A multi-dimensional evaluation method based on a new energy station wiring scheme

Abstract

The application provides a multi-dimensional evaluation method based on a new energy station wiring scheme, extracts a wiring scene of grid connection of a new energy station, and classifies according to a station main body organization mode, an access node position and an access structure mode, constructs a three-dimensional index system of economy, reliability and settlement convenience, combines node classification and multi-scene simulation analysis, models power plants and power grids involved, optimizes units at minimum cost, respectively analyzes and comprehensively analyzes index characteristics of multiple dimensions such as economy, reliability and settlement convenience, and obtains an optimal wiring mode under specific conditions through influence factor changes. The method of the application clearly defines the applicable boundary of different station organization modes in the aspect of metering and settlement convenience, and provides quantifiable decision basis for power grid enterprises in the process of grid connection of new energy stations and power grid planning.

Description

Technical Field

[0001] This invention belongs to the field of power system planning technology, and in particular relates to a multi-dimensional evaluation method based on the wiring scheme of new energy power plants. Background Technology

[0002] With the continuous development of green energy, electricity has gradually become a mainstream energy source, and the requirements for power systems are increasing, bringing new challenges to the planning, design, operation, and management of grid connection schemes in terms of flexibility, adequacy, and security. However, traditional grid connection models are difficult to adapt to the diverse grid connection needs of new energy power plants. Furthermore, the metering and settlement mechanisms for grid integration schemes and the allocation of rights among multiple stakeholders are becoming increasingly prominent, and the proportion of metering and settlement disputes related to new energy grid connection is also on the rise.

[0003] In existing technologies, grid connection schemes for new energy power plants mainly focus on the selection of grid connection nodes. Evaluation is conducted based on information such as grid structure, substation distribution, load distribution, and substation capacity. However, current evaluation methods do not consider the specific grid connection of new energy power plants, nor do they account for the related human factors. They neglect the multi-dimensional factors of the coupling relationship between the connection node and the transmission network, and do not adequately consider the criticality of the connection node. Therefore, the current evaluation dimensions for grid connection schemes of new energy power plants are relatively singular, resulting in poor evaluation effectiveness. Summary of the Invention

[0004] This application provides a multi-dimensional evaluation method based on the wiring scheme of new energy power plants, aiming to enrich the evaluation dimensions of the wiring scheme of new energy power plants and improve the evaluation effect of the wiring scheme of grid access.

[0005] Specifically, this application addresses the shortcomings of existing technologies in renewable energy power plant grid connection schemes, such as the lack of consideration for node criticality, the impact of specific renewable energy power plant wiring and grid connection, and the lack of in-depth analysis of practical needs such as property rights clarity and metering independence in complex scenarios involving multiple entities. It proposes a multi-dimensional grid connection scheme evaluation method for renewable energy power plants that considers node classification. This method starts with renewable energy power plant grid connection schemes, extracts typical grid connection scenarios, classifies nodes based on IEEE standard node and unit models, selects typical nodes for unit combination and operation simulation, and analyzes the multi-dimensional characteristics of renewable energy power plants under different nodes and grid connection schemes based on simulation analysis. This comprehensively identifies the advantages and disadvantages of various grid connection schemes, providing a multi-dimensional evaluation for high-quality grid connection of renewable energy power plants and grid planning, and ultimately offering decision-making basis for high-quality grid connection and grid planning.

[0006] To achieve the above objectives, this application proposes a multi-dimensional evaluation method based on the wiring scheme of new energy power stations, including:

[0007] Collect sample data of wiring schemes for grid connection of new energy power plants;

[0008] Based on the sample data of the wiring scheme, the wiring schemes of new energy power stations are classified to obtain the classified wiring schemes;

[0009] Collect grid connection index data of new energy power stations, and construct multi-dimensional evaluation indicators for evaluating the new energy power stations based on the grid connection characteristics in the grid connection index data. The multi-dimensional evaluation indicators include at least economic indicators, reliability indicators and settlement convenience indicators.

[0010] Based on the multi-dimensional evaluation indicators and the classified wiring schemes, simulation training is performed to generate grid connection simulation data corresponding to different wiring schemes, and a power grid model is created based on the grid connection simulation data.

[0011] Based on the power grid model, the wiring scheme for the current grid connection is evaluated and calculated using multi-dimensional evaluation indicators, and the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators are determined. The multi-dimensional evaluation results include the evaluation results corresponding to the dimensions of economy, reliability and settlement convenience.

[0012] In a preferred embodiment of the present invention, the classified wiring schemes include multiple access schemes classified according to different main organization methods, access node locations, and access structure methods;

[0013] According to the main organizational method of new energy power stations, the new energy connection scenarios include: typical forms of bundled access and multi-entity access;

[0014] According to the location of the access node of the new energy power station, the new energy connection scenarios include: access to the main transmission network, access to the regional distribution network, access to the low-voltage distribution network, and access to the load-side node;

[0015] According to the access structure of new energy power stations, the new energy connection scenarios include: direct access, series access, T-type access and Π-type access.

[0016] In a preferred embodiment of the present invention, the step of classifying the wiring schemes of new energy power plants according to the wiring scheme sample data to obtain the classified wiring schemes includes:

[0017] Calculate the eigenvector centrality of each wiring scheme in the sample data of the wiring schemes;

[0018] The wiring scheme sample data is classified according to the eigenvector centrality to determine the classified wiring scheme.

[0019] In a preferred embodiment of the present invention, each wiring scheme includes at least one wiring node, and each wiring scheme has different connection relationships or topologies for different wiring nodes;

[0020] The step of calculating the eigenvector centrality of each wiring scheme in the wiring scheme sample data includes:

[0021] Based on the connection relationship or topology of different wiring nodes in the wiring scheme, calculate the local node characteristic values ​​in the wiring scheme.

[0022] The formula for calculating the feature values ​​of the local nodes is as follows: ;

[0023] Among them, the These are local eigenvalues ​​of the node; N represents the branch that the node is directly connected to in the power network, and N is the number of nodes in the wiring scheme.

[0024] Calculate the global node feature values ​​based on the local node feature values;

[0025] The formula for calculating the global node feature value is as follows: ;

[0026] Among them, the The global feature value of the node; Let be the number of shortest paths between two adjacent nodes i and j; the global eigenvalues ​​of all nodes form an adjacency matrix. ;

[0027] Based on the global feature values ​​of the nodes, calculate the eigenvector centrality corresponding to the wiring scheme;

[0028] The formula for calculating the eigenvector centrality corresponding to the wiring scheme is: ;

[0029] Among them, the For the desired eigenvector centrality, These are the eigenvalues ​​corresponding to the adjacency matrix.

[0030] In a preferred embodiment of the present invention, the multi-dimensional evaluation indicators include economic indicators, which include investment costs and daily returns, and the multi-dimensional evaluation results include the evaluation results of the economic indicators.

[0031] The steps of evaluating and calculating multi-dimensional evaluation indicators for the wiring scheme of the current grid connection based on the power grid model, and determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, include:

[0032] Calculate the investment cost of the wiring scheme for the current grid connection of the new energy power station;

[0033] Calculate the daily revenue of the wiring scheme for the current grid connection of the new energy power station;

[0034] The evaluation results of the economic indicators of the wiring scheme for the current grid connection of the new energy power station are determined based on the investment cost and the daily revenue.

[0035] In a preferred embodiment of the present invention, the step of evaluating and calculating multi-dimensional evaluation indicators for the wiring scheme of the current grid connection based on the power grid model, and determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, further includes:

[0036] The investment cost includes: total investment in the transmission line, in-plant step-up equipment, and power plant investment. The investment cost is calculated taking into account the depreciation formula.

[0037] The formula for calculating investment costs is as follows: ;

[0038] Among them, the , , These are investment in transmission lines, substations, and power plants, respectively, in yuan. It is the residual value rate; It refers to the service life, in years; It is a collection of routes;

[0039] The daily revenue is the product of the grid-connected electricity price and the daily generated electricity, minus the operating costs, wherein the operating costs include grid losses and the power plant's operation and maintenance costs;

[0040] The formula for calculating the operating costs is as follows:

[0041] in, Let represent the power generation of the i-th generating unit at time t, in MW. Internet access loss rate; The time interval is expressed in hours (h). The figure represents the grid connection price, expressed in yuan / MWh; M represents the operation and maintenance cost of the power generation project, expressed in yuan. This is a collection of generator sets.

[0042] In a preferred embodiment of the present invention, the multi-dimensional evaluation index includes a reliability index, which includes a resilience index composed of expected unsupplied power and average annual outage time, and the multi-dimensional evaluation result includes the evaluation result of the reliability index.

[0043] The steps of evaluating and calculating multi-dimensional evaluation indicators for the wiring scheme of the current grid connection based on the power grid model, and determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, include:

[0044] The reliability index is calculated based on the resilience index, which is composed of the expected unsupplied power and the average annual outage time.

[0045] The formula for calculating the resilience index is as follows:

[0046]

[0047] Among them, the Here is the average load power at node i, in MW; The duration of the stop point. The probability of failure of the components or devices connected at this node; Let i be the number of users at node i, in units of households. For the number of nodes, Node i user's cumulative annual power outage time Total load power consumption.

[0048] In a preferred embodiment of the present invention, the multi-dimensional evaluation indicators include convenience indicators, which include property division clarity (OCI) and gateway independence (MIS).

[0049] The steps of evaluating and calculating multi-dimensional evaluation indicators for the wiring scheme of the current grid connection based on the power grid model, and determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, include:

[0050] Calculate the property rights division clarity (OCI) of the wiring scheme for the current grid connection of a new energy power station;

[0051] Calculate the gate independence (MIS) of the wiring scheme for the current grid connection of the new energy power station;

[0052] The evaluation results of the convenience index of the new energy power station wiring scheme are determined based on the property division clarity (OCI) and the gateway independence (MIS).

[0053] In a preferred embodiment of the present invention, the step of evaluating and calculating multi-dimensional evaluation indicators for the wiring scheme of the current grid connection based on the power grid model, and determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, further includes:

[0054] The clarity of property rights division is measured by the number of different enterprises connected to the same line to measure the complexity of the network topology; the smaller the index, the more complex the network topology.

[0055] The formula for calculating the clarity of the property division is as follows:

[0056] Among them, the This represents the number of enterprises connected to the i-th node. The maximum number of companies allowed;

[0057] The independence of the checkpoints is measured by the ratio of the total number of independent metering points to the total number of metering points in the system to measure the complexity of metering management.

[0058] The formula for calculating the independence of the checkpoint is as follows:

[0059] Among them, the For independent measurement points, This represents the total number of measurement points.

[0060] In a preferred embodiment of the present invention, after determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, the node classification multi-dimensional evaluation method based on the new energy power station wiring scheme further includes:

[0061] The characteristics of the indicators in the multidimensional evaluation results are analyzed separately and comprehensively, and corresponding adjustment suggestions are determined.

[0062] Based on the aforementioned adjustment recommendations, determine the target network connection scheme.

[0063] One or more technical solutions proposed in this application have at least the following technical effects:

[0064] This application collects sample data of grid connection schemes for new energy power plants; classifies the grid connection schemes of new energy power plants based on the sample data, obtaining classified grid connection schemes; collects grid connection index data of new energy power plants, and constructs multi-dimensional evaluation indicators for evaluating new energy power plants based on the grid connection characteristics in the grid connection index data. These multi-dimensional evaluation indicators include at least economic indicators, reliability indicators, and settlement convenience indicators. Based on the multi-dimensional evaluation indicators and the classified grid connection schemes, simulation training is conducted to generate grid connection simulation data corresponding to different grid connection schemes, and a power grid model is created based on the grid connection simulation data. Based on the power grid model, the multi-dimensional evaluation indicators are calculated for the grid connection scheme of the current grid connection, determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators. These multi-dimensional evaluation results include evaluation results corresponding to the dimensions of economic efficiency, reliability, and settlement convenience.

[0065] Compared to existing technologies, this application constructs multi-dimensional evaluation indicators for economy, reliability, and settlement convenience, and combines this with multi-scenario simulation analysis based on the classification of access nodes in different wiring schemes to create a power grid model. This power grid model can effectively identify the advantages and disadvantages of various grid connection schemes under different dimensions, and evaluate the current access scheme according to the multi-dimensional evaluation indicators based on this power grid model, obtaining corresponding multi-dimensional evaluation results. This not only reveals the impact of access structure on system economy and reliability, but also clarifies the applicable boundaries of different power station organization methods in terms of metering and settlement convenience, providing power grid companies with quantifiable decision-making basis in the process of new energy power station grid connection and power grid planning. Compared to existing evaluation schemes, this application comprehensively evaluates wiring schemes from multiple dimensions, optimizes the evaluation effect of wiring scheme evaluation, has higher reference value and application potential, and can significantly improve the scientificity and rationality of grid connection scheme design. Attached Figure Description

[0066] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0067] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0068] Figure 1 This is a flowchart illustrating an embodiment of a multi-dimensional evaluation method based on a new energy power station wiring scheme provided in this application.

[0069] Figure 2 This is a flowchart illustrating a second embodiment of a multi-dimensional evaluation method based on a new energy power station wiring scheme, as provided in this application.

[0070] Figure 3 This is a flowchart illustrating a third embodiment of a multi-dimensional evaluation method based on a new energy power station wiring scheme, as provided in this application.

[0071] Figure 4 This is a flowchart illustrating Embodiment 4 of a multi-dimensional evaluation method based on a new energy power station wiring scheme, as provided in this application.

[0072] Figure 5 This is a flowchart illustrating a fifth embodiment of a multi-dimensional evaluation method based on a new energy power station wiring scheme, as provided in this application.

[0073] Figure 6This is a flowchart illustrating an embodiment of a multi-dimensional evaluation method based on a new energy power station wiring scheme provided in this application.

[0074] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0075] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0076] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0077] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or resource allocation device capable of performing the above functions. The following description uses a resource allocation device (hereinafter referred to as the device) as an example to illustrate this embodiment and the subsequent embodiments.

[0078] Based on this, the embodiments of this application provide a multi-dimensional evaluation method based on the wiring scheme of new energy power stations, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the resource allocation method of this application.

[0079] In this embodiment, the resource allocation method includes steps S10 to S50:

[0080] Step S10: Collect sample data of wiring schemes for grid connection of new energy power plants.

[0081] Among them, the wiring scheme sample data refers to the collection of basic information related to various wiring methods used to support scheme analysis and evaluation during the grid connection process of new energy power plants. The wiring scheme sample data can record the specific characteristics, technical parameters and related information of different wiring schemes.

[0082] Specifically, the wiring scheme sample data may include: data related to the main organization of the site, data on the location of access nodes, and data on the access structure.

[0083] Among them, the relevant data of the site main organization may include: whether the access scenario is a bundled access (single property owner) or a multi-owner access (multiple property owners), the number of enterprises involved, the property division boundary, etc., which are used to distinguish the wiring characteristics under different main participation modes.

[0084] Access node location data can include: the power grid level to which the access node belongs (such as the main transmission network, regional distribution network, low-voltage distribution network, load-side node), node number, voltage level corresponding to the node, distribution of surrounding substations and load capacity, etc., reflecting the spatial positioning characteristics of the wiring scheme.

[0085] Access structure data may include: specific wiring methods (e.g., direct access, series access, T-type access, Π-type access, etc.), and physical parameters related to the structure, such as line type (e.g., LGJ-300), line length, distance between nodes, distance between new site and access node / line, whether line removal is involved and the proportion of removal costs, etc., reflecting the topology of the wiring and details of the engineering implementation.

[0086] In step S10, basic data on various wiring schemes during the grid connection process of new energy power plants can be systematically collected. Specifically, detailed information on wiring schemes under different scenarios needs to be comprehensively collected, including but not limited to the main organizational form of the power plant (such as bundled access, multi-entity access), the spatial location of access nodes (such as main transmission network, regional distribution network, low-voltage distribution network, load-side nodes), access structure type (such as direct access, series access, T-type access, Π-type access, etc.), and technical parameters related to the wiring scheme (such as line type, node number, distance parameters, number of involved entities, etc.). By standardizing the collection of the above sample data, a data foundation is laid for the subsequent classification and evaluation of wiring schemes.

[0087] In embodiments of the present invention, the structures can be classified according to the main organization of the site, the location of the access node, and the access structure.

[0088] The organizational form of a renewable energy power station essentially determines the basic logic of resource allocation, ownership division, dispatch control, and economic settlement. Based on the organizational form of renewable energy power stations, renewable energy access scenarios can be divided into two typical forms: bundled access and multi-entity access.

[0089] From the perspective of the power system hierarchy, the spatial location of renewable energy access nodes directly affects their role in system power flow distribution, voltage support, and dispatch control. Based on the location of the access node, they can be mainly classified as access to the main transmission network, access to the regional distribution network, access to the low-voltage distribution network, and access to load-side nodes.

[0090] According to the access structure, the access structures widely used in engineering practice at present mainly include direct access, series access, T-type access and Π-type access.

[0091] Step S20: Based on the wiring scheme sample data, classify the wiring schemes of new energy power stations to obtain the classified wiring schemes.

[0092] According to the preset classification criteria, the wiring schemes of new energy power stations are systematically divided. The classification logic mainly includes three dimensions: (1) According to the main organization of the power station, it can be divided into bundled access (single property owner) and multi-owner access (multiple property owners); (2) According to the location of the access node, it can be divided into access to the main transmission network, access to the regional distribution network, access to the low-voltage distribution network and access to the load side node; (3) According to the access structure, it can be divided into typical forms such as direct access, series access, T-type access and Π-type access. Through the above classification, the diverse wiring schemes are sorted into categories with clear characteristics, providing a structured framework for targeted evaluation of the characteristics of different schemes.

[0093] Step S30: Collect grid connection index data of new energy power stations, and construct multi-dimensional evaluation indicators for evaluating new energy power stations based on the grid connection characteristics in the grid connection index data. The multi-dimensional evaluation indicators include at least economic indicators, reliability indicators, and settlement convenience indicators.

[0094] Economic efficiency mainly involves investment costs and daily revenue, reliability is measured by the resilience of the system, and settlement convenience is mainly affected by the number of entities connected at the same interface and whether the metering point at the gateway is affected by the electricity metering of other metering points.

[0095] In step S30, key indicator data during the grid connection process of new energy power plants are collected, covering core parameters related to grid connection operation such as investment cost, power generation, grid loss rate, power outage time, and metering point configuration. Based on the grid connection characteristics reflected by these data, an evaluation indicator system with the following three dimensions is constructed: Economic indicators: including total project investment (including investment and depreciation costs of lines, substations, power plants) and daily revenue (the product of on-grid electricity price and power generation minus grid loss and operation and maintenance costs), used to measure the economic feasibility of the wiring scheme; Reliability indicators: with system resilience (resilience) as the core, quantified by parameters such as expected unsupplied power and average annual power outage time, reflecting the system's ability to maintain function and resume normal operation after being disturbed; Settlement convenience indicators: including property rights division clarity (OCI, i.e., the ratio of the number of node access enterprises to the maximum allowed number) and gate independence (MIS, i.e., the ratio of independent metering points to total metering points), used to evaluate the convenience of metering and settlement and the clarity of rights division in multi-entity scenarios.

[0096] Step S40: Based on the multi-dimensional evaluation indicators and the classified wiring schemes, conduct simulation training to generate grid connection simulation data corresponding to different wiring schemes, and create a power grid model based on the grid connection simulation data.

[0097] Simulation training is conducted by combining the categorized wiring schemes with the constructed multi-dimensional evaluation indicators. Specifically, output models for new energy power plants (such as photovoltaic and wind power) and traditional power plants need to be established (considering equipment characteristics, environmental impacts, and operational constraints), and a power grid model framework including elements such as node power balance and line power flow constraints needs to be constructed. Unit combination simulations are performed with the goal of minimizing cost, simulating the actual operation of different wiring schemes, and generating grid connection simulation data covering economy, reliability, and settlement convenience (such as investment cost, daily revenue, outage time, Ownership Clarity Index (OCI), and Metering Independence Score (MIS)). Based on the above simulation data, a power grid model consistent with the actual power grid operation is finally constructed, providing a simulation platform for subsequent evaluation calculations.

[0098] Step S50: Based on the power grid model, perform multi-dimensional evaluation calculations on the wiring scheme for the current grid connection, and determine the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators. The multi-dimensional evaluation results include the evaluation results corresponding to the dimensions of economy, reliability and settlement convenience.

[0099] Based on the established power grid model, multi-dimensional evaluation indicators are quantitatively calculated for the current grid connection scheme to be evaluated. Specifically, in terms of economic efficiency, the total project investment (including depreciation) and daily revenue are calculated to clarify the economic cost and benefit level of the scheme; in terms of reliability, the resilience level of the system is quantified through parameters such as expected unsupplied power and average annual outage time; in terms of settlement convenience, the clarity of ownership division (OCI) and gate independence (MIS) are calculated to assess the convenience of metering and settlement and the clarity of rights division.

[0100] Therefore, based on the above calculations, a multi-dimensional evaluation result covering economy, reliability, and settlement convenience is formed, providing a quantitative decision-making basis for the optimal selection of grid connection schemes for new energy power plants.

[0101] Based on the first embodiment of this application, a second embodiment of this application is proposed. In this second embodiment, content that is the same as or similar to that in the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 2 Step S20: Based on the wiring scheme sample data, classify the wiring schemes of new energy power stations to obtain the classified wiring schemes, including steps S21-S22:

[0102] Step S21: Calculate the eigenvector centrality of each wiring scheme in the wiring scheme sample data.

[0103] Eigenvector centrality is a network analysis metric. In different wiring schemes, eigenvector centrality is used to calculate the eigenvectors of the network adjacency matrix to evaluate the importance of nodes. In different wiring schemes, the importance of a node depends not only on the number of nodes it directly connects to, but also on the importance of those connecting nodes themselves.

[0104] In step 21, the node importance characteristics of various wiring schemes in the power network are quantified by calculating eigenvector centrality in the sample data. Specifically, for each wiring scheme (such as bundled access to the main transmission network, multi-entity T-type access to the regional distribution network, etc.), a corresponding network adjacency matrix needs to be constructed. The elements in the matrix are used to characterize the connection relationships between the nodes involved in the scheme (such as whether they are directly connected, connection strength, etc.). Then, the eigenvector corresponding to the largest eigenvalue of the adjacency matrix is ​​solved. The value of each element in the eigenvector represents the eigenvector centrality score of the corresponding node. Through this calculation, the network influence of the access node due to its connection relationship with other nodes (especially important nodes) under different wiring schemes can be clarified, providing a quantitative basis for subsequent classification and evaluation of wiring schemes based on node importance.

[0105] In one specific implementation, the wiring scheme can be classified by calculating the eigenvector centrality of the corresponding connection relationship or topology in each wiring scheme and based on the eigenvector centrality.

[0106] Here, each wiring scheme has at least one wiring node, and each wiring scheme has different connection relationships or topologies for different wiring nodes; the steps to calculate the eigenvector centrality of each wiring scheme in the wiring scheme sample data specifically include the following steps:

[0107] (1) Calculate the characteristic values ​​of local nodes in the wiring scheme based on the connection relationship or topology of different wiring nodes in the wiring scheme;

[0108] (2) The formula for calculating the eigenvalues ​​of local nodes is: ;

[0109] in, These are local eigenvalues ​​of the node; This refers to the branch that the node is directly connected to in the power network, where N is the number of nodes in the wiring scheme.

[0110] (3) Calculate the global node feature values ​​based on the local node feature values;

[0111] The formula for calculating the global node feature value is: ;

[0112] in, The global feature value of the node; Let be the number of shortest paths between two adjacent nodes i and j; the global eigenvalues ​​of all nodes form an adjacency matrix. ;

[0113] (4) Calculate the eigenvector centrality corresponding to the wiring scheme based on the global eigenvalues ​​of the nodes;

[0114] The formula for calculating the eigenvector centrality of the wiring scheme is: ;

[0115] in, For the desired eigenvector centrality, These are the eigenvalues ​​corresponding to the adjacency matrix.

[0116] Step S22: Classify each wiring scheme in the wiring scheme sample data according to the eigenvector centrality to determine the classified wiring scheme.

[0117] Here, the wiring scheme is classified according to the feature necklace centrality, which can be based on the Pareto principle to classify nodes. Specific classification types include critical nodes, secondary critical nodes, and general nodes.

[0118] In step S22, after calculating the eigenvector centrality of each wiring scheme, a systematic classification of all wiring scheme samples can be performed based on this eigenvector centrality. Specifically, firstly, the eigenvector centrality quantification results corresponding to each type of wiring scheme (i.e., the score reflecting the importance of each scheme's access node in the power network) are summarized. Then, according to preset classification criteria (such as a score threshold defined based on the Pareto principle, or a hierarchical range determined in conjunction with the actual operation requirements of the power grid), different wiring schemes are divided into categories corresponding to the importance level of the corresponding nodes (for example, schemes with eigenvector centrality scores in the top 20% are classified as critical node access schemes, those with scores in the middle range are classified as secondary critical node access schemes, and those with lower scores are classified as general node access schemes). Through this classification, the differences in the network influence of different wiring schemes can be clearly distinguished, so that the classified wiring schemes retain their respective structural characteristics and reflect the importance level of their access nodes, laying the foundation for subsequent targeted evaluation of wiring schemes for different levels of nodes.

[0119] Based on the first embodiment of this application, a third embodiment of this application is proposed. In this third embodiment, content that is the same as or similar to that of the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 3 , Figure 3This is a scheme for evaluating and calculating wiring schemes based on economic indicators. As step S50, based on the power grid model, multi-dimensional evaluation indicators are calculated for the wiring scheme of the current grid connection, and a detailed scheme for the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators is determined, including steps S31~S33:

[0120] Step S31: Calculate the investment cost of the wiring scheme for the current grid connection of the new energy power station;

[0121] In step S31, the total cost of the current wiring scheme in terms of engineering construction and equipment investment can be calculated, mainly including the investment in core facilities such as lines, substations, and power plants. At the same time, the depreciation cost (amortized cost after deducting residual value) during the service life of the equipment should be considered to quantify the initial investment scale of the scheme.

[0122] It should be noted that the investment cost includes: total investment in the transmission line, in-plant booster equipment, and power plant investment. The investment cost is calculated using the depreciation formula.

[0123] In one specific implementation, the formula for calculating investment costs is as follows:

[0124] ;

[0125] in, , , These are investment in transmission lines, substations, and power plants, respectively, in yuan. It is the residual value rate; It refers to the service life, in years; It is a set of routes.

[0126] Step S32: Calculate the daily revenue of the wiring scheme for the current grid connection of the new energy power station;

[0127] In step S32, the daily economic return of the wiring scheme is calculated, which is the product of the daily on-grid electricity volume and the on-grid electricity price, and then the daily operating costs (such as line loss, equipment maintenance costs, etc.) are subtracted to finally obtain the daily net income of the wiring scheme, reflecting its short-term economic output capacity.

[0128] The daily revenue is the product of the grid connection price and the daily generated electricity, minus the operating costs, which include grid losses and the power plant's operation and maintenance costs.

[0129] In one specific implementation, the formula for calculating operating costs is as follows:

[0130] in, Let represent the power generation of the i-th generating unit at time t, in MW. Internet access loss rate; The time interval is expressed in hours (h). The figure represents the grid connection price, expressed in yuan / MWh; M represents the operation and maintenance cost of the power generation project, expressed in yuan. This is a collection of generator sets.

[0131] Step S33: Determine the economic indicators of the wiring scheme for the current grid connection of the new energy power station based on investment costs and daily revenue.

[0132] After calculating the investment cost and daily revenue, the economic viability of the current wiring scheme can be comprehensively evaluated based on these factors. A comprehensive analysis of the total investment cost and daily revenue forms an overall assessment of the economic viability of the current wiring scheme. For example, by combining the investment scale and daily revenue, the payback period can be estimated, or the cost-benefit ratio can be directly compared, ultimately clarifying the scheme's advantages and disadvantages in terms of economic dimensions and providing a quantitative basis for decision-making.

[0133] Based on the first embodiment of this application, a fourth embodiment of this application is proposed. In this fourth embodiment, content that is the same as or similar to that of the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 4 , Figure 4 This is a scheme for evaluating and calculating wiring schemes based on reliability indicators. As step S50, based on the power grid model, multi-dimensional evaluation indicators are calculated for the wiring scheme of the current grid connection, and a detailed scheme for the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators is determined, including step S41:

[0134] Step S41: Calculate the reliability index based on the resilience index composed of the expected unsupplied power and the average annual power outage time.

[0135] In step S41, the reliability index is calculated using the resilience index. Specifically, it combines two key parameters: expected unsupplied power (i.e., the power that is expected to be unable to be supplied normally) and average annual outage time (the average of the total outage time throughout the year). This quantitatively assesses the reliability of the power system under the current wiring scheme of the renewable energy power plant. These two parameters directly reflect the system's ability to maintain power supply and its efficiency in restoring normal operation after being subjected to disturbances (such as equipment failures, natural disasters, etc.). The combination of the two parameters comprehensively reflects the system's performance in terms of reliability.

[0136] In one specific implementation, the formula for calculating the resilience toughness index is:

[0137]

[0138] in, Here is the average load power at node i, in MW; The duration of the stop point. The probability of failure of the components or devices connected at this node; Let i be the number of users at node i, in units of households. For the number of nodes, Node i user's cumulative annual power outage time Total load power consumption.

[0139] Based on the first embodiment of this application, a fifth embodiment of this application is proposed. In this fifth embodiment, content that is the same as or similar to that of the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 5 , Figure 5 This is a scheme for evaluating and calculating wiring schemes based on convenience indicators. As step S50, based on the power grid model, multi-dimensional evaluation indicators are calculated for the wiring scheme of the current grid connection, and a detailed scheme for the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators is determined, including steps S51-S53:

[0140] Step S51: Calculate the property rights division clarity (OCI) of the wiring scheme for the current grid connection of the new energy power station.

[0141] Among them, the property rights division clarity (OCI) measures the network topology complexity based on the number of different enterprises connected to the same line.

[0142] In step S51, the clarity of property rights division in the current wiring scheme is quantified. Specifically, the OCI value is calculated by dividing the actual number of enterprises connected to the same access node into the maximum number of enterprises allowed to connect to that node. The smaller the ratio, the more enterprises are connected to the same node, and the more complex the property rights division; the closer the ratio is to 1, the clearer the property rights division, which can reduce disputes between multiple parties.

[0143] It should be noted that the clarity of property rights division measures the complexity of the network topology based on the number of different companies connected to the same line; the smaller the index, the more complex the network topology.

[0144] In one specific implementation, the formula for calculating the clarity of property rights division is:

[0145]

[0146] in, This represents the number of enterprises connected to the i-th node. The maximum number of companies allowed;

[0147] Gate point independence is measured by the ratio of the total number of independent metering points in the system to the total number of metering points, which measures the complexity of metering management.

[0148] Step S52: Calculate the gate independence (MIS) of the wiring scheme for the current grid connection of the new energy power station.

[0149] Among them, the gate independence MIS measures the complexity of metering management by the ratio of the total number of independent metering points to the total number of metering points in the system.

[0150] In step S52, the independence of metering and settlement in the current wiring scheme is evaluated. The MIS value is obtained by calculating the ratio of the number of independent metering points to the total number of metering points in the system. The higher the ratio, the higher the proportion of independent metering, the less interference from other metering points on the electricity metering of each entity, and the lower the risk of confusion during settlement; the lower the ratio, the stronger the metering correlation and the higher the settlement complexity.

[0151] In one specific implementation, the formula for calculating gate independence is:

[0152] in, For independent measurement points, This represents the total number of measurement points.

[0153] Step S51: Determine the evaluation results of the convenience index of the wiring scheme for new energy power stations based on the property division clarity (OCI) and gate independence (MIS).

[0154] After determining the clarity of property rights division and the independence of the gateway, an overall evaluation of the settlement convenience of the current wiring scheme can be formed based on these factors. For example, a scheme with an OCI close to 1 and a high MIS indicates clear property rights and independent metering, resulting in excellent settlement convenience; conversely, a low OCI and low MIS suggest that settlement is prone to disputes, leading to poor convenience. By combining these two factors, the actual performance of the scheme in the settlement dimension can be clarified, providing a basis for scheme selection in multi-entity access scenarios.

[0155] Based on the first embodiment of this application, a sixth embodiment of this application is proposed. In this sixth embodiment, content that is the same as or similar to that of the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 2 Before step S10, the multi-dimensional evaluation method based on the wiring scheme of new energy power stations includes steps S61-S62:

[0156] Step S61: Analyze the characteristics of the indicators in the multidimensional evaluation results separately and comprehensively, and determine the corresponding adjustment suggestions.

[0157] First, the characteristics of the indicators in the three dimensions of economy, reliability, and settlement convenience in the multi-dimensional evaluation results are analyzed separately to clarify the advantages and disadvantages of the current wiring scheme under each dimension (for example, whether the investment cost is too high and whether the daily revenue meets the target in the economy indicator; whether the resilience of the system meets the requirements in the reliability indicator; and whether OCI and MIS meet the multi-entity access requirements in the settlement convenience indicator). Then, by comprehensively analyzing the correlation and trade-offs of the indicators in each dimension (e.g., a scheme has good economy but insufficient reliability, or high settlement convenience but high investment cost), and combining the core needs of the actual application scenario (e.g., prioritizing reliability or focusing on cost reduction), targeted adjustment suggestions are proposed. These include optimizing the access node location to reduce investment, adding independent metering points to improve settlement convenience, and adjusting the wiring structure to enhance system resilience, providing direction for subsequent scheme optimization.

[0158] Step S61: Determine the target network connection scheme based on the adjustment recommendations.

[0159] Based on the adjustment suggestions proposed in step S61, the original wiring scheme is optimized and iterated. By comparing the improvement effects of different adjustment schemes on multi-dimensional evaluation indicators, the scheme with the best overall performance is selected as the target grid connection scheme. The target grid connection scheme needs to achieve a balance between economy, reliability, and settlement convenience, and meet the actual access needs of new energy power plants (such as clear property rights in multi-entity scenarios, system resilience under high reliability requirements, etc.). Ultimately, it provides a feasible and quantifiable optimal wiring scheme for the grid connection of new energy power plants, ensuring their high-quality grid connection and the safe and stable operation of the power grid.

[0160] The following describes an optimal embodiment of this application to illustrate the content protected by this application. It should be noted that this embodiment is only an example and does not limit the patent scope of this application. All equivalent structural transformations made using the contents of this application's specification and drawings under the technical concept of this application, or direct / indirect applications in other related technical fields, are included within the patent protection scope of this application.

[0161] Step 1: Extract typical wiring scenarios for grid connection of new energy power stations.

[0162] Step 2: Analyze the grid connection characteristics of new energy power stations, construct evaluation indicators, and extract indicators from three dimensions: economy, reliability, and settlement convenience. Economy mainly involves investment costs and daily revenue, reliability is measured by the resilience of the system, and settlement convenience is mainly affected by the number of entities connected at the same interface and whether the metering point at the gateway is affected by the electricity metered by other metering points.

[0163] Economic indicators mainly include investment costs and daily returns.

[0164] Investment costs mainly consider the larger expenses, consisting of the total investment in the transmission line, the on-site step-up equipment, and the power plant investment. The depreciation formula is as follows.

[0165]

[0166] In the formula , , These are investment in transmission lines, substations, and power plants, respectively, in yuan. It is the residual value rate; It refers to the service life, in years; It is a set of routes.

[0167] Daily revenue is the product of the grid-connected electricity price and the daily generated electricity, minus operating costs. The power plant's operating costs consist of grid losses and the power plant's operation and maintenance fees.

[0168]

[0169] In the formula, Let represent the power generation of the i-th generating unit at time t, in MW. Internet access loss rate; The time interval is expressed in hours (h). The figure represents the grid connection price, expressed in yuan / MWh; M represents the operation and maintenance cost of the power generation project, expressed in yuan. This is a collection of generator sets.

[0170] Reliability indicators are composed of resilience indicators, which are determined by the expected amount of unsupplied power and the average annual outage time. The resilience of a power system mainly includes several aspects such as strain, defense, resilience, perception, coordination, and learning. This invention focuses on resilience, which describes the system's ability to absorb shocks, maintain function, and recover to normal operating conditions within a short period of time after being subjected to disturbances such as natural disasters, equipment failures, and attacks.

[0171]

[0172] In the formula, Here is the average load power at node i, in MW; The duration of the stop point. The probability of failure of the components or devices connected at this node; Let i be the number of users at node i, in units of households. For the number of nodes, Node i user's cumulative annual power outage time Total load power consumption.

[0173] This leads to two indicators for settlement convenience: Clearness of Property Division (OCI) and Gateway Independence (MIS). Clarity of Property Division measures the complexity of the network topology based on the number of different companies connected to the same line; a lower index indicates greater complexity.

[0174]

[0175] This represents the number of enterprises connected to the i-th node. The maximum number of companies allowed.

[0176] Gate independence is measured by the ratio of the total number of independent metering points to the total number of metering points in the system, which determines the complexity of metering management.

[0177]

[0178] In the formula For independent measurement points, This represents the total number of measurement points.

[0179] Step 3: Consider the impact of the node's location and topology on the access scheme, calculate the eigenvector centrality, and classify the nodes.

[0180] Based on the Pareto principle, nodes are classified into critical nodes, secondary critical nodes, and general nodes.

[0181] In this invention, the global eigenvalues ​​of nodes are used as the adjacency matrix.

[0182]

[0183] In the formula These are local eigenvalues ​​of the node; This refers to the branch that the node is directly connected to in the power network.

[0184]

[0185] In the formula The global feature value of the node; The number of shortest paths between node i and node j; the global eigenvalues ​​of all nodes form an adjacency matrix. .

[0186]

[0187] In the formula For the desired eigenvector centrality, These are the eigenvalues ​​corresponding to the adjacency matrix.

[0188] Step 4: Model the power plants involved, such as photovoltaic, wind power, coal-fired power plants, and power grids, optimize the units at the lowest cost, and calculate the indicators in three dimensions: economy, reliability, and settlement convenience.

[0189] For photovoltaic (PV) power plants, an output model is established. The output of a newly built PV power plant is related to the efficiency of the photovoltaic panels and solar radiation.

[0190]

[0191] in, This represents the total number of photovoltaic panels. The area of ​​each photovoltaic panel is expressed in m². Global horizontal radiation refers to the sum of direct solar radiation and atmospheric diffuse radiation received perpendicular to the ground, measured in W / m². The nominal efficiency of the panel under standard conditions; For temperature coefficient, Reference battery temperature, in °C; This is the actual operating temperature; For inverter efficiency; It is the factor that reduces the rated value.

[0192] For coal-fired power plants, a coal-fired power unit model is established, which includes constraints on output, ramp-up, minimum start / stop time, start-up and shutdown costs, output costs, and thermal reserve.

[0193]

[0194] in, Let be the output of unit i at time t, in MW; , These are the minimum and maximum outputs of the generator unit, in MW. Unit status: 1 indicates the unit is running, and 0 indicates the unit is stopped. , This is the power rate limit for acceleration and deceleration, measured in MW / h. The variable is set to 1 to indicate that unit i starts at time t. This is a shutdown variable; a value of 1 indicates that unit i shuts down at time t. , The minimum operating and minimum downtime of unit i are given in hours; T is the scheduling period in hours. The total cost of starting and stopping is expressed in yuan. , Startup and shutdown costs, in yuan; Operating costs, in yuan. , , This is the operating cost coefficient. Reserved thermal backup capacity for accidents, in MW.

[0195] Establish a power grid model, including matrix-form node inflow power, node balancing, and line power flow constraints.

[0196]

[0197] in, Inject power matrices into nodes. Let be the admittance matrix. The phase angle vector of the nodes. The diagonal elements of the admittance matrix, For the off-diagonal elements of the admittance matrix, For line impedance, For line flow, This represents the maximum power flow of the line.

[0198] Based on this system, nodes are selected to connect to newly built photovoltaic power plants and the units are combined. The goal of unit combination optimization is to minimize system cost.

[0199]

[0200] Step 5: Analyze the characteristics of the indicators in the three dimensions of economy, reliability and settlement convenience separately and comprehensively. Then, by analyzing the changes in influencing factors, determine under what specific conditions which wiring method performs best, and thus provide a network connection scheme recommendation.

[0201] The following is an illustration using a specific example. We will discuss the connection of a newly built photovoltaic power plant in northern Hebei Province to the IEEE-30 node.

[0202] This photovoltaic power plant has a rated capacity of 80MW, using monocrystalline silicon 440Wp+ solar cell modules. Based on calculations of maximum load hours, economic current density, conductor cross-sectional area selection, and heat dissipation verification, the LGJ-300 conductor cross-sectional area was chosen. The main components of the investment cost also include the support structure, inverter, switchgear, transformer unit cost parameters, and other economic parameters, as shown in Table 1.

[0203] Table 1 Economic Parameters

[0204]

[0205] Nodes were categorized, and their scores are shown in Table 2. After categorization, nodes 4 and 6 were selected as key nodes, nodes 7 and 8 as secondary key nodes, and nodes 1 and 3 as general nodes to determine the power plant's access location. Considering the impact of the access structure, for the selected nodes 4 and 6, four scenarios were set: direct access to node 4, direct access to node 6, T-connection between nodes 4 and 6, and Π-connection between nodes 4 and 6. The distance between nodes 4 and 6 is 24.05 km. The new power plant is assumed to be 4.5 km from the 4-6 line, 11.23 km from node 4, and 14.71 km from node 6. For the selected nodes 7 and 8, three scenarios were set: direct access to node 7, direct access to node 8, and series access to node 8. There is no direct connection between nodes 7 and 8. The new power plant is 23.11 km from node 7 and 18 km from node 8. For the selected nodes 1 and 3, four scenarios were set: direct access to node 1, direct access to node 3, T-connection between nodes 1 and 3, and Π-connection between nodes 1 and 3. The power plant is set 10km away from lines 1-3, and the distance between nodes 1 and 3 is 107.56km. The newly built power plant is 48.54km away from node 1 and 60.89km away from node 3. Special attention should be paid to the dismantling fee for Π connections, which is 35% of the fee for new construction. Considering the different organizational methods of the power station, four scenarios are set up: internal bundling of 4 enterprises, multi-entity access to nodes 1 and 3.

[0206] Table 2 Node Classification Table

[0207]

[0208] The unit combination and indicator calculations are based on minimizing costs, resulting in the indicators shown in Table 3 below. Wiring schemes and access points can be selected according to one's own priorities.

[0209] Table 3. Access Structure Scenario Indicators

[0210]

[0211] In terms of economics, the investment costs and daily revenues of the various schemes differ significantly. For critical nodes, directly connecting to node 4 is the most economical; for secondary critical nodes, the scheme directly connecting to node 8 has the lowest investment cost of 14,006.49 yuan / day and the highest daily revenue of 126,361.65 yuan / day, balancing low investment and high returns, making it the most economical; for general nodes, the T-connection between nodes 1 and 3 is the most economical.

[0212] In terms of reliability, direct access node 7 performed best overall. Among the critical nodes, direct access node 4 had the highest reliability; among the secondary critical nodes, direct access node 7 performed best overall; and among the general nodes, direct access node 1 performed best.

[0213] In terms of settlement convenience, the series access node 8 presents the most complex settlement scenario. The total number of access node entities is set to 5, the same as the maximum allowed number of entities. Its OCI is 0.776 and MIS is 0.75. This is because this scheme involves sharing equipment with existing power plants and reducing independent metering points, resulting in the worst settlement convenience. Table 4 compares different site access methods. Taking direct access node 1 as an example, the OCI for internal bundling is 0.7667 and MIS is 0.8750, while the OCI for multi-entity access is 0.6667 and MIS is 0.9091. Multi-entity access has poorer property rights clarity but better gateway independence compared to the bundling access scheme. Different access schemes need to be selected based on settlement requirements.

[0214] Table 4. Scenarios and Indicators of Station Main Organization Methods

[0215]

[0216] Table 4. Scenarios and Indicators of Station Main Organization Methods

[0217] This embodiment is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-dimensional evaluation method based on the wiring scheme of new energy power stations, characterized in that, The method includes: Collect sample data of wiring schemes for grid connection of new energy power plants; Based on the sample data of the wiring scheme, the wiring schemes of new energy power stations are classified to obtain the classified wiring schemes; Collect grid connection index data of new energy power stations, and construct multi-dimensional evaluation indicators for evaluating the new energy power stations based on the grid connection characteristics in the grid connection index data. The multi-dimensional evaluation indicators include at least economic indicators, reliability indicators and settlement convenience indicators. Based on the multi-dimensional evaluation indicators and the classified wiring schemes, simulation training is performed to generate grid connection simulation data corresponding to different wiring schemes, and a power grid model is created based on the grid connection simulation data. Based on the power grid model, the wiring scheme for the current grid connection is evaluated and calculated using multi-dimensional evaluation indicators, and the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators are determined. The multi-dimensional evaluation results include the evaluation results corresponding to the dimensions of economy, reliability and settlement convenience. The step of classifying the wiring schemes of new energy power plants based on the wiring scheme sample data to obtain the classified wiring schemes includes: Calculate the eigenvector centrality of each wiring scheme in the sample data of the wiring schemes; The wiring scheme sample data is classified according to the eigenvector centrality to determine the classified wiring scheme. Each wiring scheme includes at least one wiring node, and each wiring scheme has different connection relationships or topologies for different wiring nodes. The step of calculating the eigenvector centrality of each wiring scheme in the wiring scheme sample data includes: Based on the connection relationship or topology of different wiring nodes in the wiring scheme, calculate the local characteristic values ​​of the nodes in the wiring scheme. The formula for calculating the local eigenvalues ​​of the node is: ; Among them, the These are local eigenvalues ​​of the node; N represents the branch that the node is directly connected to in the power network, and N is the number of nodes in the wiring scheme. Calculate the global feature value of the node based on the local feature values ​​of the node; The formula for calculating the global feature value of the node is: ; Among them, the The global feature value of the node; The number of shortest paths between two adjacent nodes i and j; the global eigenvalues ​​of all nodes form an adjacency matrix. ; Based on the global feature values ​​of the nodes, calculate the eigenvector centrality corresponding to the wiring scheme; The formula for calculating the eigenvector centrality corresponding to the wiring scheme is: ; Among them, the For the desired eigenvector centrality, These are the eigenvalues ​​corresponding to the adjacency matrix; The multi-dimensional evaluation indicators include convenience indicators, which include property division clarity (OCI) and border independence (MIS). The steps of evaluating and calculating multi-dimensional evaluation indicators for the wiring scheme of the current grid connection based on the power grid model, and determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, include: Calculate the property rights division clarity (OCI) of the wiring scheme for the current grid connection of a new energy power station; Calculate the gate independence (MIS) of the wiring scheme for the current grid connection of the new energy power station; The evaluation results of the convenience index of the new energy power station wiring scheme are determined based on the property division clarity (OCI) and the gateway independence (MIS). The process of evaluating and calculating multi-dimensional evaluation indicators for the wiring scheme of the current grid connection based on the power grid model, and determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, also includes: The clarity of property rights division is measured by the number of different enterprises connected to the same line to measure the complexity of the network topology; the smaller the index, the more complex the network topology. The formula for calculating the clarity of the property division is as follows: , Among them, the This represents the number of enterprises connected to the i-th node. The maximum number of companies allowed; The independence of the checkpoints is used to measure the complexity of metering management by the ratio of the total number of independent metering points to the total number of metering points in the system. The formula for calculating the independence of the checkpoint is as follows: , Among them, the For independent measurement points, This represents the total number of measurement points.

2. The multi-dimensional evaluation method based on the wiring scheme of new energy power stations according to claim 1, characterized in that, The categorized wiring schemes include multiple access schemes classified according to different main organizational methods, access node locations, and access structure methods; According to the main organizational method of new energy power stations, the new energy connection scenarios include: typical forms of bundled access and multi-entity access; According to the location of the access node of the new energy power station, the new energy connection scenarios include: access to the main transmission network, access to the regional distribution network, access to the low-voltage distribution network, and access to the load-side node; According to the access structure of new energy power stations, the new energy connection scenarios include: direct access, series access, T-type access and Π-type access.

3. The multi-dimensional evaluation method based on the wiring scheme of new energy power stations according to claim 1, characterized in that, The multi-dimensional evaluation indicators include economic indicators, which include investment costs and daily returns, and the multi-dimensional evaluation results include the evaluation results of the economic indicators. The steps of evaluating and calculating multi-dimensional evaluation indicators for the wiring scheme of the current grid connection based on the power grid model, and determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, include: Calculate the investment cost of the wiring scheme for the current grid connection of the new energy power station; Calculate the daily revenue of the wiring scheme for the current grid connection of the new energy power station; The evaluation results of the economic indicators of the wiring scheme for the current grid connection of the new energy power station are determined based on the investment cost and the daily revenue.

4. The multi-dimensional evaluation method based on the wiring scheme of new energy power stations according to claim 3, characterized in that, The process of evaluating and calculating multi-dimensional evaluation indicators for the wiring scheme of the current grid connection based on the power grid model, and determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, also includes: The investment cost includes: total investment in the transmission line, in-plant step-up equipment, and power plant investment. The investment cost is calculated taking into account the depreciation formula. The formula for calculating investment costs is as follows: ; Among them, the , , These are investment in transmission lines, substations, and power plants, respectively, in yuan. It is the residual value rate; It refers to the service life, in years; It is a collection of routes; The daily revenue is the product of the grid-connected electricity price and the daily generated electricity, minus the operating costs, wherein the operating costs include grid losses and the power plant's operation and maintenance costs; The formula for calculating the operating costs is as follows: ， in, Let represent the power generation of the i-th generating unit at time t, in MW. Internet access loss rate; The time interval is expressed in hours (h). The figure represents the grid connection price, expressed in yuan / MWh; M represents the operation and maintenance cost of the power generation project, expressed in yuan. This is a collection of generator sets.

5. The multi-dimensional evaluation method based on the wiring scheme of new energy power stations according to claim 1, characterized in that, The multi-dimensional evaluation indicators include reliability indicators, which include resilience indicators composed of expected unsupplied power and average annual outage time. The multi-dimensional evaluation results include the evaluation results of the reliability indicators. The steps of evaluating and calculating multi-dimensional evaluation indicators for the wiring scheme of the current grid connection based on the power grid model, and determining the multi-dimensional evaluation results corresponding to the multi-dimensional evaluation indicators, include: The reliability index is calculated based on the resilience index, which is composed of the expected amount of unsupplied power and the average annual outage time.

6. A multi-dimensional evaluation method based on the wiring scheme of new energy power stations according to any one of claims 1 to 5, characterized in that, After determining the multidimensional evaluation results corresponding to the multidimensional evaluation indicators, the node classification multidimensional evaluation method based on the new energy power station wiring scheme further includes: The characteristics of the indicators in the multidimensional evaluation results are analyzed separately and comprehensively, and corresponding adjustment suggestions are determined. Based on the aforementioned adjustment recommendations, determine the target network connection scheme.

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