Power grid carbon emission factor calculation method and system based on power grid tidal current distribution

Abstract

The invention provides a power grid carbon emission factor calculation method and system based on power grid power flow distribution, and the method employs a power flow distribution matrix which represents the relation between the power of a power system generator and the node flowing power to calculate the carbon flow density and the node carbon potential, and further can calculate the carbon emission factor of a power system more accurately. Finer data support is provided for carbon emission control; by evaluating and analyzing the carbon emission condition of each node in the electric power system, the weight of each node is analyzed, flexible adjustment and optimization can be performed according to the actual condition of the electric power system, and better self-adaptability and adaptability are achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field related to power grid carbon emission analysis, and in particular relates to a method and system for calculating a power grid carbon emission factor based on power grid flow distribution. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] The carbon emission issue of the power system is one of the current research hotspots. Accurately calculating the carbon emission factor of the power grid is of great significance for environmental protection and energy management. At present, the evaluation of the carbon emission factor of the power system mainly adopts the traditional macro-statistical analysis method, which starts from the macro data and uses the total energy consumption of the entire power grid to make statistics, such as based on data collection and analysis, or model calculation, etc., which has the advantages of simple calculation. However, these methods have some limitations, such as only being able to provide an overall average value but not fine-grained data at the node level, lacking dynamics and real-time performance, and are not conducive to specific carbon emission calculations.

[0004] In the power system, the transmission and distribution of electricity is complex and dynamic, and its carbon emission factor is affected by factors such as power flow between nodes, load changes, and power regulation. Therefore, in order to accurately calculate the carbon emission factor of the power grid and the specific flow of carbon emissions, more sophisticated data and models are needed to analyze the power transmission at the node level and its impact on carbon emissions.

[0005] The power flow distribution matrix reflects the power transmission between nodes in the power system, that is, the power flow and exchange between nodes. The power flow distribution matrix is ​​obtained through power flow calculation. The power flow distribution matrix can be used as basic data and reference indicators to calculate the flow state of the power grid carbon emission flow, thereby further evaluating the power grid carbon emission factor. However, there is currently a lack of an accurate calculation method and system to fully utilize the information of the power flow distribution matrix to accurately calculate the power grid carbon emission factor.

[0006] In summary, the development of an accurate grid carbon emission factor calculation method and system based on the grid power flow distribution matrix is ​​to address the limitations of existing technologies and provide a method for accurately analyzing the carbon emission factor of the power system. Summary of the invention

[0007] In order to overcome the shortcomings of the above-mentioned prior art, the present invention provides a method and system for calculating the carbon emission factor of a power grid based on the power grid flow distribution, which uses the power flow distribution matrix that represents the relationship between the generator power of the power system and the power flowing through the node to calculate the carbon flow density and the node carbon potential, thereby being able to more accurately calculate the carbon emission factor of the power system and provide more refined data support for carbon emission control; by evaluating and analyzing the carbon emissions of each node in the power system and analyzing the weight of each node, it is possible to flexibly adjust and optimize according to the actual situation of the power system.

[0008] To achieve the above object, a first aspect of the present invention provides a grid carbon emission factor calculation system based on grid flow distribution, comprising:

[0009] Perform power flow calculation on the acquired power system power flow distribution data to obtain the active power and active power loss of each branch;

[0010] Based on the active power and active power loss of each branch and Kirchhoff's current law, the power flow distribution matrix representing the relationship between the power of the power system generator and the power flowing through the node is obtained;

[0011] According to the obtained power flow distribution matrix, the carbon flow density and node carbon potential corresponding to each branch-node are calculated;

[0012] Calculate the carbon emission factor of each node based on the calculated carbon flow density and node carbon potential corresponding to each branch-node;

[0013] Using the entropy weight method and TOPSIS algorithm, the weight matrix of each node is calculated according to multiple evaluation indicators of each node;

[0014] The carbon emission factor of each node is combined with the corresponding weight matrix to calculate the overall carbon emission factor of the power system.

[0015] A second aspect of the present invention provides a grid carbon emission factor calculation system based on grid flow distribution, comprising:

[0016] Power flow calculation module: performs power flow calculation on the power system power flow distribution data obtained to obtain the active power and active power loss of each branch;

[0017] The first calculation module: based on the active power and active power loss of each branch, according to Kirchhoff's current law, obtain the power flow distribution matrix representing the relationship between the power of the power system generator and the power flowing through the node;

[0018] The second calculation module: calculates the carbon flow density and node carbon potential corresponding to each branch-node according to the obtained power flow distribution matrix;

[0019] Carbon emission factor calculation module: Calculate the carbon emission factor of each node according to the calculated carbon flow density and node carbon potential corresponding to each branch-node;

[0020] Weight calculation module: using entropy weight method and TOPSIS algorithm, according to multiple evaluation indicators of each node, calculate the weight matrix of each node;

[0021] Comprehensive calculation module: Combine the carbon emission factors of each node with the corresponding weight matrix to calculate the overall carbon emission factor of the power system.

[0022] The third aspect of the present invention provides a computer device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the computer device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, a method for calculating a grid carbon emission factor based on grid flow distribution is performed.

[0023] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, a method for calculating a grid carbon emission factor based on grid flow distribution is executed.

[0024] One or more of the above technical solutions have the following beneficial effects:

[0025] In the present invention, the carbon flow density and node carbon potential are calculated by utilizing the power flow distribution matrix representing the relationship between the power of the power system generator and the power flowing through the node, thereby being able to more accurately calculate the carbon emission factor of the power system and provide more refined data support for carbon emission control; by evaluating and analyzing the carbon emissions of each node in the power system and analyzing the weight of each node, it is possible to flexibly adjust and optimize according to the actual situation of the power system, with better self-adaptability and adaptability.

[0026] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0028] Figure 1 This is a flow chart of a precise grid carbon emission factor calculation model based on a grid power flow distribution matrix in Embodiment 1 of the present invention;

[0029] Figure 2The present invention is a design diagram of a power grid system node weight calculation model in the first embodiment of the present invention. DETAILED DESCRIPTION

[0030] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0031] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0032] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0033] Embodiment 1

[0034] This embodiment discloses a method for calculating a carbon emission factor of a power grid based on power grid flow distribution, including:

[0035] Perform power flow calculation on the acquired power system power flow distribution data to obtain the active power and active power loss of each branch;

[0036] Based on the active power and active power loss of each branch and Kirchhoff's current law, the power flow distribution matrix representing the relationship between the power of the power system generator and the power flowing through the node is obtained;

[0037] According to the obtained power flow distribution matrix, the carbon flow density and node carbon potential corresponding to each branch-node are calculated;

[0038] Calculate the carbon emission factor of each node based on the calculated carbon flow density and node carbon potential corresponding to each branch-node;

[0039] Using the entropy weight method and TOPSIS algorithm, the weight matrix of each node is calculated according to multiple evaluation indicators of each node;

[0040] The carbon emission factor of each node is combined with the corresponding weight matrix to calculate the overall carbon emission factor of the power system.

[0041] Combine the following Figure 1 A method for calculating a grid carbon emission factor based on grid power flow distribution in this embodiment is described in detail.

[0042] This embodiment proposes a method for calculating the carbon emission factor of a power grid based on power flow distribution. By obtaining power flow distribution matrix data to calculate the carbon emission factor of a node, and finally integrating the carbon emission factor, it effectively responds to the needs of carbon emission assessment of the power system and makes important contributions to the sustainable development and environmental protection of the power industry. Specifically, it includes:

[0043] Step 1: Get data in real time.

[0044] Obtain basic data on power flow distribution of the power system, including network topology, generator injection power, location and power of loads in the power system, and power transmission between nodes, etc. The power flow distribution data obtained can be achieved by using real-time monitoring devices and information transmission technology, with high accuracy and real-time performance.

[0045] The acquired data is preprocessed and stored in the form of a matrix for subsequent use.

[0046] Step 2: AC power flow calculation.

[0047] For a power system with n nodes, the active power flow and reactive power flow balance equations are as follows:

[0048]

[0049]

[0050] Among them, P Gi , Q Gi are the active and reactive outputs of the engine at node i respectively; P Li , Q Li are the active and reactive loads of node i respectively; G ij , B ij are the negative values ​​of conductance and susceptance of branch ij respectively; U i , U j are the voltage amplitudes of nodes i and j respectively; δ ij is the voltage angle difference between nodes i and j, i.e. δ ij =δ i -δ j .

[0051] The Newton-Raphson method is used to iteratively solve the voltage amplitude V of each node. i and angle δ i , and bring it into the calculation formula of active power and loss of each branch transmission, as shown below:

[0052] P ij =V i V j (G ij cosδ ij +B ij sinδ ij ) (3)

[0053]

[0054] Among them, Pij , P ij are the active power and active loss flowing through branch ij respectively, and finally the active power P of each branch is obtained ij and active power loss

[0055] Step 3: Construct the power flow distribution matrix.

[0056] The power flow distribution matrix is ​​constructed through the basic data of power flow distribution and the calculated active power, and the relationship between the generator power and the power flowing through the node is established;

[0057] According to Kirchhoff's Current Law, in any circuit node (the intersection connecting multiple electronic devices), the sum of the currents entering the node is equal to the sum of the currents flowing out of the node, that is,

[0058] Taking branch ij as an example, the power flowing through node j can be expressed as:

[0059]

[0060] Further rewriting:

[0061]

[0062] Expressed in matrix form:

[0063] A u P=P G (7)

[0064] So far, the power flow distribution matrix A is obtained u :

[0065]

[0066] Power flow distribution matrix A u The generator power P is established G The relationship between the power P flowing through the node can be used to obtain the active power distribution of the system. This relationship is the basis for the subsequent calculation of carbon flow density and node carbon potential.

[0067] Step 4: Calculate the nodal carbon potential.

[0068] Based on the power flow distribution matrix data, the carbon potential of each node is calculated using the carbon emission related calculation model. Assuming that the power flow direction of branch ij is from node i to node j, the branch transmission power P ij It can be expressed as:

[0069]

[0070] Among them, e i ∈R n×1 is a column vector whose i-th component is 1 and the rest are 0.

[0071] Based on the active power, reactive power and other data of each node, the carbon potential of each node is calculated comprehensively.

[0072] Coal consumption per kWh of coal-fired units i The calculation formula is:

[0073]

[0074] Among them, a i , b i 、c i is the characteristic parameter of the coal consumption curve of unit i under normal operation; i is the correction factor, and its value is related to the status of the unit;

[0075] Carbon emission factor E of coal-fired units Gi The calculation formula is:

[0076]

[0077] in, and M C are the molar masses of carbon dioxide and carbon, respectively; η i is the carbon content of coal used in unit i; ξ i is the carbon oxidation rate of coal fired in unit i; μ i is the carbon capture rate.

[0078] According to formula (9) and formula (11), the carbon flow rate R corresponding to the power flowing through branch ij can be obtained: ij for

[0079]

[0080] Then the carbon potential of node j can be expressed as:

[0081]

[0082] Among them, S j is the set of branches directly connected to node j, R ij is the carbon flow rate from branch i to j, is the carbon emission corresponding to the active power loss from branch i to j.

[0083] Step 5: Calculate the node carbon emission factor.

[0084] Carbon flow is a virtual network based on power flow. The node carbon potential is the carbon emission value equivalent to the power generation side caused by the consumption of a unit of electricity at a certain node, which is equal to the real-time carbon emission intensity of power generation of the power plant. It is numerically equal to the weighted average of the carbon flow density of all branches flowing into the node with respect to the active power flow.

[0085] When the carbon potential of all nodes in the power grid system is known, the carbon flow rate of all branches can be calculated, and the carbon emission factor can be obtained. It can be expressed as:

[0086] C j =E Nj ×P j (14)

[0087] Among them, P j The power flowing through node j, E Nj is the carbon potential at node j, C j is the carbon emission factor of node j.

[0088] At this point, the carbon emission factor of each node in the power grid can be obtained.

[0089] Step 6: Integrate grid carbon emission factors.

[0090] The carbon emission factors of each node are comprehensively considered to obtain the overall carbon emission factor of the power system. The analysis results can reflect the carbon emission of the power system and provide a basis for subsequent carbon emission control and environmental protection. A node weight calculation model for the power grid system is proposed here. By combining the entropy weight method and the TOPSIS algorithm, a comprehensive weight algorithm is used to obtain the weight of each node in the power grid system, thereby integrating the carbon emission factor of the entire power grid.

[0091] Example of a formula that incorporates a carbon emission factor:

[0092] Overall carbon emission factor = Σ(node ​​carbon emission factor * node weight) / total number of nodes.

[0093] Combination Figure 2 , assuming that the power grid system has n nodes and m evaluation indicators. First, the reliability, transmission and economic characteristics of the nodes are considered manually, and the scores are assigned to the node importance I, and the load demand P of each node is obtained from the power grid data. L and power generation capacity P g . Secondly, I and P L and P G Integration of three evaluation indicators. Since all three indicators are extremely large indicators, no additional conversion is required. The forward matrix X can be directly obtained by using the original data.

[0094]

[0095] Then the normalized matrix X is standardized as follows:

[0096]

[0097] Among them, Z ij Each element in the standardized matrix represents the standardized value of the i-th evaluation object on the j-th indicator. ij is the element in the original matrix, that is, the element in the X matrix of formula (15), which represents the original value of the i-th evaluation object on the j-th indicator.

[0098] After standardization, the standardized matrix Z is obtained. The entropy weight method is used to assign values ​​to the standardized matrix Z, and the probability matrix P and information entropy E are calculated. The formula is as follows:

[0099]

[0100]

[0101] Among them, p ij Each element in the probability matrix represents the probability value of the i-th evaluation object on the j-th indicator.

[0102] Information utility j =1-e j , that is, the larger the information utility value is, the more information it corresponds to. The information utility is normalized to obtain the commercial weight W of each indicator. j , the formula is as follows:

[0103]

[0104] Again, combining the standardized matrix Z and the quotient weight W j , substitute into TOPSIS algorithm to calculate comprehensive score index SC, the calculation process and formula are as follows:

[0105] Find the maximum and minimum values ​​of each indicator in the standardized matrix Z and construct a multidimensional maximum indicator vector Z + and the multidimensional minimum index vector Z - :

[0106]

[0107]

[0108] The distance from the i-th node to the optimal solution is recorded as

[0109] The distance from the i-th node to the worst solution is recorded as

[0110] Calculate the composite score index

[0111] Finally, the scores are normalized to obtain

[0112] Finally, the weight matrix of each node in the power grid system is obtained

[0113] In summary, this embodiment utilizes information such as the power grid flow distribution matrix to more accurately calculate the carbon emission factor of the power system and provide more refined data support for carbon emission control; at the same time, by evaluating and analyzing the carbon emissions of each node in the power system, including power stations, substations, load nodes, etc., it more comprehensively supports environmental protection and carbon emission control; in particular, it can be flexibly adjusted and optimized according to the actual situation of the power system, and has better adaptability and adaptability.

[0114] Through testing and verification on multi-type and multi-source data sets, the accuracy, precision and AUC value of the present invention have been significantly improved compared with traditional models.

[0115] The present invention can effectively meet the needs of carbon emission assessment in power systems and make important contributions to the sustainable development and environmental protection of the power industry. The model and its calculation are based on the principle of fairness and rationality, and have the advantages of clear physical concepts, simple calculations, and real-time analysis. It is hoped that it can provide a useful reference for the development of future low-carbon power technology.

[0116] This embodiment ensures the accuracy and real-time performance of the calculation by acquiring the power system's flow distribution data in real time. This is more advanced than traditional methods based on historical data or static data; it not only takes into account the carbon flow density and node carbon potential, but also introduces the entropy weight method and TOPSIS algorithm to comprehensively evaluate the weight of each node. This method can more comprehensively reflect the importance of each node in the power grid and its contribution to carbon emissions; it can be flexibly adjusted and optimized according to the actual situation of the power system, and has better adaptability. This means that under different power grid configurations and operating conditions, this method can provide accurate calculation of carbon emission factors.

[0117] This embodiment integrates multiple technical means such as the power flow distribution matrix, carbon flow density, node carbon potential and comprehensive evaluation index to form a comprehensive carbon emission factor calculation framework. This integration improves the accuracy and practicality of the calculation.

[0118] Embodiment 2

[0119] The purpose of this embodiment is to provide a grid carbon emission factor calculation system based on grid power flow distribution, including:

[0120] Power flow calculation module: performs power flow calculation on the power system power flow distribution data obtained to obtain the active power and active power loss of each branch;

[0121] The first calculation module: based on the active power and active power loss of each branch, according to Kirchhoff's current law, obtain the power flow distribution matrix representing the relationship between the power of the power system generator and the power flowing through the node;

[0122] The second calculation module: calculates the carbon flow density and node carbon potential corresponding to each branch-node according to the obtained power flow distribution matrix;

[0123] Carbon emission factor calculation module: Calculate the carbon emission factor of each node according to the calculated carbon flow density and node carbon potential corresponding to each branch-node;

[0124] Weight calculation module: using entropy weight method and TOPSIS algorithm, according to multiple evaluation indicators of each node, calculate the weight matrix of each node;

[0125] Comprehensive calculation module: Combine the carbon emission factors of each node with the corresponding weight matrix to calculate the overall carbon emission factor of the power system.

[0126] Embodiment 3

[0127] The purpose of this embodiment is to provide a computing device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the steps of the above method are implemented when the processor executes the program.

[0128] Embodiment 4

[0129] The purpose of this embodiment is to provide a computer-readable storage medium.

[0130] A computer-readable storage medium stores a computer program, which executes the steps of the above method when executed by a processor.

[0131] The steps involved in the apparatuses of the above embodiments 2, 3 and 4 correspond to the method embodiment 1, and the specific implementation methods can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0132] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0133] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A method for calculating the carbon emission factor of a power grid based on power grid flow distribution, characterized in that: include: Perform power flow calculation on the acquired power system power flow distribution data to obtain the active power and active power loss of each branch; Based on the active power and active power loss of each branch and Kirchhoff's current law, the power flow distribution matrix representing the relationship between the power of the power system generator and the power flowing through the node is obtained; According to the obtained power flow distribution matrix, the carbon flow density and node carbon potential corresponding to each branch-node are calculated; Calculate the carbon emission factor of each node based on the calculated carbon flow density and node carbon potential corresponding to each branch-node; Using the entropy weight method and TOPSIS algorithm, the weight matrix of each node is calculated according to multiple evaluation indicators of each node; The carbon emission factor of each node is combined with the corresponding weight matrix to calculate the overall carbon emission factor of the power system.

2. A method for calculating a power grid carbon emission factor based on power grid flow distribution according to claim 1, characterized in that: The power flow distribution data obtained for the power system include the network topology, the generator injection power, the location and power of the loads in the power system, and the power transmission status between the nodes.

3. A method for calculating the carbon emission factor of a power grid based on power grid flow distribution according to claim 1, characterized in that: The power flow distribution data of the power system is obtained and the power flow calculation is performed to obtain the active power and active power loss of each branch, which are as follows: Establish active power flow and reactive power flow balance equations of the power system; The established active power flow and reactive power flow balance equations of the power system are iteratively solved using the Newton-Raphson method to obtain the voltage amplitude and angle of each node; According to the voltage amplitude and angle of each node, the active power and loss calculation formula of each branch transmission is substituted to obtain the active power and active loss of each branch.

4. A method for calculating a power grid carbon emission factor based on power grid flow distribution according to claim 1, characterized in that: According to Kirchhoff's current law, the sum of the currents entering a node is equal to the sum of the currents flowing out of the node, and the relationship between the generator power and the power flowing through the node is established based on the power flow distribution matrix.

5. A method for calculating the carbon emission factor of a power grid based on power grid flow distribution according to claim 1, characterized in that: According to the obtained power flow distribution matrix, the carbon flow density and node carbon potential corresponding to each branch-node are calculated, specifically: Calculate branch transmission power based on power flow distribution matrix; Calculate the carbon emission factor of coal-fired units using carbon emission related calculation models; The carbon flow rate corresponding to each branch is obtained by using the branch transmission power and the carbon emission factor of the coal-fired unit, and the node carbon potential is obtained; The carbon emission factor of each node is calculated by calculating the node carbon potential and the node flow power.

6. A method for calculating a power grid carbon emission factor based on power grid flow distribution according to claim 1, characterized in that: The evaluation indicators include: node importance, load demand and power generation capacity.

7. A method for calculating the carbon emission factor of a power grid based on power grid flow distribution according to claim 6, characterized in that: Using the entropy weight method and TOPSIS algorithm, the weight matrix of each node is calculated according to multiple evaluation indicators of each node, specifically: Determining whether the node importance, the load demand and the power generation capacity are positive indicators; If so, the node importance, the load demand and the power generation capacity are standardized to obtain a corresponding standardized matrix; Calculating the business weight of the standardized matrix, and calculating the standardized matrix and the calculated business weight using the TOPSIS algorithm to obtain a comprehensive score index; The comprehensive score index is normalized to obtain the weight matrix of each node.

8. A grid carbon emission factor calculation system based on grid flow distribution, characterized in that: include: Power flow calculation module: performs power flow calculation on the power system power flow distribution data obtained to obtain the active power and active power loss of each branch; The first calculation module: based on the active power and active power loss of each branch, according to Kirchhoff's current law, obtain the power flow distribution matrix representing the relationship between the power of the power system generator and the power flowing through the node; The second calculation module: calculates the carbon flow density and node carbon potential corresponding to each branch-node according to the obtained power flow distribution matrix; Carbon emission factor calculation module: Calculate the carbon emission factor of each node according to the calculated carbon flow density and node carbon potential corresponding to each branch-node; Weight calculation module: using entropy weight method and TOPSIS algorithm, according to multiple evaluation indicators of each node, calculate the weight matrix of each node; Comprehensive calculation module: Combine the carbon emission factors of each node with the corresponding weight matrix to calculate the overall carbon emission factor of the power system.

9. A computer device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the computer device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, a method for calculating a grid carbon emission factor based on grid flow distribution is performed as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for calculating the carbon emission factor of a power grid based on power grid flow distribution as described in any one of claims 1 to 7 is executed.

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