Safety control system for power distribution control box

Abstract

The invention relates to the technical field of intelligent power distribution control, in particular to a safety control system for a power distribution control box, which comprises a data acquisition module, an abnormity preliminary screening module, a scheduling judgment module, a load state detection module and a load distribution optimization module. According to the invention, operation parameters such as internal temperature, voltage difference and load current of the power distribution control box are collected in real time, abnormal time tolerance matching is carried out in combination with planned power failure and power transmission scheduling information, and the system can effectively identify temperature abnormity and distinguish scheduling fluctuation and potential faults in a plan; a partition response mechanism is established based on load deviation measurement, corresponding control strategies are implemented for different abnormal intervals, meanwhile, the priority of the distribution box with the abnormal load is dynamically reconstructed, the scheduling sequence is optimized, and the adjustment process is automatically terminated, so that the stability and the safety of the power distribution system in a complex load fluctuation environment are enhanced; operation and maintenance resource configuration is obviously optimized, and the method is suitable for risk early warning and control optimization of a large-scale intelligent power distribution scene.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent power distribution control, and particularly relates to a safety control system for a power distribution control box. BACKGROUND

[0002] With the rapid development of smart grid and power distribution automation technology, the safe and stable operation of the power distribution system has become an important foundation for ensuring the quality of power supply and the safety of user power consumption. As a key node in the power distribution network, the power distribution control box bears multiple functions such as power distribution, load monitoring and protection control.

[0003] In recent years, with the diversification and complication of power distribution load, the internal environment and operating state of the power distribution control box show highly dynamic change characteristics, and the traditional single-point monitoring and manual inspection method cannot meet the requirements of real-time and accuracy.

[0004] In the power distribution control system, real-time collection of operating parameters such as temperature, current, and pressure difference through sensors, combined with dispatching plans, realizes dynamic monitoring and abnormal identification, and becomes a key technology for improving the intelligent level of power distribution safety. There are various power distribution safety control schemes based on environmental monitoring and data analysis at home and abroad. For example, in the prior art, an intelligent microcontroller is used to collect and locally control the environmental parameters of a single power distribution box, and local fault warning is realized through the fusion of environmental information and power consumption data, but such schemes are mostly limited to single-point devices, lack of collaborative management capability among multiple power distribution boxes, and are difficult to form a global dynamic scheduling and risk response mechanism.

[0005] In addition, some existing systems rely on complex sensor integration and mechanical driving devices, increasing installation and maintenance costs and reducing the universality and application value of the system. More importantly, the current technology generally lacks the ability to distinguish between planned power-on and power-off scheduling and load fluctuations in abnormal identification, cannot accurately distinguish between normal scheduling fluctuations and potential faults, and thus causes frequent false alarms, affecting operation and maintenance efficiency. At the same time, there is a lack of a partition control response mechanism based on load deviation measurement, which cannot realize rapid partition power-off of abnormal loads and dynamic adjustment of priority, limiting the emergency handling capability of the system in emergency events.

[0006] Chinese Patent Publication No. CN115664039A discloses a power distribution safety control system, which includes a management background for managing the power distribution of a community; an indoor power distribution box for distributing power to corresponding users and acquiring power consumption information of the users; an environment collection device for collecting environmental information of the indoor power distribution box; an intelligent microcontroller for acquiring the environmental information collected by the environment collection device and the power consumption information collected by the indoor power distribution box, and generating a local control command based on the environmental information and the power consumption information to control the corresponding indoor power distribution box, and feeding back the local control command to the management background.

[0007] At the same time, the intelligent microcontroller in the prior art can only locally control a single incoming household distribution box, lacks coordinated management and partition control of multiple distribution boxes, and cannot realize dynamic safety adjustment of the overall power distribution system, with limited safety protection range; the environmental collection device integrates multiple sensors and a complex rotary drive mounting mechanism, resulting in increased installation difficulty and maintenance cost, affecting the universality and popularization and application of the system; the fire extinguishing system starts depending on environmental information determination, lacks multi-dimensional intelligent analysis and real-time dynamic evaluation, and the precision and timeliness of fire response are insufficient; and lacks real-time monitoring of load abnormalities and partition control response mechanism, and cannot quickly implement partition power failure and adjustment of abnormal loads, reducing the emergency handling efficiency of emergencies. SUMMARY

[0008] Therefore, the present application provides a safety control system for a power distribution control box to overcome the problem of low emergency handling efficiency caused by the lack of automatic adjustment of power distribution scheduling priority in combination with the internal fault type of the distribution box in the prior art.

[0009] To achieve the above-mentioned purpose, the present application provides a safety control system for a power distribution control box, comprising:

[0010] A data acquisition module comprising a sensing device arranged in each power distribution control box in the monitored area, for collecting operating parameter information in any power distribution control box;

[0011] An abnormality preliminary screening module connected to the data acquisition module, for judging whether there is a temperature abnormality in the power distribution control box based on the operating parameter information, and when there is, matching the time tolerance with the planned power outage scheduling information to judge whether the current abnormal period is in the planned power outage period;

[0012] A scheduling judgment module connected to the abnormality preliminary screening module, for judging the temperature abnormality state when the current abnormal period is in the planned power outage period, determining the temperature abnormality origin category in the second abnormal state, and executing the corresponding control adjustment strategy;

[0013] A load state detection module connected to the data acquisition module and the abnormality preliminary screening module, respectively, for determining that the power distribution control box is an abnormal power distribution control box when the current abnormal period is not in the planned power outage period, detecting the current load state of the abnormal power distribution control box, obtaining a power distribution deviation analysis result, determining the load abnormality proportion and the corresponding power distribution load deviation interval of the power distribution control box in the monitored area based on the power distribution deviation analysis result, and executing the corresponding control adjustment strategy;

[0014] A load distribution optimization module connected to the load state detection module, configured to reconstruct the dispatch priority of the load abnormal distribution box in the second interval, and generate a dispatch priority update table.

[0015] Further, the abnormal preliminary screening module comprises a thermal abnormality identification unit and a dispatch tolerance judgment unit.

[0016] The thermal abnormality identification unit is configured to obtain temperature data of each monitoring point in the power distribution control box, and determine whether there is a temperature abnormality in the power distribution control box according to a comparison result of the temperature data and a preset temperature threshold.

[0017] The dispatch tolerance judgment unit is configured to determine that the operation state of the power distribution control box is dispatch fluctuation or potential failure according to the planned power-off period.

[0018] The operation parameter information comprises temperature data, and the power-off and power-on dispatch information comprises a planned power-off period.

[0019] Further, the thermal abnormality identification unit comprises a thermal eccentricity detection subunit and a gas cavity pressure difference detection subunit.

[0020] The thermal eccentricity detection subunit is configured to determine a thermal barycenter offset degree of a local temperature rise region relative to a geometric center of the power distribution control box based on a spatial distribution of each temperature monitoring point.

[0021] The gas cavity pressure difference detection subunit is configured to analyze transient pressure change data in the power distribution control box to determine whether there is a pressure difference jump.

[0022] The operation parameter information further comprises the transient pressure change data.

[0023] Further, the dispatch judgment module comprises a load fluctuation detection unit and an abnormality source inference unit, wherein:

[0024] The load fluctuation detection unit is configured to analyze load current and power factor.

[0025] The abnormality source inference unit is configured to determine a temperature abnormality state according to an analysis result, including a first abnormality state and a second abnormality state.

[0026] The first abnormality state is caused by a first abnormality origin, and the second abnormality state is caused by a second abnormality origin; the temperature abnormality origin category comprises the first abnormality origin and the second abnormality origin; the first abnormality origin is a fault other than a load surge after unplanned power-off and power-on, and the second abnormality origin is the load surge after unplanned power-off and power-on.

[0027] Further, the scheduling judgment module further comprises an emergency control strategy execution unit and a running state source analysis unit;

[0028] The emergency control strategy execution unit is configured to execute a corresponding control adjustment strategy in the first abnormal state.

[0029] The running state source analysis unit is configured to determine a specific category of the second abnormal state according to the load current change rate and the power factor fluctuation value and execute a corresponding control adjustment strategy.

[0030] The running parameter information further comprises a load current and a power factor.

[0031] Further, the load state detection module comprises a power distribution deviation analysis unit and a partition regulation response unit.

[0032] The power distribution deviation analysis unit is configured to detect the power distribution load deviation of each abnormal power distribution control box and count the proportion of the number of abnormal load power distribution control boxes in the to-be-monitored area to obtain a load abnormality proportion.

[0033] The partition regulation response unit determines a corresponding power distribution load deviation interval based on the load abnormality proportion and executes a corresponding control adjustment strategy for different intervals.

[0034] Further, the partition regulation response unit comprises a first response subunit and a second response subunit.

[0035] The first response subunit is configured to trigger temperature parameter detection of the abnormal power distribution control box when the first power distribution load deviation interval result is obtained and return the detection result to the operation and maintenance end.

[0036] The second response subunit is configured to trigger detection of the loop switch state of the abnormal power distribution control box when the third power distribution load deviation interval result is obtained and return the detection result to the operation and maintenance end.

[0037] Further, the load distribution optimization module comprises a priority adjustment unit and a dynamic convergence monitoring unit.

[0038] The priority adjustment unit is configured to dynamically construct a priority score model based on the initial priority and load attribute of each power distribution box and generate an updated scheduling priority table to reconstruct the priority of the load abnormal power distribution box in the second power distribution load deviation interval.

[0039] The dynamic convergence monitoring unit is configured to continuously monitor whether the load abnormality proportion belongs to a power distribution load deviation interval that changes during the scheduling adjustment process and terminate the priority adjustment operation when it changes to the first power distribution load deviation interval.

[0040] Further, the priority adjustment unit comprises a priority reconstruction subunit;

[0041] The priority reconstruction subunit is used to update the priority score model based on the initial scheduling priority weight value and the key coefficient associated with the load attribute, and generate a corresponding scheduling priority update table.

[0042] Further, the priority adjustment unit further comprises a weight adjustment subunit;

[0043] The weight adjustment subunit is used to adjust the priority of each power distribution box in the second interval according to the scheduling priority update table.

[0044] Compared with the prior art, the beneficial effects of the present application are that by introducing a multi-source operating parameter acquisition module, the system can real-time perceive the key indicators such as the internal temperature, current and pressure difference of the power distribution box; combined with the thermal anomaly recognition and scheduling tolerance judgment mechanism, the transient anomaly caused by unplanned scheduling and the actual fault behavior are effectively distinguished, and the accuracy of anomaly recognition is improved; the system establishes a partition response mechanism through anomaly state classification and load deviation measurement, and matches the corresponding control strategy according to different load deviation intervals, realizes the reasonable allocation of operation and maintenance resources; at the same time, a dynamic priority score model based on the key coefficient of load attribute is adopted to reconstruct the scheduling priority of the load abnormal power distribution box, and the adjustment process is automatically terminated under dynamic convergence monitoring, so as to avoid the system disturbance caused by excessive intervention; the overall system has the adaptive identification and scheduling optimization capability of data driving, can significantly improve the stability, safety and operation and maintenance efficiency of the power distribution system in the complex load fluctuation environment, and is suitable for risk early warning and control optimization application in large-scale intelligent power distribution scene.

[0045] Further, by setting the abnormal preliminary screening module, the rapid thermal anomaly recognition can be performed based on the temperature data inside the power distribution control box and the preset threshold, and combined with the scheduling tolerance judgment during the planned power outage period, the normal scheduling fluctuation and the potential fault situation are effectively distinguished, the accuracy and response efficiency of the system in the initial anomaly detection stage are improved, and a reliable pre-provided basis is provided for subsequent scheduling judgment and control strategy execution.

[0046] Further, by setting the thermal eccentricity detection subunit and the air cavity pressure difference detection subunit, the local temperature rise deviation characteristics inside the power distribution control box can be recognized from the spatial distribution angle, and whether there is abnormal air flow fluctuation inside the box body is judged combined with the transient pressure change analysis, so as to improve the spatial sensitivity and response accuracy of thermal anomaly recognition, and enhance the discrimination ability of the system to hidden thermal faults and sudden abnormal states. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 It is a connection schematic diagram of the safety control system for the power distribution control box of the embodiment of the present application.

[0048] Figure 2 The connection diagram of the heat anomaly recognition unit of the embodiment of the present application is shown in the figure;

[0049] Figure 3 The connection diagram of the scheduling judgment module of the embodiment of the present application is shown in the figure;

[0050] Figure 4 The connection diagram of the load state detection module of the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0051] In order to make the objects and advantages of the present application clearer, the present application will be further described in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0052] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and are not used to limit the protection scope of the present application.

[0053] It should be noted that, in the description of the present application, the terms of direction or position relationship such as "upper", "lower", "left", "right", "inner", "outer" and the like are based on the direction or position relationship shown in the drawings, which is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application.

[0054] In addition, it should also be noted that, in the description of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connecting" should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be the communication inside two elements. Those skilled in the art can understand the specific meaning of the above terms in the present application according to the specific circumstances.

[0055] Please refer to Figure 1 The connection diagram of the safety control system for the power distribution control box of the embodiment of the present application is shown in the figure, the present application provides a safety control system for a power distribution control box, which comprises:

[0056] The data acquisition module comprises a sensing device arranged inside each power distribution control box in the to-be-monitored area, and is used to acquire the operating parameter information inside any power distribution control box;

[0057] an abnormality preliminary screening module connected with the data acquisition module, configured to determine whether there is a temperature abnormality inside the power distribution control box based on the operation parameter information, and when there is, to perform time tolerance matching in combination with planned power-off scheduling information to determine whether the current abnormal period is in a planned power-off period;

[0058] a scheduling judgment module connected with the abnormality preliminary screening module, configured to determine a temperature abnormality state when the current abnormal period is in the planned power-off period, determine a specific category of temperature abnormality of the second abnormality state, and execute a corresponding control adjustment strategy;

[0059] a load state detection module connected with the data acquisition module and the abnormality preliminary screening module respectively, configured to determine that the power distribution control box is an abnormal power distribution control box when the current abnormal period is not in the planned power-off period, detect a current load state of the abnormal power distribution control box, obtain a power distribution deviation analysis result, determine a load abnormality proportion of the power distribution control box in a to-be-monitored area and a corresponding power distribution load deviation interval based on the power distribution deviation analysis result, and execute a corresponding control adjustment strategy;

[0060] a load distribution optimization module connected with the load state detection module, configured to reconstruct a scheduling priority of the load abnormality power distribution box in the second interval and generate a scheduling priority update table.

[0061] By introducing the multi-source operation parameter acquisition module, the system can sense key indicators such as the internal temperature, current, and pressure difference of the power distribution box in real time; in combination with the thermal abnormality recognition and scheduling tolerance judgment mechanism, the system can effectively distinguish between transient abnormalities and actual fault behaviors caused by unplanned scheduling, and improve the accuracy of abnormality recognition; the system establishes a partitioned response mechanism through abnormality state classification and load deviation measurement, and matches corresponding control strategies according to different load deviation intervals to realize the rational allocation of operation and maintenance resources; at the same time, the system uses a dynamic priority scoring model based on key coefficients of load attributes to reconstruct the scheduling priority of the load abnormality power distribution box, and automatically terminates the adjustment process under dynamic convergence monitoring, thereby avoiding system disturbance caused by excessive intervention; the overall system has data-driven adaptive recognition and scheduling optimization capabilities, can significantly improve the stability, safety, and operation and maintenance efficiency of the power distribution system in a complex load fluctuation environment, and is suitable for risk early warning and control optimization applications in large-scale intelligent power distribution scenarios.

[0062] Specifically, the abnormality preliminary screening module includes a scheduling judgment module and a scheduling tolerance judgment unit;

[0063] The thermal abnormality recognition unit is configured to obtain temperature data of each monitoring point inside any power distribution control box, and determine whether there is a temperature abnormality inside the power distribution control box according to a comparison result of the temperature data and a preset temperature threshold;

[0064] The scheduling tolerance judging unit is configured to determine the operation state of the power distribution control box as scheduling fluctuation or potential fault according to the planned power-off period.

[0065] The operation parameter information includes temperature data, and the power-off and power-on scheduling information includes a planned power-off period.

[0066] In the embodiment, five temperature sensors are arranged in each power distribution control box, which are arranged at the top, bottom, left side, right side and central rear area of the box body, respectively. A central coordinate is arranged as a geometric reference point and connected to the data interface of the abnormal preliminary screening module.

[0067] The operation state of each power distribution control box in the monitoring area is monitored. In the operation process of any power distribution control box, the thermal abnormality recognition unit collects the temperature data of each monitoring point in real time, and compares the collected temperature value with the preset temperature threshold.

[0068] If the temperature data is greater than the preset temperature threshold, there is a temperature abnormality in the power distribution control box, triggering the subsequent discrimination process.

[0069] If the temperature data is less than or equal to the preset temperature threshold, there is no temperature abnormality in the power distribution control box.

[0070] The scheduling tolerance judging unit calls the planned power-off and power-on scheduling information in the scheduling database to perform time interval matching analysis on the current abnormal period and the planned power-off period.

[0071] When the system detects that the temperature data in a certain power distribution control box exceeds the preset temperature threshold, the abnormal time stamp of the abnormality is recorded.

[0072] The planned power-off and power-on time period related to the power distribution control box is extracted from the scheduling database. Usually, these time periods are stored in the form of multiple time intervals, indicating that the scheduling system allows the power distribution box to be powered off or powered on within the corresponding time.

[0073] The abnormal time stamp is matched with all the planned power-off time periods one by one.

[0074] The specific matching method is to determine whether the abnormal time falls between the start and end times of any planned time period.

[0075] If the abnormal time is within a certain planned power-off period, it is determined that the operation state of the power distribution control box is temperature fluctuation, and the temperature abnormality can be directly checked and determined by the operation and maintenance of the planned power-off period.

[0076] On the contrary, if the abnormal time does not fall into any planned scheduling time period, it is determined that there is a potential fault, which needs to be further analyzed.

[0077] By setting the abnormal preliminary screening module, rapid thermal abnormality recognition can be performed based on the temperature data inside the power distribution control box and the preset threshold, and scheduling tolerance judgment is performed in combination with the planned power-off period, so that normal scheduling fluctuations and potential fault conditions can be effectively distinguished, the accuracy and response efficiency of the system in the initial abnormal detection stage are improved, and a reliable preposition basis is provided for subsequent scheduling judgment and control strategy execution.

[0078] Referring to Figure 2 As shown in the figure, it is a connection diagram of the thermal anomaly recognition unit of the embodiment of the application.

[0079] Specifically, the thermal anomaly recognition unit includes a thermal eccentricity detection subunit and a gas cavity pressure difference detection subunit.

[0080] The thermal eccentricity detection subunit is used to judge the thermal barycenter offset degree of the local temperature rise area relative to the geometric center of the power distribution control box based on each sensing device inside the power distribution control box.

[0081] The gas cavity pressure difference detection subunit is used to analyze the transient pressure change data inside the power distribution control box to determine whether there is a pressure difference jump.

[0082] The operation parameter information further includes the transient pressure change data.

[0083] In this embodiment, the thermal eccentricity detection subunit collects data of multiple monitoring points inside the power distribution control box at a period of 5 seconds, and one-to-one correspondence between the temperature data of each monitoring point and its preset spatial coordinates is established to construct a three-dimensional thermal field distribution model of the power distribution control box; the system calculates the data collected by each sensing device in the thermal field model by using the weighted average method to obtain the spatial position of the thermal barycenter, and the expression is as follows:

[0084]

[0085] Wherein, T i is the temperature value of the i th monitoring point;

[0086] x i ,y i ,z i is its spatial coordinates;

[0087] X c ,Y c ,Z c is the spatial coordinates of its thermal barycenter;

[0088] The thermal barycenter position of the thermal field is calculated by using the weighted average method, and is compared with the geometric center point of the power distribution control box to obtain the actual offset distance, so as to determine whether the deviation degree of the thermal barycenter position and the geometric center point is greater than the deviation threshold;

[0089] The set deviation threshold is 25% of the diagonal length of the power distribution control box;

[0090] If the deviation of the thermal barycenter position from the geometric center point is greater than the deviation threshold, the thermal barycenter is abnormally deviated, and it is prompted that there is a possible local heat aggregation area in the box body;

[0091] If the deviation of the thermal barycenter position from the geometric center point is less than or equal to the deviation threshold, the heat distribution is normal;

[0092] When the thermal barycenter is abnormally deviated, the air cavity pressure difference detection subunit monitors the transient pressure change of the air cavity in the box body in real time;

[0093] The system takes 5 seconds as a time window to sample the pressure, and detects whether the transient pressure change data in the power distribution control box is greater than the pressure change threshold;

[0094] If the transient pressure change data is greater than the pressure change threshold, it is determined that there is a temperature anomaly, and the abnormal deviation of the thermal barycenter at this time is a real thermal barycenter abnormal deviation, and there is no device false detection;

[0095] If the transient pressure change data is less than or equal to the pressure change threshold, it is a non-real thermal anomaly, and there is device false detection;

[0096] The pressure change threshold is set to 200Pa / s based on the statistical results of historical thermal failure cases and simulation verification data.

[0097] By setting the thermal eccentricity detection subunit and the air cavity pressure difference detection subunit, the local temperature rise deviation characteristics in the power distribution control box can be recognized from the spatial distribution, and whether there is abnormal air flow fluctuation in the box body is analyzed and judged in combination with the transient pressure change, so that the spatial sensitivity and response accuracy of the thermal anomaly recognition are improved, and the discrimination ability of the system to the hidden thermal failure and the sudden abnormal state is enhanced.

[0098] Referring to Figure 3 Fig. 2 is a connection diagram of a scheduling judgment module according to an embodiment of the present application;

[0099] Specifically, the scheduling judgment module includes a load fluctuation detection unit and an abnormal source inference unit.

[0100] The load fluctuation detection unit is used to analyze the load current and power factor.

[0101] The abnormal source inference unit is used to judge the temperature abnormal state according to the analysis result, including a first abnormal state and a second abnormal state.

[0102] The first abnormal state is caused by a first abnormal origin, and the second abnormal state is caused by a second abnormal origin; the temperature abnormal origin category includes the first abnormal origin and the second abnormal origin; the first abnormal origin is a fault other than a load surge after unplanned power-off and power-on, and the second abnormal origin is a load surge after unplanned power-off or power-on.

[0103] In this embodiment, the thermal gravity abnormal deviation is a real thermal gravity abnormal deviation, and the load current and power factor are obtained when the current abnormal period is in the planned power-off period.

[0104] The system collects the real-time current value of the main line load of the power distribution circuit through the current transformer, and calculates the power factor through the phase angle between voltage and current.

[0105] The sampling period is 1 second, and the analysis period is 5 seconds, which ensures the continuity and response speed of data acquisition.

[0106] The collected current unit is ampere (A), and the power factor is a dimensionless real number, ranging from 0 to 1.

[0107] When the system determines that the thermal gravity deviation is a real abnormality and the current abnormal period is in the planned power-off period, it immediately captures the current and power factor data within 5 seconds in the last analysis period of 5 seconds, and takes the maximum and average values in the period as the basis for determination.

[0108] The closed interval of the load current when normal is [100, 150], and the unit is A.

[0109] The closed interval of the power factor when normal is [0.1, 0.25].

[0110] If the load current is less than 100 A and the power factor is less than 0.1, it is the first abnormal state. In this case, due to no-load operation, electrical connection failure or equipment aging, a fault other than a load surge after unplanned power-off and power-on is caused.

[0111] In the first abnormal state, the system starts the emergency control strategy execution unit and issues a warning.

[0112] If the load current is greater than 150 A and the power factor is greater than 0.25, the system determines that it is the second abnormal state, which indicates that there is a high load running phenomenon at present. At this time, a fault is caused by a load surge after unplanned power-off or power-on.

[0113] In the second abnormal state, the specific category of the second abnormal origin is analyzed based on the load current change rate, including a load surge after unplanned power-off or power-on.

[0114] By setting the scheduling judgment module and combining the pre-judgment of thermal gravity center offset and transient pressure abnormality, the associated analysis of the load current and the power factor can be realized, so that a first abnormality origin caused by a fault and a second abnormality origin caused by a sudden load change can be accurately distinguished.

[0115] Specifically, the scheduling judgment module further includes an emergency control strategy execution unit and a running state source analysis unit.

[0116] The emergency control strategy execution unit is configured to execute a corresponding control adjustment strategy in the first abnormality state.

[0117] The running state source analysis unit is configured to determine a specific category of the second abnormality origin according to the load current change rate and the power factor fluctuation value and execute a corresponding control adjustment strategy in the second abnormality state.

[0118] The running parameter information further includes the load current and the power factor.

[0119] In this embodiment, if the system determines the second abnormality state, the load current sequence {I1, I2, I3, I4, I5} of each second in the analysis cycle of 5 seconds is obtained, the load current change rate is calculated The unit is A / s.

[0120] The current change rate threshold is 2.5 A / s in this embodiment.

[0121] The load current change rate is compared with the set current change rate threshold.

[0122] If the load current change rate is greater than the current change rate threshold, it is judged that the abnormality is caused by the sudden surge of the load after power transmission.

[0123] If the load current change rate is less than or equal to the current change rate threshold, it is judged that the abnormality is caused by unplanned power-off.

[0124] By setting the running state source analysis unit, the system can further identify the abnormality cause in the second abnormality state, accurately distinguish the two types of abnormality caused by the sudden surge after power transmission and unplanned power-off based on the load current change rate, improve the abnormality classification accuracy and the pertinence of the response strategy, and enhance the system safety and scheduling efficiency.

[0125] Referring to Figure 4 Fig. 1 is a connection schematic diagram of the load state detection module according to the embodiment of the present application.

[0126] Specifically, the load state detection module includes a power distribution deviation analysis unit and a partition regulation and control response unit.

[0127] The power distribution deviation analysis unit is configured to detect the power distribution load deviation of each abnormal power distribution control box, and to count the proportion of the number of power distribution control boxes with load abnormalities in the monitored area, to obtain the load abnormality proportion.

[0128] The partition regulation response unit determines the corresponding power distribution load deviation interval based on the load abnormality proportion, and executes corresponding control adjustment strategies for different intervals.

[0129] In this embodiment, the system presets the normal power distribution load interval of each power distribution control box as the mean value of the long-term operation statistical value with a floating range above and below the mean value;

[0130] The normal interval is set as [85% μ, 115% μ], where μ is the daily average load value of the power distribution control box under historical stable operation conditions;

[0131] When the real-time load value of the power distribution control box is less than the minimum value of the normal power distribution load interval or greater than the maximum value of the normal power distribution load interval, the power distribution control box has a power distribution load deviation;

[0132] The power distribution load deviation ΔP is defined as:

[0133]

[0134] Where P t is the real-time load value of the power distribution control box, and the standard power distribution load deviation threshold is 15%;

[0135] If the power distribution load deviation is greater than the standard power distribution load deviation threshold, the power distribution control box has a load abnormality.

[0136] By setting the normal power distribution load interval based on the historical mean value and using the load deviation as the judgment basis, the running state of each power distribution control box is accurately monitored; combined with the standard threshold determination mechanism, the accuracy of abnormal identification is improved; and then based on the abnormality proportion, the deviation interval is divided, the hierarchical regulation response is realized, and the sensitivity of the power distribution system abnormality detection and the pertinence of the control strategy are effectively improved.

[0137] Specifically, the partition regulation response unit includes a first response sub-unit and a second response sub-unit;

[0138] The first response sub-unit is configured to trigger temperature parameter detection of the abnormal power distribution control box when the first power distribution load deviation interval result is obtained, and to return the detection result to the operation and maintenance end;

[0139] The second response sub-unit is configured to trigger detection of the loop switch state of the abnormal power distribution control box when the third power distribution load deviation interval result is obtained, and to return the detection result to the operation and maintenance end.

[0140] In this embodiment, the partition control response unit is divided into three deviation intervals according to the load abnormality proportion: the first power distribution load deviation interval is that the load abnormality proportion is less than 10%, the second power distribution load deviation interval is that the load abnormality proportion is in the closed interval of 10% to 30%, and the third power distribution load deviation interval is that the load abnormality proportion is more than 30%.

[0141] By setting the partition control response unit and dividing three deviation intervals according to the load abnormality proportion, a targeted differentiated response mechanism is constructed; in the first power distribution load deviation interval, temperature parameter detection is triggered to improve the pre-perception ability of potential overheating risk in the mild abnormal state; in the third power distribution load deviation interval, loop switch state detection is triggered to realize rapid judgment of electrical safety state in the severe abnormal condition; the perception depth and response accuracy of the system to different load deviation degrees are enhanced, effectively supporting the hierarchical control strategy, and improving the system operation safety and intelligent level.

[0142] Specifically, the load distribution optimization module includes a priority adjustment unit and a dynamic convergence monitoring unit.

[0143] The priority adjustment unit is configured to dynamically construct a priority score model based on the initial priority of each power distribution box and the load attribute, and generate an updated scheduling priority table to reconstruct the priority of the load abnormality power distribution box in the second power distribution load deviation interval.

[0144] The dynamic convergence monitoring unit is configured to continuously monitor whether the power distribution load deviation interval to which the load abnormality proportion belongs changes during the scheduling adjustment process, and terminate the priority adjustment operation when it changes to the first power distribution load deviation interval.

[0145] In this embodiment, when the system determines that the current load abnormality proportion is located in the second power distribution load deviation interval, the priority adjustment mechanism is started.

[0146] The capacity weight of each power distribution control box in the monitored area is adjusted so that the load abnormality proportion falls within the first power distribution load deviation interval.

[0147] In this embodiment, the priority adjustment mechanism is:

[0148] The real-time power parameters and the planned scheduling time factors of the load are considered comprehensively during the load priority adjustment process to calculate the priority factor P.

[0149] The calculation formula of the priority factor P is:

[0150] P = a x (real-time power consumption / rated capacity) + b x (remaining available time / planned period).

[0151] Wherein, a is the capacity weight, and the value is 0.7; b is the time weight, and the value is 0.3.

[0152] Decrease 0.05 every 5 seconds, minimum 0.4;

[0153] Increase 0.05 every 5 seconds, maximum 0.6;

[0154] Adjust the range to a ∈ [0.4, 0.7], β ∈ [0.3, 0.6], to ensure that the priority factor P maintains a controllable balance between capacity and scheduling efficiency;

[0155] The remaining available time is the difference between the planned power outage time window and the current system time, reflecting the sensitivity of the current load to the scheduling time;

[0156] Get the initial priority weight of each power distribution control box preset in the system, which can be based on the importance of operation (such as 1-5 levels), and refer to the power grid scheduling priority configuration rules, i.e. State Grid "Smart Distribution Network Control Technology Specification";

[0157] The system assigns a key coefficient K to the load type based on the load information library;

[0158] Among them, lighting load: K = 1.0;

[0159] Security monitoring load: K = 1.5;

[0160] Medical, industrial control, data hub load: K = 2.0;

[0161] The priority score model is constructed as follows:

[0162]

[0163] Among them, W is the initial priority weight;

[0164] K is the key coefficient;

[0165] P is the priority factor;

[0166] S is the new priority score, rounded up to ensure integer scheduling level;

[0167] The ceiling operator is used;

[0168] The system sorts all abnormal power distribution control boxes according to the S value in descending order, generates a new scheduling priority update table, and uses it to control the strategy distribution module, so that the scheduling strategy is executed first to adjust the key load line, ensuring the stability of the core system power supply;

[0169] The dynamic convergence monitoring unit continuously participates in the entire load adjustment cycle to determine whether the current scheduling has reached a stable state;

[0170] wherein the load abnormality proportion is recalculated every 5 seconds, and the calculation formula is:

[0171]

[0172] After each update, the system determines which power distribution load deviation interval the current belongs to according to the R value. When the system determines that it is in the first power distribution load deviation interval for two consecutive monitoring periods, it is considered that the scheduling optimization has converged, and the adjustment of α and β is stopped. The system automatically terminates the priority adjustment operation, closes the priority adjustment subunit, records the optimization log of this round, and switches to the normal state.

[0173] By starting the priority adjustment mechanism in the second power distribution load deviation interval and dynamically adjusting the capacity weight α and the time weight β, the priority factor of the load is accurately controlled. By adjusting the α and β parameters every 5 seconds, the system realizes dynamic balance between capacity pressure and scheduling timeliness, and then guides the load abnormality control strategy to be reasonable. The priority scoring model constructed by the key coefficient K and the initial priority weight improves the scheduling response priority of the key load. Through the dynamic convergence monitoring mechanism, the change trend of the load abnormality proportion is determined to ensure that the scheduling optimization process is convergent and stable, and the load abnormality proportion is quickly reduced to below 10%, effectively ensuring the continuity of core business power supply and the stability of system operation.

[0174] Specifically, the priority adjustment unit includes a priority reconstruction subunit and a weight adjustment subunit.

[0175] The priority reconstruction subunit is configured to update the priority scoring model based on the initial scheduling priority weight value and the key coefficient associated with the load attribute, and generate a corresponding scheduling priority update table.

[0176] The weight adjustment subunit is configured to adjust the scheduling priority of each power distribution box in the second interval according to the scheduling priority update table.

[0177] Specifically, the priority reconstruction subunit updates the priority scoring model and generates a corresponding scheduling priority update table, which includes:

[0178] Obtain the initial priority of each power distribution control box.

[0179] Identify the attribute type of the load carried by the current power distribution control box and assign it a corresponding key coefficient.

[0180] Multiply the initial scheduling priority weight value and the key coefficient, and take the product result as an integer to obtain a new priority weight score.

[0181] Resort to generate the scheduling priority update table based on the new priority weight score.

[0182] In this embodiment, the system first calls the power distribution control box basic information, extracts the initial scheduling priority value corresponding to each power distribution control box currently in abnormal load state as the basic input parameter of the subsequent scoring model;

[0183] The types of downstream loads carried by each power distribution control box, such as lighting, security, industry, medical treatment, etc., are analyzed, and a key coefficient is assigned to each type according to the preset load classification rule, which is used to reflect the key degree of the load to the system operation;

[0184] The initial priority value of each control box is multiplied by its load key coefficient to obtain the calculation expression of the priority scoring model;

[0185] In order to ensure that the scoring result adapts to the integer grading mechanism of the scheduling system, the product result is rounded up to obtain the priority score value actually used in the new round of scheduling;

[0186] The system sorts all abnormal power distribution control boxes according to the new score value from high to low to form a new scheduling priority update table.

[0187] By constructing a priority scoring model containing the key factors of load properties, the dynamic reconstruction of the scheduling priority of abnormal load power distribution control boxes is realized, which effectively guarantees the continuous power supply demand of core loads; at the same time, the response accuracy of the scheduling strategy and the resource allocation efficiency are improved, the intelligent control ability of the system in the load deviation interval is improved, and the safe and stable operation level of the power distribution network is enhanced.

[0188] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to related technical features without deviating from the principles of the present application, and the technical solutions after these changes or replacements will fall within the protection scope of the present application.

[0189] The above description is only the preferred embodiments of the present application and is not intended to limit the present application; for those skilled in the art, the present application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A safety control system for a power distribution control box, characterized in that, include: The data acquisition module includes sensing devices installed inside each power distribution control box in the area to be monitored, used to collect operating parameter information inside any power distribution control box; An anomaly screening module, which is connected to the data acquisition module, is used to determine whether there is a temperature anomaly inside the power distribution control box based on the operating parameter information, and when there is, to perform time tolerance matching in combination with the planned power outage and power supply scheduling information to determine whether the current abnormal period is within the planned power outage period. The scheduling judgment module, which is connected to the anomaly screening module, is used to judge the temperature anomaly state when the current anomaly period is within the planned power outage period, determine the specific category of the origin of the second type of temperature anomaly under the second anomaly state, and execute the corresponding control adjustment strategy. The load status detection module is connected to the data acquisition module and the anomaly screening module respectively. It is used to determine that the power distribution control box is an abnormal power distribution control box when the current abnormal period is not within the planned power outage period. It detects the current load status of the abnormal power distribution control box, obtains the power distribution deviation analysis result, and determines the load abnormality ratio of the power distribution control box in the monitoring area and the corresponding power distribution load deviation range based on the power distribution deviation analysis result, so as to execute the corresponding control adjustment strategy. The load allocation optimization module, which is connected to the load status detection module, is used to reconstruct the scheduling priority of the abnormal load distribution boxes in the second interval and generate a scheduling priority update table.

2. The safety control system for a power distribution control box according to claim 1, characterized in that, The anomaly screening module includes a thermal anomaly identification unit and a scheduling tolerance judgment unit; The thermal anomaly identification unit is used to obtain temperature data of each monitoring point inside any power distribution control box, and to determine whether there is a temperature anomaly inside the power distribution control box based on the comparison result of the temperature data and the preset temperature threshold. The scheduling tolerance judgment unit is used to determine whether the operating status of the power distribution control box is a scheduling fluctuation or a potential fault based on the planned power outage period. The operating parameter information includes temperature data, and the power outage and power supply scheduling information includes planned power outage periods.

3. The safety control system for a power distribution control box according to claim 2, characterized in that, The thermal anomaly identification unit includes a thermal eccentricity detection subunit and an air cavity pressure difference detection subunit; The thermal eccentricity detection subunit is used to determine the degree of thermal centroid offset of the local temperature rise area relative to the geometric center of the power distribution control box based on the spatial distribution of each temperature monitoring point. The gas chamber differential pressure detection subunit is used to analyze the transient pressure change data in the power distribution control box to determine whether there is a pressure jump. The operating parameter information also includes the transient pressure change data.

4. The safety control system for a power distribution control box according to claim 3, characterized in that, The scheduling judgment module includes a load fluctuation detection unit and an anomaly source inference unit, wherein: The load fluctuation detection unit is used to analyze the load current and power factor; The anomaly source inference unit is used to determine the temperature anomaly state based on the analysis results, including a first anomaly state and a second anomaly state. The first abnormal state is caused by a type 1 abnormal origin, and the second abnormal state is caused by a type 2 abnormal origin. The categories of abnormal temperature origins include type 1 and type 2 abnormal origins. Type 1 abnormal origins are faults other than unplanned power outages and load surges after power restoration, while type 2 abnormal origins are unplanned power outages or load surges after power restoration.

5. The safety control system for a power distribution control box according to claim 4, characterized in that, The scheduling judgment module also includes an emergency control strategy execution unit and an operation status source analysis unit; The emergency control strategy execution unit is used to execute the corresponding control adjustment strategy under the first abnormal state. The operating status source analysis unit is used to determine the specific category of the two types of abnormal origins based on the load current change rate and power factor fluctuation value under the second abnormal state and to execute the corresponding control adjustment strategy. The operating parameter information also includes load current and power factor.

6. The safety control system for a power distribution control box according to claim 1, characterized in that, The load status detection module includes a power distribution deviation analysis unit and a zone control response unit; The power distribution deviation analysis unit is used to detect the degree of power distribution load deviation of each abnormal power distribution control box, and to count the proportion of power distribution control boxes with abnormal loads in the monitored area to obtain the load abnormality proportion. The zone control response unit determines the corresponding power distribution load deviation range based on the abnormal load ratio, and executes corresponding control adjustment strategies for different ranges.

7. The safety control system for a power distribution control box according to claim 6, characterized in that, The partition control response unit includes a first response subunit and a second response subunit; The first response subunit is used to trigger the detection of temperature parameters of the abnormal power distribution control box when the first power distribution load deviation range result is obtained, and to send the detection result back to the operation and maintenance end. The second response subunit is used to trigger the detection of the abnormal power distribution control box circuit switch status when the third power distribution load deviation range result is obtained, and to send the detection result back to the operation and maintenance end.

8. The safety control system for a power distribution control box according to claim 1, characterized in that, The load allocation optimization module includes a priority adjustment unit and a dynamic convergence monitoring unit; The priority adjustment unit is used to dynamically construct a priority scoring model based on the initial priority and load attributes of each distribution box, and generate an updated scheduling priority table to reconstruct the priority of the distribution boxes with abnormal loads within the second distribution load deviation interval. The dynamic convergence monitoring unit is used to continuously monitor whether the distribution load deviation range to which the abnormal load ratio belongs changes during the scheduling and adjustment process, and terminates the priority adjustment operation after it changes to the first distribution load deviation range.

9. The safety control system for a power distribution control box according to claim 8, characterized in that, The priority adjustment unit includes a priority reconstruction subunit; The priority reconstruction subunit is used to update the priority scoring model based on the key coefficients associated with the initial scheduling priority weight value and the load attribute, and to generate the corresponding scheduling priority update table.

10. The safety control system for a power distribution control box according to claim 9, characterized in that, The priority adjustment unit further includes a weight adjustment subunit; The weight adjustment subunit is used to adjust the priority of each distribution box in the second interval according to the scheduling priority update table.

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