Primary and secondary fusion column breaker and ftu load limit early warning method

Abstract

The present application belongs to the technical field of intelligent power distribution automation, and particularly relates to a load over-limit early warning method for primary and secondary fusion pole-mounted circuit breakers and FTUs, comprising: collecting circuit breaker and line operation data through the FTU, and obtaining real-time load data of adjacent circuit breakers through local edge communication; calculating a dynamic allowable load threshold value based on multi-dimensional device health, generating a load prediction maximum value using edge side time series prediction, obtaining a warning decision value by combining power flow direction and neighborhood load correction, comparing the load warning decision value with the dynamic allowable load threshold value, judging the line load over-limit risk level, performing corresponding on-site load regulation and control operation, and uploading relevant data to the power distribution automation master station. The present application can improve the accuracy and timeliness of load over-limit early warning, and reduce the risk of power distribution line overload failure.

Description

Technical Field

[0001] This invention belongs to the field of intelligent power distribution automation technology, specifically relating to a load over-limit early warning method for primary and secondary integrated pole-mounted circuit breakers and FTUs. Background Technology

[0002] With the continuous advancement of intelligent power distribution network construction, integrated primary and secondary pole-mounted circuit breakers and FTU distribution terminals are gradually becoming core equipment for online monitoring and load management of 10kV distribution lines. Load over-limit early warning is a key technology to ensure the safe and stable operation of the power distribution network and improve power supply reliability. In new power distribution scenarios with the large-scale integration of distributed power sources and increasingly severe fluctuations in user loads, traditional load over-limit early warning methods can no longer meet the requirements for refined and forward-looking management.

[0003] Most existing overload warning technologies use a fixed rated load threshold as the judgment standard. These technologies do not dynamically adjust the threshold based on the circuit breaker's own electrical and mechanical health status, as well as the on-site environmental conditions. When the equipment experiences aging contacts overheating or mechanical characteristic deterioration, the system still performs warnings based on the rated load value, which can easily lead to delayed warnings, misjudgments, or missed judgments, failing to match the actual current-carrying capacity of the equipment.

[0004] Current load forecasting methods mostly employ a single forecasting model, failing to adequately consider the dynamic characteristics of the power grid topology caused by changes in power flow direction and load coupling between adjacent lines. This results in low accuracy in load forecasting, and the early warning judgment process does not integrate real-time load data from adjacent equipment, making it unable to adapt to real-time changes in power flow. The early warning results deviate significantly from actual on-site conditions, making it difficult to support subsequent control and regulation efforts.

[0005] Existing technologies lack a tiered risk assessment mechanism and on-site collaborative control strategies. Control methods are relatively crude and response times are slow, failing to form a complete control loop. The overall early warning and control processes are fragmented, with a lack of efficient linkage between local terminals and the main station, making it difficult to implement differentiated measures based on risk levels and failing to guarantee the safety and timeliness of power distribution line load control. Summary of the Invention

[0006] The present invention aims to at least partially solve one of the technical problems in the related art.

[0007] Therefore, the purpose of this invention is to propose a load over-limit early warning method that integrates primary and secondary pole-mounted circuit breakers and FTUs, in order to solve the problems of fixed and rigid thresholds, low prediction accuracy, and rough and lagging regulation in the existing technology.

[0008] To achieve the above objectives, a first aspect of the present invention proposes a load over-limit early warning method for a primary and secondary integrated pole-mounted circuit breaker and FTU, comprising:

[0009] The FTU acquires data on the three-phase current, contact temperature, ambient temperature and humidity, and mechanical characteristics of opening and closing of the primary and secondary integrated pole-mounted circuit breaker, as well as the active power and real-time power flow data of the distribution line. It also acquires real-time load data of adjacent primary and secondary integrated pole-mounted circuit breakers through local edge communication.

[0010] Based on the three-phase current, contact temperature, ambient temperature and humidity, and mechanical characteristics of opening and closing, the dynamic allowable load threshold corresponding to the primary and secondary integrated pole-mounted circuit breaker is calculated according to the preset equipment health assessment rules.

[0011] Based on the active power data of the line, the load change trend of the line is extracted, and the maximum load prediction value for a future set period is generated using a time-series prediction model. The maximum load prediction value is corrected according to the real-time power flow and the real-time load data of adjacent primary and secondary fusion pole-mounted circuit breakers to obtain a load warning judgment value adapted to the current power grid topology.

[0012] The load warning judgment value is compared with the dynamic allowable load threshold. Based on the comparison result, the risk level of line load exceeding the limit is determined, and the corresponding predictive load exceeding the limit warning instruction is matched.

[0013] According to the load over-limit warning command, the corresponding local load control operation is executed, and the warning information, load-related data and control execution results are uploaded to the distribution automation master station.

[0014] In addition, the load over-limit warning method for primary and secondary integrated pole-mounted circuit breakers and FTUs according to the above embodiments of the present invention may also have the following additional technical features:

[0015] Furthermore, in one embodiment of the present invention, obtaining real-time load data of adjacent primary and secondary fusion pole-mounted circuit breakers via local edge communication includes:

[0016] Real-time load data of upstream and downstream adjacent primary and secondary pole-mounted circuit breakers directly connected to this primary and secondary pole-mounted circuit breaker are obtained through LoRa or power line carrier communication.

[0017] The real-time load data of the adjacent primary and secondary fusion pole-mounted circuit breakers includes real-time active power, dynamic allowable load threshold, and current equipment health level.

[0018] Furthermore, in one embodiment of the present invention, the step of calculating the current dynamic allowable load threshold of the primary and secondary fusion pole-mounted circuit breaker according to a preset equipment health assessment rule includes:

[0019] A multi-dimensional equipment health assessment index system is constructed, which is divided into electrical health dimension, mechanical health dimension and environmental impact dimension;

[0020] The weights of the electrical health dimension, mechanical health dimension, and environmental impact dimension are determined using the analytic hierarchy process (AHP), and the overall equipment health score is calculated by weighted summation based on these weights.

[0021] Based on the overall health score of the equipment and the rated allowable load current of the circuit breaker, the current dynamic allowable load threshold is calculated using the dynamic threshold correction formula.

[0022] Furthermore, in one embodiment of the present invention, the dynamic threshold correction formula is:

[0023]

[0024] In the formula: This is a dynamic allowable load threshold; The rated allowable load current of the circuit breaker; The overall health score of the equipment ranges from 0 to 1.

[0025] Furthermore, in one embodiment of the present invention, based on the active power data of the line, the line load change trend is extracted, and a time-series forecast model is used to generate the maximum load forecast for a future set period, including:

[0026] Extract the active power data of the line at 15-minute intervals over the past 24 hours to construct a load time series dataset;

[0027] The TCN-BiLSTM hybrid time-series forecasting model is trained in the distribution automation master station and deployed to the FTU to perform inference on the load time-series dataset, outputting load forecast curves for two set time periods of 1 hour and 3 hours in the future.

[0028] The load forecast curves for the two set time periods are numerically filtered to extract the maximum load forecast value for the corresponding time period.

[0029] Furthermore, in one embodiment of the present invention, the maximum load prediction value is corrected based on the real-time power flow direction and the real-time load data of adjacent primary and secondary fusion pole-mounted circuit breakers to obtain a load warning judgment value adapted to the current power grid topology, including:

[0030] Match the corresponding preset power flow direction correction coefficient according to the direction of real-time power flow;

[0031] Calculate the adjacent load influence coefficient based on the real-time load data of adjacent primary and secondary fusion pole-mounted circuit breakers;

[0032] The load warning judgment value is calculated using a modified formula. The calculation formula is as follows:

[0033]

[0034] In the formula: This is the load warning judgment value; This represents the maximum predicted load. This is a power flow direction correction factor; This is the influence coefficient of adjacent loads.

[0035] Furthermore, in one embodiment of the present invention, the risk level includes:

[0036] Level 1 Normal State: The load warning judgment value is less than 80% of the dynamic allowable load threshold, and the routine monitoring command is matched;

[0037] Level 2 warning risk: The load warning judgment value is greater than or equal to 80% and less than 90% of the dynamic allowable load threshold, which matches the yellow warning instruction;

[0038] Level 3 alarm risk: The load warning judgment value is greater than or equal to 90% of the dynamic allowable load threshold and less than 100%, which matches the orange alarm command;

[0039] Level 4 Emergency Risk: The load warning judgment value is greater than or equal to the dynamic allowable load threshold, matching the red emergency instruction.

[0040] Furthermore, in one embodiment of the present invention, executing the corresponding local load control operation according to the load over-limit warning command includes:

[0041] When a routine monitoring command is received, the FTU maintains the original monitoring frequency and collects line load data every 15 minutes.

[0042] When a yellow alert is received, the FTU increases the data acquisition frequency to once every 5 minutes and simultaneously activates the reactive power compensation device to perform local voltage and current regulation.

[0043] When an orange alarm command is received, the FTU sends a load transfer request to the upstream or downstream adjacent circuit breaker through local edge communication and notifies the distribution automation master station to coordinate the tie switch to transfer the load. If there is no adjacent transferable path, the controllable load at the end of the line is requested to be cut off according to the preset priority.

[0044] When a red emergency command is received, the FTU first executes the load transfer operation of the orange alarm command. If the over-limit time exceeds the preset safe duration and there is no effective control means, the primary and secondary fusion pole-mounted circuit breakers are disconnected, and the audible and visual alarm device is triggered.

[0045] Furthermore, in one embodiment of the present invention, uploading early warning information, load-related data, and control execution results to the distribution automation master station includes:

[0046] The warning level, warning time, dynamic allowable load threshold, maximum load forecast, control operation type and execution time data are uploaded to the distribution automation master station in real time through the power wireless private network.

[0047] After receiving the data, the main station generates a visual report that includes load change curves, risk evolution trends, and control recommendations.

[0048] The master station issues optimization control instructions based on the overall network load, and the FTU adjusts the local load control strategy after receiving the instructions.

[0049] To achieve the above objectives, a second aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the load over-limit warning method for primary and secondary fusion pole-mounted circuit breakers and FTUs as described above.

[0050] The load over-limit early warning method for primary and secondary integrated pole-mounted circuit breakers and FTUs proposed in this invention has the following advantages compared with the prior art:

[0051] This invention can construct equipment health assessment rules based on the circuit breaker's own multi-dimensional operating data, and calculate a dynamic allowable load threshold that fits the actual current carrying capacity of the equipment, thus solving the problem of fixed and rigid thresholds in existing technologies.

[0052] This invention uses a pre-trained TCN-BiLSTM hybrid time-series prediction model for load inference, which can accurately extract the line load change trend, output load prediction results for multiple time periods, and improve the overall accuracy of load prediction.

[0053] This invention combines real-time power flow direction and real-time load data of adjacent circuit breakers to perform dual correction on the maximum load prediction value, thereby obtaining a load warning judgment value that is adapted to the current power grid topology and solving the problem of large deviation between the warning result and the actual operating condition.

[0054] This invention sets up a four-level load overload risk classification standard, which can match corresponding early warning instructions according to different risk levels and carry out differentiated load overload risk management;

[0055] This invention constructs a complete control system that includes edge early warning, hierarchical judgment, local control, and main station linkage. It can execute hierarchical local control operations based on early warning instructions, thus solving the problems of crude and lagging response in existing control technologies.

[0056] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0057] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0058] Figure 1 A flowchart of the load over-limit early warning method for primary and secondary integrated pole-mounted circuit breakers and FTUs provided in an embodiment of the present invention;

[0059] Figure 2 The flowchart for the 10kV circuit breaker overload warning system provided in this embodiment of the invention is shown. Detailed Implementation

[0060] Embodiments of the present invention are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0061] The following describes, with reference to the accompanying drawings, a method for early warning of overload of a primary and secondary integrated pole-mounted circuit breaker and FTU according to an embodiment of the present invention.

[0062] Figure 1 This is a schematic flowchart of the load over-limit early warning method for primary and secondary integrated pole-mounted circuit breakers and FTUs provided in an embodiment of the present invention.

[0063] like Figure 1 As shown, the load over-limit early warning method for the integrated primary and secondary pole-mounted circuit breaker and FTU includes the following steps:

[0064] S101: The FTU acquires data on the three-phase current, contact temperature, ambient temperature and humidity, and mechanical characteristics of opening and closing of the primary and secondary integrated pole-mounted circuit breaker, as well as the active power and real-time power flow data of the distribution line. It also acquires real-time load data of adjacent primary and secondary integrated pole-mounted circuit breakers through local edge communication.

[0065] Specifically, the FTU (Feeder Terminal Unit) collects three-phase current data from the primary and secondary integrated pole-mounted circuit breaker via a built-in current transformer, contact temperature data from the circuit breaker contacts via a contact-type temperature sensor, ambient temperature and humidity data via an environmental sensor, and circuit breaker opening and closing time, opening and closing speed, and contact bounce time data via a mechanical characteristic detection unit. The FTU obtains real-time active power and real-time power flow data of the distribution line where the circuit breaker is located through a voltage and current acquisition circuit. The FTU establishes a point-to-point communication link with adjacent primary and secondary integrated pole-mounted circuit breakers via a local edge communication module to obtain real-time load data from the adjacent circuit breakers.

[0066] Furthermore, in one embodiment of the present invention, obtaining real-time load data of adjacent primary and secondary fusion pole-mounted circuit breakers via local edge communication includes:

[0067] Real-time load data of upstream and downstream adjacent primary and secondary pole-mounted circuit breakers directly connected to this primary and secondary pole-mounted circuit breaker are obtained through LoRa or power line carrier communication.

[0068] The real-time load data of adjacent primary and secondary fusion pole-mounted circuit breakers includes real-time active power, dynamic allowable load threshold, and current equipment health level.

[0069] Specifically, local edge communication enables low-latency autonomous interaction between distribution terminals, allowing data transmission without relying on a distribution automation master station. Upstream adjacent circuit breakers are devices located upstream of this circuit breaker in the direction of power transmission, while downstream adjacent circuit breakers are devices located downstream of this circuit breaker. The collected operational data from adjacent devices directly reflects the load level of adjacent lines, the equipment's maximum capacity, and its health status, providing neighborhood operational support for subsequent load adjustments, risk assessment, and coordinated control.

[0070] S102: Based on three-phase current, contact temperature, ambient temperature and humidity, and mechanical characteristics of opening and closing, calculate the current dynamic allowable load threshold of the primary and secondary integrated pole-mounted circuit breaker according to the preset equipment health assessment rules.

[0071] Furthermore, in one embodiment of the present invention, the dynamic allowable load threshold corresponding to the primary and secondary fusion pole-mounted circuit breaker is calculated using a preset equipment health assessment rule, including:

[0072] A multi-dimensional equipment health assessment index system was constructed, which is divided into electrical health dimension, mechanical health dimension and environmental impact dimension;

[0073] The weights of the electrical health dimension, mechanical health dimension, and environmental impact dimension were determined using the analytic hierarchy process (AHP). Based on these weights, the overall health score of the equipment was calculated by weighted summation.

[0074] Based on the overall health score of the equipment and the rated allowable load current of the circuit breaker, the current dynamic allowable load threshold is calculated using the dynamic threshold correction formula.

[0075] Specifically, the equipment health assessment rules include a complete quantitative process encompassing multi-dimensional indicator classification, weight calculation, health status verification, and dynamic threshold conversion. First, the collected operational data is categorized into three assessment dimensions: electrical health, mechanical health, and environmental impact. The electrical health dimension corresponds to two indicators: three-phase current and contact temperature, reflecting the operating status and current-carrying capacity of the equipment's electrical circuits. The mechanical health dimension corresponds to three indicators: opening and closing time, opening and closing speed, and contact bounce time, reflecting the working status and operational reliability of the equipment's operating mechanisms. The environmental impact dimension corresponds to two indicators: ambient temperature and ambient humidity, reflecting the impact of external operating conditions on the equipment's heat dissipation and insulation performance.

[0076] The analytic hierarchy process (AHP) was used to determine the influence weights of the three evaluation dimensions. First, a third-order judgment matrix was constructed, and the importance of each of the three dimensions was assigned pairwise. Then, the largest eigenvalue and corresponding eigenvector of the judgment matrix were calculated, and the eigenvectors were normalized to obtain the initial weights for each dimension. Finally, a consistency check was performed. If the consistency ratio was less than 0.1, the weight allocation was deemed reasonable, and the initial weights were used as the final dimension influence weights.

[0077] The units and magnitudes of the various indicators differ significantly, making direct weighted calculation impossible. Normalization is necessary to convert all indicators into standardized scores within the zero-to-one range. The normalization method employs extreme value standardization. For inverse indicators where larger values ​​indicate worse equipment condition, the normalization formula is:

[0078]

[0079] In the formula, X represents the normalized score of the indicator; X represents the actual collected value of the indicator. This refers to the upper limit allowed for the indicator. This represents the ideal lower limit of the indicator.

[0080] Taking contact temperature as an example, the ideal lower limit for contact temperature is set to 40℃, and the allowable upper limit is set to 80℃. The currently collected contact temperature is 60℃. Substituting these values ​​into the formula, the normalized score for contact temperature is calculated to be 0.5. This method unifies different dimensions such as Celsius, current, ampere, time, and milliseconds into a value between zero and one, ensuring that all indicators are equally comparable when participating in weighted calculations.

[0081] Sub-weights are assigned according to the degree of influence of sub-indicators on the health score of the dimension. The health score for each dimension is calculated by weighted summation. The weights of each sub-indicator are determined through the analytic hierarchy process and statistical analysis of on-site operational data. Taking the electrical health dimension as an example, its score calculation formula is as follows:

[0082]

[0083] In the formula, The weights of the three-phase current sub-indices are... The weight of the contact temperature sub-index is... The normalized score for the three-phase current is calculated. The contact temperature score is normalized. The scoring methods for the mechanical health and environmental impact dimensions are the same as those for the electrical health dimension.

[0084] The overall health score of the device is obtained by multiplying the health scores of the three dimensions by their corresponding weights and then summing the results. The calculation formula is as follows:

[0085]

[0086] In the formula, Weighting for electrical health dimension; Weights for the mechanical health dimension; For the environmental impact dimension weights; H e Score the electrical health level; The machine's health score; H represents the environmental impact score, and H represents the overall health score of the equipment, with a value range of 0-1.

[0087] Using the overall health score of the equipment as the core adjustment parameter, and combining it with the rated allowable load current of the circuit breaker into the dynamic threshold correction formula, the maximum load current that the current equipment can safely bear is calculated.

[0088] Furthermore, in one embodiment of the present invention, the dynamic threshold correction formula is:

[0089]

[0090] In the formula: This is a dynamic allowable load threshold; The rated allowable load current of the circuit breaker; The overall health score of the equipment ranges from 0 to 1.

[0091] Specifically, the coefficients 0.6 and 0.4 were determined through statistical analysis of historical current-carrying fault data of multiple primary and secondary integrated pole-mounted circuit breakers of the same model and cross-verification with multi-condition current-carrying simulation tests. This ensures that healthy equipment with a comprehensive health level of 1 can withstand loads close to the rated value, while severely deteriorated equipment with a comprehensive health level of 0 still retains its basic safety bearing capacity.

[0092] S103: Based on the active power data of the line, extract the load change trend of the line, use the time series prediction model to generate the maximum load prediction value for the future set period, and correct the maximum load prediction value according to the real-time power flow direction and the real-time load data of the adjacent primary and secondary integrated pole-mounted circuit breakers to obtain the load warning judgment value adapted to the current power grid topology.

[0093] Specifically, the load warning judgment value refers to the final judgment threshold used to determine whether to trigger a load over-limit warning after correcting the maximum load value for the future period obtained from time-series forecasts by combining real-time power grid topology and the operating status of neighboring equipment.

[0094] Furthermore, in one embodiment of the present invention, based on the active power data of the line, the line load change trend is extracted, and a time-series forecast model is used to generate the maximum load forecast for a future set period, including:

[0095] Extract the active power data of the line at 15-minute intervals over the past 24 hours to construct a load time series dataset;

[0096] The TCN-BiLSTM hybrid time-series forecasting model is trained in the distribution automation master station and deployed to the FTU to perform inference on the load time-series dataset, outputting load forecast curves for two set time periods of 1 hour and 3 hours in the future.

[0097] Numerical filtering is performed on the load forecast curves for two set time periods to extract the maximum load forecast value for the corresponding time period.

[0098] Specifically, this step generates the maximum load forecast value through three stages: time-series data preprocessing, hybrid model feature extraction and prediction, and prediction result screening. First, the collected line active power data is preprocessed, extracting valid data at 15-minute intervals from the past 24 hours. Outliers are removed using the 3σ criterion, and missing values ​​are filled in using linear interpolation to construct the load time-series dataset. The dataset is then normalized to extreme values, converting it into standardized data within the 0-1 interval, which serves as the input to the hybrid time-series prediction model. The normalization formula is:

[0099]

[0100] In the formula: The load data is normalized. This is the original active power sample value; This represents the minimum active power value within the time-series dataset. This represents the maximum active power value within the time-series dataset.

[0101] The TCN module extracts local abrupt changes and short-term variation patterns in the load data through causal convolution and residual connections. The causal convolution operation formula is as follows:

[0102]

[0103] In the formula: For the first The convolution output at time step; For the first The weights of each convolutional kernel; For the first Input data at any given time; This represents the kernel size.

[0104] Causal convolution ensures that the output depends only on the input data at the current time step and before, avoiding the leakage of future information. The TCN module deepens the network by stacking multiple residual blocks, while also solving the gradient vanishing problem in deep networks.

[0105] The BiLSTM module processes the local features of the TCN output from both forward and reverse directions, extracting long-range temporal dependencies and periodic variation patterns in the load data. The LSTM unit controls the transmission and updating of information through input gates, forget gates, and output gates. The calculation formula is as follows:

[0106]

[0107] In the formula: Output for the forget gate; Here is the forget gate weight matrix; This is the output of the hidden layer from the previous time step; Input features for the current time step; Forget gate bias term; It is the sigmoid activation function; For input gate output; The input gate weight matrix; For input gate bias terms; Candidate cell state; This is the candidate cell state weight matrix; This refers to the candidate cell state bias term; It is the hyperbolic tangent activation function; This represents the current state of the cell. This represents the cell state at the previous moment; Output gate output; This is the output gate weight matrix; This is the output gate bias term; This is the output of the hidden layer at the current moment.

[0108] BiLSTM concatenates the outputs of the forward and backward hidden layers to obtain a global feature vector containing bidirectional temporal information. The local features output by TCN are then concatenated and fused with the global features output by BiLSTM, and the resulting load forecasts for future timeframes are mapped through a fully connected layer. The hybrid model is trained offline on a distribution automation master station using historical load data from the past year. The core hyperparameters are set as follows: TCN kernel size of 3, residual block size of 2, and dilation coefficients of 1 and 2 respectively; BiLSTM hidden layer dimension of 64, with a bidirectional concatenation output dimension of 128; fully connected layer output dimension of 1; batch size of 32, training epochs of 100, Adam optimizer, and learning rate of 0.001. After training, the lightweight model weights and inference logic are deployed locally to the FTU. The FTU inputs preprocessed real-time load time-series data into the model and outputs 15-minute load forecast curves for two set time periods: 1 hour and 3 hours in advance.

[0109] The load forecast curves for the two time periods are numerically traversed and sorted, and the maximum value among all forecast values ​​in each time period is extracted as the maximum load forecast value for the corresponding time period.

[0110] Furthermore, in one embodiment of the present invention, the maximum load prediction value is corrected based on the real-time power flow direction and the real-time load data of adjacent primary and secondary fused pole-mounted circuit breakers to obtain a load warning judgment value adapted to the current power grid topology, including:

[0111] Match the corresponding preset power flow direction correction coefficient according to the direction of real-time power flow;

[0112] Calculate the adjacent load influence coefficient based on the real-time load data of adjacent primary and secondary fusion pole-mounted circuit breakers;

[0113] The load warning judgment value is calculated using a modified formula. The calculation formula is as follows:

[0114]

[0115] In the formula: This is the load warning judgment value; This represents the maximum predicted load. This is a power flow direction correction factor; This is the influence coefficient of adjacent loads.

[0116] Specifically, relying solely on the maximum load forecast obtained from the time-series forecasting model, without considering the real-time operating topology of the power grid and the load status of neighboring devices, can easily lead to a disconnect between the load warning judgment and the actual power grid carrying capacity. This step corrects the load warning judgment value by adjusting the coefficients based on both power flow direction and neighboring load dimensions, ensuring that the load warning judgment value accurately matches the current actual operating conditions of the power grid.

[0117] First, real-time power flow data of the integrated primary and secondary pole-mounted circuit breakers are collected, and a preset power flow correction coefficient is matched according to the direction of the power flow. When the power flow is positive (i.e., when electrical energy is transmitted from upstream to downstream), the power flow correction coefficient is set to 1.0, which is suitable for the load-bearing characteristics under normal power supply conditions. When the power flow is negative (i.e., when there is reverse power supply from distributed sources or line transfer), the power flow correction coefficient is set to 0.8, which is suitable for the increased line losses and decreased actual carrying capacity under reverse power supply conditions. The specific value of the power flow correction coefficient is determined through multi-condition power grid simulation and field operation data verification.

[0118] Simultaneously, real-time load data of upstream and downstream adjacent primary and secondary fusion pole-mounted circuit breakers directly connected to this circuit breaker are acquired, and the actual load rate of adjacent equipment is calculated, i.e., the ratio of the real-time load of adjacent equipment to the dynamic allowable load threshold of the equipment. The neighborhood load influence coefficient is determined based on the highest load rate of adjacent equipment: when the highest load rate of adjacent equipment is greater than 0.9, the neighborhood load influence coefficient is 0.85 to avoid overload of adjacent equipment due to load growth on this line; when the highest load rate of adjacent equipment is between 0.7 and 0.9, the neighborhood load influence coefficient is 0.95, appropriately lowering the warning threshold to reserve margin for grid operation; when the highest load rate of adjacent equipment is less than 0.7, the neighborhood load influence coefficient is 1.0, at which point the carrying capacity of adjacent equipment is sufficient, and there is no need to further lower the warning threshold. The graded values ​​of the neighborhood load influence coefficient are calibrated based on historical statistical data of grid cascading overload faults.

[0119] The maximum load forecast value is corrected by using a power flow correction coefficient and a neighboring load influence coefficient to calculate the load warning judgment value. Through this correction method, the load warning judgment value is no longer a fixed predicted value, but rather a result of dynamic adjustments based on the real-time grid topology and the status of neighboring equipment. This effectively reduces false alarms and missed alarms, improving the accuracy and practicality of load warnings from primary and secondary integrated pole-mounted circuit breakers.

[0120] S104: Compare the load warning judgment value with the dynamic allowable load threshold, determine the line load over-limit risk level based on the comparison result, and match the corresponding predictive load over-limit warning instruction.

[0121] Specifically, the FTU locally acquires the latest updated dynamic allowable load threshold and the corresponding load warning judgment value for future periods, and compares the two values ​​in real time. This comparison operation is performed every fifteen minutes, consistent with the update cycle of the dynamic allowable load threshold, ensuring that the risk assessment results are always synchronized with the real-time health status of the equipment and the operating conditions of the power grid. Based on the comparison result between the load warning judgment value and the dynamic allowable load threshold, the degree of load overrun risk for the line in future periods is determined, and a corresponding predictive load overrun warning command is output.

[0122] Furthermore, in one embodiment of the present invention, the risk level includes:

[0123] Level 1 Normal State: The load warning judgment value is less than 80% of the dynamic allowable load threshold, and the routine monitoring command is matched;

[0124] Level 2 warning risk: The load warning judgment value is greater than or equal to 80% and less than 90% of the dynamic allowable load threshold, which matches the yellow warning instruction;

[0125] Level 3 alarm risk: The load warning judgment value is greater than or equal to 90% of the dynamic allowable load threshold and less than 100%, which matches the orange alarm command;

[0126] Level 4 Emergency Risk: The load warning judgment value is greater than or equal to the dynamic allowable load threshold, matching the red emergency instruction.

[0127] Specifically, the risk level determination and instruction matching operation are executed locally by the FTU in real time. The determination result is updated synchronously with the dynamic allowable load threshold and load warning determination value to ensure the timeliness and accuracy of risk warning.

[0128] S105: Execute the corresponding local load control operation according to the load over-limit warning command, and upload the warning information, load-related data and control execution results to the distribution automation master station.

[0129] Furthermore, in one embodiment of the present invention, executing the corresponding local load control operation according to the load over-limit warning command includes:

[0130] When a routine monitoring command is received, the FTU maintains the original monitoring frequency and collects line load data every 15 minutes.

[0131] When a yellow alert is received, the FTU increases the data acquisition frequency to once every 5 minutes and simultaneously activates the reactive power compensation device to perform local voltage and current regulation.

[0132] When an orange alarm command is received, the FTU sends a load transfer request to the upstream or downstream adjacent circuit breaker through local edge communication and notifies the distribution automation master station to coordinate the tie switch to transfer the load. If there is no adjacent transferable path, the controllable load at the end of the line is requested to be cut off according to the preset priority.

[0133] When a red emergency command is received, the FTU first executes the load transfer operation of the orange alarm command. If the over-limit time exceeds the preset safe duration and there is no effective control means, the primary and secondary fusion pole-mounted circuit breakers are disconnected, and the audible and visual alarm device is triggered.

[0134] Specifically, the FTU receives predictive load overrun warning commands in real time and executes corresponding local load control operations precisely according to the command type. This enables graded intervention and precise handling of load overrun risks, ensuring the safe and stable operation of lines and equipment. Moreover, all control operations are completed locally by the FTU, without relying on remote control from the distribution automation master station, significantly improving the timeliness of control.

[0135] When a routine monitoring command is received, the FTU maintains the original preset monitoring frequency and collects core data related to line load at an interval of once every 15 minutes to ensure basic monitoring of the line's operating status. At the same time, it updates the equipment health and dynamic allowable load thresholds to provide data support for subsequent risk assessment.

[0136] Upon receiving a yellow alert, the FTU immediately adjusts its data acquisition strategy, increasing the frequency of line load data acquisition from once every 15 minutes to once every 5 minutes. This enables precise and real-time monitoring of load changes. Simultaneously, it activates the local reactive power compensation device to optimize line operation through voltage and current regulation, reduce line losses, enhance line load carrying capacity, and proactively mitigate the risk of further load increases.

[0137] Upon receiving an orange alarm command, the FTU, relying on its local edge communication module, quickly sends load transfer requests to adjacent primary and secondary fusion pole-mounted circuit breakers upstream and downstream, clearly providing key information such as the current load, predicted load, and transferable load capacity of the line. Simultaneously, it pushes alarm information and load transfer requests to the distribution automation master station, requesting the master station to coordinate cross-regional load transfer with all interconnecting switches across the network. If no load transfer confirmation is received from adjacent circuit breakers within the preset waiting time (30 seconds), and no valid transfer command is received from the master station, the system strictly follows the preset controllable load priority, sequentially requesting the disconnection of non-critical controllable loads at the end of the line until the load returns to a safe range. The preset controllable load priority is a pre-defined hierarchical ranking rule based on the power supply importance, outage impact range, and social impact of various loads, with priorities from low to high: Level 3 general loads, Level 2 critical loads, and Level 1 critical loads. Level 3 general loads include non-essential residential lighting and non-core commercial electricity use, which have the least impact from power outages. Level 2 critical loads include schools, commercial centers, and general industrial production electricity use, which would cause some economic losses or social impacts if outed. Level 1 critical loads include hospital operating rooms, fire protection systems, and communication base stations, which would endanger personal safety or cause significant social impacts if outed. Loads with lower priority are disconnected first, and Level 1 critical loads are only considered for disconnection in extreme emergency situations.

[0138] When a red emergency command is received, the FTU prioritizes executing all control operations corresponding to the orange alarm command, namely load transfer and controllable load shedding operations. If, after the above operations are completed, the line load still continues to exceed the dynamic allowable load threshold, and the duration of exceeding the limit reaches the preset safe duration (10 seconds), and there are no other effective control measures, the FTU immediately triggers the primary and secondary integrated pole-mounted circuit breaker to disconnect the faulty line. At the same time, it activates the on-site audible and visual alarm device to promptly remind maintenance personnel to arrive at the scene and handle the situation, minimizing the risk of the fault escalating.

[0139] Furthermore, in one embodiment of the present invention, uploading early warning information, load-related data, and control execution results to the distribution automation master station includes:

[0140] The warning level, warning time, dynamic allowable load threshold, maximum load forecast, control operation type and execution time data are uploaded to the distribution automation master station in real time through the power wireless private network.

[0141] After receiving the data, the main station generates a visual report that includes load change curves, risk evolution trends, and control recommendations.

[0142] The master station issues optimization control instructions based on the overall network load, and the FTU adjusts the local load control strategy after receiving the instructions.

[0143] Specifically, after receiving the data, the master station integrates the historical operating data of this line with the real-time uploaded data through its built-in data analysis module and visualization engine, generating a visualized report that includes load change curves, risk evolution trends, and control recommendations. Based on the real-time load status, equipment health status, and grid topology of all lines in the network, the master station performs global load optimization calculations, generates optimal control schemes covering multiple lines, and issues optimized control instructions to relevant FTUs.

[0144] The following will illustrate the load over-limit early warning method for primary and secondary integrated pole-mounted circuit breakers and FTUs through a specific embodiment, such as... Figure 2 As shown, it includes:

[0145] Taking a 10kV primary and secondary integrated pole-mounted circuit breaker installed in a mixed residential and commercial power supply area in a certain city's power distribution network as an example, the rated allowable load current of this circuit breaker is 1000A.

[0146] The FTU collects the three-phase current data of the integrated primary and secondary pole-mounted circuit breaker, which is 620A, through its built-in high-precision current transformer. It also collects the contact temperature data in real time (56℃) through a contact-type temperature sensor installed at the circuit breaker contacts. An environmental sensor integrated into the FTU housing collects the ambient temperature (28℃) and humidity (55%) at the circuit breaker installation site. The built-in mechanical characteristic detection unit collects the circuit breaker's opening and closing time (38ms), opening and closing speed (2.1m / s), and contact bounce time (1.8ms). All basic operating data are collected and stored at a basic frequency of once every 15 minutes. Simultaneously, the FTU obtains the active power data of the distribution line where the circuit breaker is located in real time (3.1MW) through the voltage and current acquisition circuit. The real-time power flow direction is positive, meaning that electrical energy is being transmitted normally from upstream to downstream. In addition, the FTU establishes a point-to-point low-latency communication link with the directly connected upstream and downstream adjacent primary and secondary fusion pole-mounted circuit breakers through the local edge communication module using LoRa wireless communication. It obtains the real-time active power of the upstream adjacent circuit breaker as 2.2MW and the dynamic allowable load threshold as 3.2MW, and calculates its load rate as 0.69. The downstream adjacent circuit breaker currently has no load connected, and its load rate is 0.

[0147] The FTU categorizes and organizes all collected multi-dimensional operational data, and comprehensively evaluates the circuit breaker's operating status from three core dimensions: electrical health, mechanical health, and environmental impact, according to pre-defined equipment health assessment rules. The analytic hierarchy process (AHP) is used to determine the influence weights of the three dimensions. First, a third-order judgment matrix is ​​constructed, and the importance of each dimension is compared pairwise. The importance ratio between electrical health and mechanical health is 2:1, between electrical health and environmental impact is 3:1, and between mechanical health and environmental impact is 2:1. The maximum eigenvalue of the judgment matrix is ​​calculated to be 3.009, and the corresponding eigenvector is normalized to obtain the initial weights for each dimension. A consistency check is performed, and the calculated consistency index (CI) is 0.0045, the random consistency index (RI) is 0.58, and the consistency ratio (CR) is 0.0078, all less than 0.1, indicating that the weight allocation is reasonable. The final weights for the three dimensions were determined as follows: electrical health 0.5, mechanical health 0.3, and environmental impact 0.2. The weights of the sub-indicators for each dimension were also determined through the analytic hierarchy process and statistical analysis of on-site operational data, specifically: three-phase current 0.6, contact temperature 0.4; opening and closing time 0.4, opening and closing speed 0.3, contact bounce time 0.3; ambient temperature 0.6, and ambient humidity 0.4. First, the extreme value standardization method was used to normalize all indicators. For inverse indicators where larger values ​​indicate worse equipment condition, the normalization formula was: The normalized score of the contact temperature was calculated. Three-phase current normalized score The formula for calculating the electrical health score is: The electrical health score was calculated. Similarly, the mechanical health score is obtained by applying the same normalization and weighting calculation method. Environmental impact score The formula for calculating the overall health score of equipment is as follows: The overall health score of the equipment was calculated. The formula for calculating the dynamic allowable load threshold is: The maximum load current that the circuit breaker can safely carry at present is calculated. .

[0148] The FTU extracts active power data for the past 24 hours at 15-minute intervals from locally stored historical operating data. It uses the 3σ criterion to remove outliers and linear interpolation to fill in missing data, constructing a complete load time-series dataset. This dataset is then input into the TCN-BiLSTM hybrid time-series forecasting model deployed locally on the FTU for inference. This model is pre-trained on the distribution automation master station using nearly a year's worth of historical load data for the region and, after lightweighting, deployed to the FTU. After inference, the model outputs load forecast curves for 15-minute intervals within two set time periods: 1 hour and 3 hours. The FTU iterates through and compares all values ​​on the two forecast curves to extract the maximum load forecast for the next hour. The maximum load forecast for the next 3 hours is 720A. Subsequently, the FTU combines the currently collected real-time power flow data with the real-time load data of adjacent circuit breakers to perform a double correction on the maximum load forecast. The formula for calculating the load warning judgment value is as follows: Wherein, the power flow direction is positive, and the matching power flow direction correction coefficient is used. The highest load rate of adjacent equipment is 0.69, which is less than 0.7, matching the neighboring load influence coefficient. The calculated load warning threshold for the next hour is determined. .

[0149] The FTU locally acquires the latest updated dynamic allowable load threshold of 872A and the corresponding load warning judgment value for the next hour of operation, 780A, and compares the two values ​​in real time. This comparison operation is performed every 15 minutes, consistent with the update cycle of the dynamic allowable load threshold and load warning judgment value. The calculated ratio of the load warning judgment value to the dynamic allowable load threshold is approximately 89.45%. According to the preset four-level load overload risk classification rules, 89.45% falls within the 80% to 90% range. Therefore, the FTU automatically determines the load overload risk level for this line in the next hour to be a level two warning risk and outputs the corresponding yellow warning command. The entire risk level determination and command matching process is completed locally by the FTU, without relying on remote calculation and control from the distribution automation master station.

[0150] Upon receiving a yellow alert, the FTU immediately executes the corresponding local load control operations. First, it increases the data collection frequency of line operation from once every 15 minutes to once every 5 minutes, strengthening the monitoring of load change trends. Simultaneously, it activates the local reactive power compensation device, automatically adjusting the compensation capacity using a stepped adjustment method to adjust the line power factor from 0.86 to the optimal range of 0.94, reducing line losses and improving the actual carrying capacity of the line. While executing the control operations, the FTU, according to the upload frequency corresponding to the level 2 alert status (once every 5 minutes), uploads data such as the alert level, alert trigger time, dynamic allowable load threshold (872A), maximum predicted load (780A), type of control operation executed, and start time of the control operation to the distribution automation master station in real time via the power wireless network. After receiving the data, the main station integrates the historical operating data of this line with the real-time uploaded data through the built-in data analysis module and visualization engine, and generates a visualization report that includes load change curves, risk evolution trends and control suggestions. It also performs global optimization calculations based on the overall network load operation status and issues optimization control instructions to the relevant FTUs. After receiving the instructions, the FTUs adjust their local load control strategies accordingly.

[0151] In summary, this embodiment fully and clearly demonstrates the entire execution process of the present invention, from multi-source heterogeneous data acquisition, multi-dimensional equipment health assessment, dynamic allowable load threshold calculation, edge-side load timing prediction and grid topology adaptation correction, local real-time risk level determination, to hierarchical and precise local load regulation. It fully reflects the core technological advantages of the present invention in achieving early warning and autonomous handling of load overloads by relying on the local edge computing capabilities of the FTU. Compared with traditional centralized load warning methods at master stations, the present invention effectively solves the problems of high warning delay, inaccurate fixed thresholds, and numerous false alarms and missed alarms due to the lack of consideration for the operating status of neighboring equipment in existing technologies. It can identify risks in advance and take targeted control measures before load overload faults occur, minimizing the probability of distribution line overload faults and significantly improving the safety, reliability, and intelligence level of distribution network operation.

[0152] The load over-limit early warning method for primary and secondary integrated pole-mounted circuit breakers and FTUs proposed in this invention has the following advantages compared with the prior art:

[0153] This invention can construct equipment health assessment rules based on the circuit breaker's own multi-dimensional operating data, and calculate a dynamic allowable load threshold that fits the actual current carrying capacity of the equipment, thus solving the problem of fixed and rigid thresholds in existing technologies.

[0154] This invention uses a pre-trained TCN-BiLSTM hybrid time-series prediction model for load inference, which can accurately extract the line load change trend, output load prediction results for multiple time periods, and improve the overall accuracy of load prediction.

[0155] This invention combines real-time power flow direction and real-time load data of adjacent circuit breakers to perform dual correction on the maximum load prediction value, thereby obtaining a load warning judgment value that is adapted to the current power grid topology and solving the problem of large deviation between the warning result and the actual operating condition.

[0156] This invention sets up a four-level load overload risk classification standard, which can match corresponding early warning instructions according to different risk levels and carry out differentiated load overload risk management;

[0157] This invention constructs a complete control system that includes edge early warning, hierarchical judgment, local control, and main station linkage. It can execute hierarchical local control operations based on early warning instructions, thus solving the problems of crude and lagging response in existing control technologies.

[0158] To achieve the above objectives, a second aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the above-described method for early warning of overload of a primary and secondary integrated pole-mounted circuit breaker and FTU.

[0159] In the description of this specification, references to the terms "an embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0160] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0161] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A load over-limit early warning method for primary and secondary integrated pole-mounted circuit breakers and FTUs, characterized in that, include: The FTU acquires data on the three-phase current, contact temperature, ambient temperature and humidity, and mechanical characteristics of opening and closing of the primary and secondary integrated pole-mounted circuit breaker, as well as the active power and real-time power flow data of the distribution line. It also acquires real-time load data of adjacent primary and secondary integrated pole-mounted circuit breakers through local edge communication. Based on the three-phase current, contact temperature, ambient temperature and humidity, and mechanical characteristics of opening and closing, the dynamic allowable load threshold corresponding to the primary and secondary integrated pole-mounted circuit breaker is calculated according to the preset equipment health assessment rules. Based on the active power data of the distribution lines, the load change trend of the lines is extracted, and a time-series prediction model is used to generate the maximum predicted load value for a future set period. The maximum predicted load value is then corrected based on the real-time power flow direction and the real-time load data of adjacent primary and secondary integrated pole-mounted circuit breakers to obtain a load warning judgment value adapted to the current power grid topology. Specifically, correcting the maximum predicted load value based on the real-time power flow direction and the real-time load data of adjacent primary and secondary integrated pole-mounted circuit breakers to obtain a load warning judgment value adapted to the current power grid topology includes: matching a corresponding preset power flow direction correction coefficient based on the direction of the real-time power flow; calculating the adjacent load influence coefficient based on the real-time load data of adjacent primary and secondary integrated pole-mounted circuit breakers; and calculating the load warning judgment value using a correction formula. The calculation formula is as follows: ； In the formula: This is the load warning judgment value; This represents the maximum predicted load. This is a power flow direction correction factor; The adjacent load influence coefficient is defined as follows: when the power flow direction is positive (i.e., when electrical energy is transmitted from upstream to downstream), the power flow direction correction coefficient is 1.0; when the power flow direction is reverse (i.e., when there is reverse power supply from distributed sources or line transfer), the power flow direction correction coefficient is 0.

8. The adjacent load influence coefficient is determined by calculating the actual load rate of adjacent equipment, which is the ratio of the real-time active power of adjacent equipment to the dynamic allowable load threshold of the equipment, based on the highest load rate of adjacent equipment. The load warning judgment value is compared with the dynamic allowable load threshold. Based on the comparison result, the risk level of line load exceeding the limit is determined, and the corresponding predictive load exceeding the limit warning instruction is matched. According to the load over-limit warning command, the corresponding local load control operation is executed, and the warning information, load-related data and control execution results are uploaded to the distribution automation master station.

2. The load over-limit early warning method for the primary and secondary integrated pole-mounted circuit breaker and FTU according to claim 1, characterized in that, Real-time load data of adjacent primary and secondary fusion pole-mounted circuit breakers is obtained through local edge communication, including: Real-time load data of upstream and downstream adjacent primary and secondary pole-mounted circuit breakers directly connected to this primary and secondary pole-mounted circuit breaker are obtained through LoRa or power line carrier communication. The real-time load data of the adjacent primary and secondary fusion pole-mounted circuit breakers includes real-time active power, dynamic allowable load threshold, and current equipment health score.

3. The load over-limit early warning method for the primary and secondary integrated pole-mounted circuit breaker and FTU according to claim 1, characterized in that, The step of calculating the current dynamic allowable load threshold of the primary and secondary integrated pole-mounted circuit breaker according to preset equipment health assessment rules includes: A multi-dimensional equipment health assessment index system is constructed, which is divided into electrical health dimension, mechanical health dimension and environmental impact dimension; The weights of the electrical health dimension, mechanical health dimension, and environmental impact dimension are determined using the analytic hierarchy process (AHP), and the overall equipment health score is calculated by weighted summation based on these weights. Based on the overall health score of the equipment and the rated allowable load current of the circuit breaker, the current dynamic allowable load threshold is calculated using the dynamic threshold correction formula.

4. The load over-limit early warning method for the primary and secondary integrated pole-mounted circuit breaker and FTU according to claim 3, characterized in that, The dynamic threshold correction formula is: ； In the formula: This is a dynamic allowable load threshold; This refers to the rated allowable load current of the circuit breaker. The overall health score of the equipment ranges from 0 to 1.

5. The load over-limit early warning method for the primary and secondary integrated pole-mounted circuit breaker and FTU according to claim 1, characterized in that, Based on the active power data of the distribution lines, the load change trend of the lines is extracted, and a time-series forecast model is used to generate the maximum load forecast for a future set period, including: Extract the active power data of the line at 15-minute intervals over the past 24 hours to construct a load time series dataset; The TCN-BiLSTM hybrid time-series forecasting model is trained in the distribution automation master station and deployed to the FTU to perform inference on the load time-series dataset, outputting load forecast curves for two set time periods of 1 hour and 3 hours in the future. The load forecast curves for the two set time periods are numerically filtered to extract the maximum load forecast value for the corresponding time period.

6. The load over-limit early warning method for the primary and secondary integrated pole-mounted circuit breaker and FTU according to claim 1, characterized in that, The risk levels include: Level 1 Normal State: The load warning judgment value is less than 80% of the dynamic allowable load threshold, and the routine monitoring command is matched; Level 2 warning risk: The load warning judgment value is greater than or equal to 80% and less than 90% of the dynamic allowable load threshold, which matches the yellow warning instruction; Level 3 alarm risk: The load warning judgment value is greater than or equal to 90% of the dynamic allowable load threshold and less than 100%, which matches the orange alarm command; Level 4 Emergency Risk: The load warning judgment value is greater than or equal to the dynamic allowable load threshold, matching the red emergency instruction.

7. The load over-limit early warning method for the primary and secondary integrated pole-mounted circuit breaker and FTU according to claim 6, characterized in that, Execute the corresponding local load control operation according to the load over-limit early warning command, including: When a routine monitoring command is received, the FTU maintains the original monitoring frequency and collects line load data every 15 minutes. When a yellow alert is received, the FTU increases the data acquisition frequency to once every 5 minutes and simultaneously activates the reactive power compensation device to perform local voltage and current regulation. When an orange alarm command is received, the FTU sends a load transfer request to the upstream or downstream adjacent circuit breaker through local edge communication and notifies the distribution automation master station to coordinate the tie switch to transfer the load. If there is no adjacent transferable path, the controllable load at the end of the line is requested to be cut off according to the preset priority. When a red emergency command is received, the FTU first executes the load transfer operation of the orange alarm command. If the over-limit time exceeds the preset safe duration and there is no effective control means, the primary and secondary fusion pole-mounted circuit breakers are disconnected, and the audible and visual alarm device is triggered.

8. The load over-limit early warning method for the primary and secondary integrated pole-mounted circuit breaker and FTU according to claim 1, characterized in that: Upload early warning information, load-related data, and control execution results to the distribution automation master station, including: The warning level, warning time, dynamic allowable load threshold, maximum load forecast, control operation type and execution time data are uploaded to the distribution automation master station in real time through the power wireless private network. After receiving the data, the main station generates a visual report that includes load change curves, risk evolution trends, and control recommendations. The master station issues optimization control instructions based on the overall network load, and the FTU adjusts the local load control strategy after receiving the instructions.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When a computer program or instruction is executed, it implements the load over-limit warning method for a primary and secondary integrated pole-mounted circuit breaker and FTU as described in any one of claims 1-8.

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