A method and system for determining power grid section limit parameters

Abstract

The application discloses a kind of power grid section limit parameter determination method and system, it is related to power grid data analysis technical field, including the synergistic relationship between analysis different power grid section each other, provide analysis basis for subsequent power flow calculation and unstable condition.According to the characteristics of section to define the calculation requirement level of each power grid section, ensure the adaptability and timeliness of power flow calculation.Combining power grid operating condition and power grid section operating condition to dynamically adjust the calculation requirement level of different section, to adjust the model parameters of different section, consider the operating condition fluctuation factor of both power grid operating condition and section operating condition to dynamically adjust model parameters, further ensure the reliability of power flow calculation.Combining the reference value of the limit parameter of section and the safety margin output the target value of the limit parameter of section, improve the accuracy and adaptability of power grid section limit parameter determination, ensure the safe and stable operation of power grid, improve power grid service quality.

Description

Technical Field

[0001] This invention relates to the field of power grid data analysis technology, and in particular to a method and system for determining the limiting parameters of a power grid section. Background Technology

[0002] In power grid operation, transmission sections serve as crucial channels for inter-regional power exchange, and the accurate determination of their limiting parameters is essential for ensuring the safe and stable operation of the power grid. With the expansion of the power grid and the large-scale integration of new energy sources, power fluctuations at transmission sections have intensified, making traditional limit calculation methods based on single operating conditions insufficient for practical needs. On the one hand, the thermal stability limit of the power grid is limited by the temperature resistance characteristics of equipment materials; excessive transmission power can easily lead to equipment damage. On the other hand, transient stability limits need to consider the stability of the initial swing after a fault, while dynamic stability limits involve low-frequency oscillation suppression. Furthermore, the volatility of new energy sources increases the error in power flow prediction at transmission sections, and traditional methods cannot effectively capture the nonlinear risks brought about by the interaction of global and local operating conditions.

[0003] Existing technologies do not take into account the correlation between different sections of the power grid and the changes in power grid operating conditions, resulting in poor accuracy and adaptability in determining the limit parameters of the power grid sections, and thus failing to effectively guarantee the safe operation of the power grid.

[0004] Therefore, improving the accuracy and adaptability of determining the limit parameters of power grid sections is a technical problem that needs to be solved. Summary of the Invention

[0005] The purpose of this invention is to address the problem of poor accuracy and adaptability in determining the limiting parameters of power grid sections in existing technologies, and to propose a method for determining the limiting parameters of power grid sections, the method comprising:

[0006] The topological structure information of the power grid is obtained, the power grid is divided into sections, multiple power grid sections are obtained, the synergistic relationship between different power grid sections is analyzed, and the power grid sections are divided into individual sections and related sections.

[0007] Perform characteristic analysis on each power grid section, define the computational demand level for each power grid section, construct a power flow calculation model for the power grid, and configure the model parameters for different sections under the power flow calculation model according to the computational demand level.

[0008] Define the power grid operating conditions and power grid section operating conditions, and combine the power grid operating conditions and power grid section operating conditions to dynamically adjust the calculation requirement level of different sections, thereby adjusting the model parameters of different sections.

[0009] The baseline values ​​of the limit parameters of each section are obtained by using the power flow calculation model, the instability of the cooperative relationship under the associated sections is captured, and the safety margin of the limit parameters of each section is generated.

[0010] The target values ​​of the limit parameters of the cross section are output by combining the baseline values ​​of the limit parameters and the safety margin.

[0011] In some embodiments of this application, the power grid is divided into cross-sections to obtain multiple power grid cross-sections, including,

[0012] Based on the power transmission path or control area of ​​the power grid topology, multiple sections are divided. Graphviz is used to draw the power exchange path between sections, determine the correspondence between sections and nodes and paths, and generate a section topology map.

[0013] In some embodiments of this application, the synergistic relationship between different power grid sections is analyzed, and the power grid sections are divided into individual sections and related sections, including...

[0014] Based on the cross-sectional topology map, a synergistic effect model between different power grid cross sections is established to analyze the synergistic effect relationship between different power grid cross sections, and to determine and quantify the synergistic effect index of multiple synergistic effect relationships.

[0015] The intensity of synergy is determined by combining multiple synergy indicators, and the power grid sections are divided into individual sections and associated sections based on the intensity and relationship of synergy.

[0016] In some embodiments of this application, characteristic analysis is performed on each power grid section, including:

[0017] Characteristic analysis includes four dimensions: electrical characteristics, operating status, dynamic response, and topology.

[0018] Collect all descriptive parameters for each of the four dimensions of electrical characteristics, operating status, dynamic response, and topology, and determine the time scale range for each of the four dimensions of electrical characteristics, operating status, dynamic response, and topology;

[0019] The fluctuation characteristics of each descriptive parameter under each dimension are statistically analyzed according to the time scale range. Based on the fluctuation characteristics, all descriptive parameters under each dimension are divided into two categories: stable descriptive parameters and fluctuating descriptive parameters.

[0020] The values ​​of the two types of parameters, namely the stability description parameter and the fluctuation description parameter, are determined. Based on the values ​​of the fluctuation description parameter, the representative values ​​of the fluctuation description parameter are calculated. The calculation requirements of each dimension under the four dimensions of electrical characteristics, operating status, dynamic response, and topology are analyzed by combining the values ​​of the stability description parameter and the representative values ​​of the fluctuation description parameter.

[0021] In some embodiments of this application, the computational requirement level for each power grid section is defined, including:

[0022] The computational difficulty of each dimension is assessed by evaluating the values ​​of stability description parameters and representative values ​​of fluctuation description parameters under the four dimensions of electrical characteristics, operating status, dynamic response, and topology. The computational difficulty of each dimension under the four dimensions of electrical characteristics, operating status, dynamic response, and topology is integrated to define the computational requirement level of each power grid section.

[0023] In some embodiments of this application, power grid operating conditions and power grid section operating conditions are defined, including:

[0024] The relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are statistically analyzed separately. The relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are divided into intervals, and the intervals of the relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are combined to obtain the operation condition combination.

[0025] Collect historical failure data for each operating condition combination, calculate the failure probability for each operating condition combination, and map the failure probability to a coupling correction term.

[0026] The relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are normalized.

[0027] In some embodiments of this application, the computational demand levels for different sections are dynamically adjusted by combining the power grid operating conditions and the operating conditions of power grid sections, including:

[0028] The relevant parameters of the power grid operating conditions and the relevant parameters of the power grid section operating conditions are weighted separately. Based on the weighted values ​​of the power grid operating conditions and the power grid section operating conditions, a coupling correction term is added to determine whether the calculation requirement level needs to be adjusted.

[0029] In some embodiments of this application, the instability of the cooperative relationship under associated cross-sections is captured, and a safety margin for the limit parameters of each cross-section is generated, including,

[0030] Unstable indicators related to the synergistic relationship under the associated cross sections are screened out, and the safety margin of the limit parameters is determined by comprehensively considering the unstable indicators.

[0031] Correspondingly, this application also provides a system for determining the limiting parameters of a power grid section, including,

[0032] The first module is used to obtain the topological structure information of the power grid, divide the power grid into sections, obtain multiple power grid sections, analyze the synergistic relationship between different power grid sections, and divide the power grid sections into individual sections and related sections.

[0033] The second module is used to perform characteristic analysis on each power grid section, define the calculation requirement level of each power grid section, construct the power flow calculation model of the power grid, and configure the model parameters of different sections under the power flow calculation model according to the calculation requirement level.

[0034] The third module is used to define the power grid operating conditions and the power grid section operating conditions. By combining the power grid operating conditions and the power grid section operating conditions, the calculation requirement level of different sections is dynamically adjusted, thereby adjusting the model parameters of different sections.

[0035] The fourth module is used to obtain the baseline values ​​of the limit parameters of each section through the power flow calculation model, capture the instability of the cooperative relationship under the associated sections, and generate the safety margin of the limit parameters of each section.

[0036] The fifth module is used to combine the baseline values ​​of the limit parameters of the cross section with the safety margin to output the target values ​​of the limit parameters of the cross section.

[0037] This application has the following beneficial effects:

[0038] 1. Analyze the interrelationships between different power grid sections to provide an analytical basis for subsequent power flow calculations and instability scenarios. Define the calculation requirement level for each power grid section based on its characteristics to ensure the adaptability and timeliness of power flow calculations.

[0039] 2. By dynamically adjusting the calculation requirement levels of different cross-sections in conjunction with the operating conditions of the power grid and the operating conditions of power grid cross-sections, the model parameters of different cross-sections are adjusted. The dynamic adjustment of model parameters takes into account the fluctuation factors of both the power grid operating conditions and the cross-section operating conditions, further ensuring the reliability of power flow calculations. The instability of the cooperative relationship under associated cross-sections is captured to determine the safety margin of the limit parameters. Combined with the baseline value of the limit parameters of the cross-sections and the safety margin, the target value of the limit parameters of the cross-sections is output, improving the accuracy and adaptability of determining the limit parameters of the power grid cross-sections, ensuring the safety and stability of power grid operation, and improving the quality of power grid service. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating a method for determining the limit parameters of a power grid section proposed in this invention.

[0041] Figure 2 This is a schematic diagram of the structure of a power grid cross-sectional limit parameter determination system proposed in this invention. Detailed Implementation

[0042] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0043] Reference Figure 1 A method for determining the limiting parameters of a power grid section includes the following steps:

[0044] Step S101: Obtain the topology information of the power grid, divide the power grid into sections to obtain multiple power grid sections, analyze the synergistic relationship between different power grid sections, and divide the power grid sections into individual sections and related sections.

[0045] In this embodiment, a power grid section refers to a collection of transmission lines, transformers, and other components with specific electrical or physical connections within the power grid. These components collectively undertake key tasks such as inter-regional power transmission and energy exchange, and their power flow (active power and reactive power) transmission characteristics are interconnected and mutually influential. Topology information includes static and dynamic data. Static data includes a CIM / XML format power grid model (containing node, line, and transformer parameters); dynamic data includes SCADA real-time topology (switch status, line operation status) and PMU measurement data (voltage amplitude, phase angle, and power).

[0046] In some embodiments of this application, the power grid is divided into cross-sections to obtain multiple power grid cross-sections, including,

[0047] Based on the power transmission path or control area of ​​the power grid topology, multiple sections are divided. Graphviz is used to draw the power exchange path between sections, determine the correspondence between sections and nodes and paths, and generate a section topology map.

[0048] In this embodiment, the cross-section division method is based on power transmission paths: identifying key transmission corridors (such as inter-regional interconnection lines and new energy aggregation channels); merging multiple lines in the same corridor into a single cross-section (such as the East China-Central China 1000kV interconnection line cross-section). It is also based on control areas: dividing according to regional conditions, for example, dividing cross-sections by provincial dispatching zones (such as Jiangsu Power Grid and Zhejiang Power Grid); and refining to prefecture-level cross-sections (such as Nanjing Power Grid and Hangzhou Power Grid). Different cross-sections correspond to different nodes and paths or routes; for example, cross-section A corresponds to nodes 1-10 and lines L1-L5, etc.

[0049] In some embodiments of this application, the synergistic relationship between different power grid sections is analyzed, and the power grid sections are divided into individual sections and related sections, including...

[0050] Based on the cross-sectional topology map, a synergistic effect model between different power grid cross sections is established to analyze the synergistic effect relationship between different power grid cross sections, and to determine and quantify the synergistic effect index of multiple synergistic effect relationships.

[0051] The intensity of synergy is determined by combining multiple synergy indicators, and the power grid sections are divided into individual sections and associated sections based on the intensity and relationship of synergy.

[0052] In this embodiment, the synergistic interaction model includes a power coupling model, a dynamic response model, and a fault propagation model (analyzing the strength of power interaction between cross sections, quantifying the mutual influence of dynamic stability between cross sections, and assessing the risk of fault cascading reactions between cross sections). Synergistic interaction indicators include power coupling degree, voltage coupling degree, dynamic response synchronization (frequency deviation correlation coefficient), and power deficit. First, the above models are used to analyze which cross sections have synergistic interaction relationships (candidates). From these candidate relationships, stronger relationships are selected. Multiple synergistic interaction indicators are then combined to determine the synergistic interaction strength. The calculation formula is as follows:

[0053] ;

[0054] in, For the first The strength of synergy among the candidate synergistic relationships. For the first The number of synergy indicators under each alternative synergy relationship. For the first The combined weights of the synergistic effect indicators, For the first The first alternative synergistic relationship The magnitude of each synergistic effect indicator for The maximum value in, For the first The first constant corresponding to each of the alternative cooperative relationships (used to balance the magnitude of the correction function). This represents the correction of the average value of the synergy index by the maximum effect of the synergy index, with a value range between 1.134 and 1.259.

[0055] Step S102: Perform characteristic analysis on each power grid section, define the calculation requirement level for each power grid section, construct the power flow calculation model of the power grid, and configure the model parameters for different sections under the power flow calculation model according to the calculation requirement level.

[0056] In this embodiment, using differentiated model parameters (such as iteration count, convergence threshold, algorithm type, etc.) for different cross-sections in power grid power flow calculation has the following advantages:

[0057] 1. Optimize computational efficiency, avoid excessive iteration on simple cross sections, fully solve complex cross sections, and reduce global computation time.

[0058] 2. Precise resource allocation: GPU / CPU computing power is concentrated and allocated to high-complexity sections to improve hardware resource utilization.

[0059] 3. Accuracy-efficiency balance: High-precision models (such as the third harmonic method) are used for sections with high penetration rates of new energy sources, while fast algorithms (such as the PQ decomposition method) are used for traditional sections.

[0060] 4. Dynamic risk management: set stricter convergence thresholds (e.g., 1e-6) for sections with high failure rates, and relax thresholds (e.g., 1e-4) for stable sections.

[0061] In some embodiments of this application, characteristic analysis is performed on each power grid section, including:

[0062] Characteristic analysis includes four dimensions: electrical characteristics, operating status, dynamic response, and topology.

[0063] Collect all descriptive parameters for each of the four dimensions of electrical characteristics, operating status, dynamic response, and topology, and determine the time scale range for each of the four dimensions of electrical characteristics, operating status, dynamic response, and topology;

[0064] The fluctuation characteristics of each descriptive parameter under each dimension are statistically analyzed according to the time scale range. Based on the fluctuation characteristics, all descriptive parameters under each dimension are divided into two categories: stable descriptive parameters and fluctuating descriptive parameters.

[0065] The values ​​of the two types of parameters, namely the stability description parameter and the fluctuation description parameter, are determined. Based on the values ​​of the fluctuation description parameter, the representative values ​​of the fluctuation description parameter are calculated. The calculation requirements of each dimension under the four dimensions of electrical characteristics, operating status, dynamic response, and topology are analyzed by combining the values ​​of the stability description parameter and the representative values ​​of the fluctuation description parameter.

[0066] In this embodiment, the electrical characteristics, with core descriptive parameters including voltage amplitude (V), phase angle (θ), line impedance (Z), and transformer ratio (k), are described on a time scale ranging from seconds to minutes (1s-10min). Typical variation characteristics include voltage / phase angle fluctuations and stable impedance. The operating status, with core descriptive parameters including active power (P), reactive power (Q), load factor (L), and node injected power (S), is described on a time scale ranging from minutes to hours (1min-24h). Typical fluctuation characteristics include dynamic power changes and periodic load factor fluctuations. The dynamic response, with core descriptive parameters including frequency deviation (Δf), transient voltage drop (Vsag), and damping ratio (ζ), is described on a time scale ranging from milliseconds to seconds (1ms-10s). Typical fluctuation characteristics include rapid transient fluctuations and damping attenuation. The topology, with core descriptive parameters including node degree (di), number of branches (Nb), number of loops (L), and critical branch percentage (rcrit), is described on a time scale ranging from hours to days (1h-7d). Typical fluctuation characteristics: structurally stable, with planned topological adjustments. Fluctuations are described based on the standard deviation, peak-to-trough difference, and other typical fluctuation characteristics over a time scale, thus distinguishing between stability-descriptive parameters and fluctuation-descriptive parameters.

[0067] Stability description parameter: fluctuation range within the time scale is less than the threshold (e.g., voltage amplitude fluctuation < ±1%).

[0068] Fluctuation description parameter: Fluctuation range exceeds the threshold (e.g., power fluctuation > ±10%).

[0069] Based on the values ​​of the fluctuation description parameters, the representative values ​​of the fluctuation description parameters are calculated. The representative values ​​are extracted by weighted moving average. The active power of a certain section fluctuates in 1 hour as [100, 120, 90, 110] MW, and the representative value is calculated as 105 MW (weight attenuation coefficient λ=0.1).

[0070] In some embodiments of this application, the computational requirement level for each power grid section is defined, including:

[0071] The computational difficulty of each dimension is assessed by evaluating the values ​​of stability description parameters and representative values ​​of fluctuation description parameters under the four dimensions of electrical characteristics, operating status, dynamic response, and topology. The computational difficulty of each dimension under the four dimensions of electrical characteristics, operating status, dynamic response, and topology is integrated to define the computational requirement level of each power grid section.

[0072] In this embodiment, based on the parameter calculation difficulty assessment of four dimensions (electrical characteristics, operating status, dynamic response, and topology), the Computational Demand Level of Power Grid Section is defined through hierarchical quantification and dimensional integration. The calculation formula is as follows:

[0073] ;

[0074] in, For the first The cross-sectional calculation requirement level for each section. , , , The weights are combined across four dimensions: electrical characteristics, operating status, dynamic response, and topology. , , , The computational difficulty is categorized into four dimensions: electrical characteristics, operating status, dynamic response, and topology. , They are respectively The maximum and minimum values ​​among the four. , These are the second and third constants (used to calculate the demand level and correction function, respectively). This represents the correction of the sum of the four values ​​to the average of the four values, with a value range of 0.832-1.267. [] is the rounding symbol.

[0075] Step S103: Define the power grid operating conditions and power grid section operating conditions. Combine the power grid operating conditions and power grid section operating conditions to dynamically adjust the calculation requirement level of different sections, thereby adjusting the model parameters of different sections.

[0076] In this embodiment, the computational requirements will change with the continuous changes in the power grid conditions and cross-section conditions. It is necessary to adjust the model parameters of the cross-section in a timely manner to ensure the reliability of power flow calculation. Different combinations of model parameters correspond to different computational requirement levels.

[0077] In some embodiments of this application, power grid operating conditions and power grid section operating conditions are defined, including:

[0078] The relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are statistically analyzed separately. The relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are divided into intervals, and the intervals of the relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are combined to obtain the operation condition combination.

[0079] Collect historical failure data for each operating condition combination, calculate the failure probability for each operating condition combination, and map the failure probability to a coupling correction term.

[0080] The relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are normalized.

[0081] In some embodiments of this application, the computational demand levels for different sections are dynamically adjusted by combining the power grid operating conditions and the operating conditions of power grid sections, including:

[0082] The relevant parameters of the power grid operating conditions and the relevant parameters of the power grid section operating conditions are weighted separately. Based on the weighted values ​​of the power grid operating conditions and the power grid section operating conditions, a coupling correction term is added to determine whether the calculation requirement level needs to be adjusted.

[0083] In this embodiment, grid operating condition parameters include overall grid load factor, average frequency deviation, and N-1 throughput, while grid section operating condition parameters include power flow parameters, equipment status parameters, and dynamic response parameters. A fault-operating condition mapping table is established to record the fault type (e.g., transient instability, equipment overload) and frequency under each operating condition combination. Bayesian networks or random forests are used to calculate conditional fault probabilities, which are then mapped to calculate demand adjustment coefficients (coupling correction terms).

[0084] In this embodiment, a coupling correction term is added based on the weighted value of the power grid operating conditions and the power grid section operating conditions to determine whether the calculation demand level needs to be adjusted. A standard calculation demand level is determined, and the deviation between the standard calculation demand level and the current calculation demand level is compared to see if it is within a reasonable range, thereby determining whether adjustment is needed.

[0085] ;

[0086] in, For the first The standard calculation requirement level corresponding to each cross section , These are the weighted values ​​of the power grid operating conditions and the first... The weighted value of the operating conditions of the power grid section corresponding to each section. To adjust the coefficient, For the first The fourth constant corresponding to each cross section is used to balance the standard calculation of the required level. [] is the rounding symbol.

[0087] Step S104: Obtain the baseline values ​​of the limit parameters for each section through the power flow calculation model, capture the instability of the cooperative relationship under the associated sections, and generate the safety margin of the limit parameters for each section.

[0088] In some embodiments of this application, the instability of the cooperative relationship under associated cross-sections is captured, and a safety margin for the limit parameters of each cross-section is generated, including,

[0089] Unstable indicators related to the synergistic relationship under the associated cross sections are screened out, and the safety margin of the limit parameters is determined by comprehensively considering the unstable indicators.

[0090] In this embodiment, real-time operating condition adaptation is achieved: traditional margins use a fixed percentage (e.g., 15%), while this solution dynamically adjusts the margin based on real-time operating condition combinations (e.g., increasing the safety margin to 25% under heavy load conditions). Risk-cost balance is achieved by coupling correction terms to transform failure probabilities into computational requirements, thereby affecting the safety margin (e.g., for every 1% increase in failure probability, the safety margin increases by 0.8%). Synergistic effects are made explicit: traditional methods only perform N-1 or N-2 fault analysis on a single section, ignoring the risk of cascading failures across multiple sections. This solution, through the identification of associated sections and modeling of synergistic effects, can quantify the power flow transfer risk between multiple sections (e.g., the probability of a failure in section A leading to overload in section B increases by 37%).

[0091] In this embodiment, the instability indicators include power transfer instability (TSM), voltage control instability (VCM), power transfer distribution factor, and power transfer distribution factor. These instability indicators are weighted and summed to map a safety margin level. Different levels correspond to different safety margins with different limiting parameters.

[0092] Step S105: Combine the baseline values ​​of the limit parameters of the cross section with the safety margin to output the target values ​​of the limit parameters of the cross section.

[0093] In this embodiment, the baseline value + safety margin (positive or negative) = target value. The target value of the limiting parameter is the determined value of the limiting parameter.

[0094] Correspondingly, this application also provides a system for determining the limiting parameters of a power grid section, such as... Figure 2 The diagram includes,

[0095] The first module is used to obtain the topological structure information of the power grid, divide the power grid into sections, obtain multiple power grid sections, analyze the synergistic relationship between different power grid sections, and divide the power grid sections into individual sections and related sections.

[0096] The second module is used to perform characteristic analysis on each power grid section, define the calculation requirement level of each power grid section, construct the power flow calculation model of the power grid, and configure the model parameters of different sections under the power flow calculation model according to the calculation requirement level.

[0097] The third module is used to define the power grid operating conditions and the power grid section operating conditions. By combining the power grid operating conditions and the power grid section operating conditions, the calculation requirement level of different sections is dynamically adjusted, thereby adjusting the model parameters of different sections.

[0098] The fourth module is used to obtain the baseline values ​​of the limit parameters of each section through the power flow calculation model, capture the instability of the cooperative relationship under the associated sections, and generate the safety margin of the limit parameters of each section.

[0099] The fifth module is used to combine the baseline values ​​of the limit parameters of the cross section with the safety margin to output the target values ​​of the limit parameters of the cross section.

[0100] This application has the following beneficial effects:

[0101] This study analyzes the interrelationships between different power grid sections to provide a foundation for subsequent power flow calculations and instability assessments. The computational requirement level for each power grid section is defined based on its characteristics to ensure the adaptability and timeliness of power flow calculations.

[0102] By combining the operating conditions of the power grid and the operating conditions of different power grid sections, the computational demand levels of different sections are dynamically adjusted, thereby adjusting the model parameters of different sections. The dynamic adjustment of model parameters takes into account the fluctuation factors of both the power grid operating conditions and the operating conditions of the sections, further ensuring the reliability of power flow calculations. The instability of the cooperative relationship under associated sections is captured to determine the safety margin of the limit parameters. Combining the baseline value of the limit parameters of the sections with the safety margin, the target value of the limit parameters of the sections is output, improving the accuracy and adaptability of determining the limit parameters of the power grid sections, ensuring the safety and stability of power grid operation, and improving the quality of power grid service.

[0103] Through the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented in hardware or by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, portable hard drive, etc.) and includes several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0104] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing the present invention.

[0105] Those skilled in the art will understand that the modules in the system of the implementation scenario can be distributed throughout the system of the implementation scenario as described, or they can be modified to reside in one or more systems different from this implementation scenario. The modules of the above-mentioned implementation scenario can be merged into one module, or they can be further divided into multiple sub-modules.

[0106] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for determining the limiting parameters of a power grid cross section, characterized in that, include, The topological structure information of the power grid is obtained, the power grid is divided into sections, multiple power grid sections are obtained, the synergistic relationship between different power grid sections is analyzed, and the power grid sections are divided into individual sections and related sections. Perform characteristic analysis on each power grid section, define the computational demand level for each power grid section, construct a power flow calculation model for the power grid, and configure the model parameters for different sections under the power flow calculation model according to the computational demand level. Define the power grid operating conditions and power grid section operating conditions, and combine the power grid operating conditions and power grid section operating conditions to dynamically adjust the calculation requirement level of different sections, thereby adjusting the model parameters of different sections. The baseline values ​​of the limit parameters of each section are obtained by using the power flow calculation model, the instability of the cooperative relationship under the associated sections is captured, and the safety margin of the limit parameters of each section is generated. The target values ​​of the limit parameters of the cross section are output by combining the baseline values ​​of the limit parameters and the safety margin.

2. The method for determining the limiting parameters of a power grid section according to claim 1, characterized in that, The power grid is divided into sections, resulting in multiple power grid sections, including: Based on the power transmission path or control area of ​​the power grid topology, multiple sections are divided. Graphviz is used to draw the power exchange path between sections, determine the correspondence between sections and nodes and paths, and generate a section topology map.

3. The method for determining the limiting parameters of a power grid section according to claim 2, characterized in that, This analysis examines the synergistic relationships between different power grid sections, categorizing them into individual sections and interconnected sections. Based on the cross-sectional topology map, a synergistic effect model between different power grid cross sections is established to analyze the synergistic effect relationship between different power grid cross sections, and to determine and quantify the synergistic effect index of multiple synergistic effect relationships. The intensity of synergy is determined by combining multiple synergy indicators, and the power grid sections are divided into individual sections and associated sections based on the intensity and relationship of synergy.

4. The method for determining the limiting parameters of a power grid section according to claim 1, characterized in that, Characteristic analysis is performed on each power grid section, including: Characteristic analysis includes four dimensions: electrical characteristics, operating status, dynamic response, and topology. Collect all descriptive parameters for each of the four dimensions of electrical characteristics, operating status, dynamic response, and topology, and determine the time scale range for each of the four dimensions of electrical characteristics, operating status, dynamic response, and topology; The fluctuation characteristics of each descriptive parameter under each dimension are statistically analyzed according to the time scale range. Based on the fluctuation characteristics, all descriptive parameters under each dimension are divided into two categories: stable descriptive parameters and fluctuating descriptive parameters. The values ​​of the two types of parameters, namely the stability description parameter and the fluctuation description parameter, are determined. Based on the values ​​of the fluctuation description parameter, the representative values ​​of the fluctuation description parameter are calculated. The calculation requirements of each dimension under the four dimensions of electrical characteristics, operating status, dynamic response, and topology are analyzed by combining the values ​​of the stability description parameter and the representative values ​​of the fluctuation description parameter.

5. The method for determining the limiting parameters of a power grid section according to claim 4, characterized in that, And define the computational requirement level for each power grid section, including, The computational difficulty of each dimension is assessed by evaluating the values ​​of stability description parameters and representative values ​​of fluctuation description parameters under the four dimensions of electrical characteristics, operating status, dynamic response, and topology. The computational difficulty of each dimension under the four dimensions of electrical characteristics, operating status, dynamic response, and topology is integrated to define the computational requirement level of each power grid section.

6. The method for determining the limiting parameters of a power grid section according to claim 1, characterized in that, Define the operating conditions of the power grid and the operating conditions of power grid sections, including: The relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are statistically analyzed separately. The relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are divided into intervals, and the intervals of the relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are combined to obtain the operation condition combination. Collect historical failure data for each operating condition combination, calculate the failure probability for each operating condition combination, and map the failure probability to a coupling correction term. The relevant parameters of power grid operation conditions and the relevant parameters of power grid section operation conditions are normalized.

7. The method for determining the limiting parameters of a power grid section according to claim 6, characterized in that, The calculation requirement levels for different power grid sections are dynamically adjusted based on both the overall power grid operating conditions and the operating conditions of specific power grid sections. The relevant parameters of the power grid operating conditions and the relevant parameters of the power grid section operating conditions are weighted separately. Based on the weighted values ​​of the power grid operating conditions and the power grid section operating conditions, a coupling correction term is added to determine whether the calculation requirement level needs to be adjusted.

8. The method for determining the limiting parameters of a power grid section according to claim 1, characterized in that, To capture the instability of the cooperative relationship under the associated cross-section, and generate the safety margin of the limit parameters for each cross-section. include, Unstable indicators related to the synergistic relationship under the associated cross sections are screened out, and the safety margin of the limit parameters is determined by comprehensively considering the unstable indicators.

9. A system for determining the limiting parameters of a power grid section, characterized in that, include, The first module is used to obtain the topological structure information of the power grid, divide the power grid into sections, obtain multiple power grid sections, analyze the synergistic relationship between different power grid sections, and divide the power grid sections into individual sections and related sections. The second module is used to perform characteristic analysis on each power grid section, define the calculation requirement level of each power grid section, construct the power flow calculation model of the power grid, and configure the model parameters of different sections under the power flow calculation model according to the calculation requirement level. The third module is used to define the power grid operating conditions and the power grid section operating conditions. By combining the power grid operating conditions and the power grid section operating conditions, the calculation requirement level of different sections is dynamically adjusted, thereby adjusting the model parameters of different sections. The fourth module is used to obtain the baseline values ​​of the limit parameters of each section through the power flow calculation model, capture the instability of the cooperative relationship under the associated sections, and generate the safety margin of the limit parameters of each section. The fifth module is used to combine the baseline values ​​of the limit parameters of the cross section with the safety margin to output the target values ​​of the limit parameters of the cross section.

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