Multi-target optimization operation regulation and control method, system and equipment for distribution and micro-power cooperation and medium

Abstract

The invention discloses a multi-target optimization operation regulation and control method, system and device for distribution and micro-power cooperation, and a medium, and relates to the technical field of power grid operation control. The method comprises the following steps: acquiring real-time micro-distribution data of a power distribution network and a micro-grid, and calculating a voltage deviation value, power loss and average load according to the real-time micro-distribution data; constructing a power evaluation model based on the voltage deviation value, the power loss and the average load, and performing evaluation to obtain a first evaluation result; generating a regulation and control strategy based on the first evaluation result; and optimizing a regulation and control strategy in real time according to user feedback and a monitoring result. The differential regulation and control strategy is generated by constructing the comprehensive evaluation model and combining threshold grading, and the strategy is optimized in real time according to the user feedback and the monitoring result, so that the defects of single target optimization, insufficient dynamic adaptability, low user participation degree and the like in the prior art are overcome; and collaborative quantitative evaluation and accurate regulation and control of voltage quality, power loss and load balance are realized.

Description

Technical Field

[0001] The present invention relates to the field of power grid operation control technology, and in particular to a multi-objective optimization operation control method, system, equipment and medium for distribution and micro-cooperation. Background Art

[0002] As the "last mile" connecting the transmission network and users, the distribution network's operational stability, economy and reliability directly affect users' electricity experience and energy efficiency. With the large-scale access of distributed energy and the rapid growth of nonlinear loads, the coordinated operation of distribution networks and microgrids has become the core direction of smart grid development. As the key link connecting the transmission network and users, the distribution network plays an important role in power distribution and load support; while the microgrid, as an autonomous system including distributed power sources, energy storage devices and loads, can be flexibly connected to the grid or operate in an isolated manner. The coordinated optimization of the two is of great significance to improving energy utilization efficiency and ensuring grid stability.

[0003] Traditional control methods face the following challenges: Limitations of single-target optimization: Existing methods mostly target single targets such as voltage deviation or power loss, and lack the coordinated optimization of voltage, loss, and load balance, which can easily lead to problems such as "voltage meets standards but losses increase" or "load is balanced but voltage exceeds the limit"; Insufficient dynamic adaptability: Relying on preset thresholds and fixed strategies, it is difficult to cope with uncertain factors such as fluctuations in new energy output and sudden load changes. In scenarios with high photovoltaic penetration, traditional strategies may cause voltage surges due to failure to adjust reactive compensation in a timely manner, or cause equipment overload due to load forecast deviations. Summary of the Invention

[0004] In response to the above problems, the present invention provides a multi-objective optimization operation control method, system, equipment and medium for micro-cooperation.

[0005] The present invention provides the following technical solutions:

[0006] A multi-objective optimization operation and control method for distribution and microgrid collaboration includes obtaining real-time distribution and microgrid data of the distribution network and microgrid, and calculating the voltage deviation value, power loss and average load based on the real-time distribution and microgrid data; constructing a power evaluation model based on the voltage deviation value, power loss and average load and performing an evaluation to obtain a first evaluation result; generating a control strategy based on the first evaluation result; and optimizing the control strategy in real time based on user feedback and monitoring results.

[0007] The real-time distribution data is obtained through the built-in sensors in the distribution network and microgrid; the voltage deviation value refers to the degree of deviation between the actual voltage value of each node in the distribution network and microgrid and the rated voltage value; the power loss refers to the power loss of the distribution network and microgrid during the power transmission process; the average load refers to the average active power demand in the distribution network and microgrid.

[0008] Based on the voltage deviation value, power loss and average load, a power evaluation model is constructed, which includes the following steps: calculating the voltage deviation degree by comparing the real-time actual voltage of each node in the distribution network and microgrid with the rated voltage. The specific formula is as follows:

[0009]

[0010] Where, δ V is the voltage deviation value; V a is the actual voltage of the node in real time; V r is the node rated voltage;

[0011] Taking into account the line resistance loss and transformer loss, the total power loss is the sum of the line loss and transformer loss. The specific formula is as follows:

[0012]

[0013] Where, P total is the total power loss of the distribution network and microgrid; n is the number of segmented lines; I i is the current of the i-th line; R i is the resistance of the i-th line; P0 is the no-load loss of the transformer; P k Transformer rated short-circuit loss; S is the actual power of the transformer; S N is the rated capacity of the transformer;

[0014] The arithmetic mean of the active power data collected during the statistical period is calculated using the following formula:

[0015]

[0016] Where, is the average active power; m is the number of power acquisition times; P j is the active power collected for the jth time;

[0017] A comprehensive evaluation is conducted based on voltage deviation, power loss, and average load, and a power evaluation model is constructed.

[0018] The specific formula of the power evaluation model is as follows:

[0019]

[0020] Where E is the first evaluation result; w1, w2 and w3 are weight coefficients, representing the relative importance of voltage deviation, power loss and average load respectively; δ V is the voltage deviation value; P total is the total power loss of the distribution network and microgrid; is the average active power.

[0021] The specific steps for generating a control strategy based on the first evaluation result are as follows: comparing the voltage deviation value, power loss and average load in the first evaluation result with the set threshold value; generating a control strategy based on the severity of each indicator; using simulation software to simulate and evaluate the control strategy; optimizing and improving the control strategy based on the evaluation results to form a final control strategy plan.

[0022] The specific situation of comparing the voltage deviation value, power loss and average load in the first evaluation result with the set threshold value is as follows:

[0023] When the first evaluation result is less than the first threshold, it means that the voltage of each node is close to the rated value, the power loss is at the historical lowest range, the average load is within the equipment operating range, and the distribution network and microgrid are in an ideal operating state. Continuous detection is sufficient;

[0024] If the first evaluation result is greater than the first threshold and less than the second threshold, it means that at least one indicator has exceeded the first threshold. A level 1 warning message is sent to maintenance personnel for further analysis:

[0025] If the voltage deviation exceeds the first threshold and is less than the second threshold, it indicates that the equipment is unstable and the equipment parameters should be recorded and analyzed. If the power loss exceeds the first threshold and is less than the second threshold, it indicates that the power loss of the line has increased and a comprehensive inspection of the line should be carried out, and the load distribution should be adjusted. If the average load exceeds the first threshold and is less than the second threshold, it indicates that the load factor of the transformer has increased and the real-time load changes should be monitored immediately to understand the load changes in real time.

[0026] When the first assessment result is greater than the second threshold, it means that at least one indicator has exceeded the second threshold, and a second-level warning message is sent to maintenance personnel for further analysis:

[0027] When the voltage deviation exceeds the second threshold, the emergency plan is immediately activated: use reactive power compensation devices to increase the supply of reactive power, isolate the faulty line, and notify professional technicians to conduct on-site inspections; when the power loss exceeds the second threshold, the operation of the equipment is immediately stopped, and the backup equipment is started at the same time, and professional maintenance personnel are notified to repair the faulty equipment; when the average load exceeds the second threshold, emergency load reduction measures are immediately taken, giving priority to cutting off non-critical loads, starting the backup power supply, adjusting the operating status of the equipment, and closely monitoring the transformer equipment.

[0028] Executing the control strategy and building a dynamic closed-loop feedback optimization mechanism include the following steps: collecting feedback for the control strategy and monitoring the real-time micro-distribution data after control; comparing the control targets to determine whether the voltage, loss and load meet the standards; if not, adjusting the equipment parameters or calling the historical effective strategy, and rechecking the real-time micro-distribution data and user feedback based on the adjusted strategy; if the standards are met, adding the control strategy to the common strategy library.

[0029] The multi-objective optimization operation and control system of the micro-distribution collaboration includes:

[0030] The data acquisition module is used to obtain real-time distribution data of the distribution network and microgrid, and calculate the voltage deviation value, power loss and average load based on the real-time distribution data;

[0031] A model building module is used to build a power evaluation model based on the voltage deviation value, power loss and average load, and perform evaluation to obtain a first evaluation result;

[0032] A strategy generation module, configured to generate a control strategy based on the first evaluation result;

[0033] The feedback optimization module is used to optimize the control strategy in real time based on user feedback and monitoring results.

[0034] A computer device includes a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, the multi-objective optimization operation control method of the micro-device collaboration is implemented.

[0035] A computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, the multi-objective optimization operation control method of the micro-cooperation is implemented.

[0036] During operation, the present invention collects data in real time through sensors to calculate voltage deviation, power loss and average load, constructs a comprehensive evaluation model and generates differentiated control strategies in combination with threshold grading. At the same time, the strategy is optimized in real time according to user feedback and monitoring results, breaking through the defects of single-target optimization, insufficient dynamic adaptability and low user participation in existing technologies, realizing coordinated quantitative evaluation and precise control of voltage quality, power loss and load balance, taking into account grid security, economy and user experience, and being suitable for distribution networks and microgrids in multiple scenarios, significantly improving operating efficiency and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0038] Figure 1 is a flow chart of the method of the present invention;

[0039] Figure 2 It is a dynamic adjustment diagram of the control strategy. DETAILED DESCRIPTION

[0040] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0041] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0042] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0043] Example 1

[0044] Reference Figure 1 and Figure 2 , a multi-objective optimization operation control method for distribution and micro-cooperation is provided for the first embodiment of the present invention, comprising the following steps:

[0045] S1: Obtain real-time distribution data of the distribution network and microgrid, and calculate the voltage deviation, power loss and average load based on the real-time distribution data.

[0046] Preferably, real-time distribution network and microgrid data are obtained through sensors built into the distribution network and microgrid.

[0047] Furthermore, the voltage deviation value refers to the degree of deviation between the actual voltage value of each node in the distribution network and the microgrid and the rated voltage value.

[0048] Furthermore, power loss refers to the power loss in the distribution network and microgrid during the power transmission process.

[0049] Furthermore, average load refers to the average active power demand in the distribution network and microgrid.

[0050] It should be noted that the sensors include voltage sensors, current sensors and active power sensors.

[0051] S2: Constructing a power evaluation model based on the voltage deviation value, power loss and average load and performing an evaluation to obtain a first evaluation result.

[0052] Preferably, a power evaluation model is constructed based on the voltage deviation value, power loss and average load, including the following steps: calculating the voltage deviation degree by comparing the real-time actual voltage of each node in the distribution network and microgrid with the rated voltage. The specific formula is as follows:

[0053]

[0054] Where, δ V is the voltage deviation value; V a is the actual voltage of the node in real time; V r is the node rated voltage.

[0055] Taking into account the line resistance loss and transformer loss, the total power loss is the sum of the line loss and transformer loss. The specific formula is as follows:

[0056]

[0057] Where, P total is the total power loss of the distribution network and microgrid; n is the number of segmented lines; I i is the current of the i-th line, which reflects the line load condition; R i is the resistance of the i-th line; P0 is the transformer no-load loss, that is, the transformer excitation and core loss; P k The rated short-circuit loss of the transformer is the winding loss under rated load; S is the actual power of the transformer; S N is the rated capacity of the transformer.

[0058] The arithmetic mean of the active power data collected during the statistical period is calculated using the following formula:

[0059]

[0060] Where, is the average active power; m is the number of power acquisition times; P j is the active power collected for the jth time, which is used to reflect the instantaneous active load.

[0061] A comprehensive evaluation is conducted based on voltage deviation, power loss, and average load, and a power evaluation model is constructed.

[0062] Furthermore, the specific formula of the power evaluation model is as follows:

[0063]

[0064] Where E is the first evaluation result; w1, w2 and w3 are weight coefficients, representing the relative importance of voltage deviation, power loss and average load respectively; δ V is the voltage deviation value; P total is the total power loss of the distribution network and microgrid; is the average active power.

[0065] It should be noted that the weight coefficients w1, w2 and w3 are determined according to the degree of variation of each indicator data. The greater the degree of variation, the more information the indicator provides and the greater the weight.

[0066] Preferably, multi-objective conflicts are quantified and optimization priorities are dynamically assigned through weight coefficients.

[0067] S3: Generate a control strategy based on the first evaluation result.

[0068] Preferably, the specific steps of generating the control strategy based on the first evaluation result are as follows: comparing the voltage deviation value, power loss and average load in the first evaluation result with the set threshold value;

[0069] Generate regulatory strategies based on the severity of each indicator;

[0070] Use simulation software to simulate and evaluate control strategies;

[0071] Optimize and improve the control strategy based on the evaluation results to form the final control strategy plan.

[0072] Furthermore, the specific situation of comparing the voltage deviation value, power loss and average load in the first evaluation result with the set threshold value is as follows:

[0073] When the first evaluation result is less than the first threshold, it means that the voltage of each node is close to the rated value, the power loss is in the historical lowest range, the average load is within the equipment operating range, the distribution network and the microgrid are in an ideal operating state, and continuous detection is carried out.

[0074] If the first evaluation result is greater than the first threshold and less than the second threshold, it means that at least one indicator has exceeded the first threshold. A level 1 warning message is sent to maintenance personnel for further analysis:

[0075] If the voltage deviation value exceeds the first threshold and is less than the second threshold, it indicates that the equipment is unstable and the equipment parameters are recorded and analyzed. First, try to adjust the tap of the on-load tap-changing transformer, gradually adjust the voltage, check the operation of the reactive power compensation device, increase the number of capacitor groups to improve the power factor, reduce reactive power loss, and thus increase the voltage. During the adjustment process, closely monitor the voltage changes. If the voltage still does not return to normal after adjustment, the line needs to be modified.

[0076] If the power loss exceeds the first threshold and is less than the second threshold, it means that the power loss of the line has increased. A comprehensive inspection of the line should be carried out, including measuring the resistance of the wires and checking the connection conditions of the joints. By adjusting the load distribution, the single-phase load should be evenly distributed to the three phases to reduce the imbalance of the three-phase current, optimize the configuration of the reactive compensation device, and reasonably adjust the number of capacitor groups according to the actual load conditions and power factor. The trend of increasing losses should be analyzed. If the losses continue to rise, the aging lines should be replaced.

[0077] If the average load exceeds the first threshold and is less than the second threshold, it means that the load rate of the transformer has increased. Immediately monitor the real-time changes in the load, grasp the changes in the load in real time, communicate with users in the area, understand the reasons for the increase in electricity demand, correct any illegal electricity use, and reduce the burden on the transformer by adjusting the power consumption time of some non-important loads. If the load is still too high, start the standby transformer and transfer part of the load to the standby transformer.

[0078] When the first assessment result is greater than the second threshold, it means that at least one indicator has exceeded the second threshold, and a second-level warning message is sent to the maintenance personnel for further analysis: When the voltage deviation value exceeds the second threshold, the emergency plan is immediately activated: Immediately activate the emergency plan, first put all available reactive power compensation devices into use, increase the supply of reactive power, and increase the voltage. If the voltage still cannot return to normal, quickly isolate the faulty line to avoid affecting the power supply of other areas, notify professional and technical personnel to go to the site for investigation, check whether the line has short circuit, grounding and other faults, and carry out emergency repairs or modifications to the line.

[0079] When the power loss exceeds the second threshold, the operation of the equipment is stopped immediately, the power supply is cut off to prevent the fault from expanding, the backup equipment is started to ensure the continuity of power supply, and professional maintenance personnel are notified to inspect the faulty equipment and replace the damaged parts. During the inspection and maintenance process, the entire distribution network and microgrid are comprehensively inspected to check whether there are other potential fault hazards.

[0080] When the average load exceeds the second threshold, emergency load reduction measures will be taken immediately, with non-critical loads given priority, and the backup power supply started to ensure the normal operation of core businesses. Communicate with data center managers to understand business needs, reasonably adjust the operating status of equipment, and closely monitor equipment such as transformers to ensure that they operate within a safe range. If the load is still too high, increase the capacity of the backup power supply or expand and transform the power supply system.

[0081] Preferably, differentiated control strategies are generated according to risk levels to match equipment action costs with risk consequences, reduce ineffective control, and lower equipment maintenance costs.

[0082] S4: Optimize control strategies in real time based on user feedback and monitoring results.

[0083] Preferably, the control strategy is optimized in real time according to user feedback and monitoring results, including the following steps: collecting feedback for the control strategy and monitoring the real-time micro-matching data after the control.

[0084] Compare with the control targets to determine whether the voltage, loss and load meet the standards.

[0085] If the standards are not met, adjust the device parameters or call the historical effective strategy. According to the adjusted control strategy, check the real-time micro-distribution data and user feedback again.

[0086] If the standards are met, the control strategy will be added to the common strategy library.

[0087] It should be noted that the equipment includes reactive power compensation equipment, transformers and related control equipment, load control equipment, backup power supply equipment and line control equipment.

[0088] Preferably, the participation in demand response is improved, historical strategy experience is accumulated, and the efficiency of system regulation is improved with the running time.

[0089] In a specific embodiment, it is assumed that in a certain power supply area of ​​a distribution network in a certain town, an intelligent monitoring system continuously collects data such as line voltage and power loss. The system calculates and finds that although the voltage deviation value of a certain line has not exceeded the first threshold value at a single time, during the continuous 8-hour monitoring, the deviation shows a trend of continuously approaching the first threshold value and the rate of change gradually increases. Based on the comprehensive judgment of the power assessment model, the system determines that the impact of this indicator on the operating status of the distribution network has reached a level that requires attention, and immediately sends a first-level warning to the operation and maintenance personnel. After receiving the warning, the operation and maintenance personnel immediately check and find that the transformer tap in a certain area has poor contact, and make timely adjustments and repairs, thereby avoiding the voltage deviation from further deteriorating to breaking through the second threshold, effectively ensuring the stability and reliability of electricity use for residents in the area, and preventing damage to electrical appliances or power supply failures caused by voltage problems.

[0090] In an embodiment of the present application, the first threshold is determined based on the normal adjustment capability margin of the equipment and the upper limit of the normal range of historical operating data, and the second threshold is an absolute critical value based on the safe operation limit of the equipment.

[0091] In summary, the present invention calculates voltage deviation, power loss and average load through real-time data collection by sensors, constructs a comprehensive evaluation model and generates differentiated control strategies in combination with threshold grading. At the same time, the strategy is optimized in real time according to user feedback and monitoring results, breaking through the defects of single-target optimization, insufficient dynamic adaptability and low user participation in existing technologies, realizing coordinated quantitative evaluation and precise control of voltage quality, power loss and load balance, taking into account grid security, economy and user experience, and being suitable for multi-scenario distribution networks and microgrids, significantly improving operating efficiency and reliability.

[0092] Example 2 provides a multi-objective optimization operation and control system for distribution network and microgrid collaboration, including: a data acquisition module for obtaining real-time distribution network and microgrid data of the distribution network and microgrid, and calculating the voltage deviation value, power loss and average load based on the real-time distribution network and microgrid data; a model construction module for constructing an electric power evaluation model based on the voltage deviation value, power loss and average load and performing an evaluation to obtain a first evaluation result; a strategy generation module for generating a control strategy based on the first evaluation result; a feedback optimization module for optimizing the control strategy in real time according to user feedback and monitoring results.

[0093] Embodiment 3 is different from the previous embodiment in that:

[0094] This embodiment also provides a computer device, which is suitable for a multi-objective optimization operation and control method for collaboration between micro-devices and distribution networks, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the multi-objective optimization operation and control method for collaboration between micro-devices and distribution networks proposed in the above embodiment.

[0095] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0096] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the multi-objective optimization operation control method for realizing micro-distribution collaboration as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk.

[0097] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A multi-objective optimization operation control method for coordination between micro-devices and distribution, characterized by: include: Obtaining real-time distribution data of the distribution network and microgrid, and calculating voltage deviation value, power loss and average load based on the real-time distribution data; Building a power evaluation model based on the voltage deviation value, power loss and average load and performing an evaluation to obtain a first evaluation result; generating a control strategy based on the first evaluation result; The control strategy is optimized in real time based on user feedback and monitoring results.

2. The multi-objective optimization operation control method for the coordination of micro-devices according to claim 1 is characterized by: The real-time distribution data is obtained through sensors built into the distribution network and microgrid.

3. The multi-objective optimization operation control method for the coordination of micro-devices according to claim 2 is characterized by: The specific formula of the voltage deviation value is as follows: Where, δ V is the voltage deviation value; V a is the actual voltage of the node in real time; V r is the node rated voltage; The specific formula for the power loss is as follows: Where, P total is the total power loss of the distribution network and microgrid; n is the number of segmented lines; I i is the current of the i-th line; R i is the resistance of the i-th line; P0 is the no-load loss of the transformer; P k Transformer rated short-circuit loss; S is the actual power of the transformer; S N is the rated capacity of the transformer; The specific formula of the average load is as follows: Where, is the average active power; m is the number of power acquisition times; P j is the active power collected for the jth time.

4. The multi-objective optimization operation control method for the coordination of micro-devices according to claim 3 is characterized by: The specific formula of the power evaluation model is as follows: Where E is the first evaluation result; w1, w2 and w3 are weight coefficients, representing the relative importance of voltage deviation, power loss and average load respectively; δ V is the voltage deviation value; P total is the total power loss of the distribution network and microgrid; is the average active power.

5. The multi-objective optimization operation control method for the coordination of micro-devices according to claim 4 is characterized by: The specific steps for generating a control strategy based on the first evaluation result are as follows: comparing the voltage deviation value, power loss and average load in the first evaluation result with a set threshold value; Generate regulatory strategies based on the severity of each indicator; Use simulation software to simulate and evaluate control strategies; Optimize and improve the control strategy based on the evaluation results to form the final control strategy plan.

6. The multi-objective optimization operation control method for the coordination of micro-devices according to claim 5 is characterized by: Comparing the voltage deviation value, power loss, and average load in the first evaluation result with the set threshold value specifically includes: When the first evaluation result is less than the first threshold, it indicates that the voltage of each node is close to the rated value, the power loss is at a historical low, and the average load is within the equipment operating range; If the first evaluation result is greater than the first threshold and less than the second threshold, it means that at least one indicator has exceeded the first threshold. A level 1 warning message is sent to maintenance personnel for further analysis: If the voltage deviation value exceeds the first threshold and is less than the second threshold, it indicates that the device is unstable and the device parameters are recorded and analyzed; If the power loss exceeds the first threshold and is less than the second threshold, it indicates that the power loss of the line has increased, and a comprehensive inspection of the line is performed, and the load distribution is adjusted at the same time; If the average load exceeds the first threshold and is less than the second threshold, it means that the load rate of the transformer has increased. The real-time load changes are monitored immediately to understand the load changes in real time. When the first assessment result is greater than the second threshold, it means that at least one indicator has exceeded the second threshold, and a second-level warning message is sent to maintenance personnel for further analysis: When the voltage deviation exceeds the second threshold, the emergency plan is immediately activated: reactive power compensation devices are used to increase reactive power supply, the fault line is isolated, and professional technicians are notified to conduct on-site inspections. When the power loss exceeds the second threshold, the operation of the device is immediately stopped, the backup device is started, and professional maintenance personnel are notified to repair the faulty device; When the average load exceeds the second threshold, emergency load reduction measures are immediately taken, with non-critical loads being cut off first, backup power supplies being started, the operating status of the equipment being adjusted, and transformer equipment being closely monitored.

7. The multi-objective optimization operation control method for micro-distribution collaboration according to claim 6 is characterized by: Optimizing the control strategy in real time based on user feedback and monitoring results includes the following steps: Collect feedback for control strategies and monitor real-time micro-distribution data after control; Compare with the control targets to determine whether the voltage, loss and load meet the standards; If the standards are not met, adjust the device parameters or call the historical effective strategy. Based on the adjusted strategy, check the real-time micro-distribution data and user feedback again. If the standards are met, the control strategy will be added to the common strategy library.

8. The multi-objective optimization operation control system of the micro-distribution collaboration is characterized by: include, The data acquisition module is used to obtain real-time distribution data of the distribution network and microgrid, and calculate the voltage deviation value, power loss and average load based on the real-time distribution data; A model building module is used to build a power evaluation model based on the voltage deviation value, power loss and average load, and perform evaluation to obtain a first evaluation result; A strategy generation module, configured to generate a control strategy based on the first evaluation result; The feedback optimization module is used to optimize the control strategy in real time based on user feedback and monitoring results.

9. 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 multi-objective optimization operation control method of the micro-device collaboration described in any one of claims 1 to 7 are implemented.

10. 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 multi-objective optimization operation control method of the micro-device collaboration described in any one of claims 1 to 7 are implemented.

Images