Carbon meter configuration scheme optimization method and device, medium and equipment

Abstract

The invention discloses a carbon meter configuration scheme optimization method and device, a medium and equipment. The method comprises the following steps: constructing a first configuration model about cost; based on the first configuration model, determining an initial carbon meter configuration scheme by using a pre-constructed carbon meter position constraint condition, a pre-constructed complete metering demand constraint condition and a pre-constructed non-redundancy metering constraint condition; constructing a second configuration model related to the total metering error of the carbon emission factors; and based on the second configuration model and a pre-constructed minimum carbon table number constraint condition, optimizing the initial carbon table configuration scheme to obtain a target carbon table configuration scheme. According to the invention, the layout setting of the carbon meter can be reasonably and accurately determined.

Description

Technical Field

[0001] The present invention relates to the field of carbon emission measurement, and particularly to an optimization method, device, medium and equipment for a carbon meter configuration scheme. Background Art

[0002] The power carbon meter system is an important carrier for realizing real-time and accurate electricity carbon measurement. The power carbon meter system mainly consists of carbon meters, an electricity-carbon platform and a communication link that are dispersedly arranged throughout the network. The carbon meter calculates the direct carbon emissions generated on the power generation side through methods such as flue gas monitoring or real-time coal consumption measurement; on the grid side and the load side, the carbon meter device is realized by installing a carbon measurement chip in the smart meter.

[0003] However, at present, the layout settings of each carbon meter in the power carbon meter system are not reasonable and accurate enough, which in turn leads to inaccurate and unreliable carbon emission data detection results.

[0004] Therefore, there is an urgent need for an optimization method for the carbon meter configuration scheme to reasonably and accurately determine the installation positions of carbon meters in the power system. Summary of the Invention

[0005] In view of this, the present invention provides an optimization method, device, medium and equipment for a carbon meter configuration scheme, mainly aiming to solve the problem that the current layout settings of each carbon meter are not reasonable and accurate enough.

[0006] To solve the above problems, the present application provides an optimization method for a carbon meter configuration scheme, including:

[0007] Construct a first configuration model regarding cost;

[0008] Based on the first configuration model, use the pre-constructed carbon meter position constraint conditions, the pre-constructed complete measurement requirement constraint conditions, and the pre-constructed non-redundant measurement constraint conditions to determine an initial carbon meter configuration scheme;

[0009] Construct a second configuration model regarding the total measurement error of carbon emission factors;

[0010] Based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint conditions, optimize the initial carbon meter configuration scheme to obtain a target carbon meter configuration scheme.

[0011] Optionally, the construction of the first configuration model regarding cost specifically includes:

[0012] Determine the first cost of the grid-side carbon meter, the second cost of the source-side carbon meter, and the third cost of the load-side carbon meter;

[0013] Based on the first cost, the second cost, and the third cost, construct the first configuration model.

[0014] Optionally, determining the first cost of the grid-side carbon meter, the second cost of the source-side carbon meter, and the third cost of the load-side carbon meter specifically includes:

[0015] For each first node with a configurable grid-side carbon meter in the power system, determine the first cost according to each of the first nodes and the unit price of the grid-side carbon meter;

[0016] For each second node with a configurable source-side carbon meter in the power system, determine the second cost according to each of the second nodes and the unit price of the source-side carbon meter;

[0017] For each third node with a configurable load-side carbon meter in the power system, determine the third cost according to each of the third nodes and the unit price of the load-side carbon meter.

[0018] Optionally, constructing the second configuration model for the total measurement error of carbon emission factors specifically includes:

[0019] Based on the initial carbon meter configuration scheme, determine the theoretical values of the initial carbon emission factors for each node in the power system;

[0020] Based on the theoretical values of the initial carbon emission factors and the actual measured values of the carbon emission factors, construct the second configuration model.

[0021] Optionally, based on the initial carbon meter configuration scheme, determining the theoretical values of the initial carbon emission factors for each node in the power system specifically includes:

[0022] Based on the actual power of the loads connected to each node and the actual power of the generator sets connected to each node, calculate the actual power of each branch corresponding to each node;

[0023] Based on the actual power of each branch corresponding to each node, the carbon emission factors of the generator sets connected to each node, the carbon flow density of each branch, the actual power of the loads connected to each node, and the actual power of the generator sets connected to each node, calculate the theoretical values of the initial carbon emission factors for each node.

[0024] Optionally, the carbon meter configuration scheme optimization method further includes: pre-constructing carbon meter position constraint conditions, complete measurement requirement constraint conditions, non-redundant measurement constraint conditions, and minimum carbon meter quantity constraint conditions, specifically including:

[0025] Based on the positions of the generator sets in the power system, the positions of the loads, and whether there is a line between any two nodes, construct the carbon meter position constraint conditions;

[0026] Based on the number of branches, the number of loads, the number of generator sets, and the number of nodes in the power system, construct the complete measurement requirement constraint conditions;

[0027] Construct the non-redundant metering constraint conditions based on the binary variables of whether to arrange grid-side carbon meters, whether to arrange source-side carbon meters, whether to arrange load-side carbon meters, the binary coefficients of generator set connection relationships, the binary coefficients of branch connection relationships, and the binary coefficients of load connection relationships;

[0028] Construct the minimum carbon meter quantity constraint conditions based on the quantity of grid-side carbon meters and the quantity of load-side carbon meters.

[0029] Optionally, optimizing the initial carbon meter configuration plan based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint conditions to obtain the target carbon meter configuration plan specifically includes:

[0030] Optimizing the initial carbon meter configuration plan based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint conditions to obtain the line power flow distribution matrix of each node;

[0031] Determine the theoretical value of the target carbon emission factor after optimization for each node based on the line power flow distribution matrix of each node;

[0032] Determine the target carbon meter configuration plan based on the theoretical value of the target carbon emission factor of each node.

[0033] To solve the above problems, the present application provides an optimization device for a carbon meter configuration plan, including:

[0034] A first construction module for constructing a first configuration model regarding cost;

[0035] A determination module for determining the initial carbon meter configuration plan based on the first configuration model by using the pre-constructed carbon meter position constraint conditions, the pre-constructed complete metering requirement constraint conditions, and the pre-constructed non-redundant metering constraint conditions;

[0036] A second construction module for constructing a second configuration model regarding the total metering error of carbon emission factors;

[0037] An optimization module for optimizing the initial carbon meter configuration plan based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint conditions to obtain the target carbon meter configuration plan.

[0038] To solve the above problems, the present application provides a storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the optimization method for the carbon meter configuration plan described in any one of the above are implemented.

[0039] To solve the above problems, the present application provides an electronic device, which at least includes a memory and a processor. A computer program is stored on the memory, and when the processor executes the computer program on the memory, the steps of the optimization method of the carbon meter configuration scheme described in any one of the above are implemented.

[0040] In the optimization method, device, medium and equipment of the carbon meter configuration scheme in the present application, by constructing a first configuration model regarding cost and a second configuration model regarding the total measurement error of carbon emission factors, subsequently, the current carbon meter configuration scheme / initial carbon meter configuration scheme can be determined based on the first configuration model and the corresponding constraint conditions. Furthermore, subsequently, the current carbon meter configuration scheme / initial carbon meter configuration scheme can be continuously optimized and adjusted by further combining the second configuration model and the corresponding preset conditions until the cost corresponding to the optimized carbon meter configuration scheme is the lowest and the total measurement error of carbon emission factors is the smallest, and the final optimization result can be obtained, that is, the target carbon meter configuration scheme can be obtained. It is ensured that the carbon emissions can be accurately detected even when the carbon meter configuration cost is the lowest, and the rationality and accuracy of the carbon meter layout position are ensured.

[0041] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the description. And in order to make the above and other purposes, features and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention are specifically described below. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. And throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0043] Figure 1 is a flowchart of an optimization method for a carbon meter configuration scheme according to an embodiment of the present application;

[0044] Figure 2 is a node topology diagram of the PJM5 power system in another embodiment of the present application;

[0045] Figure 3 is a measurement result error curve of the target carbon meter configuration scheme before and after network loss correction in another embodiment of the present application;

[0046] Figure 4 is a structural block diagram of an optimization device for a carbon meter configuration scheme according to another embodiment of the present application;

[0047] Figure 5 is a structural block diagram of an electronic device according to another embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] The various solutions and features of the present application are described herein with reference to the accompanying drawings.

[0049] It should be understood that various modifications can be made to the embodiments applied herein. Therefore, the above description should not be construed as limiting, but merely as an example of the embodiments. Those skilled in the art will envision other modifications within the scope and spirit of the present application.

[0050] The accompanying drawings, which are included in and form a part of this specification, illustrate embodiments of the present application and, together with the general description of the present application given above and the detailed description of the embodiments given below, serve to explain the principles of the present application.

[0051] These and other features of the present application will become apparent from the following description of the preferred forms of the embodiments, given by way of non-limiting example with reference to the accompanying drawings.

[0052] It should also be understood that, although the present application has been described with reference to some specific examples, those skilled in the art can surely implement many other equivalent forms of the present application.

[0053] When combined with the accompanying drawings, the above and other aspects, features, and advantages of the present application will become more apparent in view of the following detailed description.

[0054] Specific embodiments of the present application are hereinafter described with reference to the accompanying drawings; however, it should be understood that the embodiments applied are merely examples of the present application, which can be implemented in various ways. Well-known and / or repetitive functions and structures are not described in detail to avoid obscuring the present application with unnecessary or redundant details. Therefore, the specific structural and functional details applied herein are not intended to be limiting, but merely as a basis and representative basis for the claims to teach those skilled in the art to use the present application in substantially any suitable detailed structure in a variety of ways.

[0055] This specification may use the phrases "in one embodiment", "in another embodiment", "in yet another embodiment", or "in other embodiments", which may each refer to one or more of the same or different embodiments according to the present application.

[0056] The embodiments of the present application provide an optimization method for a carbon meter configuration solution, which can be specifically applied to electronic devices such as terminals and servers, such as Figure 1 As shown, the method in this embodiment includes the following steps:

[0057] Step S101, construct a first configuration model regarding cost;

[0058] In the specific implementation process of this step, the first cost of the grid-side carbon meter, the second cost of the source-side carbon meter, and the third cost of the load-side carbon meter can be determined first; then, based on the first cost, the second cost, and the third cost, the first configuration model is constructed.

[0059] Step S102: Based on the first configuration model, using the pre-constructed carbon meter position constraint conditions, the pre-constructed complete metering requirement constraint conditions, and the pre-constructed non-redundant metering constraint conditions, determine the initial carbon meter configuration plan;

[0060] In the specific implementation process of this step, the carbon meter position constraint conditions, the complete metering requirement constraint conditions, and the non-redundant metering constraint conditions can be pre-constructed, and these three constraint conditions are used to solve the first configuration model to obtain the initial carbon meter configuration plan / current carbon meter configuration plan.

[0061] Step S103: Construct a second configuration model for the total metering error of carbon emission factors;

[0062] In this step, specifically, the second configuration model can be constructed according to the theoretical values of the initial carbon emission factors of each node in the power system and the actual metering values of the carbon emission factors.

[0063] Step S104: Based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint conditions, optimize the initial carbon meter configuration plan to obtain the target carbon meter configuration plan.

[0064] In this step, after the second configuration model is constructed, the initial carbon meter configuration plan can be continuously optimized based on the second configuration model and the minimum carbon meter quantity constraint conditions, so as to obtain the target carbon meter configuration plan.

[0065] In the optimization method of the carbon meter configuration plan in this embodiment, by constructing the first configuration model regarding cost and the second configuration model regarding the total metering error of carbon emission factors, subsequently, the current carbon meter configuration plan / initial carbon meter configuration plan can be determined based on the first configuration model and the corresponding constraint conditions. Furthermore, subsequently, the current carbon meter configuration plan / initial carbon meter configuration plan can be continuously optimized and adjusted in combination with the second configuration model and the corresponding preset conditions until the cost corresponding to the optimized carbon meter configuration plan is minimized and the total metering error of the carbon emission factors is minimized, and the final optimization result can be obtained, that is, the target carbon meter configuration plan is obtained. It ensures that the carbon emissions can be accurately detected with the lowest carbon meter configuration cost, and ensures the rationality and accuracy of the carbon meter layout position.

[0066] Based on the above embodiments, another embodiment of the present application provides an optimization method for a carbon meter configuration plan, which specifically includes the following steps:

[0067] Step S201: Determine the first cost of the grid-side carbon meter, the second cost of the source-side carbon meter, and the third cost of the load-side carbon meter;

[0068] In this step, for each first node in the power system where a grid-side carbon meter can be configured, based on each of the first nodes and the unit price of the grid-side carbon meter, determine the first cost; similarly, for each second node in the power system where a source-side carbon meter can be configured, based on each of the second nodes and the unit price of the source-side carbon meter, determine the second cost; similarly, for each third node in the power system where a load-side carbon meter can be configured, based on each of the third nodes and the unit price of the load-side carbon meter, determine the third cost.

[0069] Step S202: Based on the first cost, the second cost, and the third cost, construct the first configuration model;

[0070] In this step, after determining the first cost, the second cost, and the third cost, a first configuration model regarding cost can be constructed. The first configuration model is:

[0071]

[0072] In Equation (1): B is the set of first nodes in the power system where a grid-side carbon meter can be configured, i.e., the branch node set; G is the set of second nodes in the power system where a source-side carbon meter can be configured, i.e., the unit node set; D is the set of third nodes in the power system where a source-side carbon meter can be configured, i.e., the load node set; u ij , u ig and u id are binary variables indicating whether the grid-side carbon meter ij, the source-side carbon meter id, and the load-side carbon meter ig are arranged respectively; c ij , c ig and c id are the configuration costs / configuration unit prices corresponding to the grid-side carbon meter, the source-side carbon meter, and the load-side carbon meter respectively. For the grid-side carbon meter ij, u ij = 0 indicates that no grid-side spare carbon meter is arranged on the i side of the branch ij, or there is no branch connecting nodes i and j; u ij = 1 indicates that a grid-side spare carbon meter is arranged on the i side of the branch ij; similarly, u ig = u id = 0 indicates that no spare carbon meter is configured for the corresponding unit and load or not at node i, u ig = u id = 1 indicates that a spare carbon meter is configured.

[0073] Step S203: Pre-construct the carbon meter position constraint conditions, the complete metering requirement constraint conditions, and the non-redundant metering constraint conditions;

[0074] In this step, the carbon meter position constraint is used to ensure that: only when the unit g is at node i, can the source-side carbon meter be configured at the corresponding position; only when there is a line between branches ij, can the network-side spare carbon meter be configured at both ends of the line; only when the load d is at node i, can the load-side carbon meter be configured at the corresponding position. That is, the carbon meter position constraint can be constructed based on the positions of each generator set, each load, and whether there is a line between any two nodes in the power system, as shown in formula (2);

[0075] u ig L ge,ig ≥u ij

[0076] u ig L line,ij ≥u ij

[0077] u id L load,id ≥u id (2)

[0078] In formula (2): L ge,ig 、L line,ij and L load,id are binary coefficients reflecting the connection relationships of the unit, branch, and load respectively.

[0079] The complete metering demand constraint is used to ensure that the layout plan of the spare carbon meter can achieve the metering of carbon emission information at all points in all links of the power system without considering network loss errors. That is, the complete metering demand constraint can be constructed based on the number of branches N L 、the number of loads, the number of generator sets N G and the number of nodes N B in the power system, as shown in formulas (3) and (4).

[0080]

[0081]

[0082] In formulas (3) and (4): N L is the number of branches in the system; N D is the number of loads in the system; N G is the number of generator sets in the system; N B is the number of nodes in the system.

[0083] The non-redundant metering constraint is used to ensure that the number of carbon meters arranged is as small as possible. That is, based on the binary variables of whether to arrange network-side carbon meters, whether to arrange source-side carbon meters, whether to arrange load-side carbon meters, the binary coefficients of generator set connection relationships, the binary coefficients of branch connection relationships, and the binary coefficients of load connection relationships, the non-redundant metering constraint is constructed. This constraint is expressed as shown in Equations (5) and (6).

[0084] u ij +u ji ≤1 (5)

[0085]

[0086] In Equations (5) and (6), u ij is the binary variable of whether to arrange network-side carbon meters; u ig is the binary variable of whether to arrange source-side carbon meters; u id is the binary variable of whether to arrange load-side carbon meters; L ge，ig is the binary coefficient of the generator set connection relationship; L line，ij is the binary coefficient of the branch connection relationship; L load，id is the binary coefficient of the load connection relationship.

[0087] Step S204: Based on the first configuration model, use the pre-constructed carbon meter position constraint, the pre-constructed complete metering requirement constraint, and the pre-constructed non-redundant metering constraint to determine the initial carbon meter configuration plan;

[0088] In this step, after constructing the first configuration model and the corresponding constraints, the initial carbon meter configuration plan / current carbon meter configuration plan can be obtained by jointly solving based on the above Formulas (1)-(6).

[0089] Step S205: Based on the initial carbon meter configuration plan, determine the theoretical value of the initial carbon emission factor of each node in the power system; based on the theoretical value of the initial carbon emission factor and the actual measured value of the carbon emission factor, construct the second configuration model.

[0090] In the specific implementation process of this step, the process of constructing the second configuration model is as follows:

[0091] Step 1: Based on the actual power of the loads connected to each node and the actual power of the generator sets connected to each node, calculate the actual power of each branch corresponding to each node;

[0092]

[0093] In Equation (7), P ij =-Pji ; p ij is the actual power of branch ij corresponding to the node; is the actual power of the load connected to the node; p ik is the actual power of branch ik; is the actual power of the generator set connected to the node.

[0094] In this embodiment, solving equation (7) can obtain the magnitude and direction of the active power flow at the endpoints of each branch, and further obtain the indirect carbon emissions of each node. Among them, for the entire power system, equation (7) expands to a total of N B + N L ones, and when solving the magnitude and direction of the active power flow at the endpoints of each branch of the system, the total number of unknowns is 2NL for the endpoints at both ends of the branch, and N d + N G ones for the endpoints of all loads and generator sets. It is necessary to configure carbon meter measurement to reduce the number of unknowns in the equations and ensure the solvability of the linear equations in order to meet the requirements of the indirect carbon emissions of each node in the whole system. Therefore, the number of additional carbon meters on the grid side and load side needs to be at least N L + N D - N B ones, and then obtain the above constraint equation (4).

[0095] Step 2: Based on the actual power of each branch corresponding to each node, the carbon emission factor of the generator set connected to each node, the carbon flow density of each branch, the actual power of the load connected to each node, and the actual power of the generator set connected to each node, calculate and obtain the theoretical value of the initial carbon emission factor of each node;

[0096]

[0097] In equation (8), e i is the theoretical value of the initial carbon emission factor of node i; e k is the carbon flow density of the branch; is p ik the actual power of branch ik corresponding to node i; is the carbon emission factor of the generator set connected to node i; is the actual power of the generator set connected to node i; p ij is the actual power of branch ij corresponding to node i; is the actual power of the load connected to node i;

[0098] In this embodiment, the carbon meter calculates the direct carbon emissions generated on the power generation side through methods such as flue gas monitoring or real-time coal consumption metering. On the grid side and the load side, the carbon meter device is implemented by installing a carbon metering chip in the smart meter. The grid-side carbon meter is arranged at both ends of all input and output lines connected to the node. It reads the active power flow data measured by the smart meter and obtains the carbon emission factor information output by the upstream carbon meter through the communication module. After local calculation, it obtains the carbon emission factor of the node where it is located and synchronizes it to the downstream carbon meter. The load-side carbon meter outputs the indirect carbon emission data of user electricity consumption in real time according to the user load result measured by the smart meter and in combination with the carbon emission factor information input by the upstream carbon meter. According to the carbon emission flow theory, there is a certain quantitative relationship between the carbon emission flow and the active power flow at node i in the power system, as shown in the following formula.

[0099]

[0100] In formula (9): B1 and B2 are respectively the sets of node numbers corresponding to the branches flowing out of and into node i in the system; e i and are respectively the carbon emission factors of node i and the connected generator sets; p ij , and are respectively the actual powers of branch ij, the load connected to node i, and the connected generator sets.

[0101] The left side of the equal sign in formula (9) represents all the carbon flows flowing out of node i, and the right side represents all the carbon flows flowing into node i. According to formula (9), the "decentralized" carbon meter device can locally calculate the carbon emission factor of the node by obtaining the carbon emission factor magnitudes of the upstream input branches and generator sets through the communication module and simultaneously reading the branch power flow and load magnitudes measured at the node where it is located, that is, obtain the above formula (8).

[0102] Step 3: Construct the second configuration model based on the initial carbon emission factor theoretical value and the actual measured value of the carbon emission factor;

[0103] In this embodiment, the power carbon emission factor is the most important indicator for carrying out power carbon metering work. This optimization model / second configuration model aims to find a layout scheme that can minimize the metering error of the power carbon emission factor. Therefore, this model takes the minimum average absolute error of the carbon emission factor metering results on a typical day as the optimization goal, and the expression is:

[0104]

[0105] In formula (10): N T is the number of time periods on a typical day; b is the total number of nodes in the power system; T is the set of all moments within a typical day; e t，iis the measured value of the carbon emission factor at node i at time t; e' t，i is the theoretical value of the measured value of the carbon emission factor at node i at time t; e‘ t，i It is obtained by solving according to the theoretical value of the power flow data combined with the carbon emission flow theory, and can be calculated through the above formula (8).

[0106] Step S206: Optimize the initial carbon meter configuration plan based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint condition to obtain the target carbon meter configuration plan.

[0107] In this step, the minimum carbon meter quantity constraint condition can be constructed based on the quantity of grid-side carbon meters and the quantity of load-side carbon meters. The minimum carbon meter quantity constraint condition is shown in the following formula (11):

[0108]

[0109] In formula (11): n op is the minimum layout quantity of the grid side and the load side that can realize the carbon measurement function output by the minimum standby carbon meter cost determination method, that is, the minimum carbon meter layout quantity corresponding to the current carbon meter configuration plan / initial carbon meter configuration plan.

[0110] In the specific implementation process of this step, the carbon emission factor calculation constraint includes two steps. According to formula (7), the power flow information of each line is calculated under the current carbon meter placement plan / current carbon meter configuration plan, and the line power flow distribution matrix P under the current measurement result is obtained B，t This matrix is represented by P B，t = P B，ij，t If there is a branch connection between node i and node j, and the positive active power flow flowing into node j through this branch at time t is p, that is, the power flow P of branch ij at time t B，ij，t = p, P B，ij，t = 0; if the active power flow p flowing through this branch is a reverse power flow, then P B，ij，t = 0, P B,ji，t = p; in other cases, P B,ij,t = P B，ji，t = 0. The calculation process of this matrix needs to be solved by iteration.

[0111] The power flow distribution matrix is initialized from the current carbon meter placement situation / current carbon meter configuration plan where, t0 is the initial moment. Then, in combination with the "node power balance" feature, according to Equation (7), taking each node of the power system as a unit, querying and calculating each node, updating the system power flow information, and calculating the number of elements N1 that still need to be calculated. In combination with the "node power balance" and "approximate equality of power flows at both ends of the line" features, taking nodes and lines as units respectively, calculating and complementing the inflow and outflow power flow information of each node and the power flow information at both ends of each line, and updating the system power flow distribution matrix. Continuously repeat this process until all the information corresponding to P B，t is complemented.

[0112] That is, based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint condition, the initial carbon meter configuration scheme can be optimized to obtain the power flow distribution matrix P of each node line B，t ; then based on the power flow distribution matrix P of each node B，t determine the theoretical value E of the target carbon emission factor after optimization for each node B，t ; finally, based on the theoretical value of the target carbon emission factor of each node, determine the carbon meter configuration scheme.

[0113] Specifically, based on the power flow distribution matrix P of each node B，t determine the theoretical value E of the target carbon emission factor after optimization for each node B，t , and the calculation expression is as follows:

[0114]

[0115] In Equation (12): E B,t is the node carbon emission factor matrix at time t, and the elements therein are the measurement results e of the carbon emission factors of each node in the system during this period i，t ; P N，t is the node active power flux matrix at time t, and this matrix is a diagonal matrix, representing the absolute value of the active power flow into each node in the power flow direction; P B，t is the line power flow distribution matrix at time t; C G，t is the carbon emission matrix of the generator set at time t, and the elements in this matrix are determined by the measurement results of the carbon meter on the source side.

[0116] In this embodiment, by constructing a first configuration model for cost and a second configuration model for the total measurement error of carbon emission factors, the current carbon meter configuration plan / initial carbon meter configuration plan can be determined based on the first configuration model and the corresponding constraint conditions in the subsequent process. Furthermore, in the subsequent process, the current carbon meter configuration plan / initial carbon meter configuration plan can be continuously optimized and adjusted by combining the second configuration model and the corresponding preset conditions until the cost corresponding to the optimized carbon meter configuration plan is minimized and the total measurement error of carbon emission factors is minimized, so as to obtain the final optimization result, that is, to obtain the target carbon meter configuration plan. This ensures accurate detection of carbon emissions while minimizing the cost of carbon meter configuration, and ensures the rationality and accuracy of the carbon meter layout location.

[0117] Based on the above embodiment, the method in this application is verified using the PJM5 power system as shown in Figure 2 . This power system includes 5 power system nodes (B1 - B5), 4 generating units (G1 - G4), and 3 loads (D1 - D3). Among them, the first nodes where network - side carbon meters can be configured are B1 - B5. The second nodes where source - side carbon meters can be configured are G1 - G4 (i.e., B1, B3, B4, and B5). The third nodes where load - side carbon meters can be configured are D1 - D3 (i.e., B2, B3, and B4).

[0118] At a certain typical moment, the system is operating stably, and only the output power of the unit at node 1 reaches the rated maximum power. Data such as the active power at the in - line and out - line of each branch, the active power of the unit output, the load, and the carbon emission factor are measured.

[0119] For the above - mentioned power system, the population size of the discrete particle swarm algorithm is set to 20 particles, and it is iterated 200 times to output the historical optimal value and its corresponding backup carbon meter layout plan. After 100 runs, there are two optimal results output by this algorithm (the mean absolute error results are basically the same). Although there are slight differences in the carbon meter positions at the marked locations in the figure, the carbon measurement errors of each node at the typical moment of the PJM5 node system for the two layout plans are basically the same. The discrete particle swarm algorithm is used to calculate and solve the backup carbon meter layout plan that conforms to the CPLEX solution result in this power system.

[0120] As shown in Table 1, it corresponds to an optimal layout plan, that is, carbon meters are installed at nodes 1 - 5 respectively; another optimal layout plan is not shown in this embodiment. For the layout plan in Table 1, the measured mean absolute percentage error is less than 0.02%.

[0121] Table 1:

[0122]

[0123] In this embodiment, the discrete particle swarm optimization algorithm is used to solve the layout scheme of spare carbon meters that conforms to the CPLEX solution results in the power system, aiming to find the carbon meter layout scheme with the smallest cumulative measurement error within 24 hours of the selected typical day. Due to the existence of non-linear constraint conditions in the model and the adoption of the penalty function method, the discrete particle swarm optimization algorithm cannot guarantee that the global optimal solution can be found every time it is solved. When the population size is set to 2000 particles and the iteration is 20000 times, the algorithm is run 30 times in total. Among them, 23 times the output results meet the system constraint conditions and the number of meters is the minimum layout number of the spare carbon meter system, and the results are relatively valuable for reference.

[0124] In this case, the measurement errors of the carbon emission factors of each node at each moment of the typical day are shown in Table 2. It can be seen from Table 2 that for the optimal scheme of spare carbon meters obtained by the discrete particle swarm optimization algorithm, the mean absolute percentage error of the measurement of the carbon emission factors of each node in the power system of this city does not exceed 0.2% at each moment within the typical day. This shows that the system can better adapt to the impact of the carbon flow change caused by the change of the active power flow in the system on the measurement of carbon emission factors within the typical day, and can achieve relatively accurate measurement of the carbon emission factors of the whole system while minimizing the number of spare carbon meters used and the measurement error. Thus, it can be seen that the optimized layout scheme of spare carbon meters obtained by this method is effective, can meet the measurement requirements of the system, and has practical application value.

[0125] Table 2:

[0126]

[0127]

[0128] Based on the typical day operation conditions of the selected city power system in this embodiment, the calculated value of the system average line loss rate (1.20%) is used to carry out line loss correction, and explore the impact of line loss correction on the measurement error of the spare carbon meter system. The mean absolute percentage errors of the system measurement results before and after correction are as Figure 3 shown.

[0129] It can be seen from Figure 3 that after the line loss correction, the measurement errors of the spare carbon meter system are all reduced. Among them, for the scenarios with obvious measurement errors, the accuracy improvement effect of this correction method is more obvious; but for the scenarios with relatively small measurement errors, the improvement effect of this method is relatively not significant. Therefore, for the scenarios where the measurement error caused by line loss is already relatively small, it may be necessary to explore more accurate line loss estimation methods to deal with.

[0130] The carbon meter calculates energy consumption and carbon emissions by measuring active power. If the network loss is not accurately corrected, the carbon meter may underestimate or overestimate the actual energy consumption, resulting in errors in carbon emissions calculation.

[0131] Considering the redundant standby requirements of the carbon meter system in case of failure, the method in this embodiment can be applied to the determination of the standby carbon meter system. The method in this embodiment adopts a step-by-step optimization method to determine the economically optimal carbon meter quantity configuration scheme under the condition of meeting the complete carbon metering requirements of the power system. On this basis, with the goal of optimizing the measurement error of the standby carbon meter system, the optimized layout scheme of the carbon meter device is determined. The effectiveness and effect of the method in this paper are tested respectively through the actual data of the PJM5-node system and a certain city power system in China, and the effectiveness of the proposed method is verified.

[0132] Another embodiment of this application provides an optimization device for a carbon meter configuration scheme, as Figure 4 shown, including:

[0133] The first construction module 11 is used to construct a first configuration model about cost;

[0134] The determination module 12 is used to determine an initial carbon meter configuration scheme based on the first configuration model, using the pre-constructed carbon meter position constraint conditions, the pre-constructed complete metering requirement constraint conditions, and the pre-constructed non-redundant metering constraint conditions;

[0135] The second construction module 13 is used to construct a second configuration model about the total measurement error of carbon emission factors;

[0136] The optimization module 14 is used to optimize the initial carbon meter configuration scheme based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint conditions to obtain a target carbon meter configuration scheme.

[0137] In the specific implementation process of this embodiment, the first construction module specifically includes a determination unit and a construction unit. The determination unit is used to: determine the first cost of the grid-side carbon meter, the second cost of the source-side carbon meter, and the third cost of the load-side carbon meter; the construction unit is used to: construct the first configuration model based on the first cost, the second cost, and the third cost.

[0138] In the specific implementation process of this embodiment, the determination unit is specifically used to: for each first node in the power system where the grid-side carbon meter can be configured, determine the first cost according to each first node and the grid-side carbon meter unit price; for each second node in the power system where the source-side carbon meter can be configured, determine the second cost according to each second node and the source-side carbon meter unit price; for each third node in the power system where the load-side carbon meter can be configured, determine the third cost according to each third node and the load-side carbon meter unit price.

[0139] In the specific implementation process of this embodiment, the second construction module is specifically configured to: determine the theoretical value of the initial carbon emission factor of each node in the power system based on the initial carbon meter configuration scheme; construct the second configuration model based on the theoretical value of the initial carbon emission factor and the actual measured value of the carbon emission factor.

[0140] In the specific implementation process of this embodiment, the second construction module is specifically configured to: calculate the actual power of each branch corresponding to each node based on the actual power of the load connected to each node and the actual power of the generator set connected to each node; calculate the theoretical value of the initial carbon emission factor of each node based on the actual power of each branch corresponding to each node, the carbon emission factor of the generator set connected to each node, the carbon flow density of each branch, the actual power of the load connected to each node, and the actual power of the generator set connected to each node.

[0141] In the specific implementation process of this embodiment, the optimization device for the carbon meter configuration scheme further includes a constraint condition construction module, and the constraint condition construction module is specifically configured to: construct the carbon meter position constraint condition based on the positions of each generator set in the power system, the positions of each load, and whether there is a line between any two nodes; construct the complete measurement requirement constraint condition based on the number of branches, the number of loads, the number of generator sets, and the number of nodes in the power system; construct the non-redundant measurement constraint condition based on the binary variables of whether to arrange a grid-side carbon meter, whether to arrange a source-side carbon meter, whether to arrange a load-side carbon meter, the binary coefficients of the generator set connection relationship, the binary coefficients of the branch connection relationship, and the binary coefficients of the load connection relationship; construct the minimum carbon meter number constraint condition based on the number of grid-side carbon meters and the number of load-side carbon meters.

[0142] In the specific implementation process of this embodiment, the optimization module is specifically configured to: optimize the initial carbon meter configuration scheme based on the second configuration model and the pre-constructed minimum carbon meter number constraint condition to obtain the line power flow distribution matrix of each node; determine the optimized theoretical value of the target carbon emission factor of each node based on the line power flow distribution matrix of each node; determine the target carbon meter configuration scheme based on the theoretical value of the target carbon emission factor of each node.

[0143] An optimization device for a carbon meter configuration solution in this embodiment can, by constructing a first configuration model regarding cost and a second configuration model regarding the total measurement error of carbon emission factors, subsequently determine the current carbon meter configuration solution / initial carbon meter configuration solution based on the first configuration model and corresponding constraint conditions. Furthermore, the current carbon meter configuration solution / initial carbon meter configuration solution can be continuously optimized and adjusted by further combining the second configuration model and corresponding preset conditions until the cost corresponding to the optimized carbon meter configuration solution is minimized and the total measurement error of carbon emission factors is minimized, thus obtaining the final optimization result, that is, obtaining the target carbon meter configuration solution. This ensures accurate detection of carbon emissions even when the carbon meter configuration cost is the lowest, and ensures the rationality and accuracy of the carbon meter layout position.

[0144] Another embodiment of the present application provides a storage medium. The storage medium stores a computer program, and when the computer program is executed by a processor, the following method steps are implemented:

[0145] Step 1: Construct a first configuration model regarding cost;

[0146] Step 2: Based on the first configuration model, use the pre-constructed carbon meter position constraint conditions, the pre-constructed complete measurement requirement constraint conditions, and the pre-constructed non-redundant measurement constraint conditions to determine the initial carbon meter configuration solution;

[0147] Step 3: Construct a second configuration model regarding the total measurement error of carbon emission factors;

[0148] Step 4: Based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint conditions, optimize the initial carbon meter configuration solution to obtain the target carbon meter configuration solution.

[0149] For the specific implementation process of the above method steps, reference can be made to the embodiments of the optimization method of any carbon meter configuration solution above, and this embodiment will not be repeated here.

[0150] The storage medium in the present application can, by constructing a first configuration model regarding cost and a second configuration model regarding the total measurement error of carbon emission factors, subsequently determine the current carbon meter configuration solution / initial carbon meter configuration solution based on the first configuration model and corresponding constraint conditions. Furthermore, the current carbon meter configuration solution / initial carbon meter configuration solution can be continuously optimized and adjusted by further combining the second configuration model and corresponding preset conditions until the cost corresponding to the optimized carbon meter configuration solution is minimized and the total measurement error of carbon emission factors is minimized, thus obtaining the final optimization result, that is, obtaining the target carbon meter configuration solution. This ensures accurate detection of carbon emissions even when the carbon meter configuration cost is the lowest, and ensures the rationality and accuracy of the carbon meter layout position.

[0151] Another embodiment of the present application provides an electronic device, such as Figure 5 shown, at least including a memory 1 and a processor 2. A computer program is stored on the memory 1, and when the processor 2 executes the computer program on the memory 1, the following method steps are implemented:

[0152] Step 1: Construct a first configuration model regarding cost;

[0153] Step 2: Based on the first configuration model, use the pre-constructed carbon meter position constraint conditions, the pre-constructed complete measurement requirement constraint conditions, and the pre-constructed non-redundant measurement constraint conditions to determine an initial carbon meter configuration plan;

[0154] Step 3: Construct a second configuration model regarding the total measurement error of carbon emission factors;

[0155] Step 4: Based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint conditions, optimize the initial carbon meter configuration plan to obtain a target carbon meter configuration plan.

[0156] For the specific implementation process of the above method steps, reference can be made to the embodiments of the optimization method of any of the above carbon meter configuration plans, and this embodiment will not be repeated here.

[0157] In the electronic device of the present application, by constructing a first configuration model regarding cost and a second configuration model regarding the total measurement error of carbon emission factors, subsequently, the current carbon meter configuration plan / initial carbon meter configuration plan can be determined based on the first configuration model and the corresponding constraint conditions. Furthermore, the current carbon meter configuration plan / initial carbon meter configuration plan can be continuously optimized and adjusted by further combining the second configuration model and the corresponding preset conditions until the cost corresponding to the optimized carbon meter configuration plan is minimized and the total measurement error of carbon emission factors is minimized, thereby obtaining the final optimization result, that is, obtaining the target carbon meter configuration plan. This ensures accurate detection of carbon emissions while minimizing the cost of carbon meter configuration, and ensures the rationality and accuracy of the carbon meter layout position.

[0158] The above embodiments are only exemplary embodiments of the present application and are not used to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art can make various modifications or equivalent replacements within the essence and protection scope of the present application, and such modifications or equivalent replacements should also be regarded as falling within the protection scope of the present application.

Claims

1. A method for optimizing a carbon table configuration scheme, characterized in that: include: Constructing the first configuration model about cost; Based on the first configuration model, an initial carbon meter configuration plan is determined using a pre-built carbon meter location constraint, a pre-built complete metering requirement constraint, and a pre-built non-redundant metering constraint; Construct a second configuration model for the total measurement error of carbon emission factors; Based on the second configuration model and the pre-constructed minimum carbon table quantity constraint, the initial carbon table configuration scheme is optimized to obtain a target carbon table configuration scheme.

2. The method according to claim 1, characterized in that The first configuration model for cost is constructed, specifically including: Determine the first cost of the network-side carbon table, the second cost of the source-side carbon table, and the third cost of the load-side carbon table; The first configuration model is constructed based on the first cost, the second cost, and the third cost.

3. The method according to claim 2, characterized in that The determining of the first cost of the network-side carbon table, the second cost of the source-side carbon table, and the third cost of the load-side carbon table specifically includes: For each first node in the power system where a grid-side carbon meter can be configured, determining the first cost according to each first node and a grid-side carbon meter price; For each second node in the power system that can be configured with a source-measured carbon meter, determine the second cost according to each second node and a source-side carbon meter price; For each third node in the power system that can be configured with a load-side carbon meter, the third cost is determined according to each of the third nodes and the load-side carbon meter price.

4. The method according to claim 1, characterized in that The constructing of the second configuration model for the total measurement error of the carbon emission factor specifically includes: Determining the initial carbon emission factor theoretical value of each node in the power system based on the initial carbon table configuration scheme; The second configuration model is constructed based on the initial carbon emission factor theoretical value and the actual measured value of the carbon emission factor.

5. The method according to claim 4, characterized in that The determining of the initial carbon emission factor theoretical value of each node in the power system based on the initial carbon table configuration scheme specifically includes: Based on the actual power of the load connected to each node and the actual power of the generator set connected to each node, the actual power of each branch corresponding to each node is calculated; Based on the actual power of each branch corresponding to each node, the carbon emission factor of the generator set connected to each node, the carbon flow density of each branch, the actual power of the load connected to each node and the actual power of the generator set connected to each node, the theoretical value of the initial carbon emission factor of each node is calculated.

6. The method according to claim 1, characterized in that The method further includes: pre-constructing carbon meter location constraints, complete metering requirement constraints, no redundant metering constraints, and minimum carbon meter quantity constraints, specifically including: Constructing the carbon table location constraint condition based on the location of each generator set in the power system, the location of each load, and whether there is a line between any two nodes; Constructing the complete metering demand constraint condition based on the number of branches, the number of loads, the number of generator sets and the number of nodes in the power system; The non-redundant metering constraint condition is constructed based on the binary variables of whether to arrange the grid-side carbon meter, whether to arrange the source-side carbon meter, whether to arrange the load-side carbon meter, the binary coefficients of the connection relationship of the generator sets, the binary coefficients of the branch connection relationship, and the binary coefficients of the load connection relationship; The minimum carbon table quantity constraint condition is constructed based on the network side carbon table quantity and the load side carbon table quantity.

7. The method according to any one of claims 1 to 6, characterized in that: The step of optimizing the initial carbon table configuration scheme based on the second configuration model and the pre-constructed minimum carbon table quantity constraint condition to obtain a target carbon table configuration scheme specifically includes: Based on the second configuration model and the pre-constructed minimum carbon meter quantity constraint condition, the initial carbon meter configuration scheme is optimized to obtain a power flow distribution matrix of each node line; Determine the theoretical value of the target carbon emission factor after optimization of each node based on the line power flow distribution matrix of each node; The target carbon table configuration scheme is determined based on the theoretical value of the target carbon emission factor of each node.

8. A device for optimizing a carbon table configuration scheme, characterized in that: include: A first building module, used for building a first configuration model about cost; A determination module, configured to determine an initial carbon meter configuration scheme based on the first configuration model using a pre-built carbon meter location constraint, a pre-built complete metering requirement constraint, and a pre-built non-redundant metering constraint; A second building module is used to build a second configuration model for the total measurement error of the carbon emission factor; The optimization module is used to optimize the initial carbon table configuration scheme based on the second configuration model and the pre-constructed minimum carbon table quantity constraint condition to obtain a target carbon table configuration scheme.

9. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for optimizing the carbon table configuration scheme described in any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: The method comprises at least a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program in the memory, the steps of the method for optimizing the carbon table configuration scheme according to any one of claims 1 to 7 are implemented.

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