A renewable energy power regulation early warning method and system

Abstract

The embodiment of the present invention provides a renewable energy power regulation early warning method and system, the method comprising: collecting the distribution addresses of distributed power sources and incorporating them into a microgrid, and continuously detecting the power supply value, power demand value and corresponding environmental attribute value of the distributed power sources in the microgrid; and performing model training to generate the supply relationship of the influencing factor value to the power supply value, and the demand relationship of the influencing factor value to the power demand value; and generating a power supply curve and a power demand curve; comparing and determining the abnormal time points where the supply and demand abnormalities exist, and determining the abnormal adjustment plan based on the type and degree of fluctuation of the abnormal time points, as well as the connection plan between the microgrid and the public power grid. The method can be used to predict the volatility of the power supply and demand in the microgrid through a fluctuation prediction model, and to make a fluctuation warning in advance to make a prediction plan for the energy storage system to smooth its fluctuation characteristics, thereby improving the stability of renewable energy in the microgrid.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid power supply, and in particular to a renewable energy power regulation early warning method and system. Background Art

[0002] Micro-Grid refers to a small power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc. It aims to achieve flexible and efficient application of distributed power sources and solve the problem of grid connection of a large number of distributed power sources in various forms. The development and extension of micro-grids can fully promote the large-scale access of distributed power sources and renewable energy, realize highly reliable supply of various energy forms to loads, and is an effective way to realize active distribution networks, making the transition from traditional power grids to smart grids.

[0003] However, in microgrid systems, except for a few areas where wind, solar, biomass and other energy sources can be used in a large-scale centralized manner, renewable energy in most areas appears in the form of distributed power sources. Since these distributed power sources have obvious randomness, intermittency and decentralized layout characteristics, external conditions such as weather factors can easily affect their output power changes, resulting in problems such as power quality degradation and voltage mutations. Summary of the invention

[0004] In view of the problems existing in the prior art, an embodiment of the present invention provides a renewable energy power regulation early warning method and system.

[0005] An embodiment of the present invention provides a renewable energy power regulation early warning method, comprising:

[0006] Collecting the distribution address of the distributed power source, incorporating the distributed power source into the microgrid based on the distribution address, and continuously detecting the power supply value, power demand value and corresponding environmental attribute value of the distributed power source in the microgrid;

[0007] Obtain a preset fluctuation prediction model, take the power supply value, power demand value, and influencing factor value as input data, input the fluctuation prediction model for model training, and generate a supply relationship between the influencing factor value and the power supply value, and a demand relationship between the influencing factor value and the power demand value;

[0008] Detecting a fluctuation event of the distributed power source, and determining a corresponding environmental fluctuation value based on the fluctuation event, generating an electric power supply curve corresponding to the fluctuation event based on the environmental fluctuation value and the supply relationship, and generating an electric power demand curve corresponding to the fluctuation event based on the environmental fluctuation value and the demand relationship;

[0009] The power supply curve and the power demand curve are compared, and the abnormal time point where the supply and demand anomaly exists is determined according to the comparison result, and based on the type and fluctuation degree of the abnormal time point, an abnormal adjustment plan for the energy storage system in the microgrid and a connection plan for the microgrid and the public power grid are generated.

[0010] In one embodiment, the method further comprises:

[0011] When the value corresponding to the power supply curve in the comparison result is greater than the value corresponding to the power demand curve at the same time point, the distributed power source is used to complete self-power supply, and the excess power is stored in the energy storage system, and when the energy storage system is fully charged, the microgrid is connected to the public power grid;

[0012] When the corresponding value of the power supply curve in the comparison result is less than the corresponding value at the same time point in the power demand curve, the distributed power supply is powered by the distributed power supply and the energy storage system, and when the power of the energy storage system is exhausted, the microgrid is connected to the public power grid.

[0013] In one embodiment, the method further comprises:

[0014] When the difference between the corresponding value of the power supply curve in the comparison result and the corresponding value of the same time point in the power demand curve is greater than the preset threshold, the corresponding excess time point and fluctuation event are obtained and sent to the binding terminal.

[0015] In one embodiment, the method further comprises:

[0016] During the implementation of the abnormal adjustment plan, the actual power supply and the actual power demand are continuously monitored. When the comparison result of the actual power supply and the actual power demand does not conform to the adjustment content of the abnormal adjustment plan, the power supply and demand are switched with other distributed power sources in a preset range based on the distribution address of the corresponding distributed power source.

[0017] In one embodiment, the method further comprises:

[0018] Performing data evaluation on the training data in the model training process based on the input data, the data evaluation comprising: calculating the accuracy, error rate, precision rate, and recall rate of the training data;

[0019] Based on the data evaluation result, verify whether the training data obtained by the iterative adjustment process is accurate.

[0020] An embodiment of the present invention provides a renewable energy power regulation early warning system, comprising:

[0021] A collection module, used to collect the distribution address of the distributed power source, merge the distributed power source into the microgrid based on the distribution address, and continuously detect the power supply value, power demand value and corresponding environmental attribute value of the distributed power source in the microgrid;

[0022] A training module is used to obtain a preset fluctuation prediction model, take the power supply value, power demand value, and influencing factor value as input data, input the fluctuation prediction model for model training, and generate a supply relationship between the influencing factor value and the power supply value, and a demand relationship between the influencing factor value and the power demand value;

[0023] A detection module, configured to detect a fluctuation event of the distributed power source, and determine a corresponding environmental fluctuation value based on the fluctuation event, generate an electric power supply curve corresponding to the fluctuation event based on the environmental fluctuation value and the supply relationship, and generate an electric power demand curve corresponding to the fluctuation event based on the environmental fluctuation value and the demand relationship;

[0024] A comparison module is used to compare the power supply curve and the power demand curve, determine the abnormal time point when the supply and demand anomaly exists according to the comparison result, and generate an abnormal adjustment plan for the energy storage system in the microgrid and a connection plan between the microgrid and the public power grid based on the type and fluctuation degree of the abnormal time point.

[0025] In one embodiment, the system further comprises:

[0026] The first adjustment module is used to complete self-power supply through the distributed power supply when the corresponding value of the power supply curve in the comparison result is greater than the corresponding value of the power demand curve at the same time point, and store the excess power in the energy storage system, and when the energy storage system is fully charged, connect the microgrid to the public power grid;

[0027] The second adjustment module is used to supply power to the distributed power supply through the distributed power supply and the energy storage system when the corresponding value of the power supply curve in the comparison result is less than the corresponding value at the same time point in the power demand curve, and to connect the microgrid to the public power grid when the power of the energy storage system is exhausted.

[0028] In one embodiment, the system further comprises:

[0029] The third adjustment module is used to obtain the corresponding excess time points and fluctuation events when the difference between the corresponding value of the power supply curve in the comparison result and the corresponding value of the same time point in the power demand curve is greater than a preset threshold, and send the excess time points and fluctuation events to the binding terminal.

[0030] An embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned renewable energy power regulation early warning method when executing the program.

[0031] An embodiment of the present invention provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned renewable energy power regulation early warning method are implemented.

[0032] A renewable energy power regulation early warning method and system provided by an embodiment of the present invention collects the distribution addresses of distributed power sources, incorporates the distributed power sources into a microgrid based on the distribution addresses, and continuously detects the power supply value, power demand value and corresponding environmental attribute value of the distributed power sources in the microgrid; obtains a preset fluctuation prediction model, takes the power supply value, power demand value and influencing factor value as input data, inputs the fluctuation prediction model for model training, and generates a supply relationship between the influencing factor value and the power supply value, and a demand relationship between the influencing factor value and the power demand value; detects fluctuation events of distributed power sources, and determines the corresponding environmental fluctuation value based on the fluctuation event, generates a power supply curve corresponding to the fluctuation event based on the environmental fluctuation value and the supply relationship, and generates a power demand curve corresponding to the fluctuation event based on the environmental fluctuation value and the demand relationship; compares the power supply curve and the power demand curve, determines the abnormal time point where the supply and demand abnormality exists according to the comparison result, and generates an abnormal adjustment plan for the energy storage system in the microgrid and a connection plan for the microgrid and the public power grid based on the type and degree of fluctuation of the abnormal time point. In this way, the fluctuation prediction model can be used to predict the fluctuation of power supply and demand in the microgrid, and fluctuation warning can be given in advance to make prediction plans for the energy storage system to smooth its fluctuation characteristics, thereby improving the stability of renewable energy in the microgrid. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 This is a flow chart of a renewable energy power regulation early warning method according to an embodiment of the present invention;

[0035] Figure 2 This is a structural diagram of a renewable energy power regulation early warning system in an embodiment of the present invention;

[0036] Figure 3 Schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Figure 1 A schematic diagram of a process flow of a renewable energy power regulation early warning method provided by an embodiment of the present invention, such as Figure 1 As shown, an embodiment of the present invention provides a renewable energy power regulation early warning method, comprising:

[0039] Step S101, collecting the distribution address of the distributed power source, integrating the distributed power source into the microgrid based on the distribution address, and continuously detecting the power supply value, power demand value and corresponding environmental attribute value of the distributed power source in the microgrid.

[0040] Specifically, the distribution addresses of distributed power sources are collected, where the distributed power sources may include distributed individual power generation devices such as gas turbines, wind power, photovoltaic power generation, fuel cells and energy storage devices, which are incorporated into the microgrid through power electronic devices, and in the microgrid, the power supply value, power demand value and environmental attribute value at the address of the distributed power source are continuously detected by the detection module. Wherein, because the distributed power source is easily affected by environmental attributes, such as temperature, wind force, light intensity, etc., when recording the distributed power source data, the power generation type of the distributed power source itself can be obtained, such as wind power, photovoltaic power generation, hydropower wind power, etc., and then the corresponding type of environmental attribute value is determined according to the corresponding power generation type. For example, if the distributed power source is a wind power source, the wind attribute value of the corresponding geographical location of the wind power source is determined.

[0041] Step S102, obtain a preset fluctuation prediction model, take the power supply value, power demand value, and influencing factor value as input data, input the fluctuation prediction model, and generate the supply relationship of the influencing factor value to the power supply value, and the demand relationship of the influencing factor value to the power demand value.

[0042] Specifically, the preset fluctuation model can perform logical operations based on the power supply value and the influencing factor value, and the power demand value and the influencing factor value of the distributed power source, and then train the neural network model of the logical operation result, and complete the predictive analysis of the supply and demand power data based on the neural network model training result, that is, generate the supply relationship of the influencing factor value to the power supply value, and the demand relationship of the influencing factor value to the power demand value, wherein the supply relationship and the demand relationship are corresponding relationships, and the corresponding form can be the correlation curve between the influencing factor value and the power supply value, and the influencing factor value and the power demand value, or it can be the correlation matrix between the two.

[0043] Step S103, detecting a fluctuation event of the distributed power source, and determining a corresponding environmental fluctuation value based on the fluctuation event, generating a power supply curve corresponding to the fluctuation event based on the environmental fluctuation value and the supply relationship, and generating a power demand curve corresponding to the fluctuation event based on the environmental fluctuation value and the demand relationship.

[0044] Specifically, fluctuation events of distributed power sources are detected, wherein fluctuation events are related events that may affect environmental attribute values ​​corresponding to the geographical locations of distributed power sources, such as temperature drop events, rain events, strong wind events, etc. On the basis of the impact on environmental attribute values, the above events may further affect the power supply and power demand of distributed power sources, and then the actual value of the fluctuation event is determined, such as obtaining a temperature curve of the specific drop in temperature of a cooling event, a rainfall data curve of a rain event, etc. through third-party data, and generating a power supply curve corresponding to the fluctuation event based on the actual value and the supply relationship, and generating a power demand curve corresponding to the fluctuation event based on the actual value and the demand relationship.

[0045] Step S104, comparing the power supply curve and the power demand curve, determining the abnormal time point when the supply and demand abnormality exists according to the comparison result, and generating an abnormal adjustment plan for the energy storage system in the microgrid and a connection plan for the microgrid and the public power grid based on the type and fluctuation degree of the abnormal time point.

[0046] Specifically, the power supply curve and the power demand curve are compared to determine the comparison value between the power supply value and the power demand value of the distributed power source at the same time point, and the abnormal time point where the supply and demand abnormality exists is determined according to the comparison value, wherein normal supply and demand means that the difference between the power supply value and the power demand value is in a stable range, and the difference between the two is not large. In addition, all other situations are supply and demand abnormalities. Then, based on the type and degree of fluctuation of the abnormal time point, an abnormal adjustment plan for the energy storage system in the microgrid and a connection plan for the microgrid and the public power grid are generated, wherein the abnormal time point types are usually of two types, the type where supply exceeds demand and the type where demand exceeds supply, and the corresponding abnormal adjustment plan and the connection plan for the microgrid and the public power grid are determined according to the difference between supply and demand.

[0047] Figure 2 A renewable energy power regulation early warning system provided by an embodiment of the present invention includes: a collection module S201, a training module S202, a detection module S203, and a comparison module S204, wherein:

[0048] The acquisition module S201 is used to acquire the distribution address of the distributed power source, integrate the distributed power source into the microgrid based on the distribution address, and continuously detect the power supply value, power demand value and corresponding environmental attribute value of the distributed power source in the microgrid.

[0049] The training module S202 is used to obtain a preset fluctuation prediction model, take the power supply value, power demand value, and influencing factor value as input data, input the fluctuation prediction model for model training, and generate the supply relationship of the influencing factor value to the power supply value, and the demand relationship of the influencing factor value to the power demand value.

[0050] The detection module S203 is used to detect fluctuation events of the distributed power source, and determine the corresponding environmental fluctuation value based on the fluctuation event, generate a power supply curve corresponding to the fluctuation event based on the environmental fluctuation value and the supply relationship, and generate a power demand curve corresponding to the fluctuation event based on the environmental fluctuation value and the demand relationship.

[0051] The comparison module S204 is used to compare the power supply curve and the power demand curve, determine the abnormal time point when the supply and demand anomaly exists according to the comparison result, and generate an abnormal adjustment plan for the energy storage system in the microgrid and a connection plan between the microgrid and the public power grid based on the type and fluctuation degree of the abnormal time point.

[0052] In one embodiment, the system further comprises:

[0053] The first adjustment module is used to complete self-power supply through the distributed power supply when the corresponding value of the power supply curve in the comparison result is greater than the corresponding value of the power demand curve at the same time point, and store the excess power in the energy storage system; and when the energy storage system is fully charged, connect the microgrid to the public power grid.

[0054] The second adjustment module is used to supply power to the distributed power supply through the distributed power supply and the energy storage system when the corresponding value of the power supply curve in the comparison result is less than the corresponding value at the same time point in the power demand curve, and to connect the microgrid to the public power grid when the power of the energy storage system is exhausted.

[0055] In one embodiment, the system further comprises:

[0056] The third adjustment module is used to obtain the corresponding excess time points and fluctuation events when the difference between the corresponding value of the power supply curve in the comparison result and the corresponding value of the same time point in the power demand curve is greater than a preset threshold, and send the excess time points and fluctuation events to the binding terminal.

[0057] For the specific definition of the renewable energy power regulation warning system, please refer to the definition of the renewable energy power regulation warning method above, which will not be repeated here. Each module in the above renewable energy power regulation warning system can be implemented in whole or in part by software, hardware and a combination thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0058] Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3 As shown, the electronic device may include: a processor (processor) 301, a memory (memory) 302, a communication interface (Communications Interface) 303 and a communication bus 304, wherein the processor 301, the memory 302, and the communication interface 303 communicate with each other through the communication bus 304. The processor 301 can call the logic instructions in the memory 302 to execute the following method: collect the distribution address of the distributed power source, merge the distributed power source into the microgrid based on the distribution address, and continuously detect the power supply value, power demand value and corresponding environmental attribute value of the distributed power source in the microgrid; obtain a preset fluctuation prediction model, take the power supply value, power demand value and influencing factor value as input data, input the fluctuation prediction model for model training, and generate the supply relationship of the influencing factor value to the power supply value, and the demand relationship of the influencing factor value to the power demand value; detect the fluctuation event of the distributed power source, and determine the corresponding environmental fluctuation value based on the fluctuation event, generate the power supply curve corresponding to the fluctuation event based on the environmental fluctuation value and the supply relationship, and generate the power demand curve corresponding to the fluctuation event based on the environmental fluctuation value and the demand relationship; compare the power supply curve and the power demand curve, determine the abnormal time point where the supply and demand abnormality exists according to the comparison result, and generate the abnormal adjustment plan of the energy storage system in the microgrid and the connection plan of the microgrid and the public power grid based on the type and fluctuation degree of the abnormal time point.

[0059] In addition, the logic instructions in the above-mentioned memory 302 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0060] On the other hand, an embodiment of the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when executed by a processor to execute the transmission method provided by the above embodiments, for example, including: collecting the distribution address of the distributed power source, incorporating the distributed power source into the microgrid based on the distribution address, and continuously detecting the power supply value, power demand value and corresponding environmental attribute value of the distributed power source in the microgrid; obtaining a preset fluctuation prediction model, taking the power supply value, power demand value and influencing factor value as input data, inputting the fluctuation prediction model for model training, and generating a supply relationship between the influencing factor value and the power supply value, and a demand relationship between the influencing factor value and the power demand value; detecting fluctuation events of the distributed power source, and determining the corresponding environmental fluctuation value based on the fluctuation event, generating a power supply curve corresponding to the fluctuation event based on the environmental fluctuation value and the supply relationship, and generating a power demand curve corresponding to the fluctuation event based on the environmental fluctuation value and the demand relationship; comparing the power supply curve and the power demand curve, determining the abnormal time point where the supply and demand abnormality exists according to the comparison result, and generating an abnormal adjustment plan for the energy storage system in the microgrid based on the type and degree of fluctuation of the abnormal time point, and a connection plan for the microgrid and the public power grid.

[0061] The system embodiment described above is merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0062] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A renewable energy power regulation early warning method, characterized in that: include: Collect the distribution address of the distributed power source, merge the distributed power source into the microgrid based on the distribution address, and continuously detect the power supply value, power demand value and corresponding environmental attribute value of the distributed power source in the microgrid, record the distributed power, record the power generation type of the distributed power source, and determine the environmental attribute value according to the power generation type; Obtain a preset fluctuation prediction model, take the power supply value, power demand value, and influencing factor value as input data, input the fluctuation prediction model for model training, and generate a supply relationship between the influencing factor value and the power supply value, and a demand relationship between the influencing factor value and the power demand value; Detecting fluctuation events of the distributed power source, and determining corresponding environmental fluctuation values ​​based on the fluctuation events, generating a power supply curve corresponding to the fluctuation events based on the environmental fluctuation values ​​and the supply relationship, and generating a power demand curve corresponding to the fluctuation events based on the environmental fluctuation values ​​and the demand relationship, wherein the fluctuation events are associated events in which the distributed addresses of the distributed power sources affect the environmental attribute values, power supply values, and power demand values; Compare the power supply curve and the power demand curve, determine the abnormal time point where the supply and demand are abnormal according to the comparison result, and generate the abnormal adjustment plan of the energy storage system in the microgrid and the connection plan of the microgrid and the public grid based on the type and fluctuation degree of the abnormal time point, the abnormal time point includes the type of supply greater than demand and the type of demand greater than supply, and determine the corresponding abnormal adjustment plan and the connection plan of the microgrid and the public grid according to the difference between supply and demand; The abnormal time point where the supply and demand abnormality exists is determined according to the comparison result, and the abnormal connection scheme between the microgrid and the public grid and the abnormal adjustment scheme of the energy storage system in the microgrid are generated based on the type and fluctuation degree of the abnormal time point, including: When the value corresponding to the power supply curve in the comparison result is greater than the value corresponding to the power demand curve at the same time point, the distributed power source is used to complete self-power supply, and the excess power is stored in the energy storage system, and when the energy storage system is fully charged, the microgrid is connected to the public power grid; When the value corresponding to the power supply curve in the comparison result is less than the value corresponding to the same time point in the power demand curve, the distributed power supply is powered by the distributed power supply and the energy storage system, and when the power of the energy storage system is exhausted, the microgrid is connected to the public power grid; When the difference between the corresponding value of the power supply curve in the comparison result and the corresponding value of the same time point in the power demand curve is greater than the preset threshold, the corresponding excess time point and fluctuation event are obtained and sent to the binding terminal.

2. The renewable energy power regulation early warning method according to claim 1 is characterized in that: The method further comprises: During the implementation of the abnormal adjustment plan, the actual power supply and the actual power demand are continuously monitored. When the comparison result of the actual power supply and the actual power demand does not conform to the adjustment content of the abnormal adjustment plan, the power supply and demand are switched with other distributed power sources in a preset range based on the distribution address of the corresponding distributed power source.

3. The renewable energy power regulation early warning method according to claim 1, characterized in that: The method further comprises: Performing data evaluation on the training data in the model training process based on the input data, the data evaluation comprising: calculating the accuracy, error rate, precision rate, and recall rate of the training data; Based on the data evaluation results, verify whether the training data obtained in the model training process is accurate.

4. A renewable energy power regulation early warning system, characterized in that: The system comprises: A collection module, used to collect the distribution address of the distributed power source, merge the distributed power source into the microgrid based on the distribution address, and continuously detect the power supply value, power demand value and corresponding environmental attribute value of the distributed power source in the microgrid, record the distributed power, record the power generation type of the distributed power source, and determine the environmental attribute value according to the power generation type; A training module is used to obtain a preset fluctuation prediction model, take the power supply value, power demand value, and influencing factor value as input data, input the fluctuation prediction model for model training, and generate a supply relationship between the influencing factor value and the power supply value, and a demand relationship between the influencing factor value and the power demand value; a detection module, configured to detect fluctuation events of the distributed power source, and determine corresponding environmental fluctuation values ​​based on the fluctuation events, generate a power supply curve corresponding to the fluctuation events based on the environmental fluctuation values ​​and the supply relationship, and generate a power demand curve corresponding to the fluctuation events based on the environmental fluctuation values ​​and the demand relationship, wherein the fluctuation events are associated events in which the distributed addresses of the distributed power sources affect the environmental attribute values, power supply values, and power demand values; A comparison module, used to compare the power supply curve and the power demand curve, determine the abnormal time point where the supply and demand are abnormal according to the comparison result, and generate an abnormal adjustment plan for the energy storage system in the microgrid and a connection plan between the microgrid and the public grid based on the type and fluctuation degree of the abnormal time point, wherein the abnormal time point includes a supply greater than demand type and a demand greater than supply type, and determine the corresponding abnormal adjustment plan and the connection plan between the microgrid and the public grid according to the supply and demand difference; The first adjustment module is used to complete self-power supply through the distributed power supply when the corresponding value of the power supply curve in the comparison result is greater than the corresponding value of the power demand curve at the same time point, and store the excess power in the energy storage system, and when the energy storage system is fully charged, connect the microgrid to the public power grid; A second adjustment module is used to supply power to the distributed power source through the distributed power source and the energy storage system when the corresponding value of the power supply curve in the comparison result is less than the corresponding value at the same time point in the power demand curve, and connect the microgrid to the public power grid when the power of the energy storage system is exhausted; The third adjustment module is used to obtain the corresponding excess time points and fluctuation events when the difference between the corresponding value of the power supply curve in the comparison result and the corresponding value of the same time point in the power demand curve is greater than a preset threshold, and send the excess time points and fluctuation events to the binding terminal.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the renewable energy power regulation early warning method according to any one of claims 1 to 3 are implemented.

6. A non-transitory 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 renewable energy power regulation early warning method as claimed in any one of claims 1 to 3 are implemented.

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