Power distribution network state real-time monitoring system based on internet of things technology

Abstract

The application relates to the technical field of power distribution network monitoring and control, and discloses a power distribution network state real-time monitoring system based on Internet of Things technology, which comprises a monitoring module and a topology controller. When the dynamic margin of a standby path is insufficient, the topology controller precalculates a margin deficit and determines a standby tripping feeder. When a main path fails at this time, the topology controller executes the control timing sequence of tripping the standby tripping feeder first and then switching the execution module. The application provides an active recovery path under the working condition that the margin of the standby path is insufficient, actively trips unnecessary loads before switching, guarantees the safe switching of critical loads, realizes the hierarchical survival of the power supply and distribution system, and avoids the rigid dilemma of safety but paralysis.

Description

Technical Field

[0001] This invention relates to a real-time monitoring system for distribution network status based on Internet of Things (IoT) technology, belonging to the field of distribution network monitoring and control technology. Background Technology

[0002] Currently, in power supply or distribution circuit devices or systems, ensuring the continuity and reliability of power supply to downstream loads is the primary engineering objective. To this end, adopting an N-1 redundant topology design, including at least a first and second path, and incorporating automatic transfer switches or tie-down circuit breakers has become the standard technical configuration for ensuring system high availability. This traditional approach relies on a crucial static assumption: the capacity of the two paths is fixed, and the load distribution is relatively balanced and controllable. However, with the large-scale integration of new dynamic loads, such as electric vehicle charging stations, variable frequency HVAC systems, and data centers, the real-time load characteristics of the distribution network exhibit high nonlinearity and volatility. This fundamentally undermines the premise of the aforementioned static design. Under such dynamic operating conditions, there is a type of operational risk: when the real-time load of the primary path (i.e., the first path) is low, while the backup path (i.e., the second path) is severely insufficient in its remaining capacity (margin) due to carrying a large number of concentrated dynamic loads, the overall system may still be in a safe operating range. However, if the first path fails at this time, the automatic transfer switch will still execute its preset static switching logic, instantly superimposing all the load of the first path onto the backup path. This switching action itself will cause the backup path to be momentarily overloaded and trigger its protective trip. Ultimately, the switching behavior designed to ensure power supply will instead cause a power outage of the entire system.

[0003] To address this issue, while IoT technology has begun to be applied for load monitoring, the monitoring data in existing control logic is mostly used only for upper-level energy efficiency analysis or post-event alarms. It does not participate in the lower-level automatic switching decision-making, and cannot pre-determine the safety of the switching action before it is executed. On the other hand, simply relying on increasing the static capacity of lines or transformers to cope with dynamic impacts not only faces high modification costs but also fails to fundamentally solve the problem of insufficient dynamic safety margin caused by instantaneous load imbalance. This disconnect between monitoring and control logic is also prevalent in existing IoT applications. For example, Chinese utility model patent CN202906579U discloses… An IoT-based real-time monitoring and control system for power distribution networks aims to achieve real-time monitoring and fault location of the power distribution network's operating status by deploying various sensors and communication networks. However, its technical focus is on data acquisition, transmission, and upper-level display, while its so-called control is still mainly limited to alarm and isolation operations after a fault occurs. This solution also fails to solve the core problem of N-1 redundant topologies, namely, it does not provide a mechanism to dynamically assess the actual carrying capacity of backup paths using real-time monitoring data before fault switching. Its control logic and redundancy switching decisions are still separate. Therefore, when facing dynamic load shocks, this type of system cannot avoid the risk of systemic collapse due to blind switching.

[0004] Therefore, the technical problem to be solved by this invention is how to utilize real-time monitoring data to enable the redundancy switching logic of the distribution network to have dynamic judgment capabilities, so that it can actively determine the real-time carrying capacity of the backup path before performing topology switching, and avoid systemic power outages caused by blind switching. Summary of the Invention

[0005] This invention provides a real-time monitoring system for distribution network status based on Internet of Things (IoT) technology. Its main purpose is to solve the problem that the existing distribution network redundancy switching logic relies on static design and cannot perceive the real-time dynamic margin of backup paths, which may lead to blind switching under dynamic loads and thus cause systemic power outages.

[0006] To achieve the above objectives, this invention provides a real-time distribution network status monitoring system based on Internet of Things (IoT) technology, applicable to a redundant distribution network including at least a first path and a second path, wherein the second path has static capacity. The system includes: an execution module for switching the load to the second path when the first path fails; and multiple feeder execution modules for controlling the on / off states of multiple downstream feeders of the first path, respectively. The system further includes:

[0007] The monitoring module is used to acquire the real-time load of the first path, the real-time load of the second path, the load of multiple downstream feeders of the first path, and the fault status of the first path.

[0008] A topology controller, electrically connected to a monitoring module, an execution module, and multiple feeder execution modules, is configured to: Step a, calculate the dynamic margin of the second path based on the static capacity and real-time load of the second path; Step b, determine whether the real-time load of the first path is less than the dynamic margin of the second path; Step c, when the determination in step b is yes, output a first control signal to enable the automatic switching function of the execution module; Step d, when the determination in step b is no, calculate the dynamic margin deficit between the real-time load and the dynamic margin of the first path, and determine one or more feeders to be tripped whose total load is sufficient to cover the dynamic margin deficit according to the preset load priority of downstream feeders; Step e, and when the monitoring module detects a fault in the first path, if the determination in step b is no, the topology controller is configured to send a trip command to multiple feeder execution modules corresponding to the feeder to be tripped, and after the trip command is executed, send a switching command to the execution module.

[0009] Preferably, the topology controller is also configured to: monitor the data communication status of the module, and when the data communication interruption of the real-time load of the first path or the real-time load of the second path is detected, the topology controller is also configured to execute the logic of step b when the judgment is negative.

[0010] Preferably, the topology controller is further configured to: in step a, further calculate the standard deviation of the real-time load of the second path within a time window as a volatility quantification indicator. Based on volatility quantitative indicators and preset safety factor Generate safety penalty items; calculate dynamic margin in step a. The rules have been revised as follows: ,in This is static capacity. This represents the real-time load of the second path; the judgment in step b is based on this corrected dynamic margin. It was carried out.

[0011] Preferably, the topology controller is further configured to: in step a, further obtain the peak-to-average power ratio (PAPR) of the real-time load of the second path within a time window; generate a safety penalty item based on the PAPR and a preset safety factor; the rule for calculating the dynamic margin in step a is modified to deduct the real-time load of the second path and the safety penalty item from the static capacity; the judgment in step b is based on the dynamic margin calculated after deducting the safety penalty item.

[0012] Preferably, the system further includes: a temperature monitoring unit for acquiring the ambient temperature of the critical equipment in the second path; the topology controller is also configured to: dynamically correct the static capacity of the second path based on the ambient temperature and according to a preset capacity-temperature derating relationship to obtain the true dynamic capacity; and the dynamic margin in step a is calculated based on the true dynamic capacity and the real-time load of the second path.

[0013] Preferably, the monitoring module is also used to obtain the real-time feeder load of multiple downstream feeders under the second path, and the topology controller is further configured to: before executing step a, calculate the sum of the real-time feeder loads of multiple downstream feeders under the second path, and determine whether the difference between the real-time load of the second path and the sum is within a preset error threshold; when the difference is within the error threshold, steps a to e are executed; when the difference continues to exceed the error threshold, the automatic switching function of the module is prohibited.

[0014] Preferably, the topology controller is configured such that the automatic switching function of the execution module is disabled by default when the topology controller itself fails or loses power.

[0015] Preferably, when the determination in step b is negative, the topology controller is also configured to send an early warning signal to the upper management system while calculating the dynamic margin deficit. The early warning signal is used to indicate that the dynamic margin of the second path is insufficient.

[0016] Preferably, the topology controller is a programmable logic controller.

[0017] Preferably, the execution module is an automatic transfer switch.

[0018] Compared with the prior art, the beneficial effects of the present invention are:

[0019] 1. By real-time monitoring of the load to be transferred in the first path and the remaining carrying capacity of the second path, a pre-emptive topology switching safety judgment mechanism is established. This mechanism transforms the conventional automatic switching function of the automatic transfer switch in the power distribution system from a fixed and unconditional topology change action into a closed-loop control behavior that dynamically enables or disables based on the real-time margin of the second path. This makes the redundant switching action itself no longer a potential overload threat to the backup path and avoids the risk of systemic power outage caused by blind switching under dynamic load disturbances.

[0020] 2. When the load on the first path is higher than the dynamic margin of the second path, a recovery path that transcends the prohibition of switching is provided for the system. When a power supply failure is confirmed in the first path, the controller no longer executes the switching prohibition, but instead calculates the margin deficit required for switching. Based on the preset load priority, it actively disconnects some unnecessary feeders on the first path to free up capacity, and then safely switches the remaining critical loads to the second path. Under extreme conditions, the power supply continuity of high-priority loads is ensured, and the operation mode of the power supply and distribution system is changed from a rigid all-or-nothing to a flexible hierarchical survival mode.

[0021] 3. The load volatility of the second path is incorporated into the safety margin calculation model. By analyzing the statistical characteristics of the second path load within a time window, its potential instantaneous impact amplitude is quantified, and a dynamic safety buffer value is generated based on this. This buffer value is actively deducted when calculating the dynamic margin. This mechanism changes the topology controller's judgment of the safety margin from being based on the instantaneous value of the average load to a conservative assessment based on the load volatility characteristics. This effectively filters out false safety margins caused by nonlinear load impacts and prevents misjudgments during switching in impact load scenarios. Attached Figure Description

[0022] Figure 1 This is a timing flowchart of the dynamic margin judgment and hierarchical survival control of the topology controller of the present invention;

[0023] Figure 2 This is a schematic diagram illustrating the relationship between the load standard deviation and the safety penalty term in this invention;

[0024] Figure 3 This is a diagram showing the overall system architecture and pre-security discrimination data flow of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific embodiments. However, it should be understood that the specific embodiments described below are only preferred examples of the present invention and are not intended to limit the scope of protection of the present invention.

[0026] This invention discloses a real-time distribution network status monitoring system based on Internet of Things (IoT) technology. Its application scenario is an N-1 redundant distribution network with a primary path (first path) and a backup path (second path). Physically, the system mainly consists of three types of entities: monitoring modules deployed on each critical path and feeder; a topology controller as the control core; and two types of execution modules: execution modules for topology switching between primary and backup paths, and multiple feeder execution modules for controlling downstream branch feeders. The basic information flow is as follows: the monitoring module sends the collected real-time electrical parameters of the distribution network to the topology controller; the topology controller makes judgments based on its internal control logic and ultimately outputs control commands to the execution modules and feeder execution modules to achieve distribution network status monitoring. Adaptive closed-loop control of the network topology; in a specific distribution network deployment, the monitoring module is the foundation for system perception, solving the problem of blindness to real-time load dynamic margin in traditional systems; to achieve this function, the monitoring module preferably consists of a series of smart meters or smart circuit breakers with metering functions deployed at the main switches of the first path and the second path, as well as at each downstream feeder switch. These smart components have standardized industrial communication interfaces, such as Modbus RTU or converted to MQTT protocol through an IoT gateway. They continuously collect and report their respective electrical parameters to the topology controller at a high frequency and a preset period, which can be set to no more than 5 seconds. These parameters include at least: the real-time load of the first path. Real-time load of the second path The monitoring module also monitors the loads of the multiple feeders downstream of the first path. In addition, the monitoring module monitors the voltage status of the first path to obtain its fault status. This monitoring can be achieved through an undervoltage release or a voltmeter, thereby providing the topology controller with all the real-time data inputs necessary to execute all subsequent safety logic.

[0027] The topology controller, as the core unit of the system, acts as a safety decision-making unit for the N-1 redundant topology. It receives data from the monitoring module and decides on the switching permission of the execution module, thus addressing the redundancy paradox. In a typical operating cycle, this topology controller, which can be implemented by a high-reliability programmable logic controller (PLC) or industrial edge controller, internally incorporates the core logic of dynamic margin safety interlocking. In step a, the controller retrieves a pre-set static capacity value representing the engineering design carrying capacity of the second path from its internal memory. In conjunction with the real-time load of the second path reported by the monitoring module By subtraction The dynamic margin of the second path at the current moment is calculated in real time. Next, in step b, the controller performs the core safety pre-decision, which involves periodically determining the real-time load of the first path once per second. Is it less than the dynamic margin? This safety condition applies if and only if, in step c, this safety condition, namely Only when deemed safe does the topology controller determine that the potential N-1 switch is safe, and accordingly output a first control signal. This signal can be a 24V DC closed signal, used to enable or activate the execution module. Taking the Automatic Transfer Switch (ATS) as an example, this puts its automatic switching function in a safe standby state. This helps to ensure that redundant switching actions are only allowed when confirmed to be safe. However, this invention further solves the secondary technical problem of safety but paralysis caused by only enable or disable logic, namely, when... If switching is only disabled, and a failure actually occurs on the first path, all the load carried by the first path, including high-priority loads, will be lost. Therefore, this invention provides a control path with active lossy recovery. Specifically, in step d, if the judgment in step b is negative, i.e. At this point, the topology controller no longer simply executes the prohibition action, but immediately switches to the contingency plan generation phase: calculating the dynamic margin deficit. Simultaneously, the controller retrieves a pre-configured protection priority list associated with the downstream feeder of the first path. This list categorizes the load into P1 (highest priority, non-disconnectable), P2 (second highest priority), and P3 (disconnectable), among other levels. The controller then starts from the lowest priority P3 and accumulates the real-time load of the downstream feeder of the first path in reverse priority order until the accumulated load to be tripped is reached. First time greater than or equal to dynamic margin deficit The controller marks the selected P3 feeders, as well as the possible P2 feeders, as feeders to be tripped. Finally, in step e, when the system is in the state of waiting to execute this plan, that is, when step b is judged as no, and the monitoring module does detect a fault in the first path at this moment, taking undervoltage as an example, the topology controller will execute a control sequence: immediately send a forced trip command to the multiple feeder execution modules, such as smart circuit breakers, corresponding to each feeder in the list of feeders to be tripped; after confirming the execution of the trip command or after a certain logical delay, which can be set to 500 milliseconds, the topology controller will then send a switching command to the main execution module, i.e., ATS. This 13 / 00 control sequence arrangement of tripping first and then switching helps the system to actively sacrifice low-priority loads to ensure the hierarchical survival of high-priority loads in extreme conditions where the backup path margin is insufficient, thus realizing the transformation from passive safety paralysis to active lossy recovery.

[0028] In the engineering configuration environment of a topology controller, such as a programmable logic controller (PLC), a human-machine interface is provided for configuring the protection levels of multiple feeder execution modules downstream of the first path. This configuration process explicitly binds the unique communication address or I / O point of each feeder execution module to a preset protection level identifier, such as P1 (non-disconnectable), P2 (minor), and P3 (disconnectable). This binding relationship is embedded in the topology controller's non-volatile data table. When the topology controller calculates the dynamic margin deficit in step d, it uses this data table... The communication addresses of all feeder execution modules identified as P3 level are retrieved, and their loads are accumulated in reverse order of priority until the deficit coverage requirement is met, thereby generating a list of feeders to be tripped. To further improve the decision reliability of the system when dealing with highly volatile or random impact loads such as electric vehicle charging piles and variable frequency HVAC systems, the topology controller of this invention can also integrate control logic for load volatility quantization and margin adaptive correction to solve the problem of false safety margin caused by the average load value masking instantaneous peak values. In this preferred embodiment, when the topology controller executes step a, it no longer only obtains... Instead of obtaining the instantaneous value, it obtains the value at a higher frequency within a short time window, for example, sampling 10 times within 1 second. A short-time series; the controller then performs statistical calculations on the series to obtain a volatility quantification index; this index is the standard deviation of the load. The controller then based on this and a preset dimensionless safety factor This coefficient can be preset to 3 to generate a security penalty item. The rule for calculating the dynamic margin in step a has been revised to: ,in This represents a more conservative safety dynamic margin that has been penalized for volatility; correspondingly, the safety decision in subsequent step b, and the calculation of the dynamic margin deficit in step d, both use this more conservative margin. This mechanism quantifies uncertain fluctuations into deterministic margin deductions, effectively preventing misjudgments during switching in scenarios with impactful loads. In another implementation, the volatility quantification index can also be the real-time load of the second path within a time window. The security penalty item is accordingly modified to a value calculated based on the peak-to-average power ratio, and is also used to deduct the real-time load and security penalty item of the second path from the static capacity to achieve the same security control effect based on conservative assessment.

[0029] Furthermore, to address the actual load-bearing capacity of key equipment such as transformers or cables in practical engineering applications... Addressing the objective physical issue of capacity derating as ambient temperature rises, this invention can also introduce a dynamic capacity derating correction mechanism based on environmental sensing. In this scheme, the system further includes a temperature monitoring unit, which can be an industrial temperature sensor deployed near critical equipment in the second path, such as a switchgear busbar, to acquire real-time ambient temperature data. The topology controller internally stores a widely accepted capacity-temperature derating lookup table; before executing step a, the controller uses measured data... Retrieve a dynamic depreciation factor from the lookup table. and static capacity Perform dynamic adjustments to obtain a true dynamic capacity. All subsequent calculations regarding dynamic margin are based on this adaptive adjustment according to the real physical environment. This effectively avoids the risk of false safety margin misjudgment caused by environmental changes. Regarding the initial setting of the safety factor K, when there is no historical load data available for statistical analysis in the early stage of system operation, the K value is based on the inherent characteristics of the typical load carried by the second path. For example, the K value of data center load can be initially set to 2.5, while the K value of impact charging pile load can be initially set to 4.0. This conservative initial value is used for operation. After the system is running stably and a complete statistical cycle of data is accumulated, the statistical procedure described in Example 5 is used to recalculate and optimize the K value. Furthermore, when performing dynamic capacity derating correction based on ambient temperature, if the capacity bottleneck of the second path is in key equipment such as a specific type of transformer or automatic transfer switch, the construction of its capacity-temperature derating relationship lookup table should preferentially adopt the correction curve or data table of ambient temperature on rated current carrying capacity in the official performance data manual provided by the equipment manufacturer, instead of general engineering standards.

[0030] To ensure that the control system is protected from input contamination risks caused by sensor drift or communication interference during long-term operation, i.e., to prevent contamination caused by sensor drift or communication interference... In cases where inaccurate data leads to misleading information, this invention can also integrate a data reliability arbitration mechanism based on power balance verification. This scheme utilizes Kirchhoff's law of the system, namely that the total inlet current equals the sum of the outlet branch currents, as the basis for physical arbitration. Before executing step a, the topology controller will first perform a data reliability arbitration: using the real-time feeder loads of multiple downstream feeders under the second path simultaneously acquired by the monitoring module, its sum is calculated. Subsequently, the controller determines the real-time load of the second path. That is, the bus entry value, and the sum. This refers to whether the difference between the sum of the output values ​​and the output values ​​falls within a preset measurement error threshold, which can be set to 5%. The controller only confirms the measurement if the difference is within the threshold. If the data is reliable, subsequent steps a through e are allowed to proceed; otherwise, if the difference continues to exceed the error threshold, the controller immediately makes a decision. If the data is deemed unreliable, normal logic is forcibly rejected, and a fail-safe strategy is implemented instead. This means that the automatic switching function of the execution module is disabled, and a sensor reliability alarm is issued. This 13 / 00 control logic enhances the reliability of the input data, the cornerstone of system decision-making. Finally, to ensure the principle of system safety first is upheld, the present invention also incorporates fail-safe design for the control system itself and the communication link. On the one hand, the topology controller hardware is designed to be fail-safe. Its first control signal for enabling, for example, is a normally open contact output. This means that the controller must actively output a signal to activate the ATS. If the controller itself fails or loses power, the enabling signal automatically disappears, and the automatic switching function of the execution module is disabled by default. On the other hand, the topology controller also incorporates a data timeout watchdog to continuously monitor the data communication status of the monitoring module. When the real-time load of the first path is detected... Or the real-time load of the second path If data communication fails to update within a preset time (which can be set to 5 seconds), i.e., if communication is interrupted, the controller will forcibly remove the enable signal and be configured to execute the logic for if step b is not correct, i.e., enter a safety alert state to calculate the dynamic margin deficit and prepare for tiered pre-tripping. This design helps ensure that the system would rather prohibit automatic switching or switch to a lossy recovery plan when information is uncertain than perform a blind switch that could lead to a complete black screen. In addition, if step d is not correct, i.e., when the system recognizes the risk of insufficient margin, the topology controller can also be configured to send an early warning signal to the upper management system, i.e., BMS, through IoT communication, such as the MQTT protocol, while calculating the deficit. This signal is used to indicate that the dynamic margin of the second path is insufficient, so that the upper system can coordinate the execution of the load scheduling strategy.

[0031] Example 1: In a redundant power distribution network supplying power to a large medical data center, the first path of its N-1 topology, i.e., the primary path, supplies power to the critical server room (P1, highest priority) and the auxiliary office area (P3, lower priority). The second path, i.e., the backup path, supplies power to the hospital's air conditioning chillers and other public facilities, which are subject to high-impact loads. On a summer afternoon, the second path experiences a surge in static capacity due to the air conditioning chillers operating at full load. The calibrated capacity is 2000A, while the real-time load is... It has climbed to 1700A; meanwhile, the real-time load on the first path... The load stabilizes at 450A, with the P1 critical server at 300A and the P3 office area at 150A. Under this condition, a traditional automatic transfer switch based on static topology logic will be enabled. Because it cannot detect the real-time load capacity of the second path, if the first path fails at this time, its preset switching logic will be executed, causing the total load of the second path to momentarily reach [a certain value]. The load exceeds its static capacity. This will trigger the overload protection trip of the second path, ultimately causing the redundancy switching action intended to ensure power supply, resulting in a power outage for the critical server room; the topology controller deployed in this distribution network, as the system's safety decision-making unit, periodically executes its internal logic when the above-mentioned conditions occur: Execute step a, based on the static capacity of the second path and real-time load The dynamic margin of the second path is calculated. Only The controller then executes step b, the pre-determination of safety conditions, which involves determining the real-time load of the first path. Is it less than the dynamic margin? ;because The safety condition is determined to be negative; therefore, before any failure occurs in the first path, the topology controller has already entered the logic of step d, which calculates the dynamic margin deficit. Based on the preset load priority list, the P3 office area with a load of 150A was locked as the feeder to be tripped. At this time, the system's automatic switching function was disabled and entered the pre-planned execution state.

[0032] When the system is in a pre-planned, standby state, a power outage occurs on the first path due to a cable well fault. The monitoring module immediately reports this fault status to the topology controller. At this time, the topology controller immediately executes step e: sending trip commands to the multiple feeder execution modules corresponding to the P3 office area, cutting off the 150A unnecessary load from the first path within a defined logical delay, instantly reducing the load on the first path to only 300A for the critical P1 server. After the trip command is executed, the topology controller sends a switching command to the execution module, i.e., the automatic transfer switch. The automatic transfer switch then activates, safely switching the remaining 300A critical load to the second path. After the switching is completed, the final load carried by the second path is... This load value is equal to its static capacity. The second path system maintained stable operation, and the power supply continuity of the P1 critical server room was maintained under extreme conditions. The operation of this control logic shows that the system, through the coordinated operation of the dynamic margin safety interlock mechanism and the graded load pre-trip mechanism, has addressed the technical conflict between reliability and safety under dynamic load in the redundant design. It no longer relies on rigid topology switching of all or nothing, but has transformed into an active and elastic topology reconfiguration based on real-time carrying capacity. That is, when the margin is insufficient, it actively discards the preset low-priority loads to make room for switching capacity for high-priority loads, thus realizing the graded survival of the power supply and distribution system.

[0033] Example 2: To objectively verify the effectiveness of the technical solution of the present invention under dynamic load and complex engineering environments, this example constructs a hardware-in-the-loop simulation test platform. This platform simulates an N-1 redundant distribution network with a first path and a second path, wherein the rated static capacity of the second path is... The circuit was set to 1000A and connected to a load simulator capable of accurately simulating dynamic load characteristics. The experiment was divided into three groups: Control Group 1 used a traditional automatic transfer switch, which lacked dynamic margin sensing capability; Control Group 2 used a switch that only implemented basic margin judgment, i.e. The controller in the previous example did not integrate correction for load variability or ambient temperature; the present invention's sample uses a complete topology controller, which integrates load variability-based quantization, i.e. The control logic was modified to reflect ambient temperature sensing; the initial state parameters of the experiment were uniformly set to simulate a high-risk operating condition: the real-time load of the first path was set. The load is 100A, consisting of a 60A high-priority load (P1) and a 40A low-priority load (P3); the average real-time load of the second path is set. The current rating is 750A; to simulate nonlinear load impacts in real-world engineering, the load simulator adds an additional random fluctuation signal to the second path, making... Standard deviation of load volatility quantification index Stabilize at 30A; simultaneously, set the ambient temperature. 45 Based on the capacity-temperature derating lookup table in the specific implementation, the temperature-corrected derating is calculated. for In the topology controller of the prototype of this invention, a preset safety factor is included. The value is 3; before the fault trigger at t=10s, the operating status of each test group is as follows, and their operation and decision status are shown in the first four columns of Table 1; Control group 1 has no operation and remains unconditionally on standby; the controller of control group 2 is based on static capacity. and average load Perform calculations, its ,because The controller incorrectly output an enable signal; the topology controller of the present invention's sample executed the complete safety logic and determined... Given 900A, calculate the deductions used for volatility correction. This leads to the conclusion of the safety dynamic margin. ,because If the controller determines otherwise, it immediately disables the automatic switching function of the automatic transfer switch and proceeds to step d to calculate the dynamic margin deficit. Based on the priority list, the P3 load was then identified as the feeder to be tripped.

[0034] At t=10s, the HIL platform simulates a failure in the first path, and at the instant the failure triggers a switchover, a synchronous force is applied to the second path. The instantaneous load peak, causing its instantaneous load to reach The responses of each group are shown in the last three columns of Table 1. Control groups 1 and 2, being in an enabled state, immediately performed a complete 100A load switch, resulting in the final instantaneous load of the second path reaching [values ​​missing]. This value exceeds its temperature-corrected value. (900A) triggered the overload protection trip of the second path, causing a power outage in the system. When the topology controller of the prototype of this invention detected the fault in the first path, it strictly executed the trip-then-switch sequence of step e, sending a trip command to the P3 feeder execution module to disconnect the 40A load, and then sending a switching command to the automatic transfer switch to switch only the 60A load of P1 to the second path. Its final instantaneous load was The value did not exceed The system maintained stable operation, and the power supply continuity of the high-priority load P1 was maintained.

[0035] Table 1: Comparison of Dynamic Switching Test Results of HIL Simulation Platform

[0036]

[0037] Experimental data shows that the failure of control group 2 was due to its simplified control logic, which ignored load fluctuations. and ambient temperature The combined effects of the dynamic margin resulted in a calculated excessively high dynamic margin value of 250A, leading to an incorrect enable decision. The control logic of the prototype of this invention, through... and Two key variables in the operation of the project were quantified as... Deductions and Through dynamic correction, a margin assessment value of 60A was obtained for the actual load-bearing capacity of the system. Based on this, a graded load pre-tripping mechanism was implemented in conjunction with the system, and finally, the power supply to high-priority loads was restored without the system crashing.

[0038] Example 3: The test platform, simulation conditions, and all initial state parameters used in this example, including the static capacity of the second path. Ambient temperature Real-time load of the first path Average real-time load of the second path Quantitative indicators of load volatility and safety factor All are completely consistent with the sample group of the present invention in Example 2; the only difference in this embodiment is that the topology controller used is also integrated with the present invention based on and The revised complete margin calculation logic is implemented, but it does not integrate a tiered load pre-trip mechanism, meaning it lacks the latter half of step d and the control timing of step e in the aforementioned specific implementation. Under this simulation condition, the topology controller in this embodiment also performs a complete margin calculation before the fault is triggered, based on... , and The safety dynamic margin is calculated. Only 60A; the controller then executes the judgment in step b, based on If the decision is negative, the controller performs its only safety action: outputting a second control signal to disable the automatic transfer switch's automatic switching function and sending a warning signal of insufficient dynamic margin to the upper-level management system. At t=10s, the HIL platform simulates a fault in the first path. Since the topology controller in this embodiment is in a disabled state and does not have a graded load pre-trip mechanism, it continues to maintain the disabled state after detecting the fault, and the automatic transfer switch does not perform any switching action. The final result is that the load on the second path remains stable and no overload trip occurs, but all 100A loads on the first path, including the 60A P1 highest priority load and the 40A P3 load, are lost because they were not switched. The system enters a safe but paralyzed state, failing to achieve the goal of ensuring the continuity of power supply to critical loads. The comparative example of this embodiment and the operation comparison of the sample group of the present invention in Embodiment 2 are shown in Table 2.

[0039] Table 2: Comparison of the operation of this embodiment (comparative example) and embodiment 2 (sample of the present invention)

[0040]

[0041] The experimental data comparison in Table 2 shows that control schemes with advanced margin calculation capabilities, such as the comparative examples in this embodiment, can avoid the risk of systemic power outages caused by blind switching, i.e., the failure modes of control groups 1 and 2 in Example 2. However, they themselves fall into the engineering dilemma of being safe but paralyzed, and still cannot achieve the goal of ensuring the continuity of power supply to high-priority loads. The sample group of this invention solved this technical problem by further integrating the control timing of graded load pre-tripping based on accurate margin judgment, and achieved the recovery of the P1 critical load under the premise of ensuring the overall safety of the system.

[0042] Example 4: This example combines Figures 1 to 3 A description of a real-time monitoring system for distribution network status based on Internet of Things (IoT) technology, such as... Figure 1 As shown, the process begins by acquiring initial data such as ambient temperature, real-time load of the second path, and real-time load of the first path. Ambient temperature is used for dynamic capacity derating correction to obtain the true dynamic capacity, and the real-time load of the second path is used for load volatility quantification to generate a safety penalty item. Subsequently, the system calculates the safety dynamic margin based on the true dynamic capacity, load, and safety penalty item. At the core topology switching safety judgment node, the system determines whether the real-time load of the first path is less than the safety dynamic margin. If yes, it enables automatic switching and enters a safety standby state. If no, it calculates the margin deficit, sends a margin insufficiency warning, and generates a pre-trip plan. This process also monitors for faults in the first path. Once a fault is detected, the system will decide the switching mode based on the judgment result: when in safety standby, it performs a regular switch; when in pre-plan execution, it performs a tiered survival sequence, namely 1. first tripping non-essential feeders and 2. then switching the remaining critical loads.

[0043] like Figure 2 As shown, the horizontal axis represents the time window, and the vertical axis represents the current (A). The figure uses two curves to illustrate the load standard deviation monitored within different time windows. ( (Solid line) and the safety penalty items calculated accordingly (Dashed line) This graph visually illustrates how the safety penalty is based on statistical indicators of load volatility. Dynamically magnified; such as Figure 3As shown in the diagram, the external monitoring module, temperature monitoring unit, and upper-level management system interact with the core control logic. Data from the monitoring module is input to the module for acquiring the real-time status of the distribution network and verifying data reliability. Data from the temperature monitoring unit is input to the module for applying temperature derating correction. Failure to verify data reliability will force a response to insufficient margin. Status acquisition is used for applying load volatility correction. These two corrections, along with temperature derating correction, work together to calculate the dynamic safety margin. This margin value is the basis for pre-safety judgment. If the margin is deemed sufficient, the automatic switching function is enabled. If the margin is deemed insufficient, the calculation of margin deficit is triggered, an insufficient margin warning is sent, and a graded survival plan is generated. This plan is triggered when a fault is detected, thereby executing the first trip and then switching sequence, ultimately controlling the execution module and the feeder execution module.

[0044] Example 5: This example illustrates the systematic calibration procedure for key parameters introduced for control logic, addressing the challenge of converting preset parameters into reproducible and verifiable engineering values ​​during the initial system deployment phase. This procedure is a prerequisite for ensuring the reliable operation of the topology controller in a specific engineering field. The first key parameter calibrated is the safety factor. This coefficient is used to calculate safety penalty items. Its purpose is to ensure that the penalty is sufficient to cover the second path. In real-world engineering scenarios, most instantaneous load shocks are detected, thus avoiding misjudgments caused by false safety margins. The calibration procedure inputs high-temporal-resolution historical load data obtained from the second path monitoring module of the distribution network, in a continuous 30-day period with a sampling interval of 1 second. Taking a dataset as an example, the calibration procedure includes the following steps: First, set a statistical time window, such as 1 minute; second, execute this window repeatedly over the entire 30-day dataset, calculating the average load value within each window. and standard deviation The third step is to identify the instantaneous load peak within each window. And calculate its maximum positive deviation from the window mean. The fourth step is to calculate the results for all windows. Statistical analysis was performed on the values ​​to identify the deviation value corresponding to the 99.9th percentile. The fifth step is to... Standard deviation of this time window Compare and determine Value, that is In a specific calibration, the standard deviation of a second-path dataset containing high-impact loads within a 1-minute window is analyzed. It stabilizes at around 30A, while the maximum positive deviation at its corresponding 99.9% quantile is... The statistics show it to be 88A, therefore The calibration result of the value is Therefore, the safety factor will be... The default setting of 3 is a reproducible engineering choice based on statistical analysis, making... The safety penalty item represented, 90A, can cover more than 99.9% of the actual load impact 88A.

[0045] The second key parameter for calibration is the preset error threshold used by the power balance verification logic in the aforementioned specific implementation. Its calibration purpose is to distinguish between normal data imbalance caused by CT metering and line loss in the system, and abnormal data imbalance caused by sensor failure or communication interruption. The input to the calibration procedure is the real-time load at the second path bus inlet, which is continuously and synchronously collected for 24 hours under normal system operation. and the sum of all downstream feeder loads The calibration procedure includes the following steps: First, calculate the relative error for each sampling point. The second step is to apply this to all... Perform statistical distribution analysis on the values ​​to find the error value corresponding to the 99.9th percentile. This value represents the maximum inherent measurement error of the system under non-fault conditions; in a specific calibration, after analyzing 24 hours of data, the following result was obtained. The baseline error is 4.2%. Based on this calibration result, an engineering trade-off needs to be made. If the preset error threshold is set too low, such as 3%, the inherent error below 4.2% will be frequently misjudged as unreliable, causing the controller to frequently enter the fail-safe switching-prohibited state, affecting the availability of the system. If it is set too high, such as 10%, it may not be able to detect the actual fault and the progressive sensor drift fault with a data deviation in the range of 6% to 9% in time. Therefore, setting the preset error threshold to 5% is a reproducible engineering decision that balances the system sensitivity and reliability based on the 4.2% inherent error baseline.

[0046] The third item specified is a capacity-temperature derating lookup table, which is used in the aforementioned specific embodiments. The calculations are not based on empirical estimations, but rather on publicly available engineering standards in the field, such as the current-carrying capacity correction factor tables for cables or busbars under different ambient air temperatures in GB / T16895.6 or IEC60364-5-52. The construction procedure includes: First, determining the design reference operating temperature of the transformer and feeder cable, which are key equipment in the second path, taking 40℃ as an example; Second, looking up the current-carrying capacity correction factor tables for different ambient air temperatures from the aforementioned engineering standards. The corresponding standard reduction coefficient The third step is to pair these standard data, such as... correspond , correspond , correspond The capacity-temperature derating relationship lookup table is pre-stored in the internal memory of the topology controller, forming a table that can be called in real time by the logic; this procedure ensures that in Example 2... The use of a correction factor of 0.9 has a clear engineering standard source. By executing the above calibration procedure, the key logic parameters in the topology controller, namely... The values, error thresholds, and temperature derating models are no longer based on estimated empirical values, but are transformed into reproducible parameters based on historical operating data of specific power distribution networks or recognized engineering standards, with statistical basis and clear engineering trade-offs. This ensures that the control system of this invention has a consistent and reliable operating foundation in different engineering sites.

[0047] Example 6: To verify the effectiveness of another disclosed technical solution, namely the control logic that uses peak-to-average ratio as a volatility quantification indicator, this example uses the HIL simulation test platform and initial state parameters that are completely consistent with Examples 2 and 3, including... , (correspond (for 900A) , The difference from Example 2 is that in this example, the load simulator... Based on this, an instantaneous load peak was applied within its short time window. Upon receiving an impact signal of 832.5A, and given that the topology controller employs peak-to-average power ratio (PAPR) correction logic, in this embodiment, the topology controller executes safety logic before a fault is triggered: within a short time window, the controller, based on the monitored... (832.5A) and (750A), the peak-to-average power ratio was calculated. Subsequently, the controller adopted The rule calculates the safety dynamic margin, where the safety factor is... In this embodiment, the default value is 1.0; based on this, the security penalty item is calculated as follows: The final safety dynamic margin is obtained. .

[0048] The controller then executes the judgment in step b, based on... The decision is negative; the controller then proceeds to step d to calculate the dynamic margin deficit. The controller increments the priority list starting from P3 (40A). It is already greater than Therefore, only the P3 load (40A) is identified as the feeder to be tripped, and the system enters the pre-planned execution state. At t=10s, the HIL platform simulates a fault in the first path, and the topology controller immediately executes the timing sequence of step e: sending a trip command (cutting off 40A) to the P3 feeder execution module, and then switching the remaining P1 load (60A) to the second path; the switching action is superimposed on the instantaneous load peak (832.5A) of the second path, resulting in the final instantaneous load of the second path being... The value did not exceed... The system maintains stable operation, and the power supply continuity of the high-priority load P1 is also maintained. This embodiment verifies that using peak-to-average power ratio as a volatility quantification indicator can also provide a reliable safety margin assessment for the control system and coordinate with the graded load pre-trip mechanism.

[0049] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A real-time monitoring system for distribution network status based on Internet of Things (IoT) technology, applied to a redundant distribution network including at least a first path and a second path, wherein the second path has static capacity, the system comprising: The execution module is used to switch the load to the second path when the first path fails; The system also includes multiple feeder execution modules, each used to control the on / off state of multiple downstream feeders of the first path. The system is characterized by further comprising: The monitoring module is used to acquire the real-time load of the first path, the real-time load of the second path, the load of multiple downstream feeders of the first path, and the fault status of the first path. A topology controller, electrically connected to the monitoring module, the execution module, and multiple feeder execution modules, is configured to: Step a, calculate the dynamic margin of the second path based on the static capacity and real-time load of the second path; further calculate the standard deviation of the real-time load of the second path within a time window as a volatility quantification indicator. Based on volatility quantitative indicators and preset safety factor Generate safety penalty items; calculate dynamic margin in step a. The rules have been revised as follows: ,in For static capacity, This represents the real-time load of the second path; the judgment in step b is based on this corrected dynamic margin. The process is as follows: Step b: Determine whether the real-time load of the first path is less than the dynamic margin of the second path; Step c: If the determination in step b is yes, output the first control signal to enable the automatic switching function of the execution module; Step d: If the determination in step b is no, calculate the dynamic margin deficit between the real-time load and the dynamic margin of the first path, and determine one or more feeders to be tripped whose total load is sufficient to cover the dynamic margin deficit according to the preset load priority of downstream feeders; Step e: And when the monitoring module detects a fault in the first path, if the determination in step b is no, the topology controller is configured to send a trip command to multiple feeder execution modules corresponding to the feeder to be tripped, and after the trip command is executed, send a switching command to the execution module.

2. The real-time monitoring system for distribution network status based on Internet of Things (IoT) technology according to claim 1, characterized in that, The topology controller is also configured to detect the data communication status of the monitoring module, and when the data communication interruption of the real-time load of the first path or the real-time load of the second path is detected, the topology controller is also configured to execute the logic of step b if the judgment is negative.

3. The real-time monitoring system for distribution network status based on Internet of Things (IoT) technology according to claim 1, characterized in that, The system also includes: a temperature monitoring unit for acquiring the ambient temperature of key equipment in the second path; the topology controller is also configured to: dynamically correct the static capacity of the second path based on the ambient temperature and according to a preset capacity-temperature derating relationship to obtain the true dynamic capacity; and the dynamic margin in step a is calculated based on the true dynamic capacity and the real-time load of the second path.

4. The real-time monitoring system for distribution network status based on Internet of Things (IoT) technology according to claim 1, characterized in that, The monitoring module is also used to obtain the real-time feeder load of multiple downstream feeders under the second path. The topology controller is also configured to: before executing step a, calculate the sum of the real-time feeder loads of multiple downstream feeders under the second path, and determine whether the difference between the real-time load of the second path and the sum is within the preset error threshold. Steps a to e are executed only when the difference is within the error threshold; When the difference continues to exceed the error threshold, the automatic switching function of the module will be disabled.

5. A real-time monitoring system for distribution network status based on Internet of Things (IoT) technology according to claim 1, characterized in that, The topology controller is configured such that the automatic switching function of the execution module is disabled by default when the topology controller itself fails or loses power.

6. The real-time monitoring system for distribution network status based on Internet of Things (IoT) technology according to claim 1, characterized in that, When the determination in step b is negative, the topology controller is also configured to send an early warning signal to the upper management system while calculating the dynamic margin deficit. The early warning signal is used to indicate that the dynamic margin of the second path is insufficient.

7. The real-time monitoring system for distribution network status based on Internet of Things (IoT) technology according to claim 1, characterized in that, The topology controller is a programmable logic controller.

8. The real-time monitoring system for distribution network status based on Internet of Things (IoT) technology according to claim 1, characterized in that, The execution module is an automatic switching switch.

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