A coupled modeling method for energy flow and material flow considering uncertainty

Abstract

The present invention discloses a modeling and coupling method for energy flow and material flow that takes uncertainty into account. The method comprises: correlating distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line loads and material storage warehouses to obtain an energy-material flow coupling correlation diagram system; constructing an energy-material flow coupling model; inputting preset amounts of energy and material parameters of each distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line loads and material storage warehouses and outputting adjustment amounts to achieve coupling of energy flow and material flow that takes uncertainty into account. The method of the present invention unifies the different modeling methods of distributed new energy power generation equipment, energy conversion equipment and industrial production line loads in industrial production, and can be applied to multiple fields such as industrial production scheduling, equipment investment and construction, and thus assist in the refined scheduling of industrial production, production data correction, energy saving and efficiency improvement, etc.

Description

Technical Field

[0001] The present invention relates to a modeling coupling method, in particular to an energy flow and material flow modeling coupling method considering uncertainty. Background Art

[0002] As an important load in the integrated energy system, industrial loads consume a lot of energy and have many types of energy consumption. They are the key objects that the integrated energy system should focus on to improve its flexibility and resilience. At the same time, there are different types of production lines in industrial production, different production lines produce different materials, and there is a coupling relationship between production lines. In addition, industrial loads and distributed new energy installed in industrial parks have uncertainties, and these uncertainties will affect the energy balance and energy demand of industrial loads. In order to further refine the operating status of industrial loads and improve the flexibility and resilience of the overall integrated energy system, it is necessary to fine-tune the energy consumption of industrial loads. To this end, the patent of this invention proposes a method for coupling modeling of energy flow and material flow considering uncertainty. Summary of the Invention

[0003] The present invention proposes a coupled modeling method for energy flow and material flow that takes uncertainty into account. This method can obtain a refined relationship between the energy consumed, the materials consumed, and the materials produced in the industrial production process, and can incorporate various uncertainties in the industrial production process and distributed renewable energy power generation into the above relationship, which can be well applied.

[0004] The technical solution adopted in the present invention is:

[0005] The coupling method of the present invention comprises the following steps:

[0006] 1) Using graph theory, several distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line loads and material storage warehouses are associated to obtain an energy-material flow coupling association graph system.

[0007] 2) Construct an energy-material flow coupling model of the energy-material flow coupling association diagram system.

[0008] 3) The preset amounts of energy and material parameters of each distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line load and material storage warehouse are input into the energy-material flow coupling model. The energy-material flow coupling model outputs the adjustment amounts of the energy and material parameters of each distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line load and material storage warehouse and directly uses them as energy and material parameters, thereby realizing the coupling of energy flow and material flow considering uncertainty.

[0009] The uncertainties mentioned specifically include uncertainties in the industrial production process and uncertainties in distributed renewable energy power generation. Uncertainties in the industrial production process refer to uncertainties such as changes in production inventory caused by equipment failures, temporary arrival or cancellation of orders, unit production fluctuations, and production changes caused by equipment parameter changes. These uncertainties will affect the energy flow and material flow balance of the system. In order to characterize these uncertainties, random variables can be used to represent them in the subsequent modeling process. The distribution of random variables can be an empirical distribution obtained based on historical data, or a commonly used probability distribution model such as a normal distribution or a Poisson distribution. The uncertainty of distributed renewable energy power generation refers to the inability to accurately obtain the power generation of distributed renewable energy through prediction. The power generation of distributed renewable energy will also affect the energy flow and material flow balance of the system. In order to characterize this impact, the power generation of distributed renewable energy can be represented by random variables. The distribution of random variables can be a probability distribution obtained based on various existing prediction models, or a normal distribution can be used.

[0010] In the step 1), the distributed new energy power generation equipment is a device that converts new energy into electrical energy, specifically a distributed photovoltaic power generation device or a wind power generation device, but not limited thereto; the distributed new energy power generation equipment transmits electrical energy to the bus; the multi-energy conversion equipment is a device that converts natural gas chemical energy into thermal energy, natural gas chemical energy into thermal energy and electrical energy, or electrical energy into thermal energy, but not limited thereto, specifically a gas boiler, a cogeneration unit or an electric boiler, etc.; the energy storage device is a device that stores natural gas chemical energy or electrical energy, but not limited thereto, specifically a gas storage device or an energy storage battery; the industrial production line load includes the intermediate production line load and the final production line load, and the intermediate production line load is a device that consumes externally directly transmitted electrical energy, multi-energy The electric energy and thermal energy delivered after conversion by the conversion equipment, or the simultaneous consumption of the electric energy directly delivered from the outside and the thermal energy delivered after conversion by the multi-energy conversion equipment, thereby converting the materials to be processed into the assembly line load of the processed materials, but not limited to this; the material storage warehouse is a warehouse for storing the processed materials obtained by the conversion of the industrial production assembly line load; the final production assembly line load is the production line load that simultaneously consumes the electric energy directly delivered from the outside and the electric energy delivered after conversion by the multi-energy conversion equipment, thereby converting the processed materials in all material storage warehouses into the final materials; the distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production assembly line load and material storage warehouse are associated using graph theory to directly construct an energy-material flow coupling association graph system.

[0011] The energy-material flow coupling association diagram system includes E distributed new energy power generation equipment, F multi-energy conversion equipment, G industrial production line loads, U energy storage equipment, V material storage warehouses, P nodes, K branches, Q ports, Z buses, U+V virtual lines and U+V virtual interfaces, where P=E+F+G+U+V. Each node represents a distributed renewable energy power generation device, a multi-energy conversion device, an energy storage device, an industrial production line load or a material storage warehouse; each branch represents the material flow or the same energy flow input to each node, or represents the material flow or the same energy flow output from each node. The types of energy flow include thermal energy flow, electric current and natural gas flow, etc.; each port represents the input endpoint of the material flow or the same energy flow input to each node, or represents the output port of the material flow or the same energy flow output from each node; each bus represents the physical network carrier through which the same energy flow flows. The type of energy flow is equal to the number of buses. The physical network carrier is specifically the regional distribution network through which the current flows and the regional thermal network through which the thermal energy flow flows. The regional natural gas network through which natural gas chemical energy flows. Each node representing an energy storage device or material storage warehouse is constructed with a virtual circuit and a virtual interface. For each energy storage device's virtual circuit and virtual interface, the virtual circuit represents the energy increment of the energy storage device per unit time, that is, the increment of the energy storage device's charge and discharge energy per unit time. The virtual interface represents the virtual location connecting the energy storage device and the virtual circuit. For each material storage warehouse's virtual circuit and virtual interface, the virtual circuit represents the material increment of the material storage warehouse per unit time, that is, the increment of material stored and transported per unit time. The virtual interface represents the virtual location connecting the material storage warehouse and the virtual circuit. To ensure energy-material flow balance at the node, virtual circuits and virtual interfaces are constructed as virtual physical carriers.

[0012] In step 2), the energy-material flow coupling model constructed is as follows:

[0013]

[0014] Where H represents the energy flow-material flow balance matrix, W represents the combination of the branch set matrix of energy-material flow with and without uncertainty, B represents the branch set matrix without uncertainty, and B min and B max Denote the minimum and maximum set matrices of the branch set matrix without uncertainty, B min ≤B≤B max Represents the branch set matrix operation constraints.

[0015] The combination W of the branch set matrix of energy-material flow with and without uncertainty is as follows:

[0016] W=[Α T ,B T ] T

[0017] Where A represents the branch set matrix of energy-material flow containing uncertainty.

[0018] The predicted values ​​of each element in the branch set matrix A of the energy-material flow containing uncertainty are the energy and material parameters of each distributed new energy power generation equipment and each industrial production line load in step 3); the predicted values ​​of each element in the branch set matrix B that does not contain uncertainty are the energy and material parameters of each multi-energy conversion equipment, energy storage equipment and material storage warehouse in step 3.

[0019] The branch set matrix A of the energy-material flow containing uncertainty is as follows:

[0020]

[0021] Among them, the nodes where E distributed new energy power generation equipment are located in the energy-material flow coupling association graph system constitute a distributed new energy power generation node set, and the distributed new energy power generation node set includes E distributed new energy power generation nodes. The nodes where G industrial production line loads are located constitute an industrial production line load node set, and the industrial production line load node set includes G industrial production line load nodes. A1 represents the branch set matrix of the branches connected by the distributed new energy power generation node set, and A2 represents the branch set matrix of the branches connected by the industrial production line load node set.

[0022] The branch set matrix A1 of the branches connected by the distributed new energy generation node set is as follows:

[0023] A1=[R1,R2,…,R E ] T

[0024] Among them, R1, R2, …, R E They respectively represent the energy flow of the branches connected to the 1st, 2nd...Eth distributed renewable energy generation nodes in the distributed renewable energy generation node set, that is, the power generation of distributed renewable energy generation equipment; due to the uncertainty of distributed renewable energy generation, these quantities are random variables.

[0025] The branch set matrix A2 of the branches connected to the industrial production line load node set is as follows:

[0026] A2=[M 11,M 12 ,…,M 1D ,M 21 ,M 22 ,…M 2D ,…,M G1 ,M G2 ,…M GD ] T

[0027] Among them, the P nodes in the energy-material flow coupling association graph system, except for the nodes where the G industrial production line loads are located, and the Z buses constitute an industrial connection element set. There are P-G+Z industrial connection elements in the industrial connection element set. D represents the number of industrial connection elements in the industrial connection element set, D=P-G+Z; M 11 ,M 12 ,…,M 1D ,M 21 ,M 22 ,…M 2D ,…,M G1 ,M G2 ,…M GD They respectively represent the size of the energy flow or material flow flowing through the branches connecting the 1st, 2nd, ..., G industrial production line load nodes in the industrial production line load node set and the 1st, 2nd, ..., D industrial connection elements in the industrial connection element set.

[0028] The energy-material flow of the branch constructed above includes uncertainty, but it is correlated with the energy-material flow on the branch connected to the same industrial production line load node. Therefore, for a certain industrial production line load, one branch is selected from all the branches connected to it as a random variable, and the other variables are decision variables. The output material flow of an industrial production line load is often selected as the branch of the random variable.

[0029] The branch set matrix B without uncertainty is as follows:

[0030]

[0031] Among them, the nodes where the F multi-energy conversion devices in the energy-material flow coupling association diagram system are located constitute a multi-energy conversion device node set, and the multi-energy conversion device node set includes F multi-energy conversion device nodes. The nodes where the U energy storage devices are located constitute an energy storage device node set, and the energy storage device node set includes U energy storage device nodes. The Z buses constitute a bus set, B1 represents a virtual line set matrix, and B2 represents a branch set matrix of branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set.

[0032] The virtual circuit set matrix B1 is as follows:

[0033] B1=[ΔS1,ΔS2,…,ΔS Y ] T

[0034] Among them, the Y virtual lines in the energy-material flow coupling association diagram system constitute a virtual line set, ΔS1, ΔS2,…, ΔS Y It represents the energy increment of the energy storage device connected to the 1st, 2nd, ...Yth virtual lines in the virtual line set per unit time, or the material increment of the material storage warehouse connected to the virtual line, Y = U + V. These quantities are all decision variables.

[0035] The branch set matrix B2 of the branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set is as follows:

[0036]

[0037] in, They represent the energy flow of the branches connecting the 1st, 2nd, ..., Fth multi-energy conversion device nodes in the multi-energy conversion device node set and the 1st, 2nd, ..., Uth energy storage device nodes in the energy storage device node set, respectively. They represent the energy flow of the branches connecting the 1st, 2nd, ..., Fth multi-energy conversion device nodes in the multi-energy conversion device node set and the 1st, 2nd, ..., Zth buses in the bus set, respectively. They respectively represent the energy flow sizes of the branches connecting the 1st, 2nd, ..., U energy storage device nodes in the energy storage device node set and the 1st, 2nd, ..., Z buses in the bus set; the sizes of the branch energy flows constructed above do not include uncertainty and are all decision variables.

[0038] The energy flow-material flow balance matrix H is as follows:

[0039]

[0040] The nodes where E distributed new energy power generation equipment, F multi-energy conversion equipment and G industrial production line loads are located in the energy-material flow coupling association graph system constitute the first node set, which includes X first nodes, X = E + F + G, H 11 ,H 12 …H 1XRepresents the energy-material conversion matrix of the 1st, 2nd, ..., Xth first nodes in the first node set; the nodes where the U energy storage devices and the V material storage warehouses are located in the energy-material flow coupling association graph system constitute a second node set, and the second node set includes Y second nodes, Y = U + V, H 21 ,H 22 …H 2y …H 2Y represents the energy-material conversion matrix of the 1st, 2nd, ..., Yth second nodes in the second node set; H 31 ,H 32 …H 3z …H 3Z represents the energy balance matrix of the 1st, 2nd, ..., Zth buses.

[0041] The energy-material conversion matrix H of the xth first node in the energy-material conversion matrices of the 1st, 2nd, ..., Xth first nodes in the first node set 1x The details are as follows:

[0042] H 1x =C 1x I 1x

[0043] H 1x W=0

[0044] Among them, C 1x Represents the conversion feature matrix of the x-th first node in the first node set, I 1x represents the port-branch coefficient matrix of the x-th first node in the first node set, 1≤x≤X.

[0045] The conversion feature matrix C of the x-th first node in the first node set 1x The number of rows is the total number of conversion processes in the x-th first node in the first node set. The conversion process includes the process of converting one energy into another energy, the process of converting one material into another material, and the process of consuming one energy to produce one material. 1x The number of columns is the total number of ports of the x-th first node in the first node set; if the x-th first node in the first node set has L conversion processes and J ports, and the input of the l-th conversion process is input from the j-th port, then C 1x The value of the lth row and jth column is the conversion efficiency of the conversion process; if the output of the lth conversion process of the xth first node in the first node set is output from the jth port, then C 1x The value of row l and column j is 1; 1x All other unassigned values ​​are 0, 1≤l≤L, 1≤j≤J <Q。

[0046] The port-branch coefficient matrix I of the xth first node in the first node set 1x The number of rows is the total number of ports of the x-th first node in the first node set; 1x The number of columns is the total number of branches and virtual lines in the energy-material flow coupling association diagram system, which is K+Y; if the x-th first node in the first node set has O branches and J ports, and the o-th branch inputs to the j-th port, then I 1x The value of the jth row and the oth column of is 1; if the oth branch of the xth first node in the first node set outputs from the jth port, then I 1x The value of row j and column o is -1; 1x All other values ​​not assigned in the table are 0, 1≤o≤O <K+Y。

[0047] The energy-material conversion matrix H of the yth second node in the energy-material conversion matrices of the 1st, 2nd ..., Yth second nodes in the second node set is 2y The details are as follows:

[0048] H 2y =C 2y I 2y

[0049] H 2y W=0

[0050] Among them, C 2y represents the conversion feature matrix of the y-th second node in the second node set, I 2y represents the port-branch coefficient matrix of the y-th second node in the second node set, 1≤y≤Y.

[0051] The conversion feature matrix C of the y-th second node in the second node set 2y is a 1×3 matrix, C 2y The value of the first column of is 1. If the yth second node in the second node set is an energy storage device, then C 2y The value of the second column is the charging efficiency of the y-th second node, C 2y The value of the third column is the energy release efficiency of the yth second node; if the yth second node in the second node set is a material storage warehouse, then C 2y The value of the second column is the efficiency of the storage material of the y-th second node, C 2y The value in the third column is the efficiency of the output material of the y-th second node.

[0052] The port-branch coefficient matrix I of the yth second node in the second node set 2y The number of rows is 3, I 2yThe number of columns is the total number of branches and virtual lines in the energy-material flow coupling association diagram system, that is, K+Y; if the increment of the virtual line of the y-th second node in the second node set is located in the y-th column of the branch set matrix B without uncertainty, then I 2y The value of the yth column of the first row of is 1, and the other unassigned values ​​in the same column are 0; if the branch of the yth second node in the input second node set is located in the Y+kth column of the branch set matrix B that does not contain uncertainty, then I 2y The value of the yth column of the second row of is 1, and the other unassigned values ​​in the same column are 0, 1≤k≤K; if the branch output from the yth second node in the second node set is located in the Y+kth column of the branch set matrix B that does not contain uncertainty, then I 2y The value of the y column in the third row is -1, and all other unassigned values ​​in the same column are 0.

[0053] The energy balance matrix H of the 1st, 2nd, ..., Zth bus is 3z The details are as follows:

[0054] H 3z W=0

[0055] Among them, the energy balance matrix H of the zth bus in the energy-material flow coupling correlation diagram system is 3z The number of rows is 1, H 3z The number of columns is the total number of branches and virtual lines in the energy-material flow coupling association diagram system, which is K+Y. If the branch of the zth bus in the input energy-material flow coupling association diagram system is located in the Y+kth column of the branch set matrix B without uncertainty, then H 3z The value of the Y+kth column of is 1; if the branch output from the zth bus in the energy-material flow coupling association diagram system is located in the Y+kth column of the branch set matrix B without uncertainty, then H 3z The value of the Y+kth column of 3z All other unassigned values ​​are 0.

[0056] In the energy-material flow coupling model, the minimum set matrix B of the branch set matrix without uncertainty min Specifically, it is the common set of the minimum values ​​of each element in the virtual line set matrix B1 and the minimum values ​​of each element in the branch set matrix B2 of the branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set; the maximum set matrix B of the branch set matrix without uncertainty max Specifically, it is a common set of the maximum values ​​of each element in the virtual line set matrix B1 and the maximum values ​​of each element in the branch set matrix B2 of the branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set.

[0057] The yth element ΔS of each element in the virtual circuit set matrix B1 y , that is, the energy increment of the energy storage device connected to the 1st, 2nd, ...Yth virtual circuit in the virtual circuit set per unit time, or the material increment of the material storage warehouse connected to the virtual circuit, specifically satisfies the following formula:

[0058]

[0059] Where, ΔS y，min It represents the minimum value of the energy increment of the energy storage device connected to the yth virtual line in the virtual line set or the material increment of the material storage warehouse connected to the yth virtual line in unit time, ΔS y，max It represents the maximum value of the energy increment of the energy storage device connected to the yth virtual line in the virtual line set or the material increment of the material storage warehouse connected to the yth virtual line in unit time; S y，min S represents the minimum energy storage capacity of the energy storage device connected to the yth virtual line in the virtual line set or the minimum material storage capacity of the material storage warehouse connected to the yth virtual line. y，max S represents the maximum energy storage capacity of the energy storage device connected to the yth virtual line in the virtual line set or the maximum material storage capacity of the material storage warehouse connected to the yth virtual line; y，soc It represents the energy storage capacity of the energy storage device connected to the y-th virtual line in the virtual line set or the material storage capacity of the material storage warehouse connected to the y-th virtual line before building the energy-material flow coupling model.

[0060] The beneficial effects of the present invention are:

[0061] The method of the present invention unifies the different modeling methods of energy conversion equipment and industrial production line loads in industrial production, uses a unified method to describe energy flows and material flows with and without uncertainty, and expresses them in the form of a matrix. It can be applied to multiple fields such as industrial production scheduling and equipment investment and construction, and further assist in the refined scheduling of industrial production, production data correction, equipment investment and construction, energy saving and efficiency improvement, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a flow chart of the modeling method of the present invention;

[0063] Figure 2 Schematic diagram of the energy-material flow coupling correlation diagram system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0065] The modeling and coupling method of the present invention comprises the following steps:

[0066] 1) Using graph theory, several distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line loads and material storage warehouses are associated to obtain an energy-material flow coupling association graph system.

[0067] In step 1), the distributed new energy power generation equipment is a device that converts new energy into electrical energy, specifically a distributed photovoltaic power generation device or a wind power generation device, but not limited thereto; the distributed new energy power generation equipment transmits electrical energy to the bus; the multi-energy conversion equipment is a device that converts the chemical energy of natural gas into thermal energy, the chemical energy of natural gas into thermal energy and electrical energy, or the electrical energy into thermal energy, but not limited thereto, specifically a gas boiler, a cogeneration unit or an electric boiler, etc.; the energy storage device is a device that stores the chemical energy of natural gas or electrical energy, but not limited thereto, specifically a gas storage device or an energy storage battery; the industrial production line load includes the intermediate production line load and the final production line load, and the intermediate production line load is a device that consumes the external directly transmitted electrical energy, the multi-energy conversion device and the energy storage device. The electric energy and thermal energy delivered after conversion by the conversion equipment are consumed simultaneously, or the electric energy directly delivered from the outside and the thermal energy delivered after conversion by the multi-energy conversion equipment are consumed simultaneously, thereby converting the unprocessed materials into the assembly line load of the processed materials, but not limited to this; the material storage warehouse is a warehouse for storing the processed materials obtained by the conversion of the industrial production assembly line load; the final production assembly line load is the production line load that consumes the electric energy directly delivered from the outside and the electric energy delivered after conversion by the multi-energy conversion equipment, thereby converting the processed materials in all material storage warehouses into the final materials; the distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production assembly line load and material storage warehouse are associated using the graph theory method to directly construct an energy-material flow coupling association graph system.

[0068] The energy-material flow coupling association diagram system includes E distributed new energy power generation equipment, F multi-energy conversion equipment, G industrial production line loads, U energy storage equipment, V material storage warehouses, P nodes, K branches, Q ports, Z buses, U+V virtual lines and U+V virtual interfaces, where P=E+F+G+U+V.

[0069] Each node represents a distributed renewable energy power generation device, a multi-energy conversion device, an energy storage device, an industrial production line load or a material storage warehouse; each branch represents the material flow or the same energy flow input to each node, or represents the material flow or the same energy flow output from each node. The types of energy flow include thermal energy flow, electric current and natural gas flow, etc.; each port represents the input endpoint of the material flow or the same energy flow input to each node, or represents the output port of the material flow or the same energy flow output from each node; each bus represents the physical network carrier through which the same energy flow flows. The type of energy flow is equal to the number of buses. The physical network carrier is specifically the regional distribution network through which the current flows and the regional thermal network through which the thermal energy flow flows. The regional natural gas network through which natural gas chemical energy flows. Each node representing an energy storage device or material storage warehouse is constructed with a virtual circuit and a virtual interface. For each energy storage device's virtual circuit and virtual interface, the virtual circuit represents the energy increment of the energy storage device per unit time, that is, the increment of the energy storage device's charge and discharge energy per unit time. The virtual interface represents the virtual location connecting the energy storage device and the virtual circuit. For each material storage warehouse's virtual circuit and virtual interface, the virtual circuit represents the material increment of the material storage warehouse per unit time, that is, the increment of material stored and transported per unit time. The virtual interface represents the virtual location connecting the material storage warehouse and the virtual circuit. To ensure energy-material flow balance at the node, virtual circuits and virtual interfaces are constructed as virtual physical carriers.

[0070] 2) Construct an energy-material flow coupling model of the energy-material flow coupling association diagram system.

[0071] In step 2), the energy-material flow coupling model constructed is as follows:

[0072]

[0073] Where H represents the energy flow-material flow balance matrix, W represents the combination of the branch set matrix of energy-material flow with and without uncertainty, B represents the branch set matrix without uncertainty, and B min and B max Denote the minimum and maximum set matrices of the branch set matrix without uncertainty, B min ≤B≤B max Represents the branch set matrix operation constraints.

[0074] The combination W of the branch set matrix with and without uncertainty of energy-material flow is as follows:

[0075] W=[Α T ,B T ] T

[0076] Where A represents the branch set matrix of energy-material flow containing uncertainty.

[0077] The predicted values ​​of each element in the branch set matrix A of the energy-material flow containing uncertainty are the energy and material parameters of each distributed new energy power generation equipment and each industrial production line load in step 3); the predicted values ​​of each element in the branch set matrix B that does not contain uncertainty are the energy and material parameters of each multi-energy conversion equipment, energy storage equipment and material storage warehouse in step 3.

[0078] The branch set matrix A of the energy-material flow with uncertainty is as follows:

[0079]

[0080] Among them, the nodes where E distributed new energy power generation equipment are located in the energy-material flow coupling association graph system constitute a distributed new energy power generation node set, and the distributed new energy power generation node set includes E distributed new energy power generation nodes. The nodes where G industrial production line loads are located constitute an industrial production line load node set, and the industrial production line load node set includes G industrial production line load nodes. A1 represents the branch set matrix of the branches connected by the distributed new energy power generation node set, and A2 represents the branch set matrix of the branches connected by the industrial production line load node set.

[0081] The branch set matrix A1 of the branches connected by the distributed new energy generation node set is as follows:

[0082] A1=[R1,R2,…,R E ] T

[0083] Among them, R1, R2, …, R E They respectively represent the energy flow of the branches connected to the 1st, 2nd...Eth distributed renewable energy generation nodes in the distributed renewable energy generation node set, that is, the power generation of distributed renewable energy generation equipment; due to the uncertainty of distributed renewable energy generation, these quantities are random variables.

[0084] The branch set matrix A2 of the branches connected to the industrial production line load node set is as follows:

[0085] A2=[M 11 ,M 12 ,…,M 1D ,M 21 ,M 22 ,…M 2D ,…,M G1 ,M G2,…M GD ] T

[0086] Among them, the P nodes in the energy-material flow coupling association graph system, except for the nodes where the G industrial production line loads are located, and the Z buses constitute an industrial connection element set. There are P-G+Z industrial connection elements in the industrial connection element set. D represents the number of industrial connection elements in the industrial connection element set, D=P-G+Z; M 11 ,M 12 ,…,M 1D ,M 21 ,M 22 ,…M 2D ,…,M G1 ,M G2 ,…M GD They respectively represent the size of the energy flow or material flow flowing through the branches connecting the 1st, 2nd, ..., G industrial production line load nodes in the industrial production line load node set and the 1st, 2nd, ..., D industrial connection elements in the industrial connection element set.

[0087] The energy-material flow of the branch constructed above includes uncertainty, but it is correlated with the energy-material flow on the branch connected to the same industrial production line load node. Therefore, for a certain industrial production line load, one branch is selected from all the branches connected to it as a random variable, and the other variables are decision variables. The output material flow of an industrial production line load is often selected as the branch of the random variable.

[0088] The branch set matrix B without uncertainty is as follows:

[0089]

[0090] Among them, the nodes where the F multi-energy conversion devices in the energy-material flow coupling association diagram system are located constitute a multi-energy conversion device node set, and the multi-energy conversion device node set includes F multi-energy conversion device nodes. The nodes where the U energy storage devices are located constitute an energy storage device node set, and the energy storage device node set includes U energy storage device nodes. The Z buses constitute a bus set, B1 represents a virtual line set matrix, and B2 represents a branch set matrix of branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set.

[0091] The virtual circuit set matrix B1 is as follows:

[0092] B1=[ΔS1,ΔS2,…,ΔS Y ] T

[0093] Among them, the Y virtual lines in the energy-material flow coupling association diagram system constitute a virtual line set, ΔS1, ΔS2,…, ΔS Y It represents the energy increment of the energy storage device connected to the 1st, 2nd, ...Yth virtual lines in the virtual line set per unit time, or the material increment of the material storage warehouse connected to the virtual line, Y = U + V. These quantities are all decision variables.

[0094] The branch set matrix B2 of the branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set is as follows:

[0095]

[0096] in, They represent the energy flow of the branches connecting the 1st, 2nd, ..., Fth multi-energy conversion device nodes in the multi-energy conversion device node set and the 1st, 2nd, ..., Uth energy storage device nodes in the energy storage device node set, respectively. They represent the energy flow of the branches connecting the 1st, 2nd, ..., Fth multi-energy conversion device nodes in the multi-energy conversion device node set and the 1st, 2nd, ..., Zth buses in the bus set, respectively. They respectively represent the energy flow sizes of the branches connecting the 1st, 2nd, ..., U energy storage device nodes in the energy storage device node set and the 1st, 2nd, ..., Z buses in the bus set; the sizes of the branch energy flows constructed above do not include uncertainty and are all decision variables.

[0097] The energy flow-material flow balance matrix H is as follows:

[0098]

[0099] The nodes where E distributed new energy power generation equipment, F multi-energy conversion equipment and G industrial production line loads are located in the energy-material flow coupling association graph system constitute the first node set, which includes X first nodes, X = E + F + G, H 11 ,H 12 …H 1X Represents the energy-material conversion matrix of the 1st, 2nd, ..., Xth first nodes in the first node set; the nodes where the U energy storage devices and the V material storage warehouses are located in the energy-material flow coupling association graph system constitute a second node set, and the second node set includes Y second nodes, Y = U + V, H 21 ,H 22 …H 2y …H 2Yrepresents the energy-material conversion matrix of the 1st, 2nd, ..., Yth second nodes in the second node set; H 31 ,H 32 …H 3z …H 3Z represents the energy balance matrix of the 1st, 2nd, ..., Zth buses.

[0100] The energy-material conversion matrix H of the xth first node in the energy-material conversion matrices of the 1st, 2nd, ..., Xth first nodes in the first node set 1x The details are as follows:

[0101] H 1x =C 1x I 1x

[0102] H 1x W=0

[0103] Among them, C 1x Represents the conversion feature matrix of the x-th first node in the first node set, I 1x represents the port-branch coefficient matrix of the x-th first node in the first node set, 1≤x≤X.

[0104] The conversion feature matrix C of the x-th first node in the first node set 1x The number of rows is the total number of conversion processes in the x-th first node in the first node set. The conversion process includes the process of converting one energy into another energy, the process of converting one material into another material, and the process of consuming one energy to produce one material. 1x The number of columns is the total number of ports of the x-th first node in the first node set; if the x-th first node in the first node set has L conversion processes and J ports, and the input of the l-th conversion process is input from the j-th port, then C 1x The value of the lth row and jth column is the conversion efficiency of the conversion process; if the output of the lth conversion process of the xth first node in the first node set is output from the jth port, then C 1x The value of row l and column j is 1; 1x All other unassigned values ​​are 0, 1≤l≤L, 1≤j≤J <Q。

[0105] The port-branch coefficient matrix I of the xth first node in the first node set 1x The number of rows is the total number of ports of the x-th first node in the first node set; 1x The number of columns is the total number of branches and virtual lines in the energy-material flow coupling association diagram system, which is K+Y; if the x-th first node in the first node set has O branches and J ports, and the o-th branch inputs to the j-th port, then I 1xThe value of the jth row and the oth column of is 1; if the oth branch of the xth first node in the first node set outputs from the jth port, then I 1x The value of row j and column o is -1; 1x All other values ​​not assigned in the table are 0, 1≤o≤O <K+Y。

[0106] The energy-material conversion matrix H of the yth second node in the energy-material conversion matrices of the 1st, 2nd, ..., Yth second nodes in the second node set 2y The details are as follows:

[0107] H 2y =C 2y I 2y

[0108] H 2y W=0

[0109] Among them, C 2y represents the conversion feature matrix of the y-th second node in the second node set, I 2y represents the port-branch coefficient matrix of the y-th second node in the second node set, 1≤y≤Y.

[0110] The conversion feature matrix C of the y-th second node in the second node set 2y is a 1×3 matrix, C 2y The value of the first column of is 1. If the yth second node in the second node set is an energy storage device, then C 2y The value of the second column is the charging efficiency of the y-th second node, C 2y The value of the third column is the energy release efficiency of the yth second node; if the yth second node in the second node set is a material storage warehouse, then C 2y The value of the second column is the efficiency of the storage material of the y-th second node, C 2y The value in the third column is the efficiency of the output material of the y-th second node.

[0111] The port-branch coefficient matrix I of the yth second node in the second node set 2y The number of rows is 3, I 2y The number of columns is the total number of branches and virtual lines in the energy-material flow coupling association diagram system, that is, K+Y; if the increment of the virtual line of the y-th second node in the second node set is located in the y-th column of the branch set matrix B without uncertainty, then I 2y The value of the yth column of the first row of is 1, and the other unassigned values ​​in the same column are 0; if the branch of the yth second node in the input second node set is located in the Y+kth column of the branch set matrix B that does not contain uncertainty, then I 2yThe value of the yth column of the second row of is 1, and the other unassigned values ​​in the same column are 0, 1≤k≤K; if the branch output from the yth second node in the second node set is located in the Y+kth column of the branch set matrix B that does not contain uncertainty, then I 2y The value of the y column in the third row is -1, and all other unassigned values ​​in the same column are 0.

[0112] The energy balance matrix H of the 1st, 2nd, ..., Zth bus 3z The details are as follows:

[0113] H 3z W=0

[0114] Among them, the energy balance matrix H of the zth bus in the energy-material flow coupling correlation diagram system is 3z The number of rows is 1, H 3z The number of columns is the total number of branches and virtual lines in the energy-material flow coupling association diagram system, which is K+Y. If the branch of the zth bus in the input energy-material flow coupling association diagram system is located in the Y+kth column of the branch set matrix B without uncertainty, then H 3z The value of the Y+kth column of is 1; if the branch output from the zth bus in the energy-material flow coupling association diagram system is located in the Y+kth column of the branch set matrix B without uncertainty, then H 3z The value of the Y+kth column of 3z All other unassigned values ​​are 0.

[0115] The minimum set matrix B of the branch set matrix without uncertainty in the energy-material flow coupling model min Specifically, it is the common set of the minimum values ​​of each element in the virtual line set matrix B1 and the minimum values ​​of each element in the branch set matrix B2 of the branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set; the maximum set matrix B of the branch set matrix without uncertainty max Specifically, it is a common set of the maximum values ​​of each element in the virtual line set matrix B1 and the maximum values ​​of each element in the branch set matrix B2 of the branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set.

[0116] The yth element ΔS in each element of the virtual circuit set matrix B1 y , that is, the energy increment of the energy storage device connected to the 1st, 2nd, ...Yth virtual circuit in the virtual circuit set per unit time, or the material increment of the material storage warehouse connected to the virtual circuit, specifically satisfies the following formula:

[0117]

[0118] Where, ΔS y，min It represents the minimum value of the energy increment of the energy storage device connected to the yth virtual line in the virtual line set or the material increment of the material storage warehouse connected to the yth virtual line in unit time, ΔS y，max It represents the maximum value of the energy increment of the energy storage device connected to the yth virtual line in the virtual line set or the material increment of the material storage warehouse connected to the yth virtual line in unit time; S y，min S represents the minimum energy storage capacity of the energy storage device connected to the yth virtual line in the virtual line set or the minimum material storage capacity of the material storage warehouse connected to the yth virtual line. y，max S represents the maximum energy storage capacity of the energy storage device connected to the yth virtual line in the virtual line set or the maximum material storage capacity of the material storage warehouse connected to the yth virtual line; y，soc It represents the energy storage capacity of the energy storage device connected to the y-th virtual line in the virtual line set or the material storage capacity of the material storage warehouse connected to the y-th virtual line before building the energy-material flow coupling model.

[0119] 3) The preset amounts of energy and material parameters of each distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line load and material storage warehouse are input into the energy-material flow coupling model. The energy-material flow coupling model outputs the adjustment amounts of the energy and material parameters of each distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line load and material storage warehouse and directly uses them as energy and material parameters, thereby realizing the coupling of energy flow and material flow considering uncertainty.

[0120] The uncertainties mentioned specifically include uncertainties in the industrial production process and uncertainties in distributed renewable energy power generation. Uncertainties in the industrial production process refer to uncertainties such as changes in production inventory caused by equipment failures, temporary arrival or cancellation of orders, unit production fluctuations, and production changes caused by equipment parameter changes. These uncertainties will affect the energy flow and material flow balance of the system. In order to characterize these uncertainties, random variables can be used to represent them in the subsequent modeling process. The distribution of random variables can be an empirical distribution obtained based on historical data, or a commonly used probability distribution model such as a normal distribution or a Poisson distribution. The uncertainty of distributed renewable energy power generation refers to the inability to accurately obtain the power generation of distributed renewable energy through prediction. The power generation of distributed renewable energy will also affect the energy flow and material flow balance of the system. In order to characterize this impact, the power generation of distributed renewable energy can be represented by random variables. The distribution of random variables can be a probability distribution obtained based on various existing prediction models, or a normal distribution can be used.

[0121] The specific embodiments are as follows:

[0122] According to step 1), the energy-material flow coupling correlation diagram system can be obtained, such as Figure 2 As shown in the figure, the system has one node of distributed renewable energy power generation equipment, two nodes of multi-energy conversion equipment, namely, a cogeneration unit and a gas boiler, three nodes of industrial production line load type, two nodes of energy storage equipment, namely, a battery and a gas storage device, and two nodes of material storage warehouse type, namely, a material storage warehouse. These nodes correspond to four virtual circuits, four virtual interfaces, 21 branches, and three buses. Production Line 1 is the injection molding and two-device processing workshop, Production Line 2 is the sheet metal production workshop, and Production Line 3 is the air conditioner outdoor unit assembly workshop. The input material flow of Production Line 1 specifically consists of injection molding raw materials and compressor (metal pipe) raw materials. Production Line 1 outputs finished evaporators and condensers to Material Storage Warehouse 1, which then delivers them to Production Line 3. The input material flow of Production Line 2 specifically consists of hot-dip galvanized sheets and other metal parts. Production Line 2 outputs finished sheet metal parts to Material Storage Warehouse 2, which then delivers them to Production Line 3, which ultimately delivers finished air conditioner outdoor units.

[0123] According to step 2), the energy-material conversion equations for distributed power generation equipment, cogeneration units, gas boilers, production lines 1, 2, and 3 can be calculated. Taking the cogeneration unit as an example, the specific equations are as follows:

[0124]

[0125] Among them, η g2e and η g2h are the power generation efficiency and heat generation efficiency of the cogeneration unit, which are known quantities. The matrix on the left side of the above formula is the node energy-material conversion matrix of the cogeneration unit node, which can be expressed as H chp . 0 2×16 Represented as a 2-row, 16-column matrix filled with all zeros, 0 2×2 Same thing.

[0126] According to step 2), the energy-material storage equations of the energy storage battery, material storage warehouse 1, and material storage warehouse 2 can be calculated. Taking the energy storage battery as an example, the specific equations are as follows:

[0127] [0 1×12 -1 0 1×9 η + -η - ]W=0

[0128] Among them, η + and η -are the charging efficiency and discharging efficiency of the energy storage battery, respectively, which are known quantities. The matrix on the left side of the above equation is the node energy-material storage matrix of the energy storage battery node.

[0129] According to step 2), the energy balance equation of the bus can be calculated. Taking the natural gas bus as an example, the specific equation is as follows:

[0130] [0 1×15 1 -1 -1 0 1×6 ]W=0

[0131] Finally, the energy-material flow coupling model of the entire system is constructed as follows:

[0132]

[0133] It can be seen from the above embodiments that the final result obtained by the present invention completely separates variables from fixed parameters, unifies the different modeling methods of distributed new energy power generation equipment, energy conversion equipment and industrial production line loads in industrial production, and uses a unified method to describe energy flows and material flows with and without uncertainty. It can be applied to multiple fields such as industrial production data correction, production scheduling, equipment investment and construction, etc.

Claims

1. A modeling and coupling method for energy flow and material flow considering uncertainty, characterized by: The steps include: 1) Using graph theory, a number of distributed renewable energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line loads, and material storage warehouses are associated to obtain an energy-material flow coupling association graph system; 2) Constructing an energy-material flow coupling model of the energy-material flow coupling association diagram system; 3) Inputting the preset values ​​of the energy and material parameters of each distributed renewable energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line load, and material storage warehouse into the energy-material flow coupling model, the energy-material flow coupling model outputs the adjusted values ​​of the energy and material parameters of each distributed renewable energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line load, and material storage warehouse and directly uses them as energy and material parameters, thus achieving the coupling of energy flow and material flow taking into account uncertainty; The energy-material flow coupling association graph system includes E distributed new energy power generation equipment, F multi-energy conversion equipment, G industrial production line loads, U energy storage equipment, V material storage warehouses, P nodes, K branches, Q ports, Z buses, U+V virtual lines and U+V virtual interfaces, where P = E+F+G+U+V; each node represents a distributed new energy power generation equipment, a multi-energy conversion equipment, an energy storage equipment, an industrial production line load or a material storage warehouse; Each branch represents the material flow or homogeneous energy flow input to each node, or represents the material flow or homogeneous energy flow output from each node. The types of energy flow include heat flow, electric current, and natural gas flow. Each port represents the input endpoint of the material flow or homogeneous energy flow input to each node, or represents the output port of the material flow or homogeneous energy flow output from each node. Each bus represents the physical network carrier through which the homogeneous energy flow flows. The types of energy flow are equal to the number of buses. Each node representing an energy storage device or material storage warehouse is also constructed with a virtual circuit and a virtual interface. For each virtual circuit and virtual interface of each energy storage device, the virtual circuit represents the energy increment of the energy storage device per unit time. The virtual interface represents a virtual location point connecting the energy storage device and the virtual line; For each material storage warehouse's virtual line and virtual interface, the virtual line represents the material increment of the material storage warehouse per unit time; the virtual interface represents the virtual location point connecting the material storage warehouse and the virtual line; In step 2), the energy-material flow coupling model constructed is as follows: Where H represents the energy flow-material flow balance matrix, W represents the combination of the branch set matrix of energy-material flow with and without uncertainty, B represents the branch set matrix without uncertainty, and B min and B max They represent the minimum and maximum set matrices of the branch set matrices without uncertainty; The combination W of the branch set matrix of energy-material flow with and without uncertainty is as follows: W=[A T ,B T ] T Where A represents the branch set matrix of energy-material flow with uncertainty; The predicted values ​​of each element in the branch set matrix A of the energy-material flow containing uncertainty are the energy and material parameters of each distributed new energy power generation equipment and each industrial production line load in step 3); the predicted values ​​of each element in the branch set matrix B that does not contain uncertainty are the energy and material parameters of each multi-energy conversion equipment, energy storage equipment and material storage warehouse in step 3).

2. The method for modeling and coupling energy and material flows considering uncertainty according to claim 1, characterized in that: In step 1), the distributed new energy power generation equipment is a device that converts new energy into electrical energy; Multi-energy conversion equipment is a device that converts the chemical energy of natural gas into thermal energy, converts the chemical energy of natural gas into thermal energy and electrical energy, or converts electrical energy into thermal energy; Energy storage equipment is equipment that stores chemical energy or electrical energy of natural gas; industrial production line loads include intermediate production line loads and final production line loads. Intermediate production line loads are line loads that simultaneously consume externally directly transmitted electrical energy, electrical energy and thermal energy converted by multi-energy conversion equipment, or simultaneously consume externally directly transmitted electrical energy and thermal energy converted by multi-energy conversion equipment, thereby converting unprocessed materials into processed materials; material storage warehouses are warehouses for storing processed materials obtained by the conversion of industrial production line loads; final production line loads are production line loads that simultaneously consume externally directly transmitted electrical energy and electrical energy converted by multi-energy conversion equipment, thereby converting processed materials in all material storage warehouses into final materials; distributed new energy power generation equipment, multi-energy conversion equipment, energy storage equipment, industrial production line loads and material storage warehouses are associated using graph theory to directly construct an energy-material flow coupling association graph system.

3. The method for modeling and coupling energy and material flows considering uncertainty according to claim 1, characterized in that: The branch set matrix A of the energy-material flow containing uncertainty is as follows: Among them, the nodes where E distributed new energy power generation equipment are located in the energy-material flow coupling association graph system constitute a distributed new energy power generation node set, and the distributed new energy power generation node set includes E distributed new energy power generation nodes. The nodes where G industrial production line loads are located constitute an industrial production line load node set, and the industrial production line load node set includes G industrial production line load nodes. A1 represents the branch set matrix of the branches connected by the distributed new energy power generation node set, and A2 represents the branch set matrix of the branches connected by the industrial production line load node set; The branch set matrix A1 of the branches connected by the distributed new energy generation node set is as follows: A1=[R1,R2,…,R E ] T Among them, R1, R2, …, R E They respectively represent the energy flow of the branches connected to the 1st, 2nd…Eth distributed renewable energy generation nodes in the distributed renewable energy generation node set; The branch set matrix A2 of the branches connected to the industrial production line load node set is as follows: A2=[M 11 ,M 12 ,…,M 1D ,M 21 ,M 22 ,…M 2D ,…,M G1 ,M G2 ,…M GD ] T Among them, the P nodes in the energy-material flow coupling association graph system, except for the nodes where the G industrial production line loads are located, and the Z buses constitute an industrial connection element set. There are P-G+Z industrial connection elements in the industrial connection element set. D represents the number of industrial connection elements in the industrial connection element set, D=P-G+Z; M 11 ,M 12 ,…,M 1D ,M 21 ,M 22 ,…M 2D ,…,M G1 ,M G2 ,…M GD They respectively represent the size of the energy flow or material flow flowing through the branches connecting the 1st, 2nd, ..., G industrial production line load nodes in the industrial production line load node set and the 1st, 2nd, ..., D industrial connection elements in the industrial connection element set.

4. The method for modeling and coupling energy and material flows considering uncertainty according to claim 1, characterized in that: The branch set matrix B without uncertainty is as follows: Among them, the nodes where the F multi-energy conversion devices in the energy-material flow coupling association graph system are located constitute a multi-energy conversion device node set, and the multi-energy conversion device node set includes F multi-energy conversion device nodes. The nodes where the U energy storage devices are located constitute an energy storage device node set, and the energy storage device node set includes U energy storage device nodes. The Z buses constitute a bus set. B1 represents a virtual line set matrix, and B2 represents a branch set matrix of branches connecting the multi-energy conversion device node set, the energy storage device node set, and the bus set. The virtual circuit set matrix B1 is as follows: B1=[ΔS1,ΔS2,…,ΔS Y ] T Among them, the Y virtual lines in the energy-material flow coupling association diagram system constitute a virtual line set, ΔS1, ΔS2,…, ΔS Y It represents the energy increment of the energy storage device connected to the 1st, 2nd, ...Yth virtual line in the virtual line set or the material increment of the material storage warehouse connected to the virtual line within a unit time, Y = U + V; The branch set matrix B2 of the branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set is as follows: in, They represent the energy flow of the branches connecting the 1st, 2nd, ..., Fth multi-energy conversion device nodes in the multi-energy conversion device node set and the 1st, 2nd, ..., Uth energy storage device nodes in the energy storage device node set, respectively. They represent the energy flow of the branches connecting the 1st, 2nd, ..., Fth multi-energy conversion device nodes in the multi-energy conversion device node set and the 1st, 2nd, ..., Zth buses in the bus set, respectively. They respectively represent the energy flow sizes of the branches connecting the 1st, 2nd, ..., U energy storage device nodes in the energy storage device node set and the 1st, 2nd, ..., Z buses in the bus set.

5. The method for modeling and coupling energy and material flows considering uncertainty according to claim 1, characterized in that: The energy flow-material flow balance matrix H is as follows: The nodes where E distributed new energy power generation equipment, F multi-energy conversion equipment and G industrial production line loads are located in the energy-material flow coupling association graph system constitute the first node set, which includes X first nodes, X = E + F + G, H 11 ,H 12 …H 1X Represents the energy-material conversion matrix of the 1st, 2nd, ..., Xth first nodes in the first node set; the nodes where the U energy storage devices and the V material storage warehouses are located in the energy-material flow coupling association graph system constitute a second node set, and the second node set includes Y second nodes, Y = U + V, H 21 ,H 22 …H 2y …H 2Y represents the energy-material conversion matrix of the 1st, 2nd, ..., Yth second nodes in the second node set; H 31 ,H 32 …H 3z …H 3Z represents the energy balance matrix of the 1st, 2nd, ..., Zth buses.

6. The method for modeling and coupling energy and material flows considering uncertainty according to claim 5, characterized in that: The energy-material conversion matrix H of the xth first node in the energy-material conversion matrices of the 1st, 2nd, ..., Xth first nodes in the first node set 1x The details are as follows: H 1x =C 1x I 1x H 1x W=0 Among them, C 1x Represents the conversion feature matrix of the x-th first node in the first node set, I 1x represents the port-branch coefficient matrix of the x-th first node in the first node set, 1≤x≤X; The conversion feature matrix C of the x-th first node in the first node set 1x The number of rows is the total number of conversion processes in the x-th first node in the first node set. The conversion process includes the process of converting one energy into another energy, the process of converting one material into another material, and the process of consuming one energy to produce one material. 1x The number of columns is the total number of ports of the x-th first node in the first node set; if the x-th first node in the first node set has L conversion processes and J ports, and the input of the l-th conversion process is input from the j-th port, then C 1x The value of the lth row and jth column is the conversion efficiency of the conversion process; if the output of the lth conversion process of the xth first node in the first node set is output from the jth port, then C 1x The value of row l and column j is 1; 1x All other unassigned values ​​are 0, 1≤l≤L, 1≤j≤J <Q; The port-branch coefficient matrix I of the xth first node in the first node set 1x The number of rows is the total number of ports of the x-th first node in the first node set; 1x The number of columns is the total number of branches and virtual lines in the energy-material flow coupling association diagram system, which is K+Y; if the x-th first node in the first node set has O branches and J ports, and the o-th branch inputs to the j-th port, then I 1x The value of the jth row and the oth column of is 1; if the oth branch of the xth first node in the first node set outputs from the jth port, then I 1x The value of row j and column o is -1; 1x All other values ​​not assigned in the table are 0, 1≤o≤O <K+Y; The energy-material conversion matrix H of the yth second node in the energy-material conversion matrices of the 1st, 2nd ..., Yth second nodes in the second node set is 2y The details are as follows: H 2y =C 2y I 2y H 2y W=0 Among them, C 2y represents the conversion feature matrix of the y-th second node in the second node set, I 2y represents the port-branch coefficient matrix of the y-th second node in the second node set, 1≤y≤Y; The conversion feature matrix C of the y-th second node in the second node set 2y is a 1×3 matrix, C 2y The value of the first column of is 1. If the yth second node in the second node set is an energy storage device, then C 2y The value of the second column is the charging efficiency of the y-th second node, C 2y The value of the third column is the energy release efficiency of the yth second node; if the yth second node in the second node set is a material storage warehouse, then C 2y The value of the second column is the efficiency of the storage material of the y-th second node, C 2y The value of the third column is the efficiency of the output material of the y-th second node; The port-branch coefficient matrix I of the yth second node in the second node set 2y The number of rows is 3, I 2y The number of columns is the total number of branches and virtual lines in the energy-material flow coupling association diagram system, that is, K+Y; if the increment of the virtual line of the y-th second node in the second node set is located in the y-th column of the branch set matrix B without uncertainty, then I 2y The value of the yth column of the first row of is 1, and the other unassigned values ​​in the same column are 0; if the branch of the yth second node in the input second node set is located in the Y+kth column of the branch set matrix B that does not contain uncertainty, then I 2y The value of the yth column of the second row of is 1, and the other unassigned values ​​in the same column are 0, 1≤k≤K; if the branch output from the yth second node in the second node set is located in the Y+kth column of the branch set matrix B that does not contain uncertainty, then I 2y The value of the y column in the third row is -1, and all other unassigned values ​​in the same column are 0; The energy balance matrix H of the 1st, 2nd, ..., Zth bus is 3z The details are as follows: H 3z W=0 Among them, the energy balance matrix H of the zth bus in the energy-material flow coupling correlation diagram system is 3z The number of rows is 1, H 3z The number of columns is the total number of branches and virtual lines in the energy-material flow coupling association diagram system, which is K+Y. If the branch of the zth bus in the input energy-material flow coupling association diagram system is located in the Y+kth column of the branch set matrix B without uncertainty, then H 3z The value of the Y+kth column of is 1; if the branch output from the zth bus in the energy-material flow coupling association diagram system is located in the Y+kth column of the branch set matrix B without uncertainty, then H 3z The value of the Y+kth column of 3z All other unassigned values ​​are 0.

7. The method for modeling and coupling energy and material flows considering uncertainty according to claim 1, characterized in that: In the energy-material flow coupling model, the minimum set matrix B of the branch set matrix without uncertainty min Specifically, it is the common set of the minimum values ​​of each element in the virtual line set matrix B1 and the minimum values ​​of each element in the branch set matrix B2 of the branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set; the maximum set matrix B of the branch set matrix without uncertainty max Specifically, it is a common set of the maximum values ​​of each element in the virtual line set matrix B1 and the maximum values ​​of each element in the branch set matrix B2 of the branches connecting the multi-energy conversion device node set, the energy storage device node set and the bus set.

8. The method for modeling and coupling energy and material flows considering uncertainty according to claim 7, characterized in that: The yth element ΔS of each element in the virtual circuit set matrix B1 y , that is, the energy increment of the energy storage device connected to the 1st, 2nd, ...Yth virtual circuit in the virtual circuit set per unit time, or the material increment of the material storage warehouse connected to the virtual circuit, specifically satisfies the following formula: Where, ΔS y，min It represents the minimum value of the energy increment of the energy storage device connected to the yth virtual line in the virtual line set or the material increment of the material storage warehouse connected to the yth virtual line in unit time, ΔS y，max It represents the maximum value of the energy increment of the energy storage device connected to the yth virtual line in the virtual line set or the material increment of the material storage warehouse connected to the yth virtual line in unit time; S y，min S represents the minimum energy storage capacity of the energy storage device connected to the yth virtual line in the virtual line set or the minimum material storage capacity of the material storage warehouse connected to the yth virtual line. y，max S represents the maximum energy storage capacity of the energy storage device connected to the yth virtual line in the virtual line set or the maximum material storage capacity of the material storage warehouse connected to the yth virtual line; y，soc It represents the energy storage capacity of the energy storage device connected to the y-th virtual line in the virtual line set or the material storage capacity of the material storage warehouse connected to the y-th virtual line before building the energy-material flow coupling model.

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