A source network load storage coordination method

Abstract

The application relates to the technical field of source network load storage, and discloses a source network load storage coordination method, which comprises the following steps: dividing an electric power network into multiple basic control areas; evaluating a first electrical coupling strength index between the basic control area and its adjacent area; if the first electrical coupling strength index is greater than or equal to a coupling threshold value for a first duration, then the associated basic control area is combined into a coordinated control group, and a regional coordination controller is selected as a master controller of the coordinated control group; evaluating a second electrical coupling strength index between each basic control area in the coordinated control group; if the second electrical coupling strength index between the areas is less than the coupling threshold value for a second duration, then the coordinated control group is dissolved, and each basic control area is switched back to an operation mode independently managed by the configured regional coordination controller. The source network load storage coordination method realizes coordinated control by monitoring the coupling strength between the areas in real time.

Description

Technical Field

[0001] This invention relates to the field of source-grid-load-storage technology, and in particular to a source-grid-load-storage coordinated method. Background Technology

[0002] With a high proportion of distributed energy sources (such as photovoltaic and wind power) being integrated into the power system, the grid's operating state has shifted from the traditional source-following-load dynamic to source-load interactive, exhibiting high uncertainty and bidirectional power flow. Traditional source-grid-load-storage coordinated control often employs pre-defined fixed control zones. Traditional rigid structures with fixed zones struggle to adapt to continuous changes in system operating states, such as sudden changes in distributed power output and load fluctuations. This can easily lead to a mismatch between the control range and the actual electrical coupling relationship, resulting in decreased coordination efficiency, wasted control resources, and even triggering local oscillations.

[0003] Specifically, the technical drawbacks of existing fixed partitioning methods include:

[0004] (1) Under a fixed partition architecture, control resources in each region cannot be shared across regions. Even if the regions are electrically tightly coupled, it is easy for resources in one region to be idle, while neighboring regions may experience voltage over-limits or power imbalances due to insufficient resources.

[0005] (2) When two strongly coupled regions are forcibly separated for control, the controller action of one region may cause unexpected disturbances to the other region, triggering a chain control reaction, forming oscillations between regional controllers, which seriously affects the stability of the system.

[0006] (3) The traditional fixed partition structure cannot dynamically adjust the control range according to the real-time operating status of the system, resulting in a slow response and insufficient adaptive capability when the system is dealing with rapid changes. Summary of the Invention

[0007] Therefore, the purpose of this invention is to overcome the problem that the fixed partitioning method used in traditional source-grid-load-storage coordinated control cannot adapt to the rapid changes in the grid operation status after a high proportion of distributed energy access, resulting in a mismatch between the control range and the actual electrical coupling relationship, which in turn leads to a decrease in coordination efficiency, waste of control resources, and even local oscillations. The invention provides a source-grid-load-storage coordinated method that achieves coordinated control by real-time monitoring of the coupling strength between regions and performing grouping or disgrouping.

[0008] To address the aforementioned technical problems, this invention provides a source-grid-load-storage coordination method, comprising the following steps:

[0009] The power grid is divided into multiple basic control areas, each basic control area is configured with a regional coordination controller, and the regional coordination controller is used to evaluate the first electrical coupling strength index between the basic control area under its jurisdiction and its adjacent areas.

[0010] Compare the first electrical coupling strength index with the coupling threshold: if the first electrical coupling strength index is greater than or equal to the coupling threshold for a continuous first duration, then the associated basic control areas are grouped into a collaborative control group, and a regional coordination controller is selected as the main controller of the collaborative control group.

[0011] The main controller is used to evaluate the second electrical coupling strength index between each basic control area in the cooperative control group under its jurisdiction, and compares the second electrical coupling strength index with the coupling threshold. If the second electrical coupling strength index between the areas is less than the coupling threshold for a continuous second duration, the cooperative control group is disbanded, and each basic control area is switched back to the operating mode independently managed by the configured area coordination controller.

[0012] Compared with the prior art, the above-described technical solution of the present invention has the following advantages:

[0013] The source-grid-load-storage coordination method described in this invention achieves coordinated control by real-time monitoring of the coupling strength between basic control areas. When the coupling is strong, related basic control areas are merged into a coordinated control group for unified optimization. When the coupling strength weakens, the coordinated control group is disbanded and each basic control area resumes independent operation. Specifically:

[0014] By continuously evaluating the first electrical coupling strength index, the electrical connection strength between basic control areas is sensed in real time. When the strong coupling state continues for a first duration, the relevant basic control areas are merged into a coordinated control group, so that the control range is consistent with the actual electrical influence range, thereby improving coordination efficiency.

[0015] By forming a collaborative control group and electing a master controller, the originally independent basic control area is integrated into a larger optimization unit, and the source, network, load and storage resources within the group are allocated in a coordinated manner to achieve the global optimization goal of reducing the total network loss and improving voltage quality.

[0016] When the coupling between the basic control areas within the collaborative control group continues to weaken, and the second electrical coupling strength index is lower than the coupling threshold during the second duration, the system disbands the collaborative control group, restores the independent operation of each basic control area, and ensures that the system releases resources in a timely manner when global coordination is not required, returning to a distributed autonomous state.

[0017] By setting a first duration and a second duration as the criteria for grouping and ungrouping, the influence of transient fluctuations can be effectively filtered out, ensuring that the control structure is only adjusted under continuous and trend-based changes, thereby improving system reliability. Attached Figure Description

[0018] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings, wherein:

[0019] Figure 1 This is a schematic flowchart of a source-grid-load-storage coordination method in an embodiment of the present invention.

[0020] Figure 2 This is a structural block diagram of a cooperative control group in an embodiment of the present invention.

[0021] Figure 3 This is a flowchart illustrating a strong coupling relationship in a power network according to an embodiment of the present invention.

[0022] Figure 4 This is another flowchart illustrating a strong coupling relationship in a power network according to an embodiment of the present invention. Detailed Implementation

[0023] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0024] In modern power grids where distributed generation output and load fluctuate frequently, the actual electrical coupling relationship of the grid changes dynamically with operating modes (such as photovoltaic output, load distribution, and network topology), making it difficult for fixed zones to adapt to fluctuations in actual operating conditions. Once distributed generation output fluctuates drastically or load distribution shifts, some electrically interconnected source, grid, load, and storage devices may be divided into different regions, making effective cross-regional coordination and optimization impossible. This application proposes a source-grid-load-storage coordination method.

[0025] Example 1: This embodiment of the invention discloses a source-grid-load-storage coordination method.

[0026] The source-grid-load-storage coordination method in this embodiment includes steps SS1 to SS3.

[0027] Step SS1: Divide the power network into multiple basic control areas, configure a regional coordination controller for each basic control area, and use the regional coordination controller to evaluate the first electrical coupling strength index between the basic control area under its jurisdiction and its adjacent areas, referring to... Figure 1 .

[0028] In order to ensure that each basic control area can operate independently, safely and efficiently under normal conditions, this invention divides the power network into multiple basic control areas based on the power grid physical topology and configures a regional coordination controller for each basic control area.

[0029] In practical applications, step SS1 divides the power network into multiple basic control areas, including steps SS101 to SS103.

[0030] Step SS101: Obtain the node impedance matrix of the power network.

[0031] When applied, the nodes of the power network should include at least the medium-voltage busbar of the substation, the sectionalizing switch, the high-voltage side of the distribution transformer, the access point of the distributed power source, the access point of the load, and the end of the feeder.

[0032] when At that time, the elements in the nodal impedance matrix For nodes With nodes The mutual impedance value between them, that is, when at the node When a unit current (1A) is injected and all other nodes are in an open-circuit state, at node The magnitude of the voltage value obtained from the measurement. The smaller the value, the more likely it is to be a node. With nodes The closer the electrical distance between them, the higher the degree of coupling. The larger the value, the more likely it is to be a node. With nodes The greater the electrical distance between them, the lower the degree of coupling.

[0033] when At that time, the elements in the nodal impedance matrix For nodes or node The self-impedance value, that is, when at the node or node When a unit current (1A) is injected and all other nodes are in an open-circuit state, at node or node The magnitude of the voltage value obtained from the measurement.

[0034] Step SS102: Determine the electrical distance between nodes using the node impedance matrix.

[0035] In application, the electrical distance is the sum of the self-impedance values ​​of the two nodes minus twice the mutual impedance value between the two nodes.

[0036] In practical applications, electrical distance includes the following formula:

[0037] ;

[0038] In the formula, For nodes With nodes Electrical distance between them; For nodes The self-impedance value; For nodes The self-impedance value; For nodes With nodes The mutual impedance values ​​between them.

[0039] In actual implementation, at the nodes With nodes When unit currents of equal magnitude but opposite direction are injected, according to circuit superposition, the node... With nodes The absolute value of the voltage difference between them is proportional to Therefore, the electrical distance of the present invention can reflect the node. With nodes The difference lies in their ability to maintain the same voltage level when subjected to power transfer or disturbances. A smaller electrical distance indicates stronger voltage stability and higher electrical coupling between the two nodes; conversely, a larger electrical distance indicates weaker electrical connection and less mutual influence.

[0040] Step SS103: Starting from any node, use a clustering algorithm to divide nodes whose electrical distance is less than the electrical threshold into the same basic control area to form multiple basic control areas.

[0041] When applied, step SS103 includes steps A11 to A13.

[0042] Step A11: Create an empty base control region and select a node that has not been assigned to any base control region (e.g., node A11). As the initial seed node, add it to the basic control region and mark it as visited.

[0043] Step A12: Calculate the electrical distance between the initial seed node and each of its adjacent nodes. Then the node Add to the initial seed node (i.e., node) The basic control area to which the node belongs, and the node Marked as visited. This is the electrical threshold.

[0044] Step A13: Repeat steps A11 to A12 until all nodes have been marked as visited, completing the partitioning and forming multiple basic control areas.

[0045] Each basic control area is assigned a unique area identifier; each basic control area is configured with at least one area coordination controller for local information acquisition and control execution. The area coordination controller establishes communication connections with all distributed collaborative units and intelligent terminals within the area to realize data collection and control command issuance; it communicates with the area coordination controllers of adjacent basic control areas and the upper-level scheduling system; and it records and maintains the static parameters (e.g., equipment capacity, controllable status) and operating constraints (e.g., voltage safety range, tie line power limit) of its own basic control area.

[0046] In practical applications, the method for determining the electrical threshold includes steps B11 to B13.

[0047] Step B11: Obtain the electrical distance sample set.

[0048] In application, the electrical distance sample set includes all monitoring node pairs (e.g., node) of the power network under various operating conditions (e.g., peak, off-peak, and peak solar power generation). With nodes Historical electrical distance.

[0049] Step B12: Based on the statistical distribution of the electrical distance sample set, the 70th percentile of the electrical distance sample set is used as the initial value of the electrical threshold.

[0050] When applying the method, the data in the electrical distance sample set are sorted in ascending order, and the 70th percentile is used as the initial value of the electrical threshold.

[0051] Step B13: Determine the electrical threshold based on the initial value.

[0052] When applied, the electrical threshold includes the following formula:

[0053] ;

[0054] In the formula, Electrical threshold; This is the initial value for the electrical threshold. To optimize the coefficients, the optimization coefficients can be determined based on verification experience, and are generally taken as 0.9 to 1.1.

[0055] In practical implementation, the first electrical coupling strength index is the sensitivity of the total net power change in the current basic control area to the voltage of the boundary nodes of adjacent areas. Specifically, the first electrical coupling strength index includes the following formula:

[0056] ;

[0057] In the formula, The first electrical coupling strength index; This refers to the total net power change in the basic control area, for example, the total net power change in the basic control area A-1. This refers to the boundary node voltage of adjacent basic control regions, such as the boundary node voltage of basic control region A-2, where basic control region A-1 is adjacent to basic control region A-2.

[0058] The total net power change is the difference in net power between adjacent assessment periods. Specifically, the total net power change refers to the difference between the net power at the end of the current assessment period and the net power at the end of the previous assessment period. Net power is the algebraic sum of the power of distributed power sources, energy storage systems, and loads within the current basic control area A-1 and the power transmitted externally. Specifically, net power refers to the instantaneous value at the end of a certain assessment period after settling all power income and expenditure within a basic control area. The adjacent area boundary node voltage is the voltage of the nearest node in the adjacent basic control area A-2 of the current basic control area.

[0059] The evaluation period can be determined based on the timescale of system dynamic changes, communication and computing capabilities, and the real-time requirements of control response. Furthermore, fluctuations in distributed energy resources (such as photovoltaics and wind power) and loads typically occur significantly on a minute-by-minute scale; therefore, the evaluation period should not be too long to avoid missing critical coupling changes. Simultaneously, the evaluation period should be longer than the time required to complete a full evaluation (including data acquisition, communication transmission, and computation). Further, if the system has high requirements for voltage stability or power balance, the evaluation period should be shorter, for example, 5 minutes; if the system has significant inertia, the evaluation period can be appropriately extended, for example, 15 minutes.

[0060] In some embodiments, the evaluation period can be fixed, for example, 5 to 15 minutes; the evaluation period can also be dynamically adjusted, by setting a minimum period to ensure that the evaluation period is greater than the total system latency, avoiding invalid or chaotic evaluation behavior due to excessively fast response. Specifically, the evaluation period includes the following formula:

[0061] ;

[0062] In the formula, For the evaluation period; For the minimum period, Greater than the sum of system delays, generally speaking. Preferred ; This is a scaling factor, typically ranging from 0.1 to 0.3, to ensure that the evaluation frequency is higher than the system's dynamic frequency; This is the system time constant, which can be obtained through historical data analysis, such as the autocorrelation time of power fluctuations.

[0063] Step SS2: Compare the first electrical coupling strength index with the coupling threshold. If the first electrical coupling strength index remains greater than or equal to the coupling threshold for a first duration, then the associated basic control areas are grouped into a collaborative control group, and a regional coordination controller is selected as the master controller of the collaborative control group. Figure 2 .

[0064] In application, when two or more basic control areas are electrically tightly coupled, power fluctuations in one basic control area can affect the voltage of another. These basic control areas can be merged into a cooperative control group for coordinated control. To avoid frequent oscillations in the control structure due to transient fluctuations, merging is only considered necessary and dynamic grouping decisions are triggered when the strong coupling persists for a first duration. Furthermore, dynamic grouping decisions temporarily merge at least two basic control areas to form a cooperative control group. For example, the area coordination controller of this basic control area proposes a merge and communicates with the area coordination controllers of adjacent areas whose coupling strength index continuously exceeds the coupling threshold for a first duration to reach a merge consensus.

[0065] refer to Figure 3 In a power grid, changes in the operational status of a basic control area (e.g., basic control area A-1) may simultaneously create strong coupling with multiple adjacent basic control areas (e.g., basic control areas A-2, A-3, and A-4). In this case, merging basic control areas A-1, A-2, A-3, and A-4 into a coordinated control group can achieve large-scale resource coordination. Furthermore, refer to... Figure 4 Strong coupling relationships in power networks may not be one-to-one, but rather chain-like or forming local mesh structures. For example, basic control areas A-1 and A-2 are strongly coupled, and A-2 is also strongly coupled with A-3. Although the direct coupling between basic control areas A-1 and A-3 is not strong, through the transmission from basic control area A-2, basic control areas A-1, A-2, and A-3 are merged into a coordinated control group for unified optimization. After the coordinated control group is formed, under the unified coordination of the main controller, resource allocation can be optimized on a larger scale, resulting in lower overall operating costs, lower network losses, and better voltage quality. At this time, the scope of control commands covers the physical scope of electrical impacts, enabling the entire coordinated control group to share the burden of a large disturbance (such as a photovoltaic slump). For example, by making coordinated use of the resources of all basic control areas within the coordinated control group, neighborhood problems caused by strong coupling can be solved, thereby improving the resilience and reliability of the system.

[0066] In practical applications, to achieve a good balance between control effectiveness and system stability, the coupling threshold setting includes: acquiring historical data (e.g., historical coupling strength indicators for one quarter), sorting the historical data in ascending order, and using the 85th percentile as the baseline value for the coupling threshold. The coupling threshold is then determined based on this baseline value. Specifically, the coupling threshold includes the following formula:

[0067] ;

[0068] In the formula, This is the coupling threshold; As the baseline value; This is an empirical coefficient used to fine-tune the baseline value, typically ranging from 0.9 to 1.1. If the system experiences frequent disturbances, the empirical coefficient can be appropriately increased (e.g., from 1.05 to 1.1) to improve stability; if the system response is slow, the empirical coefficient can be appropriately decreased (e.g., from 0.9 to 0.95) to improve sensitivity.

[0069] Furthermore, to improve anti-interference capability and prevent frequent oscillations of the control structure caused by transient fluctuations (such as load switching and short-term power fluctuations of distributed sources), the first duration is generally 2 to 4 consecutive evaluation cycles. Further, this embodiment is based on the evaluation cycle... The first duration is determined by the minimum possible duration of the system disturbance. For example, the first duration is determined based on the ratio of the minimum possible duration of the system disturbance to the evaluation period, specifically including the following formula:

[0070] ;

[0071] In the formula, For the number of evaluation periods; For the evaluation period; This represents the minimum acceptable duration of a system disturbance, typically the maximum duration of a short-term disturbance that the system is expected to ignore.

[0072] Transient disturbances and persistent disturbances are distinguished by the minimum permissible duration of the system disturbance. Short-term disturbances are generally caused by switching operations, lightning strikes, or short-term load switching; their duration is short, typically a few seconds to tens of seconds, and the system should ignore them. Persistent disturbances are generally caused by a continuous decrease in photovoltaic output or a continuous increase in load; their duration is long, typically greater than one minute, and the system should respond. This is achieved by setting... This can filter out short-term fluctuations, avoid frequent switching of control structures, and improve system stability.

[0073] In practical implementation, the method for determining the master controller includes: calculating the comprehensive score of the regional coordination controllers configured in each basic control area of ​​the collaborative control group based on the regional coordination controller's computing power, communication reliability, operational stability, and electrical centrality. The regional coordination controller with the highest comprehensive score is selected as the master controller of the collaborative control group.

[0074] The overall score includes the following formula:

[0075] ;

[0076] ;

[0077] In the formula, For the first in the collaborative control group Regional coordination controller, It is a positive integer, and , This represents the total number of regional coordination controllers in the coordinated control group; For the first The overall score of each regional coordination controller; To calculate weights in real time; For real-time communication weights; For real-time weighting; Real-time electrical weights; For the first A score of the computing power of each regional coordination controller. ; For the first The communication reliability score of each regional coordination controller. ; For the first The rating of the operational stability of each regional coordination controller. ; For the first The electrical centrality score of each regional coordination controller. .

[0078] Furthermore, the real-time weight can be determined based on the real-time adjustment coefficient and the basic weight. The real-time adjustment coefficient includes a calculation adjustment coefficient, a communication adjustment coefficient, an operational adjustment coefficient, and an electrical adjustment coefficient; the calculation adjustment coefficient and the electrical adjustment coefficient are both 1; the communication adjustment coefficient is 1 + packet loss rate; and the operational adjustment coefficient is 1 + failure rate. The basic weight includes a calculation basic weight, a communication basic weight, an operational basic weight, and an electrical basic weight. The real-time weight includes a real-time calculation weight, a real-time communication weight, a real-time operational weight, and a real-time electrical weight. Specifically, the real-time weight includes the following formula:

[0079] ;

[0080] ;

[0081] , ;

[0082] , ;

[0083] , ;

[0084] , ;

[0085] In the formula, To calculate the basic weights; For communication basic weights; To run the basic weights; For electrical foundation weights; It is the accumulation of the basic weights; To calculate the adjustment factor; This is a communication adjustment factor; This is the operating adjustment factor; This is the electrical adjustment factor; To calculate weights in real time; For real-time communication weights; For real-time weighting; For real-time electrical weights.

[0086] By dynamically adjusting the weights of communication reliability and operational stability based on real-time packet loss rate and failure rate, the priority of the corresponding regional coordination controller as the main controller can be reduced when the controller communication quality deteriorates or the failure risk increases. This can guide the system to proactively avoid potential risks and prioritize the selection of the currently healthier and more reliable regional coordination controller to undertake the coordination tasks of the collaborative control group, thereby enhancing the robustness of the collaborative control group.

[0087] Step SS3: Use the main controller to evaluate the second electrical coupling strength index between each basic control area in the cooperative control group under its jurisdiction, and compare the second electrical coupling strength index with the coupling threshold. If the second electrical coupling strength index between the areas is less than the coupling threshold for a continuous second duration, then disband the cooperative control group and switch each basic control area back to the operating mode independently managed by the configured area coordination controller.

[0088] In practice, when changes in system operating status lead to reduced coupling between regions, maintaining a large-scale cooperative control group becomes unnecessary and even imposes additional burdens. The system should be de-grouped to return to a more economical and efficient operating mode. If the group is not de-grouped, the main controller will continue to perform global optimization calculations, and the basic control regions will continue to engage in extensive data communication, resulting in unnecessary consumption of computing and communication resources. Furthermore, the reaction speed of the cooperative control group may be slower than that of multiple independent basic control regions. Maintaining a grouped state after coupling has weakened will prevent a rapid response to rapid local changes.

[0089] When the second electrical coupling strength index between basic control areas remains below the coupling threshold for a continuous period of time, the coupling is determined to have weakened, triggering a decision to dissolve the merger and restore the autonomy of the basic control areas. Specifically, the main controller notifies all regional coordination controllers within the collaborative control group to declare the collaborative control group disbanded. Each basic control area switches back to a static operating mode managed independently by its own regional coordination controller until the next dynamic grouping is triggered.

[0090] In practical applications, the second electrical coupling strength index is the sensitivity of the total net power change of one basic control region within the cooperative control group to the boundary node voltage of another basic control region within the same group. Here, the total net power change is the difference in net power over adjacent evaluation periods; the net power is the value of the basic control region within the cooperative control group. The algebraic sum of internal distributed power sources, energy storage, loads, and external power output; the boundary node voltage is the basic control area within the cooperative control group. Central control area The voltage of the nearest node. Specifically, the second electrical coupling strength index includes the following formula:

[0091] ;

[0092] In the formula, This is the second electrical coupling strength index; For the basic control area within the collaborative control group The change in voltage at the boundary node; For the basic control area within the coordinated control group The total net power change.

[0093] In practical implementation, to prevent frequent disconnection and reconfiguration of the cooperative control group due to system transient fluctuations, the second duration is determined based on the first duration. For example, the second duration is greater than the first duration. Specifically, the second duration includes the following formula:

[0094] ;

[0095] In the formula, This is the first duration; This is the second duration; To adjust the coefficient, and Generally The adjustment factor should be between 1.5 and 2.0. If the system fluctuates greatly, the adjustment factor can be increased appropriately (e.g., between 1.8 and 2.0) to enhance stability; if the system response requirements are high, the adjustment factor can be decreased appropriately (e.g., between 1.5 and 1.7) to accelerate the dismantling speed.

[0096] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0098] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0099] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0100] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A source-grid-load-storage coordinated method, characterized in that, Includes the following steps: The power grid is divided into multiple basic control areas, each basic control area is configured with a regional coordination controller, and the regional coordination controller is used to evaluate the first electrical coupling strength index between the basic control area under its jurisdiction and its adjacent areas. Compare the first electrical coupling strength index with the coupling threshold: if the first electrical coupling strength index is greater than or equal to the coupling threshold for a continuous first duration, then the associated basic control areas are grouped into a collaborative control group, and a regional coordination controller is selected as the main controller of the collaborative control group. The main controller is used to evaluate the second electrical coupling strength index between each basic control area in the cooperative control group under its jurisdiction, and compares the second electrical coupling strength index with the coupling threshold. If the second electrical coupling strength index between the areas is less than the coupling threshold for a continuous second duration, the cooperative control group is disbanded, and each basic control area is switched back to the operating mode independently managed by the configured area coordination controller. The first electrical coupling strength index is the sensitivity of the total net power change of the current basic control area to the voltage of the boundary node of the adjacent area; The total net power change is the difference in net power between adjacent evaluation periods; net power is the algebraic sum of the distributed power sources, energy storage, loads, and outgoing power within the current basic control area; the voltage of the adjacent area boundary node is the voltage of the nearest node in the adjacent area of ​​the current basic control area. The second electrical coupling strength index is the sensitivity of the total net power change of one basic control region within the cooperative control group to the boundary node voltage of another basic control region within the cooperative control group. The total net power change is the difference in net power between adjacent evaluation periods; net power is the basic control area within the coordinated control group. The algebraic sum of internal distributed power sources, energy storage, loads, and external power output; the boundary node voltage is the basic control area within the cooperative control group. Central control area Voltage of the nearest node.

2. The source-grid-load-storage coordination method according to claim 1, characterized in that, The division of the power network into multiple basic control areas includes: Obtain the node impedance matrix of the power network; The electrical distance between nodes is determined using the node impedance matrix, whereby the electrical distance is the sum of the self-impedance values ​​of the two nodes minus twice the mutual impedance value between the two nodes. Starting from any node, a clustering algorithm is used to divide nodes whose electrical distance is less than the electrical threshold into the same basic control area, so as to form multiple basic control areas.

3. The source-grid-load-storage coordination method according to claim 2, characterized in that, The method for determining the electrical threshold includes: Obtain an electrical distance sample set, which includes historical electrical distances; Based on the statistical distribution of the electrical distance sample set, the 70th percentile of the electrical distance sample set is used as the initial value of the electrical threshold. The electrical threshold is determined based on the initial value.

4. The source-grid-load-storage coordination method according to claim 1, characterized in that, The evaluation period includes the following formula: ； In the formula, For the evaluation period; The minimum period; This is the scaling factor; This is the system time constant.

5. The source-grid-load-storage coordination method according to claim 1, characterized in that, The method for setting the coupling threshold includes: Obtain historical coupling strength indices, sort them in ascending order, and take the 85th percentile as the benchmark value for the coupling threshold. Determine the coupling threshold based on the benchmark value.

6. The source-grid-load-storage coordination method according to claim 1, characterized in that, The second duration is greater than the first duration; The first duration is determined based on the ratio of the minimum possible duration of the system disturbance to the evaluation period.

7. The source-grid-load-storage coordination method according to claim 1, characterized in that, Selecting a regional coordination controller as the master controller of the coordinated control group includes: The comprehensive score of the regional coordination controller configured in each basic control area of ​​the coordinated control group is calculated based on the regional coordination controller's computing power, communication reliability, operational stability, and electrical centrality. The regional coordination controller with the highest overall score will be designated as the master controller of the collaborative control group.

8. The source-grid-load-storage coordination method according to claim 7, characterized in that, The method for setting the real-time weights in the comprehensive score includes: The real-time weight is determined based on the real-time adjustment coefficient and the basic weight; The real-time adjustment coefficients include calculation adjustment coefficients, communication adjustment coefficients, operation adjustment coefficients, and electrical adjustment coefficients; the calculation adjustment coefficient and the electrical adjustment coefficient are both 1; the communication adjustment coefficient is 1 + packet loss rate; and the operation adjustment coefficient is 1 + failure rate. The basic weights include calculation basic weights, communication basic weights, operation basic weights, and electrical basic weights. The real-time weights include real-time calculation weights, real-time communication weights, real-time operation weights, and real-time electrical weights.

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