Multi-energy carbon flow emission monitoring method and device suitable for industrial park

Abstract

The invention discloses a multi-energy carbon flow emission monitoring method and device suitable for an industrial park, and the method comprises the steps: building a source-network-load full-link multi-energy carbon flow model from the two links of energy transmission and energy conversion in combination with the carbon emission characteristics of each link of an energy network; providing a basic flow of multi-energy carbon flow calculation of the industrial park in combination with respective characteristics of various energy sources; on the basis of the multi-energy carbon flow model and the basic flow of industrial park multi-energy carbon flow calculation, energy carbon flow information of all inflow nodes of a current node is inquired in combination with a decentralized iteration thought until the energy carbon flow information of the node is calculated, and global energy carbon flow information is output when preset iteration times are reached; and on the basis of global energy carbon flow information, the multi-energy carbon flow of the industrial park is monitored in combination with the characteristics of the global energy carbon flow information. The device comprises a processor and a memory. According to the invention, accurate and credible real-time carbon emission calculation and monitoring of the industrial park energy system are realized, and the atmospheric environment is improved.

Description

Technical Field

[0001] The present invention relates to the field of energy carbon emissions in industrial parks, and in particular to a monitoring method and device for multi-energy carbon flow emissions suitable for industrial parks. Background Art

[0002] In the latest "Green and Low-carbon Transformation Industry Guidance Catalog (2024 Edition)", industrial industries with high energy consumption and carbon emissions are still the top priority of low-carbon transformation. my country's industrial energy consumption accounts for about 65% of the total social energy consumption. As an important platform for my country's industrial agglomeration and economic development, industrial parks have energy consumption characteristics and carbon emission status that directly affect regional and even national energy consumption and environmental quality. They are an important group on the energy consumption side of my country and shoulder the important mission of reducing carbon emissions in terminal energy consumption. Their efficient energy utilization and effective control of carbon emissions play an important role in my country's industrial green and low-carbon transformation and high-quality economic development.

[0003] Monitoring the carbon emissions of industrial park energy is an important prerequisite for industrial users to achieve energy conservation and emission reduction. However, since the multi-energy links in industrial parks belong to different entities, there are multiple areas of heterogeneous energy coupling, and the degree of energy flow-carbon flow coupling is high, the park's comprehensive energy planning lacks system coordination, operation lacks in-depth optimization, and multi-energy carbon flow lacks accurate monitoring and accounting. This seriously affects the accurate and reliable carbon emission calculation and monitoring of the industrial park energy system, and it is urgent to study the full-link, accurate, and real-time industrial park energy carbon emission calculation and monitoring method.

[0004] There are various ways to measure carbon emissions, and they are widely used in coal-fired power plants. [1][2][3] , and there are also many studies on carbon emission measurement technology for integrated energy areas. However, the current method of calculating carbon emissions in energy systems is limited to calculating the total carbon emissions of the system from the energy production end, that is, based on the emissions generated by the combustion of fossil fuels. [4] This method fails to clearly identify carbon emissions directly related to energy use from the perspective of the consumer, and has computational lag problems, making it difficult to track the carbon footprint of different energy types in a multi-energy system in real time. Although the theory of carbon emission flow analysis has made great progress [5-7] However, there is no clear theoretical system for analyzing and calculating carbon flow in industrial parks, including electricity, cooling, heat and other energy forms. In addition, the existing methods for calculating carbon emission flow mainly include matrix method. [8] , Graph Theory [9] , recursive method

[10] ,These methods usually require a centralized system to complete the calculation, which places high ,requirements on computing power and storage resources, and it is difficult to ,guarantee the real-time performance of the flow data.

[0005] In actual technical applications, various shortcomings in carbon emission measurement will lead to technical difficulties such as insufficient carbon data management, difficulty in carbon traceability, and difficulty in carbon quota allocation. Especially in the actual monitoring of carbon emissions, the real-time, comprehensive and accurate monitoring cannot be guaranteed. There are often problems such as long monitoring time period, single monitored energy type, and poor monitoring data accuracy. Summary of the invention

[0006] The present invention provides a method and device for monitoring multi-energy carbon flow emissions suitable for industrial parks. The present invention realizes accurate and reliable real-time carbon emission calculation and monitoring of the energy system of industrial parks, and improves the atmospheric environment. See the following description for details:

[0007] In the first aspect, a monitoring method for multi-energy carbon flow emissions applicable to industrial parks, the method comprising:

[0008] Combined with the carbon emission characteristics of each link of the energy network, a multi-energy carbon flow model of the source-grid-load link is established from the two links of energy transmission and energy conversion; combined with the characteristics of various energy sources, the basic process of multi-energy carbon flow calculation in industrial parks is given;

[0009] Based on the multi-energy carbon flow model and the basic process of multi-energy carbon flow calculation in industrial parks, combined with the decentralized iteration idea, query the energy carbon flow information of all nodes flowing into the current node until the energy carbon flow information of the node is calculated. When the preset number of iterations is reached, the global energy carbon flow information is output;

[0010] Based on the global energy carbon flow information and combined with the characteristics of global energy carbon flow information, the multi-energy carbon flow of industrial parks is monitored.

[0011] The multi-energy carbon flow model is divided into two parts: energy transmission and energy conversion.

[0012] The multi-energy carbon flow model in the energy transmission link is divided into power grid, heat grid and gas grid models, as follows:

[0013]

[0014] Among them, ρ N,n represents the node carbon density; P l represents the active power of branch l; ρ B,l represents the branch carbon density of energy transmission line l; G h represents the active power injected by the energy production end h; ρ G,h represents the production carbon density of energy production end h; Ω G,n Represents the set of energy production terminals connected to the node; Ω L,n Represents the set of all branches flowing into the node; Ω N Represents a collection of nodes in the energy transmission network;

[0015] The multi-energy carbon flow model in the energy conversion link is as follows:

[0016] ρ out =Dρ in

[0017]

[0018] Among them, the matrix ρ out is the output carbon density coupling matrix, matrix ρi n is the input carbon density coupling matrix, matrix D is the carbon flow coupling matrix, and the coupling between each output port and the input port is calculated through the matrix element d ij By coupling the energy flow of the input port and its corresponding carbon density carbon flow coupling matrix, the carbon flow rate and carbon density output by the energy flow hub can be calculated.

[0019] The basic process of calculating the multi-energy carbon flow in the industrial park is as follows:

[0020] Obtain energy flow results for the industrial park, including power grid flow, gas grid air flow, and heat grid heat flow; use energy transmission models to calculate the carbon density and carbon flow rate of the power grid and gas grid;

[0021] The energy conversion model is used to calculate the carbon flow of each energy hub. For each energy hub, the input energy comes from the electricity network and the gas network. The energy transmission model is used to calculate the carbon flow of each regional heating network. The heat source of each regional heating network is the heat output of the connected energy hub.

[0022] The energy carbon flow information of the node is calculated as follows:

[0023]

[0024] Among them, P m→n is the energy injected by node m to node n; ρ m is the carbon density of node m; G h Energy produced in the energy production process.

[0025] In a second aspect, a monitoring device for multi-energy carbon flow emissions suitable for an industrial park, the device comprising:

[0026] Establish a model to combine the carbon emission characteristics of each link of the energy network and establish a multi-energy carbon flow model for the entire source-grid-load link from the two links of energy transmission and energy conversion;

[0027] The calculation module is used to combine the characteristics of various energy sources and provide the basic process of multi-energy carbon flow calculation in industrial parks;

[0028] The output module is used to query the energy carbon flow information of all nodes flowing into the current node based on the multi-energy carbon flow model and the basic process of multi-energy carbon flow calculation in the industrial park, combined with the decentralized iteration idea, until the energy carbon flow information of the node is calculated, and when the preset number of iterations is reached, the global energy carbon flow information is output;

[0029] The monitoring module is used to monitor the multi-energy carbon flow of the industrial park based on the global energy carbon flow information and combined with the characteristics of the global energy carbon flow information.

[0030] The multi-energy carbon flow model is divided into two parts: energy transmission and energy conversion.

[0031] The multi-energy carbon flow model in the energy transmission link is divided into power grid, heat grid and gas grid models, as follows:

[0032]

[0033] Among them, ρ N,n represents the node carbon density; P l represents the active power of branch l; ρ B,l represents the branch carbon density of energy transmission line l; G h represents the active power injected by the energy production end h; ρ G,h represents the production carbon density of energy production end h; Ω G,n Represents the set of energy production terminals connected to the node; Ω L,n Represents the set of all branches flowing into the node; Ω N Represents a collection of nodes in the energy transmission network;

[0034] The multi-energy carbon flow model in the energy conversion link is as follows:

[0035] ρ out =Dρ in

[0036]

[0037] Among them, the matrix ρ out is the output carbon density coupling matrix, matrix ρi n is the input carbon density coupling matrix, matrix D is the carbon flow coupling matrix, and the coupling between each output port and the input port is calculated through the matrix element d ij By coupling the energy flow of the input port and its corresponding carbon density carbon flow coupling matrix, the carbon flow rate and carbon density output by the energy flow hub can be calculated.

[0038] Wherein, the calculation module includes:

[0039] The acquisition submodule is used to obtain the energy flow results of the industrial park, including: power grid flow, gas grid air flow, and heat grid heat flow; the carbon density and carbon flow rate of the power grid and gas grid are calculated using the energy transmission model;

[0040] A calculation submodule, for calculating the carbon flow of each energy hub using an energy conversion model, and for each energy hub, the input energy comes from the electricity network and the gas network;

[0041] The output submodule is used to calculate the carbon flow of each district heating network using the energy transfer model. The heat source of each district heating network is the heat output of the connected energy hub.

[0042] A third aspect is a monitoring device for multi-energy carbon flow emissions suitable for industrial parks, the device comprising: a processor and a memory, the memory storing program instructions, the processor calling the program instructions stored in the memory to enable the device to execute any one of the methods described in the first aspect.

[0043] In a fourth aspect, a computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes any one of the methods described in the first aspect.

[0044] The beneficial effects of the technical solution provided by the present invention are:

[0045] 1. The present invention establishes energy carbon flow models for various energy forms in industrial parks, and performs energy conversion modeling for multi-energy coupling links; compared with carbon flow calculations in traditional power systems, the present invention can adapt to carbon emission calculations in various energy areas;

[0046] 2. Compared with traditional carbon flow calculation, the present invention adopts a decentralized multi-energy iterative carbon flow calculation method suitable for large-scale energy networks. It improves the overall calculation efficiency on the basis of ensuring accuracy and real-time performance, which is conducive to saving computing power. At the same time, it takes into account the carbon emissions in the whole process, which is conducive to the real-time calculation of carbon emissions in all links.

[0047] 3. Compared with traditional monitoring methods, the monitoring method of the present invention can conduct real-time and high-accuracy carbon emission monitoring for multi-energy industrial parks; in addition, the monitoring method adopts the iterative method as the core algorithm, which significantly saves computing power and shortens the monitoring response time. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a flowchart of a multi-energy carbon flow calculation method applicable to industrial parks;

[0049] Figure 2 It is a schematic diagram of the heating network nodes;

[0050] Figure 3 It is the schematic diagram of the improved IEEE39 node power grid;

[0051] Figure 4 It is a schematic diagram of a 6-node gas network;

[0052] Figure 5 This is a schematic diagram of a 6-node heating network;

[0053] Figure 6 This is a schematic diagram of the energy hub;

[0054] Figure 7 This is a schematic diagram of energy carbon flow in a 6-node gas grid;

[0055] Figure 8 This is a schematic diagram of energy carbon flow in the energy hub;

[0056] Fig. 9 This is a schematic diagram of energy carbon flow in a 6-node heat network;

[0057] Fig.10 Schematic diagram of multi-energy carbon flow monitoring. DETAILED DESCRIPTION

[0058] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention are described in further detail below.

[0059] Example 1

[0060] The embodiment of the present invention provides a monitoring method for multi-energy carbon flow emissions applicable to industrial parks. A multi-energy carbon flow model is established by using the carbon emission flow related theory and the energy convergence and allocation principle. The energy carbon flow is calculated by using the iteration method. A carbon emission monitoring method is proposed with the iteration method as the core algorithm. This method provides a more feasible reference for the calculation method of energy carbon emissions in industrial parks, and improves the comprehensiveness, accuracy and rapidity of carbon emission monitoring. The method includes the following steps:

[0061] 101: Based on the carbon emission flow theory and the principle of energy convergence and allocation, the carbon emission flow indicators and calculation principles are proposed. Combined with the carbon emission characteristics of each link of the energy network, a multi-energy carbon flow model of the source-grid-load link is established from the two links of energy transmission and energy conversion;

[0062] 102: Combine the characteristics of various energy sources to judge the type of industrial park and give the basic process of multi-energy carbon flow calculation in industrial parks;

[0063] 103: Introducing the idea of ​​decentralized iteration, based on the multi-energy carbon flow model and the basic process of multi-energy carbon flow calculation in industrial parks, a multi-energy carbon flow calculation method suitable for large-scale networks is proposed. Each node only uses the energy carbon flow data of the node related to it for a single calculation, and the global energy carbon flow information is finally calculated through continuous iteration;

[0064] 104: Based on the global energy carbon flow information and combined with the characteristics of the global energy carbon flow information, the multi-energy carbon flow of the industrial park is monitored.

[0065] In summary, the embodiment of the present invention can effectively calculate and monitor multi-energy carbon flows through the above steps 101 to 104, providing theoretical support for the comprehensive energy carbon emission measurement and monitoring method.

[0066] Example 2

[0067] Combine the following Figure 1 , Figure 2 , Table 1, Table 2 and specific calculation formulas further introduce the scheme in Example 1, see the description for details:

[0068] 201: Establishment of multi-energy carbon flow model:

[0069] Among them, this step includes:

[0070] 2011; Proposed carbon emission flow indicators and calculation principles:

[0071] The multi-energy carbon emission flow indicators are shown in Table 1:

[0072] Table 1 Carbon emission flow indicators

[0073]

[0074] According to the energy convergence principle, when energy from different branches is injected into a node, the energy carbon flow is mixed, and the node carbon density ρ of the node is N,n is the carbon density of all branches flowing into the branch ρ B,i The weighted average of is as follows:

[0075]

[0076] in, represents the set of all energy flow branches flowing into the node n; E i represents the energy flow into the i-th branch of node n; R i represents the carbon flow rate of the i-th branch flowing into node n.

[0077] According to the energy distribution principle, the energy flowing out from a node should have the same ratio as the energy flowing in, that is, the energy flow when flowing out should be distributed according to the ratio of the energy flow when flowing in. The formula is as follows:

[0078]

[0079] in, represents the set of outgoing branches of node n; E j,i represents the energy flow from branch j to branch i; E j represents the energy flow of the jth branch out of node n; E s represents the energy flow into the sth branch of node n.

[0080] At the same time, the carbon flow rate of the jth branch flowing out of node n is equal to all The sum of the contributions of all inflow branches to the carbon flow rate of outflow branch j is as follows:

[0081]

[0082] Among them, R j represents the carbon flow rate out of branch j.

[0083] Therefore, the carbon density ρ of the outflow branch j is B,j It can be expressed as:

[0084]

[0085] Combined with formula (2), substitute into E j,i get:

[0086]

[0087] From this we can draw an important conclusion: the carbon density ρ of any branch outflow node n B,j Equal to the node carbon density ρ of the node n N,n ; Furthermore, it is concluded that in the calculation of energy carbon flow, the node carbon density is only affected by the injected energy flow, and the energy flow out of the node has no effect on the node carbon density. This conclusion is the basic principle of the subsequent multi-energy carbon flow model and its calculation.

[0088] 2012: Multi-energy carbon flow model in energy transmission;

[0089] The establishment of a multi-energy carbon flow model in the energy transmission process first requires modeling different energy transmission links separately based on the characteristics of each energy network and the basic principles of the multi-energy carbon flow model and its calculation.

[0090] In the power grid, electricity, as a secondary energy source, does not directly participate in the carbon emission process, and carbon emissions almost all come from the production process. The power system carbon emission flow is used to characterize the indirect carbon emissions of each branch flow, which is a virtual network flow formed by the power flow.

[0091] The node carbon density formula of the power grid is as follows:

[0092]

[0093] Among them, ρ NP,n represents the carbon density of the grid node; P l represents the active power of line l; X=1 means that the carbon emissions generated by network loss are allocated to the demand side, and X=0 means that they are allocated to the grid side; ρ B,l represents the branch carbon density of the power grid branch line l; G h represents the active power injected by generator h; ρ G,h represents the production carbon density of generator h; Ω G,n represents the generator set of the node; Ω L,n Represents the set of all branches flowing into the node; Ω N Represents a set of power grid nodes. By inputting the active power of the power grid generator, the production carbon density, and the power grid flow information, the carbon density and carbon flow rate information of each node in the power grid can be calculated.

[0094] In the gas grid, natural gas is the main source of energy. The carbon compounds such as methane in it contain carbon, which directly produces carbon emissions when the gas is converted into secondary energy. The carbon emissions in the gas network are regarded as potential carbon emissions of the gas.

[0095] The nodal carbon density formula of the gas grid is as follows:

[0096]

[0097] Among them, R b is the carbon flow rate of the gas network pipeline; f b represents the gas flow rate in pipe b, f w Indicates the gas flow rate of the fuel gas source w, in km 3 / h;Ω B,g ,Ω GS,g They represent the set of pipelines flowing into node g and the set of gas sources w on node g respectively; ρ GGS,w It represents the carbon emissions generated by burning one unit of energy of natural gas; B is the calorific value of natural gas, which is 10.45MWh / km 3 .

[0098] By inputting the gas network gas source output airflow rate, compressor power, pipeline airflow rate, and load airflow rate, the carbon density and carbon flow rate information of each node in the gas network can be calculated.

[0099] In the heat network, Figure 2 As shown in the figure, the heat network consists of heat source, heat load and heat network pipeline, in which the heat network is divided into heat supply network and return water network. Heat is generated by the heat source, and finally supplied to the load through the water circulation process in the heating pipeline.

[0100] Similar to the electricity and gas grids, the node carbon density of the heat network is only related to the branch carbon density of all related branches flowing into the node. In the heat network, the water in each pipe flowing into the heat network node is mixed at the node. For the heat network, there is:

[0101]

[0102] Among them, m S,p is the total mass of water in the heating network node p; m S,k is the quality of water in the heating network port pipe k; T S,p is the water temperature in the heating network node p; T S,out,k Indicates the outlet water temperature of heating network branch k; Ω K,p is the set of all heating network pipes flowing into the heating network node p; Ω P It is a collection of heating network nodes.

[0103] The calculation formula for the carbon density of heating network nodes is:

[0104]

[0105] Among them, ρ NHS,p is the node carbon density of heating network node p; R NHS,p is the node carbon flow rate of the heating network node p; c represents the specific heat capacity of water, which is 4.2×10 3 J / (kg·℃); ρ BHS , k represents the branch carbon density of the heating network port pipeline k; T S,Loss,k Represents the loss temperature of heating network branch k.

[0106] Similarly, the carbon density of the return network node is:

[0107]

[0108] Among them, ρ NHR,p is the node carbon density of the backwater network node p; R NHR,p is the node carbon flow rate of the backwater network node p; m R,p is the total mass of water in the return network node p; T R,p is the water temperature in the return network node p; ρ BHR,k represents the branch carbon density of the return network port pipe k; m R,k is the quality of water in the return network port pipe k; T R,out,k , T R,Loss,k They represent the outlet water temperature and loss temperature of return network branch k respectively.

[0109] By inputting the output energy of the heat supply source of the heat network, the quality and temperature of the water in the heat network pipeline, and the energy required for the heat load, the carbon density and carbon flow rate information of each node in the heat network can be calculated.

[0110] 2013: Multi-energy carbon flow model in energy conversion;

[0111] The basis for establishing the multi-energy carbon flow model in the energy conversion process is EH (energy hub) modeling, which specifically models the single input process in energy conversion to generate an energy conversion model with multi-port energy input and multi-port energy output.

[0112] For energy hubs, the following relationships can be established:

[0113] V out =CV in (12)

[0114] Among them, V out represents the energy output vector; V in represents the energy input vector; C is the energy coupling matrix, which represents the relationship between the energy input vector and the energy output vector of the energy hub.

[0115] According to formula (12), the following relationship is established to describe the carbon density at the port:

[0116] ρ out =Dρ in (13)

[0117]

[0118] Among them, the matrix ρ out is the output carbon density coupling matrix, matrix ρi n is the input carbon density coupling matrix, matrix D is the carbon flow coupling matrix, and the coupling between each output port and the input port is calculated through the matrix element d ij By coupling the energy flow of the input port and its corresponding carbon density carbon flow coupling matrix, the carbon flow rate and carbon density output by the energy flow hub can be calculated.

[0119] 202: Multi-energy carbon flow calculation in industrial parks;

[0120] First, it is necessary to clarify the specific data of energy flow and carbon emissions required for multi-energy carbon flow calculation, sort out the calculation objectives in multi-energy carbon flow calculation, and the known contents and unrequired contents of multi-energy carbon flow calculation are shown in Table 2:

[0121] Table 2 Known and unresolved content of multi-energy carbon flow meter

[0122]

[0123]

[0124] Among them, the multi-energy network topology infrastructure of the industrial park is composed of a series of network connections and nodes. These connections represent the paths of energy transmission, mainly including: power transmission lines, urban centralized heating system pipelines, and gas transmission pipelines. The nodes represent various key interfaces in the energy system, including input nodes (energy entry points), load nodes (energy consumption points), energy storage nodes (energy storage facilities), and energy conversion nodes (such as substations or cogeneration plants). According to Table 2, the goal of multi-energy carbon flow calculation is to obtain the carbon density of nodes and branches of each network and to grasp the energy and carbon emissions of each link.

[0125] The multi-energy carbon flow calculation model established in 201 can be applied to two types of parks: industrial park clusters and industrial parks. First, it is necessary to determine the type of industrial park. The industrial park cluster consists of an electricity network and a gas network, which connect industrial parks in different regions and realize long-distance energy transmission. The interior of the industrial park can be modeled as multiple energy hubs, and the heat output of each energy hub is transmitted to the heat load through the heating network. For industrial park clusters, the carbon flow of the electric-gas coupling network in the industrial park cluster, the carbon flow of the energy hub, and the carbon flow of the heating network inside the industrial park can be calculated in turn.

[0126] The main steps for calculating the energy carbon flow of industrial park clusters are as follows:

[0127] 1) Obtain the energy flow results of the industrial park, including: power grid flow, gas grid air flow, and heat grid heat flow.

[0128] 2) Calculate the carbon density and carbon flow rate of the power grid and the gas grid using the energy transmission model in step 201.

[0129] 3) Calculate the carbon flow of each energy hub using the energy conversion model in step 201. For each energy hub, the input energy comes from the power network and the gas network. Therefore, the node carbon density of each input port is equal to the node carbon density of the corresponding network node to which it is connected, which can be obtained from the carbon flow calculation result of the electric-gas coupling network in step (2).

[0130] 4) Calculate the carbon flow of each district heating network using the energy transfer model in step 201. The heat source of each district heating network is the heat output of the energy hub it is connected to. Therefore, the gas carbon density of the heat source can be obtained from the carbon flow result of the energy hub in step (3).

[0131] 203: Introducing the decentralized iterative idea, a multi-energy carbon flow calculation method suitable for large-scale industrial park networks is proposed.

[0132] The iterative multi-energy carbon flow calculation formula is as follows:

[0133]

[0134] Among them, P m→n is the energy injected by node m to node n; ρ m is the carbon density of node m; G h Energy produced in the energy production process.

[0135] like Figure 1 As shown in the figure, taking an N-node energy network as an example, the iterative method for calculating energy carbon flow first needs to set the number of iterations k, then query the energy carbon flow information of the inflow nodes of node 1 in turn from node 1 (the carbon density of the initial nodes is 0), calculate the carbon density of node 1 after finding all the inflow nodes, and then calculate the carbon density of node 2, and so on until the carbon density of node N is calculated, and all the node carbon densities in this round have been calculated. After repeating this iterative process k times, the final node carbon density will be output, and other carbon flow information such as branch carbon flow rate and load carbon flow rate can be calculated later.

[0136] Example 3

[0137] The following is a specific example. Figure 3-9 , and Tables 3-7 verify the feasibility of the solutions in Examples 1 and 2, as described below:

[0138] 301: Multi-energy system consisting of a simple 6-node gas-heat network and an improved IEEE 39-node power grid;

[0139] 3011; Obtain the energy network topology and key parameters of each energy link as known conditions for multi-energy carbon flow calculation; Among them, the key parameters of each energy link include: energy production power, energy transmission related parameters, energy load power. 39-node power grid topology structure is as follows Figure 3 As shown, the frequency is 60Hz and the base capacity is 100MVA.

[0140] The production carbon density of all power generation units in the system is known, and the specific data are shown in Table 3:

[0141] Table 3 Carbon density of power generation units

[0142]

[0143] Gas network structure Figure 4 As shown in the figure, the gas grid is supplied by two gas sources, at nodes 5 and 6 respectively. Nodes 1, 2, 3, and 4 supply gas to load L1, gas unit G2, energy hub H, and load L2 respectively. There is a compressor between nodes 1 and 2, and the carbon emissions generated by the energy consumption of the compressor are converted to the grid side. The carbon density of all nodes in the gas grid is It represents the carbon emissions generated by burning one unit of energy of natural gas, which is 0.2tCO2 / MWh.

[0144] The gas network pipeline parameters Kp are shown in Table 4:

[0145] Table 4 Pipeline parameters Kp

[0146]

[0147] Heat network structure Figure 5 As shown, the heat network is supplied by the energy hub H to nodes 1 and 2 respectively, and nodes 5 and 6 supply heat to loads L1 and L2 respectively.

[0148] Energy hub structure Figure 6 As shown in Table 5, the energy hub H has 2 input ports and 5 output ports. The input end receives energy from the power grid and gas grid, and the hub performs energy conversion inside. It consists of three energy conversion components, namely compression electrical refrigerator group (CERG), combined heat and power (CHP), and auxiliary boilers (AB). The conversion parameters of each component are shown in Table 5. The output end can output three energy forms: electricity, cold, and heat. The carbon density of the port representing the output power, represents the carbon density at the cooling port, The carbon density of the port representing the output heat energy.

[0149] Table 5 Energy hub component conversion parameters

[0150]

[0151] 3012: The multi-energy carbon flow model is further constructed based on the actual network, which is divided into energy transmission link and energy conversion link.

[0152] The energy transmission link is divided into the electricity-gas-heat network multi-energy carbon flow model, and the energy conversion link is divided into single-input and multi-input multi-energy carbon flow models.

[0153] For this energy network structure, the gas network and the heat network are simple structures with 6 nodes, and the power grid is a complex structure with 39 nodes. The specific modeling method is modeled with reference to Example 2.

[0154] 3013; Decentralized iterative calculation is performed according to the energy carbon flow calculation process of the industrial park.

[0155] For large networks, distributed computing is performed according to the iterative multi-energy carbon flow calculation formula to calculate the carbon flow information of each node.

[0156] First, the energy carbon flow information of the power grid is calculated according to the iterative method. The calculation formula is as follows:

[0157]

[0158] Among them, P m→n is the energy injected by node m to node n; ρ m is the carbon density of node m; G h Energy produced in the energy production process.

[0159] Input the grid-related parameters in step 3011, specifically the grid topology, the carbon density of the generator set, and the power flow results of 39 nodes. Use the iterative method to solve the carbon density of each node, and the initial node carbon density value is set to 0tCO2 / MWh.

[0160] Combining the calculation results of node carbon density and the 39-node power grid flow, the carbon flow rate of each branch can be obtained. The carbon flow rate at the beginning is 1953.618tCO2 / h, the carbon flow rate at the end is 1978.686tCO2 / h, the carbon flow rate at the network loss is 25.068tCO2 / h, and the energy carbon flow calculation is conservative.

[0161] Next, calculate the energy carbon flow information of the gas grid. The calculation formula is as follows:

[0162]

[0163] Among them, R b is the carbon flow rate of the gas network pipeline; f b represents the gas flow rate in pipe b, f w Indicates the gas flow rate of the fuel gas source w, in km 3 / h;Ω B,g ,Ω GS,g They represent the set of pipelines flowing into node g and the set of gas sources w on node g respectively; ρ GGS,w It represents the carbon emissions generated by burning one unit of energy of natural gas; B is the calorific value of natural gas, which is 10.45MWh / km 3 .

[0164] Input the gas network related parameters in step 3011, specifically the gas network topology, pipeline parameters, gas network airflow, and calculate the gas network energy carbon flow distribution as follows: Figure 7 shown.

[0165] The carbon flows injected into the gas grid are 558.61tCO2 / h and 428.45tCO2 / h, respectively, totaling 987.06tCO2 / h. The carbon flows out of the gas supply are 313.5tCO2 / h, 313.5tCO2 / h, 207tCO2 / h, and 142.8tCO2 / h, respectively, with a loss of 10.26tCO2 / h, totaling 987.06tCO2 / h. The carbon flow injected into the gas grid is equal to the total carbon flow out, and the energy carbon flow of the gas grid is conserved.

[0166] Next, calculate the energy carbon flow information of the energy hub, the calculation formula is as follows:

[0167]

[0168] Among them, the matrix ρ out is the output carbon density coupling matrix, matrix ρi n is the input carbon density coupling matrix, matrix D is the carbon flow coupling matrix, and the coupling between each output port and the input port is calculated through the matrix element d ij By coupling the energy flow of the input port and its corresponding carbon density carbon flow coupling matrix, the carbon flow rate and carbon density output by the energy flow hub can be calculated.

[0169] Input the energy hub related parameters in step 3011, specifically the energy hub structure diagram, energy hub energy conversion parameters, and energy hub energy flow results, and calculate the energy hub energy carbon flow distribution as follows: Figure 8 shown.

[0170] The carbon flows injected into the energy hub are 189.40tCO2 / h and 207tCO2 / h, respectively, totaling 396.40tCO2 / h. The outflowing carbon flows are 135.29tCO2 / h, 160.14tCO2 / h, 32.34tCO2 / h, 35.56tCO2 / h, and 33.07tCO2 / h, respectively, totaling 396.40tCO2 / h. The inflowing carbon flow is equal to the outflowing carbon flow, and the calculation results of the energy carbon flow of the energy hub are conserved. In addition, the port carbon density of each output port is as follows (unit: tCO2 / MWh):

[0171]

[0172] Finally, the energy carbon flow information of the heat network is calculated using the following formula:

[0173]

[0174] Among them, ρ NHS,p is the node carbon density of heating network node p; R NHS,p is the node carbon flow rate of the heating network node p; c represents the specific heat capacity of water, which is 4.2×10 3J / (kg·℃);m S , p is the total mass of water in the heating network node p; T S , p is the water temperature in the heating network node p; ρ BHS,k represents the branch carbon density of the heating network port pipeline k; m S,k is the quality of water in the heating network port pipe k; T S,out,k represents the outlet water temperature of heating network branch k; T S,Loss,k represents the loss temperature of heating network branch k; ρ NHR,p is the node carbon density of the backwater network node p; R NHR,p is the node carbon flow rate of the backwater network node p; m R,p is the total mass of water in the return network node p; T R,p is the water temperature in the return network node p; ρ BHR,k represents the branch carbon density of the return network port pipe k; m R,k is the quality of water in the return network port pipe k; T R,out,k , T R,Loss,k Respectively represent the outlet water temperature and loss temperature of return network branch k; Ω K,p is the set of all heating network pipes flowing into the heating network node p; Ω P It is a collection of heating network nodes.

[0175] Input the relevant parameters of the heating network in step 3011, specifically the heating network topology diagram and the energy flow results of the heating network, and calculate the carbon flow distribution of the heating network energy. Fig. 9 shown.

[0176] The carbon flows into the heat network are 35.56tCO2 / h and 33.07tCO2 / h, respectively, and the total carbon flows into the heat network are 68.63tCO2 / h. The carbon flows out of the heat network are 28.97tCO2 / h and 24.7tCO2 / h, respectively, the carbon flow caused by energy loss is 14.96tCO2 / h, and the total carbon flow out of the heat network is 68.63tCO2 / h. The carbon flow into the heat network is equal to the total carbon flow out of the heat network, and the calculation result of the energy carbon flow of the heat network is conserved.

[0177] At this point, the energy carbon flows of the power grid, gas grid, energy hub, and heat grid have been calculated in turn, and the calculation results all conform to the law that the incoming carbon flow is equal to the outgoing carbon flow, that is, the law of conservation of carbon flow.

[0178] The energy carbon flow calculations for the simple 6-node gas-heat network and the improved IEEE39-node power grid have been completed, and the energy carbon flow information for each node in the system has been calculated.

[0179] 302: Multi-energy carbon flow monitoring method The multi-energy carbon flow monitoring method uses the iterative calculation method of the multi-energy carbon flow in the industrial park as the core algorithm. According to the characteristics of calculating the energy carbon flow information in 301, the carbon flow information of each node in the energy network is only related to the energy flow and carbon flow related data of its adjacent nodes. Each node in the monitored energy network can perform iterative calculations locally based on the energy flow and carbon flow related data of its adjacent nodes to obtain the energy flow and carbon flow data of the node, which can greatly save monitoring time. The multi-energy carbon flow monitoring method is as follows: Fig.10 shown.

[0180] First, the lower-level carbon meter needs to obtain the energy flow data of the monitored branch. Subsequently, the upper-level carbon meter will send the relevant information of the branches they monitor (including carbon density and energy flow data) to the lower-level carbon meter. After the lower-level carbon meter receives this data, it will use the calculation formula given in the energy carbon flow calculation model to perform local iterative operations to calculate the branch carbon density, node carbon density and other related information. After completing this calculation, the lower-level carbon meter needs to pass the calculated carbon density and energy flow information to the lower-level carbon meter. By iterating in this way, the calculation of relevant energy flow and carbon emissions of each node in the energy network can be completed. During the monitoring process, each node communicates with each other through the adjacent connection characteristics of the energy network nodes to exchange their respective relevant energy carbon flow data. Each node uses the energy carbon flow calculation formula based on the iterative algorithm to calculate its own carbon emission data. This process is iterated continuously, and the carbon emission information on the demand side can be determined in the end, where the required input data includes the energy output information and carbon information of the unit. During each iteration, the energy flow and carbon flow information is transmitted along the direction of the energy flow, which is equivalent to simulating the flow of carbon emissions from the energy source to the consumer along the energy flow path. While realizing the energy carbon flow monitoring function, it also shows the dynamic change characteristics of carbon flow in the energy network. In addition, energy carbon flow monitoring based on iterative algorithms can realize local decentralized computing, greatly saving the computing power and storage resources of data centers and shortening the overall monitoring time.

[0181] The multi-energy iterative carbon flow calculation and monitoring method suitable for large-scale energy networks that adopts a decentralized concept proposed in an embodiment of the present invention has the advantages of being fast, accurate, and saving computing power. It lays the foundation for specific low-carbon analysis applications such as low-carbon path planning, carbon emission forecasting, and carbon quota allocation, and promotes the development of industrial parks in an efficient, clean, and sustainable direction.

[0182] Example 4

[0183] A monitoring device for multi-energy carbon flow emissions suitable for industrial parks, the device comprising:

[0184] Establish a model to combine the carbon emission characteristics of each link of the energy network and establish a multi-energy carbon flow model for the entire source-grid-load link from the two links of energy transmission and energy conversion;

[0185] The calculation module is used to combine the characteristics of various energy sources and provide the basic process of multi-energy carbon flow calculation in industrial parks;

[0186] The output module is used to query the energy carbon flow information of all nodes flowing into the current node based on the multi-energy carbon flow model and the basic process of multi-energy carbon flow calculation in the industrial park, combined with the decentralized iteration idea, until the energy carbon flow information of the node is calculated, and when the preset number of iterations is reached, the global energy carbon flow information is output;

[0187] The monitoring module is used to monitor the multi-energy carbon flow of the industrial park based on the global energy carbon flow information and combined with the characteristics of the global energy carbon flow information.

[0188] Among them, the multi-energy carbon flow model is divided into two parts: energy transmission and energy conversion.

[0189] The multi-energy carbon flow model in the energy transmission link is divided into power grid, heat grid and gas grid models, as follows:

[0190]

[0191] Among them, ρ N,n represents the node carbon density; P l represents the active power of branch l; ρ B,l represents the branch carbon density of energy transmission line l; G h represents the active power injected by the energy production end h; ρ G,h represents the production carbon density of energy production end h; Ω G,n Represents the set of energy production terminals connected to the node; Ω L,n Represents the set of all branches flowing into the node; Ω N Represents a collection of nodes in the energy transmission network;

[0192] The multi-energy carbon flow model in the energy conversion link is as follows:

[0193] ρ out =Dρ in

[0194]

[0195] Among them, the matrix ρ out is the output carbon density coupling matrix, matrix ρi n is the input carbon density coupling matrix, matrix D is the carbon flow coupling matrix, and the coupling between each output port and the input port is calculated through the matrix element d ij By coupling the energy flow of the input port and its corresponding carbon density carbon flow coupling matrix, the carbon flow rate and carbon density output by the energy flow hub can be calculated.

[0196] The calculation module includes:

[0197] The acquisition submodule is used to obtain the energy flow results of the industrial park, including: power grid flow, gas grid air flow, and heat grid heat flow; the carbon density and carbon flow rate of the power grid and gas grid are calculated using the energy transmission model;

[0198] A calculation submodule, for calculating the carbon flow of each energy hub using an energy conversion model, and for each energy hub, the input energy comes from the electricity network and the gas network;

[0199] The output submodule is used to calculate the carbon flow of each district heating network using the energy transfer model. The heat source of each district heating network is the heat output of the connected energy hub.

[0200] In summary, the embodiments of the present invention achieve accurate and reliable real-time carbon emission calculation and monitoring of the industrial park energy system, thereby improving the atmospheric environment.

[0201] Example 5

[0202] A monitoring device for multi-energy carbon flow emissions suitable for industrial parks, the device comprising: a processor and a memory, the memory storing program instructions, the processor calling the program instructions stored in the memory to enable the device to execute the following method steps in Example 1:

[0203] Establish a multi-energy carbon flow model for the entire source-grid-load link; combine the characteristics of various energy sources to judge the type of industrial park and provide the basic process for calculating the multi-energy carbon flow of industrial parks;

[0204] Introducing the idea of ​​decentralized iteration, based on the multi-energy carbon flow model and the basic process of multi-energy carbon flow calculation in industrial parks, a multi-energy carbon flow calculation suitable for large-scale networks is proposed. Each node only uses the energy carbon flow data of the node related to it for a single calculation, and the global energy carbon flow information is finally calculated through continuous iteration.

[0205] Based on the global energy carbon flow information and combined with the characteristics of global energy carbon flow information, the multi-energy carbon flow of industrial parks is monitored.

[0206] Among them, the multi-energy carbon flow model is divided into two parts: energy transmission and energy conversion.

[0207] The multi-energy carbon flow model in the energy transmission link is divided into power grid, heat grid and gas grid models, as follows:

[0208]

[0209] Among them, ρ N,n represents the node carbon density; P l represents the active power of branch l; ρ B,lrepresents the branch carbon density of energy transmission line l; G h represents the active power injected by the energy production end h; ρ G,h represents the production carbon density of energy production end h; Ω G,n Represents the set of energy production terminals connected to the node; Ω L,n Represents the set of all branches flowing into the node; Ω N Represents a collection of nodes in the energy transmission network;

[0210] The multi-energy carbon flow model in the energy conversion link is as follows:

[0211] ρ out =Dρ in

[0212]

[0213] Among them, the matrix ρ out is the output carbon density coupling matrix, matrix ρi n is the input carbon density coupling matrix, matrix D is the carbon flow coupling matrix, and the coupling between each output port and the input port is calculated through the matrix element d ij By coupling the energy flow of the input port and its corresponding carbon density carbon flow coupling matrix, the carbon flow rate and carbon density output by the energy flow hub can be calculated.

[0214] Among them, the basic process of multi-energy carbon flow calculation in industrial parks is:

[0215] Obtain energy flow results for the industrial park, including power grid flow, gas grid air flow, and heat grid heat flow; use energy transmission models to calculate the carbon density and carbon flow rate of the power grid and gas grid;

[0216] The energy conversion model is used to calculate the carbon flow of each energy hub. For each energy hub, the input energy comes from the electricity network and the gas network. The energy transmission model is used to calculate the carbon flow of each regional heating network. The heat source of each regional heating network is the heat output of the connected energy hub.

[0217] Among them, the multi-energy carbon flow is calculated as:

[0218]

[0219] Among them, P m→n is the energy injected by node m to node n; ρ m is the carbon density of node m; G h Energy produced in the energy production process.

[0220] It should be pointed out here that the device description in the above embodiment corresponds to the method description in the embodiment, and the embodiment of the present invention will not be described in detail here.

[0221] The execution subjects of the above-mentioned processor and memory can be devices with computing functions such as computers, single-chip microcomputers, and microcontrollers. In specific implementation, the embodiments of the present invention do not limit the execution subjects and are selected according to the needs of actual applications.

[0222] The data signal is transmitted between the memory and the processor via a bus, which is not described in detail in the embodiment of the present invention.

[0223] Based on the same inventive concept, an embodiment of the present invention further provides a computer-readable storage medium, the storage medium includes a stored program, and when the program is running, the device where the storage medium is located is controlled to execute the method steps in the above embodiment.

[0224] The computer-readable storage medium includes but is not limited to a flash memory, a hard disk, a solid-state drive, and the like.

[0225] It should be pointed out here that the description of the readable storage medium in the above embodiment corresponds to the description of the method in the embodiment, and the embodiment of the present invention will not be described in detail here.

[0226] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions according to the embodiments of the present invention are generated.

[0227] The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions may be stored in a computer-readable storage medium or transmitted via a computer-readable storage medium. The computer-readable storage medium may be any available medium that can be accessed by the computer or a data storage device such as a server or a data center that includes one or more available media. The available medium may be a magnetic medium or a semiconductor medium, etc.

[0228] Unless otherwise specified, the models of the components in the embodiments of the present invention are not limited, and any device that can perform the above functions may be used.

[0229] Those skilled in the art will appreciate that the accompanying drawing is only a schematic diagram of a preferred embodiment, and the serial numbers of the embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0230] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A monitoring method for multi-energy carbon flow emissions suitable for industrial parks, characterized in that: The method comprises: Combined with the carbon emission characteristics of each link of the energy network, a multi-energy carbon flow model of the source-grid-load link is established from the two links of energy transmission and energy conversion; combined with the characteristics of various energy sources, the basic process of multi-energy carbon flow calculation in industrial parks is given; Based on the multi-energy carbon flow model and the basic process of multi-energy carbon flow calculation in industrial parks, combined with the decentralized iteration idea, query the energy carbon flow information of all nodes flowing into the current node until the energy carbon flow information of the node is calculated. When the preset number of iterations is reached, the global energy carbon flow information is output; Based on the global energy carbon flow information and combined with the characteristics of global energy carbon flow information, the multi-energy carbon flow of industrial parks is monitored.

2. A method for monitoring multi-energy carbon flow emissions suitable for industrial parks according to claim 1, characterized in that: The multi-energy carbon flow model is divided into two parts: energy transmission and energy conversion. The multi-energy carbon flow model in the energy transmission link is divided into power grid, heat grid and gas grid models, as follows: Among them, ρ N,n represents the node carbon density; P l represents the active power of branch l; ρ B,l represents the branch carbon density of energy transmission line l; G h represents the active power injected by the energy production end h; ρ G,h represents the production carbon density of energy production end h; Ω G,n Represents the set of energy production terminals connected to the node; Ω L,n Represents the set of all branches flowing into the node; Ω N Represents a collection of nodes in the energy transmission network; The multi-energy carbon flow model in the energy conversion link is as follows: r out =Dρ in Among them, the matrix ρ out is the output carbon density coupling matrix, matrix ρi n is the input carbon density coupling matrix, matrix D is the carbon flow coupling matrix, and the coupling between each output port and the input port is calculated through the matrix element d ij By coupling the energy flow of the input port and its corresponding carbon density carbon flow coupling matrix, the carbon flow rate and carbon density output by the energy flow hub can be calculated.

3. A method for monitoring multi-energy carbon flow emissions suitable for industrial parks according to claim 1, characterized in that: The basic process of calculating the multi-energy carbon flow in the industrial park is as follows: Obtain energy flow results for the industrial park, including power grid flow, gas grid air flow, and heat grid heat flow; use energy transmission models to calculate the carbon density and carbon flow rate of the power grid and gas grid; The energy conversion model is used to calculate the carbon flow of each energy hub. For each energy hub, the input energy comes from the electricity network and the gas network. The energy transmission model is used to calculate the carbon flow of each regional heating network. The heat source of each regional heating network is the heat output of the connected energy hub.

4. The method for monitoring multi-energy carbon flow emissions applicable to industrial parks according to claim 1, characterized in that: The energy carbon flow information of the node is calculated as: Among them, P m→n is the energy injected by node m to node n; ρ m is the carbon density of node m; G h Energy produced in the energy production process.

5. A multi-energy carbon flow emission monitoring device suitable for industrial parks, characterized in that: The device comprises: Establish a model to combine the carbon emission characteristics of each link of the energy network and establish a multi-energy carbon flow model for the entire source-grid-load link from the two links of energy transmission and energy conversion; The calculation module is used to combine the characteristics of various energy sources and provide the basic process of multi-energy carbon flow calculation in industrial parks; The output module is used to query the energy carbon flow information of all nodes flowing into the current node based on the multi-energy carbon flow model and the basic process of multi-energy carbon flow calculation in the industrial park, combined with the decentralized iteration idea, until the energy carbon flow information of the node is calculated, and when the preset number of iterations is reached, the global energy carbon flow information is output; The monitoring module is used to monitor the multi-energy carbon flow of the industrial park based on the global energy carbon flow information and combined with the characteristics of the global energy carbon flow information.

6. A multi-energy carbon flow emission monitoring device suitable for industrial parks according to claim 5, characterized in that: The multi-energy carbon flow model is divided into two parts: energy transmission and energy conversion. The multi-energy carbon flow model in the energy transmission link is divided into power grid, heat grid and gas grid models, as follows: Among them, ρ N,n represents the node carbon density; P l represents the active power of branch l; ρ B,l represents the branch carbon density of energy transmission line l; G h represents the active power injected by the energy production end h; ρ G,h represents the production carbon density of energy production end h; Ω G,n Represents the set of energy production terminals connected to the node; Ω L,n Represents the set of all branches flowing into the node; Ω N Represents a collection of nodes in the energy transmission network; The multi-energy carbon flow model in the energy conversion link is as follows: r out =Dρ in Among them, the matrix ρ out is the output carbon density coupling matrix, matrix ρi n is the input carbon density coupling matrix, matrix D is the carbon flow coupling matrix, and the coupling between each output port and the input port is calculated through the matrix element d ij By coupling the energy flow of the input port and its corresponding carbon density carbon flow coupling matrix, the carbon flow rate and carbon density output by the energy flow hub can be calculated.

7. A multi-energy carbon flow emission monitoring device suitable for industrial parks according to claim 5, characterized in that: The calculation module comprises: The acquisition submodule is used to obtain the energy flow results of the industrial park, including: power grid flow, gas grid air flow, and heat grid heat flow; the carbon density and carbon flow rate of the power grid and gas grid are calculated using the energy transmission model; A calculation submodule, for calculating the carbon flow of each energy hub using an energy conversion model, and for each energy hub, the input energy comes from the electricity network and the gas network; The output submodule is used to calculate the carbon flow of each district heating network using the energy transfer model. The heat source of each district heating network is the heat output of the connected energy hub.

8. A multi-energy carbon flow emission monitoring device suitable for industrial parks, characterized in that: The device comprises: a processor and a memory, wherein program instructions are stored in the memory, and the processor calls the program instructions stored in the memory to enable the device to execute the method according to any one of claims 1 to 4.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is enabled to perform the method according to any one of claims 1 to 4.

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