A safety evaluation method for active power distribution network multi-element subject collaborative control

Abstract

The application discloses a kind of active power distribution network multi-element subject collaborative control safety evaluation method, it is related to power grid safety technical field, for solving the problem that potential operation risk cannot be early warning, by monitoring each subject safety support trigger information Unified trigger analysis period is constructed, the node voltage deviation and line power flow direction data in this period are obtained, it is judged whether subject enters safety support state, only to trigger subject is marked and its voltage regulation margin and control output are collected;Introduce control output attenuation rate, safety suppression coefficient and conflict intensity factor, the control suppression relationship under the support of multiple subjects and the competition of safety degree of freedom are quantified, the proportion of historical safety degree of freedom is corrected, nonlinear system safety evaluation result is formed, the subject combination that cannot be simultaneously used as safety resource is identified, the safety boundary of distribution network is described, and basis is provided for operation evaluation and dispatching decision.

Description

Technical Field

[0001] This invention relates to the field of power grid security technology, and more specifically, to a security assessment method for multi-entity collaborative control of active distribution networks. Background Technology

[0002] With the widespread integration of diverse entities such as distributed photovoltaic power, wind power, energy storage systems, electric vehicle charging facilities, and various flexible loads into the distribution network, the traditional passive distribution network, dominated by centralized power generation and single loads, is gradually evolving into an active distribution network with multi-directional power flow and proactive regulation characteristics. While this evolution enhances system flexibility and renewable energy absorption capacity, it also brings complex dynamic interaction effects. In particular, when multiple entities participate in the coordinated control of grid security, their regulation capabilities influence each other, and competition for security freedom intensifies, posing new challenges to the safe and stable operation of the distribution network.

[0003] Currently, power distribution network security assessment methods mainly rely on steady-state power flow calculations or hypothetical analyses based on the control behavior of a single entity. Existing technologies have the following shortcomings:

[0004] 1. Most 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 about by the output fluctuation of distributed power sources, rapid load changes, and multi-entity coordinated adjustment, resulting in deviations between the assessment results and the actual situation.

[0005] 2. Existing research often treats each entity as an independent security resource, neglecting their mutual constraints and competition in voltage regulation and power flow control. This makes it difficult to accurately characterize the superposition and suppression effects of security capabilities when multiple entities provide concurrent support, and it is easy to overestimate the overall security margin of the system.

[0006] 3. Existing technologies typically evaluate based on fixed time segments or statistical periods, failing to incorporate security support trigger events to construct refined time periods. This makes it difficult to capture the temporal correlation and coupling characteristics of multi-entity response behaviors after a disturbance occurs, leading to delayed or misjudged warnings.

[0007] 4. Traditional methods often use linear superposition or fixed weights 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 degrees of freedom in actual operation.

[0008] 5. Due to the lack of quantitative means to measure the intensity and inhibition relationship of conflicts among multiple entities, existing methods are unable to accurately identify which entity combinations have security capability conflicts under specific operating conditions, and thus cannot provide a reliable list of "non-shared resources" for scheduling decisions.

[0009] To overcome the above shortcomings, it is urgent to propose a method that can dynamically perceive the collaborative behavior of multiple entities, quantify security inhibition relationships, and conduct refined security assessments based on triggering events, so as to improve the early warning capability of active distribution networks and the reliability of dispatching decisions under the condition of multiple entities coexisting. Summary of the Invention

[0010] To overcome the aforementioned deficiencies in the prior art, embodiments of the present invention provide a safety assessment method for multi-subject collaborative control of active distribution networks. This method utilizes a multi-subject state determination mechanism based on a safety support trigger analysis period, and combines control output attenuation rate, safety suppression coefficient, and conflict intensity factor to construct a dynamic correction model of the safety degrees of freedom of the multi-subjects, thereby solving the problems mentioned in the background art.

[0011] To achieve the above objectives, the present invention provides the following technical solution: a safety assessment method for multi-entity collaborative control of active power distribution networks, comprising the following steps:

[0012] 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;

[0013] 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.

[0014] 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.

[0015] 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.

[0016] In a preferred embodiment, step S1, which involves monitoring several entities of the distribution network, detecting the safety support trigger information of each entity, retrieving the trigger time based on the safety support trigger information, and setting the trigger analysis period, includes:

[0017] 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.

[0018] 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;

[0019] 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.

[0020] Extend the timeline forward and backward by a preset duration to construct a trigger analysis period centered on the trigger moment.

[0021] In a preferred embodiment, step S1 involves acquiring node voltage offset data and line power flow direction data for the trigger analysis period, including:

[0022] 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.

[0023] 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.

[0024] 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.

[0025] In a preferred embodiment, in step S2, determining whether the safety triggering state of each entity is activated by combining node voltage offset data and line power flow direction data includes:

[0026] 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.

[0027] 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.

[0028] 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.

[0029] In a preferred embodiment, 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:

[0030] 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.

[0031] 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.

[0032] When the security trigger state of the subject is determined to be activated, the subject is marked;

[0033] For the main body that has completed marking, the voltage regulation margin and control output are collected;

[0034] 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.

[0035] 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.

[0036] In a preferred embodiment, step S3 involves calculating the control output attenuation rate of the marker subject based on the control output quantity, analyzing the safety suppression coefficient of adjacent marker subjects in conjunction with the voltage regulation margin, and generating a conflict intensity factor by superimposing all marker subjects according to the safety suppression coefficient, including:

[0037] 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.

[0038] 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.

[0039] 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.

[0040] The ratio of the effective adjustment attenuation amount to the adjustment margin value is used as the safety inhibition coefficient of adjacent marker subjects;

[0041] 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.

[0042] The product of the standardized safety suppression energy and the safety suppression peak value is used as the conflict intensity factor.

[0043] In a preferred embodiment, step S4 involves accessing a historical database to retrieve the safe degrees of freedom ratio of the marked subject, adjusting the safe degrees of freedom ratio of the marked subject using a conflict intensity factor, and determining whether the marked subject poses a security risk based on the adjusted safe degrees of freedom ratio, thereby generating an alarm signal. This includes:

[0044] The percentage of secure freedom to access historical databases and retrieve tagged entities;

[0045] 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;

[0046] 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.

[0047] Conversely, it is determined that the subject of the marker does not pose a security risk;

[0048] An alarm signal is generated when the subject being marked poses a security risk.

[0049] The technical effects and advantages of this invention are as follows:

[0050] This invention monitors the safety support triggering information of each entity, constructs a unified triggering analysis period, and acquires node voltage offset data and line power flow direction data within this period to determine whether each entity has actually entered the safety support control state. Based on this, only entities in the safety triggering state are marked, and their voltage regulation margin and control output are further collected to characterize the actual regulation capability of the entity under the current operating state. By introducing control output attenuation rate, safety suppression coefficient, and conflict intensity factor, the control behavior suppression and safety degree-of-freedom competition when multiple entities simultaneously participate in safety support are quantitatively analyzed. The historical safety degree-of-freedom ratio is corrected, thus forming a nonlinear system safety assessment result. This identifies combinations of entities that cannot simultaneously serve as safety resources under the current state, reflects the distribution network safety boundary under the condition of multiple entities coexisting, and provides a reliable basis for the operation assessment and scheduling decisions of active distribution networks. Attached Figure Description

[0051] Figure 1 This is a flowchart illustrating the implementation of a safety assessment method for multi-entity collaborative control of an active power distribution network according to the present invention.

[0052] Figure 2 This is a schematic diagram illustrating the steps of a safety assessment method for multi-entity collaborative control of an active power distribution network according to the present invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] This invention monitors the safety support triggering information of each entity, constructs a unified triggering analysis period, and acquires node voltage offset data and line power flow direction data within this period to determine whether each entity has actually entered the safety support control state. Based on this, only entities in the safety triggering state are marked, and their voltage regulation margin and control output are further collected to characterize the actual regulation capability of the entity under the current operating state. By introducing control output attenuation rate, safety suppression coefficient, and conflict intensity factor, the control behavior suppression and safety degree-of-freedom competition when multiple entities simultaneously participate in safety support are quantitatively analyzed. The historical safety degree-of-freedom ratio is corrected, thus forming a nonlinear system safety assessment result to identify combinations of entities that cannot simultaneously serve as safety resources under the current state, reflecting the distribution network safety boundary under the condition of multiple entities coexisting.

[0055] Example 1, as Figures 1 to 2 As shown, a security assessment method for multi-entity collaborative control of an active power distribution network includes the following steps:

[0056] 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;

[0057] 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.

[0058] 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.

[0059] 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.

[0060] The specific implementation is as follows:

[0061] In step S1, several entities in the distribution network are continuously monitored, including distributed photovoltaic entities, electric vehicle entities, and grid-type energy storage entities.

[0062] 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. The safety support trigger information is a status indication information used to characterize whether the main body enters the safety support control mode. When the main body meets the preset safety support trigger conditions, it switches from the closed state to the open state.

[0063] It should be noted that the operation status monitoring unit is a functional unit set on each subject side for online sensing and status determination of the subject's operation status. It is used to establish a communication connection with the subject's local controller to obtain control status signals that reflect the subject's current control mode.

[0064] When a state transition of the safety support trigger information of any entity is detected, the time point corresponding to the state transition is recorded as the trigger time, which is used to characterize the starting time reference of the distribution network when a disturbance occurs and triggers the entity's safety support behavior. Based on the trigger time, a preset duration is extended forward and backward on the time axis to construct a trigger analysis period centered on the trigger time, which limits the data time range for analyzing the operation status of the distribution network, ensuring that subsequent analyses all revolve around the same disturbance event.

[0065] 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.

[0066] 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.

[0067] 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.

[0068] 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.

[0069] 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.

[0070] 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.

[0071] After completing the separate determinations for the voltage and power flow dimensions, the two types of determination results are processed comprehensively. That is, when the subject meets at least one of the safety trigger conditions in the voltage and power flow determination results, the safety trigger state of the determination subject is activated; when the subject does not meet the safety trigger conditions in either of the above two types of determination results, the safety trigger state of the determination subject is not activated.

[0072] When the safety trigger state of a subject is determined to be activated, the subject is marked. The mark is used to indicate that the subject has actually entered the safety support control mode and its subsequent operation may have a substantial impact on the voltage state or power flow structure of the distribution network. Subjects that do not meet the conditions for activating the safety trigger state are not marked and do not participate in the subsequent safety assessment and processing procedures.

[0073] For the marked entity, its operating parameters are further collected, specifically including voltage regulation margin and control output. The voltage regulation margin characterizes the remaining regulation capacity available for voltage regulation under the current safe support control state. It is calculated by the difference between the maximum allowable voltage regulation range of the entity and the voltage regulation amplitude already implemented by the entity during the trigger analysis period.

[0074] The control output quantity is used to characterize the intensity of the actual control action output by the subject during the trigger analysis period. It originates from the control command output by the subject's local controller and is used to reflect the actual control output level applied by the subject to the distribution network after the safety trigger state is activated.

[0075] By collecting the voltage regulation margin and control output, basic data support is provided for subsequent safety suppression analysis and conflict intensity calculation based on the main control behavior.

[0076] In step S3, a single marker subject is used as the processing object, and its control output during the trigger analysis period is analyzed in time series, and the control output is arranged in the order of the acquisition time.

[0077] Calculate the control output attenuation rate based on each control output quantity:

[0078] ;

[0079] in, To control the output attenuation rate, The number of data collection moments within the trigger analysis period. For the first Each data collection moment, For the first Control output at each acquisition moment;

[0080] The larger the control output decay rate, the weaker the marker's ability to maintain safety support under the current operating state, and the easier it is to suppress its safety contribution; the smaller the control output decay rate, the more stable the marker's control output remains during the trigger analysis period, and the more stably it can occupy and release the corresponding safety degrees of freedom under the current operating state.

[0081] The set of adjacent marker subjects is obtained by using the topology relation library. The set of adjacent marker subjects refers to other marker subjects in the electrical topology that have a direct coupling relationship with the marker subject, such as being on the same feeder or in the same voltage support area. This includes all adjacent marker subjects.

[0082] The safety suppression coefficient of adjacent markers is analyzed based on the voltage regulation margin of adjacent markers. Specifically, the voltage regulation margin of the marker and the adjacent marker are summed to obtain the regulation margin value. The voltage regulation margin of the marker is multiplied by the control output attenuation rate to obtain the effective regulation attenuation amount. The ratio of the effective regulation attenuation amount to the regulation margin value is used as the safety suppression coefficient of adjacent markers.

[0083] The security inhibition coefficient is used to quantify the degree to which the security support behavior of the marker subject inhibits the release of security capabilities of adjacent marker subjects. The larger the security inhibition coefficient, the higher the proportion of security freedom occupied by the marker subject in the current operating state, the more obvious the crowding-out and inhibition effect of its security support behavior on adjacent marker subjects, and the more restricted the security capabilities that adjacent marker subjects can actually release.

[0084] The maximum value of the safety suppression coefficient of adjacent marker subjects is taken as the safety suppression peak. The safety suppression energy is obtained by summing the squares of the safety suppression coefficients outside the safety suppression peak.

[0085] The product of the standardized safety suppression energy and the safety suppression peak value is used as the conflict intensity factor;

[0086] The conflict intensity factor reflects the intensity of competition and encroachment faced by the marker subject in terms of the safe degrees of freedom that can be actually released under the current operating state. The larger the conflict intensity factor, the more neighboring marker subjects the marker subject competes for safe degrees of freedom under the current operating state, and the higher the intensity of competition, the easier it is for its safety support behavior to be suppressed or offset.

[0087] It should be noted that the topology database is a basic data set used to store static and quasi-static structural information of the distribution network; the standardization methods include, but are 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. The application methods of standardization will not be elaborated here.

[0088] This step transforms the assessment from single-entity security capability evaluation to multi-entity inter-constraint relationship evaluation. It changes the perception of security contributions from being independent, additive static parameters to being modeled as dynamic results influenced by operational status and the behavior of adjacent entities, providing a quantitative basis for subsequent security degree of freedom correction and risk assessment.

[0089] In step S4, the historical database is accessed to retrieve the safety degree of freedom ratio of the marked subject. The safety degree of freedom ratio refers to the proportion of control degrees of freedom that can be allocated and used for safety regulation in the overall safety support system, which is obtained by statistical analysis based on the distribution network planning, the rated control capacity of the subject and historical safety support behavior during the historical operating cycle.

[0090] The effective safe degrees of freedom ratio is obtained by adjusting the safe degrees of freedom ratio of the marked subject using the conflict intensity factor. The formula for adjusting the safe degrees of freedom ratio is as follows: ,in, As a factor of conflict intensity, As a preset adjustment factor, For the percentage of safe degrees of freedom, The percentage of effective and safe degrees of freedom;

[0091] The effective security degree of freedom ratio reflects the proportion of the marked subject's security degree of freedom that can still be actually occupied and released, and characterizes the degree of security support available to the marked subject after considering the security suppression and conflict effects of multiple subjects;

[0092] The percentage of effective safe degrees of freedom is compared with a preset security threshold to determine whether the marked subject poses a security risk.

[0093] 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.

[0094] Conversely, it is determined that the subject of the marker does not pose a security risk;

[0095] When a security risk is detected in the marked entity, an alarm signal is generated to indicate that the security support capability of the marked entity has been affected by multi-entity conflict and may not be able to continue to play its expected security support role in subsequent disturbances.

[0096] It should be noted that the historical database is a basic data set used to store the operating status and safety assessment data of multiple entities in the distribution network during the historical operating cycle; the preset adjustment factor can be set according to the access scale, control type and operational risk bias of the multiple entities in the distribution network; the preset safety judgment threshold can be set according to the distribution network operation standards, historical accident statistics or dispatch strategy requirements.

[0097] This step improves the dynamic correction of the safety degree of freedom ratio in the historical database, transforming the safety assessment results from static ratios into dynamic indicators that reflect the current operating status and the interaction between the main entities. This avoids assessment bias caused by the simple superposition of safety capabilities and improves the accuracy of safety risk identification and the controllability of decision-making in active distribution networks under the condition of multiple entities coexisting.

[0098] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0099] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0100] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0101] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0102] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded 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: The method comprises the following steps: Step S1: monitoring a plurality of subjects of a power distribution network, detecting safety support trigger information of each subject, calling a triggering 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 subject is opened by comprehensively judging the node voltage offset data and the line power flow direction data, marking the subject when the safety trigger state is opened, collecting the voltage regulation margin and the control output of the marked subject; Step S3: calculating the control output decay rate of the marked subject based on the control output, analyzing the safety suppression coefficient of the adjacent marked subject in combination with the voltage regulation margin, and generating a conflict intensity factor by superimposing all the marked subjects according to the safety suppression coefficient; Step S4: accessing a historical database to call the safety freedom ratio of the marked subject, adjusting the safety freedom ratio of the marked subject by using the conflict intensity factor, and judging whether the safety risk of the marked subject exists based on the adjusted safety freedom ratio and generating an alarm signal. 2.The method of claim 1, wherein: In step S1, the plurality of subjects of the power distribution network are monitored, the safety support trigger information of each subject is detected, the triggering time is called according to the safety support trigger information, and the trigger analysis period is set, comprising: continuously monitoring a plurality of subjects in the power distribution network, the subjects including a distributed photovoltaic subject, an electric vehicle subject and a network construction type energy storage subject; collecting the control state signal of each subject through the operation state monitoring unit arranged on the side of each subject to detect whether each subject generates safety support trigger information; wherein the safety support trigger information is state indication information for indicating whether the subject enters a safety support control mode; when the safety support trigger information of any subject is detected to have a state switching, the time point corresponding to the state switching is recorded as the triggering time; a preset time length is respectively extended forward and backward on the time axis to build a trigger analysis period centered on the triggering time.

3. The method of claim 1, wherein the method further comprises: In step S1, the node voltage offset data and the line power flow direction data of the trigger analysis period are obtained, comprising: in the trigger analysis period, the operation state of the power distribution network is data collected to obtain the node voltage offset data and the line power flow direction data in the trigger analysis period; the node voltage offset data is derived from the voltage collection device 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 the power monitoring device arranged on the line or feeder, and is used to represent the flow direction change of the active power of each line in the trigger analysis period.

4. The method of claim 1, wherein the method further comprises: In step S2, the safety trigger state of each subject is judged by comprehensively judging the node voltage offset data and the line power flow direction data, comprising: in the trigger analysis period, the electrical access node of each subject is taken as an analysis object, and the node voltage offset data corresponding to the access node of the subject is called; when the absolute value of the node voltage offset data exceeds the voltage offset judgment threshold, it is determined that the subject satisfies the safety trigger condition in the voltage dimension; The line flow direction data of the corresponding line in the triggering analysis period is called, and the line flow direction before the triggering analysis period is compared and analyzed. When the line flow direction is detected to change, it is determined that the subject satisfies the security triggering condition in the flow dimension.

5. The method of claim 4, wherein the method further comprises: In step S2, the subject is marked when the security triggering state is turned on, and the voltage regulation margin and control output of the marked subject are collected, including: When the subject satisfies at least one of the security triggering conditions in the voltage dimension determination result and the flow dimension determination result, it is determined that the security triggering state of the subject is turned on; When the subject does not satisfy the security triggering condition in the voltage dimension determination result and the flow dimension determination result, it is determined that the security triggering state of the subject is not turned on; When it is determined that the security triggering state of the subject is turned on, the subject is marked; For the marked subject, the voltage regulation margin and control output are collected; The voltage regulation margin is calculated by subtracting the voltage regulation amplitude actually put into the subject in the triggering analysis period from the maximum voltage regulation range allowed by the subject. The control output is the control action intensity actually output by the subject in the triggering analysis period.

6. The method of claim 1, wherein: In step S3, the control output decay rate of the marked subject is calculated based on the control output, and the security suppression coefficient of the adjacent marked subject is analyzed combined with the voltage regulation margin, and the conflict intensity factor is generated by superimposing all the marked subjects according to the security suppression coefficient, including: Taking a single marked subject as the processing object, arranging the control output in the order of collection time, and calculating the control output decay rate based on each control output; The adjacent marked subject set of the marked subject is obtained through the topology relationship library, and each marked adjacent subject is included in the adjacent marked subject set; The voltage regulation margin of the marked subject and the adjacent marked subject is summed to obtain the regulation margin value, and the effective regulation decay amount is obtained by multiplying the voltage regulation margin of the marked subject by the control output decay rate; The ratio of the effective regulation decay amount to the regulation margin value is taken as the security suppression coefficient of the adjacent marked subject; The square of the maximum value of the security suppression coefficient is taken as the security suppression peak value, and the security suppression energy is obtained by summing the squares of the security suppression coefficients other than the security suppression peak value. The product of the standardized processing results of the security suppression energy and the security suppression peak value is taken as the conflict intensity factor.

7. The method of claim 1, wherein the method further comprises: In step S4, the security freedom degree proportion of the marked subject is called from the historical database, the security freedom degree proportion of the marked subject is adjusted using the conflict intensity factor, and whether the marked subject has a security risk is judged based on the adjusted security freedom degree proportion and an alarm signal is generated, including: Accessing the historical database to call the security freedom degree proportion of the marked subject; The effective security freedom degree proportion is obtained by adjusting the security freedom degree proportion of the marked subject using the conflict intensity factor; If the effective security freedom degree proportion is less than the preset security judgment threshold, it is judged that the marked subject has a security risk; Otherwise, it is judged that the marked subject does not have a security risk; An alarm signal is generated when the marked subject has a security risk.

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