steam pipe network structure at the logical level. The processor executes the execution instructions stored in the memory to implement a method for determining a steam pipe network structure provided in any one of the embodiments of the present invention through the executed execution instructions.

[0192] A processor may be an integrated circuit chip with the ability to process signals. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in the processor or the instructions in the form of software. The above-mentioned processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0193] The embodiments of the present invention also provide a computer-readable storage medium, including execution instructions. When the processor of the electronic device executes the execution instructions, the processor executes the method provided in any one of the embodiments of the present invention. The electronic device may specifically be the electronic device as Figure 3 shown; the execution instructions are the computer program corresponding to a determining device for a steam pipe network structure.

[0194] Those skilled in the art should understand that the embodiments of the present invention may be provided as a method or a computer program product. Therefore, the present invention may be implemented in the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware.

[0195] The various embodiments of the present invention are described in a progressive manner. The same or similar parts among the various embodiments may be referred to each other, and the differences between each embodiment and other embodiments are emphasized. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts may refer to the partial description of the method embodiments.

[0196] It should also be noted that the term "including", "comprising", or any other variant thereof is intended to cover a non-exclusive inclusion, such that a process, method, commodity, or boiler including a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, commodity, or boiler. Without further limitations, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, commodity, or boiler including the said element.

[0197] The above are only embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims

1. A method for determining the structure of a steam pipe network, characterized in that, comprising: Constructing an optimization model of the steam pipe network according to the road network data and user load data in the area to be set up of the steam pipe network; Performing convex relaxation processing on the optimization model of the steam pipe network to obtain the processed optimization model of the steam pipe network; Performing decomposition and coordination on the processed optimization model of the steam pipe network to determine the main problem of the steam pipe network optimization and the sub-problem of the steam pipe network optimization; Determining the steam pipe network structure corresponding to the solution of the optimization model of the steam pipe network according to the main problem of the steam pipe network optimization and the sub-problem of the steam pipe network optimization; The optimization model of the steam pipe network includes an objective function for minimizing the total planning cost; The specific formula of the objective function is as follows: minC = C v + C O ; Among them, C represents the total planning cost; C v represents the average annual pipe network investment cost; C O represents the pipe loss cost; The specific formula of the annual average pipe network investment cost is as follows: Among them, d ij represents the pipe diameter level of the connecting pipe ij between road network node i and road network node j, which is an integer variable, and 0 ≤ d ij ≤ MaxDia, where MaxDia is the maximum pipe diameter level; p represents the unit price of the pipe; L represents the pipe life; r represents the salvage value rate; arcs represents the set of connectable pipes ij in the road network; D ij represents the length between pipes ij; The specific formula of the pipe loss cost is as follows: Among them, G ij represents the steam flow rate of pipeline ij; λ represents the friction factor along the path; ρ represents the fluid density; The optimization model of the steam pipe network further includes constraint conditions; The constraint conditions include: Pipe section connection and pipe diameter relationship constraints, and the specific formula is as follows: where x ij represents whether pipeline ij is connected, which is an integer variable. 1 means connected and 0 means not connected; Energy station capacity constraints, and the specific formula is as follows: Among them, IES_cap_0 represents the maximum steam capacity of the energy station; I 0 represents the set of nodes connected to the energy station at node 0; G 0j represents the steam flow rate of pipeline 0j with the energy station node as the first segment; Pipe quantity constraints, and the specific formula is as follows: Wherein, MaxL represents the maximum number of pipes at the outlet of the energy station; Node pipe inflow quantity constraints, and the specific formula is as follows: Among them, N represents the set of all nodes, including the energy station nodes and the plot nodes; I j represents the set of nodes connected to node j; Pipe section flow constraints, and the specific formula is as follows: Coupling constraints between pipe section pressure loss and flow rate and pipe diameter, and the specific formula is as follows: where, P i represents the pressure of node i; P j represents the pressure of node j; Inflow pipe quantity constraints for plot nodes, and the specific formula is as follows: Among them, B k represents the set of nodes belonging to plot k; Block represents the set of plots; Plot pressure constraints, and the specific formula is as follows: Among them, P k represents the lower limit of the pressure of plot k; Plot flow balance constraints, and the specific formula is as follows: Among them, G k,load represents the load of plot k; Node pressure constraints, and the specific formula is as follows: Routing node flow balance constraints, and the specific formula is as follows: Among them, N net represents the set of routing nodes, excluding the energy station node and the plot node.

2. The method for determining the structure of a steam pipe network according to claim 1, characterized in that, The performing convex relaxation processing on the optimization model of the steam pipe network to obtain the processed optimization model of the steam pipe network includes: Equivalently relaxing the coupling constraint formula between pipe section pressure loss and flow rate and pipe diameter to: Convert Use the Big-M method to transform and reconstruct the constraint conditions, and obtain the coupled constraints of the pressure loss, flow rate, and pipe diameter after transformation: x ij ≤ Big_M * v ij ; Among them, Big_M represents the introduced larger number; v ij represents the introduced integer variable, v ij ∈ {0, 1}; Determining the processed optimization model of the steam pipe network according to the objective function, the pipe section connection and pipe diameter relationship constraints, the energy station capacity constraints, the pipe quantity constraints, the node pipe inflow quantity constraints, the pipe section flow constraints, the converted coupling constraints between pipe section pressure loss and flow rate and pipe diameter, the inflow pipe quantity constraints for plot nodes, the plot pressure constraints, the plot flow balance constraints, the node pressure constraints, and the routing node flow balance constraints.

3. The method for determining the structure of a steam pipe network according to claim 2, characterized in that, The sub-problem of the steam pipe network optimization includes: Among them, represents the integer variables obtained from the calculation of the main problem of steam pipe network optimization; s.t. represents the constraint conditions.

4. The method for determining the structure of a steam pipe network according to claim 3, characterized in that, The main problem of the steam pipe network optimization includes: minz; Wherein, z represents the newly introduced variable to be solved as the objective of the main problem of the steam pipe network optimization.

5. A device for determining the structure of a steam pipe network, which is used to execute the method according to any one of claims 1-4, characterized in that, comprising: A model construction module, which is used to construct an optimization model of the steam pipe network according to the road network data and user load data in the area to be set up of the steam pipe network; A model processing module that performs convex relaxation processing on the steam pipe network optimization model to obtain the processed steam pipe network optimization model; A model decomposition module for decomposing and coordinating the processed steam pipe network optimization model to determine the steam pipe network optimization main problem and the steam pipe network optimization sub-problem; A structure determination module for determining the steam pipe network structure corresponding to the solution of the steam pipe network optimization model according to the steam pipe network optimization main problem and the steam pipe network optimization sub-problem.

6. A readable medium comprising execution instructions, wherein when a processor of an electronic device executes the execution instructions, the electronic device executes the method according to any one of claims 1 to 4.

7. An electronic device comprising a processor and a memory storing execution instructions, wherein when the processor executes the execution instructions stored in the memory, the processor executes the method according to any one of claims 1 to 4.

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