Multi-energy coordinated energy management and control evaluation method based on electric-carbon coupling support power grid

Abstract

The invention discloses a multi-energy coordinated energy management and control evaluation method based on an electricity-carbon coupling support power grid, and belongs to the technical field of power system operation analysis and energy management. By establishing a connection relation between a power grid structure and multiple types of energy units, power generation power output data, type information and a power flow distribution result are collected; and calculating the carbon factor injection amount of a power generation side node, and sharing the carbon factor injection amount to a load node to form an inter-node power-carbon transmission relationship. Based on the carbon factors received by the load nodes, identifying the power generation power supply type composition, counting the energy supply contribution proportion, and constructing a multi-energy energy supply structure; and further constructing a node-level energy index and an electric carbon index, quantifying an energy receiving structure, a cooperative adjustment capability and a carbon factor receiving intensity, and evaluating the cooperative energy and management and control response of the multi-energy energy supply structure under different working conditions.

Description

Technical Field

[0001] This invention relates to the field of power system operation analysis and energy management technology, specifically to a multi-energy coordinated energy control and assessment method for power grids based on electric-carbon coupling. Background Technology

[0002] With the large-scale integration of new energy sources and the coordinated operation of multiple types of power generation, the power grid's energy supply structure is becoming increasingly complex, and energy distribution is exhibiting characteristics of diversification and time-varying nature. Traditional power grid assessment methods mainly focus on power allocation and power balance, lacking a systematic identification and analysis of energy type composition and its carbon emission characteristics, making it difficult to fully reflect the impact of multi-source energy supply on node operating status.

[0003] In existing technologies, the operation and control of multi-energy systems often neglects the coupling mechanism between electricity and carbon emissions, making it impossible to assess the flow, reception characteristics, and dynamic trends of carbon factors at the node level. Furthermore, the lack of a response index system based on the proportion of energy supply contribution and carbon factor intensity limits the refined management and optimization of node regulation capabilities and energy-carbon matching characteristics in multi-energy systems. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem addressed by this invention is to resolve the disconnect between the multi-energy supply structure and carbon emission characteristics in existing power grids, which fails to effectively support coordinated regulation and carbon index assessment. For the complex energy supply relationships under multiple types of power generation, this invention proposes an energy management and assessment method based on electro-carbon coupling. This method can identify the composition of power generation types at the node level, calculate the carbon factor injection and allocation relationship, and construct node-level energy and electro-carbon indices. By analyzing the response trends of energy and carbon indices under multiple operating conditions, the coordinated regulation capability and carbon reception intensity of nodes are quantified, and node control levels are classified, providing support for hierarchical regulation and carbon management of multi-energy systems.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling, comprising:

[0007] Establish the connection relationship between the power grid structure and various energy units, and collect power output data, power generation type information, and power flow distribution results under typical operating conditions;

[0008] Based on the power output data of the generating source and the corresponding carbon factor, the carbon factor injection amount of the generating side node is calculated, and combined with the power flow distribution results, the carbon factor is allocated to the load node to form the inter-node electric carbon transmission relationship.

[0009] Based on the carbon factors received by the load nodes, the corresponding power generation types are identified, and the contribution of power generation to the power supply of the load nodes is statistically analyzed to form a multi-energy supply structure.

[0010] Based on the multi-energy supply structure, node-level energy indicators and electrical carbon indicators are constructed to quantify the energy acceptance structure, coordinated regulation capability, and carbon factor reception intensity, and to evaluate the coordinated energy and control response of the multi-energy supply structure under different operating conditions.

[0011] As a preferred embodiment of the multi-energy coordinated energy management and assessment method for power grid based on electro-carbon coupling described in this invention, the establishment of the connection relationship between the power grid structure and multiple energy units includes obtaining the node number and branch start and end information in the power grid, determining the node location of the power generation source, recording the type, capacity, operating status of the power generation source and the corresponding branch number and node number, and sorting out the connection relationship between the power generation source, nodes and branches.

[0012] As a preferred embodiment of the multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling described in this invention, wherein: the carbon factor injection amount of the calculated generation-side node is expressed as:

[0013]

[0014] Among them, C i P represents the amount of carbon factor injected at the i-th power generation node. i,j λ represents the output of the j-th type of generating power source in the node under the selected operating condition. j denoted by , where is the unit carbon factor corresponding to the power generation source, n represents the number of power generation source types connected to the node, i represents the number of the power generation node in the grid, and j represents the number of the power generation source type connected to node i.

[0015] As a preferred embodiment of the multi-energy coordinated energy management and assessment method for power grid based on electric carbon coupling described in this invention, the step of allocating carbon factors to load nodes in conjunction with power flow distribution results to form inter-node electric carbon transmission relationships includes: proportionally allocating carbon factors according to the active power distribution ratio of power generation nodes to load nodes in the power flow distribution results, based on the carbon factor injection amount of power generation nodes, to obtain the total amount of carbon factors received by the load nodes, recording the corresponding power generation node numbers, establishing a carbon factor allocation mapping relationship between power generation nodes and load nodes, and forming an inter-node electric carbon transmission relationship matrix, represented as:

[0016] T = [T] i,k ] k×N

[0017] Among them, T i,kLet M represent the amount of carbon factor allocated from power generation node i to load node k, M represent the total number of power generation nodes, N represent the total number of load nodes, T represent the carbon transfer matrix, and k represent the load node number.

[0018] As a preferred embodiment of the multi-energy coordinated energy management and assessment method for power grid based on electric carbon coupling described in this invention, the step of identifying the corresponding power generation type based on the carbon factor received by the load node includes extracting the power generation node number corresponding to the carbon factor received by the load node through the electric carbon transmission relationship matrix, combining the type information of the power generation node and the connected power generation, classifying and summarizing the carbon factor allocation value corresponding to the power generation, and outputting the power generation type and corresponding carbon factor component corresponding to the load node.

[0019] As a preferred embodiment of the multi-energy coordinated energy management and assessment method for power grid based on electric carbon coupling described in this invention, the method of statistically analyzing the energy contribution ratio of power generation sources to load nodes and forming a multi-energy supply structure includes calculating the proportion of carbon factors to the total carbon factors of load nodes based on the carbon factor allocation values ​​corresponding to different types of power generation sources received by load nodes, thereby obtaining the contribution ratio of power generation sources to load nodes; and recording the corresponding power generation source type and corresponding energy supply ratio according to the load node number, and outputting a multi-energy supply structure map.

[0020] The proportion of the calculated carbon factor to the total carbon factor of the load nodes is expressed as follows:

[0021]

[0022] Among them, P m,k T represents the proportion of the energy supply contribution of the m-th type of power generation to load node k. m,k This represents the amount of carbon factor allocated to load node k by the generating power source, and m represents the type number of the generating power source.

[0023] As a preferred embodiment of the multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling described in this invention, the step of constructing node-level energy indicators and electro-carbon indicators according to the multi-energy supply structure includes:

[0024] The node-level energy index is expressed as follows:

[0025]

[0026] Among them, D k The node-level energy index representing load node k;

[0027] The carbon dioxide index is expressed as follows:

[0028]

[0029] Among them, Γ k E represents the carbon receiving intensity index of load node k. k This represents the equivalent energy supply of node k under the current operating conditions.

[0030] As a preferred embodiment of the multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling described in this invention, the quantification of energy acceptance structure, coordinated regulation capability, and carbon factor reception intensity, and the assessment of the coordinated energy and management response of the multi-energy supply structure under different operating conditions, include comparing the node-level energy indicators and carbon factor reception intensity of load nodes under various operating conditions, identifying the response trend and offset magnitude under changing conditions of the multi-source energy supply structure; combining the impact of changes in power generation type on energy structure and carbon reception mode, analyzing the degree of adaptability and adjustment margin of nodes to changes in energy supply; based on the difference in the value of coordinated regulation capability, judging the coordinated energy supply coordination of multiple types of power generation under different operating conditions, and classifying the management response level of load nodes.

[0031] The present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor executes the computer program to implement the steps of the multi-energy coordinated energy management and assessment method based on the electric carbon coupling-supported power grid.

[0032] The present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the multi-energy coordinated energy management and assessment method based on the electric carbon coupling-supported power grid.

[0033] The beneficial effects of this invention are as follows: By constructing the coupling relationship between the power grid structure and multiple types of power generation sources, this invention quantifies the injection, transmission, and reception processes of carbon factors, achieving refined identification of the multi-source energy supply composition of load nodes and the sources of carbon factors; by statistically analyzing the proportion of energy contribution of different types of power sources to load nodes and constructing a node-level electric carbon index system, it effectively characterizes the energy acceptance capacity, carbon factor reception intensity, and energy supply structure stability of nodes under multiple operating conditions; further, by combining the quantification of differences in coordinated regulation capabilities, it identifies the coordination between power sources and classifies the response levels of load nodes, providing support for the hierarchical regulation of multi-energy systems and enhancing the adaptability and regulation capability of the power grid to complex energy and carbon structures. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 The above is a flowchart of a multi-energy coordinated energy management and assessment method for power grids based on electric carbon coupling, provided as an embodiment of the present invention. Detailed Implementation

[0036] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0037] Example 1, referring to Figure 1 This is one embodiment of the present invention, which provides a multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling, including:

[0038] S1: Establish the connection relationship between the power grid structure and various energy units, and collect power generation output data, power generation type information, and power flow distribution results under typical operating conditions; such as Figure 1 As shown in S1;

[0039] It should be noted that establishing the connection relationship between the power grid structure and various energy units includes obtaining the node number and branch start and end information in the power grid, determining the node location of the power generation source, recording the type, capacity, operating status of the power generation source, as well as the corresponding branch number and node number, and sorting out the connection relationship between the power generation source, nodes and branches.

[0040] Furthermore, the topology information of the power grid is obtained from the power grid modeling data or the dispatch system. The node numbers of all nodes are extracted, and the start and end information of each branch in the power grid is extracted simultaneously, including the start node number and end node number corresponding to each branch. This is used to characterize the connection path between nodes in the power grid. Combined with the multiple types of power generation sources connected, the node location of each power generation source is determined, that is, the power grid node number to which the power generation source is connected. This node number is used to identify the specific connection point of the power generation source in the power grid structure. Relevant attribute information of the power generation source is collected, including the type of power generation source (such as photovoltaic, wind power, coal-fired, etc.), capacity parameters, and current operating status (such as running, shutdown, regulation, etc.). The branch number and corresponding node number associated with each power generation source are recorded. The correspondence between branch number and node number is merged and organized to form the pairing information between each power generation source and node, and between node and branch, to ensure that each power generation source has a clear access location and branch connection path.

[0041] It should also be noted that by one-to-one correspondence between branch numbers and node numbers, the problem of fuzzy or incorrect identification of power generation unit access points in traditional modeling is avoided. This ensures that the access location and electrical path of each power generation source in the power grid structure are unique and traceable. For multiple types of energy units, a structured approach is used to collect and map their physical access points and attribute information, realizing accurate access and integrated modeling of multiple energy types under the same topology. This provides a scalable data foundation for subsequent operations such as carbon factor calculation and energy index quantification.

[0042] S2: Based on the power output data and corresponding carbon factors, calculate the carbon factor injection amount at the power generation nodes, and combine this with the power flow distribution results to allocate the carbon factors to the load nodes, forming the inter-node electrical carbon transport relationship; such as Figure 1 As shown in S2;

[0043] It should be noted that the carbon factor injection amount calculated at the power generation side node is expressed as:

[0044]

[0045] Among them, C i P represents the amount of carbon factor injected at the i-th power generation node. i,j λ represents the output of the j-th type of generating power source in the node under the selected operating condition. j denoted by , where is the unit carbon factor corresponding to the power generation source, n represents the number of power generation source types connected to the node, i represents the number of the power generation node in the grid, and j represents the number of the power generation source type connected to node i.

[0046] Furthermore, based on the established power grid structure and the connection relationship of power generation sources, all power generation node numbers i in the power grid are traversed, all power generation source types j connected to node i are extracted, and the output value P of each type of power generation source under the current selected operating condition is read. i,j According to the type of power generation source, for each type j, the corresponding unit carbon factor λ is extracted from the carbon factor database. j This represents the carbon emissions corresponding to 1 MWh output by this type of power source. For power generation node i, for all connected power source types j, a multiplication operation is performed item by item to obtain the carbon factor injection value generated by each type of power source at that node. The product results are then summed to obtain the total carbon factor injection C at that node. i The calculation represents the total carbon emission intensity introduced by all the power generation sources connected to the node under the current operating conditions.

[0047] It should also be noted that by multiplying and superimposing the output of different types of power sources with their carbon factors on a node-by-node basis, the true carbon-introducing force of each power generation node can be accurately reflected. By combining dynamic operating output values ​​with static carbon factor parameters, the differences in the contribution of different energy types to carbon emissions are taken into account, which significantly enhances the ability to characterize the carbon characteristics of node energy.

[0048] Furthermore, combining the power flow distribution results, carbon factors are allocated to load nodes to form inter-node electrical carbon transport relationships. This includes allocating carbon factors proportionally based on the active power distribution ratio of power generation nodes to load nodes in the power flow distribution results, according to the amount of carbon factors injected by power generation nodes, to obtain the total amount of carbon factors received by load nodes, and recording the corresponding power generation node numbers. A carbon factor allocation mapping relationship is then established between power generation nodes and load nodes, forming an inter-node electrical carbon transport relationship matrix, represented as follows:

[0049] T = [T] i,k ] M×N

[0050] Among them, T i,k Let M represent the amount of carbon factor allocated from power generation node i to load node k, M represent the total number of power generation nodes, N represent the total number of load nodes, T represent the carbon transfer matrix, and k represent the load node number.

[0051] Furthermore, based on the power flow simulation results of the power grid under the current selected operating conditions, the distribution ratio of active power transmitted from all generating nodes i to each load node k is obtained. Combined with the carbon factor injection amount of the generating nodes, it is allocated according to the power flow distribution ratio. For each load node, the amount of carbon factor received from the generating nodes is calculated, which represents the carbon factor contribution of the generating nodes to the load nodes under the current operating conditions. All combinations of generating nodes and load nodes are traversed sequentially, and the carbon factor allocation value of each pair is summarized. Using the generating node number and the load node number as indices, an electrical carbon transmission relationship matrix is ​​established with a dimension of M×N, where M represents the total number of generating nodes and N represents the total number of load nodes. The electrical carbon transmission relationship matrix is ​​used as a quantitative expression of the carbon factor flow between nodes to describe the path strength of carbon factor transmission from the source side to the load side, forming a node-level carbon factor allocation mapping relationship.

[0052] It should also be noted that by combining the active power distribution ratio output from the power flow simulation with the carbon factor injection amount at the generation nodes, a carbon factor allocation path from the generation nodes to the load nodes was established. The directionality and intensity of the carbon flow between nodes were quantified, and this was achieved through T... i,k The construction of this system can clearly identify the generation nodes from which the carbon factors received by the load nodes originate, and the magnitude of their contribution, which is beneficial for providing quantifiable data in scenarios such as carbon quotas, power dispatch, and low-carbon optimization.

[0053] S3: Based on the carbon factors received by the load nodes, identify the corresponding power generation types and calculate the contribution of each power generation source to the load nodes' energy supply, forming a multi-energy supply structure; such as Figure 1 As shown in S3;

[0054] It should be noted that, based on the carbon factors received by the load nodes, identifying the corresponding power generation type involves extracting the power generation node number corresponding to the carbon factors received by the load nodes through the carbon transmission relationship matrix, combining the type information of the power generation nodes and the connected power generation sources, classifying and summarizing the carbon factor allocation value corresponding to the power generation sources, and outputting the power generation type and corresponding carbon factor component of the load nodes.

[0055] Furthermore, the constructed carbon transfer relationship matrix is ​​invoked. For each load node, the numbers of all power generation nodes that have carbon factor allocation to that load node and their corresponding carbon factor allocation values ​​are extracted. Combined with the access information of each power generation node, the type of power generation source it is connected to is extracted, and the correspondence between the power generation source type number and the node number is further determined. All carbon factor allocation values ​​received by the load node are classified according to the power generation source type: that is, all allocation values ​​from the same power generation source type are summed to obtain the carbon factor components corresponding to each type of power generation source received by the load node. The power generation source type corresponding to the load node and the carbon factor allocation value corresponding to each type are output.

[0056] It should also be noted that by using the power generation type and carbon factor allocated to the load node as output results, a structured index system for the carbon source type of the load node was established, providing a quantitative basis for subsequent calculation of energy contribution ratio, construction of multi-energy spectrum and carbon constraint optimization control.

[0057] Furthermore, the contribution of power generation sources to the load nodes is statistically analyzed to form a multi-energy power supply structure. This includes calculating the proportion of carbon factors to the total carbon factors of the load nodes based on the carbon factor allocation values ​​corresponding to different types of power generation sources received by the load nodes, thus obtaining the contribution of power generation sources to the load nodes. The corresponding power generation source type and corresponding power supply proportion are recorded according to the load node number, and a multi-energy power supply structure map is output.

[0058] The proportion of the calculated carbon factor to the total carbon factor of the load nodes is expressed as follows:

[0059]

[0060] Among them, P m,k T represents the proportion of the energy supply contribution of the m-th type of power generation to load node k. m,k This represents the amount of carbon factor allocated to load node k by the generating power source, and m represents the type number of the generating power source.

[0061] It should be noted that, based on the established carbon transmission relationship matrix, for each load node, the carbon factor allocation value corresponding to different types of power generation received is extracted. Taking the total carbon factor of all types of power generation received by the load node as the benchmark, the energy supply contribution ratio of each type of power generation to the node is calculated to obtain the type-level energy supply composition ratio. According to each load node number, its corresponding power generation type and its energy supply contribution ratio are recorded to form the multi-energy supply structure of the node under the current operating conditions. The energy supply composition structure of all load nodes is summarized and displayed, and a multi-energy supply structure map containing node number, power generation type, and energy supply ratio is output.

[0062] It should also be noted that, based on the carbon transport relationship matrix, the carbon factor allocation value corresponding to different types of power generation received by each load node is extracted. Using the total carbon factor as the standard, the energy contribution ratio of each type of power generation to that node is calculated, thus obtaining the proportional relationship of the energy supply structure. This clearly identifies the type of power generation and its energy contribution ratio corresponding to each load node under the current operating conditions, making the energy supply composition at the node level calculable and distinguishable. By recording the type of power generation and its energy contribution ratio one by one according to the node number, a multi-energy supply structure map is formed, achieving a structured expression of the node energy composition under a multi-source power supply background.

[0063] S4: Based on the multi-energy supply structure, construct node-level energy and carbon emission indicators to quantify the energy acceptance structure, coordinated regulation capability, and carbon factor reception intensity, and evaluate the coordinated energy and control response of the multi-energy supply structure under different operating conditions; such as... Figure 1 Shown in S4;

[0064] It should be noted that, based on the multi-energy supply structure, the node-level energy indicators and carbon dioxide indicators include:

[0065] The node-level energy index is expressed as follows:

[0066]

[0067] Among them, D k The node-level energy index representing load node k;

[0068] The carbon dioxide index is expressed as follows:

[0069]

[0070] Among them, Γ k E represents the carbon receiving intensity index of load node k. k This represents the equivalent energy supply of node k under the current operating conditions.

[0071] Furthermore, based on the energy contribution ratio of various types of power sources received by each load node, for each load node, all corresponding power source type numbers and the corresponding energy contribution ratio of that type of power source are extracted, and the energy composition of the node is quantified. The calculation results represent the diversity and balance of the energy composition of the node under the current operating conditions. Combined with the total amount of carbon factors received by the node and the equivalent energy supply of the node under the current operating conditions, the carbon intensity index of the load node is obtained by substituting it into the formula for calculating the carbon emission index.

[0072] It should also be noted that, based on the energy contribution ratio of various types of power sources received by the load node, the number of all power source types corresponding to that node and the energy contribution ratio of that type of power source are extracted. The energy contribution ratio is used to calculate the node-level energy index, which can quantify the diversity and balance of the energy supply structure of the node under the current operating conditions. Then, combined with the total amount of carbon factors received by the node and the equivalent energy supply, the carbon reception intensity index of the node is obtained. Thus, at the node level, the quantitative status of both the energy supply structure and carbon emission intensity is reflected simultaneously, providing a calculable basic index for subsequent energy-carbon coordinated optimization control.

[0073] Furthermore, the study quantifies the energy acceptance structure, coordinated regulation capability, and carbon factor reception intensity, and assesses the coordinated energy and control response of multi-energy supply structures under different operating conditions. This includes comparing the node-level energy indicators and carbon factor reception intensity of load nodes under various operating conditions, identifying the response trends and deviations under changing multi-source energy supply structures, analyzing the degree of node adaptability and adjustment margin in response to energy supply changes by combining the impact of changes in power generation type on energy structure and carbon reception pattern, and judging the coordinated energy supply of multiple types of power generation under different operating conditions based on the differences in coordinated regulation capability, and classifying the control response levels of load nodes.

[0074] It should be noted that multiple operating scenarios are set up, and the node-level energy index and carbon factor receiving intensity index of each load node are calculated under each scenario to obtain the characteristic quantities of the energy supply structure under different scenarios. Based on the changes of the index of each node under multiple scenarios, the numerical changes of the node-level energy index are compared to analyze the response trend and offset of the node under the change of energy supply structure. The adaptability of the node to the multi-source energy supply structure under different operating conditions is identified. Combining the changes in the energy supply structure and the changes in the node carbon receiving mode of each power generation type under different operating conditions, the impact of the change of power generation type on the node's energy supply composition and carbon factor distribution is evaluated. Based on the numerical differences of the node-level energy index and the carbon factor index of different nodes under multiple operating conditions, the adaptability and adjustment margin of each node to the changes in energy supply are analyzed. Based on the numerical distribution of the coordinated adjustment capability of each node, nodes with higher adjustment capability are identified, and the control response level of the nodes is divided according to the strength of the coordinated adjustment capability.

[0075] It should also be noted that by constructing node-level energy indicators and carbon factor reception intensity indicators under various operating conditions, the energy supply capacity and carbon reception performance of nodes under different energy structure conditions are characterized. This breaks through the limitation of existing assessment methods that only statically assess a single energy scenario. By combining the trend and deviation of indicator values, the adaptability and adjustment margin of nodes under the adjustment of multiple energy supply structures can be identified, thereby effectively supporting the fine classification of node-level control and response levels.

[0076] Example 2 is an embodiment of the present invention, which provides a multi-energy coordinated energy management and assessment method for power grid based on electric carbon coupling. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0077] Six typical load nodes (nodes AF) in a regional power grid were selected as test subjects, covering two voltage levels: 110kV and 220kV, to cover the power flow distribution characteristics under different voltage levels. Three types of power sources were constructed, including photovoltaic, wind power, and thermal power. Output data for each type of power source was collected under typical operating conditions (sunny midday, peak load, and nighttime off-peak), with the unit uniformly expressed in MW. Simultaneously, the actual load of each node was extracted, and the power flow distribution path and ratio between the power injected by the generator side and the power received by the load nodes were obtained through a power flow simulation system.

[0078] Based on the carbon factor of the power generation source, the carbon emissions per unit output of each power generation source are calculated separately, and the carbon emission factor is proportionally allocated to each load node according to the power flow distribution path. For example, node A mainly receives energy from 20MW photovoltaic, 10MW wind power and 30MW thermal power, and its total carbon factor injection is calculated to be 30×0.9=27tCO2, which is accumulated to 80tCO2 after being allocated to the load nodes.

[0079] After obtaining the total carbon factor received by each node, the carbon factor received intensity per unit load is calculated in combination with the load capacity. Furthermore, the contribution ratio of various power sources to the load nodes is analyzed based on the energy supply structure to obtain the multi-energy supply structure, and the node-level energy indicators are extracted. The experimental data are shown in Table 1.

[0080] Table 1. Experimental Results of Carbon Factor Receiving at Nodes in Multi-Energy Power Supply Structures

[0081]

[0082]

[0083] As can be observed from the table above, node E has the highest photovoltaic output (25MW) and the lowest thermal power output (20MW). Therefore, its total carbon factor injection (70tCO2) is significantly lower than that of nodes with a high proportion of thermal power, such as node D (150tCO2) and node F (130tCO2). This result directly reflects that by adjusting the power generation energy structure (such as increasing the output proportion of low-carbon energy such as photovoltaic and wind power), the carbon absorption intensity of load nodes can be effectively reduced. Regarding the key indicator of node carbon factor absorption intensity, node E is slightly higher than node A (1.6tCO2 / MW) at 1.75tCO2 / MW, mainly because node E has a smaller total load (40MW), leading to an increased carbon absorption intensity per unit load, but its total carbon injection is still the lowest.

[0084] From the perspective of nodal-level energy structure, nodes C and F have relatively balanced wind-solar-thermal energy supply structures. The carbon factor receiving intensity at node C is 1.58 tCO2 / MW, slightly lower than that at node F (1.44), indicating that under the same energy structure conditions, power flow path and load distribution also significantly affect the carbon factor receiving result. Simple power output analysis is insufficient to support a reasonable allocation of the carbon factor; a power-carbon mapping relationship needs to be constructed in conjunction with power flow distribution results.

[0085] By establishing the aforementioned carbon factor allocation and electricity carbon index system, we can compare the carbon absorption, energy supply structure adaptability, and regulation capabilities of different nodes under different operating scenarios, thereby identifying high-carbon nodes, weak regulation nodes, and renewable energy acceptance bottlenecks.

[0086] Example 3 is an embodiment of the present invention. This embodiment provides an electronic device applicable to the multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling. The device includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes the computer-executable instructions to implement the multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling as proposed in the above embodiments.

[0087] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling proposed in the above embodiments.

[0088] The storage medium proposed in this embodiment and the multi-energy coordinated energy management and evaluation method based on electro-carbon coupling to support the power grid proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0089] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0090] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling, characterized in that: include: Establish the connection relationship between the power grid structure and various energy units, and collect power output data, power generation type information, and power flow distribution results under typical operating conditions; Based on the power output data of the generating source and the corresponding carbon factor, the carbon factor injection amount of the generating side node is calculated, and combined with the power flow distribution results, the carbon factor is allocated to the load node to form the inter-node electric carbon transmission relationship. Based on the carbon factors received by the load nodes, the corresponding power generation types are identified, and the contribution of power generation to the power supply of the load nodes is statistically analyzed to form a multi-energy supply structure. Based on the multi-energy supply structure, node-level energy indicators and electrical carbon indicators are constructed to quantify the energy acceptance structure, coordinated regulation capability, and carbon factor reception intensity, and to evaluate the coordinated energy and control response of the multi-energy supply structure under different operating conditions.

2. The multi-energy coordinated energy management and assessment method for power grid based on electro-carbon coupling as described in claim 1, characterized in that: The process of establishing the connection relationship between the power grid structure and various energy units includes obtaining the node number and branch start and end information in the power grid, determining the node location where the power generation source is connected, recording the type, capacity, operating status of the power generation source, as well as the corresponding branch number and node number, and sorting out the connection relationship between the power generation source, nodes and branches.

3. The multi-energy coordinated energy management and assessment method for power grid based on electro-carbon coupling as described in claim 2, characterized in that: The carbon factor injection amount calculated at the power generation side node is expressed as: where C i represents the carbon factor injection of the ith generation node, P i,j represents the output of the jth type of power generation source in the selected operating condition, λ j represents the corresponding unit carbon factor of the power generation source, n represents the number of types of power generation sources connected to the node, i represents the number of the generation node in the power grid, and j represents the number of the type of power generation source connected to the node i.

4. The multi-energy coordinated energy management and assessment method for power grid based on electro-carbon coupling as described in claim 3, characterized in that: The process of allocating carbon factors to load nodes based on the power flow distribution results to form inter-node electrical carbon transport relationships includes: allocating carbon factors proportionally according to the active power distribution ratio of power generation nodes to load nodes in the power flow distribution results, based on the amount of carbon factors injected by power generation nodes, to obtain the total amount of carbon factors received by load nodes, recording the corresponding power generation node numbers, establishing a carbon factor allocation mapping relationship between power generation nodes and load nodes, and forming an inter-node electrical carbon transport relationship matrix, represented as: T = [T i,k ] k×N where T i,k represents the carbon factor amount allocated to load node k by power generation node i, M represents the total number of power generation nodes, N represents the total number of load nodes, T represents the electric carbon transmission relationship matrix, and k represents the number of load nodes.

5. The multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling as described in claim 4, characterized in that: The process of identifying the corresponding power generation type based on the carbon factor received by the load node includes extracting the power generation node number corresponding to the carbon factor received by the load node through the carbon transfer relationship matrix, combining the type information of the power generation node and the connected power generation, classifying and summarizing the carbon factor allocation value corresponding to the power generation, and outputting the power generation type and corresponding carbon factor component of the load node.

6. The multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling as described in claim 5, characterized in that: The statistical analysis of the contribution of power generation sources to the load nodes, forming a multi-energy power supply structure, includes calculating the proportion of carbon factors to the total carbon factors of the load nodes based on the carbon factor allocation values ​​corresponding to different types of power generation sources received by the load nodes, thus obtaining the contribution of power generation sources to the load nodes; and recording the corresponding power generation source type and corresponding power supply proportion according to the load node number, and outputting a multi-energy power supply structure map. The proportion of the calculated carbon factor to the total carbon factor of the load nodes is expressed as follows: wherein P m,k represents the contribution ratio of the mth type of power generation source to the energy supply of the load node k, T m,k represents the carbon factor amount allocated to the load node k by the power generation source, and m represents the type number of the power generation source.

7. The multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling as described in claim 6, characterized in that: Based on the multi-energy supply structure, node-level energy indicators and electricity carbon indicators are constructed. include: The node-level energy index is expressed as follows: wherein D k denotes the node-level energy indicator of the load node k; The carbon dioxide index is expressed as follows: Among them, Γ k E represents the carbon receiving intensity index of load node k. k This represents the equivalent energy supply of node k under the current operating conditions.

8. The multi-energy coordinated energy management and assessment method for power grids based on electro-carbon coupling as described in claim 7, characterized in that: The quantitative energy acceptance structure, coordinated regulation capability, and carbon factor reception intensity are used to evaluate the coordinated energy and control response of the multi-energy supply structure under different operating conditions. This includes comparing the node-level energy indicators and carbon factor reception intensity of load nodes under various operating conditions, identifying the response trend and offset magnitude under changing conditions of the multi-source energy supply structure, and analyzing the degree of adaptability and adjustment margin of nodes to changes in energy supply by combining the impact of changes in power generation type on energy structure and carbon reception mode. Based on the differences in the magnitude of coordinated regulation capabilities, the coordination of energy supply of multiple types of power generation sources under different operating conditions is determined, and the control and response levels of load nodes are classified.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the multi-energy coordinated energy management and assessment method based on the electric carbon coupling-supported power grid as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the multi-energy coordinated energy management and assessment method based on the electric carbon coupling-supported power grid as described in any one of claims 1 to 7.

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