A load shedding and load removal balancing method and system based on low frequency and low voltage

Abstract

The present invention discloses a load shedding and load balancing method and system based on low frequency and low voltage, which relates to the technical field of load shedding and load balancing in power systems. It includes collecting data of the lines to be shed, establishing a dynamic model of the lines to identify the line attributes; clarifying the shedding targets based on the identification results, generating a dynamic load shedding strategy according to the real-time load data, setting the load priorities and matching the required load shedding amount; performing the load shedding operation, and monitoring the shedding effect in real time and uploading the status to the master station. The method of the present invention has accurate line attribute identification, improves the pertinence and effectiveness of the load shedding strategy, enhances the adaptability of the power grid to load fluctuations through the generation of the dynamic load shedding strategy, realizes the closed-loop management of the load shedding operation through real-time monitoring and feedback, and improves the intelligent level of power grid dispatching.

Description

Technical Field

[0001] The present invention relates to the technical field of load shedding load balancing in power systems, and specifically to a load shedding load balancing method and system based on low frequency and low voltage. Background Art

[0002] In recent years, with the continuous expansion of the power grid scale and the increasing growth of power demand, the safe and stable operation of power systems has faced severe challenges. In this context, the load shedding load balancing technology has emerged as an important means to ensure the stable operation of the power grid. This technology reasonably cuts off some loads to maintain the power balance of the system and prevent equipment damage and large-scale power outages caused by overload.

[0003] However, there are many deficiencies in the existing load shedding load balancing methods. When collecting line data and establishing models in the prior art, the dynamic attributes of lines are often ignored, resulting in inaccurate identification of line attributes, thus affecting the selection of shedding targets. When formulating load shedding strategies in the prior art, the full utilization of real-time load data is lacking, and dynamic and efficient load shedding schemes cannot be generated. In addition, the prior art fails to effectively set load priorities, which may affect important loads during the load shedding process. Finally, after performing the load shedding operation, the prior art lacks real-time monitoring and feedback on the shedding effect, making it impossible for the master station to adjust the load shedding strategy in a timely manner. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed.

[0005] Therefore, the technical problems solved by the present invention are: the existing load shedding load balancing methods have inaccurate line attribute identification, insufficient dynamic load shedding strategies, unreasonable load priority setting, and how to achieve real-time monitoring and feedback.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a load shedding load balancing method based on low frequency and low voltage, including collecting data of lines to be shed, establishing a dynamic model of the lines to identify line attributes; clarifying shedding targets based on the identification results, generating a dynamic load shedding strategy according to real-time load data, setting load priorities and matching the required load shedding amount; performing the load shedding operation, and real-time monitoring the shedding effect and uploading the status to the master station.

[0007] As a preferred solution of the load shedding load balancing method based on low frequency and low voltage according to the present invention, wherein: the data of the lines to be shed includes real-time data and historical data; the real-time data includes active power, reactive power, and real-time frequency volatility; the historical data includes load change curves and power direction switching frequencies.

[0008] As a preferred solution of the load shedding load balancing method based on low frequency and low voltage according to the present invention, wherein: establishing the dynamic model of the line includes dynamically matching the collected real-time data and historical data, and the system establishes the dynamic model of the line and identifies the attributes of the line, including the load line attributes and the power supply line attributes, expressed as:

[0009] ,

[0010] Wherein, represents the predicted value of the line dynamic model at time , which is used to reflect the real-time load fluctuation trend and provide a basis for generating subsequent load shedding strategies. is the prediction time window length. is the total number of lines, representing the number of load lines or power supply lines in the current power grid. is the th line's historical load change curve at time . is the historical power direction switching frequency, representing the frequency of power direction change of the th line, which is used to capture the dynamic characteristics of the line. is the real-time frequency volatility. is the th line's real-time active power. is the th line's real-time reactive power. is the imaginary unit. is the th line's weight factor; based on the established dynamic model of the line, the line attributes are identified.

[0011] When , it is determined that the line is a load line. is the threshold of the dynamic response degree of the load line.

[0012] When and the fluctuation range is lower than , it is determined that the line is a power supply line. is the non-linear characteristic threshold of the stable load of the power supply line. is the maximum fluctuation value of the steady range of the complex power amplitude.

[0013] As a preferred solution of the load shedding load balancing method based on low frequency and low voltage according to the present invention, wherein: generating the dynamic load shedding strategy includes combining the real-time load data with the prediction result of the dynamic model and allocating the load shedding priority according to the fluctuation characteristics of the load type, expressed as:

[0014] ,

[0015] Among them, is the load shedding priority allocation strategy representing the moment. The higher the value, the higher the load shedding priority. is the number of total load types. is the dynamic adjustment factor of the load type is the dynamic adjustment factor of the load type is the dynamic adjustment factor of the load type is the real-time load fluctuation value of the load type at the moment The higher the value, the higher the load shedding priority. is the fluctuation sensitivity parameter of the load type is the fluctuation sensitivity parameter of the load type is the fluctuation change function of the load type is the fluctuation change function of the load type is the dynamic compensation coefficient. is the predicted value of the line dynamic model at time The higher the value, the higher the load shedding priority. is the load shedding capacity demand sent by the master station at the moment The load type The fluctuation change function of the load type is expressed as:

[0016] ,

[0017] Among them, is the weight of the real-time load fluctuation value. is the weight of the second-order change rate of the historical load curve. is the load type at the moment The second-order change rate of the historical load curve.

[0018] As a preferred solution of the load shedding and load balancing method based on low frequency and low voltage described in the present invention, among them: the setting of load priority and matching of the required load shedding amount includes when , the load type is a safety load, and the safety load is never shed; when , the load type is a livelihood load, and a lower priority is taken during the non-peak period; during the peak period, it is dynamically adjusted according to the fluctuation change; when , the load type is a production load, which is divided according to the energy consumption gradient, and the secondary production load is shed first; when , the load type is an adjustable load, and the adjustable load is shed first.

[0019] As a preferred solution of the load shedding and load balancing method based on low frequency and low voltage according to the present invention, wherein: the execution of load shedding operation includes that when receiving a load shedding instruction from the master station, the system selects the load lines to be cut according to the priority matching algorithm, and uses the low frequency and low voltage load shedding device to implement the cutting operation; if the load shedding operation does not meet the required load shedding capacity demand issued by the master station at time, the system starts an error correction mechanism to automatically supplement the cutting of adjustable load lines, which is expressed as:

[0020] ,

[0021] wherein, is the error compensation value at time , is the cut-off amount of the -th type of load at time , representing the specific value of the executed load shedding, is the total cut-off load amount before the -th round, is the dynamic compensation coefficient, is the load recovery rate, is the residual capacity influence coefficient, is the remaining capacity of the system, representing the load amount that has not been cut off but can be used as compensation; if the total load shedding amount after the current cut-off meets , it is expressed as:

[0022] ,

[0023] then stop the load shedding operation.

[0024] As a preferred solution of the load shedding and load balancing method based on low frequency and low voltage according to the present invention, wherein: the real-time monitoring of the cutting effect and uploading the status to the master station includes that the system real-time monitors the execution status of the load shedding action through the load shedding device, including the load shedding amount, line status, load recovery situation, and regularly uploads the relevant data to the master station.

[0025] Another object of the present invention is to provide a load shedding and load balancing system based on low frequency and low voltage, which can clarify the cutting target based on the recognition result, generate a dynamic load shedding strategy according to the real-time load data, set the load priority and match the required load shedding amount, and solves the problem of insufficient dynamics in the current load shedding and load balancing technology.

[0026] As a preferred solution of the load shedding and load balancing system based on low frequency and low voltage according to the present invention, wherein: it includes

[0027] a computer device, including a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the steps of the load shedding and load balancing method based on low frequency and low voltage.

[0028] A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of a load shedding and load balancing method based on low frequency and low voltage are implemented.

[0029] Advantages of the present invention: The load shedding and load balancing method based on low frequency and low voltage provided by the present invention improves the pertinence and effectiveness of the load shedding strategy through accurate line attribute identification, enhances the adaptability of the power grid to load fluctuations through the generation of dynamic load shedding strategies, realizes the closed-loop management of load shedding operations through real-time monitoring and feedback, and improves the intelligent level of power grid dispatching. The present invention achieves better effects in terms of efficiency, reliability, and intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0031] Figure 1 It is the overall flowchart of a load shedding and load balancing method based on low frequency and low voltage provided for the first embodiment of the present invention.

[0032] Figure 2 It is the overall flowchart of a load shedding and load balancing system based on low frequency and low voltage provided for the third embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention will be described in detail below with reference to the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0034] Embodiment 1, referring to Figure 1 , which is an embodiment of the present invention, provides a load shedding and load balancing method based on low frequency and low voltage, including:

[0035] S1: Collect data of the line to be shed, establish a dynamic model of the line, and identify the line attributes.

[0036] Furthermore, the data of the line to be shed includes real-time data and historical data; the real-time data includes active power, reactive power, and real-time frequency volatility; the historical data includes the load change curve and the power direction switching frequency.

[0037] It should be noted that establishing the dynamic model of the line includes dynamically matching the collected real-time data and historical data, and the system establishes the dynamic model of the line to identify the attributes of the line, including the load line attributes and the power supply line attributes, which are expressed as:

[0038] ,

[0039] Among them, represents the predicted value of the line dynamic model at time , which is used to reflect the real-time load fluctuation trend and provide a basis for generating subsequent load shedding strategies. is the length of the prediction time window. is the total number of lines, indicating the number of load lines or power supply lines in the current power grid. is the th line's historical load change curve at time . is the historical power direction switching frequency, indicating the frequency of power direction change of the th line, which is used to capture the dynamic characteristics of the line. is the real-time frequency volatility. is the real-time active power of the th line. is the real-time reactive power of the th line. is the imaginary unit. is the weight factor of the th line; based on the established dynamic model of the line, line attribute identification is carried out.

[0040] When , the line is determined to be a load line. is the threshold of the dynamic response degree of the load line.

[0041] When and the fluctuation range is lower than , the line is determined to be a power supply line. is the non-linear characteristic threshold for the load stability of the power supply line. is the maximum fluctuation value of the steady range of the complex power amplitude.

[0042] It should also be noted that by collecting the real-time data and historical data of the line to be disconnected, establishing the dynamic model of the line and identifying the line attributes, the accurate grasp of the power grid operation state is realized, which can provide accurate basic data for subsequent load shedding strategies. In this way, the accuracy of line attribute identification is improved, and the mistakes of load shedding strategies caused by misidentification are reduced, thus ensuring the stable operation of the power grid and power supply reliability.

[0043] S2: Based on the recognition result, clarify the excision target, generate a dynamic load shedding strategy according to the real-time load data, set the load priority, and match the required load shedding amount.

[0044] Furthermore, generating the dynamic load shedding strategy includes combining the real-time load data with the dynamic model prediction result, and allocating the load shedding priority according to the fluctuation characteristics of the load type, expressed as:

[0045] ,

[0046] where, is the load shedding priority allocation strategy at time , the higher the value, the higher the load shedding priority, is the total number of load types, is the load type 's dynamic adjustment factor, is the load type at time 's real-time load fluctuation value, is the load type 's fluctuation sensitivity parameter, is the load type 's fluctuation change function, is the dynamic compensation coefficient, is the predicted value of the line dynamic model at time , is the load capacity demand to be shed issued by the master station at time ; the fluctuation change function of the load type is expressed as:

[0047] ,

[0048] where, is the weight of the real-time load fluctuation value, is the weight of the second-order change rate of the historical load curve, is the load type at time 's second-order change rate of the historical load curve.

[0049] It should be noted that setting the load priority and matching the required load shedding amount includes that when , the load type is a safety load, and the safety load is never shed; when , the load type is a livelihood load, and a lower priority is taken during the non-peak period; during the peak period, it is dynamically adjusted according to the fluctuation change; when , the load type is a production load, which is divided according to the energy consumption gradient, and the secondary production load is shed first; when When the load type is adjustable load, the adjustable load is preferentially shed.

[0050] It should also be noted that based on the recognition result, the shedding target is clarified, and a dynamic load shedding strategy is generated according to the real-time load data. The load priority is set and the required load shedding amount is matched, realizing the intelligence and refinement of the load shedding operation. The load shedding scheme can be dynamically adjusted according to the actual operation conditions of the power grid, improving the flexibility and adaptability of the load shedding strategy, ensuring that load shedding can be effectively implemented under different operating states of the power grid. At the same time, by setting the load priority, the power supply of important loads is guaranteed not to be affected, and the power supply service quality is improved.

[0051] S3: Execute the load shedding operation, and monitor the shedding effect in real time and upload the status to the master station.

[0052] Furthermore, the execution of the load shedding operation includes that when receiving the load shedding instruction from the master station, the system selects the load line to be shed according to the priority matching algorithm, and uses the low-frequency and low-voltage load shedding device to implement the shedding operation; if the load shedding operation does not reach the required load shedding capacity demand issued by the master station at time The system starts the error correction mechanism and automatically supplements the shedding of the adjustable load line, which is expressed as:

[0053] ,

[0054] where is the error compensation value at time , is the shed amount of the th type of load at time , representing the specific value of the executed load shedding, is the total shed load amount before the th round, is the dynamic compensation coefficient, is the load recovery rate, is the residual capacity influence coefficient, is the remaining capacity of the system, representing the load amount that has not been shed but can be used as compensation; if the total load shedding amount after the current shedding meets , it is expressed as:

[0055] ,

[0056] then stop the load shedding operation.

[0057] It should be noted that monitoring the shedding effect in real time and uploading the status to the master station includes that the system monitors the execution status of the load shedding action through the load shedding device in real time, including the load shedding amount, line status, and load recovery situation, and regularly uploads the relevant data to the master station.

[0058] It should also be noted that performing the load shedding operation and real-time monitoring of the removal effect and uploading the status to the master station ensure the timeliness and effectiveness of the load shedding operation, can provide real-time feedback on the load shedding effect, provide decision-making support for power grid dispatching, improve the response speed of the load shedding operation, ensure that the load shedding measures can be implemented quickly and effectively, and enhance the closed-loop control ability of the power grid dispatching system through real-time monitoring and status uploading, thereby improving the overall operation efficiency and safety of the power grid.

[0059] Embodiment 2 is an embodiment of the present invention, which provides a load shedding removal load balancing method based on low frequency and low voltage. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0060] First, six representative power grid lines (Line 1 to Line 6) were selected as the research objects. First, through the sensors installed on each line, data such as active power, reactive power, and frequency volatility were collected in real time. At the same time, the historical load change curves and power direction switching frequencies of each line were collected. Based on these data, using the proposed dynamic model establishment method, the dynamic characteristics of each line were modeled. During the model establishment process, special attention was paid to the identification of the load and power source attributes of the line. Through the set threshold, the load line and the power source line were successfully distinguished. Then, according to the real-time load data and combined with the dynamic model prediction results, a load shedding priority strategy for each line was generated. This strategy considered the importance of different types of loads, classified the loads into safety loads, livelihood loads, production loads, and adjustable loads, and dynamically adjusted the load shedding priority according to the real-time situation. When performing the load shedding operation, the system implemented the removal operation on the selected line through the low frequency and low voltage load shedding device according to the priority matching algorithm. During the removal process, the removal effect was monitored in real time, and information such as the removal status, removal amount, and line status was uploaded to the master station through the communication system. If the actual removal amount did not reach the predetermined target, the system would start the error correction mechanism and automatically supplement the removal of the adjustable load line until the requirement was met. Refer to Table 1 for recording and analyzing the experimental data.

[0061] Table 1 Experimental data record form

[0062]

[0063] The acquisition of real-time active power and reactive power provides accurate basic data for the establishment of the dynamic model. For example, the active power of Line 1 is 120 kW and the reactive power is 50 kVar. Through model analysis, its load shedding priority is set to 0.85, indicating that this line has a high priority in load shedding operations. The combined use of the historical load change curve and the power direction switching frequency effectively improves the accuracy of line attribute identification. The power direction switching frequencies of Line 2 and Line 3 are 6 times / hour and 7 times / hour respectively, indicating that the dynamic characteristics of these two lines are relatively significant, so they are appropriately considered in the load shedding strategy. The setting of the load shedding priority ensures that the power supply to important loads is not affected. For example, for Line 4 and Line 5, although their real-time active power is high, due to being classified as livelihood loads and production loads, their load shedding priorities are relatively low, effectively ensuring the continuity and reliability of power supply. The data of the actually shed loads shows that the method of the present invention can effectively adjust the load shedding amount according to the actual situation of the power grid. For example, 50 kW of load is actually shed from Line 6, achieving the expected load shedding target.

[0064] Example 3, referring to Figure 2 , which is an embodiment of the present invention, provides a load shedding and load balancing system based on low frequency and low voltage, including a line identification module, a dynamic load shedding module, and a real-time monitoring module.

[0065] Among them, the line identification module is used to collect data of the lines to be shed, establish a dynamic model of the lines to identify line attributes; the dynamic load shedding module is used to clarify the shedding target based on the identification result, generate a dynamic load shedding strategy according to real-time load data, set the load priority and match the required load shedding amount; the real-time monitoring module is used to perform load shedding operations, monitor the shedding effect in real time and upload the status to the master station.

[0066] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. And the aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, etc., which can store program codes.

[0067] The logic and / or steps represented in the flowchart or otherwise described herein can, for example, be considered as a definitional sequence of executable instructions for implementing logical functions, and can be embodied specifically in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0068] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection (electronic device) having one or more wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which a program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then storing it in a computer memory.

[0069] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc. It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

[0070] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A load shedding and load balancing method based on low frequency and low voltage, characterized in that: include: Collect data of the line to be cut, establish a dynamic model of the line and identify line attributes; Based on the identification results, the removal target is clearly defined, and a dynamic load reduction strategy is generated according to the real-time load data to set the load priority and match the required load reduction amount; Execute load shedding operations, monitor the shedding effect in real time and upload the status to the master station; The establishment of the dynamic model of the line includes dynamically matching the collected real-time data with the historical data, and the system establishes the dynamic model of the line, identifies the attributes of the line, including the load line attributes and the power line attributes, which are expressed as: Where D(t) represents the predicted value of the line dynamic model at time t, which is used to reflect the real-time load fluctuation trend and provide a basis for the subsequent generation of load reduction strategies. T is the length of the prediction time window, n is the total number of lines, indicating the number of load lines or power lines in the current power grid, and H i (t) is the historical load variation curve of the i-th line at time t, F s is the historical power direction switching frequency, which indicates the frequency of power direction changes of the ith line and is used to capture the dynamic characteristics of the line. r is the real-time frequency fluctuation rate, P act,i is the real-time active power of the ith line, P react,i is the real-time reactive power of the i-th line, j is the imaginary unit, λ i is the weight factor of the ith line; Identify route attributes based on the established dynamic model of the route; when When , the line is determined to be a load line, and τ1 is the dynamic response threshold of the load line; When tanh(λ i H i (t))<τ2 and When the fluctuation range is lower than Δsource, the line is determined to be a power line. τ2 is the nonlinear characteristic threshold of the power line load stability. Δ source is the maximum fluctuation value of the stable range of complex power amplitude; The generation of dynamic load shedding strategy includes combining real-time load data with dynamic model prediction results and assigning load shedding priority according to the fluctuation characteristics of load types, which is expressed as: Among them, P r (t) represents the load shedding priority allocation strategy at time t. The higher the value, the higher the priority of load shedding. m is the number of total load types. η k is the dynamic adjustment factor of load type k, L k (t) is the real-time load fluctuation value of load type k at time t, β k is the fluctuation sensitivity parameter of load type k, f k (t) is the fluctuation function of load type k, ξ is the dynamic compensation coefficient, D(t) is the line dynamic model prediction value at time t, C d is the load shedding capacity requirement issued by the master station at time t; The fluctuation function of load type k is expressed as: Among them, α k is the real-time load fluctuation value weight, γ k is the second-order change rate weight of the historical load curve, H k (t) is the second-order rate of change of the historical load curve of load type k at time t.

2. The load balancing method based on low frequency and low voltage load shedding as claimed in claim 1, characterized in that: The line data to be cut includes real-time data and historical data; Real-time data includes active power, reactive power, and real-time frequency fluctuation rate; Historical data includes load change curves and power direction switching frequency.

3. The load balancing method based on low frequency and low voltage load shedding as claimed in claim 1, characterized in that: The setting of load priority and matching the required load reduction amount includes: <P r When (t)≤0.25, the load type is safety load, and the safety load will never be cut off; When 0.25 <P r When (t)≤0.5, the load type is livelihood load, and a lower priority is taken during non-peak hours; during peak hours, dynamic adjustments are made according to fluctuations; When 0.5 <P r When (t)≤0.75, the load type is production load, divided according to the energy consumption gradient, the secondary production load is cut off first; when 0.75 <P r When (t)<1, the load type is adjustable load, and the adjustable load is cut off first.

4. The load balancing method based on low frequency and low voltage load shedding as claimed in claim 3 is characterized in that: The execution of the load shedding operation includes, when receiving the load shedding instruction from the master station, the system selects the load line to be shedding according to the priority matching algorithm, and performs the shedding operation by using the low-frequency and low-voltage load shedding device; If the load shedding operation does not reach the load shedding capacity requirement issued by the master station at time t, the system starts the error correction mechanism and automatically supplements the shedding of the adjustable load line, which is expressed as: Where E(t) is the error compensation value at time t, R k (t) is the amount of load of the kth type removed at time t, indicating the specific value of load reduction execution, q is the total load removed in the first q rounds, ξ is the dynamic compensation coefficient, R r is the load recovery rate, ζ is the residual capacity influence coefficient, R c The remaining capacity of the system indicates the amount of load that has not been removed but can be used as compensation; If the total load reduction after the current shedding meets C d , expressed as: The load shedding operation is stopped.

5. The load balancing method based on low frequency and low voltage load shedding as claimed in claim 4, characterized in that: The real-time monitoring of the shedding effect and uploading of the status to the main station includes the system monitoring the execution status of the load shedding action in real time through the load shedding device, including the load shedding amount, line status, and load recovery status, and uploading the relevant data to the main station regularly.

6. A system using the load shedding and load balancing method based on low frequency and low voltage as claimed in any one of claims 1 to 5, characterized in that: Including line identification module, dynamic load reduction module, and real-time monitoring module; The line identification module is used to collect data of the line to be cut, establish a dynamic model of the line and identify line attributes; The dynamic load shedding module is used to clarify the removal target based on the identification result, generate a dynamic load shedding strategy according to the real-time load data, set the load priority and match the required load shedding amount; The real-time monitoring module is used to perform load shedding operations, monitor the shedding effect in real time and upload the status to the main station.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the load shedding and load balancing method based on low frequency and low voltage are implemented as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the load shedding and load balancing method based on low frequency and low voltage are implemented as described in any one of claims 1 to 5.

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