Safety assessment method for multi-element main body cooperative control of active power distribution network

Abstract

The invention discloses a safety assessment method for multi-element main body cooperative control of an active power distribution network, relates to the technical field of power grid safety, and is used for solving the problem that potential operation risks cannot be warned in advance. Acquiring node voltage offset and line power flow direction data in the time period, judging whether the main body enters a safe support state, only marking the trigger main body, and acquiring voltage regulation allowance and control output quantity of the trigger main body; a control output attenuation rate, a safety suppression coefficient and a conflict strength factor are introduced, a control suppression relation and safety freedom degree competition under multi-agent concurrent support are quantified, a historical safety freedom degree proportion is corrected, a nonlinear system safety assessment result is formed, an agent combination which cannot be used as a safety resource at the same time is identified, and a system safety assessment result is obtained. And a power distribution network safety boundary is described, and a basis is provided for operation evaluation and scheduling decision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid safety, more specifically, the present application relates to a safety evaluation method for multi-element subject collaborative control of active power distribution network. BACKGROUND

[0002] With the wide access of multi-element subjects such as distributed photovoltaic, wind power generation, energy storage system, electric vehicle charging facilities and various flexible loads in the distribution network, the traditional passive distribution network mainly based on centralized power generation and single load is gradually evolving into an active distribution network with multi-directional power flow and active regulation characteristics. This evolution, while improving system flexibility and renewable energy consumption capacity, also brings complex dynamic interaction effects, especially when multi-element subjects participate in grid safety collaborative control, their adjustment capabilities influence each other, and the safety freedom competition intensifies, bringing new challenges to the safe and stable operation of the distribution network.

[0003] At present, the safety evaluation method of the distribution network mainly relies on steady-state power flow calculation or assumption analysis based on single subject control behavior, and the existing technology has the following shortcomings: 1. Most of the existing methods are based on fixed operating points or typical operating conditions for safety analysis, which is difficult to adapt to the dynamic operating state brought by distributed power output fluctuation, load rapid change and multi-subject collaborative regulation, resulting in deviation between the evaluation results and the actual situation.

[0004] 2. Existing researches often regard each subject as an independent safety resource, ignoring the mutual restriction and competition relationship in voltage regulation and power flow control, and cannot accurately depict the safety capacity superposition effect and inhibition effect when multiple subjects support concurrently, which is easy to overestimate the overall safety margin of the system.

[0005] 3. The existing technology usually evaluates at fixed time sections or statistical periods, and fails to combine safety support triggering events for fine period construction, making it difficult to capture the time sequence correlation and coupling characteristics of multi-subject response behavior after disturbance, resulting in delayed warning or misjudgment.

[0006] 4. Traditional methods often use linear superposition or fixed weight to allocate the safety contribution of each subject, without considering dynamic factors such as control output attenuation and limited adjustment margin, and cannot reflect the nonlinear compression and redistribution process of safety freedom in actual operation.

[0007] 5. Due to the lack of quantitative means for the conflict intensity and inhibition relationship between multi-element subjects, the existing methods cannot accurately identify which subject combination has safety capacity conflict under a certain operating state, and thus cannot provide a reliable list of "unshareable resources" for dispatching decisions.

[0008] To overcome the above shortcomings, it is urgent to propose a method capable of dynamically perceiving multi-agent collaborative behavior, quantifying safety inhibition relationship, and performing fine safety evaluation based on trigger events, so as to improve the operation risk early warning capability and dispatching decision reliability of the active power distribution network under the condition of coexistence of multiple agents. SUMMARY

[0009] In order to overcome the above-mentioned defects of the prior art, embodiments of the present application provide a safety evaluation method for multi-agent collaborative control of an active power distribution network, which solves the problems raised in the above background technology by using a multi-agent state determination mechanism based on a safety support trigger analysis period, and combining a control output decay rate, a safety inhibition coefficient and a conflict intensity factor to construct a dynamic correction model of the safety freedom degree of the multiple agents.

[0010] To achieve the above-mentioned purpose, the present application provides the following technical scheme, a safety evaluation method for multi-agent collaborative control of an active power distribution network, comprising the following steps: Step S1: monitoring a plurality of agents in the power distribution network, detecting safety support trigger information of each agent, calling a trigger time according to the safety support trigger information and setting a trigger analysis period, obtaining node voltage offset data and line power flow direction data of the trigger analysis period; Step S2: judging whether the safety trigger state of each agent is opened or not by comprehensively considering the node voltage offset data and the line power flow direction data, marking the agent when the safety trigger state is opened, and collecting voltage regulation margin and control output of the marked agent; Step S3: calculating the control output decay rate of the marked agent based on the control output, analyzing the safety inhibition coefficient of the adjacent marked agent in combination with the voltage regulation margin, and generating a conflict intensity factor by superimposing all the marked agents according to the safety inhibition coefficient; Step S4: accessing a historical database to call the safety freedom degree proportion of the marked agent, adjusting the safety freedom degree proportion of the marked agent by using the conflict intensity factor, and judging whether the marked agent exists a safety risk based on the adjusted safety freedom degree proportion and generating an alarm signal.

[0011] In a preferred embodiment, in step S1, the monitoring of the plurality of agents in the power distribution network and the detection of the safety support trigger information of each agent according to the safety support trigger information to call the trigger time and set the trigger analysis period, comprises: continuously monitoring a plurality of agents in the power distribution network, the agents including a distributed photovoltaic agent, an electric vehicle agent and a network-forming energy storage agent; The control state signal of each agent is collected by the operation state monitoring unit arranged on the side of each agent to detect whether the safety support trigger information of each agent is generated; wherein the safety support trigger information is state indication information for indicating whether the agent enters a safety support control mode. When the state switching of the safety support trigger information of any subject is detected, the time point corresponding to the state switching is recorded as a trigger time; A preset time length is extended forward and backward on a time axis, respectively, to construct a trigger analysis period with the trigger time as the center.

[0012] In a preferred embodiment, in step S1, the node voltage deviation data and line power flow direction data of the trigger analysis period are acquired, including: In the trigger analysis period, data collection is performed on the operation state of the power distribution network to acquire the node voltage deviation data and line power flow direction data in the trigger analysis period; The node voltage deviation data is derived from voltage collection devices arranged at each node of the power distribution network, and represents the deviation of the actual node voltage of each node in the trigger analysis period from the corresponding rated voltage; The line power flow direction data is derived from power monitoring devices arranged at lines or feeders, and is used to represent the change in the flow direction of active power of each line in the trigger analysis period.

[0013] In a preferred embodiment, in step S2, the node voltage deviation data and line power flow direction data are comprehensively analyzed to determine whether the safety trigger state of each subject is opened, including: In the trigger analysis period, the electrical access node of each subject is taken as the analysis object, and the node voltage deviation data corresponding to the access node of the subject is retrieved; When the absolute value of the node voltage deviation data exceeds the voltage deviation determination threshold, it is determined that the subject satisfies the safety trigger condition in the voltage dimension; The line power flow direction data of the corresponding line in the trigger analysis period is retrieved, and is compared and analyzed with the line power flow direction before the trigger analysis period, and when a change in the line power flow direction is detected, it is determined that the subject satisfies the safety trigger condition in the power flow dimension.

[0014] In a preferred embodiment, in step S2, the subject is marked when the safety trigger state is opened, and the voltage regulation margin and control output of the marked subject are collected, including: When the subject satisfies at least one safety trigger condition in the voltage dimension determination result and the power flow dimension determination result, it is determined that the safety trigger state of the subject is opened; When the subject does not satisfy the safety trigger condition in the voltage dimension determination result and the power flow dimension determination result, it is determined that the safety trigger state of the subject is not opened; When it is determined that the safety trigger state of the subject is opened, the subject is marked; For the marked subject, the voltage regulation margin and control output are collected; The voltage adjustment margin is obtained by subtracting the voltage adjustment range allowed by the subject from the voltage adjustment range actually used by the subject during the trigger analysis period. The control output quantity is used to represent the control action intensity actually output by the subject during the trigger analysis period.

[0015] In a preferred embodiment, in step S3, the control output decay rate of the marked subject is calculated based on the control output quantity, the safety suppression coefficient of the adjacent marked subject is analyzed in combination with the voltage adjustment margin, and the conflict intensity factor is generated by superimposing all the marked subjects according to the safety suppression coefficient, including: The control output quantity is arranged in the order of the collection time, and the control output decay rate is calculated based on each control output quantity. The adjacent marked subject set of the marked subject is obtained from the topological relationship library, and each adjacent marked subject is included in the adjacent marked subject set. The voltage adjustment margin of the marked subject and the adjacent marked subject is summed to obtain the adjustment margin value, and the effective adjustment decay amount is obtained by multiplying the voltage adjustment margin of the marked subject by the control output decay rate. The ratio of the effective adjustment decay amount to the adjustment margin value is taken as the safety suppression coefficient of the adjacent marked subject. The square of the maximum value of the safety suppression coefficient is taken as the safety suppression peak value, and the safety suppression energy is obtained by summing the squares of the safety suppression coefficients other than the safety suppression peak value. The product of the safety suppression energy and the safety suppression peak value after standardization is taken as the conflict intensity factor.

[0016] In a preferred embodiment, in step S4, the safety freedom degree proportion of the marked subject is retrieved from the historical database, the safety freedom degree proportion of the marked subject is adjusted using the conflict intensity factor, and it is judged whether the marked subject has a safety risk and an alarm signal is generated based on the adjusted safety freedom degree proportion, including: The safety freedom degree proportion of the marked subject is retrieved from the historical database. The effective safety freedom degree proportion is obtained by adjusting the safety freedom degree proportion of the marked subject using the conflict intensity factor. If the effective safety freedom degree proportion is less than the preset safety judgment threshold, it is judged that the marked subject has a safety risk. Otherwise, it is judged that the marked subject does not have a safety risk. An alarm signal is generated when the marked subject has a safety risk.

[0017] The technical effects and advantages of the present application are: The application monitors the safety support trigger information of each subject, constructs a unified trigger analysis period, and obtains node voltage offset data and line power flow direction data in the period to determine whether each subject actually enters a safety support control state. On this basis, only the subject with the safety trigger state turned on is marked, and its voltage regulation margin and control output are further collected to depict the actual regulation capacity of the subject under the current operating state. By introducing the control output decay rate, safety suppression coefficient and conflict intensity factor, the control behavior suppression and safety freedom competition when multiple subjects participate in safety support at the same time are quantitatively analyzed, the historical safety freedom ratio is corrected, and then a nonlinear system safety evaluation result is formed to identify the subject combination that cannot be used as a safety resource at the same time under the current state, reflect the safety boundary of the distribution network under the condition of coexistence of multiple subjects, and provide a reliable basis for operation evaluation and scheduling decision of the active distribution network. BRIEF DESCRIPTION OF DRAWINGS

[0018] Fig. 1 The implementation flowchart of the safety evaluation method for the multi-subject collaborative control of the active distribution network according to the application.

[0019] Fig. 2 The step schematic diagram of the safety evaluation method for the multi-subject collaborative control of the active distribution network according to the application. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0021] The application monitors the safety support trigger information of each subject, constructs a unified trigger analysis period, and obtains node voltage offset data and line power flow direction data in the period to determine whether each subject actually enters a safety support control state. On this basis, only the subject with the safety trigger state turned on is marked, and its voltage regulation margin and control output are further collected to depict the actual regulation capacity of the subject under the current operating state. By introducing the control output decay rate, safety suppression coefficient and conflict intensity factor, the control behavior suppression and safety freedom competition when multiple subjects participate in safety support at the same time are quantitatively analyzed, the historical safety freedom ratio is corrected, and then a nonlinear system safety evaluation result is formed to identify the subject combination that cannot be used as a safety resource at the same time under the current state, reflect the safety boundary of the distribution network under the condition of coexistence of multiple subjects.

[0022] Embodiment 1, as Figs. 1-2As shown, a safety evaluation method for active power distribution network multi-element subject collaborative control includes the following steps: Step S1: Monitor several subjects in the power distribution network, detect the safety support trigger information of each subject, retrieve the trigger time according to the safety support trigger information and set the trigger analysis period, obtain the node voltage offset data and line power flow direction data in the trigger analysis period; Step S2: Judge whether the safety trigger state of each subject is opened by comprehensively judging the node voltage offset data and the line power flow direction data, mark the subject when the safety trigger state is opened, and collect the voltage regulation margin and control output of the marked subject; Step S3: Calculate the control output decay rate of the marked subject based on the control output, analyze the safety suppression coefficient of the adjacent marked subject combined with the voltage regulation margin, and generate the conflict intensity factor by superimposing all marked subjects according to the safety suppression coefficient; Step S4: Access the historical database to retrieve the safety freedom ratio of the marked subject, adjust the safety freedom ratio of the marked subject using the conflict intensity factor, and judge whether the marked subject has a safety risk based on the adjusted safety freedom ratio and generate an alarm signal.

[0023] The specific implementation is as follows: In step S1, several subjects in the power distribution network are continuously monitored, including distributed photovoltaic subjects, electric vehicle subjects and network-type energy storage subjects.

[0024] Through the operation state monitoring unit arranged on the side of each subject, the control state signal of each subject is collected to detect whether the safety support trigger information of each subject is generated, wherein the safety support trigger information is state indication information for indicating whether the subject enters the safety support control mode, and the state is switched from off to on when the subject meets the preset safety support trigger condition.

[0025] It should be noted that the operation state monitoring unit is a functional unit arranged on the side of each subject for online sensing and state determination of the subject operation state, which is used to establish a communication connection with the local controller of the subject to obtain the control state signal reflecting the current control mode of the subject.

[0026] When the safety support trigger information of any subject is detected to switch the state, the time point corresponding to the state switching is recorded as the trigger time, which is used to represent the starting time reference of the power distribution network when the disturbance occurs and triggers the subject safety support behavior. Based on the trigger time, a preset time length is extended forward and backward on the time axis to build a trigger analysis period centered on the trigger time, which limits the data time range for analyzing the operation state of the power distribution network to ensure that the subsequent analysis is carried out around the same disturbance event.

[0027] During the trigger analysis period, data on the operating status of the distribution network is collected to obtain node voltage offset data and line power flow direction data. The node voltage offset data comes from voltage acquisition devices deployed at each node of the distribution network and is used to characterize the deviation of the actual node voltage from its corresponding rated voltage during the trigger analysis period. This data reflects the voltage change characteristics of the distribution network under disturbance conditions. The line power flow direction data comes from power monitoring devices deployed at lines or feeders and is used to characterize the changes in the direction of active power flow on each line during the trigger analysis period. This data reflects whether the power transmission path of the distribution network reverses before and after the intervention of safety support measures.

[0028] It should be noted that voltage acquisition devices are measuring devices installed at various nodes of the distribution network to collect the voltage status of the nodes online. They are electrically connected to the electrical connection points of the corresponding nodes and are used to obtain the actual voltage value of the nodes in real time during operation. Power monitoring devices are measuring devices installed at the distribution network lines or feeders to monitor the active power transmission status of the lines online. They are electrically connected to the electrical circuits of the corresponding lines and are used to obtain the active power data of the lines in real time during operation.

[0029] Through the above process, the synchronous acquisition of node voltage offset data and line power flow direction data is achieved under the constraints of unified triggering time and triggering analysis period, providing a consistent time reference and status data basis for subsequent determination of the triggering status of each main safety support.

[0030] In step S2, during the trigger analysis period, the electrical access nodes of each subject are taken as the analysis objects, the node voltage offset data corresponding to the access node of the subject is retrieved, and the node voltage offset data is compared and analyzed according to the preset voltage offset judgment conditions. When the absolute value of the node voltage offset data exceeds the voltage offset judgment threshold, it is determined that the subject meets the safety triggering conditions in the voltage dimension.

[0031] It should be noted that the voltage deviation judgment threshold is a reference threshold set based on the rated operating standards and main control characteristics of the distribution network, used to distinguish between normal voltage fluctuations and abnormal voltage states that require the activation of safety support control.

[0032] Secondly, during the trigger analysis period, the feeders where each entity is located, or the lines adjacent to the entity's access node, are taken as the analysis objects. The power flow direction data of the corresponding lines during the trigger analysis period is retrieved and compared with the power flow direction before the start of the trigger analysis period. When a change in power flow direction is detected, it is determined that the entity meets the safety triggering conditions in the power flow dimension.

[0033] After the respective determination of the voltage dimension and the power flow dimension, the two types of determination results are comprehensively processed, that is, when the subject satisfies at least one of the safety trigger conditions in the voltage dimension determination result and the power flow dimension determination result, it is determined that the safety trigger state of the subject is opened; when the subject does not satisfy the safety trigger condition in the above two types of determination results, it is determined that the safety trigger state of the subject is not opened.

[0034] When the safety trigger state of the subject is opened, the subject is marked, which is used to indicate that the subject has actually entered the safety support control mode, and its subsequent running behavior may have a substantial impact on the voltage state or the power flow structure of the power distribution network. The subject that does not satisfy the safety trigger state opening condition is not marked and does not participate in the subsequent safety evaluation process.

[0035] For the subject that has completed the marking, the running parameters thereof are further collected, specifically including the voltage regulation margin and the control output. The voltage regulation margin is the remaining regulation capacity that can be used for voltage regulation under the current safety support control state of the subject, which is obtained by calculating the difference between the maximum voltage regulation range allowed by the subject and the voltage regulation amplitude that has been put into by the subject in the trigger analysis period; The control output is the intensity of the control action actually output by the subject in the trigger analysis period, which is derived from the control instruction output by the local controller of the subject, and is used to reflect the actual control output level of the subject on the power distribution network after the safety trigger state is opened.

[0036] By collecting the voltage regulation margin and the control output, basic data support is provided for subsequent safety suppression analysis and conflict intensity calculation based on the control behavior of the subject.

[0037] In step S3, the single marked subject is taken as the processing object, the control output of the subject in the trigger analysis period is subjected to time series analysis, and the control output is arranged in the order of collection time; The control output decay rate is calculated based on each control output: ; Wherein, is the control output decay rate, is the number of collection time in the trigger analysis period, is the th collection time, is the th collection time, The greater the control output decay rate value, the weaker the sustainability of the marked subject in maintaining the safety support capability in the current operating state, and the more easily the safety contribution is inhibited; the smaller the control output decay rate value, the more stable the control output remains in the triggering analysis period, and the more capable the marked subject is in stably occupying and releasing the corresponding safety degree in the current operating state; Obtain a set of adjacent marked subjects of the marked subject through a topological relationship library, which refers to other marked subjects that have a direct coupling relationship with the marked subject in the same feeder, the same voltage support area, etc. in the electrical topology, including each adjacent marked subject; Analyze the safety inhibition coefficient of the adjacent marked subject based on the voltage regulation margin of the adjacent marked subject, specifically, sum the voltage regulation margins of the marked subject and the adjacent marked subject to obtain a regulation margin value, multiply the voltage regulation margin of the marked subject by the control output decay rate to obtain an effective regulation decay amount, and take the ratio of the effective regulation decay amount to the regulation margin value as the safety inhibition coefficient of the adjacent marked subject; The safety inhibition coefficient is used to quantify the degree of inhibition of the safety support behavior of the marked subject on the release of safety capability of the adjacent marked subject; the greater the safety inhibition coefficient, the higher the proportion of the marked subject in occupying the safety degree in the current operating state, the more obvious the squeezing and inhibition effect of the safety support behavior of the marked subject on the adjacent marked subject, and the more limited the safety capability that can be actually released by the adjacent marked subject; Take the square of the maximum value of the safety inhibition coefficient of the adjacent marked subject as the safety inhibition peak value, and sum the squares of the safety inhibition coefficients outside the safety inhibition peak value to obtain the safety inhibition energy; The product of the safety inhibition energy and the safety inhibition peak value after standardization is taken as the conflict intensity factor; The conflict intensity factor reflects the competition and squeezing intensity faced by the safety degree that can be actually released by the marked subject in the current operating state; the greater the conflict intensity factor, the more adjacent marked subjects the marked subject competes with for the safety degree in the current operating state, and the higher the competition intensity, the more easily the safety support behavior is inhibited or offset.

[0038] It should be noted that the topological relationship library is a basic data set for storing static and quasi-static structure information of the power distribution network; the standardization method includes but is not limited to standard linear transformation based on interval scaling, Z-Score standardization method based on statistics, or normalization method based on nonlinear mapping function, and here the application method of standardization is not described.

[0039] The step realizes the change from single-agent security capability evaluation to multi-agent mutual restraint relationship evaluation, so that the security contribution is no longer regarded as independent, superimposable static parameters, but is modeled as a dynamic result jointly affected by the running state and the behavior of adjacent agents, providing a quantitative basis for subsequent security freedom correction and risk judgment.

[0040] In step S4, the security freedom ratio of the marked agent is called from the history database, which is the control freedom degree share of the marked agent in the overall security support system, which is obtained according to the distribution network planning, the rated control capability of the agent and the historical security support behavior statistics in the historical operation period. The effective security freedom ratio is obtained by adjusting the security freedom ratio of the marked agent using the conflict intensity factor, and the adjustment formula of the security freedom ratio is: Wherein, is the conflict intensity factor, is a preset adjustment factor, is the security freedom ratio, is the effective security freedom ratio; The effective security freedom ratio reflects the proportion of the marked agent that can still be actually occupied and released in its security freedom, and represents the available degree of security support of the marked agent after considering the multi-agent security inhibition and conflict influence; The effective security freedom ratio is compared with the preset security judgment threshold to determine whether the marked agent has a security risk: If the effective security freedom ratio is less than the preset security judgment threshold, it is determined that the marked agent has a security risk; Otherwise, it is determined that the marked agent does not have a security risk; When it is detected that the marked agent has a security risk, an alarm signal is generated to prompt that the security support capability of the marked agent has been affected by the multi-agent conflict and may not be able to continue to bear the expected security support role in the subsequent disturbance.

[0041] It should be noted that the history database is a basic data set for storing the multi-agent running state and security evaluation related data of the distribution network in the historical operation period; the preset adjustment factor can be set according to the access scale of the multi-agent in the distribution network, the type of agent control and the operation risk preference; the preset security judgment threshold can be set according to the distribution network operation standard, the historical accident statistics result or the dispatching strategy requirement.

[0042] The step improves the dynamic correction of the security freedom ratio in the historical database, converts the security evaluation result from a static ratio into a dynamic index reflecting the current running state and the influence of the subject interaction, thereby avoiding the evaluation deviation caused by the simple superposition of security capabilities, and improving the security risk identification accuracy and decision controllability of the active power distribution network under the condition of coexistence of multiple subjects.

[0043] Finally, it should be noted that the terms such as first and second, etc. are used herein only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0044] Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0045] In this document, the singular forms "a", "an" and "the" can also include plural forms unless the context clearly indicates otherwise. It should also be understood that the terms "include", "contain" or "have" and the like specify the presence of stated features, integers, steps, operations, components, parts or combinations thereof, but do not exclude the presence or addition of one or more other features, integers, steps, operations, components, parts or combinations thereof. The term "and / or" used in this specification includes any and all combinations of the associated listed items.

[0046] The various embodiments in the specification are described in a progressive manner, each embodiment focuses on the difference from other embodiments, and each embodiment can be combined as needed, and the same and similar parts refer to each other.

[0047] The above description of the disclosed embodiments enables those skilled in the art to implement or use the various modifications of the embodiments of the present application, and it will be obvious to those skilled in the art that the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A safety assessment method for multi-entity collaborative control of active power distribution networks, characterized in that: Includes the following steps: Step S1: Monitor several main entities of the distribution network, detect the safety support trigger information of each entity, retrieve the trigger time based on the safety support trigger information and set the trigger analysis period, and obtain the node voltage offset data and line power flow direction data during the trigger analysis period; Step S2: Combine node voltage offset data and line power flow direction data to determine whether the safety trigger status of each main body is activated. When the safety trigger status is activated, mark the main body and collect the voltage regulation margin and control output of the marked main body. Step S3: Calculate the control output attenuation rate of the marker body based on the control output quantity, analyze the safety suppression coefficient of adjacent marker bodies in combination with the voltage regulation margin, and generate the conflict intensity factor by superimposing all marker bodies according to the safety suppression coefficient. Step S4: Access the historical database to retrieve the safe degree of freedom ratio of the marked subject, adjust the safe degree of freedom ratio of the marked subject using the conflict intensity factor, determine whether there is a security risk to the marked subject based on the adjusted safe degree of freedom ratio, and generate an alarm signal.

2. The safety assessment method for multi-entity collaborative control of an active power distribution network according to claim 1, characterized in that: In step S1, the monitoring of several entities in the power distribution network, the detection of safety support trigger information for each entity, and the retrieval of trigger times and setting of trigger analysis periods based on the safety support trigger information include: Continuous monitoring is conducted on several entities in the power distribution network, including distributed photovoltaic entities, electric vehicle entities, and grid-type energy storage entities. By deploying operation status monitoring units on each main body side, the control status signals of each main body are collected to detect whether each main body generates safety support trigger information; among which, safety support trigger information is status indication information used to characterize whether the main body enters the safety support control mode; When a state change is detected in the security support trigger information of any subject, the time point corresponding to the state change is recorded as the trigger time. Extend the timeline forward and backward by a preset duration to construct a trigger analysis period centered on the trigger moment.

3. The safety assessment method for multi-entity collaborative control of an active power distribution network according to claim 1, characterized in that: In step S1, node voltage offset data and line power flow direction data for the trigger analysis period are acquired, including: During the trigger analysis period, data on the operating status of the distribution network are collected to obtain node voltage offset data and line power flow direction data during the trigger analysis period. The node voltage offset data comes from the voltage acquisition devices deployed at each node of the distribution network, and represents the degree of deviation of the actual node voltage from the corresponding rated voltage during the trigger analysis period. The power flow direction data comes from power monitoring devices installed on the lines or feeders, and is used to characterize the changes in the direction of active power flow in each line during the trigger analysis period.

4. The safety assessment method for multi-entity collaborative control of an active power distribution network according to claim 1, characterized in that: In step S2, the system combines node voltage offset data and line power flow direction data to determine whether the safety triggering status of each entity is activated, including: During the trigger analysis period, the electrical access nodes of each subject are taken as the analysis objects, and the node voltage offset data corresponding to the access node of the subject is retrieved. When the absolute value of the node voltage offset data exceeds the voltage offset judgment threshold, the judgment subject meets the safety triggering condition in the voltage dimension. The power flow direction data of the corresponding line during the trigger analysis period is retrieved and compared with the power flow direction of the line before the start of the trigger analysis period. When a change in the power flow direction is detected, it is determined that the subject meets the safety triggering conditions in the power flow dimension.

5. The safety assessment method for multi-entity collaborative control of an active power distribution network according to claim 4, characterized in that: In step S2, when the safety trigger state is activated, the main body is marked, and the voltage regulation margin and control output of the marked main body are collected, including: The safety triggering state of the main body is activated when the main body meets at least one of the safety triggering conditions in the voltage dimension judgment result and the power flow dimension judgment result. When the subject fails to meet the safety triggering conditions in both the voltage dimension and power flow dimension judgment results, the safety triggering state of the subject is not activated. When the security trigger state of the subject is determined to be enabled, the subject is marked; For the main body that has completed marking, the voltage regulation margin and control output are collected; The voltage regulation margin is calculated by the difference between the maximum allowable voltage regulation range of the main body and the voltage regulation amplitude that the main body has already invested during the trigger analysis period. The control output quantity is used to characterize the strength of the control effect of the subject's actual output during the trigger analysis period.

6. The safety assessment method for multi-entity collaborative control of an active power distribution network according to claim 1, characterized in that: In step S3, the control output attenuation rate of the marker body is calculated based on the control output quantity. The safety suppression coefficient of adjacent marker bodies is analyzed in conjunction with the voltage regulation margin. Based on the safety suppression coefficient, all marker bodies are superimposed to generate a conflict intensity factor, including: Taking a single marker as the processing object, the control output quantities are arranged in the order of acquisition time, and the control output attenuation rate is calculated based on each control output quantity; Obtain the set of neighboring tag subjects of the tag subject through the topology relation database. The set of neighboring tag subjects includes the subjects adjacent to each tag. The adjustment margin value is obtained by summing the voltage adjustment margins of the main marker and the adjacent markers. The effective adjustment attenuation amount is obtained by multiplying the voltage adjustment margin of the main marker by the control output attenuation rate. The ratio of the effective adjustment attenuation amount to the adjustment margin value is used as the safety inhibition coefficient of adjacent marker subjects; The square of the maximum value of the safety suppression coefficient is taken as the safety suppression peak value. The safety suppression energy is obtained by summing the squares of the safety suppression coefficients outside the safety suppression peak value. The product of the standardized security suppression energy and the security suppression peak value is used as the conflict intensity factor.

7. The safety assessment method for multi-entity collaborative control of an active power distribution network according to claim 1, characterized in that: In step S4, the historical database is accessed to retrieve the safe degree-of-freedom ratio of the marked subject. This ratio is then adjusted using a conflict intensity factor. Based on the adjusted safe degree-of-freedom ratio, it is determined whether the marked subject poses a security risk and an alarm signal is generated, including: The percentage of secure freedom to access historical databases and retrieve tagged entities; The effective safe degree of freedom ratio is obtained by adjusting the safe degree of freedom ratio of the marked subject using the conflict intensity factor; If the percentage of effective safe degrees of freedom is less than the preset safety judgment threshold, then the marked subject is judged to have a security risk. Conversely, it is determined that the subject of the marker does not pose a security risk; An alarm signal is generated when the subject being marked poses a security risk.

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