A power distribution network collaborative control method and system

Abstract

The application discloses a power distribution network cooperative control method and system, and belongs to the field of power distribution network control. The method is as follows: based on the voltage data of each feeder node in the power distribution network obtained in real time, the voltage deviation value is calculated, and the source node is determined when the voltage deviation value of any node exceeds the first preset threshold; the electrical correlation feeder set of the source node is obtained to calculate the power interaction amount, and the operation coupling degree is evaluated based on the power interaction amount; the potential influence path is predicted based on the electrical coupling strength and the operation coupling degree, and the electrical parameter change rate of the several influence feeders in the potential influence path which have appeared operation parameter fluctuation is monitored; when the electrical parameter change rate is greater than the second preset threshold, the optimal target cooperative control scheme is generated, and power regulation is carried out based on the target cooperative control scheme to realize the cooperative control of the power distribution network. Therefore, by implementing the application, the cooperative control level and stability of the power distribution network can be improved.

Description

Technical Field

[0001] This invention relates to the field of power distribution network control, and in particular to a method and system for coordinated control of power distribution networks. Background Technology

[0002] With the large-scale integration of distributed power sources (such as photovoltaic and wind power), the random fluctuations in electric vehicle charging loads, and the widespread adoption of smart devices on the user side, the distribution network has transformed from a traditional unidirectional radial network into a complex system with multiple sources and bidirectional power flow. This transformation leads to a highly dynamic operating state of the power grid. Local faults or disturbances (such as voltage sags and current surges) can easily spread rapidly through electrical coupling effects between feeders, triggering cascading faults and even evolving into large-scale power outages, seriously threatening power supply reliability and socio-economic benefits. Against this backdrop, how to predict potential anomalies in advance and coordinate their resolution to improve the coordinated control level and stability of the distribution network has become an urgent need.

[0003] Currently, most methods for improving the collaborative control level of distribution networks rely on hierarchical distributed control systems based on local information and fixed thresholds. However, these methods have significant limitations and are difficult to effectively cope with the dynamic operating environment under high-proportion renewable energy integration. First, existing methods cannot predict the propagation path and speed of abnormal states based on the real-time coupling relationship of the power grid before a fault occurs, resulting in the inability to implement "pre-emptive" intervention and missed control opportunities. Second, traditional control strategies rely on offline-set, fixed coordination logic, which cannot quantitatively assess the electrical coupling strength and power interaction coupling degree between feeder nodes in real time. Therefore, it is difficult to accurately identify the source of risk and potential cascading paths when disturbances occur. Therefore, there is an urgent need to provide a method that can predict the propagation of abnormalities in advance and perform collaborative control based on global optimization, fundamentally improving the active defense capability and resilience of the distribution network. Summary of the Invention

[0004] This invention provides a method and system for coordinated control of power distribution networks, which can improve the level of coordinated control and stability of power distribution networks.

[0005] An embodiment of the present invention provides a distribution network coordinated control method, comprising:

[0006] Based on the voltage data of each feeder node in the distribution network acquired in real time, the voltage deviation value is calculated. When the voltage deviation value of any node exceeds the first preset threshold, the source node with the operational status deviation is identified.

[0007] Obtain the set of electrically associated feeders of the source node within a preset range, and calculate the power interaction amount between the source node and each associated feeder in the set of electrically associated feeders, so as to evaluate the operational coupling degree of the source node to each associated feeder based on the power interaction amount;

[0008] Based on the electrical coupling strength between the source node and each of the associated feeders and the degree of operational coupling, several potential influence propagation paths of the source node are predicted, and the rate of change of electrical parameters of several influence feeders in each influence propagation path that have experienced fluctuations in operational parameters is monitored in real time. The electrical coupling strength is calculated based on the current network topology and line parameters.

[0009] When the rate of change of the electrical parameters is greater than the second preset threshold, an optimal target coordinated control scheme is generated based on the operating coupling degree, real-time load rate and capacity margin of each of the affected feeders, and power regulation is performed based on the target coordinated control scheme to achieve coordinated control of the distribution network.

[0010] This application's embodiments, through real-time calculation of deviation values, can quickly capture anomalies and prevent problem propagation. Identifying source nodes focuses on the root cause of the problem, rather than surface symptoms, thus improving the targeting of control. By calculating power interaction quantities to assess the degree of operational coupling, the mutual influence relationship between source nodes and other feeders can be quantified. By calculating power interaction quantities, the method can objectively assess coupling strength and identify which feeders are most susceptible to the influence of source nodes. After assessing the degree of operational coupling, the control strategy can prioritize tightly coupled components, avoiding blind control, thereby improving the accuracy of coordinated control and resource utilization efficiency. Based on electrical coupling strength and operational coupling degree, the direction of fault propagation can be accurately predicted. Real-time monitoring of parameter change rate and setting a second preset threshold enable the system to promptly detect potential risks and trigger control before the problem worsens. The degree of operational coupling ensures that control actions target critically affected feeders, real-time load rate avoids overload risks during the control process, and capacity margin ensures that the control scheme operates within the safe range of equipment. By coordinating the operation of multiple feeders, secondary problems caused by islanded control are avoided, thereby improving the overall level of coordinated control and ensuring that the distribution network quickly recovers stability after disturbances. Compared with existing technologies, this application can improve the level of coordinated control and stability of power distribution networks.

[0011] Furthermore, the calculation of the voltage deviation value based on the real-time acquired voltage data of each feeder node in the distribution network is specifically as follows:

[0012] Based on the real-time current values ​​at each feeder node, the effective current value is calculated.

[0013] The line impedance value is determined based on the line parameters from each feeder node to the corresponding feeder head, and the voltage drop value from the feeder head to each feeder node is calculated based on the effective current value and the line impedance value.

[0014] The voltage value at the beginning of the feeder is obtained, and the voltage data of each feeder node is determined based on the voltage value and the voltage drop value. The voltage data is then compared with the preset rated voltage value to obtain the voltage deviation value.

[0015] By calculating the deviation value in real time, anomalies can be quickly captured, the problem can be prevented from spreading, and the source node can be easily identified in the future.

[0016] Further, the step of obtaining the set of electrically associated feeders of the source node within a preset range and calculating the power interaction between the source node and each associated feeder in the set of electrically associated feeders specifically involves:

[0017] From the network topology database of the power distribution automation master station, identify all associated feeders that have an electrical connection relationship with the source node within a preset range, and form the set of electrical associated feeders;

[0018] The active power and reactive power measurements at the interconnection switches between the source node and each associated feeder are collected in real time. Based on the active power and reactive power measurements, the power interaction quantity between the source node and each associated feeder is determined, wherein the power interaction quantity includes the power flow direction and power magnitude.

[0019] By calculating power interaction quantities, this method can objectively assess coupling strength and identify which feeders are most susceptible to the influence of source nodes. After assessing the degree of operational coupling, the control strategy can prioritize tightly coupled components, avoiding blind control and thus improving the accuracy of coordinated control and resource utilization efficiency.

[0020] Furthermore, the step of evaluating the operational coupling degree of the source node to each of the associated feeders based on the power interaction amount specifically includes:

[0021] The power interaction amount between the source node and each of the associated feeders is normalized to obtain the target power interaction amount.

[0022] The voltage deviation amplitude of the source node is obtained, and the voltage deviation amplitude is normalized to obtain the target voltage deviation amplitude.

[0023] Based on preset power weighting coefficients and deviation weighting coefficients, the target power interaction amount and the target voltage deviation amplitude are weighted and fused to determine the first operational coupling degree evaluation value of the source node to each of the associated feeders;

[0024] When the operational coupling degree evaluation value is greater than the third preset threshold, the operational coupling degree between the source node and the corresponding associated feeder is determined.

[0025] By calculating the degree of coupling during operation, it becomes easier to accurately predict the direction of fault propagation.

[0026] Furthermore, the prediction of several potential impact propagation paths of the source node based on the electrical coupling strength between the source node and each of the associated feeders and the operational coupling degree specifically includes:

[0027] Based on the current network topology, construct a distribution network topology with feeder nodes as vertices and electrical connections between feeders as edges;

[0028] Starting from the source node, all candidate propagation paths are identified, and for each candidate propagation path, an electrical coupling strength sequence between adjacent nodes on the path is calculated. Based on the electrical coupling strength sequence, the electrical coupling strength on each candidate propagation path is calculated.

[0029] For each of the candidate propagation paths, obtain the second operational coupling degree evaluation value between the source node and the first node on the path, and calculate the product of the electrical coupling strength and the second operational coupling degree evaluation value as the comprehensive propagation weight;

[0030] A depth-first search algorithm is used to traverse the network topology and select several paths whose comprehensive propagation weight exceeds a fourth preset threshold as potential influence propagation paths.

[0031] By calculating the degree of coupling during operation, it becomes easier to accurately predict the direction of fault propagation.

[0032] Furthermore, the real-time monitoring of the electrical parameter change rate of several influencing feeders in each of the influence propagation paths where operating parameter fluctuations have occurred specifically includes:

[0033] Identify several influencing feeders along each of the aforementioned influence propagation paths where fluctuations in operating parameters have occurred, and collect the electrical parameters of each influencing feeder in real time, obtaining the time series of the electrical parameters within a preset time window; wherein, the electrical parameters include the effective value of current, the effective value of voltage, active power, and reactive power;

[0034] Linear regression analysis was performed on the time series, and the slope of the regression line was calculated to determine the rate of change of electrical parameters.

[0035] By accurately quantifying the rate of change of electrical parameters, early warning of fault propagation trends can be achieved, providing a basis for timely triggering of collaborative control strategies, thereby transforming passive response into active defense and effectively improving the stability and control efficiency of power grid operation.

[0036] Furthermore, the optimal target coordinated control scheme is generated based on the operational coupling degree, real-time load rate, and capacity margin of each of the influencing feeders, specifically as follows:

[0037] Based on the real-time load rate and capacity margin of each of the aforementioned affected feeders, determine the corresponding load adjustment priority;

[0038] Based on the operational coupling degree, feasible load transfer paths between the affected feeders are determined, and a target coordinated control scheme is generated according to the load adjustment priority and the feasible load transfer paths, which includes at least one control command among load transfer, distributed power supply power adjustment, reactive power compensation equipment switching and load shedding control.

[0039] This high degree of coupling ensures that control actions target critical feeders, real-time load rate avoids overload risks during control, and capacity margin guarantees that the control scheme operates within the safe range of the equipment. By coordinating the operation of multiple feeders, secondary problems caused by islanded control are avoided, thereby improving the overall level of coordinated control and ensuring that the distribution network quickly recovers stability after disturbances.

[0040] Furthermore, the power regulation based on the target coordinated control scheme to achieve coordinated control of the distribution network specifically includes:

[0041] According to the control priority and execution sequence determined in the target collaborative control scheme, power adjustment instructions are sent to the corresponding controllable devices. The power adjustment instructions include at least one or more combinations of load transfer instructions, distributed power supply output adjustment instructions, reactive power compensation equipment switching instructions, and load shedding control instructions.

[0042] The response status of the controllable equipment and the power grid operating parameters are collected in real time. When it is detected that the power grid operating parameters do not meet the preset conditions, the parameters of the power regulation command are dynamically adjusted based on the response status until the distribution network returns to stable operation.

[0043] By coordinating the operation of multiple feeders, the secondary problems caused by islanded control are avoided, thereby improving the overall level of coordinated control and ensuring that the distribution network can quickly recover stability after disturbances.

[0044] Another embodiment of the present invention provides a power distribution network collaborative control system, including: an acquisition module, a calculation module, a prediction module, and a control module;

[0045] The acquisition module is used to calculate the voltage deviation value based on the voltage data of each feeder node in the distribution network acquired in real time. When the voltage deviation value of any node exceeds a first preset threshold, the source node with the operating status deviation is identified.

[0046] The calculation module is used to obtain the set of electrically associated feeders of the source node within a preset range, and calculate the power interaction between the source node and each associated feeder in the set of electrically associated feeders, so as to evaluate the operational coupling degree of the source node to each associated feeder based on the power interaction.

[0047] The prediction module is used to predict several potential impact propagation paths of the source node based on the electrical coupling strength between the source node and each of the associated feeders and the degree of operational coupling, and to monitor in real time the electrical parameter change rate of several impact feeders in each impact propagation path that have experienced operational parameter fluctuations, wherein the electrical coupling strength is calculated based on the current network topology and line parameters;

[0048] The control module is used to generate an optimal target coordinated control scheme based on the operating coupling degree, real-time load rate and capacity margin of each of the affected feeders when the rate of change of the electrical parameters is greater than a second preset threshold, and to perform power regulation based on the target coordinated control scheme to achieve coordinated control of the distribution network.

[0049] This application's embodiments, through real-time deviation calculation, can quickly capture anomalies and prevent problem propagation. Identifying source nodes focuses on the root cause of the problem, rather than surface symptoms, thus improving the targeting of control. By calculating power interaction quantities to assess the degree of operational coupling, the mutual influence relationship between source nodes and other feeders can be quantified. By calculating power interaction quantities, the method can objectively assess coupling strength and identify which feeders are most susceptible to the influence of source nodes. After assessing the degree of operational coupling, the control strategy can prioritize tightly coupled components, avoiding blind control, thereby improving the accuracy of coordinated control and resource utilization efficiency. Based on electrical coupling strength and operational coupling degree, the direction of fault propagation can be accurately predicted. Real-time monitoring of parameter change rate and setting a second preset threshold enable the system to promptly detect potential risks and trigger control before the problem worsens. The degree of operational coupling ensures that control actions target critically affected feeders. Real-time load rate avoids overload risks during the control process. Capacity margin ensures that the control scheme operates within the safe range of equipment. By coordinating the operation of multiple feeders, secondary problems caused by islanded control are avoided, thereby improving the overall level of coordinated control and ensuring that the distribution network quickly recovers stability after disturbances. Compared with existing technologies, this application can improve the level of coordinated control and stability of power distribution networks.

[0050] Furthermore, the prediction module includes:

[0051] The construction unit is used to construct a distribution network topology graph based on the current network topology, with feeder nodes as vertices and electrical connections between feeders as edges;

[0052] The first calculation unit is used to identify all candidate propagation paths starting from the source node, calculate the electrical coupling strength sequence between adjacent nodes on each candidate propagation path, and calculate the electrical coupling strength on each candidate propagation path based on the electrical coupling strength sequence.

[0053] The second calculation unit is used to obtain a second operational coupling degree evaluation value between the source node and the first node on the path for each candidate propagation path, and calculate the product of the electrical coupling strength and the second operational coupling degree evaluation value as the comprehensive propagation weight.

[0054] The filtering unit is used to traverse the network topology using a depth-first search algorithm to filter out several paths whose comprehensive propagation weight exceeds a fourth preset threshold as potential influence propagation paths. Attached Figure Description

[0055] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0056] Figure 1 This is a flowchart illustrating one embodiment of the power distribution network collaborative control method provided in this application;

[0057] Figure 2 This is a flowchart illustrating one embodiment of steps S201 to S204 provided in this application;

[0058] Figure 3 This is a flowchart illustrating one embodiment of steps S301 to S304 provided in this application;

[0059] Figure 4 This is a flowchart illustrating one embodiment of steps S401 to S402 provided in this application;

[0060] Figure 5 This is a schematic diagram of an embodiment of the power distribution network collaborative control system provided in this application. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0063] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0064] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0065] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0066] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0067] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0068] See Figure 1 To improve the level and stability of coordinated control of power distribution networks, an embodiment of the present invention provides a coordinated control method for power distribution networks, including steps S101 to S104.

[0069] Step S101: Based on the voltage data of each feeder node in the distribution network acquired in real time, calculate the voltage deviation value. When the voltage deviation value of any node exceeds the first preset threshold, identify the source node with the operating status deviation.

[0070] In some embodiments, calculating the voltage deviation value based on the voltage data of each feeder node in the distribution network acquired in real time specifically involves: calculating the effective current value based on the acquired real-time current value at each feeder node; determining the line impedance value based on the line parameters from each feeder node to the corresponding feeder head, and calculating the voltage drop value from the feeder head to each feeder node based on the effective current value and the line impedance value; acquiring the voltage value at the feeder head, determining the voltage data of each feeder node based on the voltage value and the voltage drop value, and performing a difference operation between the voltage data and a preset rated voltage value to obtain the voltage deviation value. Specifically: First, three-phase current signals are acquired in real time by current transformers deployed at each feeder node, converted into digital signals by a signal conditioning circuit, and transmitted to a data acquisition unit. Then, the data acquisition unit reads the instantaneous current value according to a set sampling period and calculates the effective current value reflecting the current actual load level using the root mean square algorithm. Subsequently, based on pre-determined line parameters (including conductor material, cross-sectional area, and line length), the line impedance value from each feeder node to the corresponding feeder head is determined. Then, according to Ohm's law, the effective current value is multiplied by the line impedance value to calculate the voltage drop from the feeder head to each node. Next, the voltage value at the feeder head is obtained through the substation bus voltage monitoring device. Subtracting the calculated voltage drop value from this head voltage value yields the actual voltage data for each feeder node. Finally, the actual voltage data is compared with the preset rated voltage value corresponding to that node to obtain the voltage deviation value.

[0071] It should be noted that the rated voltage value is determined according to the voltage level of the distribution network. When the voltage deviation exceeds the preset allowable limit, it indicates that the voltage quality of the node is abnormal, providing a key criterion for subsequent fault propagation analysis.

[0072] By calculating the deviation value in real time, anomalies can be quickly captured, the problem can be prevented from spreading, and the source node can be easily identified in the future.

[0073] In some embodiments, when the voltage deviation value of any node exceeds a first preset threshold, the source node with the operational status deviation is identified. Specifically, the voltage deviation value is compared with the first preset threshold in real time, wherein the first preset threshold is dynamically set according to the power grid operation procedures and historical data. When the voltage deviation value of a node continuously exceeds the first preset threshold, the system determines that the node has an operational status deviation and marks it as a "source node," while recording the time and magnitude of the deviation to provide a location basis for subsequent coupling analysis and propagation prediction. This achieves early detection and accurate location of abnormal states in the distribution network, providing key input for subsequent coordinated control.

[0074] Step S102: Obtain the set of electrically associated feeders of the source node within a preset range, and calculate the power interaction amount between the source node and each associated feeder in the set of electrically associated feeders, so as to evaluate the operational coupling degree of the source node to each associated feeder based on the power interaction amount;

[0075] In some embodiments, obtaining the set of electrically associated feeders of the source node within a preset range and calculating the power interaction between the source node and each associated feeder in the set of electrically associated feeders specifically involves: identifying all associated feeders that have an electrical connection with the source node within a preset range from the network topology database of the distribution automation master station, forming the set of electrically associated feeders; real-time acquisition of active power and reactive power measurements at the tie switches between the source node and each associated feeder, and determining the power interaction between the source node and each associated feeder based on the active power and reactive power measurements, wherein the power interaction includes power flow direction and power magnitude. Specifically, firstly, the distribution automation master station, as the core processing unit of the system, immediately initiates an associated feeder search program after identifying a source node with an operational status deviation. Subsequently, the master station system accesses its built-in or external network topology database, and, starting from the source node, automatically identifies all feeders that have a direct or indirect electrical connection with the source node based on a preset electrical distance range using a topology traversal algorithm, forming the "set of electrically associated feeders". Secondly, instantaneous measurements of three-phase active and reactive power are synchronously collected by measuring devices (such as smart meters or remote terminal units) deployed at the interconnection switches between the source node and each associated feeder. These measurements are then uploaded in real time to the distribution automation master station via a communication network. Next, these instantaneous measurements undergo preliminary processing, such as calculating the average power value within a time window to eliminate instantaneous fluctuations, thereby obtaining stable and reliable active and reactive power measurements. Finally, a power difference is calculated based on these measurements to reflect the net power flow and direction from one feeder to another. The power interaction between the source node and the target associated feeder is calculated by combining the power difference, active component, and reactive component. The magnitude of the power interaction is typically expressed as apparent power (kVA or MVA), and the flow direction is indicated by the sign of the power (e.g., positive indicates flow from the source node to the associated feeder, negative indicates reverse flow).

[0076] It should be noted that the network topology database dynamically maintains the latest connection relationships of the distribution network, including the layout of all feeders, the real-time opening and closing status of switches (such as sectionalizing switches and tie switches), and the connection information of electrical nodes.

[0077] It should be noted that if the tie switch is in the open state, it means that the two feeders are electrically isolated and the power interaction between them is recorded as zero.

[0078] By calculating power interaction quantities, this method can objectively assess coupling strength and identify which feeders are most susceptible to the influence of source nodes. After assessing the degree of operational coupling, the control strategy can prioritize tightly coupled components, avoiding blind control and thus improving the accuracy of coordinated control and resource utilization efficiency.

[0079] Please refer to Figure 2 In some embodiments, the step of evaluating the operational coupling of the source node to each of the associated feeders based on the power interaction amount includes steps S201 to S204.

[0080] Step S201: Normalize the power interaction amount between the source node and each of the associated feeders to obtain the target power interaction amount;

[0081] In some embodiments, due to differences in the rated capacity and operating levels of different feeders, directly comparing the original power values ​​lacks accuracy. Therefore, the power interaction quantity needs to be normalized to transform the actual value of the power interaction quantity into a unified, dimensionless relative value range, thereby eliminating the influence of dimensions and making the degree of power interaction between different feeder pairs comparable. The target power interaction quantity obtained in this step can more accurately characterize the relative strength of the power interaction.

[0082] Step S202: Obtain the voltage deviation amplitude of the source node, and normalize the voltage deviation amplitude to obtain the target voltage deviation amplitude;

[0083] In some embodiments, voltage deviation amplitude also needs to be normalized for collaborative analysis with power interaction quantities. The target voltage deviation amplitude is obtained by converting the absolute voltage deviation value into a deviation ratio relative to the normal operating voltage range. This indicator quantifies the degree of instability in the operating state of the source node itself, providing a basis for assessing its potential impact on adjacent feeders.

[0084] Step S203: Based on preset power weighting coefficients and deviation weighting coefficients, the target power interaction amount and the target voltage deviation amplitude are weighted and fused to determine the first operational coupling degree evaluation value of the source node to each of the associated feeders;

[0085] In some embodiments, the tightness of power interaction and the degree of anomaly of the source node itself jointly determine the likelihood of fault risk propagation. Therefore, it is necessary to integrate the two key indicators, the target power interaction amount and the target voltage deviation magnitude. Specifically, the two normalized indicators are weighted and fused using preset power weighting coefficients and deviation weighting coefficients. Through weighted fusion, a quantitative first operational coupling degree assessment value is finally calculated. This value comprehensively characterizes the electrical connection tightness and risk propagation potential between the source node and the associated feeder under the current operating state.

[0086] It should be noted that the weighting coefficients can be set based on historical power grid data or simulation optimization, aiming to balance the contributions of power correlation and voltage anomaly in the coupling assessment.

[0087] Step S204: When the operational coupling degree evaluation value is greater than the third preset threshold, determine the operational coupling degree between the source node and the corresponding associated feeder.

[0088] In some embodiments, when the calculated first operational coupling assessment value exceeds a third preset threshold, it indicates that the mutual influence between the source node and the associated feeder has exceeded the safe operating range, forming a significantly high-coupling operating state with a high risk of fault propagation. At this point, the system formally determines that there is an operational coupling degree between the associated feeder and the source node that requires high attention, and uses this result for subsequent propagation path prediction and control strategy generation.

[0089] It should be noted that the third preset threshold is a critical value determined based on statistical analysis of historical normal operation data and failure case data.

[0090] By calculating the degree of coupling during operation, it becomes easier to accurately predict the direction of fault propagation.

[0091] Step S103: Based on the electrical coupling strength between the source node and each of the associated feeders and the degree of operational coupling, predict several potential influence propagation paths of the source node, and monitor in real time the change rate of electrical parameters of several influence feeders in each influence propagation path that have experienced fluctuations in operational parameters. The electrical coupling strength is calculated based on the current network topology and line parameters.

[0092] Please refer to Figure 3 In some embodiments, predicting several potential impact propagation paths of the source node based on the electrical coupling strength between the source node and each of the associated feeders and the degree of operational coupling includes steps S301 to S304.

[0093] Step S301: Based on the current network topology, construct a distribution network topology with feeder nodes as vertices and electrical connections between feeders as edges;

[0094] In some embodiments, firstly, the distribution automation master station obtains the current network connection status of the distribution network from the real-time data acquisition and monitoring system, including the commissioning status of all feeders, the location information of tie switches and sectionalizing switches. Then, each feeder electrical node is abstracted as a vertex of the topology graph, and the electrical connection between nodes through lines or closed switches is abstracted as an edge, thereby constructing a topology graph model that reflects the real-time connectivity of the distribution network, providing a structural basis for subsequent path search.

[0095] Step S302: Starting from the source node, identify all candidate propagation paths, calculate the electrical coupling strength sequence between adjacent nodes on each candidate propagation path, and calculate the electrical coupling strength on each candidate propagation path based on the electrical coupling strength sequence.

[0096] In some embodiments, in the constructed topology graph, starting from the source node identified as having operational deviations, the system initially explores all possible extending electrical paths, forming multiple candidate propagation paths. For each candidate path, the system calculates the electrical coupling strength between each adjacent node along the path. Subsequently, the electrical coupling strengths of all adjacent node pairs along the path are combined (e.g., multiplied or weighted averaged) to obtain a quantitative value characterizing the tightness of electrical coupling along the entire path.

[0097] It should be noted that the electrical coupling strength is calculated based on the current network topology and line parameters. Specifically, for the edges between adjacent nodes in the topology diagram, the electrical coupling strength is calculated using the formula: Electrical Coupling Strength = k × (1 / Z) × S, where Z is the line impedance, S is the rated capacity of the feeder, and k is a normalization coefficient (e.g., set to 1 or adjusted according to the system baseline value). The line impedance consists of conductor resistance and reactance, and is calculated using the line parameters. Generally, the smaller the impedance and the larger the capacity, the tighter the coupling.

[0098] Step S303: For each of the candidate propagation paths, obtain the second operational coupling degree evaluation value between the source node and the first node on the path, and calculate the product of the electrical coupling strength and the second operational coupling degree evaluation value as the comprehensive propagation weight;

[0099] In some embodiments, in order to more accurately assess the likelihood of fault risk propagating along each candidate path, the inherent electrical coupling strength of the path itself (the result of step S302) is taken into account, and the real-time operational coupling degree between the source node and the directly adjacent node (i.e., the second operational coupling degree assessment value) is also incorporated. By multiplying these two key factors, a comprehensive propagation weight is calculated so as to dynamically reflect the comprehensive risk level of abnormal state propagating outward through the path under the current operating conditions.

[0100] Step S304: Use a depth-first search algorithm to traverse the network topology and select several paths whose comprehensive propagation weight exceeds a fourth preset threshold as potential influence propagation paths.

[0101] In some embodiments, firstly, a depth-first search algorithm is used to traverse all paths reachable from the source node. During the traversal, the algorithm calculates and compares the overall propagation weight of each path in real time; then, all paths with an overall propagation weight exceeding a pre-set fourth threshold are filtered out and marked as high-risk "potential impact propagation paths".

[0102] By calculating the transmission path, key channels that require focused monitoring and priority blocking measures can be identified, providing a direct basis for subsequent precise control.

[0103] In some embodiments, the real-time monitoring of the electrical parameter change rate of several influencing feeders in each of the influence propagation paths where operating parameter fluctuations have occurred specifically involves: identifying several influencing feeders in each of the influence propagation paths where operating parameter fluctuations have occurred, collecting the electrical parameters of each influencing feeder in real time, and obtaining the time series of the electrical parameters within a preset time window; wherein, the electrical parameters include the effective value of current, the effective value of voltage, active power, and reactive power; performing linear regression analysis on the time series, and calculating the slope of the regression line to determine the electrical parameter change rate. Specifically, firstly, for each predicted potential impact propagation path, based on real-time operational data obtained from the distribution automation master station, it is necessary to automatically identify which feeders have experienced significant fluctuations in operating parameters (e.g., current or voltage deviating significantly from their historical normal operating range) to determine the affected feeders. Next, for each marked affected feeder, key electrical parameters, including RMS current, RMS voltage, active power, and reactive power, are synchronously collected at a high frequency of milliseconds or seconds using high-precision monitoring terminals (such as PMUs or smart meters) deployed at the feeder nodes. These parameters are arranged chronologically to form a continuous time series covering a preset time window. Then, to quantify the rate of change of electrical parameters, the time series of electrical parameters collected within the preset time window is subjected to linear regression analysis using the least squares method to fit a straight line, and the slope of this line is calculated as the rate of change of electrical parameters. Finally, the rate of change of electrical parameters is compared with a preset second threshold. If the rate of change exceeds the second preset threshold, it indicates that the operating status of the affected feeder is deteriorating rapidly, and the fault propagation process is likely accelerating.

[0104] It should be noted that the length of the preset time window has been optimized to capture the dynamic trend of parameter changes without introducing too much historical lag information due to an excessively long window.

[0105] It should be noted that the slope represents the amount of change of the parameter per unit time; a positive slope indicates that the parameter is increasing, and a negative slope indicates that the parameter is decreasing.

[0106] This allows for the detection of higher-level alarms and provides crucial decision-making basis for the subsequent generation of target-oriented collaborative control schemes, thereby enabling proactive perception and rapid response to distribution network risks.

[0107] Step S104: When the rate of change of the electrical parameters is greater than the second preset threshold, an optimal target coordinated control scheme is generated based on the operating coupling degree, real-time load rate and capacity margin of each of the affected feeders, and power regulation is performed based on the target coordinated control scheme to achieve coordinated control of the distribution network.

[0108] In some embodiments, when it is determined that the rate of change of electrical parameters on one or more impact propagation paths exceeds a second preset threshold, i.e., when the fault propagation is considered to have entered an accelerated phase and there is an emergency situation of chain risk spread, the collaborative control strategy generation process needs to be initiated immediately.

[0109] In some embodiments, the optimal target coordinated control scheme is generated based on the operational coupling degree, real-time load rate, and capacity margin of each of the affected feeders: The corresponding load adjustment priority is determined according to the real-time load rate and capacity margin of each of the affected feeders; based on the operational coupling degree, feasible load transfer paths between the affected feeders are determined; and based on the load adjustment priority and the feasible load transfer paths, a target coordinated control scheme is generated that includes at least one control instruction among load transfer, distributed power supply power adjustment, reactive power compensation equipment switching, and load shedding control. Specifically, firstly, the operational coupling degree assessment value, real-time load rate (i.e., the ratio of current operating current to rated current), and capacity margin (i.e., the difference between line transmission power and design capacity) of each affected feeder are obtained, and a risk level score is calculated for each affected feeder. This score integrates the degree of load rate exceeding the standard and the degree of capacity margin deficiency. When the risk level score is high, it needs to be given higher priority in load adjustment, thus obtaining the load adjustment priority, to ensure that control measures are taken first for the most urgent risk sources. Then, the operational coupling degree between each feeder is used to determine feasible load transfer paths. All feasible paths are then constructed into a load transfer path matrix, and paths with higher capacity values ​​are selected from the matrix as feasible load transfer paths. Finally, by combining load adjustment priorities and feasible load transfer paths, a final target coordinated control scheme is generated. This scheme is a combined strategy containing multiple control commands, aiming to restore grid stability with minimal operating costs and the fastest response speed.

[0110] It should be noted that feeder pairs with high coupling have close electrical connections and strong power exchange capabilities, making them more suitable as sources and targets for load transfer.

[0111] It should be noted that the elements in the load transfer path matrix represent the feasibility value of transferring load from one feeder (source) to another feeder (target). This capability value is jointly determined by the capacity margin of the target feeder, the current carrying capacity of the tie switch, and the electrical coupling strength on the path.

[0112] It should be noted that the generation process of the target collaborative control scheme is a multi-objective optimization process. The core principle is to prioritize the most direct and fastest control measures for high-risk and high-priority feeders, and to make full use of the coupling relationship between feeders to transfer load in order to optimize the overall operating status. The specific generation method is not the focus of this application, so it will not be elaborated here.

[0113] It should be noted that the target coordinated control scheme may include a combination of one or more of the following schemes: (1) Load transfer: According to the determined feasible path, part of the load of the overloaded feeder will be smoothly and quickly transferred to the adjacent feeder with sufficient capacity through the tie switch. The transfer amount is accurately calculated to ensure that it will not cause the receiving feeder to be overloaded. (2) Distributed power adjustment: The active and reactive power output of distributed power sources (such as photovoltaic and energy storage systems) within the coverage of the control scheme is adjusted. For example, the energy storage system is instructed to discharge to support the local voltage, or the reactive power output of the photovoltaic inverter is adjusted to improve the power factor. (3) Switching of reactive power compensation equipment: The capacitor bank, reactor and other equipment in the substation or feeder are switched on and off to quickly compensate for reactive power and stabilize the voltage within the allowable range. (4) Load shedding control: As a last resort, when the above flexible adjustment means are insufficient to eliminate the risk, part of the non-critical load is cut off according to the predetermined load shedding sequence to ensure the overall safety of the power grid.

[0114] This high degree of coupling ensures that control actions target critical feeders, real-time load rate avoids overload risks during control, and capacity margin guarantees that the control scheme operates within the safe range of the equipment. By coordinating the operation of multiple feeders, secondary problems caused by islanded control are avoided, thereby improving the overall level of coordinated control and ensuring that the distribution network quickly recovers stability after disturbances.

[0115] Please refer to Figure 4 In some embodiments, the step of performing power regulation based on the target coordinated control scheme to achieve coordinated control of the distribution network includes steps S401 to S402:

[0116] Step S401: According to the control priority and execution sequence determined in the target collaborative control scheme, a power adjustment command is sent to the corresponding controllable device. The power adjustment command includes at least one or more combinations of load transfer command, distributed power supply output adjustment command, reactive power compensation device switching command and load shedding control command.

[0117] In some embodiments, the distribution automation master station decomposes the generated target coordinated control scheme into specific, executable instructions. Control priority ensures that critical operations (such as ensuring power supply to important loads) are executed first, while execution timing avoids operational conflicts; for example, reactive power compensation is performed first to raise the voltage level, followed by load transfer. These instructions are then sent to the corresponding controllable devices in the field via standard communication protocols (such as IEC 61850). Specifically, load transfer instructions are sent to the tie switch controller to change the power flow distribution; distributed generation output adjustment instructions are sent to the inverter or controller to adjust its active or reactive power output; reactive power compensation device switching instructions are sent to the capacitor bank or SVG / SVC controller to stabilize node voltage; and load shedding instructions are sent as a last resort to the relevant load switch.

[0118] Step S402: Real-time acquisition of the response status of the controllable device and the power grid operating parameters. When it is detected that the power grid operating parameters do not meet the preset conditions, the parameters of the power regulation command are dynamically adjusted based on the response status until the distribution network returns to stable operation.

[0119] In some embodiments, after an instruction is issued, the system does not passively wait but instead tracks feedback in real time from two aspects through a data acquisition and monitoring system: first, the response status of the controllable equipment itself, such as whether the switch has successfully operated and whether the actual output power of the distributed power source has reached the target value; second, the overall operating parameters of the power grid, such as whether the voltage amplitude of key nodes has recovered to the allowable deviation range, whether the current of each feeder is balanced, and whether the system power factor meets the standard. Subsequently, these real-time parameters are continuously compared with preset stable operating conditions. If a deviation is found, it indicates that the initial control scheme is insufficient or the situation has changed. The system will dynamically adjust the instruction parameters based on the actual response status, for example, increasing the power adjustment amount of the distributed power source, adding or switching another set of reactive power compensation equipment, or adjusting the target value of load transfer.

[0120] By coordinating the operation of multiple feeders, the secondary problems caused by islanded control are avoided, thereby improving the overall level of coordinated control and ultimately driving the distribution network to eliminate abnormal states, ensuring that the distribution network can quickly recover stability after disturbances.

[0121] This application's embodiments, through real-time calculation of deviation values, can quickly capture anomalies and prevent problem propagation. Identifying source nodes focuses on the root cause of the problem, rather than surface symptoms, thus improving the targeting of control. By calculating power interaction quantities to assess the degree of operational coupling, the mutual influence relationship between source nodes and other feeders can be quantified. By calculating power interaction quantities, the method can objectively assess coupling strength and identify which feeders are most susceptible to the influence of source nodes. After assessing the degree of operational coupling, the control strategy can prioritize tightly coupled components, avoiding blind control, thereby improving the accuracy of coordinated control and resource utilization efficiency. Based on electrical coupling strength and operational coupling degree, the direction of fault propagation can be accurately predicted. Real-time monitoring of parameter change rate and setting a second preset threshold enable the system to promptly detect potential risks and trigger control before the problem worsens. The degree of operational coupling ensures that control actions target critically affected feeders, real-time load rate avoids overload risks during the control process, and capacity margin ensures that the control scheme operates within the safe range of equipment. By coordinating the operation of multiple feeders, secondary problems caused by islanded control are avoided, thereby improving the overall level of coordinated control and ensuring that the distribution network quickly recovers stability after disturbances. Compared with existing technologies, this application can improve the level of coordinated control and stability of power distribution networks.

[0122] like Figure 5 As shown, based on the above method embodiments, corresponding apparatus embodiments are provided;

[0123] An embodiment of the present invention provides a power distribution network collaborative control system, including: an acquisition module 100, a calculation module 200, a prediction module 300, and a control module 400;

[0124] The acquisition module 100 is used to calculate the voltage deviation value based on the voltage data of each feeder node in the distribution network acquired in real time, and to identify the source node with the operating state deviation when the voltage deviation value of any node exceeds a first preset threshold.

[0125] The calculation module 200 is used to obtain the set of electrically associated feeders of the source node within a preset range, and calculate the power interaction amount between the source node and each associated feeder in the set of electrically associated feeders, so as to evaluate the operational coupling degree of the source node to each associated feeder based on the power interaction amount.

[0126] The prediction module 300 is used to predict several potential influence propagation paths of the source node based on the electrical coupling strength between the source node and each of the associated feeders and the degree of operational coupling, and to monitor in real time the change rate of electrical parameters of several influence feeders in each influence propagation path that have experienced fluctuations in operational parameters, wherein the electrical coupling strength is calculated based on the current network topology and line parameters;

[0127] The control module 400 is used to generate an optimal target coordinated control scheme based on the operating coupling degree, real-time load rate and capacity margin of each of the affected feeders when the rate of change of the electrical parameters is greater than a second preset threshold, and to perform power regulation based on the target coordinated control scheme to achieve coordinated control of the distribution network.

[0128] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement the power distribution network coordinated control method provided by any of the above-described method embodiments of the present invention.

[0129] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0130] Based on the above embodiments of the distribution network coordinated control method, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the distribution network coordinated control method of any embodiment of the present invention.

[0131] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0132] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0133] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0134] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the power distribution network coordinated control method described in any of the above-described method embodiments of the present invention.

[0135] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0136] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for coordinated control of a power distribution network, characterized in that, include: Based on the voltage data of each feeder node in the distribution network acquired in real time, the voltage deviation value is calculated. When the voltage deviation value of any node exceeds the first preset threshold, the source node with the operational status deviation is identified. Obtain the set of electrically associated feeders of the source node within a preset range, and calculate the power interaction amount between the source node and each associated feeder in the set of electrically associated feeders, so as to evaluate the operational coupling degree of the source node to each associated feeder based on the power interaction amount; Based on the electrical coupling strength between the source node and each of the associated feeders and the degree of operational coupling, several potential influence propagation paths of the source node are predicted, and the rate of change of electrical parameters of several influence feeders in each influence propagation path that have experienced fluctuations in operational parameters is monitored in real time. The electrical coupling strength is calculated based on the current network topology and line parameters. When the rate of change of the electrical parameters is greater than the second preset threshold, an optimal target coordinated control scheme is generated based on the operating coupling degree, real-time load rate and capacity margin of each of the affected feeders, and power regulation is performed based on the target coordinated control scheme to achieve coordinated control of the distribution network. Specifically, predicting several potential impact propagation paths of the source node based on the electrical coupling strength between the source node and each of the associated feeders and the operational coupling degree involves: constructing a distribution network topology with feeder nodes as vertices and electrical connections between feeders as edges based on the current network topology; identifying all candidate propagation paths starting from the source node, and calculating the electrical coupling strength sequence between adjacent nodes on each candidate propagation path; calculating the electrical coupling strength on each candidate propagation path based on the electrical coupling strength sequence; obtaining a second operational coupling degree evaluation value between the source node and the first node on the path for each candidate propagation path, and calculating the product of the electrical coupling strength and the second operational coupling degree evaluation value as a comprehensive propagation weight; and using a depth-first search algorithm to traverse the network topology and select several paths whose comprehensive propagation weight exceeds a fourth preset threshold as potential impact propagation paths.

2. The power distribution network coordinated control method according to claim 1, characterized in that, The voltage deviation value is calculated based on the voltage data of each feeder node in the distribution network acquired in real time, specifically as follows: Based on the real-time current values ​​obtained at each feeder node, the effective current value is calculated. The line impedance value is determined based on the line parameters from each feeder node to the corresponding feeder head, and the voltage drop value from the feeder head to each feeder node is calculated based on the effective current value and the line impedance value. The voltage value at the beginning of the feeder is obtained, and the voltage data of each feeder node is determined based on the voltage value and the voltage drop value. The voltage data is then compared with the preset rated voltage value to obtain the voltage deviation value.

3. The power distribution network coordinated control method according to claim 1, characterized in that, The step of obtaining the set of electrically associated feeders of the source node within a preset range and calculating the power interaction between the source node and each associated feeder in the set of electrically associated feeders specifically involves: From the network topology database of the power distribution automation master station, identify all associated feeders that have an electrical connection relationship with the source node within a preset range, and form the set of electrical associated feeders; The active power and reactive power measurements at the interconnection switches between the source node and each associated feeder are collected in real time. Based on the active power and reactive power measurements, the power interaction quantity between the source node and each associated feeder is determined, wherein the power interaction quantity includes the power flow direction and power magnitude.

4. The power distribution network coordinated control method according to claim 1, characterized in that, The evaluation of the operational coupling degree of the source node to each associated feeder based on the power interaction amount specifically includes: The power interaction amount between the source node and each of the associated feeders is normalized to obtain the target power interaction amount. The voltage deviation amplitude of the source node is obtained, and the voltage deviation amplitude is normalized to obtain the target voltage deviation amplitude. Based on preset power weighting coefficients and deviation weighting coefficients, the target power interaction amount and the target voltage deviation amplitude are weighted and fused to determine the first operational coupling degree evaluation value of the source node to each of the associated feeders; When the first operational coupling degree evaluation value is greater than the third preset threshold, the operational coupling degree between the source node and the corresponding associated feeder is determined.

5. The power distribution network coordinated control method according to claim 1, characterized in that, The real-time monitoring of the electrical parameter change rate of several influencing feeders that have experienced fluctuations in operating parameters along each of the aforementioned influence propagation paths specifically includes: Identify several influencing feeders along each of the aforementioned influence propagation paths where fluctuations in operating parameters have occurred, and collect the electrical parameters of each influencing feeder in real time, obtaining the time series of the electrical parameters within a preset time window; wherein, the electrical parameters include the effective value of current, the effective value of voltage, active power, and reactive power; Linear regression analysis was performed on the time series, and the slope of the regression line was calculated to determine the rate of change of electrical parameters.

6. The distribution network coordinated control method according to claim 1, characterized in that, The optimal target coordinated control scheme is generated based on the operational coupling degree, real-time load rate, and capacity margin of each of the aforementioned influencing feeders, specifically as follows: Based on the real-time load rate and capacity margin of each of the aforementioned affected feeders, determine the corresponding load adjustment priority; Based on the operational coupling degree, feasible load transfer paths between the affected feeders are determined, and a target coordinated control scheme is generated according to the load adjustment priority and the feasible load transfer paths, which includes at least one control command among load transfer, distributed power supply power adjustment, reactive power compensation equipment switching and load shedding control.

7. The power distribution network coordinated control method according to claim 6, characterized in that, The power regulation based on the target coordinated control scheme to achieve coordinated control of the distribution network specifically includes: According to the control priority and execution sequence determined in the target collaborative control scheme, power adjustment instructions are sent to the corresponding controllable devices. The power adjustment instructions include at least one or more combinations of load transfer instructions, distributed power supply output adjustment instructions, reactive power compensation equipment switching instructions, and load shedding control instructions. The response status of the controllable equipment and the power grid operating parameters are collected in real time. When it is detected that the power grid operating parameters do not meet the preset conditions, the parameters of the power regulation command are dynamically adjusted based on the response status until the distribution network returns to stable operation.

8. A power distribution network collaborative control system, characterized in that, include: The module comprises an acquisition module, a calculation module, a prediction module, and a control module. The acquisition module is used to calculate the voltage deviation value based on the voltage data of each feeder node in the distribution network acquired in real time. When the voltage deviation value of any node exceeds a first preset threshold, the source node with the operating status deviation is identified. The calculation module is used to obtain the set of electrically associated feeders of the source node within a preset range, and calculate the power interaction between the source node and each associated feeder in the set of electrically associated feeders, so as to evaluate the operational coupling degree of the source node to each associated feeder based on the power interaction. The prediction module is used to predict several potential impact propagation paths of the source node based on the electrical coupling strength between the source node and each of the associated feeders and the degree of operational coupling, and to monitor in real time the electrical parameter change rate of several impact feeders in each impact propagation path that have experienced operational parameter fluctuations, wherein the electrical coupling strength is calculated based on the current network topology and line parameters; The control module is used to generate an optimal target coordinated control scheme based on the operating coupling degree, real-time load rate and capacity margin of each of the affected feeders when the rate of change of the electrical parameters is greater than a second preset threshold, and to perform power regulation based on the target coordinated control scheme to achieve coordinated control of the distribution network. Specifically, predicting several potential impact propagation paths of the source node based on the electrical coupling strength between the source node and each of the associated feeders and the operational coupling degree involves: constructing a distribution network topology with feeder nodes as vertices and electrical connections between feeders as edges based on the current network topology; identifying all candidate propagation paths starting from the source node, and calculating the electrical coupling strength sequence between adjacent nodes on each candidate propagation path; calculating the electrical coupling strength on each candidate propagation path based on the electrical coupling strength sequence; obtaining a second operational coupling degree evaluation value between the source node and the first node on the path for each candidate propagation path, and calculating the product of the electrical coupling strength and the second operational coupling degree evaluation value as a comprehensive propagation weight; and using a depth-first search algorithm to traverse the network topology and select several paths whose comprehensive propagation weight exceeds a fourth preset threshold as potential impact propagation paths.

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