Adaptive power distribution method and system for new energy direct current convergence delivery system

Abstract

The invention relates to the technical field of direct current transmission of a new energy power system, and particularly discloses a self-adaptive power distribution method and system for a new energy direct current convergence delivery system, and the method comprises the steps: obtaining the real-time operation state data of a converter station of the new energy direct current convergence delivery system, the real-time operation state data of the converter stations comprises transmitting and receiving end frequency deviation of a direct-current power grid, direct-current network voltage deviation and active power and reactive power output values of the converter stations; acquiring operation characteristic information of each converter station according to the real-time operation state data of the converter stations; and obtaining the adjustable capacity of the converter station according to the operation characteristic information, and constructing an adjustment control network according to the adjustable capacity corresponding to each converter station. According to the method, the system operation state data is acquired in real time, the regulation control network is constructed, the power distribution limit value and the optimal value of each converter station are dynamically optimized, the balance degree table is established in combination with the frequency response test rate, and finally power distribution regulation based on the optimal working condition is realized.

Description

Technical Field

[0001] This invention relates to the field of DC power transmission technology for new energy power systems, and in particular to an adaptive power allocation method and system for a new energy DC aggregation and transmission system. Background Technology

[0002] With the rapid expansion of new energy power generation, large-scale new energy bases have adopted DC transmission systems for power transmission, which has become a typical application model. New energy DC aggregation and transmission systems aggregate distributed new energy power generation units through multiple converter stations and transmit them to remote load centers.

[0003] Traditional power allocation methods primarily employ fixed power allocation coefficients or simple droop control strategies, which have significant limitations. First, they lack the ability to dynamically perceive the real-time operating status of the system and cannot respond promptly to changes in key parameters such as frequency deviation and voltage fluctuations. Furthermore, existing technologies exhibit significant shortcomings in system coordination control. Traditional control strategies focus on the operating status of a single converter station, lacking a comprehensive analysis of the overall system's operating characteristics. When power fluctuations occur, insufficient coordination between converter stations can easily lead to unreasonable power allocation, affecting the stable operation of the system. Summary of the Invention

[0004] The purpose of this invention is to provide an adaptive power allocation method and system for a new energy DC aggregation and transmission system, so as to solve the technical problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] An adaptive power allocation method for a new energy DC aggregation and transmission system, wherein the DC aggregation and transmission system includes multiple converter stations, and each converter station is connected to a new energy power generation unit and a DC grid, comprising:

[0007] The real-time operating status data of the converter stations of the new energy DC aggregation and transmission system are obtained. The real-time operating status data of the converter stations includes the frequency deviation of the DC grid at the sending and receiving ends, the voltage deviation of the DC network, and the active power and reactive power output values ​​of each converter station.

[0008] The operational characteristic information of each converter station is obtained based on the real-time operational status data of the converter stations;

[0009] The adjustable capacity of the converter station is obtained based on the operational characteristic information, and an adjustment control network is constructed based on the adjustable capacity corresponding to each converter station.

[0010] The power allocation limit for each converter station is obtained based on the regulation and control network, and the optimal power allocation value for each converter station is obtained based on the power allocation limit.

[0011] The power regulation test range is obtained based on the optimal power allocation value, and the frequency response test rate of each converter station is obtained from the power regulation test range based on the frequency deviation between the sending and receiving ends.

[0012] A converter station equalization table is established based on the corresponding frequency response test rate of each converter station, and the power regulation processing range of each converter station is obtained based on the converter station equalization table.

[0013] The optimal operating condition information of the converter station is obtained based on the power regulation processing range of the converter station, and the power distribution of the converter station is adjusted based on the optimal operating condition information of the converter station.

[0014] Preferably, the step of obtaining the operating characteristic information of each converter station based on the real-time operating status data of the converter stations includes:

[0015] The operating parameter sequence of each converter station is obtained based on the real-time operating status data of the converter station. The operating parameter sequence includes an active power output value sequence, a reactive power output value sequence, a DC voltage measurement value sequence, and a DC side frequency measurement value sequence.

[0016] The power fluctuation characteristics of each converter station are obtained based on the active power output value sequence and the reactive power output value sequence, wherein the power fluctuation characteristics include the power change rate statistics and the power fluctuation amplitude index.

[0017] The voltage stability coefficient of each converter station node is obtained based on the DC voltage measurement value sequence;

[0018] The frequency response characteristics of each converter station are obtained based on the DC side frequency measurement sequence, including the average frequency deviation and the maximum frequency change rate.

[0019] A multi-dimensional operation feature vector for each converter station is generated based on power fluctuation characteristics, voltage stability coefficient, and frequency response characteristics.

[0020] The multi-dimensional operational feature vectors are normalized to obtain standardized operational feature information.

[0021] Preferably, the step of obtaining the adjustable capacity of the converter stations based on the operational characteristic information, and constructing a regulation and control network based on the adjustable capacity of each converter station, includes:

[0022] Obtain the preset safe operating threshold for converter stations, and obtain the power regulation range for each converter station based on the preset safe operating threshold, rate fluctuation characteristics, and voltage stability coefficient;

[0023] The adjustment influence coefficient of each converter station in the system frequency regulation process is obtained based on the frequency response characteristics, and the adjustable capacity of the converter station is obtained based on the adjustment influence coefficient and the power regulation range.

[0024] Based on the adjustable capacity, the corresponding converter stations are divided to obtain a capacity control hierarchy, wherein the capacity control hierarchy includes a backbone regulation layer, a regional coordination layer and a local response layer.

[0025] Obtain the electrical distance between converter stations, and determine the hierarchical affiliation of each converter station in the DC grid based on the electrical distance and capacity control level, thereby generating a hierarchical control structure framework;

[0026] A coordination control mechanism between converter stations is generated based on a hierarchical control structure, wherein the coordination control mechanism includes power allocation priority setting, adjustment response time configuration, and reserve capacity allocation rules.

[0027] The information interaction protocol and control command transmission path are obtained based on the hierarchical control structure framework, and a regulation and control network is constructed based on the coordination control mechanism, information interaction protocol and control command transmission path.

[0028] Preferably, the steps of obtaining the power allocation limit for each converter station based on the regulation and control network, and obtaining the optimal power allocation value for each converter station based on the power allocation limit, include:

[0029] The hierarchical affiliation information of each converter station is obtained according to the regulation and control network, and the power allocation coefficients corresponding to the backbone regulation layer, regional coordination layer and local response layer are obtained. The initial power allocation limit of each converter station is generated according to the power allocation coefficients.

[0030] The frequency and voltage deviations in the real-time operating status data of the converter stations are obtained, and the power regulation demand values ​​are obtained based on the adjustable capacity of each converter station.

[0031] The dynamic power allocation adjustment amount for each converter station is obtained based on the power regulation demand value and the initial power allocation limit, and the power allocation limit for real-time operation is obtained based on the dynamic power allocation adjustment amount.

[0032] Obtain preset operating constraints, including converter station capacity limits, transmission line thermal stability limits, and power grid safety operation requirements. Generate a power allocation constraint set based on the preset operating constraints, and verify the power allocation limit through the power allocation constraint set to obtain corrected power allocation limits that exclude those exceeding the safe operation range.

[0033] The optimal power allocation value for each converter station is obtained based on the modified power allocation limit.

[0034] Preferably, the steps of obtaining the power regulation test range based on the optimal power allocation value, and obtaining the frequency response test rate of each converter station from the power regulation test range based on the frequency deviation between the sending and receiving ends, include:

[0035] Obtain the percentage fluctuation above and below the optimal power allocation value, and obtain the power adjustment test range based on the percentage fluctuation above and below;

[0036] Based on the power regulation test range, obtain the frequency deviation data under real-time operating conditions, and obtain the nominal frequency disturbance amplitude during the test process based on the frequency deviation data;

[0037] The nominal frequency disturbance is obtained at each power regulation test point based on the nominal frequency disturbance amplitude, and the frequency response process data of each converter station is obtained based on the nominal frequency disturbance.

[0038] Frequency response characteristic parameters are obtained based on frequency response process data, including maximum frequency deviation, frequency recovery time, and power adjustment rate. Frequency response evaluation indexes for each power adjustment test point are calculated based on the frequency response characteristic parameters.

[0039] The frequency response test rate of each converter station is obtained based on the frequency response evaluation index of all power regulation test points.

[0040] Establish a correspondence table between frequency response test rate and power regulation test point, identify the power regulation area with the highest frequency response test rate, and obtain the optimal power regulation range of each converter station by analyzing the data distribution characteristics in the correspondence table.

[0041] The power regulation range for each converter station is generated based on the optimal power regulation range and frequency response test rate.

[0042] Preferably, the steps of establishing a converter station equalization table based on the corresponding frequency response test rate of each converter station, and obtaining the corresponding converter station power regulation processing range for each converter station based on the converter station equalization table, include:

[0043] Obtain frequency response test rate data for each converter station at different power regulation test points, and obtain frequency response stability index for each converter station at each power level based on the frequency response test rate data.

[0044] Obtain the adjustable capacity data for each converter station, and obtain the power regulation balance of each converter station based on the frequency response stability index and the adjustable capacity data;

[0045] Based on the power regulation balance, each converter station is classified into the corresponding balance level, and a converter station balance table is generated.

[0046] The data distribution characteristics are obtained from the converter station balance table. Based on the data distribution characteristics, a group of converter stations with high balance levels are identified, and the location information of each converter station is determined based on the optimal power allocation value.

[0047] The set power regulation coefficient for each converter is obtained based on the location information, and the power regulation responsibility range of each converter station is obtained based on the set power regulation coefficient and the adjustable capacity data.

[0048] Based on the power regulation responsibility scope, the upper and lower limits of power regulation for each converter station are obtained, and a power regulation processing range is generated.

[0049] Preferably, the step of obtaining the optimal operating condition information of the converter station based on the power regulation processing range of the converter station, and adjusting the power distribution of the converter station based on the optimal operating condition information, includes:

[0050] Multiple candidate operating condition combinations are generated based on the power regulation processing range of each converter station;

[0051] The performance indicators of each candidate operating condition combination are obtained based on the real-time operating status data of the converter station.

[0052] Candidate operating conditions are sorted according to performance indicators, and the operating condition with the highest score is selected as the optimal operating condition information.

[0053] The optimal operating condition information is converted into power allocation instructions, which include the active power setpoint, reactive power output target and voltage regulation requirements of each converter station; the expected operating data of each converter station under optimal conditions is obtained through the power allocation instructions.

[0054] The power distribution command is distributed to each converter station for execution by adjusting the control network, and the real-time operation data of the power distribution adjustment process is monitored in real time. Based on the expected operation data, the difference between the actual operation status and the expected operating condition is obtained.

[0055] Determine whether the operational difference value is within the preset range;

[0056] If in operation, complete the power distribution adjustment of the converter station;

[0057] If not, multiple candidate operating condition combinations are generated again based on the power regulation processing range of each converter station to ensure that the system always operates near the optimal operating condition and completes the power distribution regulation of the converter station.

[0058] Preferably, the steps of constructing a regulation and control network based on a coordination and control mechanism, information exchange protocol, and control command transmission path include:

[0059] Based on the priority, response time, and other rules in the hierarchical affiliation and coordination mechanism defined in the framework, specific and differentiated control logic and action rules are generated for each level of converter station, forming an executable set of control rules;

[0060] Based on the control rule set, the logical relationships between the various levels in the control structure framework are obtained. Based on the logical relationships, the information interaction protocol is standardized by unifying the data communication format, transmission cycle and triggering conditions, and generating a standardized information interaction protocol.

[0061] A deterministic control command transmission path is generated from the backbone adjustment layer to the regional coordination layer and then to the local response layer based on the information interaction protocol and control command transmission path.

[0062] The configured control rule set, standardized information exchange protocol, and deterministic control command transmission path are integrated to obtain the regulation and control network.

[0063] This invention also provides an adaptive power distribution system for a new energy DC aggregation and transmission system, comprising:

[0064] The status data acquisition module is used to acquire real-time operating status data of converter stations in the new energy DC aggregation and transmission system. The real-time operating status data of the converter stations includes the frequency deviation of the DC grid at the sending and receiving ends, the voltage deviation of the DC network, and the active power and reactive power output values ​​of each converter station.

[0065] The operation feature information acquisition module is used to acquire the operation feature information of each converter station based on the real-time operation status data of the converter stations;

[0066] The regulation control network construction module is used to obtain the adjustable capacity of the converter station based on the operating characteristic information, and to construct the regulation control network based on the adjustable capacity corresponding to each converter station.

[0067] The power allocation optimal value acquisition module is used to obtain the power allocation limit of each converter station according to the regulation and control network, and to obtain the optimal power allocation value of each converter station according to the power allocation limit.

[0068] The response test rate acquisition module is used to obtain the power regulation test range based on the optimal power allocation value, and to obtain the frequency response test rate of each converter station from the power regulation test range based on the frequency deviation between the sending and receiving ends.

[0069] The power regulation processing range acquisition module is used to establish a converter station equalization table based on the corresponding frequency response test rate of each converter station, and to obtain the corresponding converter station power regulation processing range for each converter station based on the converter station equalization table.

[0070] The adjustment module is used to obtain the optimal operating condition information of the converter station according to the power adjustment processing range of the converter station, and to adjust the power distribution of the converter station based on the optimal operating condition information.

[0071] Preferably, the runtime feature information acquisition module includes:

[0072] The operating parameter sequence acquisition unit is used to acquire the operating parameter sequence of each converter station based on the real-time operating status data of the converter station. The operating parameter sequence includes an active power output value sequence, a reactive power output value sequence, a DC voltage measurement value sequence, and a DC side frequency measurement value sequence.

[0073] The power fluctuation characteristic acquisition unit is used to acquire the power fluctuation characteristic of each converter station based on the active power output value sequence and the reactive power output value sequence, wherein the power fluctuation characteristic includes the power change rate statistical value and the power fluctuation amplitude index.

[0074] The voltage stability coefficient acquisition unit is used to acquire the voltage stability coefficient of each node of the converter station based on the DC voltage measurement value sequence.

[0075] The frequency response characteristic acquisition unit is used to acquire the frequency response characteristics of each converter station based on the DC side frequency measurement value sequence, including the average frequency deviation and the maximum frequency change rate.

[0076] The multi-dimensional operation feature vector generation unit is used to generate a multi-dimensional operation feature vector for each converter station based on power fluctuation features, voltage stability coefficient, and frequency response features.

[0077] The operation feature information processing unit is used to normalize the multi-dimensional operation feature vector to obtain standardized operation feature information.

[0078] The beneficial effects of this application are as follows: This invention acquires system operating status data in real time and constructs a regulation and control network to dynamically optimize the power allocation limits and optimal values ​​of each converter station, and establishes an equalization table in combination with the frequency response test rate, ultimately realizing power allocation regulation based on optimal operating conditions. Attached Figure Description

[0079] Figure 1 This is a schematic diagram of a method flow according to an embodiment of the present invention.

[0080] Figure 2 This is a schematic diagram of the system structure according to an embodiment of the present invention.

[0081] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0082] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0083] like Figure 1 As shown, this application provides an adaptive power allocation method for a new energy DC aggregation and transmission system, applied to a new energy DC aggregation and transmission system, wherein the DC aggregation and transmission system includes multiple converter stations, and each converter station is connected to a new energy power generation unit and a DC grid, including:

[0084] S1. Obtain real-time operating status data of converter stations in the new energy DC aggregation and transmission system. The real-time operating status data of converter stations includes the frequency deviation of the DC grid at the sending and receiving ends, the voltage deviation of the DC network, and the active and reactive power output values ​​of each converter station.

[0085] S2. Obtain the operating characteristic information of each converter station based on the real-time operating status data of the converter stations;

[0086] S3. Obtain the adjustable capacity of the converter station based on the operating characteristic information, and construct an adjustment control network based on the adjustable capacity of the converter station corresponding to each converter station;

[0087] S4. Obtain the power allocation limit for each converter station based on the regulation and control network, and obtain the optimal power allocation value for each converter station based on the power allocation limit.

[0088] S5. Obtain the power regulation test range based on the optimal power allocation value, and obtain the frequency response test rate of each converter station from the power regulation test range based on the frequency deviation between the sending and receiving ends.

[0089] S6. Establish a converter station equalization table based on the corresponding frequency response test rate of each converter station, and obtain the corresponding converter station power regulation processing range for each converter station based on the converter station equalization table.

[0090] S7. Obtain the optimal operating condition information of the converter station according to the power regulation processing range of the converter station, and adjust the power distribution of the converter station based on the optimal operating condition information of the converter station.

[0091] As described in steps S1-S7 above, the real-time operating status data of the converter stations includes the frequency deviation of the DC grid at the sending and receiving ends, the voltage deviation of the DC network, and the power output value of each converter station. This data is collected through sensors and communication equipment and is used to reflect the dynamic operating characteristics of the system. Operating characteristic information refers to the power fluctuation characteristics, voltage stability coefficient, and frequency response characteristics of the converter stations. This information is extracted through sequence analysis and statistical methods and is used to evaluate the regulation capabilities of the converter stations. The regulation and control network is a hierarchical control architecture built based on the adjustable capacity of the converter stations, including a main regulation layer, a regional coordination layer, and a local response layer. This hierarchical division enables multi-temporal and spatial scale collaborative control. The optimal power allocation value is an allocation scheme determined through dynamic adjustment and verification mechanisms under operating constraints, used to balance system power demand and converter station regulation capabilities. The frequency response test rate is obtained through nominal frequency disturbance experiments within the power regulation test range, reflecting the frequency regulation performance of the converter stations at different power levels. The converter station balance table is generated based on the frequency response test rate and adjustable capacity, used to quantify the power regulation responsibility range of each converter station.

[0092] This invention constructs a multi-dimensional operational status sensing system by real-time acquisition of frequency deviation, voltage deviation, and converter station power data. Based on power fluctuation characteristics and frequency response analysis, the adjustable capacity of each converter station is calculated, and control levels are divided according to capacity to form a hierarchical and coordinated regulation and control network. By dynamically adjusting power allocation limits and combining them with safety constraint verification, an optimal power allocation value that balances regulation needs and operational safety is generated. A nominal frequency disturbance experiment is conducted within the power regulation test range to obtain the frequency response test rate of each converter station, thereby establishing an equalization table and determining the power regulation processing range. Finally, through performance evaluation and closed-loop optimization of candidate operating condition combinations, the optimal operating condition is selected and a power allocation command is issued to achieve coordinated regulation of multiple converter stations.

[0093] In one embodiment, the step of obtaining the operating characteristic information of each converter station based on the real-time operating status data of the converter stations includes:

[0094] S201. Obtain the operating parameter sequence of each converter station based on the real-time operating status data of the converter station, wherein the operating parameter sequence includes an active power output value sequence, a reactive power output value sequence, a DC voltage measurement value sequence, and a DC side frequency measurement value sequence;

[0095] S202. Obtain the power fluctuation characteristic of each converter station based on the active power output value sequence and the reactive power output value sequence, wherein the power fluctuation characteristic includes the power change rate statistical value and the power fluctuation amplitude index.

[0096] S203. Obtain the voltage stability coefficient of each converter station node based on the DC voltage measurement value sequence;

[0097] S204. Obtain the frequency response characteristics of each converter station based on the DC side frequency measurement value sequence, including the average frequency deviation and the maximum frequency change rate.

[0098] S205. Generate a multi-dimensional operation feature vector for each converter station based on power fluctuation characteristics, voltage stability coefficient, and frequency response characteristics.

[0099] S206. Normalize the multi-dimensional operational feature vector to obtain standardized operational feature information.

[0100] As described in steps S201-S206 above, the power change rate statistics refer to the rate statistics of change of active and reactive power over time, which can be implemented using standard deviation or coefficient of variation, and are used to quantify the degree of power output fluctuation. The power fluctuation amplitude index refers to the maximum deviation of power output from the average value, which can be implemented by calculating the sequence range or peak-to-valley difference, and is used to reflect the severity of power fluctuations. The voltage stability coefficient refers to the stability of node voltage within a set time window, which can be implemented using voltage fluctuation variance or the percentage of time continuously deviating from the threshold, and is used to assess the voltage support capability of the node where the converter station is located. The mean frequency deviation refers to the average deviation between the DC-side frequency measurement value and the rated value, which can be obtained through moving average filtering, and is used to characterize the overall impact of the converter station on the system frequency. The maximum frequency change rate refers to the maximum rate of change of the frequency measurement value per unit time, which can be obtained through difference calculation combined with extreme value screening, and is used to capture frequency mutation events. The multi-dimensional operating feature vector refers to integrating operating feature parameters of different dimensions into a vector of a unified dimension, which can be implemented using feature splicing, and is used to comprehensively reflect the operating status of the converter station.

[0101] This invention collects four parameter sequences from converter stations: active power, reactive power, DC voltage, and DC frequency, forming a fundamental dataset reflecting the station's operating status. Time-domain analysis of the power output sequence is performed to calculate the statistical value of the power change rate and fluctuation amplitude index, quantifying the impact of renewable energy output fluctuations on the converter station. Statistical analysis of the DC voltage sequence extracts characteristic parameters reflecting node voltage stability, identifying the risk of sustained voltage deviations from the normal range. Mean and extreme value analysis of the DC frequency sequence assesses both the overall frequency shift and captures sudden nominal frequency disturbance events. These characteristic parameters are integrated into a multi-dimensional vector to establish a comprehensive evaluation model of the converter station's operating status. Normalization eliminates the influence of different physical dimensions, making the operating characteristics of each converter station comparable and providing standardized input for subsequent coordinated control.

[0102] In one embodiment, the steps of obtaining the adjustable capacity of converter stations based on the operational characteristic information and constructing a regulation control network based on the adjustable capacity of each converter station include:

[0103] S301. Obtain the preset safe operating threshold of the converter station, and obtain the power adjustment range of each converter station based on the preset safe operating threshold, rate fluctuation characteristics and voltage stability coefficient.

[0104] S302. Obtain the adjustment influence coefficient of each converter station in the system frequency adjustment process according to the frequency response characteristics, and obtain the adjustable capacity of the converter station according to the adjustment influence coefficient and the power adjustment range.

[0105] S303. Based on the adjustable capacity, the corresponding converter stations are divided to obtain a capacity control hierarchy, wherein the capacity control hierarchy includes a backbone regulation layer, a regional coordination layer and a local response layer.

[0106] S304. Obtain the electrical distance between converter stations, and determine the hierarchical affiliation of each converter station in the DC grid based on the electrical distance and capacity control level, and generate a hierarchical control structure framework;

[0107] S305. A coordination control mechanism between converter stations is generated based on a hierarchical control structure, wherein the coordination control mechanism includes power allocation priority setting, adjustment response time configuration, and reserve capacity allocation rules.

[0108] S306. Obtain the information interaction protocol and control command transmission path according to the hierarchical control structure framework, and construct the regulation control network according to the coordination control mechanism, information interaction protocol and control command transmission path.

[0109] As described in steps S301-S306 above, this invention dynamically calculates the power regulation safety boundary of each converter station through joint analysis of preset operating safety thresholds and real-time power fluctuation characteristics, avoiding the conservative defects of fixed thresholds in traditional methods. By combining dynamic parameters in the frequency response characteristics to calculate the regulation influence coefficient, the actual role of each converter station in system frequency regulation can be accurately quantified, providing a dynamic basis for capacity assessment. Based on a three-layer control architecture with adjustable capacity division, large-capacity converter stations are assigned to the main regulation layer to undertake global power balance, medium-capacity converter stations are assigned to the regional coordination layer to achieve area coordination, and small-capacity converter stations are assigned to the local response layer to handle rapid fluctuations, forming a multi-timescale collaborative control system. When determining the level of assignment through electrical distance calculation, converter stations with close electrical coupling are preferentially assigned to the same control level to reduce the transmission delay of control commands in the power grid. The dynamic priority rules set in the coordinated control mechanism can adjust the power allocation weight of each level according to the real-time operating status.

[0110] The power regulation range refers to the interval within which a converter station can adjust its power while meeting operational safety thresholds. This can be calculated using the difference between the safety threshold and the power fluctuation amplitude, ensuring that power regulation does not exceed the equipment's capacity. The regulation influence coefficient is a quantitative indicator of the converter station's contribution to system frequency regulation. It can be calculated by weighting the mean frequency deviation and the maximum rate of change, reflecting the dynamic role of each converter station in frequency regulation. The capacity control hierarchy refers to the system control levels based on adjustable capacity. This can be achieved using clustering algorithms to divide converter stations into a backbone regulation layer, a regional coordination layer, and a local response layer, enabling coordinated control across different spatial ranges. Electrical distance refers to the tightness of electrical connections between converter stations. This can be calculated using the node admittance matrix to determine impedance parameters, establishing the physical basis for the control hierarchy division. The coordinated control mechanism refers to the rules governing coordinated operation between converter stations. This can be implemented using priority dynamic adjustment algorithms and hierarchical response time configuration, balancing regulation speed and system stability.

[0111] In one embodiment, the steps of obtaining the power allocation limit for each converter station based on the regulation and control network, and obtaining the optimal power allocation value for each converter station based on the power allocation limit, include:

[0112] S401. Obtain the hierarchical affiliation information of each converter station according to the regulation and control network, and obtain the power allocation coefficients corresponding to the backbone regulation layer, regional coordination layer and local response layer, and generate the initial power allocation limit for each converter station according to the power allocation coefficients.

[0113] S402. Obtain the frequency deviation and voltage deviation from the real-time operating status data of the converter station, and obtain the power regulation demand value based on the adjustable capacity of each converter station.

[0114] S403. Obtain the dynamic power allocation adjustment amount for each converter station based on the power regulation demand value and the initial power allocation limit, and obtain the power allocation limit for the real-time operating status based on the dynamic power allocation adjustment amount.

[0115] S404. Obtain preset operating constraints, wherein the preset operating constraints include converter station capacity limits, transmission line thermal stability limits and power grid safety operation requirements, and generate a power allocation constraint set according to the preset operating constraints, and verify the power allocation limit through the power allocation constraint set to obtain a corrected power allocation limit that excludes those exceeding the safe operating range;

[0116] S405. Obtain the optimal power allocation value for each converter station based on the corrected power allocation limit.

[0117] As described in steps S401-S405 above, when frequency deviation or voltage fluctuation is detected, the present invention first determines the basic power allocation weight of the converter station according to its control level. Then, combining the real-time collected frequency deviation data and the adjustable capacity of each station, the total power regulation required by the system is calculated. By allocating the total regulation to each converter station according to the level coefficient, a preliminary power allocation limit is generated, wherein the dynamic allocation weight formula for each converter station is: ;in, This represents the dynamic weight allocation for the i-th converter station. This represents the adjustable capacity of the i-th converter station. This represents the priority coefficient corresponding to the control level (backbone, regional, local) to which the i-th converter station belongs. This indicates the total number of converter stations participating in power allocation. This represents the sum of the products of the adjustable capacity of all converter stations and their hierarchical priority coefficients (j has no independent physical meaning; it is merely a temporary counter used in the summation operation to iterate through all converter stations (from 1 to n)). By calculating the product of the adjustable capacity of each converter station and its corresponding control level priority coefficient, and then comparing this product with the sum of the products of all converter stations in the system, the responsibility of each converter station in system power regulation is dynamically and proportionally determined, ensuring that converter stations with strong regulation capabilities and high control levels are given higher weights. At this time, the system will call the preset safety constraint database to perform multi-dimensional verification of the preliminary limits: verifying whether the current output of the converter station exceeds the rated capacity, verifying whether the transmission line is within the thermal stability limit, and checking whether the system frequency is within the safe range after power allocation. The limits that pass the verification will be used as the basis for calculating the final optimal power allocation value; schemes that fail the verification will be eliminated and recalculated.

[0118] Hierarchical classification information refers to the control level classification of a converter station. This can be achieved through electrical distance calculation and capacity control level division algorithms. Electrical distance refers to the "difficulty" or "electrical tightness" of power transmission between two converter stations in a power system network. For example, the closer two converter stations are electrically, the easier and more significant a voltage change in one station will affect the voltage level of the other. This information is used to determine the functional positioning of the converter station in the coordinated control network. Power allocation coefficients refer to the weighting parameters corresponding to different control levels. These can be generated using an allocation model based on regulation response speed and capacity ratio, used to achieve cross-level coordinated control. Dynamic power allocation adjustment refers to the power correction amount calculated based on power regulation demand. The formula for the dynamic power allocation adjustment amount for each converter station is: ;in, This represents the amount of dynamic power allocation adjustment that the i-th converter station needs to undertake. The formula for calculating the power allocation limit in real-time operation, representing the power regulation demand value, is as follows: ;in, This represents the power allocation limit for the i-th converter station. This represents the initial power allocation limit for the i-th converter station. The calculated total system power regulation demand is directly multiplied by the dynamic allocation weight of each converter station, precisely decomposing and allocating the macroscopic total system regulation demand to each converter station to achieve dynamic power allocation response. The power allocation constraint set refers to the set of boundary conditions for safe system operation. Specifically, it can be constructed using the rated capacity of converter stations, line current carrying capacity thresholds, and grid frequency stability standards, and is used to eliminate allocation schemes that exceed safety boundaries.

[0119] In one embodiment, the steps of obtaining the power regulation test range based on the optimal power allocation value and obtaining the frequency response test rate of each converter station from the power regulation test range based on the frequency deviation between the transmitting and receiving ends include:

[0120] S501. Obtain the upper and lower fluctuation percentages of the optimal power allocation value, and obtain the power adjustment test range based on the upper and lower fluctuation percentages;

[0121] S502. Obtain frequency deviation data under real-time operating conditions based on the power regulation test range, and obtain the nominal frequency disturbance amplitude during the test process based on the frequency deviation data.

[0122] S503. Obtain the nominal frequency disturbance at each power regulation test point based on the nominal frequency disturbance amplitude, and obtain the frequency response process data of each converter station based on the nominal frequency disturbance.

[0123] S504. Obtain frequency response characteristic parameters based on frequency response process data, wherein the frequency response characteristic parameters include the maximum frequency deviation value, frequency recovery time, and power adjustment rate, and calculate the frequency response evaluation index for each power adjustment test point based on the frequency response characteristic parameters.

[0124] S505. Obtain the frequency response test rate of each converter station based on the frequency response evaluation index of all power regulation test points.

[0125] S506. Establish a correspondence table between frequency response test rate and power regulation test point, identify the power regulation area with the highest frequency response test rate, and obtain the optimal power regulation range of each converter station by analyzing the data distribution characteristics in the correspondence table.

[0126] S507. Generate the power regulation processing range for each converter station based on the optimal power regulation range and frequency response test rate.

[0127] As described in steps S501-S507 above, the power adjustment test range refers to the test interval that fluctuates up and down based on the optimal power distribution value, which can be achieved by setting a percentage fluctuation range. The nominal frequency disturbance amplitude refers to the magnitude of the simulated frequency deviation applied during the test (wherein, the formula for calculating the nominal frequency disturbance amplitude is: ;in, Indicates the nominal frequency disturbance amplitude. This represents the frequency deviation value collected in real time within the statistical time window T. This represents the maximum absolute value of the frequency deviation within the time window T. This represents the 90th percentile of the absolute value of the frequency deviation within a time window T. The weighting factor (between 0 and 1) is used to calculate a baseline disturbance amplitude based on historical frequency deviation data by weighting and combining the maximum value and 90th percentile of the absolute value sequence. This defines a reasonable nominal frequency disturbance baseline for subsequent performance testing, covering both extreme cases and typical operating conditions, ensuring the rigor and practicality of the test and avoiding overly conservative or aggressive test conditions. Specifically, this can be determined by statistically analyzing the distribution characteristics of the actual frequency deviation data collected in real time. Frequency response characteristic parameters refer to a set of indicators that quantify the converter station's response performance. These can be calculated by collecting data such as extreme values, time characteristics, and power change rates during frequency fluctuations. The frequency response test rate is a quantitative indicator that comprehensively evaluates the performance of each test point. This can be achieved through a weighted calculation using multiple characteristic parameters. The optimal power adjustment range refers to the operating range where the converter station's frequency response performance is optimal. This can be identified by analyzing the correlation curve between the test rate and power points, identifying continuous power ranges where the test rate exceeds a set threshold.

[0128] After determining the optimal power allocation value, this invention first generates a power regulation test range by setting upper and lower fluctuation percentages. Then, it collects frequency deviation data during system operation in real time and statistically analyzes the fluctuation amplitude as a test disturbance benchmark. Multiple power regulation test points are selected within the test range, for example, with test points set in 1MW increments. At each test point, a nominal frequency disturbance matching the current system disturbance level is applied (wherein, the formula for calculating the nominal frequency disturbance is: ;in, This represents the nominal frequency perturbation applied at the k-th power regulation test point. The power value at the kth power regulation test point The reference power indicates the power regulation test range. This represents the half-width of the power regulation test range. Based on a given power test point, the deviation from the reference power is normalized and multiplied by the nominal frequency disturbance amplitude to generate a corresponding nominal frequency disturbance value for each test point. This establishes a correlation mapping between power level and nominal frequency disturbance intensity, simulating the real-world scenario where "the further the operating point deviates from the optimal value, the greater the disturbance risk faced by the system." This allows for a comprehensive evaluation of the converter station's frequency response performance across the full power test range. The response process of each converter station at different power points is monitored, recording parameters such as maximum frequency deviation, recovery time, and power regulation rate. A weighted scoring model is used to calculate the frequency response evaluation index for each test point. Power intervals where the test rate consistently exceeds the preset value are identified by analyzing the curve shape.

[0129] In one embodiment, the steps of establishing a converter station equalization table based on the corresponding frequency response test rate of each converter station, and obtaining the converter station power regulation processing range corresponding to each converter station based on the converter station equalization table, include:

[0130] S601. Obtain frequency response test rate data for each converter station at different power regulation test points, and obtain frequency response stability index for each converter station at each power level based on the frequency response test rate data.

[0131] S602. Obtain the adjustable capacity data of each converter station, and obtain the power regulation balance of each converter station based on the frequency response stability index and the adjustable capacity data.

[0132] S603. Based on the power regulation balance, classify each converter station into the corresponding balance level and generate a converter station balance table.

[0133] S604. Obtain data distribution characteristics based on the converter station balance table, identify a group of converter stations with high balance levels based on the data distribution characteristics, and determine the location information of each converter station based on the optimal power allocation value.

[0134] S605. Based on the positioning information, obtain the set power regulation coefficient for each converter, and obtain the power regulation responsibility range of each converter station according to the set power regulation coefficient and adjustable capacity data.

[0135] S606. Obtain the upper and lower limits of power regulation for each converter station according to the power regulation responsibility scope, and generate the power regulation processing range.

[0136] As described in steps S601-S606 above, the frequency response test rate data refers to the evaluation index calculated from the frequency response process data at different power levels within a preset power regulation test range. Specifically, it can be implemented using a weighted calculation method combining the ratio of the maximum frequency deviation value to a set threshold and the frequency recovery time, used to quantify the frequency control capability of the converter station within a specific power regulation range. The frequency response stability index refers to the dynamic performance parameter reflecting the converter station's ability to maintain system frequency stability. Specifically, it can be implemented using a correlation analysis model of power regulation rate and frequency deviation change rate, used to evaluate the frequency support capability of the converter station under different power output levels. The power regulation balance refers to a comprehensive evaluation index formed by integrating adjustable capacity and frequency response stability. Specifically, it can be implemented using the analytic hierarchy process (AHP) to weight the capacity margin and frequency stability coefficient, used to characterize the degree of matching between the converter station's regulation capability and system requirements. The power regulation responsibility range refers to the power regulation range allocated to each converter station according to system operation requirements. Specifically, it can be implemented using a linear allocation algorithm based on the adjustable capacity ratio and balance level, used to determine the specific scope of action of each converter station in system regulation.

[0137] This invention conducts multi-condition tests on converter stations within a preset power regulation test range, collecting frequency response process data at each test point. Specifically, it records key physical quantity data of the system and converter station during the dynamic response period after a controllable nominal frequency disturbance is applied. The frequency response test rate for each test point is calculated based on parameters such as frequency recovery time and power regulation rate. This test rate is used to quantify the overall performance score of the converter station. By simulating disturbances of the same magnitude as the actual frequency deviation at the transmitting and receiving ends, the dynamic response performance of the converter station at different power test points is analyzed, including key characteristic parameters such as maximum frequency deviation, recovery time, and power regulation rate. A higher test rate indicates a stronger overall ability of the converter station to suppress frequency fluctuations and restore system frequency stability at that power point or range.

[0138] In one embodiment, the step of obtaining the optimal operating condition information of the converter station according to the power regulation processing range of the converter station, and adjusting the power distribution of the converter station based on the optimal operating condition information of the converter station, includes:

[0139] S701. Generate multiple candidate operating condition combinations based on the power regulation processing range of each converter station;

[0140] S702. Obtain the performance indicators of each candidate operating condition combination based on the real-time operating status data of the converter station.

[0141] S703. Sort the candidate operating conditions according to the performance indicators and select the operating condition with the highest score as the optimal operating condition information.

[0142] S704. Convert the optimal operating condition information into a power allocation instruction, wherein the power allocation instruction includes the active power setpoint, reactive power output target and voltage regulation requirements of each converter station; obtain the expected operating data of each converter station under the optimal operating condition through the power allocation instruction;

[0143] S705. The power distribution command is distributed to each converter station for execution through the adjustment control network, and the real-time operation data of the power distribution adjustment process is monitored in real time. Based on the expected operation data, the difference between the actual operation status and the expected operating condition is obtained.

[0144] S706. Determine whether the operating difference value is within the preset range;

[0145] If in operation, complete the power distribution adjustment of the converter station;

[0146] If not, multiple candidate operating condition combinations are generated again based on the power regulation processing range of each converter station to ensure that the system always operates near the optimal operating condition and completes the power distribution regulation of the converter station.

[0147] As described in steps S701-S706 above, the candidate operating condition combination refers to a combination of multiple feasible operating states generated based on the power regulation processing range of the converter station. Specifically, it can be generated using a multi-objective optimization algorithm combined with constraints. Performance indicators refer to quantitative parameters that measure the quality of operating conditions, which can be calculated using a weighted comprehensive evaluation method. Optimal operating condition information refers to the set of best operating parameters selected through evaluation, which can be determined using a priority ranking algorithm. Power allocation instructions refer to a standardized format that converts operating condition information into control signals. Specifically, it can use the OPCUA protocol for data encapsulation, including three-dimensional control parameters such as active power setpoint, reactive power output target, and voltage regulation requirements, ensuring the executability of the instructions. Operating difference value refers to the degree of deviation between actual operating data and expected operating conditions, which can be calculated using an Euclidean distance algorithm to determine the overall deviation of multi-dimensional parameters.

[0148] This invention generates candidate operating condition combinations covering different operating ranges based on the power regulation processing range of each converter station. These candidate operating conditions explore possible power allocation schemes under the premise of satisfying system constraints through optimization algorithms. Subsequently, real-time operating data is collected, and multi-dimensional performance evaluation is performed on each candidate operating condition, focusing on its impact on frequency stability, voltage quality, and power transmission efficiency. By establishing a comprehensive evaluation model including frequency deviation coefficient, voltage fluctuation index, and power loss rate, each candidate operating condition is quantitatively scored. The operating condition with the highest comprehensive score is selected as the optimal operating target and converted into a standardized instruction format containing specific control parameters. The instructions are transmitted to each converter station for execution through a hierarchical control network, while a real-time monitoring mechanism is activated to collect actual operating data. By calculating the difference between the actual operating parameters and the expected target, it is determined whether the current regulation effect is within the allowable deviation range. When the difference exceeds a preset threshold, the candidate operating condition regeneration process is automatically triggered, forming a closed-loop control loop. This dynamic adjustment mechanism can continuously optimize the system operating state and ensure that it always operates near the optimal operating condition.

[0149] In one embodiment, the step of constructing a regulation and control network based on a coordination and control mechanism, an information exchange protocol, and a control command transmission path includes:

[0150] S3061. Based on the hierarchical affiliation and coordination mechanism rules defined in the framework, such as priority and response time, generate specific and differentiated control logic and action rules for each level of converter station to form an executable set of control rules.

[0151] S3062. Obtain the logical relationships between each level in the control structure framework according to the control rule set, and generate a standardized information interaction protocol by unifying the data communication format, transmission cycle and triggering conditions of the information interaction protocol based on the logical relationships.

[0152] S3063. Generate a deterministic control command transmission path from the backbone adjustment layer to the regional coordination layer and then to the local response layer according to the information interaction protocol and control command transmission path.

[0153] S3064. Integrate the configured control rule set, standardized information interaction protocol and deterministic control command transmission path to obtain the regulation and control network.

[0154] As described in steps S3061-S3064 above, this invention overcomes the shortcomings of traditional unified control strategies that cannot adapt to the functional differences of various converter stations by tailoring control rule sets for different control levels. For example, the backbone layer rules focus on rapid compensation for large-scale power deficits, with response times required to be in the hundreds of milliseconds; the regional layer rules focus on power redistribution and voltage support within a region, with response times in the seconds; and the local layer rules provide millisecond-level rapid damping for random fluctuations in renewable energy output. This differentiated rule design enables converter stations at each level to play a regulatory role at their most suitable spatiotemporal scale, achieving optimal allocation of control resources.

[0155] By defining a standardized information exchange protocol, a unified and open data communication environment was constructed. This protocol not only specifies the transmission format and cycle of regular periodic data but also defines the triggering mechanism and priority transmission level for emergency control commands. For example, when the system detects a severe frequency deviation, the backbone converter station can immediately trigger the highest priority control command according to the protocol. This command will interrupt regular communication, reaching the execution unit directly via the shortest path and with minimal delay, ensuring the timeliness of critical control actions.

[0156] By establishing a deterministic control command transmission path, this invention clarifies the direction and nodes of the control information flow, avoiding network congestion and command conflicts caused by traditional broadcast or flooding communication methods. This point-to-point or point-to-multipoint deterministic path, combined with the timing requirements defined in the information interaction protocol, makes the response time of the entire control system predictable and manageable.

[0157] like Figure 2 As shown, the present invention also provides an adaptive power distribution system for a new energy DC aggregation and transmission system, comprising:

[0158] The status data acquisition module 1 is used to acquire the real-time operating status data of the converter stations of the new energy DC aggregation and transmission system. The real-time operating status data of the converter stations includes the frequency deviation of the DC grid at the sending and receiving ends, the voltage deviation of the DC network, and the active power and reactive power output values ​​of each converter station.

[0159] The operation feature information acquisition module 2 is used to acquire the operation feature information of each converter station based on the real-time operation status data of the converter station;

[0160] The regulation control network construction module 3 is used to obtain the adjustable capacity of the converter station based on the operating characteristic information, and to construct the regulation control network based on the adjustable capacity corresponding to each converter station.

[0161] The power allocation optimal value acquisition module 4 is used to obtain the power allocation limit of each converter station according to the regulation and control network, and obtain the optimal power allocation value of each converter station according to the power allocation limit.

[0162] The response test rate acquisition module 5 is used to obtain the power regulation test range based on the optimal power allocation value, and to obtain the frequency response test rate of each converter station from the power regulation test range based on the frequency deviation between the sending and receiving ends.

[0163] The power regulation processing range acquisition module 6 is used to establish a converter station equalization table based on the corresponding frequency response test rate of each converter station, and to obtain the corresponding converter station power regulation processing range for each converter station based on the converter station equalization table.

[0164] The adjustment module 7 is used to obtain the optimal operating condition information of the converter station according to the power adjustment processing range of the converter station, and to adjust the power distribution of the converter station based on the optimal operating condition information of the converter station.

[0165] In one embodiment, the runtime feature information acquisition module 2 includes:

[0166] The operating parameter sequence acquisition unit is used to acquire the operating parameter sequence of each converter station based on the real-time operating status data of the converter station. The operating parameter sequence includes an active power output value sequence, a reactive power output value sequence, a DC voltage measurement value sequence, and a DC side frequency measurement value sequence.

[0167] The power fluctuation characteristic acquisition unit is used to acquire the power fluctuation characteristic of each converter station based on the active power output value sequence and the reactive power output value sequence, wherein the power fluctuation characteristic includes the power change rate statistical value and the power fluctuation amplitude index.

[0168] The voltage stability coefficient acquisition unit is used to acquire the voltage stability coefficient of each node of the converter station based on the DC voltage measurement value sequence.

[0169] The frequency response characteristic acquisition unit is used to acquire the frequency response characteristics of each converter station based on the DC side frequency measurement value sequence, including the average frequency deviation and the maximum frequency change rate.

[0170] The multi-dimensional operation feature vector generation unit is used to generate a multi-dimensional operation feature vector for each converter station based on power fluctuation features, voltage stability coefficient, and frequency response features.

[0171] The operation feature information processing unit is used to normalize the multi-dimensional operation feature vector to obtain standardized operation feature information.

[0172] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent results or equivalent process transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. An adaptive power allocation method for a new energy DC aggregation and transmission system, wherein the DC aggregation and transmission system includes multiple converter stations, and each converter station is connected to a new energy power generation unit and a DC power grid, characterized in that, include: The real-time operating status data of the converter stations of the new energy DC aggregation and transmission system are obtained. The real-time operating status data of the converter stations includes the frequency deviation of the DC grid at the sending and receiving ends, the voltage deviation of the DC network, and the active power and reactive power output values ​​of each converter station. The operational characteristic information of each converter station is obtained based on the real-time operational status data of the converter stations; The adjustable capacity of the converter station is obtained based on the operational characteristic information, and an adjustment control network is constructed based on the adjustable capacity corresponding to each converter station. The power allocation limit for each converter station is obtained based on the regulation and control network, and the optimal power allocation value for each converter station is obtained based on the power allocation limit. The power regulation test range is obtained based on the optimal power allocation value, and the frequency response test rate of each converter station is obtained from the power regulation test range based on the frequency deviation between the sending and receiving ends. A converter station equalization table is established based on the corresponding frequency response test rate of each converter station, and the power regulation processing range of each converter station is obtained based on the converter station equalization table. The optimal operating condition information of the converter station is obtained based on the power regulation processing range of the converter station, and the power distribution of the converter station is adjusted based on the optimal operating condition information of the converter station.

2. The adaptive power allocation method for a new energy DC aggregation and transmission system according to claim 1, characterized in that, The steps for obtaining the operational characteristic information of each converter station based on the real-time operational status data of the converter stations include: The operating parameter sequence of each converter station is obtained based on the real-time operating status data of the converter station. The operating parameter sequence includes an active power output value sequence, a reactive power output value sequence, a DC voltage measurement value sequence, and a DC side frequency measurement value sequence. The power fluctuation characteristics of each converter station are obtained based on the active power output value sequence and the reactive power output value sequence, wherein the power fluctuation characteristics include the power change rate statistics and the power fluctuation amplitude index. The voltage stability coefficient of each converter station node is obtained based on the DC voltage measurement value sequence; The frequency response characteristics of each converter station are obtained based on the DC side frequency measurement sequence, including the average frequency deviation and the maximum frequency change rate. A multi-dimensional operation feature vector for each converter station is generated based on power fluctuation characteristics, voltage stability coefficient, and frequency response characteristics. The multi-dimensional operational feature vectors are normalized to obtain standardized operational feature information.

3. The adaptive power allocation method for a new energy DC aggregation and transmission system according to claim 2, characterized in that, The steps of obtaining the adjustable capacity of converter stations based on the operational characteristic information and constructing a regulation and control network based on the adjustable capacity of each converter station include: Obtain the preset safe operating threshold for converter stations, and obtain the power regulation range for each converter station based on the preset safe operating threshold, rate fluctuation characteristics, and voltage stability coefficient; The adjustment influence coefficient of each converter station in the system frequency regulation process is obtained based on the frequency response characteristics, and the adjustable capacity of the converter station is obtained based on the adjustment influence coefficient and the power regulation range. Based on the adjustable capacity, the corresponding converter stations are divided to obtain a capacity control hierarchy, wherein the capacity control hierarchy includes a backbone regulation layer, a regional coordination layer and a local response layer. Obtain the electrical distance between converter stations, and determine the hierarchical affiliation of each converter station in the DC grid based on the electrical distance and capacity control level, thereby generating a hierarchical control structure framework; A coordination control mechanism between converter stations is generated based on a hierarchical control structure, wherein the coordination control mechanism includes power allocation priority setting, adjustment response time configuration, and reserve capacity allocation rules. The information interaction protocol and control command transmission path are obtained based on the hierarchical control structure framework, and a regulation and control network is constructed based on the coordination control mechanism, information interaction protocol and control command transmission path.

4. The adaptive power allocation method for a new energy DC aggregation and transmission system according to claim 1, characterized in that, The steps of obtaining the power allocation limit for each converter station based on the regulation and control network, and obtaining the optimal power allocation value for each converter station based on the power allocation limit, include: The hierarchical affiliation information of each converter station is obtained according to the regulation and control network, and the power allocation coefficients corresponding to the backbone regulation layer, regional coordination layer and local response layer are obtained. The initial power allocation limit of each converter station is generated according to the power allocation coefficients. The frequency and voltage deviations in the real-time operating status data of the converter stations are obtained, and the power regulation demand values ​​are obtained based on the adjustable capacity of each converter station. The dynamic power allocation adjustment amount for each converter station is obtained based on the power regulation demand value and the initial power allocation limit, and the power allocation limit for real-time operation is obtained based on the dynamic power allocation adjustment amount. Obtain preset operating constraints, including converter station capacity limits, transmission line thermal stability limits, and power grid safety operation requirements. Generate a power allocation constraint set based on the preset operating constraints, and verify the power allocation limit through the power allocation constraint set to obtain corrected power allocation limits that exclude those exceeding the safe operation range. The optimal power allocation value for each converter station is obtained based on the modified power allocation limit.

5. The adaptive power allocation method for a new energy DC aggregation and transmission system according to claim 4, characterized in that, The steps include obtaining the power regulation test range based on the optimal power allocation value, and obtaining the frequency response test rate of each converter station from the power regulation test range based on the frequency deviation between the sending and receiving ends, including: Obtain the percentage fluctuation above and below the optimal power allocation value, and obtain the power adjustment test range based on the percentage fluctuation above and below; Based on the power regulation test range, obtain the frequency deviation data under real-time operating conditions, and obtain the nominal frequency disturbance amplitude during the test process based on the frequency deviation data; The nominal frequency disturbance is obtained at each power regulation test point based on the nominal frequency disturbance amplitude, and the frequency response process data of each converter station is obtained based on the nominal frequency disturbance. Frequency response characteristic parameters are obtained based on frequency response process data, including maximum frequency deviation, frequency recovery time, and power adjustment rate. Frequency response evaluation indexes for each power adjustment test point are calculated based on the frequency response characteristic parameters. The frequency response test rate of each converter station is obtained based on the frequency response evaluation index of all power regulation test points. Establish a correspondence table between frequency response test rate and power regulation test point, identify the power regulation area with the highest frequency response test rate, and obtain the optimal power regulation range of each converter station by analyzing the data distribution characteristics in the correspondence table. The power regulation range for each converter station is generated based on the optimal power regulation range and frequency response test rate.

6. The adaptive power allocation method for a new energy DC aggregation and transmission system according to claim 1, characterized in that, The steps include establishing a converter station equalization table based on the frequency response test rate corresponding to each converter station, and obtaining the corresponding converter station power regulation processing range for each converter station based on the converter station equalization table, including: Obtain frequency response test rate data for each converter station at different power regulation test points, and obtain frequency response stability index for each converter station at each power level based on the frequency response test rate data. Obtain the adjustable capacity data for each converter station, and obtain the power regulation balance of each converter station based on the frequency response stability index and the adjustable capacity data; Based on the power regulation balance, each converter station is classified into the corresponding balance level, and a converter station balance table is generated. The data distribution characteristics are obtained from the converter station balance table. Based on the data distribution characteristics, a group of converter stations with high balance levels are identified, and the location information of each converter station is determined based on the optimal power allocation value. The set power regulation coefficient for each converter is obtained based on the location information, and the power regulation responsibility range of each converter station is obtained based on the set power regulation coefficient and the adjustable capacity data. Based on the power regulation responsibility scope, the upper and lower limits of power regulation for each converter station are obtained, and a power regulation processing range is generated.

7. The adaptive power allocation method for a new energy DC aggregation and transmission system according to claim 1, characterized in that, The steps for obtaining the optimal operating condition information of the converter station based on its power regulation processing range, and then adjusting the power distribution of the converter station based on this optimal operating condition information, include: Multiple candidate operating condition combinations are generated based on the power regulation processing range of each converter station; The performance indicators of each candidate operating condition combination are obtained based on the real-time operating status data of the converter station. Candidate operating conditions are sorted according to performance indicators, and the operating condition with the highest score is selected as the optimal operating condition information. The optimal operating condition information is converted into power allocation instructions, which include the active power setpoint, reactive power output target and voltage regulation requirements of each converter station; the expected operating data of each converter station under optimal conditions is obtained through the power allocation instructions. The power distribution command is distributed to each converter station for execution by adjusting the control network, and the real-time operation data of the power distribution adjustment process is monitored in real time. Based on the expected operation data, the difference between the actual operation status and the expected operating condition is obtained. Determine whether the operational difference value is within the preset range; If in operation, complete the power distribution adjustment of the converter station; If not, multiple candidate operating condition combinations are generated again based on the power regulation processing range of each converter station to ensure that the system always operates near the optimal operating condition and completes the power distribution regulation of the converter station.

8. The adaptive power allocation method for a new energy DC aggregation and transmission system according to claim 3, characterized in that, The steps for constructing a regulation and control network based on coordination and control mechanisms, information exchange protocols, and control command transmission paths include: Based on the priority, response time, and other rules in the hierarchical affiliation and coordination mechanism defined in the framework, specific and differentiated control logic and action rules are generated for each level of converter station, forming an executable set of control rules; Based on the control rule set, the logical relationships between the various levels in the control structure framework are obtained. Based on the logical relationships, the information interaction protocol is standardized by unifying the data communication format, transmission cycle and triggering conditions, and generating a standardized information interaction protocol. A deterministic control command transmission path is generated from the backbone adjustment layer to the regional coordination layer and then to the local response layer based on the information interaction protocol and control command transmission path. The configured control rule set, standardized information exchange protocol, and deterministic control command transmission path are integrated to obtain the regulation and control network.

9. An adaptive power distribution system for a new energy DC aggregation and transmission system, characterized in that, include: The status data acquisition module is used to acquire real-time operating status data of converter stations in the new energy DC aggregation and transmission system. The real-time operating status data of the converter stations includes the frequency deviation of the DC grid at the sending and receiving ends, the voltage deviation of the DC network, and the active power and reactive power output values ​​of each converter station. The operation feature information acquisition module is used to acquire the operation feature information of each converter station based on the real-time operation status data of the converter stations; The regulation control network construction module is used to obtain the adjustable capacity of the converter station based on the operating characteristic information, and to construct the regulation control network based on the adjustable capacity corresponding to each converter station. The power allocation optimal value acquisition module is used to obtain the power allocation limit of each converter station according to the regulation and control network, and to obtain the optimal power allocation value of each converter station according to the power allocation limit. The response test rate acquisition module is used to obtain the power regulation test range based on the optimal power allocation value, and to obtain the frequency response test rate of each converter station from the power regulation test range based on the frequency deviation between the sending and receiving ends. The power regulation processing range acquisition module is used to establish a converter station equalization table based on the corresponding frequency response test rate of each converter station, and to obtain the corresponding converter station power regulation processing range for each converter station based on the converter station equalization table. The adjustment module is used to obtain the optimal operating condition information of the converter station according to the power adjustment processing range of the converter station, and to adjust the power distribution of the converter station based on the optimal operating condition information.

10. The adaptive power distribution system for a new energy DC aggregation and transmission system according to claim 9, characterized in that, The operational feature information acquisition module includes: The operating parameter sequence acquisition unit is used to acquire the operating parameter sequence of each converter station based on the real-time operating status data of the converter station. The operating parameter sequence includes an active power output value sequence, a reactive power output value sequence, a DC voltage measurement value sequence, and a DC side frequency measurement value sequence. The power fluctuation characteristic acquisition unit is used to acquire the power fluctuation characteristic of each converter station based on the active power output value sequence and the reactive power output value sequence, wherein the power fluctuation characteristic includes the power change rate statistical value and the power fluctuation amplitude index. The voltage stability coefficient acquisition unit is used to acquire the voltage stability coefficient of each node of the converter station based on the DC voltage measurement value sequence. The frequency response characteristic acquisition unit is used to acquire the frequency response characteristics of each converter station based on the DC side frequency measurement value sequence, including the average frequency deviation and the maximum frequency change rate. The multi-dimensional operation feature vector generation unit is used to generate a multi-dimensional operation feature vector for each converter station based on power fluctuation features, voltage stability coefficient, and frequency response features. The operation feature information processing unit is used to normalize the multi-dimensional operation feature vector to obtain standardized operation feature information.

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