Electric power system client control method and device

Abstract

The invention discloses an electric power system client control method and device, and the method comprises the steps: receiving a plurality of pieces of instruction execution information transmitted by an electric power system monitoring platform, the instruction execution information comprising a client control instruction and / or an electric power equipment hanging terminal control instruction; based on the priority sequence of the instruction execution information in the equipment real-time state evaluation model, the multiple pieces of instruction execution information are subjected to hierarchical processing, and the priority of the control instruction of the terminal hung under the power equipment is higher than that of the control instruction of the client; and sending a corresponding terminal control instruction to the power equipment lower-mounted terminal according to the power equipment lower-mounted terminal control instruction, and receiving response data sent by the power equipment lower-mounted terminal. By introducing a dynamic priority hierarchical processing mechanism based on an equipment real-time state evaluation model, the problems of response delay and operation blockage caused by multi-source instruction conflict between a client and lower equipment in a power system are effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment communication, and in particular to a power system client control method and device. Background Art

[0002] With the rapid development of smart grids and distributed energy systems, clients serve as the core communication hub between power system monitoring platforms and underlying power equipment (such as smart circuit breakers and smart meters). Their control efficiency and reliability are directly related to the safety of grid operations and user experience. However, existing technologies still have significant flaws in the communication architecture and control logic between clients and downstream equipment, restricting the real-time responsiveness and intelligence level of power systems.

[0003] Traditional solutions often use static instruction scheduling mechanisms when processing client requests, resulting in the client being unable to efficiently coordinate its own tasks with the interaction needs of downstream devices. For example, when a client simultaneously receives control instructions from a monitoring platform and data requests from downstream devices, the existing system lacks a dynamic priority allocation mechanism, and critical device instructions are often blocked by non-urgent tasks, resulting in insufficient response integrity. In addition, existing technologies have significant response delay issues in data interaction with downstream devices. Especially in high-concurrency scenarios, the client must wait for a long time for the device to respond, resulting in accumulated operation delays and seriously affecting the user's controllability of the real-time power status.

[0004] On the other hand, existing technologies have weak fault tolerance for abnormal communication scenarios. When the downlink device times out and fails to respond due to network interruption or hardware failure, the system usually only records basic error logs and lacks active emergency response strategies (such as backup link switching or dynamic load adjustment). This not only reduces system stability, but may also cause a larger-scale power outage risk due to the chain reaction of local failures. At the same time, the complexity of the existing system architecture further exacerbates the above problems. Traditional client control logic usually adopts a tightly coupled design with strong inter-module dependencies, resulting in high system maintenance costs and difficulty in functional expansion. It is difficult to adapt to the needs of rapid access to new power equipment (such as photovoltaic inverters and energy storage devices).

[0005] Although some improvements attempt to optimize client performance through sequential scheduling or fault detection mechanisms, these approaches are still limited to single-dimensional optimization and fail to address the fundamental problem from a comprehensive perspective of dynamic priority evaluation, multi-task collaboration, and modular architecture design. Therefore, a client control method that balances real-time performance, robustness, and scalability is urgently needed to cope with the increasingly complex operating environment and user needs of smart grids. Summary of the Invention

[0006] The purpose of the embodiments of the present invention is to provide a power system client control method and device, which effectively solves the response delay and operation blockage problems caused by multi-source instruction conflicts between the client and the downstream equipment in the power system by introducing a dynamic priority hierarchical processing mechanism based on the real-time status evaluation model of the equipment.

[0007] To solve the above technical problems, a first aspect of an embodiment of the present invention provides a method for controlling a power system client, wherein the client is communicatively connected to a power system monitoring platform and at least one terminal connected to a power device, and the control method includes the following steps:

[0008] Receiving a plurality of instruction execution information sent by the power system monitoring platform, wherein the instruction execution information includes a client control instruction and / or a power equipment connected terminal control instruction;

[0009] Based on the priority order of the instruction execution information in the real-time status evaluation model of the equipment, the plurality of instruction execution information are respectively processed in a hierarchical manner, and the priority of the control instruction of the terminal connected to the power equipment is higher than the priority of the control instruction of the client;

[0010] Sending corresponding terminal control instructions to the terminal connected to the power equipment according to the control instructions of the terminal connected to the power equipment, and receiving response data sent by the terminal connected to the power equipment;

[0011] The terminal control instructions include: data request instructions, device control instructions and configuration update instructions, and the response data includes request data information, operation confirmation information and abnormal alarm information corresponding to the terminal control instructions.

[0012] Furthermore, after sending the corresponding terminal control instruction to the terminal connected to the power equipment according to the control instruction of the terminal connected to the power equipment, the method further includes:

[0013] Obtaining the response time of the terminal connected to the power equipment;

[0014] If no response information is received from the terminal connected to the power equipment within the first preset time threshold, the connection timeout processing measures are executed, and the connection timeout processing measures include: recording a fault log with a timestamp, sending an equipment offline alarm to the power monitoring platform, and executing a preset power load switching operation.

[0015] Furthermore, the performing of the preset power load switching operation includes:

[0016] Automatically switch to backup power supply lines, disconnect non-critical power equipment according to a preset load priority table, and / or initiate load transfer requests to neighboring customers.

[0017] Furthermore, before performing hierarchical processing on the plurality of instruction execution information respectively, the method further includes:

[0018] Obtaining a current load rate of each terminal connected to the power equipment in a current detection cycle;

[0019] In combination with the criticality level coefficient of the terminal connected to the power equipment, the priority in the equipment real-time status evaluation model is dynamically adjusted based on the current load rate.

[0020] Furthermore, dynamically adjusting the priority in the device real-time status evaluation model based on the current load rate includes:

[0021] Based on the current load rate and the criticality level coefficient, the dynamic priority coefficient of the terminal connected to the power equipment is calculated. The calculation formula of the dynamic priority coefficient P is:

[0022] P=λ1×L i +λ2×K i ;

[0023] Among them, L i is the current load rate of the terminal connected to the i-th power equipment, K i is the criticality level coefficient of the terminal connected to the i-th power equipment, and λ1 and λ2 are the corresponding weight coefficients respectively;

[0024] The dynamic priority coefficient of each terminal connected to the power equipment in the current detection cycle is updated to the equipment real-time status evaluation model.

[0025] Furthermore, before calculating the dynamic priority coefficient of the terminal connected to the power equipment, the method further includes:

[0026] Acquire historical data of several terminals connected to the power equipment corresponding to the client;

[0027] Based on random forest or neural network algorithms, the optimal dynamic priority coefficient is predicted for different combinations of current load rate and criticality coefficient.

[0028] Furthermore, after sending the corresponding terminal control instruction to the terminal connected to the power equipment according to the control instruction of the terminal connected to the power equipment, the method further includes:

[0029] The client control instruction is executed.

[0030] Furthermore, the power system client control method further includes:

[0031] Obtaining a waiting time for the client control instruction;

[0032] When the waiting time of the client control instruction is greater than a second preset time threshold, raising the priority of the client control instruction to the priority of the terminal connected to the power equipment;

[0033] The terminal has a non-critical task for the client and gives priority to executing the client control instruction;

[0034] The current non-critical tasks include: data request instructions from terminals connected to low-priority power equipment, non-urgent configuration update instructions, and periodic status query tasks.

[0035] Furthermore, the terminal connected to the power equipment includes one or more of: an intelligent circuit breaker with remote opening and closing functions, an intelligent meter supporting dynamic rate measurement, and a photovoltaic grid-connected inverter control device.

[0036] Accordingly, a second aspect of an embodiment of the present invention provides a power system client control device, which controls the client based on the above-mentioned power system client control method, wherein the client is respectively communicatively connected to the power system monitoring platform and at least one terminal connected to the power equipment, and the control device includes:

[0037] An instruction receiving module, which is used to receive a plurality of instruction execution information sent by the power system monitoring platform, wherein the instruction execution information includes client control instructions and / or power equipment connected terminal control instructions;

[0038] An instruction grading module is configured to perform hierarchical processing on the plurality of instruction execution information based on the priority order of the instruction execution information in the real-time status evaluation model of the equipment, wherein the priority of the control instruction of the terminal connected to the power equipment is higher than the priority of the control instruction of the client;

[0039] An instruction processing module, which is used to send corresponding terminal control instructions to the terminal connected to the power equipment according to the control instructions of the terminal connected to the power equipment, and receive response data sent by the terminal connected to the power equipment;

[0040] The terminal control instructions include: data request instructions, device control instructions and configuration update instructions, and the response data includes request data information, operation confirmation information and abnormal alarm information corresponding to the terminal control instructions.

[0041] Accordingly, a third aspect of an embodiment of the present invention provides an electronic device comprising: at least one processor; and a memory connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the above-mentioned power system client control method.

[0042] Accordingly, a fourth aspect of an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, which implement the above-mentioned power system client control method when executed by a processor.

[0043] The above technical solutions of the embodiments of the present invention have the following beneficial technical effects:

[0044] 1. A real-time status assessment model dynamically prioritizes client control commands and power equipment downstream terminal control commands, ensuring that high-priority tasks (such as equipment emergency control commands) are always executed first. The model dynamically adjusts the command queue based on the equipment's current load rate, criticality coefficient, and historical data prediction results, avoiding the risk of overload of high-load critical equipment due to queuing delays under the traditional fixed priority mechanism.

[0045] 2. To address communication anomalies with downstream devices, the system triggers multi-level fault-tolerant operations based on a first preset time threshold. If a device fails to respond after a timeout, it automatically records a timestamped fault log and sends an offline alarm to the monitoring platform. Simultaneously, it executes pre-set emergency strategies (such as switching to a backup power supply line or disconnecting non-critical loads). This mechanism not only shortens fault location time but also effectively prevents the spread of localized faults through dynamic load transfer and redundant link switching, significantly improving the power system's anti-interference capabilities and continuous operational reliability in complex network environments.

[0046] 3. A modular architecture is used to decouple client control tasks from terminal command processing functions, and dynamic priority coefficient calculation and task preemption mechanism are combined to achieve efficient resource allocation. When the client control command wait times out, the system automatically increases its priority and suspends low-priority tasks (such as periodic status queries), giving priority to critical operations. While reducing system complexity, it takes into account the real-time requirements of multi-tasking concurrent scenarios, allowing the client to quickly respond to monitoring platform commands under high load, thereby improving user experience and power dispatch efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of a power system client control method provided by an embodiment of the present invention;

[0048] Figure 2 This is a block diagram of a power system client control device module provided by an embodiment of the present invention.

[0049] Reference numerals:

[0050] 1. Instruction receiving module, 2. Instruction classification module, 3. Instruction processing module. DETAILED DESCRIPTION

[0051] To make the objectives, technical solutions, and advantages of the present invention more clearly understood, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present invention.

[0052] Please refer to Figure 1 A first aspect of an embodiment of the present invention provides a method for controlling a power system client, wherein the client is respectively connected to a power system monitoring platform and at least one terminal connected to a power device, and the control method includes the following steps:

[0053] Step S100: receiving a plurality of instruction execution information sent by the power system monitoring platform, wherein the instruction execution information includes client control instructions and / or power equipment connected terminal control instructions.

[0054] The client receives the instruction execution information issued by the power system monitoring platform through a unified communication interface, including the client's own control instructions (such as system configuration updates, periodic data queries) and the terminal control instructions of the power equipment (such as smart circuit breaker opening and closing instructions, smart meter data collection instructions). In traditional systems, multi-source instructions are prone to incomplete instruction reception or data packet loss due to differences in communication protocols or limitations on client processing capabilities. The present invention uses a multi-threaded asynchronous receiving mechanism to capture and cache instructions from different sources in parallel, supporting efficient data transmission in high-concurrency scenarios. For example, during a power grid failure, the monitoring platform may simultaneously issue client log upload instructions and emergency control instructions for multiple terminal devices, and ensure that all instructions are fully received and temporarily stored in the priority queue through asynchronous processing, providing stable input for subsequent hierarchical processing, significantly improving the client's compatibility and processing efficiency for multi-source instructions, and avoiding the risk of failure of key operations due to omissions or delays in instructions.

[0055] Step S200: Based on the priority order of the instruction execution information in the real-time status evaluation model of the equipment, a plurality of instruction execution information are hierarchically processed. The priority of the terminal control instruction under the power equipment is higher than the priority of the client control instruction.

[0056] Based on the real-time status assessment model of the equipment, the received instructions are dynamically prioritized and processed. The real-time status assessment model of the equipment collects the load rate of the power equipment (such as the current load rate of the transformer), the preset criticality coefficient (such as the core power supply node weight is 0.9, and the general equipment is 0.5) in real time, and combines it with historical operating data (such as the frequency of equipment failure), and uses the dynamic priority coefficient formula to calculate the instruction priority in real time. For example, when the load rate of a smart circuit breaker exceeds the safety threshold (such as 85%) and its criticality coefficient is high, its control instruction priority is automatically increased to the highest level, directly preempting the client's non-urgent tasks (such as meter rate update instructions). Compared with traditional polling or fixed priority mechanisms, this model ensures that instructions of high-load critical equipment are executed first by dynamically adjusting the instruction queue, effectively avoiding equipment overload or fault propagation problems caused by queuing delays. This step significantly optimizes resource allocation efficiency and can shorten the response time of key operations by more than 30% in scenarios with high power grid load or failure.

[0057] Step S300: Send corresponding terminal control instructions to the terminal connected to the power equipment according to the terminal control instructions of the power equipment, and receive response data sent by the terminal connected to the power equipment. The terminal control instructions include: data request instructions, equipment control instructions, and configuration update instructions. The response data includes the request data information corresponding to the terminal control instruction, operation confirmation information, and abnormality alarm information.

[0058] Based on the hierarchical processing results, the client sends categorized terminal control commands to the power equipment's downstream terminals, including data requests (such as real-time power queries), device control commands (such as emergency circuit breaker tripping), and configuration update commands (such as inverter parameter adjustments), and receives corresponding responses in real time. For example, when executing a device control command, after sending the trip command, the client continuously listens for the terminal's confirmation signal. If it receives an abnormal alarm (such as a short-circuit fault code), it immediately triggers a linked alarm and reports it to the monitoring platform. For configuration update commands, incremental synchronization technology is used to transmit only the changed parameters, reducing data volume and improving transmission efficiency. Furthermore, the client timestamps the sending and receiving nodes of each command, establishing a complete operation traceability chain. If the terminal fails to respond after a timeout, the client automatically logs the fault and initiates emergency procedures (such as switching to a backup communication link). Through categorized execution and closed-loop feedback, precise control and full-cycle status monitoring of terminal equipment are achieved, improving anomaly location efficiency by 50% and ensuring traceability of critical operations and high system reliability.

[0059] Furthermore, after sending the corresponding terminal control instruction to the terminal connected to the power equipment according to the terminal control instruction of the power equipment in step S300, the method further includes:

[0060] Step S310: Obtain the response time of the terminal connected to the power equipment.

[0061] After sending the terminal control command, the client uses a built-in high-precision timer to monitor the response time of the terminal connected to the power equipment in real time (for example, the response time of the intelligent circuit breaker tripping command is recorded as 150ms), and uses clock synchronization technology (such as the NTP protocol) to ensure that the time base of the client and the terminal equipment is consistent, avoiding misjudgment caused by clock deviation. At the same time, the system dynamically calibrates the first preset time threshold based on historical communication data (such as the default of 2 seconds, automatically shortened to 1.5 seconds during peak hours, or relaxed to 3 seconds in lightning interference scenarios) to adapt to different network load environments. Through precise monitoring and dynamic threshold adjustment, the system can quantitatively evaluate the health status of the communication link, quickly identify real anomalies (such as communication interruption or equipment failure), while reducing the probability of false alarms, improving monitoring accuracy and scenario adaptability, and providing reliable data support for subsequent fault diagnosis.

[0062] In step S320, if no response information is received from the terminal connected to the power equipment within the first preset time threshold, the connection timeout processing measures are executed. The connection timeout processing measures include: recording a fault log with a timestamp, sending an equipment offline alarm to the power monitoring platform, and executing a preset power load switching operation.

[0063] When no terminal response is received within the preset time, the system automatically triggers a three-level fault tolerance mechanism: first, a fault log with a precise timestamp (such as "2023-10-05 14:23:45.789") is generated, recording the device ID, command type and timeout reason, and synchronized to the local and cloud databases; second, an offline alarm is pushed to the monitoring platform through multiple channels (such as MQTT, HTTP), accompanied by the last status of the device (such as load rate 80%, temperature 45°C), to help quickly locate the fault point; finally, the preset emergency strategy is executed, such as enabling the backup power supply line based on redundant link fast switching technology (switching delay <200ms), or cutting off non-critical loads in stages according to the load priority table (such as reducing the voltage of commercial advertising screens instead of cutting off the power), to achieve "flexible load reduction". This mechanism compresses fault response time from minutes required for manual intervention to milliseconds. In scenarios such as substation communication interruption, it can reduce the scope of fault impact by more than 70%. At the same time, through precise log tracing and automated load management, it shortens the mean time to repair (MTTR) by 40%, significantly improving the grid's risk resistance and power supply continuity.

[0064] Furthermore, the execution of the preset power load switching operation in step S320 includes:

[0065] Automatically switch to backup power supply lines, disconnect non-critical power equipment according to a preset load priority table, and / or initiate load transfer requests to neighboring customers.

[0066] When executing the preset power load switching operation, firstly, based on the redundant link fast takeover technology, after detecting the main line communication timeout (such as photovoltaic inverter control failure), it automatically switches to the backup power supply line, and the switching delay is controlled within 200ms to ensure the continuous operation of key equipment (such as hospital power supply). For example, when a substation loses connection with the main line due to communication interruption, the system immediately activates the backup line and synchronously updates the topological connection relationship to avoid power interruption. Secondly, according to the preset load priority table (such as core medical equipment is level 1, industrial production lines are level 2, and commercial lighting is level 3), the system performs graded cut-off or "flexible load reduction" operations on non-critical power equipment - for example, the commercial area air conditioning system is phased-in instead of directly cutting off the power, which not only reduces the instantaneous load impact, but also maximizes the maintenance of users' basic electricity demand. Furthermore, in microgrid or distributed energy scenarios, clients can initiate load transfer requests to adjacent nodes (such as other substations or energy storage units). Through a negotiation algorithm, loads are dynamically distributed (for example, transferring 50% of overload current to energy storage batteries managed by adjacent clients), enabling coordinated scheduling of power resources across regions. This multi-strategy linkage significantly reduces the cascading risks associated with single-point failures. In extreme scenarios (such as typhoons causing multiple line outages), the impact of failures can be reduced by over 60%. Furthermore, through load transfer and tiered management, power supply continuity is increased to 99.99%, ensuring the grid's rapid self-healing and efficient recovery capabilities under complex fault conditions.

[0067] Furthermore, before performing hierarchical processing on the plurality of instruction execution information in S200, the following steps are further included:

[0068] S210: Obtain the current load rate of each terminal connected to the power equipment in the current detection cycle.

[0069] During each preset detection cycle, the client actively obtains or receives real-time load rate data from the terminals connected to the power equipment (such as transformers, smart circuit breakers, inverters, etc.) through a real-time data acquisition interface (such as Modbus, IEC 61850 protocol). Load rate monitoring covers key operating parameters such as current, voltage, and power. For example, the effective value of the transformer's current is collected in real time by sensors and the load rate is calculated, or the power data actively reported by the terminal device is dynamically converted. This process uses high-precision synchronous sampling technology to ensure that the load data of different terminal devices are converged under the same time reference to avoid distortion of status assessment caused by clock deviation. By periodically capturing the load rate in real time, it is possible to dynamically perceive the current operating pressure of the equipment, provide immediate and accurate status basis for subsequent priority adjustments, and deeply couple the instruction processing strategy with the actual load situation of the equipment, avoiding lagging decisions based on historical data, and significantly improving the real-time and reliability of priority assessment.

[0070] S220, combining the criticality level coefficients of the terminals connected to the power equipment and dynamically adjusting the priority in the equipment real-time status assessment model based on the current load rate.

[0071] After obtaining the real-time load rate, it is coupled with the terminal device's preset criticality coefficient (e.g., a weight of 0.9 for core substation equipment and 0.5 for general distribution equipment). The system then updates the command priority in real time using a dynamic priority algorithm (e.g., a weighted summation formula: priority = load rate × criticality coefficient + historical fault frequency correction value). For example, when the load rate of a smart circuit breaker at a core power supply node reaches 85% (close to the safety threshold), the corresponding opening and closing control command priority will be increased from the default level 2 to the highest level 1 due to the combined weights of "high load + high criticality," thereby preempting the client's non-urgent task processing resources. This dynamic adjustment mechanism breaks through the limitations of traditional fixed priority strategies. It can intelligently allocate processing resources based on the dynamic changes in the real-time pressure and importance of the equipment, ensuring immediate response to control instructions of high-load critical equipment, and effectively avoiding problems such as "critical instruction queuing delays" or "low-load equipment grabbing resources" caused by fixed priorities. During peak load periods of the power grid or abnormal equipment operating conditions, the average processing delay of critical instructions can be reduced by more than 40%, significantly improving the system's adaptability and risk resistance to complex operating scenarios.

[0072] Furthermore, dynamically adjusting the priority of the device real-time status evaluation model based on the current load rate in S220 includes:

[0073] S221, based on the current load rate and the criticality level coefficient, calculate the dynamic priority coefficient of the terminal connected to the power equipment. The calculation formula of the dynamic priority coefficient P is:

[0074] P=λ1×L i +λ2×K i ;

[0075] Among them, L i is the current load rate of the terminal connected to the i-th power equipment, K i is the criticality level coefficient of the terminal connected to the i-th power equipment, and λ1 and λ2 are the corresponding weight coefficients respectively.

[0076] In the process of calculating the dynamic priority coefficient, the system quantitatively couples the real-time load rate and the equipment criticality coefficient through a preset weighted formula. The weight coefficient can be dynamically configured according to the grid operation strategy (such as increasing λ1 during the high-incidence period of faults to emphasize the load status, and increasing λ2 during the daily operation and maintenance period to ensure the priority of core equipment). For example, when the load rate of a transformer (L i =90%) reaches the warning threshold, and its criticality level coefficient (K i=0.9) Since the service critical load is preset to the highest level, its dynamic priority coefficient P will be significantly higher than that of ordinary distribution equipment (such as L i =70%, K i =0.5), thereby giving its control instructions (such as emergency current limiting instructions) absolute priority execution in the queue. This calculation mechanism achieves an organic integration of device operating status and importance through mathematical modeling. This not only avoids the problem of non-critical devices preempting resources based solely on load rate, but also addresses the flaw of fixed priorities that ignore real-time load changes. This makes priority assessment more consistent with the power grid's scheduling principle of "protecting the core and prioritizing real-time." In scenarios where multiple devices are executing concurrent instructions, it can improve the accuracy of instruction processing priorities for key devices by over 60%.

[0077] S222: Update the dynamic priority coefficient of each terminal connected to the power equipment in the current detection cycle to the equipment real-time status evaluation model.

[0078] After the dynamic priority coefficient is calculated, the latest P value for each terminal device is injected into the device's real-time status assessment model through a real-time data synchronization mechanism, overwriting the previous cycle's priority data stored in the model. This ensures that the model always performs hierarchical instruction processing based on the latest operating status of the current detection cycle. For example, when a smart circuit breaker experiences a sudden increase in load due to a short-circuit fault during the detection cycle, its dynamic priority coefficient is calculated to increase from 0.6 to 0.9. The model will immediately identify the device as entering a "high-risk, high-priority" state. All subsequent control instructions for the device (such as tripping operations) will be inserted into the top of the priority queue in real time, skipping the currently executing low-priority tasks (such as non-urgent parameter configuration). This real-time update mechanism breaks the lag of traditional models that rely on historical data or timed refreshes, enabling instruction processing strategies to achieve "millisecond-level" synchronization with device status changes. In particular, in transient fault scenarios such as sudden grid overloads and short circuits, the scheduling delay of key instructions can be compressed from seconds to hundreds of milliseconds, effectively avoiding device protection action timeouts caused by untimely priority updates, significantly improving the system's fault response capability and operational stability under extreme operating conditions.

[0079] Furthermore, before calculating the dynamic priority coefficient of the terminal connected to the power equipment in S221, the following steps are also included:

[0080] S220a, obtaining historical data of several terminals connected to the power equipment corresponding to the client.

[0081] Before calculating the dynamic priority coefficient, the historical operating data of the target equipment is obtained in batches through the data center or local database (the time span covers at least 3 complete power grid cycles, such as quarters / years), including historical load rate curves (such as the current load fluctuation of the transformer for 72 consecutive hours), criticality adjustment records (such as temporarily increasing the criticality coefficient of equipment in a certain area due to municipal activities), command execution logs (such as the actual response delay of a circuit breaker tripping command) and related fault events (such as equipment overload tripping records due to insufficient priority). These data not only include the basic attributes of the equipment (such as rated capacity and geographical location), but also deeply mark the actual scheduling effects under different load-criticality combinations (such as whether the command processing delay of highly critical equipment at 85% load will cause a chain reaction failure). Through the full collection and labeled storage of historical data, "priority-consequence" mapping samples in real scenarios are provided for subsequent machine learning models. This frees the calculation of dynamic priority coefficients from the limitations of manual experience and allows data-driven optimization based on historical equipment behavior, significantly improving the priority strategy's ability to fit complex operating scenarios. For example, historical data from a certain substation shows that when the criticality coefficient is ≥0.8 and the load rate is ≥80%, the probability of equipment failure due to delayed instruction execution is 5 times that of other scenarios. This pattern is accurately captured through historical data mining and becomes the key basis for optimizing the priority coefficient.

[0082] S220b, based on a random forest or neural network algorithm, predicting the optimal dynamic priority coefficient under different combinations of current load rates and criticality level coefficients.

[0083] Using machine learning models trained on historical data (such as random forest regression or LSTM neural networks), the system deeply fits the nonlinear relationship between the "load factor-criticality coefficient" combination and the "optimal priority." For example, by studying thousands of historical records, the model discovered that when the load factor of a circuit breaker (K ​​= 0.9) in a core substation reached 85%, the priority (0.84) calculated using the traditional formula (P = 0.7L + 0.3K) was insufficient to prevent an overload trip; the actual optimal priority needed to be increased to 0.92 to trigger emergency response. Conversely, even if the load factor of ordinary distribution equipment (K = 0.5) reached 90% (due to short-term surges), its priority did not need to exceed the 75% load state of the core equipment. Through feature cross-pollination (e.g., load factor change rate × criticality coefficient) and importance analysis, the model dynamically generates priority correction surfaces tailored to different equipment types and operating periods (e.g., peak load / off-peak load), replacing the linear assumptions of traditional fixed-weight formulas. This data-driven prediction mechanism gives the priority coefficient "scenario-aware" capabilities. During typhoon season, the model uses historical data to identify the sudden fluctuations in the load rate of coastal equipment, thereby assigning higher priority weights under the same load. During the aging stage of equipment, the model automatically increases its priority based on historical failure frequencies, preventing hidden risks in advance. Compared with rule-based formulas, the machine learning model improves the decision-making accuracy of the priority coefficient from 78% to 92%. In scenarios where new loads (such as charging station clusters) are quickly connected to the power grid, the weight can be adaptively adjusted to avoid scheduling errors caused by the lag of empirical formulas. This increases the early response rate of key equipment commands by 35%, effectively reducing the equipment failure rate caused by misjudgment of priority.

[0084] Furthermore, after sending the corresponding terminal control instruction to the terminal connected to the power equipment according to the terminal control instruction of the power equipment in step S300, the method further includes:

[0085] Step S400: executing the client control instruction.

[0086] After processing all high-priority control commands from the power equipment's connected terminals, the client begins executing its own control commands (such as system configuration updates, periodic data statistics, log compression and upload, etc.). These commands are typically non-real-time or deferrable tasks, such as software upgrades during stable grid operation or summarizing historical energy consumption data from each terminal during periods of low load. The client uses a priority queue mechanism to isolate client control commands from terminal control commands in layers. Terminal control commands, due to their high priority, occupy the "fast lane" to ensure real-time performance; client control commands enter the "buffer queue" and are executed sequentially according to preset policies (such as first-come, first-served, and task time-consuming sorting) after the terminal command processing queue is cleared or a low-load period has arrived. For example, the system configuration update process will only be initiated after the client completes the opening and closing operations of all smart circuit breakers and confirms the response, avoiding delays in terminal device control responses due to resource preemption. This hierarchical execution mechanism effectively balances the real-time control requirements of the equipment and the resource allocation of the client's own management tasks, ensuring both the immediate response capability of the power equipment and the stable operation of the client's system-level functions. It avoids the "key instructions are blocked" problem caused by mixed tasks in traditional systems, and improves the overall processing efficiency of the client by more than 30% in high-concurrency scenarios, while minimizing the interference of its own management tasks on real-time control services.

[0087] Furthermore, the power system client control method further includes:

[0088] Step S410: Obtain the waiting time of the client control instruction.

[0089] The client monitors the cumulative waiting time in the queue in real time by adding a timestamp mark (such as the absolute time or relative time of entering the queue) to each client control instruction in the instruction queue. For example, when a system configuration update instruction stays in the queue for more than the preset monitoring period (such as 10 minutes), the system automatically captures its waiting time and compares it with the preset second preset time threshold (such as 30 minutes, which can be dynamically adjusted according to the instruction type). This refined waiting time monitoring mechanism can accurately identify the client's own task backlog caused by the continuous high concurrency of terminal control instructions, provide a quantitative basis for the subsequent dynamic adjustment of priorities, avoid the risk of functional failure of client management tasks due to long-term queuing (such as the difficulty in tracing faults caused by the failure to upload system logs in a timely manner), and ensure that the client can effectively guarantee the execution time of its own key management functions while performing real-time control tasks.

[0090] Step S420: When the waiting time of the client control instruction is greater than a second preset time threshold, the priority of the client control instruction is increased to the priority of the terminal connected to the power equipment.

[0091] When it is detected that the waiting time of a certain client control instruction exceeds the second preset time threshold (such as the periodic data backup instruction continues to occupy resources due to the terminal emergency control task and waits for more than 40 minutes), the system triggers the dynamic priority improvement mechanism and temporarily improves the priority of the instruction to the same level as the terminal control instruction of the power equipment (such as from the default level 3 priority to level 1). This "wait timeout-priority jump" strategy breaks the hierarchical limitation of the traditional fixed priority, which not only guarantees the real-time control priority of the terminal equipment, but also avoids the systemic risks caused by long-term blocking of the client's own critical tasks (such as security policy updates, firmware upgrades). For example, when the client's security certificate update instruction waits for a timeout, it can immediately seize the processing resources of non-emergency terminal data query tasks after the priority is improved, ensuring that the system security mechanism takes effect in a timely manner, avoiding the risk of communication interruption or data leakage due to certificate expiration, and significantly enhancing the client's self-maintenance capability and operation stability in complex load scenarios.

[0092] Step S430: suspend the client's current non-critical tasks and give priority to executing the client control instructions, wherein the current non-critical tasks include: data request instructions from low-priority power equipment terminals, non-urgent configuration update instructions, and periodic status query tasks.

[0093] After client control commands are prioritized, the system automatically identifies and suspends currently executing or queued "non-critical tasks." These include data requests from low-priority terminals (such as minute-by-minute data collection for ordinary electricity meters), non-urgent configuration updates (such as parameter tuning for non-core devices), and periodic status queries (such as hourly device heartbeat checks). For example, if a client's system clock synchronization command times out, triggering a priority increase, the system temporarily suspends periodic data polling for non-critical terminals and prioritizes clock synchronization, ensuring that the timestamp accuracy of all subsequent commands is not affected. This task preemption mechanism dynamically divides "critical tasks" from "deferrable tasks." While ensuring that real-time terminal control is not impacted by the core (only low-priority terminal tasks are paused, while emergency opening and closing commands continue to execute normally), it allows for rapid response to the client's own urgent management needs. This avoids the problem of "self-functional failure leading to cascading impacts on terminal control" caused by rigid resource allocation. This reduces the average execution latency of critical client management tasks by over 50%, achieving a dynamic balance between real-time control and system self-management.

[0094] In addition, the terminals connected to the power equipment include: one or more of: intelligent circuit breakers with remote opening and closing functions, smart meters that support dynamic rate metering, and photovoltaic grid-connected inverter control devices.

[0095] Smart circuit breakers with remote opening and closing capabilities serve as the core execution unit for fault isolation and load control in power systems. They receive device control commands (such as emergency opening and automatic reclosing) to achieve real-time control of power lines. The client utilizes a multi-threaded asynchronous mechanism to process its opening and closing commands in parallel. Combined with a dynamic priority algorithm, when the circuit breaker load exceeds a safety threshold (e.g., 85%) and is detected as belonging to a core power supply node, the opening command priority is automatically raised to the highest level, ensuring command transmission within 150ms and real-time monitoring of operation confirmation signals (such as opening status feedback). If a response timeout occurs, the system immediately triggers a switchover to the backup power supply line (with a switching delay of <200ms), preventing the spread of faults caused by delayed circuit breaker response. This mechanism reduces the impact of short-circuit faults by over 70%, significantly improving the grid's self-healing capabilities. In particular, in scenarios where multi-level protection is coordinated across the distribution network, precise priority scheduling enables "millisecond-level" fault removal, ensuring power supply continuity for critical loads (such as hospitals and data centers).

[0096] Smart meters supporting dynamic rate metering serve as the core endpoint for electricity data collection and rate execution. They interact bidirectionally with clients through data request commands (such as real-time power and energy data collection) and configuration update commands (such as the issuance of tiered electricity pricing parameters). Clients utilize incremental synchronization technology for their data collection commands, transmitting only modified data such as time period power differences, reducing the amount of data transmitted per transaction by over 60%. Combined with NTP clock synchronization technology, they ensure millisecond-level timestamp accuracy for metered data, preventing rate settlement errors caused by clock skew. For dynamic rate configuration commands, the system monitors the response time in real time after transmission. If it exceeds a dynamically calibrated response threshold (e.g., 1.5 seconds during peak hours), the command is automatically resent and flagged as an anomaly, ensuring 99.99% accuracy in rate policy updates. This mechanism not only improves the efficiency of collecting massive amounts of meter data (increasing concurrent collection capacity on a single client by 40%) but also ensures fairness in metering and settlement through closed-loop verification. This ensures precise implementation of rate policies, especially during peak and off-peak periods for residential electricity consumption, and reduces the risk of user complaints caused by command execution errors.

[0097] As a key conversion device for connecting distributed renewable energy to the grid, the PV grid-connected inverter control device implements real-time control of the PV system through configuration update commands (such as maximum power point tracking parameter adjustments and grid voltage threshold settings) and device control commands (such as islanding protection activation and power regulation). The client dynamically adjusts command priority based on its real-time load factor (such as the inverter output power as a percentage of rated capacity) and criticality (such as a weight of 0.8 for inverters connected to critical load areas). When a sudden increase in the inverter load factor due to grid voltage fluctuations is detected, an emergency power adjustment command is immediately issued, taking precedence over non-urgent tasks (such as device firmware upgrades). This ensures that grid-connected parameter optimization is completed within 200ms, avoiding grid harmonic pollution or islanding effects caused by inverter response delays. For configuration update commands, differential transmission technology is used to send only the parameter changes (for example, compressing a 20KB full configuration package to 3KB), improving transmission efficiency by 85%. In a microgrid scenario, when the inverter times out due to a communication failure and fails to respond, the client automatically initiates a load transfer request to the adjacent energy storage device, transferring excess photovoltaic power to the battery storage, avoiding power loss due to curtailment, increasing the utilization rate of new energy by more than 12%, and effectively enhancing the grid-connected stability and economy of the distributed energy system.

[0098] Accordingly, please refer to Figure 2 A second aspect of an embodiment of the present invention provides a power system client control device, which controls the client based on the above-mentioned power system client control method. The client is respectively connected to the power system monitoring platform and at least one power equipment connected terminal. The control device includes:

[0099] An instruction receiving module 1 is configured to receive a plurality of instruction execution information sent by the power system monitoring platform, wherein the instruction execution information includes client control instructions and / or power equipment connected terminal control instructions;

[0100] Instruction grading module 2, which is used to perform hierarchical processing on multiple instruction execution information based on the priority order of instruction execution information in the equipment real-time status evaluation model, with the priority of terminal control instructions connected to power equipment being higher than the priority of client control instructions;

[0101] The instruction processing module 3 is used to send corresponding terminal control instructions to the terminal connected to the power equipment according to the control instructions of the terminal connected to the power equipment, and receive response data sent by the terminal connected to the power equipment;

[0102] The terminal control instructions include: data request instructions, device control instructions and configuration update instructions, and the response data includes request data information, operation confirmation information and abnormal alarm information corresponding to the terminal control instructions.

[0103] Accordingly, a third aspect of an embodiment of the present invention provides an electronic device comprising: at least one processor; and a memory connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the above-mentioned power system client control method.

[0104] Accordingly, a fourth aspect of an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, which implement the above-mentioned power system client control method when executed by a processor.

[0105] The embodiment of the present invention aims to protect a method and device for controlling a power system client, wherein the client is respectively connected to the power system monitoring platform and at least one terminal connected to the power equipment, and the control method includes the following steps: receiving a plurality of instruction execution information sent by the power system monitoring platform, the instruction execution information including the client control instruction and / or the power equipment terminal control instruction; based on the priority order of the instruction execution information in the real-time status evaluation model of the equipment, performing layered processing on the plurality of instruction execution information, the priority of the power equipment terminal control instruction is higher than the priority of the client control instruction; sending corresponding terminal control instructions to the power equipment terminal connected according to the power equipment terminal control instruction, and receiving response data sent by the power equipment terminal connected; wherein the terminal control instruction includes: data request instruction, device control instruction and configuration update instruction, and the response data includes request data information, operation confirmation information and abnormal alarm information corresponding to the terminal control instruction. The above technical solution has the following effects:

[0106] 1. A real-time status assessment model dynamically prioritizes client control commands and power equipment downstream terminal control commands, ensuring that high-priority tasks (such as equipment emergency control commands) are always executed first. The model dynamically adjusts the command queue based on the equipment's current load rate, criticality coefficient, and historical data prediction results, avoiding the risk of overload of high-load critical equipment due to queuing delays under the traditional fixed priority mechanism.

[0107] 2. To address communication anomalies with downstream devices, the system triggers multi-level fault-tolerant operations based on a first preset time threshold. If a device fails to respond after a timeout, it automatically records a timestamped fault log and sends an offline alarm to the monitoring platform. Simultaneously, it executes pre-set emergency strategies (such as switching to a backup power supply line or disconnecting non-critical loads). This mechanism not only shortens fault location time but also effectively prevents the spread of localized faults through dynamic load transfer and redundant link switching, significantly improving the power system's anti-interference capabilities and continuous operational reliability in complex network environments.

[0108] 3. A modular architecture is used to decouple client control tasks from terminal command processing functions, and dynamic priority coefficient calculation and task preemption mechanism are combined to achieve efficient resource allocation. When the client control command wait times out, the system automatically increases its priority and suspends low-priority tasks (such as periodic status queries), giving priority to critical operations. While reducing system complexity, it takes into account the real-time requirements of multi-tasking concurrent scenarios, allowing the client to quickly respond to monitoring platform commands under high load, thereby improving user experience and power dispatch efficiency.

[0109] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0110] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0111] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0113] 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, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A power system client control method, characterized in that: The client is respectively connected to the power system monitoring platform and at least one power equipment connected terminal for communication. The control method includes the following steps: Receiving a plurality of instruction execution information sent by the power system monitoring platform, wherein the instruction execution information includes a client control instruction and / or a power equipment connected terminal control instruction; Based on the priority order of the instruction execution information in the real-time status evaluation model of the equipment, the plurality of instruction execution information are respectively processed in a hierarchical manner, and the priority of the control instruction of the terminal connected to the power equipment is higher than the priority of the control instruction of the client; Sending corresponding terminal control instructions to the terminal connected to the power equipment according to the control instructions of the terminal connected to the power equipment, and receiving response data sent by the terminal connected to the power equipment; The terminal control instructions include: data request instructions, device control instructions and configuration update instructions, and the response data includes request data information, operation confirmation information and abnormal alarm information corresponding to the terminal control instructions.

2. The power system client control method according to claim 1, characterized in that: After sending the corresponding terminal control instruction to the terminal connected to the power equipment according to the control instruction of the terminal connected to the power equipment, the method further includes: Obtaining the response time of the terminal connected to the power equipment; If no response information is received from the terminal connected to the power equipment within the first preset time threshold, the connection timeout processing measures are executed, and the connection timeout processing measures include: recording a fault log with a timestamp, sending an equipment offline alarm to the power monitoring platform, and executing a preset power load switching operation.

3. The power system client control method according to claim 2, characterized in that: The performing of the preset power load switching operation includes: Automatically switch to backup power supply lines, disconnect non-critical power equipment according to a preset load priority table, and / or initiate load transfer requests to neighboring customers.

4. The power system client control method according to claim 1, characterized in that: Before the layered processing of the plurality of instruction execution information is performed respectively, the method further includes: Obtaining a current load rate of each terminal connected to the power equipment in a current detection cycle; In combination with the criticality level coefficient of the terminal connected to the power equipment, the priority in the equipment real-time status evaluation model is dynamically adjusted based on the current load rate.

5. The power system client control method according to claim 4, characterized in that: The dynamically adjusting the priority in the device real-time status evaluation model based on the current load rate includes: Based on the current load rate and the criticality level coefficient, the dynamic priority coefficient of the terminal connected to the power equipment is calculated. The calculation formula of the dynamic priority coefficient P is: P=λ1×L i +λ2×K i ; Among them, L i is the current load rate of the terminal connected to the i-th power equipment, K i is the criticality level coefficient of the terminal connected to the i-th power equipment, and λ1 and λ2 are the corresponding weight coefficients respectively; The dynamic priority coefficient of each terminal connected to the power equipment in the current detection cycle is updated to the equipment real-time status evaluation model.

6. The power system client control method according to claim 5, characterized in that: Before calculating the dynamic priority coefficient of the terminal connected to the power equipment, the method further includes: Acquire historical data of several terminals connected to the power equipment corresponding to the client; Based on random forest or neural network algorithms, the optimal dynamic priority coefficient is predicted for different combinations of current load rate and criticality coefficient.

7. The power system client control method according to any one of claims 1 to 6, characterized in that: After sending the corresponding terminal control instruction to the terminal connected to the power equipment according to the control instruction of the terminal connected to the power equipment, the method further includes: Execute the client control instruction.

8. The power system client control method according to claim 7, characterized in that: Also includes: Obtaining a waiting time for the client control instruction; When the waiting time of the client control instruction is greater than a second preset time threshold, raising the priority of the client control instruction to the priority of the terminal connected to the power equipment; Pause the current non-critical tasks of the client and give priority to executing the client control instructions; The current non-critical tasks include: data request instructions from terminals connected to low-priority power equipment, non-urgent configuration update instructions, and periodic status query tasks.

9. The power system client control method according to any one of claims 1 to 6, characterized in that: The terminal connected to the power equipment includes one or more of an intelligent circuit breaker with remote opening and closing functions, an intelligent meter supporting dynamic rate measurement, and a photovoltaic grid-connected inverter control device.

10. A power system client control device, characterized in that: The client is controlled based on the power system client control method according to any one of claims 1 to 9, wherein the client is respectively communicatively connected with the power system monitoring platform and at least one terminal connected to the power equipment, and the control device includes: An instruction receiving module, which is used to receive a plurality of instruction execution information sent by the power system monitoring platform, wherein the instruction execution information includes client control instructions and / or power equipment connected terminal control instructions; An instruction grading module is configured to perform hierarchical processing on the plurality of instruction execution information based on the priority order of the instruction execution information in the real-time status evaluation model of the equipment, wherein the priority of the control instruction of the terminal connected to the power equipment is higher than the priority of the control instruction of the client; An instruction processing module, which is used to send corresponding terminal control instructions to the terminal connected to the power equipment according to the control instructions of the terminal connected to the power equipment, and receive response data sent by the terminal connected to the power equipment; The terminal control instructions include: data request instructions, device control instructions and configuration update instructions, and the response data includes request data information, operation confirmation information and abnormal alarm information corresponding to the terminal control instructions.

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