Control method and system for realizing low-frequency load shedding of user branch load through cooperation of terminal and master station

Abstract

The invention belongs to the technical field of power system protection control and user side load management, and particularly relates to a control method and system for achieving user branch load low-frequency load shedding through cooperation of a terminal and a master station. The method comprises the steps of main station side low-frequency load shedding research and judgment and strategy control; performing real-time frequency monitoring and load shedding strategy execution on the terminal side; and load shedding strategy optimization and regulation and control effect analysis are completed at the main station side. According to the method, traditional substation low-frequency load shedding management is advanced and applied to user branch load monitoring control, low-frequency load shedding management monitoring of a third defense line of a power grid is more advanced, load shedding is more timely, management and control are more accurate, the influence of system frequency characteristic deterioration caused by large-scale new energy grid connection and terminal electrification can be effectively restrained, and the system reliability is improved. The defects of low-frequency load shedding of a traditional transformer substation are overcome, the safety lean management level of a power grid is improved, the production influence and economic loss of users are reduced to the maximum extent, and rapid development of new energy and terminal electrification application and popularization are served.

Description

Technical Field

[0001] This invention belongs to the field of power system protection and control and user-side load management technology, and particularly relates to a control method and system for achieving low-frequency load shedding of user branch loads in collaboration between the terminal and the master station. Background Technology

[0002] With the large-scale development of grid-connected power generation and terminal electrification of high-proportion renewable energy, on the one hand, the high proportion of new energy grid connection leads to a reduction in the rotational inertia of the power system, resulting in a deterioration of the system frequency characteristics due to system disturbances, which shows a bottom-up spreading trend; on the other hand, traditional substation low-frequency load shedding schemes generally adopt the method of cutting off feeder loads, which often leads to over-cutting or under-cutting, resulting in many controversies and irrationalities such as the risk of equipment damage, impact on industrial production, and economic losses.

[0003] Therefore, continuous research and development and technological updates are urgently needed to address the aforementioned existing technological problems. Summary of the Invention

[0004] To address the shortcomings of the existing technologies, this invention provides a control method and system for achieving low-frequency load shedding of user branch circuits through collaboration between the terminal and the master station. The purpose of this invention is to solve the problems of the deterioration of system frequency characteristics caused by large-scale grid connection of new energy sources and terminal electrification, as well as the deficiencies of traditional substation low-frequency load shedding.

[0005] The technical solution adopted by the present invention to achieve the above objectives is as follows: A control method for achieving low-frequency load shedding of user branch lines through collaboration between a terminal and a master station includes: Analysis and strategy control of low-frequency load reduction at the main station; Real-time frequency monitoring and load reduction strategy execution on the terminal side; The load reduction strategy optimization and control effect analysis were completed on the main station side.

[0006] Furthermore, the low-frequency load shedding analysis and strategy control on the main station side includes multi-source data acquisition and preprocessing for panoramic monitoring, frequency anomaly detection and demand calculation for load shedding analysis, strategy generation and three-level verification; low-frequency load shedding application is realized based on a new power load management system, and based on data such as the controllable resource list of user branch loads and the low-frequency load shedding setpoint of substations, panoramic monitoring, load shedding analysis and strategy control of user branch load low-frequency load are realized, and the pre-analyzed low-frequency load shedding strategy is downloaded to the smart energy unit terminal.

[0007] Furthermore, the panoramic monitoring of low-frequency load reduction of user branch includes: real-time acquisition of multi-source data, data preprocessing, and multi-dimensional status display.

[0008] The load reduction assessment includes: frequency anomaly detection, load status evaluation, and load reduction demand calculation; The low-frequency load reduction strategy includes: load reduction strategy generation, load reduction strategy verification, and strategy download to the terminal.

[0009] Furthermore, the real-time frequency monitoring and load reduction strategy execution on the terminal side includes zero-crossing periodic frequency measurement using edge computing, anomaly detection based on round thresholds, and priority-based load shedding control. Utilizing the local edge computing capabilities of the terminal, the system monitors changes in the load frequency of user branches in real time, responds quickly when frequency anomalies occur, controls the load shedding of user branches according to the pre-installed low-frequency load reduction strategy, and sends alarm information and action events to the main station system in real time.

[0010] Furthermore, the edge computing on the terminal side is based on embedded hardware and a lightweight real-time operating system, integrating a data acquisition module, a real-time analysis module, a strategy execution module, and a communication module; the local storage unit pre-stores low-frequency load reduction strategy parameters and supports dynamic policy updates; The real-time monitoring of user branch load frequency changes includes: (1) Monitoring objects: 10kV / 0.4kV distribution network branches connected to users, and three-phase voltage / current signals are collected through the built-in voltage transformer TV and current transformer TA in the terminal; (2) Sampling parameters: voltage signal, current signal, sampling frequency 2kHz, one set of data is collected every 10ms; (3) Frequency calculation: Based on the voltage zero-crossing period measurement method, by capturing the time difference Δt (unit ms) of three consecutive zero-crossing points, the period T=2Δt and the frequency f=1000 / T (Hz) are calculated; the average frequency within 1 second is calculated once every 100ms and used as the real-time monitoring frequency f_meas; (4) Auxiliary monitoring: Synchronously calculate the frequency drop rate df / dt=(f_meas(k)-f_meas(k-1)) / Δt_s; Δt_s=0.1s, k is the current sampling time, used to determine the severity of the accident; The user branch load shedding control includes: Step (1) Pre-install strategy content: The main station pre-installs the parameters of each branch, priority L_i and total load shedding ΔP_n for each round, n=1,2,3 rounds; Step (2) Trigger judgment: Real-time monitoring shows that f_meas≤f_set and df / dt≥threshold value. If the frequency does not rise back to the blocking value within the delay t_delay, the nth round of load reduction is triggered. Step (3) Selecting load-cutting branches: Sort the branches in order of priority L_i=5→4→3, and cumulatively cut off the load ΣP_i until ΣP_i≥ΔP_n. Select the first m branches that meet the condition for the first time. If the last branch is partially cut off, calculate the required cutting ratio according to ΔP_n-ΣP_n (m-1) and control the smart switch to open to the corresponding load. Step (4) Execution control: The terminal sends a trip command to the branch intelligent switch through the RS485 / PLC communication interface, driving the built-in relay of the switch to act; at the same time, hardware anti-bounce is activated; Step (5) Event recording and uploading: Record the action time, trigger round, cut branch number / load, and frequency values ​​before and after the action, and upload them to the master station in real time via 4G / NB-IoT; The calculations include: Frequency calculation: The sampling voltage zero-crossing times are t1=10.0ms, t2=20.2ms, t3=30.3ms → period T=2×20.2-10.0=20.4ms → f=1000 / 20.4≈49.02Hz, which meets the conditions for starting a round; df / dt calculation: when t=1.0s, f_meas=49.2Hz, when t=1.1s, f_meas=48.9Hz → df / dt=48.9-49.2 / 0.1=-3.0Hz / s, which satisfies df / dt≥-0.5Hz / s for 1 round;

[0011] Load shedding calculation: 1 round ΔP_n=1000kW, pre-installed branch P1=300kW (L=5), P2=400kW (L=5), P3=350kW (L=4) → cumulative P1+P2=700kW<1000kW, P1+P2+P3=1050kW≥1000kW → disconnect P1, P2, P3, partially disconnect 50kW, that is, 50 / 350≈14% of the load of P3 is disconnected.

[0012] Furthermore, the optimization of load shedding strategies and analysis of control effects at the main station side include deviation analysis algorithm evaluation, dynamic correction of load shedding amount by PID regulation, and optimization of user priority by AHP algorithm; based on user-side power grid monitoring data, load shedding strategies, and action reports, the low-frequency load shedding effect analysis is completed, the low-frequency load shedding strategy is optimized, and the load shedding amount, user priority and load shedding ratio, and user branch control sequence of the low-frequency load shedding strategy are comprehensively adjusted to optimize the accuracy of low-frequency load shedding action and minimize the impact of low-frequency load shedding on the user range.

[0013] Furthermore, the low-frequency load shedding effect analysis process is as follows: Based on user-side power grid monitoring data, load shedding strategies, and action reports, a deviation analysis algorithm is used to calculate the deviation rate between the actual load shedding amount and the theoretical value, where the deviation rate = |actual load shedding amount - theoretical load shedding amount| / theoretical load shedding amount × 100%. The load shedding effect is evaluated in conjunction with the frequency recovery time. When the deviation rate > 5% or the recovery time > 10 seconds, it is determined that the load shedding effect is not up to standard. The optimization of the low-frequency load reduction strategy includes: ① Load shedding optimization: Based on the deviation analysis results, the load shedding is dynamically corrected using a PID control algorithm, where the correction value = theoretical load shedding × (1 - deviation rate × control coefficient). ② User priority and load shedding ratio optimization: Based on user production characteristics, security load ratio and historical action impact, user priority is reordered using the analytic hierarchy process (AHP) and load shedding ratio is adjusted to reduce the load shedding ratio of high-priority users by 5%-10%; where, security load ratio = security load amount / total load amount × 100%, and historical action impact amount = economic loss assessment value / total user load. ③ Control sequence optimization: Based on the user branch load pull sequence table, a greedy algorithm is used to adjust the control sequence, prioritizing the cutting of non-critical production branches.

[0014] A control system for achieving low-frequency load reduction of user branch circuits through collaboration between terminals and a master station includes a master station-side low-frequency load reduction application and a terminal-side low-frequency load reduction app. The low-frequency load shedding application on the main station side is used for analysis and strategy control; it has functions such as panoramic monitoring, abnormal alarm, load shedding analysis, strategy management, action briefing, and statistical analysis; the system gathers information such as regional power grid model information, user load cycles and monitoring information, load shedding action reports and analysis information, etc., to realize real-time monitoring and abnormal early warning of regional user branch load levels, and performs comprehensive analysis and judgment in combination with dispatching low-frequency load shedding schemes and settings, accurately calculates user load shedding amount and branch control cycles, intelligently generates low-frequency load shedding strategies and supports rolling optimization and arrangement, and supports remote downloading of strategies to user-side smart energy units; The terminal-side low-frequency load shedding App is used for real-time frequency monitoring and load shedding strategy execution; it has functions such as load monitoring, intelligent alarm, strategy execution, action recording, and parameter management; it utilizes the edge computing capabilities of the smart energy unit to monitor the load level of user branches in real time, performs setpoint comparison and protection blocking judgment based on the local low-frequency load shedding strategy and parameters, and triggers low-frequency load shedding protection action when an abnormal grid frequency is detected on the user side. When the protection action is triggered, an event alarm is generated, and an action record report is stored. The alarm event, action event, and action report are uploaded to the main station system in real time.

[0015] A computer device includes a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor. When the processor executes the computer program, it implements the steps of a control method for low-frequency load shedding of a user branch line in collaboration between a terminal and a master station, as described in any one of the claims.

[0016] A computer storage medium storing a computer program, wherein when the computer program is executed by a processor, the steps of the control method for low-frequency load shedding of a user branch in collaboration between a terminal and a master station, as described in any one of the above, are implemented.

[0017] The present invention has the following beneficial effects and advantages: This invention, combined with the steady progress of the construction of a new power load management system, continuously improves the precise control capability of user branch loads. The smart energy unit terminal installed on the user side features intelligent and interactive technologies, fully leveraging the terminal's edge computing and local control capabilities. It moves the traditional substation low-frequency load shedding management forward to real-time monitoring and control of user branch loads, enabling "more proactive monitoring, more timely load shedding, and more precise control" in the third line of defense for the power grid's low-frequency load shedding management. This further enhances the stability of system frequency and the safety of power grid operation, improving the level of lean and efficient power grid safety management.

[0018] This invention proposes an interactive process and implementation mechanism for low-frequency load shedding management of user branch circuits through collaboration between terminals and the master station. It clarifies the system architecture, application functions, and technical routes of the master station-side system and the terminal-side system. This invention moves the traditional substation low-frequency load shedding management forward to user branch circuit load monitoring and control, enabling more proactive monitoring, more timely load shedding, and more precise control of low-frequency load shedding—the third line of defense for the power grid. This effectively suppresses the deterioration of system frequency characteristics caused by large-scale renewable energy grid connection and terminal electrification, compensates for the shortcomings of traditional substation low-frequency load shedding, improves the level of lean management of power grid safety, minimizes the impact on user production and economic losses, and serves the rapid development of renewable energy and the promotion and application of terminal electrification.

[0019] The specific component added in this invention is the user-side smart energy unit terminal, which integrates a sensing layer (voltage / current transformer), an edge computing layer (ARM Cortex-A processor and FreeRTOS system), an application layer (local control module), and a communication layer (4G / NB-IoT interface) to realize real-time data acquisition of user branches, local policy execution, and collaborative control with the master station.

[0020] Compared with existing technologies, this invention moves load shedding management to the user branch through a terminal-master station collaboration mechanism, improving load shedding accuracy with a deviation rate of ≤5%; shortening response time to ≤0.5s; reducing the impact on critical loads by more than 30%; and solving the problem of over-shearing / under-shearing in traditional substations. Attached Figure Description

[0021] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart illustrating the overall process of achieving low-frequency load reduction of user branch lines through master station-terminal collaboration in this invention. Figure 2 This is a functional diagram of the system for low-frequency load shedding of user branch lines through master station-terminal collaboration according to the present invention; Figure 3 This is a flowchart of the process for implementing low-frequency load reduction of user branch lines through master station-terminal collaboration in this invention; Figure 4 This is a schematic diagram of the low-frequency load reduction application system architecture on the main station side of this invention; Figure 5 This is a schematic diagram of the terminal-side low-frequency load reduction App system architecture of the present invention. Detailed Implementation

[0022] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other.

[0023] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0024] The following reference Figures 1-5 The technical solutions of some embodiments of the present invention are described below.

[0025] Example 1

[0026] This invention provides an embodiment of a control method for low-frequency load shedding of user branch lines through collaboration between a terminal and a master station. For example... Figure 1 As shown, Figure 1 This is a flowchart of the overall process of achieving low-frequency load reduction through master station-terminal collaboration in this invention.

[0027] This invention is achieved collaboratively by a cloud-based master station system and user-side smart energy unit terminals. Based on information such as controllable load lists and low-frequency load reduction settings, the master station performs low-frequency load reduction analysis and strategy formulation management. After security verification, the low-frequency load reduction strategy is remotely downloaded to the user-side smart energy unit terminal. Utilizing the terminal's edge computing and local control capabilities, real-time frequency monitoring and load reduction strategy execution are performed, and monitoring data and alarm events are reported in real time. The master station analyzes the control effect and continuously optimizes the load reduction strategy, updating and downloading the updated strategy to the smart energy unit. The master station system is the low-frequency load reduction application, and the smart energy unit terminal is the low-frequency load reduction app.

[0028] This invention discloses a control method for low-frequency load shedding of user branch circuits through collaboration between a terminal and a master station. The method comprises three stages: low-frequency load shedding control, low-frequency load shedding execution, and low-frequency load shedding analysis. It is achieved collaboratively by a master station system deployed in the cloud and a smart energy unit terminal deployed on the user side. Specifically, it includes the following steps: Step 1. Analysis and strategy control of low-frequency load reduction on the main station side.

[0029] It includes multi-source data acquisition and preprocessing for panoramic monitoring, frequency anomaly detection and demand calculation for load reduction assessment, strategy generation and three-level verification.

[0030] The low-frequency load reduction application is realized based on the new power load management system. According to the user branch load controllable resource list, substation low-frequency load reduction setting and other data, the system realizes panoramic monitoring, load reduction analysis and strategy control of user branch load low-frequency load reduction, and downloads the low-frequency load reduction strategy generated in advance to the smart energy unit terminal.

[0031] The panoramic monitoring of low-frequency load shedding on user branch lines is achieved through the following steps:

[0032] Step (1) Real-time acquisition of multi-source data.

[0033] The following data was collected through the interface of the new power load management system: a) Real-time frequency of the substation busbar; Data collection target: busbars of 110kV and above substations; sampling frequency: 10Hz; b) Real-time load data of user branch lines.

[0034] Data collected: Current and voltage at the incoming switches of each user, and active power P_i calculated, where i is the user branch number; sampling frequency: 5Hz; c) User branch controllable resource status data.

[0035] Data collected: Operating status of controllable load equipment uploaded by the user-side smart energy unit terminal, such as the status of interruptible load switches and energy storage charging and discharging power; Sampling frequency: 1Hz; d) Low-frequency load shedding setting parameters for substations.

[0036] The data is obtained from the substation EMS system, including the low-frequency load shedding threshold value f_set, the delay t_set, and the rated total load shedding capacity P_set.

[0037] The threshold value f_set for low-frequency load shedding is, for example, 49.5Hz.

[0038] The delay t_set is, for example, 0.5s.

[0039] Step (2) Data preprocessing.

[0040] Perform the following operations on the collected data: a) The moving average filtering method is used to filter the bus frequency and user branch load data to eliminate high-frequency noise; The moving average filtering method refers to a window size of 5 sampling points.

[0041] b) Remove outliers using the 3σ criterion; If the load data exceeds 1.2 times its historical maximum load, it is marked as abnormal and replaced with the average of the first 3 sampling points; c) Convert the controllable resource status data of the user branch into binary status codes and the maximum reducible capacity value Qi (unit: kW).

[0042] The binary status code is: 1 - available, 0 - unavailable.

[0043] The maximum reducible capacity value Q_i is obtained by matching from the list of controllable resources for user branch loads.

[0044] Step (3) Multi-dimensional status display.

[0045] Generate a panoramic monitoring view in the system interface: a) Frequency trend chart; The bus frequency f(t) is displayed in real time, and the low-frequency load shedding threshold value f_set is marked. b) User branch load heat map; Arranged by user branch number, the ratio of real-time load P_i to rated load P_i is represented by color intensity: >0.8 is marked in red, 0.5-0.8 is marked in yellow, and <0.5 is marked in green. c) List of controllable resource statuses; Displays the Q_i of each user branch and its availability status, highlighting the branch with an availability status of 1.

[0046] The specific steps for implementing the load reduction judgment for low-frequency load reduction of user branch lines are as follows: Step (1) Frequency anomaly detection.

[0047] Real-time monitoring of the pre-processed bus frequency f(t) is performed. When f(t) < f_set and the duration is ≥ t_set, such as 0.5s, it is determined to be a frequency anomaly, triggering the load reduction assessment process.

[0048] Step (2) Load status assessment.

[0049] Calculate the load status index S_i = P_i / P_i rated (i=1,2,...,n, where n is the total number of user branches) for all user branches, and filter out user branches with S_i > 0.3, that is, the current load exceeds the rated load by 30% and the controllable resource status is 1, to form the "candidate load reduction branch set U".

[0050] Step (3) Calculate the load reduction requirement.

[0051] Calculate the required load reduction ΔP_req based on the frequency deviation: ΔP_req = K × (f s et-f(t))×S_base In the formula: K is the system frequency regulation coefficient, which takes a value of 0.5-1.0 MW / Hz and is preset according to the regional power grid inertial parameters; S_base is the base power (unit MW) of the substation power supply area, which is obtained from the substation parameter table.

[0052] The specific steps for implementing the strategy control to reduce low-frequency load on user branch lines are as follows: Step (1) Generate load reduction strategy.

[0053] For the user branches in the candidate load reduction branch set U, sort and select them according to the following rules: a) Priority 1: Sort in ascending order of "importance level"; Importance levels are obtained from the user's list of controllable resources on the branch: Level 1 - normal load, Level 2 - important load, with Level 1 being the preferred choice. b) Priority 2: Within the same level, sorted in ascending order by "response time per unit capacity"; Response time is obtained from the user branch's controllable resource list, with shorter response times receiving higher priority. c) Select user branches in order of sorting, and accumulate their Q_i until the accumulated value is ≥ ΔP_req. Generate a "preliminary load reduction strategy", which includes the branch number i and the corresponding load reduction amount q_i, where q_i ≤ Q_i.

[0054] Step (2) Load reduction strategy verification.

[0055] Perform the following verifications on the initial load reduction strategy: a) Total load reduction check: ∑q_i ≥ ΔP_req. If not satisfied, return to step (1) to reselect and add a low-priority branch. b) Single branch upper limit check: For any i, q_i ≤ Q_i. If there exists q_i > Q_i, correct it to q_i = Q_i and select the next branch. c) Important load protection verification: Remove user branches with importance level 3 or above. If the wrong branch is selected, select another branch of the same priority.

[0056] Step (3) Download the strategy to the terminal.

[0057] The verified load reduction strategy, including branch number i, load reduction amount q_i, and execution time t_exec = current time + 0.2s, is converted into JSON format and sent to the smart energy unit terminal of the corresponding user branch through the power dispatch data network using the IEC 61850 protocol. At the same time, the strategy sending timestamp and terminal receiving receipt are recorded.

[0058] The parameters involved in the above steps, such as f_set=49.5Hz, t_set=0.5s, K=0.5 MW / Hz, can be adjusted according to the actual power grid requirements. The specific values ​​are preset through the configuration interface during system deployment.

[0059] Step 2. Real-time frequency monitoring and load reduction strategy execution on the terminal side.

[0060] It includes zero-crossing periodic frequency measurement based on edge computing, anomaly detection based on round threshold, and priority-based load shedding control.

[0061] Utilizing the local edge computing capabilities of the terminal, the system monitors the frequency changes of user branch loads in real time, responds quickly when frequency anomalies occur, controls the load shedding of user branches according to the pre-installed low-frequency load reduction strategy, and sends alarm information and action events to the main station system in real time. The edge computing is implemented as follows: The terminal-side edge computing is based on embedded hardware and a lightweight real-time operating system, integrating a data acquisition module, a real-time analysis module, a policy execution module, and a communication module. Local storage units pre-store low-frequency load reduction policy parameters, supporting dynamic policy updates.

[0062] This includes embedded hardware, such as ARM Cortex-A series processors; and lightweight real-time operating systems, such as FreeRTOS.

[0063] Local storage units, such as Flash / SD cards; low-frequency load shedding strategy parameters, such as frequency thresholds for each round, latency, load shedding priority, and branch load baseline values; dynamic policy updates, including configuration via remote distribution from the main station or local debugging interfaces.

[0064] (1) Monitoring objects: 10kV / 0.4kV distribution network branches connected to the user, and three-phase voltage / current signals are collected through the built-in voltage transformer TV and current transformer TA in the terminal.

[0065] (2) Sampling parameters: voltage signal (RMS value, zero crossing time), current signal (RMS value), sampling frequency 2kHz, one set of data is collected every 10ms.

[0066] (3) Frequency calculation: Based on the voltage zero-crossing period measurement method, the period T = 2Δt and the frequency f = 1000 / T (Hz) are calculated by capturing the time difference Δt (unit ms) of three consecutive zero-crossing points; the average frequency within 1 second is calculated once every 100ms (the average of 10 sampling points is taken) as the real-time monitoring frequency f_meas.

[0067] (4) Auxiliary monitoring: Synchronously calculate the frequency drop rate df / dt=(f_meas(k)-f_meas(k-1)) / Δt_s(Δt_s=0.1s; k is the current sampling time, used to determine the severity of the accident.

[0068] Based on the pre-installation strategy, exceptions are defined in three rounds, including startup thresholds and locking conditions:

[0069] Step (1) Pre-installation strategy content: The main station pre-installs the parameters of each branch, including branch number, load type, real-time load P_i (kW), priority L_i (level 1-5, level 5 is the lowest) and total load shedding ΔP_n for each round, n=1,2,3 rounds.

[0070] Step (2) Trigger judgment: Real-time monitoring shows that f_meas≤f_set and df / dt≥threshold value. If the frequency does not rise back to the blocking value within the delay t_delay, the nth round of load reduction is triggered.

[0071] Step (3) Selecting load-cutting branches: Sort the branches in order of priority L_i=5→4→3, and cumulatively cut off the load ΣP_i until ΣP_i≥ΔP_n. Select the first m branches whose cumulative value first meets the condition. If the last branch is partially cut off, calculate the required cutting ratio according to ΔP_n-ΣP_n (m-1) and control the smart switch to open to the corresponding load.

[0072] Step (4) Execution control: The terminal sends a trip command to the branch intelligent switch through the RS485 / PLC communication interface, including the branch number and trip time, and drives the built-in relay of the switch to act; at the same time, hardware anti-bounce is activated (no repeated action within 200ms).

[0073] Step (5) Event Recording and Uploading: Record the action time (accurate to milliseconds), trigger round, cut branch number / load, and frequency values ​​before and after the action, and upload it to the master station in real time via 4G / NB-IoT. Data format: JSON, including timestamp, terminal ID, event type "low-frequency load reduction action", and detailed parameters.

[0074] The key calculation example is as follows: Frequency calculation: The sampling voltage crosses zero at times t1=10.0ms, t2=20.2ms, t3=30.3ms → Period T=2×20.2-10.0=20.4ms → f=1000 / 20.4≈49.02Hz, which meets the conditions for starting a round.

[0075] df / dt calculation: when t=1.0s, f_meas=49.2Hz, when t=1.1s, f_meas=48.9Hz → df / dt=48.9-49.2 / 0.1=-3.0Hz / s, which satisfies df / dt≥-0.5Hz / s for 1 round.

[0076] Load shedding calculation: 1 round ΔP_n=1000kW, pre-installed branch P1=300kW (L=5), P2=400kW (L=5), P3=350kW (L=4) → cumulative P1+P2=700kW<1000kW, P1+P2+P3=1050kW≥1000kW → disconnect P1, P2, P3, partially disconnect 50kW, that is, 50 / 350≈14% of the load of P3 is disconnected.

[0077] Step 3. Optimize the load reduction strategy and analyze the control effect on the main station side.

[0078] It includes deviation analysis algorithm evaluation, PID control for dynamic correction of load shedding, and AHP algorithm for optimizing user priority.

[0079] Based on user-side power grid monitoring data, load shedding strategies, and action reports, we completed the analysis of low-frequency load shedding effects, optimized the low-frequency load shedding strategy, and comprehensively adjusted the load shedding amount, user priority and load shedding ratio, and user branch control sequence of the low-frequency load shedding strategy to optimize the accuracy of low-frequency load shedding actions and minimize the impact of low-frequency load shedding on the user range.

[0080] The specific implementation process is as follows: (1) Analysis process of low-frequency load shedding effect: Based on the user-side power grid monitoring data (frequency recovery curve, actual load shedding value), load shedding strategy (preset load shedding amount, priority) and action briefing (action time, user impact range), the deviation analysis algorithm is used to calculate the deviation rate between the actual load shedding amount and the theoretical value (deviation rate = |actual load shedding amount - theoretical load shedding amount| / theoretical load shedding amount × 100%), and the load shedding effect is evaluated in combination with the frequency recovery time (the time from frequency abnormality to recovery to 49.5Hz). When the deviation rate > 5% or the recovery time > 10 seconds, it is determined that the load shedding effect is not up to standard.

[0081] (2) The optimization process for the low-frequency load reduction strategy includes: ① Load shedding optimization: Based on the deviation analysis results, the load shedding is dynamically corrected using a PID control algorithm (correction value = theoretical load shedding × (1 - deviation rate × control coefficient)). ② User priority and load shedding ratio optimization: Based on user production characteristics (continuous production / intermittent production), security load ratio (security load ratio = security load amount / total load amount × 100%) and historical action impact (impact amount = economic loss assessment value / total user load amount), the user priority is re-ranked using the analytic hierarchy process (AHP), and the load shedding ratio is adjusted (the load shedding ratio of high-priority users is reduced by 5%-10%). ③ Control sequence optimization: Based on the generated user branch load order table (derived from the user's controllable resource list), a greedy algorithm is used to adjust the control sequence, prioritizing the cutting of non-critical production branches.

[0082] (3) Reference Notes: The above parameters are all derived from the "List of Controllable Resources for User Branch Load" and the "Load Reduction Strategy Formulation" in Step 1. Among them, the load shedding amount, user priority and load shedding ratio are initially configured in the "Strategy Control" stage of Step 1, and the user branch control sequence is specified in the "Road Pulling Sequence Table" generated in Step 1. This step realizes the iterative update of parameters through dynamic optimization algorithm.

[0083] The specific sources and optimization process of the comprehensive tuning parameters are as follows: 1. Load shedding amount: It originates from the theoretical load reduction amount ΔP_req calculated in the strategy control stage in step 1. In this step, it is dynamically corrected by the PID adjustment algorithm (proportional coefficient Kp=0.8, integral coefficient Ki=0.2, derivative coefficient Kd=0.1). The adjustment coefficient in the correction formula is dynamically configured according to the grid inertia parameter, and the value range is 0.1-0.3. 2. User Priority and Load Shedding Ratio: The initial priority is obtained from the "Importance Level" field (levels 1-5) in the user branch controllable resource list in step 1. The load shedding ratio is preset according to the "Interruptible Load Ratio" in the list, such as 80% for Class III load and 50% for Class II load. This step uses the AHP algorithm to construct a judgment matrix for re-sorting. The judgment matrix constructed by the AHP algorithm includes a production continuity weight of 0.4, a security load ratio weight of 0.3, and a historical impact weight of 0.3. 3. User Branch Control Sequence: The initial sequence is obtained from the "Route Sequence Table" generated in step 1. This step uses a greedy algorithm (objective function: minimize the impact of critical loads) to adjust the sequence, selecting the branch with the lowest impact in each iteration and adding it to the control sequence. Combined with... Figure 1 As shown, after the master station completes the above parameter tuning in the "Policy Optimization" module, it synchronizes the policy to the terminal through the "Policy Distribution" link to form a closed-loop control.

[0084] Example 2 This invention provides another embodiment, which is a control system for low-frequency load shedding of user branch lines through collaboration between the terminal and the master station, such as... Figure 3 As shown, Figure 3 This is a flowchart of the process for achieving low-frequency load reduction of user branch lines through master station-terminal collaboration in this invention.

[0085] This invention discloses a control method for low-frequency load shedding of user branch lines through collaboration between a terminal and a master station, comprising the following steps: Step (1) Status monitoring: The main station collects the system frequency, total load and regional power grid operation status in real time; the terminal monitors the real-time load, voltage and local frequency of the user branch, and uploads the branch load data to the main station at regular intervals, including the load importance level and current power.

[0086] Step (2) Load reduction condition trigger: The master station determines whether the system frequency is lower than the low-frequency load reduction start threshold, such as 49.5Hz. Combined with the branch load rate (actual load / rated load) and importance label reported by the terminal, such as Class I / Class II / Class III, the master station-terminal collaborative load reduction process is started.

[0087] Step (3) Strategy formulation and instruction issuance: Based on the global load distribution and the principle of "cutting non-critical loads first and interruptible loads later", the main station calculates the total load reduction to be implemented, matches the Class III / Class II branches covered by the corresponding terminal, generates a load reduction instruction containing branch ID, load reduction amount (kW) and execution time limit (s), encrypts it and sends it to the target terminal.

[0088] Step (4) Terminal local verification and execution: After receiving the instruction, the terminal verifies the instruction signature and permissions, confirms whether the current load of the branch meets the load reduction requirement, and cuts off the specified load according to the instruction, and synchronously uploads the "execution status" (success / failure) and "actual load reduction" to the master station in real time; if it does not meet the requirement, such as the load being lower than the load reduction, it immediately feeds back to the master station and waits for the adjustment instruction.

[0089] Step (5) Effect evaluation and closed-loop control: The main station monitors whether the system frequency has risen back to the recovery threshold, such as 49.8Hz. Combined with the actual total load reduction feedback from the terminal, if the frequency does not meet the standard, the branch is re-selected, including raising the priority to Class II or increasing the load reduction of a single branch, and a new instruction is issued; if the standard is met, the load reduction process is terminated, the terminal records the load reduction event, including time, branch, load reduction, and archives the log.

[0090] Example 3 This invention provides another embodiment, a control system for low-frequency load shedding of user branch lines through collaboration between a terminal and a master station, including a master station-side low-frequency load shedding application and a terminal-side low-frequency load shedding app. For example... Figure 2 As shown, Figure 2 This is a functional diagram of the system for low-frequency load shedding of user branch loads through master station-terminal collaboration in this invention. The "new power load management system" refers to the "Power Load Management Measures (2023 Edition)".

[0091] The low-frequency load shedding application on the main station side has functions such as panoramic monitoring, anomaly alarm, load shedding analysis, strategy management, action briefing, and statistical analysis. The system gathers information such as regional power grid model information, user load cycles and monitoring information, load shedding action reports and analysis information, etc., to realize real-time monitoring and anomaly early warning of regional user branch load levels. Combined with the dispatching low-frequency load shedding scheme and setpoints, it performs comprehensive analysis and judgment, accurately calculates user load shedding amount and branch control cycle, intelligently generates low-frequency load shedding strategies and supports rolling optimization and orchestration, and supports remote downloading of strategies to user-side smart energy units.

[0092] Its overall structure is based on the new power load management system - load control application basic platform (existing technology, constructed in accordance with the "Power Load Management Measures (2023 Edition)"), and is divided into a data acquisition layer, an edge computing layer, an application function layer, and an interactive display layer from bottom to top: The overall structure of the terminal-side low-frequency load reduction app is based on the new power load management system - load control application basic platform (existing technology, constructed in accordance with the "Power Load Management Measures (2023 Edition)"). From bottom to top, it is divided into a perception layer, an edge computing layer, an application layer, and a communication layer. Sensing layer: The three-phase voltage and current signals of the user branch are collected through voltage transformers (TV) and current transformers (TA) at a sampling frequency of 2kHz to obtain the zero-crossing time and effective value. Edge computing layer: Employs ARM Cortex-A series processors and FreeRTOS system, running frequency calculation (zero-crossing period method), df / dt calculation (sliding window algorithm) and local policy verification module; Application layer: integrates local control module (including smart switch driver interface), event logging module (action log storage) and policy caching module (JSON format policy file); Communication layer: Communicates with the master station via 4G / NB-IoT (using IEC 61850 protocol), supporting command reception, data upload, and breakpoint resume functionality.

[0093] The data acquisition layer connects to the substation EMS system and the user-side smart energy unit terminal via the IEC 61850 protocol interface to collect real-time data such as bus frequency, user branch load, and controllable resource status (sampling frequency 5-10Hz). The edge computing layer is deployed at the edge nodes of the main station. It uses moving average filtering and 3σ outlier removal algorithm for data preprocessing, and realizes rapid identification of abnormal events through frequency decline rate df / dt calculation and load status assessment model. The application function layer integrates four core application modules: panoramic monitoring module (multi-dimensional status display), load reduction judgment module (frequency anomaly detection, load reduction demand calculation), strategy management module (dynamic optimization algorithm), and action briefing module (event recording and statistics). The interactive display layer is a web-based visualization interface developed based on a B / S architecture. It provides visualization components such as frequency trend charts, load heat maps, and strategy execution dashboards, and supports remote parameter configuration and manual intervention by dispatchers.

[0094] The low-frequency load shedding application on the main station side includes the following functions: Panoramic monitoring: Comprehensive monitoring of low-frequency load shedding on regional user branch lines, including load topology monitoring, real-time frequency monitoring, terminal operation monitoring, load shedding strategy monitoring, and action event monitoring; Anomaly Alarms: Features alarm definition, real-time alarms, alarm query, etc. When an alarm occurs, it will notify you through various means such as pop-up windows, voice, and SMS. It also supports historical alarm queries. Load reduction assessment: Comprehensive analysis of the total controllable quantity of the feeder, the user load shedding ratio, the user load shedding amount and the load shedding round, to evaluate whether the total load shedding amount in each round meets the low-frequency load reduction requirements of the power grid, and to give suggestions on the low-frequency load shedding amount, load shedding sequence and load reduction effect assessment. Strategy Management: Based on the load reduction assessment results, intelligently generate low-frequency load reduction strategies for user branch loads. After verification, the strategies are confirmed to be effective. Manual strategy optimization is supported, as well as strategy download and recall comparison functions. Action Briefing: When a low-frequency load shedding action occurs, the low-frequency load shedding action report information of the aggregation area is collected, including action time, action user, load shedding cycle and load shedding amount; Statistical analysis: Supports statistical analysis of load scale, load shedding capacity, load reduction and other reports by region, line, user, date and other dimensions. Supports percentage, month-on-month and change curve analysis, generates analysis reports and supports export. The terminal-side low-frequency load shedding app has functions such as load monitoring, intelligent alarm, strategy execution, action recording, and parameter management. Utilizing the edge computing capabilities of the smart energy unit, it monitors the load level of user branches in real time, performs setpoint comparison and protection blocking judgment based on local low-frequency load shedding strategies and parameters, and triggers low-frequency load shedding protection action when an abnormal grid frequency is detected on the user side. The protection action generates an event alarm, retains an action record report, and uploads the alarm event, action event, and action report to the main station system in real time.

[0095] The terminal-side low-frequency load reduction app includes the following functions: Load monitoring: Millisecond-level real-time monitoring of branch load frequency changes, terminal status, and low-frequency load shedding operation; Intelligent alarm: Supports early warning alarms based on predefined indicators and threshold parameters, and generates and sends alarm records; Strategy execution: Supports millisecond-level comparison of branch load frequency settings and low-frequency load shedding protection interlocking. When the low-frequency load shedding conditions are met, the low-frequency load shedding strategy is executed, triggering load shedding actions and saving the reported action records. Action logging: Supports saving, reporting, and querying low-frequency load shedding action logs; Parameter management: Supports querying and maintaining local low-frequency load reduction indicators and parameters on the terminal.

[0096] Example 4 This invention provides another embodiment, which is a control method for low-frequency load reduction of user branch lines in collaboration between the terminal and the master station. Taking the data flow between the master station and the terminal as an example, the main steps are as follows: Step 1. Strategy Formulation: Based on the results of load resource survey, combined with user load survey / reporting data such as user type, production characteristics, load scale, security / controllable load list, and adjustable capacity, determine user classification and low-frequency load reduction adjustment weights. Taking into account the low-frequency load reduction setpoints of dispatching services and the load status of customers, generate user load routing order tables and user low-frequency load reduction strategies according to users. Step 2. Strategy Download: After the user branch load low-frequency load reduction strategy is compiled and passes the adaptive verification, follow the remote operation safety protection mechanism, select user terminals one by one / in batches to remotely download the low-frequency load reduction strategy. After the terminal receives the low-frequency load reduction strategy sent by the master station, it performs strategy data verification. After the verification is passed, the local strategy is updated. Specifically, the following steps are included: Step 2.1 Preparation for main station policy distribution: The main station calls the policy management module to load the user branch load low-frequency load reduction policy file that has passed the adaptive verification; triggers the remote control operation safety protection process, executes operator permission verification, double confirmation mechanism and anti-misoperation verification, and generates distribution instructions after the verification is passed.

[0097] The user branch load low-frequency load reduction strategy file includes: strategy ID, version number, load reduction round configuration, and target user terminal ID list. The load shedding configuration includes: frequency setting value, delay time, and load shedding capacity for each round. Operator permission verification includes: login authentication and operation permission level matching; The dual confirmation mechanism includes: operator submission + guardian review. The anti-misoperation verification includes: online status detection of the target terminal and remote download function enable status check of the terminal.

[0098] Step 2.2 Encrypted transmission of policy data: The master station packages the policy data according to the communication protocol, such as DL / T 634.5104, and adds a frame header, data body and CRC check code; it uses an encryption algorithm, such as AES-128, to encrypt the data body, and sends the policy distribution message to the selected terminals one by one / in batches through the designated communication channel.

[0099] The frame header includes: terminal address and function code; The data body includes: strategy parameters; The designated communication channels include: power dispatch data network / wireless private network.

[0100] Step 2.3 Terminal Reception and Data Parsing: The terminal listens to the communication port in real time, and after receiving the sent message, it performs physical layer and link layer verification. After passing the verification, it enters the application layer for parsing and extracts core data such as policy ID, version number, load reduction round parameters, and user ID.

[0101] The physical layer includes: frame format and length; The link layer includes: CRC check.

[0102] Step 2.4 Terminal Policy Data Verification: The terminal starts the policy verification module and verifies each item: ① Policy version verification: the new policy version number is greater than the local storage version number to prevent the old policy from being overwritten; ② Parameter logic verification: the frequency value of the load shedding cycle decreases with each cycle and is within the specified range, such as 48Hz-50Hz; the delay time meets the requirements of the "Guidelines for the Safety and Stability of Power Systems", such as 0.1s-5s. ③ Capacity matching verification: Single wheel / total unloading capacity ≤ terminal rated unloading capacity; ④ User ID verification: Ensure the issued user ID matches the locally configured ID on the terminal.

[0103] Step 2.5 Local Policy Update and Response: After verification, the terminal writes the new policy parameters into the non-volatile memory Flash. If the old policy is overwritten, the update time, policy version, and operation log are recorded. A "Policy update successful" response message is generated and sent back to the main station through the original communication channel.

[0104] The operation log includes: a verification pass indicator; The response message includes: policy ID, version number, and update status code 0x00.

[0105] Step 2.6 Verification Failure Handling: If any verification item fails, such as version expiration, parameter exceeding limits, or user ID mismatch, the terminal refuses to update the local policy, records a failure log, including the failure reason code, such as 0x01=version expiration, 0x02=parameter exceeding limits; and returns a "policy update failed" response message to the main station, in which the response message includes the failure reason code.

[0106] Step 2.7 Master Station Result Confirmation and Log Archiving: The master station receives the terminal's response message and parses the update status: if successful, it marks the policy download for that terminal as complete; if it fails, it triggers an alarm and displays the reason for the failure, requiring intervention from operations and maintenance personnel. The master station synchronously archives the operation logs to the database.

[0107] The alarms include: sound and light / pop-up windows; Operations and maintenance personnel intervention includes: such as recompiling policies and checking terminal configurations; The main site's synchronized archived operation logs include: distribution time, terminal ID, policy version, operator, and execution result.

[0108] Step 3. Strategy Execution: The terminal monitors the load level of the user branch in real time, compares the set value with the local low-frequency load shedding strategy, generates a warning alarm report when an alarm event occurs, and triggers the low-frequency load shedding protection action when the user-side power grid frequency is detected. When the protection action is activated, an accident alarm report is generated, and the action event and alarm report are uploaded to the main station system in real time.

[0109] The terminal monitors the load level of user branches in real time: it collects three-phase current and voltage signals through the current transformers (CT) and voltage transformers (PT) configured in each branch, calculates the active power after analog-to-digital conversion (A / D), and obtains the real-time load value of the branch. The sampling frequency is ≥20 times / second, and the data is synchronized to the terminal data processing unit.

[0110] Local low-frequency load shedding strategy setting comparison: The terminal calls the locally stored load shedding strategy parameters, including the action frequency fn, delay tn, list of loads that can be shelved and their priorities, and load shedding amount Pn for each round; the real-time frequency is extracted through the Fourier transform of the voltage signal and compared with fn; at the same time, it is verified whether the branch load is in the list of loads that can be shelved and is greater than the minimum load shedding threshold.

[0111] Warning alarm report generation: When the frequency is below the normal range, such as 49.5Hz, but the action value is not reached, the branch load exceeds the limit, or the device is abnormal, a report is generated according to the format, stored locally, and triggers the yellow alarm light / HMI display.

[0112] Among them, branch load exceeding limits includes: overload threshold; Device malfunction includes: device malfunction; The format includes: event type, time, branch number, frequency / load value, and level.

[0113] Low-frequency load shedding action trigger: real-time frequency ≤ fn and duration ≥ tn, such as f1=49Hz, t1=0.5s, the terminal cuts off the loads that can be cut off according to priority, disconnects the corresponding branch circuit breaker through the output relay, and prioritizes cutting off non-critical loads to ensure that the total load cut off is ≈ Pn; if the frequency does not recover, the next round of load shedding is executed in sequence.

[0114] Accident alarm report generation: After an action is taken, a report is generated in a standardized format, stored with millisecond-level time stamps, and triggered by a red action light / HMI display. The standardized format after the action includes: cycle number, time, trigger frequency, branch / load value disconnected, and frequency before and after the action.

[0115] Action events and reports are uploaded to the main station: The terminal uploads the warning / accident report to the main station in real time via Ethernet / 4G according to the IEC 61850 protocol, including event details, device status, and action results. The main station receives, stores, and generates an analysis report.

[0116] Step 4. Strategy Optimization: The main station monitors the low-frequency load shedding protection actions and reports in real time, and optimizes the low-frequency load shedding strategy based on the grid frequency recovery and load shedding situation after the action, and updates it to the terminal as needed.

[0117] Specifically, the following steps are included: Step 4.1 Data Acquisition and Real-time Monitoring.

[0118] The main station collects low-frequency load shedding protection action information and real-time power grid data in real time through the SCADA / EMS system and terminal upload channels, and receives action reports generated by the terminal and stores them in the action event database.

[0119] Among them, the low-frequency load shedding protection action information includes: low-frequency load shedding protection action information; Real-time power grid data includes: frequency dynamic curves, voltage / current waveforms, and load distribution; The action report generated by the terminal includes: the operating conditions before and after the action, and the conditions for starting the protection logic.

[0120] Step 4.2 Evaluation of the action effect.

[0121] Round configuration optimization: Based on the action sequence of multiple rounds, adjust the frequency difference or delay between adjacent rounds to avoid action overlap or excessively long intervals.

[0122] Among them, the frequency difference between adjacent rounds is optimized from 0.2Hz to 0.15Hz; Among these measures is delay, such as shortening the delay of important rounds to 0.3 seconds; Load shedding correction: Based on the load importance level, loads that frequently malfunction or have a significant impact after restoration are removed from the load shedding list, and non-critical industrial / commercial loads are added.

[0123] Algorithm optimization: If frequency measurement jitter exists, update the terminal frequency filtering algorithm or anti-jitter criterion.

[0124] Among them, the terminal frequency filtering algorithm includes adding a moving average window; the anti-shake criterion includes that the action condition is met for three consecutive cycles before it is activated.

[0125] Step 4.4 Strategy Verification and Distribution.

[0126] Simulation verification: The main station calls the power grid simulation module, inputs the optimized strategy parameters and typical fault scenarios (such as large unit tripping), and simulates to verify the frequency recovery effect and the rationality of the load shedding, ensuring no risk of cascading faults.

[0127] Pilot testing: Select 2-3 typical regional terminals, issue optimization strategies for offline testing, monitor response time and load switching accuracy under simulated actions, and generate formal strategy files after passing the test.

[0128] Secure distribution: The master station distributes the policy file, including the version number and checksum, to each terminal through an encrypted channel, such as the power dispatch data network. After receiving the file, the terminal parses it and updates its local policy library, and sends back a "update successful" signal.

[0129] Step 4.5 Closed-loop monitoring.

[0130] The main station continuously monitors the terminal strategy operation status, records the action data in the next low-frequency event, compares the recovery indicators before and after optimization, and forms a closed loop of "monitoring-evaluation-optimization-verification". If the effect does not meet the standard, repeat steps 2-4.

[0131] like Figure 4 As shown, Figure 4 This is a schematic diagram of the low-frequency load reduction application system architecture on the main station side of this invention.

[0132] A control system for low-frequency load shedding of user branch lines based on the collaboration between the terminal and the master station is proposed. The low-frequency load shedding application on the master station side is based on the construction of a new power load management system - load control application basic platform, realizing functions such as panoramic monitoring, abnormal alarm, load shedding analysis, strategy management, action briefing, and statistical analysis. It has the ability to perform panoramic monitoring, load shedding analysis, and strategy management of low-frequency load shedding of user branch lines.

[0133] Its overall structure is based on the new power load management system - load control application basic platform (existing technology, constructed in accordance with the "Power Load Management Measures (2023 Edition)"), and is divided into a data acquisition layer, an edge computing layer, an application function layer, and an interactive display layer from bottom to top: Data acquisition layer: Connects to the substation EMS system and user-side smart energy unit terminal through the IEC 61850 protocol interface to collect real-time data such as bus frequency, user branch load, and controllable resource status (sampling frequency 5-10Hz). Edge computing layer: Deployed at the edge nodes of the main station, it uses moving average filtering and 3σ outlier removal algorithm for data preprocessing, and realizes rapid identification of abnormal events through frequency decline rate df / dt calculation and load status assessment model; Application Function Layer: Integrates four core application modules: panoramic monitoring module (multi-dimensional status display), load reduction analysis module (frequency anomaly detection, load reduction demand calculation), strategy management module (dynamic optimization algorithm), and action briefing module (event recording and statistics); Interactive Presentation Layer: Based on a B / S architecture, a web-based visualization interface is developed, providing visualization components such as frequency trend charts, load heat maps, and strategy execution dashboards, supporting remote parameter configuration and manual intervention by dispatchers.

[0134] Example 5 This invention provides another embodiment, which is a control method for low-frequency load shedding of user branch lines in collaboration between the terminal and the master station. Taking the low-frequency load shedding application system architecture on the master station side as an example, it mainly includes: (1) Communication between the terminal and the main station adopts fiber optic private network, wireless private network, and wireless virtual private network channels, and adopts TCP / IP protocol. Information exchange is realized through protocols such as DL / T698.45 and IEC60870-5-104. (2) Set up a secure access zone on the main station side, and deploy communication modules to communicate with the terminal according to the channel type. When the terminal communicates with the main station using wireless private network or wireless virtual private network, it needs to pass through the secure access zone for security isolation. When using fiber optic private network communication, choose whether to pass through the secure access zone for security isolation as needed. (3) The low-frequency load reduction application on the main station side is built on independent and controllable technology. The low-frequency load reduction application is realized based on the standardized service capabilities of the basic platform. The low-frequency load reduction application function supports flexible expansion and iterative upgrade according to business needs. (4) The safety protection measures for low-frequency load shedding applications meet the requirements of the "Regulations on Safety Protection of Power Monitoring Systems".

[0135] like Figure 5 As shown, Figure 5 This is a schematic diagram of the terminal-side low-frequency load reduction App system architecture of the present invention.

[0136] Its overall structure is based on the existing new power load management system - load control application basic platform, and is constructed in accordance with the "Power Load Management Measures (2023 Edition)". It is divided into a perception layer, an edge computing layer, an application layer, and a communication layer from bottom to top: Sensing layer: The three-phase voltage and current signals of the user branch are collected through voltage transformers (TV) and current transformers (TA) at a sampling frequency of 2kHz to obtain the zero-crossing time and effective value. Edge computing layer: Employs ARM Cortex-A series processors and FreeRTOS system, running frequency calculation (zero-crossing period method), df / dt calculation (sliding window algorithm) and local policy verification module; Application layer: integrates local control module (including smart switch driver interface), event logging module (action log storage) and policy caching module (JSON format policy file); Communication layer: Communicates with the master station via 4G / NB-IoT (using IEC 61850 protocol), supporting command reception, data upload, and breakpoint resume functionality.

[0137] A control system based on the collaboration between the terminal and the master station to achieve low-frequency load reduction of user branch lines is provided. Its user-side low-frequency load reduction App realizes functions such as load monitoring, intelligent alarm, strategy execution, action recording, and parameter management, and has the ability to monitor user branch line load in real time, provide intelligent alarms, and execute strategies.

[0138] Example 6 This invention provides another embodiment, which is a control method for low-frequency load reduction of user branch circuits through collaboration between the terminal and the main station. Taking the low-frequency load reduction App system architecture on the terminal side as an example, it mainly includes: (1) Communication between the terminal and the main station adopts fiber optic private network, wireless private network and wireless virtual private network channel, and adopts TCP / IP protocol. Information exchange is realized through protocols such as DL / T698.45 and IEC60870-5-104; the terminal communicates locally with various measurement and monitoring devices of the user branch load through RS485, Ethernet, analog cable and other means. (2) The Low Frequency Load Reduction App is deployed in the smart energy unit terminal and is located in the application layer of the terminal software architecture. It is built based on the basic capabilities of the system layer and the public services of the component layer. The Low Frequency Load Reduction App supports flexible expansion according to business needs and supports remote upgrades and updates.

[0139] Example 7 Based on the same inventive concept, embodiments of the present invention also provide a computer device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor. When the processor executes the computer program, it implements the steps of a control method for low-frequency load shedding of a user branch line in collaboration with a master station, as described in any of embodiments 1-5.

[0140] Example 8 Based on the same inventive concept, this embodiment of the invention also provides a computer storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of any one of the control methods described in embodiments 1-5 for a terminal and a master station to collaboratively achieve low-frequency load reduction of a user branch.

[0141] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0142] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0143] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0144] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A control method for low-frequency load shedding of user branch lines in collaboration between a terminal and a master station, characterized by: include: Analysis and strategy control of low-frequency load reduction at the main station; Real-time frequency monitoring and load reduction strategy execution on the terminal side; The load reduction strategy optimization and control effect analysis were completed on the main station side.

2. The control method for low-frequency load shedding of user branch lines in collaboration between the terminal and the master station according to claim 1, characterized in that: The low-frequency load reduction analysis and strategy control on the main station side includes multi-source data acquisition and preprocessing of panoramic monitoring, frequency anomaly detection and demand calculation for load reduction analysis, strategy generation and three-level verification. The low-frequency load reduction application is realized based on the new power load management system. According to the user branch load controllable resource list, substation low-frequency load reduction setting and other data, the system realizes panoramic monitoring, load reduction analysis and strategy control of user branch load low-frequency load reduction, and downloads the low-frequency load reduction strategy generated in advance to the smart energy unit terminal.

3. The control method for low-frequency load shedding of user branch lines in collaboration between the terminal and the master station according to claim 2, characterized in that: The panoramic monitoring of low-frequency load reduction of user branch lines includes: real-time acquisition of multi-source data, data preprocessing, and multi-dimensional status display. The load reduction assessment includes: frequency anomaly detection, load status evaluation, and load reduction demand calculation; The low-frequency load reduction strategy includes: load reduction strategy generation, load reduction strategy verification, and strategy download to the terminal.

4. The control method for low-frequency load shedding of user branch lines in collaboration between the terminal and the master station as described in claim 1, characterized in that: The real-time frequency monitoring and load reduction strategy execution on the terminal side includes zero-crossing periodic frequency measurement using edge computing, anomaly detection based on round thresholds, and priority-based load shedding control. Utilizing the local edge computing capabilities of the terminal, the system monitors changes in the load frequency of user branches in real time, responds quickly when frequency anomalies occur, controls the load shedding of user branches according to the pre-installed low-frequency load reduction strategy, and sends alarm information and action events to the main station system in real time.

5. The control method for low-frequency load shedding of user branch lines in collaboration between the terminal and the master station according to claim 4, characterized in that: The edge computing, wherein the terminal-side edge computing is based on embedded hardware and a lightweight real-time operating system, integrating a data acquisition module, a real-time analysis module, a strategy execution module, and a communication module; the local storage unit pre-stores low-frequency load reduction strategy parameters and supports dynamic policy updates; The real-time monitoring of user branch load frequency changes includes: (1) Monitoring objects: 10kV / 0.4kV distribution network branches connected to users, and three-phase voltage / current signals are collected through the built-in voltage transformer TV and current transformer TA in the terminal; (2) Sampling parameters: voltage signal, current signal, sampling frequency 2kHz, one set of data is collected every 10ms; (3) Frequency calculation: Based on the voltage zero-crossing period measurement method, by capturing the time difference Δt (unit ms) of three consecutive zero-crossing points, the period T=2Δt and the frequency f=1000 / T (Hz) are calculated; the average frequency within 1 second is calculated once every 100ms and used as the real-time monitoring frequency f_meas; (4) Auxiliary monitoring: Synchronously calculate the frequency drop rate df / dt=(f_meas(k)-f_meas(k-1)) / Δt_s; Δt_s=0.1s, k is the current sampling time, used to determine the severity of the accident; The user branch load shedding control includes: Step (1) Pre-install strategy content: The main station pre-installs the parameters of each branch, priority L_i and total load shedding ΔP_n for each round, n=1,2,3 rounds; Step (2) Trigger judgment: Real-time monitoring shows that f_meas≤f_set and df / dt≥threshold value. If the frequency does not rise back to the blocking value within the delay t_delay, the nth round of load reduction is triggered. Step (3) Selecting load-cutting branches: Sort the branches in order of priority L_i=5→4→3, and cumulatively cut off the load ΣP_i until ΣP_i≥ΔP_n. Select the first m branches that meet the condition for the first time. If the last branch is partially cut off, calculate the required cutting ratio according to ΔP_n-ΣP_n (m-1) and control the smart switch to open to the corresponding load. Step (4) Execution control: The terminal sends a trip command to the branch intelligent switch through the RS485 / PLC communication interface, driving the built-in relay of the switch to act; at the same time, hardware anti-bounce is activated; Step (5) Event recording and uploading: Record the action time, trigger round, cut branch number / load, and frequency values ​​before and after the action, and upload them to the master station in real time via 4G / NB-IoT; The calculation includes: Frequency calculation: The sampling voltage zero-crossing times are t1=10.0ms, t2=20.2ms, t3=30.3ms → period T=2×20.2-10.0=20.4ms → f=1000 / 20.4≈49.02Hz, which meets the conditions for starting a round; df / dt calculation: when t=1.0s, f_meas=49.2Hz, when t=1.1s, f_meas=48.9Hz → df / dt=48.9-49.2 / 0.1=-3.0Hz / s, which satisfies df / dt≥-0.5Hz / s for 1 round; Load shedding calculation: 1 round ΔP_n=1000kW, pre-installed branch P1=300kW (L=5), P2=400kW (L=5), P3=350kW (L=4) → cumulative P1+P2=700kW<1000kW, P1+P2+P3=1050kW≥1000kW → disconnect P1, P2, P3, partially disconnect 50kW, that is, 50 / 350≈14% of the load of P3 is disconnected.

6. The control method for low-frequency load shedding of user branch lines in collaboration between the terminal and the master station according to claim 1, characterized in that: The process of optimizing load shedding strategies and analyzing control effects at the main station side includes deviation analysis algorithm evaluation, dynamic correction of load shedding amount using PID regulation, and optimization of user priority using AHP algorithm. Based on user-side power grid monitoring data, load shedding strategies, and action reports, the process involves analyzing the effects of low-frequency load shedding, optimizing the low-frequency load shedding strategy, and comprehensively adjusting the load shedding amount, user priority, load shedding ratio, and user branch control sequence to improve the accuracy of low-frequency load shedding actions and minimize the impact of low-frequency load shedding on the user range.

7. The control method for low-frequency load shedding of user branch lines in collaboration between the terminal and the master station according to claim 6, characterized in that: The low-frequency load shedding effect analysis process is as follows: Based on user-side power grid monitoring data, load shedding strategies and action reports, a deviation analysis algorithm is used to calculate the deviation rate between the actual load shedding amount and the theoretical value, where the deviation rate = |actual load shedding amount - theoretical load shedding amount| / theoretical load shedding amount × 100%. The load shedding effect is evaluated in conjunction with the frequency recovery time. When the deviation rate > 5% or the recovery time > 10 seconds, it is determined that the load shedding effect is not up to standard. The optimization of the low-frequency load reduction strategy includes: ① Load shedding optimization: Based on the deviation analysis results, the load shedding is dynamically corrected using a PID control algorithm, where the correction value = theoretical load shedding × (1 - deviation rate × control coefficient). ② User priority and load shedding ratio optimization: Based on user production characteristics, security load ratio and historical action impact, user priority is reordered using the analytic hierarchy process (AHP) and load shedding ratio is adjusted to reduce the load shedding ratio of high-priority users by 5%-10%; where, security load ratio = security load amount / total load amount × 100%, and historical action impact amount = economic loss assessment value / total user load. ③ Control sequence optimization: Based on the user branch load pull sequence table, a greedy algorithm is used to adjust the control sequence, prioritizing the cutting of non-critical production branches.

8. A control system for achieving low-frequency load shedding of user branch circuits through collaboration between terminals and the master station, characterized in that: Includes a low-frequency load reduction application on the main station side and a low-frequency load reduction app on the terminal side; The low-frequency load shedding application on the main station side is used for analysis and strategy control; it has functions such as panoramic monitoring, abnormal alarm, load shedding analysis, strategy management, action briefing, and statistical analysis; the system gathers information such as regional power grid model information, user load cycles and monitoring information, load shedding action reports and analysis information, etc., to realize real-time monitoring and abnormal early warning of regional user branch load levels, and performs comprehensive analysis and judgment in combination with dispatching low-frequency load shedding schemes and settings, accurately calculates user load shedding amount and branch control cycles, intelligently generates low-frequency load shedding strategies and supports rolling optimization and arrangement, and supports remote downloading of strategies to user-side smart energy units; The terminal-side low-frequency load shedding App is used for real-time frequency monitoring and load shedding strategy execution; it has functions such as load monitoring, intelligent alarm, strategy execution, action recording, and parameter management; it utilizes the edge computing capabilities of the smart energy unit to monitor the load level of user branches in real time, performs setpoint comparison and protection blocking judgment based on the local low-frequency load shedding strategy and parameters, and triggers low-frequency load shedding protection action when an abnormal grid frequency is detected on the user side. When the protection action is triggered, an event alarm is generated, and an action record report is stored. The alarm event, action event, and action report are uploaded to the main station system in real time.

9. A computer device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the control method for low-frequency load reduction of user branch load in collaboration with the main station, as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium contains a computer program, which, when executed by a processor, implements the steps of a control method for low-frequency load reduction of user branch lines as described in any one of claims 1-7, whereby a terminal and a master station work together.

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