Virtual power plant management and control method based on Internet of Things

Abstract

The invention provides a virtual power plant management and control method based on the Internet of Things. The method comprises the steps of obtaining historical power supply data of each power supply device in a power supply device set through a virtual power plant management platform to form a historical power supply data set, then obtaining current power supply data of a target power supply device in the power supply device set, and then utilizing a preset power supply state detection model to detect the power supply state. Determining the power supply working state of the target power supply equipment according to the current power supply environment parameters and the historical power supply data set, and determining the power supply working state of the target power supply equipment when the virtual power plant management platform determines that the power supply working state of the target power supply equipment is an abnormal working state; and controlling the target energy storage equipment in the energy storage equipment set to replace the target power supply equipment to supply power to the target power supply network, so that the virtual power plant management platform can quickly start an emergency response mechanism when detecting that the target power supply equipment is in an abnormal working state, thereby ensuring continuity and stability of power supply to the target power supply network.

Description

Technical Field

[0001] The present application relates to data processing technology, and in particular to a virtual power plant management and control method based on the Internet of Things. Background Art

[0002] With the rapid development of energy internet, virtual power plants, as a new type of energy management system, are gradually occupying an important position in smart grids. Virtual power plants integrate distributed energy resources (such as distributed generation, energy storage systems and controllable loads) to achieve coordinated optimization and intelligent scheduling of these resources, thereby improving energy utilization efficiency and enhancing the flexibility and reliability of the power grid.

[0003] In the current virtual power plant system, the operation status monitoring and fault handling of power supply equipment is a key link. Once the power supply equipment fails or is in an abnormal state, if it cannot be discovered and handled in time, it is likely to cause power outages or grid instability, seriously affecting the quality and reliability of power supply. Summary of the invention

[0004] The present application provides a virtual power plant management and control method based on the Internet of Things, which is used to enable the virtual power plant management platform to quickly initiate an emergency response mechanism when it detects that the target power supply equipment is in an abnormal working state, thereby ensuring the continuity and stability of power supply to the target power supply network.

[0005] In a first aspect, the present application provides a virtual power plant management and control method based on the Internet of Things, which is applied to a virtual power plant system, wherein the virtual power plant system comprises: a virtual power plant management platform, a power supply device set, and an energy storage device set, wherein each power supply device in the power supply device set and each energy storage device in the energy storage device set are respectively connected to the virtual power plant management platform through the Internet of Things communication; the method comprises: The virtual power plant management platform obtains historical power supply data of each power supply device in the power supply device set to form a historical power supply data set, wherein the historical power supply data includes a time node sequence and power supply parameters corresponding to each time node in the time node sequence, and the power supply parameters include power supply environment parameters and power supply power parameters; The virtual power plant management platform obtains current power supply data of a target power supply device in the power supply device set, wherein the current power supply data includes current power supply environment parameters and current power supply power data; The virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set; If the virtual power plant management platform determines that the power supply working state of the target power supply device is an abnormal working state, it controls the target energy storage device in the energy storage device set to replace the target power supply device to supply power to the target power supply network, and the target power supply network is the power supply network corresponding to the virtual power plant management platform.

[0006] In the above scheme, by obtaining the historical power supply data and current power supply data of each power supply device in the power supply device set, the virtual power plant management platform can monitor the operating status of the power supply device in real time. Then, by using the preset power supply status detection model, combined with the current power supply environment parameters and historical power supply data, the virtual power plant management platform can accurately judge the power supply working status of the target power supply device, timely discover and respond to abnormal status, thereby effectively preventing the occurrence of power supply failures. Once the target power supply device is detected to be in an abnormal working state, the virtual power plant management platform can quickly start the emergency response mechanism, control the target energy storage device in the energy storage device set to replace the abnormal power supply device, and continue to supply power to the target power supply network. This automatic switching function ensures the continuity and stability of power supply, and reduces the time and scope of power outages caused by power supply device failures. In addition, by introducing energy storage devices as backup power supplies, automatically switching to energy storage devices for power supply when the power supply device is abnormal, the power supply reliability of the virtual power plant can be significantly improved. In addition, by realizing the connection between power supply equipment, energy storage equipment and virtual power plant management platform through the Internet of Things technology, the operating status of the power supply equipment and the remaining power of the energy storage equipment can be grasped in real time, providing data support for optimizing resource allocation. At the same time, through real-time data analysis and abnormal status warnings, the platform can detect potential problems in advance and take measures to resolve them, avoiding the expansion and deterioration of power supply problems.

[0007] Optionally, the virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set, including: The virtual power plant management platform determines the historical power supply power mean and the historical power supply power standard deviation according to the historical power supply data set; The virtual power plant management platform determines a power supply power fluctuation characteristic value according to the historical power supply power mean, the historical power supply power standard deviation and the current power supply power data; If the virtual power plant management platform determines that the power supply fluctuation characteristic value is greater than the preset power supply fluctuation threshold, it determines that the power supply working state of the target power supply device is the abnormal working state; If the virtual power plant management platform determines that the power supply fluctuation characteristic value is less than or equal to the preset power supply fluctuation threshold, it determines that the power supply working state of the target power supply device is a normal working state.

[0008] In the above scheme, by using the preset power supply status detection model and combining the current power supply environment parameters and the historical power supply data set, the power supply working state of the target power supply device can be accurately determined. Not only the current power supply situation is taken into account, but also the statistical analysis of historical data is integrated, making the judgment of the working state more comprehensive and accurate. By calculating the power supply power fluctuation characteristic value and comparing it with the preset power supply power fluctuation threshold, the virtual power plant management platform can quickly identify whether the target power supply device is in an abnormal working state. Once an abnormality is detected, measures can be taken immediately to avoid potential equipment failure or power supply interruption and improve the stability and safety of the power grid. Therefore, by continuously monitoring the fluctuation of the power supply, power supply risks can be discovered and prevented in time. When the power supply power fluctuation exceeds the normal range, it means that there may be problems such as unstable power supply or equipment failure. Replacing the target power supply device in time can effectively reduce the impact of these risks on the power grid. Based on accurate working state judgment and data analysis, the virtual power plant management platform can make more scientific and reasonable power supply management decisions. For example, after determining that the target power supply device is abnormal, the target energy storage device in the energy storage device set can be intelligently selected and controlled to replace the power supply to ensure the continuity and stability of the power supply network. Through real-time monitoring and intelligent scheduling, the optimal operating state of power supply equipment can be ensured, reducing energy waste caused by equipment failure or unstable power supply. At the same time, by accurately controlling the output of energy storage equipment, the power supply efficiency and reliability of the power grid can be further optimized.

[0009] Optionally, the virtual power plant management platform determines a historical power supply power mean and a historical power supply power standard deviation according to the historical power supply data set, including: The virtual power plant management platform determines a historical target power supply data set from the historical power supply data set according to the current time corresponding to the current power supply data and the current power supply environment parameters; The virtual power plant management platform determines the historical power supply power mean and the historical power supply power standard deviation according to the historical target power supply data set.

[0010] In the above scheme, by selecting the historical target power supply data set closest to the current situation from the historical power supply data set according to the time node of the current power supply data and the power supply environment parameters, the above scheme can more accurately reflect the characteristics of the current power supply environment, and provide a more reliable data basis for the subsequent calculation of the mean and standard deviation of the power supply power, thereby improving the pertinence and accuracy of the data used for subsequent analysis. In addition, the historical power supply power mean and standard deviation calculated based on the selected historical target power supply data set are closer to the actual situation of the current power supply environment. This makes the calculation of the power supply power fluctuation characteristic value more accurate, thereby improving the accuracy and reliability of the judgment of the power supply working state of the target power supply equipment. By narrowing the selection range of historical data, unnecessary data processing is reduced, thereby speeding up the speed of data processing and state judgment. This is crucial for the virtual power plant management platform to make decisions quickly in scenarios with high real-time requirements, and helps to improve the response speed and operation efficiency of the entire system. In addition, through accurate historical data screening and power supply state judgment, the resources of power supply equipment and energy storage equipment can be more effectively utilized. When an abnormality is found in the power supply equipment, it can quickly switch to a suitable energy storage device for power supply, avoiding energy waste and unnecessary equipment loss, while ensuring the continuity and stability of the power supply network.

[0011] Optionally, controlling a target energy storage device in the energy storage device set to replace the target power supply device to supply power to the target power supply network includes: The virtual power plant management platform obtains the rated power supply of each energy storage device in the energy storage device set; The virtual power plant management platform determines a target energy storage device sequence according to the rated power supply of each energy storage device and the historical power supply average, wherein the sum of the rated power supply powers of each target energy storage device in the target energy storage device sequence is greater than the historical power supply average; The virtual power plant management platform controls the target energy storage device sequence to supply power to the target power supply network with the historical power supply average value.

[0012] In the above scheme, by analyzing the rated power supply of the energy storage device and the historical power supply average, the appropriate target energy storage device sequence is automatically determined and scheduled to replace the abnormal power supply device. This intelligent scheduling method not only improves the response speed, but also ensures the continuity and stability of the power supply network. In addition, by ensuring that the sum of the rated power supply power of the target energy storage device sequence is greater than the historical power supply average, it can effectively match the load demand of the power supply network, effectively avoid power supply interruptions or instability caused by insufficient power supply capacity of the energy storage device, and improve the reliability and quality of power supply.

[0013] When dispatching energy storage equipment, the rated power supply of each energy storage equipment is further fully considered to ensure the optimal allocation of resources. By selecting the most appropriate combination of energy storage equipment, unnecessary energy waste and equipment idleness are avoided, and resource utilization efficiency is improved. When faced with abnormal conditions of power supply equipment, the above solution can respond quickly and flexibly adjust the dispatch strategy of energy storage equipment, so that the virtual power plant system can better respond to various emergencies and changes in power supply demand.

[0014] Optionally, the virtual power plant management platform controls the target energy storage device sequence to supply power to the target power supply network with the historical power supply average value, including: The virtual power plant management platform obtains the current remaining power of each target energy storage device in the target energy storage device sequence to form a current remaining power sequence; The virtual power plant management platform determines the power supply power of each target energy storage device in the target energy storage device sequence according to the current remaining power sequence and the historical power supply power average.

[0015] In the above scheme, by obtaining the current remaining power of each device in the target energy storage device sequence and determining the power supply power of each device accordingly, the refined management of the power of the energy storage device is realized. This management method can ensure that the energy storage device maintains a reasonable power level during the power supply process, avoids over-discharge or under-charging, and thus prolongs the service life of the energy storage device. In addition, determining the power supply power of each energy storage device based on the current remaining power and the historical power supply power average helps to achieve balanced load distribution. By adjusting the power supply power of each device, it can be ensured that they participate in the power supply in a relatively balanced manner, avoiding some devices from running out of power prematurely due to excessive load, thereby improving the power supply efficiency and stability of the entire energy storage device sequence. In addition, by real-time monitoring of the remaining power of the energy storage device and dynamically adjusting it during the power supply process, it can be ensured that when the power supply device is abnormal, the energy storage device can quickly and stably take over the power supply task. This seamless switching and stable power supply capabilities significantly improve the reliability and stability of the power supply system.

[0016] Optionally, after the virtual power plant management platform determines that the power supply working state of the target power supply device is an abnormal working state, the method further includes: The virtual power plant management platform records the abnormal working state into the historical power supply data of the target power supply device to mark that the power supply parameters at the current moment correspond to the abnormal working state; Correspondingly, before the virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set, it also includes: The virtual power plant management platform removes the power supply parameters marked as the abnormal working state from the historical power supply data to update the historical power supply data set.

[0017] In the above scheme, when it is found that the target power supply equipment is in an abnormal working state, the state and its corresponding power supply parameters are recorded in its historical power supply data, which helps to more accurately judge the operating state of the power supply equipment when performing power supply state detection in the future. At the same time, before each power supply state detection, the power supply parameters marked as abnormal working state are removed from the historical power supply data to ensure the input data quality of the analysis model and further improve the accuracy of power supply state detection. By removing abnormal data and updating the historical power supply data set, the interference of abnormal data on the power supply state detection model can be effectively reduced, which helps to improve the robustness and prediction accuracy of the model and make it more adaptable to complex and changeable power supply environments. In addition, recording abnormal working states and their corresponding power supply parameters not only helps post-fault analysis, but also provides data support for preventing similar faults. By analyzing abnormal data, potential power supply problems or equipment failure modes can be identified, so that targeted measures can be taken for prevention and improvement. In addition, by recording and marking abnormal working states, the virtual power plant management platform can quickly locate problem equipment and provide accurate fault information to maintenance personnel. This helps to shorten equipment maintenance time and improve the reliability and availability of power supply equipment. Through timely anomaly detection and effective data processing measures, power supply interruptions or instability caused by power supply equipment failures can be significantly reduced, which helps to improve the stability and reliability of the entire virtual power plant system and ensure the continuity and safety of power supply.

[0018] Optionally, the virtual power plant system further includes: a load device set, each load device in the load device set is connected to the virtual power plant management platform via Internet of Things communication; the method further includes: The virtual power plant management platform obtains historical power consumption data of each load device in the load device set to form a historical power consumption data set, wherein the historical power consumption data includes the time node sequence and the power parameters corresponding to each time node in the time node sequence; The virtual power plant management platform utilizes a preset virtual power plant allocation model and determines a first power grid dispatching unit based on the historical power supply data and the historical power consumption data set. The first power grid dispatching unit is composed of a first virtual machine group management module, a first power supply equipment sequence, and a first load equipment sequence. The virtual power plant management platform includes the first virtual machine group management module, the power supply equipment set includes the first power supply equipment sequence, and the load equipment set includes the first load equipment sequence. The first virtual machine group management module is used to adjust the power supply of the first load equipment sequence to output electrical energy for the first load equipment sequence.

[0019] In the above scheme, by incorporating the load equipment set into the virtual power plant management platform and combining the historical power supply data and the historical power consumption data, the matching of power supply resources and power demand can be achieved. The virtual power plant management platform can optimize the power grid dispatching unit, including the first virtual machine group management module, the first power supply equipment sequence and the first load equipment sequence through the preset virtual power plant allocation model, so as to achieve the reasonable allocation and efficient utilization of power supply resources. Using the historical power consumption data set, the virtual power plant management platform can deeply understand the power demand and power consumption mode of each load equipment. In addition, by dynamically determining and adjusting the power grid dispatching unit, including the combination of power supply equipment and load equipment, the virtual power plant can respond quickly according to the real-time power supply and power consumption. This flexible dispatching method not only enhances the dispatchability of the power grid, but also helps to improve the ability of the power system to respond to emergencies. In addition, stable power supply equipment and stable operating load equipment can be included in the first power grid dispatching unit for separate dispatching, which can effectively reduce the overall dispatching calculation amount of the virtual power grid, and also help to ensure the stable operation of stable power supply equipment and stable operating load equipment without being affected by other equipment.

[0020] In a second aspect, the present application provides a virtual power plant system, including: a virtual power plant management platform, a power supply device set, and an energy storage device set, wherein each power supply device in the power supply device set and each energy storage device in the energy storage device set are respectively connected to the virtual power plant management platform through Internet of Things communication; The virtual power plant management platform obtains historical power supply data of each power supply device in the power supply device set to form a historical power supply data set, wherein the historical power supply data includes a time node sequence, power supply environment parameters corresponding to each time node in the time node sequence, and power supply power data; The virtual power plant management platform obtains current power supply data of a target power supply device in the power supply device set, wherein the current power supply data includes current power supply environment parameters and current power supply power data; The virtual power plant management platform uses a preset power supply anomaly detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set; If the virtual power plant management platform determines that the power supply working state of the target power supply device is an abnormal working state, it controls the target energy storage device in the energy storage device set to replace the target power supply device to supply power to the target power supply network, and the target power supply network is the power supply network corresponding to the virtual power plant management platform.

[0021] Optionally, the virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set, including: The virtual power plant management platform determines the historical power supply power mean and the historical power supply power standard deviation according to the historical power supply data set; The virtual power plant management platform determines a power supply power fluctuation characteristic value according to the historical power supply power mean, the historical power supply power standard deviation and the current power supply power data; If the virtual power plant management platform determines that the power supply fluctuation characteristic value is greater than the preset power supply fluctuation threshold, it determines that the power supply working state of the target power supply device is the abnormal working state; If the virtual power plant management platform determines that the power supply fluctuation characteristic value is less than or equal to the preset power supply fluctuation threshold, it determines that the power supply working state of the target power supply device is a normal working state.

[0022] Optionally, the virtual power plant management platform determines a historical power supply power mean and a historical power supply power standard deviation according to the historical power supply data set, including: The virtual power plant management platform determines a historical target power supply data set from the historical power supply data set according to the current time corresponding to the current power supply data and the current power supply environment parameters; The virtual power plant management platform determines the historical power supply power mean and the historical power supply power standard deviation according to the historical target power supply data set.

[0023] Optionally, controlling a target energy storage device in the energy storage device set to replace the target power supply device to supply power to the target power supply network includes: The virtual power plant management platform obtains the rated power supply of each energy storage device in the energy storage device set; The virtual power plant management platform determines a target energy storage device sequence according to the rated power supply of each energy storage device and the historical power supply average, wherein the sum of the rated power supply powers of each target energy storage device in the target energy storage device sequence is greater than the historical power supply average; The virtual power plant management platform controls the target energy storage device sequence to supply power to the target power supply network with the historical power supply average value.

[0024] Optionally, the virtual power plant management platform controls the target energy storage device sequence to supply power to the target power supply network with the historical power supply average value, including: The virtual power plant management platform obtains the current remaining power of each target energy storage device in the target energy storage device sequence to form a current remaining power sequence; The virtual power plant management platform determines the power supply power of each target energy storage device in the target energy storage device sequence according to the current remaining power sequence and the historical power supply power average.

[0025] Optionally, after the virtual power plant management platform determines that the power supply working state of the target power supply device is an abnormal working state, the method further includes: The virtual power plant management platform records the abnormal working state into the historical power supply data of the target power supply device to mark that the power supply parameters at the current moment correspond to the abnormal working state; Correspondingly, before the virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set, it also includes: The virtual power plant management platform removes the power supply parameters marked as the abnormal working state from the historical power supply data to update the historical power supply data set.

[0026] Optionally, the virtual power plant system further includes: a load device set, each load device in the load device set is connected to the virtual power plant management platform via Internet of Things communication; the method further includes: The virtual power plant management platform obtains historical power consumption data of each load device in the load device set to form a historical power consumption data set, wherein the historical power consumption data includes the time node sequence and the power parameters corresponding to each time node in the time node sequence; The virtual power plant management platform utilizes a preset virtual power plant allocation model and determines a first power grid dispatching unit based on the historical power supply data and the historical power consumption data set. The first power grid dispatching unit is composed of a first virtual machine group management module, a first power supply equipment sequence, and a first load equipment sequence. The virtual power plant management platform includes the first virtual machine group management module, the power supply equipment set includes the first power supply equipment sequence, and the load equipment set includes the first load equipment sequence. The first virtual machine group management module is used to adjust the power supply of the first load equipment sequence to output electrical energy for the first load equipment sequence.

[0027] In a third aspect, the present application provides an electronic device, including: processor; and, A memory, configured to store executable instructions of the processor; The processor is configured to perform any possible method described in the first aspect by executing the executable instructions.

[0028] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement any possible method described in the first aspect.

[0029] The virtual power plant control method based on the Internet of Things provided in the present application obtains the historical power supply data of each power supply device in the power supply device set through the virtual power plant management platform to form a historical power supply data set, and then obtains the current power supply data of the target power supply device in the power supply device set, and then uses the preset power supply status detection model to determine the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set, and when the virtual power plant management platform determines that the power supply working status of the target power supply device is an abnormal working status, the target energy storage device in the energy storage device set is controlled to replace the target power supply device to supply power to the target power supply network, so that when it is detected that the target power supply device is in an abnormal working status, the virtual power plant management platform can quickly start the emergency response mechanism, control the target energy storage device in the energy storage device set to replace the abnormal power supply device, and continue to supply power to the target power supply network, thereby ensuring the continuity and stability of power supply to the target power supply network. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0031] Figure 1 It is a flowchart of a virtual power plant control method based on the Internet of Things according to an example embodiment of the present application; Figure 2 is a flow chart of a virtual power plant control method based on the Internet of Things according to another exemplary embodiment of the present application; Figure 3 is a structural schematic diagram of a virtual power plant system according to an exemplary embodiment of the present application; Figure 4 It is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present application.

[0032] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0033] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0034] In order to solve the above problems, the embodiment provided in this application provides a virtual power plant management and control method based on the Internet of Things, which realizes efficient, stable and intelligent management of the virtual power plant system by integrating Internet of Things technology, data analysis and intelligent decision-making algorithms. The following is a detailed description of the concept of this application: 1. System architecture and communication connection: The virtual power plant system in the embodiment provided in this application is mainly composed of three core components: a virtual power plant management platform, a power supply device set, and an energy storage device set. These components achieve efficient data communication and interaction through the Internet of Things technology. Specifically: Virtual power plant management platform: As the core of the system, it is responsible for data collection, processing, analysis and decision-making.

[0035] Power supply equipment collection: including various types of power generation equipment, such as wind turbines, solar photovoltaic panels, etc., which upload real-time power supply data to the management platform through the Internet of Things.

[0036] Energy storage equipment collection: including battery energy storage systems, pumped storage power stations and other forms of energy storage equipment, which are used to provide power support when power supply equipment is abnormal or grid demand fluctuates.

[0037] 2. Data collection and preprocessing: In order to achieve accurate monitoring and status judgment of power supply equipment, the embodiment provided in this application designs the following data collection and preprocessing process: Historical power supply data collection: The virtual power plant management platform obtains the historical power supply data of each device from the power supply equipment collection regularly or in real time, including time node sequence, power supply environment parameters (such as temperature, humidity, etc.) and power supply power parameters.

[0038] Current power supply data acquisition: For the target power supply equipment, the management platform obtains its current power supply data in real time to make instant status judgment.

[0039] 3. Power supply status detection and abnormality handling: In order to timely discover and handle abnormal status of power supply equipment, the embodiment provided in this application introduces a preset power supply status detection model, and combines the current power supply environment parameters with historical power supply data to judge the power supply working status of the target power supply equipment. The specific steps are as follows: Calculation of power supply fluctuation characteristic values: Based on the historical power supply data set, the historical power supply mean and standard deviation are calculated, and then the power supply fluctuation characteristic values ​​are calculated using the current power supply data.

[0040] Status judgment and abnormality handling: If the power supply fluctuation characteristic value is greater than the preset threshold, the target power supply device is judged to be in an abnormal working state and the emergency response mechanism is immediately triggered. At this time, the management platform will control the target energy storage device in the energy storage device set to replace the abnormal power supply device and continue to supply power to the target power supply network to ensure the continuity and stability of power supply.

[0041] 4. Intelligent dispatching of energy storage equipment: In the process of replacing power supply equipment with energy storage equipment, the embodiment provided in this application designs an intelligent scheduling strategy to optimize resource allocation and improve power supply efficiency: Rated power supply matching: The management platform determines the target energy storage device sequence based on the rated power supply of the energy storage device and the historical power supply average, ensuring that the sum of the rated power supply of the devices in the sequence is greater than the historical power supply average.

[0042] Refined management of remaining power: When dispatching energy storage devices, the management platform will also consider the current remaining power of each device to avoid over-discharge or under-charge. By dynamically adjusting the power supply of each energy storage device, load balancing and power optimization management can be achieved.

[0043] 5. Data update and history record: In order to ensure the accuracy and effectiveness of the power supply status detection model, the embodiment provided in this application also designs a data update and history recording mechanism: Abnormal working status record: When the target power supply equipment is found to be in an abnormal working state, the management platform will record the state and its corresponding power supply parameters in the historical power supply data of the equipment to facilitate more accurate status judgment in the future.

[0044] Historical data update: Before each power supply status detection, the management platform will remove the power supply parameters that have been marked as abnormal working status to update the historical power supply data set and reduce the interference of abnormal data on the model.

[0045] 6. Load equipment management and power grid dispatch optimization: In order to further improve the overall performance of the virtual power plant system, the embodiment provided in this application also includes the load equipment collection in the management scope of the management platform, and combines historical power supply data and historical power consumption data, and optimizes and determines the grid dispatching unit through a preset virtual power plant allocation model. This not only helps to achieve accurate matching of power supply resources and power demand, but also improves the flexibility and dispatchability of the grid.

[0046] In summary, the concept of the embodiments provided in this application is to achieve efficient communication and data interaction between the components of the virtual power plant system through the Internet of Things technology, and combine data analysis and intelligent decision-making algorithms to achieve accurate monitoring, state judgment and abnormal processing of power supply equipment, as well as intelligent scheduling and load balancing management of energy storage equipment. At the same time, through load equipment management and grid scheduling optimization, the overall performance and stability of the virtual power plant system can be further improved.

[0047] Figure 1 FIG. 1 is a flow chart of a virtual power plant control method based on the Internet of Things according to an exemplary embodiment of the present application. Figure 1 As shown, the virtual power plant management and control method based on the Internet of Things provided in this embodiment includes: S101. The virtual power plant management platform obtains historical power supply data of each power supply device in a power supply device set to form a historical power supply data set.

[0048] The method provided in this embodiment can be applied to a virtual power plant system, which includes: a virtual power plant management platform, a power supply device set and an energy storage device set, and each power supply device in the power supply device set and each energy storage device in the energy storage device set are respectively connected to the virtual power plant management platform through the Internet of Things communication. Specifically, first, a virtual power plant system including a virtual power plant management platform, a power supply device set and an energy storage device set is constructed. These components communicate in real time through the Internet of Things technology to ensure the rapid transmission of data and the accurate execution of instructions. Then, using the Internet of Things communication protocol (such as MQTT, CoAP, etc.), each power supply device in the power supply device set and each energy storage device in the energy storage device set are connected to the virtual power plant management platform to ensure real-time data collection and instant communication of instructions. It is worth noting that the above-mentioned power supply equipment can be photovoltaic equipment, wind turbine equipment, tidal power generation equipment, geothermal power generation equipment, etc. And the above-mentioned energy storage device set can be an energy storage battery box, compressed air energy storage, hydrogen energy storage, and electric vehicle power battery system.

[0049] In this step, the virtual power plant management platform obtains the historical power supply data of each power supply device in the power supply equipment set to form a historical power supply data set. The historical power supply data includes a time node sequence and the power supply parameters corresponding to each time node in the time node sequence. The power supply parameters include power supply environment parameters and power supply power parameters.

[0050] Specifically, the virtual power plant management platform obtains historical power supply data from each power supply device in the power supply device set regularly or in real time. These data include time node sequences and power supply environment parameters (such as temperature, humidity, wind speed, sunshine intensity, sunshine angle, etc.) and power supply power parameters (such as actual power supply power, voltage, current, etc.) at corresponding time nodes. The collected historical power supply data is organized into a historical power supply data set for subsequent analysis and use. At the same time, the data is cleaned and verified to ensure the accuracy and integrity of the data.

[0051] S102: The virtual power plant management platform obtains current power supply data of a target power supply device in a power supply device set.

[0052] The virtual power plant management platform obtains the current power supply data of the target power supply equipment in the power supply equipment set, and the current power supply data includes current power supply environment parameters and current power supply power data.

[0053] Specifically, the virtual power plant management platform monitors the current power supply data of the target power supply equipment in the power supply equipment set in real time. These data also include current power supply environment parameters and current power supply power data. Then, the current power supply data obtained in real time is recorded in the system to provide basic data for subsequent power supply status detection.

[0054] S103. The virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply equipment according to current power supply environment parameters and a historical power supply data set.

[0055] In this step, the virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply equipment according to the current power supply environment parameters and the historical power supply data set.

[0056] Specifically, the virtual power plant management platform uses a preset power supply status detection model, which may be built based on machine learning, deep learning, or statistical analysis. The current power supply environment parameters and historical power supply data are combined as inputs and analyzed through the power supply status detection model. The model will determine whether the power supply working status of the target power supply equipment is abnormal based on the preset algorithms and rules.

[0057] In a possible implementation, the virtual power plant management platform determines the historical power supply power mean and the historical power supply power standard deviation based on the historical power supply data set; The virtual power plant management platform uses formula 1 and determines the power supply fluctuation characteristic value based on the historical power supply mean, historical power supply standard deviation and current power supply data. , Formula 1 is: , in, For the current moment Current power supply data, is the historical power supply average value, is the standard deviation of historical power supply; If the virtual power plant management platform determines the power supply fluctuation characteristic value If the power supply fluctuation value is greater than the preset power supply fluctuation threshold, the power supply working state of the target power supply device is determined to be an abnormal working state; If the virtual power plant management platform determines the power supply fluctuation characteristic value If the power supply fluctuation value is less than or equal to the preset power supply fluctuation threshold, it is determined that the power supply working state of the target power supply device is a normal working state.

[0058] In the above scheme, by calculating the historical power supply mean and the historical power supply standard deviation, the system can fully understand the power supply performance of the target power supply equipment in the past period of time. These statistical indicators provide a benchmark for judging the current power supply status. Then, combined with the power supply data at the current moment, the system can capture the fluctuation of the power supply in real time. By calculating the power supply fluctuation characteristic value through formula 1, the system can quantify the degree of deviation between the current power supply and the historical mean. Then, by comparing the power supply fluctuation characteristic value with the preset power supply fluctuation threshold, the system can accurately identify whether the target power supply equipment is in an abnormal working state. This state judgment method based on statistical analysis is more accurate and reliable than the traditional single threshold judgment.

[0059] Through real-time monitoring of power supply and calculation of fluctuation characteristic values, the system can promptly detect abnormal status of target power supply equipment. Once an abnormality is detected, the system can quickly initiate an emergency response mechanism to avoid potential equipment failure or power outage. When the target power supply equipment is abnormal, the system can intelligently select and control the target energy storage device in the energy storage device set to replace the power supply. This automatic switching function ensures the continuity and stability of power supply and reduces the time and scope of power outages caused by power supply equipment failure. Through real-time data analysis and intelligent scheduling, the system can optimize the operating status of power supply equipment and improve power supply efficiency and quality. At the same time, by accurately controlling the output of energy storage equipment, the power supply efficiency and reliability of the power grid can be further optimized.

[0060] In addition, by using only historical power supply data related to the current power supply environment parameters to calculate statistical indicators, the system can reduce unnecessary data processing and improve the speed and efficiency of data processing. Based on the comprehensive analysis of historical power supply data and current power supply data, the system can optimize the resource allocation of power supply equipment and energy storage equipment.

[0061] S104: Control a target energy storage device in the energy storage device set to replace a target power supply device to supply power to a target power supply network.

[0062] If the virtual power plant management platform determines that the power supply working state of the target power supply device is an abnormal working state, the target energy storage device in the energy storage device set is controlled to replace the target power supply device to supply power to the target power supply network, and the target power supply network is the power supply network corresponding to the virtual power plant management platform.

[0063] Specifically, if the power supply status detection model determines that the power supply working status of the target power supply equipment is abnormal, the virtual power plant management platform will take further action.

[0064] The virtual power plant management platform can first select appropriate energy storage devices as replacement objects based on the rated power supply of each energy storage device in the energy storage device set and the power demand in the historical power supply data. The goal is to ensure that the replaced energy storage device can meet the power supply demand of the target power supply network.

[0065] Then, by sending a control instruction to the selected target energy storage device, it starts to replace the abnormal power supply device to supply power to the target power supply network. At the same time, the abnormal power supply device is isolated from the power supply network for troubleshooting or maintenance.

[0066] Then, during the replacement process, the virtual power plant management platform will monitor the power supply situation of the target power supply network in real time, and adjust the power supply power of the energy storage equipment as needed to ensure the stability and reliability of power supply.

[0067] In this embodiment, the historical power supply data of each power supply device in the power supply device set is obtained through the virtual power plant management platform to form a historical power supply data set, and then the current power supply data of the target power supply device in the power supply device set is obtained, and then the preset power supply status detection model is used to determine the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set, and when the virtual power plant management platform determines that the power supply working status of the target power supply device is an abnormal working status, the target energy storage device in the energy storage device set is controlled to replace the target power supply device to supply power to the target power supply network, so that when it is detected that the target power supply device is in an abnormal working status, the virtual power plant management platform can quickly initiate the emergency response mechanism, control the target energy storage device in the energy storage device set to replace the abnormal power supply device, and continue to supply power to the target power supply network, thereby ensuring the continuity and stability of power supply to the target power supply network.

[0068] Figure 2 FIG. 1 is a flow chart of a virtual power plant control method based on the Internet of Things according to another exemplary embodiment of the present application. Figure 2 As shown, the virtual power plant management and control method based on the Internet of Things provided in this embodiment includes: S201. The virtual power plant management platform obtains historical power supply data of each power supply device in a power supply device set to form a historical power supply data set.

[0069] In this step, the virtual power plant management platform obtains the historical power supply data of each power supply device in the power supply equipment set to form a historical power supply data set. The historical power supply data includes a time node sequence and the power supply parameters corresponding to each time node in the time node sequence. The power supply parameters include power supply environment parameters and power supply power parameters.

[0070] Specifically, the virtual power plant management platform obtains historical power supply data from each power supply device in the power supply device set regularly or in real time. These data include time node sequences and power supply environment parameters (such as temperature, humidity, wind speed, sunshine intensity, sunshine angle, etc.) and power supply power parameters (such as actual power supply power, voltage, current, etc.) at corresponding time nodes. The collected historical power supply data is organized into a historical power supply data set for subsequent analysis and use. At the same time, the data is cleaned and verified to ensure the accuracy and integrity of the data.

[0071] S202. The virtual power plant management platform obtains current power supply data of a target power supply device in a power supply device set.

[0072] The virtual power plant management platform obtains the current power supply data of the target power supply equipment in the power supply equipment set, and the current power supply data includes current power supply environment parameters and current power supply power data.

[0073] Specifically, the virtual power plant management platform monitors the current power supply data of the target power supply equipment in the power supply equipment set in real time. These data also include current power supply environment parameters and current power supply power data. Then, the current power supply data obtained in real time is recorded in the system to provide basic data for subsequent power supply status detection.

[0074] S203. The virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply equipment according to current power supply environment parameters and a historical power supply data set.

[0075] In this step, the virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply equipment according to the current power supply environment parameters and the historical power supply data set.

[0076] Specifically, the virtual power plant management platform uses a preset power supply status detection model, which may be built based on machine learning, deep learning, or statistical analysis. The current power supply environment parameters and historical power supply data are combined as inputs and analyzed through the power supply status detection model. The model will determine whether the power supply working status of the target power supply equipment is abnormal based on the preset algorithms and rules.

[0077] In a possible implementation, the virtual power plant management platform determines the historical power supply power mean and the historical power supply power standard deviation based on the historical power supply data set; The virtual power plant management platform uses formula 1 and determines the power supply fluctuation characteristic value based on the historical power supply mean, historical power supply standard deviation and current power supply data. , Formula 1 is: , in, For the current moment Current power supply data, is the historical power supply average value, is the standard deviation of historical power supply; If the virtual power plant management platform determines the power supply fluctuation characteristic value If the power supply fluctuation value is greater than the preset power supply power fluctuation threshold, it is determined that the power supply working state of the target power supply device is an abnormal working state.

[0078] If the virtual power plant management platform determines the power supply fluctuation characteristic value If the power supply fluctuation value is less than or equal to the preset power supply fluctuation threshold, it is determined that the power supply working state of the target power supply device is a normal working state.

[0079] In the above scheme, by calculating the historical power supply mean and the historical power supply standard deviation, the system can fully understand the power supply performance of the target power supply equipment in the past period of time. These statistical indicators provide a benchmark for judging the current power supply status. Then, combined with the power supply data at the current moment, the system can capture the fluctuation of the power supply in real time. By calculating the power supply fluctuation characteristic value through formula 1, the system can quantify the degree of deviation between the current power supply and the historical mean. Then, by comparing the power supply fluctuation characteristic value with the preset power supply fluctuation threshold, the system can accurately identify whether the target power supply equipment is in an abnormal working state. This state judgment method based on statistical analysis is more accurate and reliable than the traditional single threshold judgment.

[0080] Through real-time monitoring of power supply and calculation of fluctuation characteristic values, the system can promptly detect abnormal status of target power supply equipment. Once an abnormality is detected, the system can quickly initiate an emergency response mechanism to avoid potential equipment failure or power outage. When the target power supply equipment is abnormal, the system can intelligently select and control the target energy storage device in the energy storage device set to replace the power supply. This automatic switching function ensures the continuity and stability of power supply and reduces the time and scope of power outages caused by power supply equipment failure. Through real-time data analysis and intelligent scheduling, the system can optimize the operating status of power supply equipment and improve power supply efficiency and quality. At the same time, by accurately controlling the output of energy storage equipment, the power supply efficiency and reliability of the power grid can be further optimized.

[0081] Furthermore, the virtual power plant management platform records the abnormal working state in the historical power supply data of the target power supply device to mark the current power supply parameter as corresponding to the abnormal working state. Correspondingly, before the virtual power plant management platform uses the preset power supply state detection model and determines the power supply working state of the target power supply device according to the current power supply environment parameters and the historical power supply data set, the virtual power plant management platform can also remove the power supply parameters marked as abnormal working state from the historical power supply data to update the historical power supply data set.

[0082] Then, the virtual power plant management platform can also determine the historical target power supply data set from the historical power supply data set according to the current time corresponding to the current power supply data and the current power supply environment parameters. Then, the virtual power plant management platform determines the historical power supply power mean and the historical power supply power standard deviation based on the historical target power supply data set. It is worth noting that the historical target power supply data set can be generated by matching the power supply data whose similarity with the current power supply environment parameters meets the preset requirements from the historical power supply data set. The above-mentioned preset requirements can be that the deviation value is less than the preset deviation threshold, or that the deviation ratio is less than the preset deviation ratio threshold, etc. If the above-mentioned current power supply environment parameters include multiple parameters, the overall similarity can be determined by setting weights for each parameter.

[0083] Therefore, by using only historical power supply data related to the current power supply environment parameters to calculate statistical indicators, the system can reduce unnecessary data processing and improve the speed and efficiency of data processing. Based on the comprehensive analysis of historical power supply data and current power supply data, the system can optimize the resource allocation of power supply equipment and energy storage equipment.

[0084] S204. The virtual power plant management platform obtains the rated power supply power of each energy storage device in the energy storage device set.

[0085] Specifically, the virtual power plant management platform obtains the rated power supply from each energy storage device in the energy storage device set through the IoT communication connection. These rated power supplies can be basic parameters when designing energy storage devices, indicating the maximum power that the device can continuously output under standard conditions. The platform stores the collected rated power supply data in the database for subsequent analysis and scheduling.

[0086] S205. The virtual power plant management platform determines a target energy storage device sequence according to the rated power supply of each energy storage device and the historical power supply average.

[0087] The virtual power plant management platform determines the target energy storage device sequence according to the rated power supply power of each energy storage device and the historical power supply power average, wherein the sum of the rated power supply power of each target energy storage device in the target energy storage device sequence is greater than the historical power supply power average.

[0088] Specifically, the virtual power plant management platform calculates the mean historical power supply power based on the historical power supply data set. This mean reflects the average power supply power of the power supply equipment over a period of time in the past and is an important reference for determining the capacity of replacement energy storage equipment. The platform selects a number of energy storage devices based on the rated power supply power of each energy storage device and the historical power supply power mean to form a target energy storage device sequence. The sum of the rated power supply power of each energy storage device in this sequence must be greater than the historical power supply power mean to ensure that the load requirements of the power supply network can be met after replacement. After selecting the target energy storage device sequence, the platform can further optimize the equipment combination, consider factors such as the remaining life of the equipment, maintenance cost, and response speed, and select the optimal equipment combination for power supply.

[0089] S206. The virtual power plant management platform controls the target energy storage device sequence to supply power to the target power supply network with the historical power supply average.

[0090] In this step, the virtual power plant management platform issues power supply instructions to each device in the target energy storage device sequence, specifying them to supply power to the target power supply network at the historical average power supply value. During the power supply process, the platform monitors the operating status and power supply of the energy storage devices in real time through the IoT communication connection to ensure that they supply power normally according to the instructions. If it is found that the power supply power of a certain energy storage device deviates from the instruction value during the actual power supply process, the platform can dynamically adjust the power supply power of the device according to the actual situation, or select other devices from the target energy storage device sequence for replacement to ensure the stability and continuity of the power supply.

[0091] Specifically, the virtual power plant management platform obtains the target energy storage device sequence The current remaining power of each target energy storage device in the system is used to form a current remaining power sequence. ,in, The first target energy storage device, The first Target energy storage devices The current remaining power, is the number of target energy storage devices in the target energy storage device sequence.

[0092] The virtual power plant management platform uses formula 2 and calculates the current remaining power sequence And the historical power supply average Determine the target energy storage device sequence The power supply power of each target energy storage device in, where Formula 2 is: , in, The target energy storage device sequence Middle Target energy storage devices At the present moment The next moment The power supply power.

[0093] In the above scheme, the power management of energy storage devices is achieved by obtaining the current remaining power of each target energy storage device and calculating the power supply power accordingly. This ensures that the power of the energy storage device is maintained at a reasonable level during the power supply process, avoiding over-discharge or under-charging, thereby extending the service life of the energy storage device. It is worth noting that the above formula 2 calculates the power supply power of each energy storage device, which can ensure that they participate in the power supply in a relatively balanced manner, which helps to prevent some devices from running out of power prematurely due to excessive load, thereby improving the power supply efficiency and stability of the entire energy storage device sequence. By dynamically adjusting the power supply power of each device, a balanced load distribution is achieved. In addition, by real-time monitoring of the remaining power of the energy storage device and dynamically adjusting it during the power supply process, the virtual power plant management platform can ensure that the energy storage device can quickly and stably take over the power supply task when the power supply device is abnormal. This seamless switching and stable power supply capability significantly improves the reliability and stability of the power supply system and reduces the time and scope of power outages caused by power supply equipment failures.

[0094] Moreover, by calculating the power supply of each energy storage device and considering its remaining power, the virtual power plant management platform can select the most appropriate combination of energy storage devices for power supply. This avoids unnecessary energy waste and equipment idleness, and improves resource utilization efficiency. At the same time, the distribution of power supply according to the historical power supply average can ensure that the load demand of the power supply network is met, thereby maintaining the stable operation of the power grid. When faced with abnormal conditions of power supply equipment, this method can respond quickly and flexibly adjust the scheduling strategy of energy storage equipment. Through real-time monitoring and intelligent scheduling, the virtual power plant system can better respond to various emergencies and changes in power supply demand, enhancing the system's responsiveness and coping capabilities.

[0095] On the basis of the above-mentioned embodiment, the virtual power plant system may further include: a load device set, wherein each load device in the load device set is connected to the virtual power plant management platform via Internet of Things communication.

[0096] The virtual power plant management platform obtains the historical power consumption data of each load device in the load device set to form a historical power consumption data set, where the historical power consumption data includes a time node sequence and power parameters corresponding to each time node in the time node sequence; The virtual power plant management platform utilizes a preset virtual power plant allocation model and determines the first power grid dispatching unit based on a set of historical power supply data and a set of historical power consumption data. The first power grid dispatching unit is composed of a first virtual machine group management module, a first power supply equipment sequence, and a first load equipment sequence. The virtual power plant management platform includes a first virtual machine group management module, a power supply equipment set includes a first power supply equipment sequence, and a load equipment set includes a first load equipment sequence. The first virtual machine group management module is used to adjust the power supply of the first load equipment sequence to output electrical energy for the first load equipment sequence.

[0097] In the above scheme, by incorporating the load equipment set into the virtual power plant management platform and combining the historical power supply data and the historical power consumption data, the matching of power supply resources and power demand can be achieved. The virtual power plant management platform can optimize the power grid dispatching unit, including the first virtual machine group management module, the first power supply equipment sequence and the first load equipment sequence through the preset virtual power plant allocation model, so as to achieve the reasonable allocation and efficient utilization of power supply resources. Using the historical power consumption data set, the virtual power plant management platform can deeply understand the power demand and power consumption mode of each load equipment. In addition, by dynamically determining and adjusting the power grid dispatching unit, including the combination of power supply equipment and load equipment, the virtual power plant can respond quickly according to the real-time power supply and power consumption. This flexible dispatching method not only enhances the dispatchability of the power grid, but also helps to improve the ability of the power system to respond to emergencies. In addition, stable power supply equipment and stable operating load equipment can be included in the first power grid dispatching unit for separate dispatching, which can effectively reduce the overall dispatching calculation amount of the virtual power grid, and also help to ensure the stable operation of stable power supply equipment and stable operating load equipment without being affected by other equipment.

[0098] Furthermore, the virtual power plant management platform uses a preset virtual power plant allocation model and determines the first power grid dispatching unit according to the historical power consumption data set and the historical load data, which may specifically include: The virtual power plant management platform groups all fixed load devices in the load device set into a first load device sequence, wherein the fixed load device is a load device that is fixedly operated within a corresponding preset power range; The virtual power plant management platform determines the load upper limit power according to the first load device sequence, where the load upper limit power is the sum of the upper limit powers of the preset power ranges corresponding to the various fixed load devices; The virtual power plant management platform determines the safe power supply power based on the load upper limit power and the preset power supply safety factor, and determines the first power supply equipment sequence based on the safe power supply power. The total rated power supply power of the first power supply equipment sequence is greater than the safe power supply power. The power supply equipment in the first power supply equipment sequence is a power supply equipment set with power supply parameters that do not have abnormal working conditions in the historical power supply data.

[0099] In the above scheme, by forming the first load equipment sequence and determining the upper limit power of the load, the virtual power plant management platform can determine the total power demand of the fixed load equipment in the power grid. On this basis, the safe power supply power calculated in combination with the preset power supply safety factor ensures that the total rated power supply power of the power supply equipment can meet the load demand and leave a certain safety margin. This optimized scheduling method effectively avoids the unstable power supply caused by insufficient or overloaded power supply, and improves the power supply reliability of the entire power grid.

[0100] Then, the fixed load equipment and the stable power supply equipment are included in the first load equipment sequence and the first power supply equipment sequence for separate scheduling, which significantly reduces the overall scheduling calculation of the virtual power plant. This is because the power demand of the fixed load equipment is relatively stable, and the operating status of the stable power supply equipment is also relatively reliable, so the combined scheduling between them is relatively simple and efficient. This simplified scheduling process helps to improve the operating efficiency of the virtual power plant management platform, enabling it to respond to changes in the power grid more quickly.

[0101] Then, by selecting power supply equipment that does not have abnormal working conditions in the historical power supply data to form the first power supply equipment sequence, the virtual power plant management platform can ensure the stability and reliability of the selected power supply equipment. These devices are less likely to fail or be abnormal during the power supply process, thus reducing the power outage time and maintenance costs caused by equipment failure. At the same time, due to the optimization of the scheduling strategy, the resources in the power grid are more reasonably utilized, avoiding unnecessary energy waste and equipment idleness, and further reducing the operating costs of the virtual power plant.

[0102] The first grid dispatching unit is determined by using the preset virtual power plant allocation model, so that the virtual power plant can respond quickly according to the real-time power supply and power consumption. When an emergency occurs in the power grid or the load demand changes significantly, the management platform can quickly adjust the combination of the first power supply equipment sequence and the first load equipment sequence to meet the new power supply demand. This flexible dispatching method enhances the dispatchability of the power grid and improves its ability to respond to emergencies.

[0103] Furthermore, the above-mentioned controlling the target energy storage device in the energy storage device set to replace the target power supply device to supply power to the target power supply network includes: The second virtual machine group management module controls the target energy storage device in the energy storage device set to replace the target power supply device to supply power to the target power supply network. The virtual power plant management platform includes the second virtual machine group management module. The first virtual machine group management module and the second virtual machine group management module are parallel management modules.

[0104] In the traditional virtual power plant management and control mode, if the power supply equipment is abnormal, it may be necessary to use a single management module to dispatch the entire power grid, which may involve multiple steps and complex decision-making processes. After the introduction of the second virtual machine group management module, this module can be responsible for the dispatch and control of energy storage equipment, and work in parallel with the first virtual machine group management module. In this way, when an abnormality in the power supply equipment is detected, the second virtual machine group management module can respond quickly, quickly determine and control the target energy storage equipment to replace the abnormal power supply equipment, significantly improving the speed and flexibility of emergency response.

[0105] Moreover, through parallel management, the virtual power plant management platform can better cope with various emergencies and changes in power supply demand. Even if the first virtual machine group management module fails to work properly for some reason, the second virtual machine group management module can still take over the scheduling task of the energy storage equipment to ensure the continuity and stability of power supply. This redundant design enhances the robustness and reliability of the entire system and reduces the risk of power supply interruption caused by a single module failure.

[0106] In addition, the second virtual machine group management module is responsible for the scheduling and control of energy storage equipment, and can manage the power and output power of energy storage equipment more finely. By real-time monitoring of the status and needs of energy storage equipment, the module can optimize the charging and discharging strategy of energy storage equipment to avoid over-discharging or under-charging, thereby extending the service life of energy storage equipment. At the same time, by reasonably allocating the output power of energy storage equipment, it is possible to achieve balanced load distribution and improve the energy utilization efficiency of the entire virtual power plant.

[0107] Figure 3 FIG. 1 is a schematic diagram of a virtual power plant system according to an exemplary embodiment of the present application. Figure 3 As shown, the virtual power plant system 300 provided in this embodiment includes: a virtual power plant management platform 310, a power supply device set 320 and an energy storage device set 330, each power supply device in the power supply device set 320 and each energy storage device in the energy storage device set 330 are respectively connected to the virtual power plant management platform 310 through Internet of Things communication; The virtual power plant management platform 310 obtains historical power supply data of each power supply device in the power supply device set 320 to form a historical power supply data set, wherein the historical power supply data includes a time node sequence, power supply environment parameters corresponding to each time node in the time node sequence, and power supply power data; The virtual power plant management platform 310 obtains current power supply data of a target power supply device in the power supply device set 320, wherein the current power supply data includes current power supply environment parameters and current power supply power data; The virtual power plant management platform 310 uses a preset power supply anomaly detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set; If the virtual power plant management platform 310 determines that the power supply working state of the target power supply device is an abnormal working state, it controls the target energy storage device in the energy storage device set 330 to replace the target power supply device to supply power to the target power supply network, and the target power supply network is the power supply network corresponding to the virtual power plant management platform 310.

[0108] Optionally, the virtual power plant management platform 310 uses a preset power supply status detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set, including: The virtual power plant management platform 310 determines the historical power supply power mean and the historical power supply power standard deviation according to the historical power supply data set; The virtual power plant management platform 310 determines a power supply power fluctuation characteristic value according to the historical power supply power mean, the historical power supply power standard deviation and the current power supply power data; If the virtual power plant management platform 310 determines that the power supply fluctuation characteristic value is greater than the preset power supply fluctuation threshold, it determines that the power supply working state of the target power supply device is the abnormal working state; If the virtual power plant management platform 310 determines that the power supply fluctuation characteristic value is less than or equal to the preset power supply fluctuation threshold, it determines that the power supply working state of the target power supply device is a normal working state.

[0109] Optionally, the virtual power plant management platform 310 determines a historical power supply power mean and a historical power supply power standard deviation according to the historical power supply data set, including: The virtual power plant management platform 310 determines a historical target power supply data set from the historical power supply data set according to the current time corresponding to the current power supply data and the current power supply environment parameters; The virtual power plant management platform 310 determines the historical power supply power mean and the historical power supply power standard deviation according to the historical target power supply data set.

[0110] Optionally, controlling the target energy storage device in the energy storage device set 330 to replace the target power supply device to supply power to the target power supply network includes: The virtual power plant management platform 310 obtains the rated power supply of each energy storage device in the energy storage device set 330; The virtual power plant management platform 310 determines a target energy storage device sequence according to the rated power supply of each energy storage device and the historical power supply average, wherein the sum of the rated power supply powers of each target energy storage device in the target energy storage device sequence is greater than the historical power supply average; The virtual power plant management platform 310 controls the target energy storage device sequence to supply power to the target power supply network with the historical power supply average value.

[0111] Optionally, the virtual power plant management platform 310 controls the target energy storage device sequence to supply power to the target power supply network with the historical power supply average value, including: The virtual power plant management platform 310 obtains the current remaining power of each target energy storage device in the target energy storage device sequence to form a current remaining power sequence; The virtual power plant management platform 310 determines the power supply power of each target energy storage device in the target energy storage device sequence according to the current remaining power sequence and the historical power supply power average.

[0112] Optionally, after the virtual power plant management platform 310 determines that the power supply working state of the target power supply device is an abnormal working state, the method further includes: The virtual power plant management platform 310 records the abnormal working state into the historical power supply data of the target power supply device to mark that the power supply parameter at the current moment corresponds to the abnormal working state; Correspondingly, before the virtual power plant management platform 310 uses a preset power supply status detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set, it also includes: The virtual power plant management platform 310 removes the power supply parameters marked as the abnormal working state from the historical power supply data to update the historical power supply data set.

[0113] Optionally, the virtual power plant system further includes: a load device set 340, each load device in the load device set 340 is connected to the virtual power plant management platform 310 via Internet of Things communication; the method further includes: The virtual power plant management platform 310 obtains the historical power consumption data of each load device in the load device set 340 to form a historical power consumption data set, wherein the historical power consumption data includes the time node sequence and the power parameters corresponding to each time node in the time node sequence; The virtual power plant management platform 310 utilizes a preset virtual power plant allocation model and determines a first power grid dispatching unit based on the historical power supply data and the historical power consumption data set. The first power grid dispatching unit is composed of a first virtual machine group management module, a first power supply equipment sequence, and a first load equipment sequence. The virtual power plant management platform 310 includes the first virtual machine group management module, the power supply equipment set 320 includes the first power supply equipment sequence, and the load equipment set 340 includes the first load equipment sequence. The first virtual machine group management module is used to adjust the power supply of the first load equipment sequence to output electrical energy for the first load equipment sequence.

[0114] Figure 4 is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present application. Figure 4 As shown, an electronic device 400 provided in this embodiment includes: a processor 401 and a memory 402; wherein: The memory 402 is used to store computer programs, and the memory may also be a flash memory.

[0115] The processor 401 is used to execute the execution instructions stored in the memory to implement each step in the above method. For details, please refer to the relevant description in the above method embodiment.

[0116] Optionally, the memory 402 may be independent or integrated with the processor 401 .

[0117] When the memory 402 is a device independent of the processor 401, the electronic device 400 may further include: The bus 403 is used to connect the memory 402 and the processor 401 .

[0118] This embodiment further provides a readable storage medium, in which a computer program is stored. When at least one processor of an electronic device executes the computer program, the electronic device executes the methods provided in the above-mentioned various implementation modes.

[0119] This embodiment also provides a program product, which includes a computer program stored in a readable storage medium. At least one processor of the electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the electronic device implements the methods provided in the above various embodiments.

[0120] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0121] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A virtual power plant management and control method based on the Internet of Things, characterized in that: Applied to a virtual power plant system, the virtual power plant system comprises: a virtual power plant management platform, a power supply device set and an energy storage device set, each power supply device in the power supply device set and each energy storage device in the energy storage device set are respectively connected to the virtual power plant management platform through Internet of Things communication; the method comprises: The virtual power plant management platform obtains historical power supply data of each power supply device in the power supply device set to form a historical power supply data set, wherein the historical power supply data includes a time node sequence and power supply parameters corresponding to each time node in the time node sequence, and the power supply parameters include power supply environment parameters and power supply power parameters; The virtual power plant management platform obtains current power supply data of a target power supply device in the power supply device set, wherein the current power supply data includes current power supply environment parameters and current power supply power data; The virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set; If the virtual power plant management platform determines that the power supply working state of the target power supply device is an abnormal working state, it controls the target energy storage device in the energy storage device set to replace the target power supply device to supply power to the target power supply network, and the target power supply network is the power supply network corresponding to the virtual power plant management platform.

2. The method for managing and controlling a virtual power plant based on the Internet of Things according to claim 1, characterized in that: The virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set, including: The virtual power plant management platform determines the historical power supply power mean and the historical power supply power standard deviation according to the historical power supply data set; The virtual power plant management platform determines a power supply power fluctuation characteristic value according to the historical power supply power mean, the historical power supply power standard deviation and the current power supply power data; If the virtual power plant management platform determines that the power supply fluctuation characteristic value is greater than the preset power supply fluctuation threshold, it determines that the power supply working state of the target power supply device is the abnormal working state; If the virtual power plant management platform determines that the power supply fluctuation characteristic value is less than or equal to the preset power supply fluctuation threshold, it determines that the power supply working state of the target power supply device is a normal working state.

3. The method for managing and controlling a virtual power plant based on the Internet of Things according to claim 2, characterized in that: The virtual power plant management platform determines the historical power supply power mean and the historical power supply power standard deviation according to the historical power supply data set, including: The virtual power plant management platform determines a historical target power supply data set from the historical power supply data set according to the current time corresponding to the current power supply data and the current power supply environment parameters; The virtual power plant management platform determines the historical power supply power mean and the historical power supply power standard deviation according to the historical target power supply data set.

4. The method for managing and controlling a virtual power plant based on the Internet of Things according to claim 3 is characterized in that: The controlling a target energy storage device in the energy storage device set to replace the target power supply device to supply power to the target power supply network includes: The virtual power plant management platform obtains the rated power supply of each energy storage device in the energy storage device set; The virtual power plant management platform determines a target energy storage device sequence according to the rated power supply of each energy storage device and the historical power supply average, wherein the sum of the rated power supply powers of each target energy storage device in the target energy storage device sequence is greater than the historical power supply average; The virtual power plant management platform controls the target energy storage device sequence to supply power to the target power supply network with the historical power supply average value.

5. The method for controlling a virtual power plant based on the Internet of Things according to claim 4 is characterized in that: The virtual power plant management platform controls the target energy storage device sequence to supply power to the target power supply network with the historical power supply average value, including: The virtual power plant management platform obtains the current remaining power of each target energy storage device in the target energy storage device sequence to form a current remaining power sequence; The virtual power plant management platform determines the power supply power of each target energy storage device in the target energy storage device sequence according to the current remaining power sequence and the historical power supply power average.

6. The method for managing and controlling a virtual power plant based on the Internet of Things according to any one of claims 1 to 5, characterized in that: After the virtual power plant management platform determines that the power supply working state of the target power supply device is an abnormal working state, the method further includes: The virtual power plant management platform records the abnormal working state into the historical power supply data of the target power supply device to mark that the power supply parameters at the current moment correspond to the abnormal working state; Correspondingly, before the virtual power plant management platform uses a preset power supply status detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set, it also includes: The virtual power plant management platform removes the power supply parameters marked as the abnormal working state from the historical power supply data to update the historical power supply data set.

7. The method for managing and controlling a virtual power plant based on the Internet of Things according to claim 6, characterized in that: The virtual power plant system further includes: a load device set, each load device in the load device set is connected to the virtual power plant management platform via Internet of Things communication; the method further includes: The virtual power plant management platform obtains historical power consumption data of each load device in the load device set to form a historical power consumption data set, wherein the historical power consumption data includes the time node sequence and the power parameters corresponding to each time node in the time node sequence; The virtual power plant management platform utilizes a preset virtual power plant allocation model and determines a first power grid dispatching unit based on the historical power supply data and the historical power consumption data set. The first power grid dispatching unit is composed of a first virtual machine group management module, a first power supply equipment sequence, and a first load equipment sequence. The virtual power plant management platform includes the first virtual machine group management module, the power supply equipment set includes the first power supply equipment sequence, and the load equipment set includes the first load equipment sequence. The first virtual machine group management module is used to adjust the power supply of the first load equipment sequence to output electrical energy for the first load equipment sequence.

8. A virtual power plant system, characterized in that: include: A virtual power plant management platform, a power supply device set, and an energy storage device set, wherein each power supply device in the power supply device set and each energy storage device in the energy storage device set are respectively connected to the virtual power plant management platform via Internet of Things communication; The virtual power plant management platform obtains historical power supply data of each power supply device in the power supply device set to form a historical power supply data set, wherein the historical power supply data includes a time node sequence, power supply environment parameters corresponding to each time node in the time node sequence, and power supply power data; The virtual power plant management platform obtains current power supply data of a target power supply device in the power supply device set, wherein the current power supply data includes current power supply environment parameters and current power supply power data; The virtual power plant management platform uses a preset power supply anomaly detection model and determines the power supply working status of the target power supply device according to the current power supply environment parameters and the historical power supply data set; If the virtual power plant management platform determines that the power supply working state of the target power supply device is an abnormal working state, it controls the target energy storage device in the energy storage device set to replace the target power supply device to supply power to the target power supply network, and the target power supply network is the power supply network corresponding to the virtual power plant management platform.

9. An electronic device, characterized in that: include: processor; as well as, A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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