Virtual power plant anomaly detection system and method

Abstract

The invention is suitable for the technical field of virtual power plant detection control, and provides a virtual power plant anomaly detection system and method, and the detection system comprises an information collection module, a numbering module, a data processing module, a recognition and classification module, an operation processing module, a wireless communication module, an alarm, a memory, a processing center, and a smart phone. The information acquisition module, the numbering module, the data processing module, the identification and classification module, the operation processing module, the wireless communication module, the alarm and the memory are respectively connected with the processing center; the smart phone is in automatic networking connection with the wireless communication module within the range of a wireless network or the Internet; the invention further provides a virtual power plant anomaly detection method. The abnormity of the virtual power plant can be automatically detected and automatically classified, and various kinds of abnormity can be automatically processed, so that normal operation of the virtual power plant is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of virtual power plant detection and control, and more specifically, relates to a virtual power plant anomaly detection system and method thereof involving artificial intelligence. Background Art

[0002] A virtual power plant (VPP), also known as a smart energy management system, refers to a power coordination management system that uses advanced information and communication technology and software systems to achieve the aggregation and coordinated optimization of distributed energy sources such as distributed power sources, energy storage systems, controllable loads, electric vehicles, and charging piles, so as to participate in the power market and power grid operation as a special power plant. It is not a real power plant, but a smart grid technology that uses a distributed power management system to participate in power grid operation and dispatch, and achieves "source-load-grid" aggregation optimization. It achieves grid balance by coordinating power generation resources and adjusting part of the power demand, reducing peak power consumption and increasing "power elasticity" to achieve the same effect as power generation by power plants. It is an electricity "porter" and an operating platform connecting power trading centers and resource aggregators. It organizes resource entities to participate in various power market transactions and completes related settlements and profit distribution. Therefore, the design and innovation of the pricing mechanism and profit distribution mechanism of the virtual power plant operating platform for different resource combinations is the key to stimulating various user-side resources to actively participate in virtual power plants and improve the overall benefits of virtual power plants.

[0003] Currently, there are many virtual power plant patents disclosed, such as "A control method, device and system for a virtual power plant (publication number: CN116700404A)", "A virtual power plant system management and control method and system (publication number: CN116934094A)", and "A self-dispatching virtual power plant system (publication number: CN117878886A)". They all belong to the operation control technology of virtual power plants, but none of them disclose their abnormality detection technology. Summary of the invention

[0004] In order to address the deficiencies in the prior art, the purpose of the present invention is to provide a virtual power plant abnormality detection system and method thereof. By setting an information collection module, a configuration number module, a data processing module, an identification and classification module, and an operation processing module, the abnormalities of the virtual power plant can be automatically detected and classified, and various types of abnormalities can be automatically processed to ensure the normal operation of the virtual power plant.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A virtual power plant anomaly detection system comprises an information collection module, a configuration number module, a data processing module, an identification and classification module, an operation processing module, a wireless communication module, an alarm, a memory, a processing center, and a smart phone; the information collection module, the configuration number module, the data processing module, the identification and classification module, the operation processing module, the wireless communication module, the alarm, and the memory are respectively connected to the processing center; the smart phone is automatically networked with the wireless communication module within the range of a wireless network or the Internet;

[0007] The wireless communication module is provided with a wireless network unit, which is responsible for sending and receiving wireless network signals and automatically networking with a smart phone within the range of a wireless network or the Internet;

[0008] The alarm device compares the actual operating data with the normal operating range of the virtual power plant preset in the memory, and automatically sounds an audible alarm and notifies for processing if there is any inconsistency;

[0009] The memory is responsible for storing information of the information collection module, the configuration number module, the data processing module, the identification classification module, the operation processing module, the wireless communication module, the alarm, and the normal operation range of the virtual power plant;

[0010] The processing center is responsible for the information collection module, numbering module, data processing module, identification and classification module, operation processing module, wireless communication module, alarm, and storage information transmission. It is the hub center of the system and compares the actual operation data with the normal operation range of the virtual power plant preset in the storage: if they are consistent, the operation continues; if they are inconsistent, the alarm is transmitted to the alarm and notified for processing;

[0011] The information collection module includes an information aggregation unit, a coordination optimization unit, and a data classification unit, which obtains the operating status data of the power generation equipment and power consumption equipment of the virtual power plant through intelligent sensors and transmits it to the numbering module;

[0012] The configuration numbering module includes an information acquisition unit, a group numbering unit, and a power acquisition unit, which are responsible for grouping and numbering the acquired information and dividing the detection cycle into multiple task intervals according to the device execution information, obtaining the detection frequency of each interval, and passing it to the data processing module;

[0013] The data processing module includes a data cleaning unit, a processing unit, and a feature extraction unit, which are responsible for performing data cleaning and feature extraction on the collected data to obtain identifiable operating data for subsequent analysis and transmission to the processing center;

[0014] The identification and classification module includes a matching identification unit, an abnormality classification unit, and a cause analysis unit, which is responsible for matching the abnormality information with the industry database and performing abnormality identification and classification to determine the type and cause of the abnormality and pass it to the operation processing module;

[0015] The operation processing module includes a risk classification unit, a processing plan unit, an automatic adjustment unit, and an exception processing unit, which are responsible for performing risk assessment according to the severity of the exception and taking corresponding processing measures to ensure the stable operation of the power system.

[0016] The present invention also provides a virtual power plant detection method, which is applied to a virtual power plant anomaly detection system, and the method comprises the following steps:

[0017] S10, during detection, the information collection module obtains the operating status data of the power generation equipment and power consumption equipment of the virtual power plant through the intelligent sensor, and transmits it to the numbering module;

[0018] S20, the numbering module groups and numbers the obtained information and divides the detection cycle into multiple task intervals according to the device execution information, obtains the detection frequency of each interval, and transmits it to the data processing module;

[0019] S30, the data processing module performs data cleaning and feature extraction on the collected data to obtain identifiable operation data for subsequent analysis and transmits it to the processing center;

[0020] S40, the processing center compares the actual operation data with the normal operation range of the virtual power plant preset in the memory: if they are consistent, the operation continues; if they are inconsistent, the alarm is transmitted and notified for processing;

[0021] S50, the identification and classification module matches the abnormal information with the industry database and performs abnormal identification and classification to determine the type and cause of the abnormality, and passes it to the operation processing module;

[0022] S60: The operation processing module conducts risk assessment according to the severity of the abnormality and takes corresponding processing measures to ensure the stable operation of the power system.

[0023] Further, the step S10 comprises the following steps:

[0024] S11. The information aggregation unit collects real-time data of various energy resources such as the operating status, power generation, and load of distributed energy equipment through sensors and monitoring systems, and transmits it to the coordination and optimization unit;

[0025] S12, the coordination and optimization unit compares the real-time data with the historical data and uses intelligent algorithms and models to predict and reasonably allocate the power generation and load of each distributed energy device, and transmits it to the data classification unit;

[0026] S13. The data classification unit classifies the optimized data into power source type, load type, energy storage type, and hybrid type to reflect the different roles and functions of the virtual power plant in the power system.

[0027] Further, the step S20 comprises the following steps:

[0028] S21, the information acquisition unit monitors the operating status of the power plant's current information, time information, and power change information within a specific time period, and transmits the information to the grouping numbering unit;

[0029] S22, the grouping and numbering unit obtains the current value of each input and output and groups the same current into a group and numbers it, sums the time value of each group, and transmits it to the power acquisition unit;

[0030] S23, the power acquisition unit acquires each group of power according to the current value and the total time value to obtain the input and output information of each group of power for subsequent analysis and processing.

[0031] Further, the step S30 comprises the following steps:

[0032] S31. The data cleaning unit purifies the collected real-time data of various energy resources through the industrial Internet of Things gateway and cloud computing technology for subsequent processing and transmits it to the processing unit;

[0033] S32, the processing unit counts and checks the local power data, registers the identity information of the staff, counts the aggregated local data, and transmits it to the feature extraction unit;

[0034] S33, the feature extraction unit realizes the aggregation and coordinated optimization of various geographically dispersed distributed energy resources (DER) through advanced communication technology and software architecture.

[0035] Further, the step S50 comprises the following steps:

[0036] S51, the matching identification unit realizes the aggregation and coordinated optimization of energy resources of distributed generation, energy storage system, controllable load, and electric vehicle according to information communication technology and software system, and transmits it to the abnormal classification unit;

[0037] S52, the abnormality classification unit matches and identifies the abnormalities into resource abnormalities, communication abnormalities, control abnormalities, market abnormalities, and security abnormalities, and transmits them to the cause analysis unit;

[0038] S53. The cause analysis unit analyzes the causes of technical bottlenecks, imperfect market mechanisms, low participation, and lack of unified market access standards based on abnormal classification to ensure the normal operation of the virtual power plant.

[0039] Further, the step S60 comprises the following steps:

[0040] S61. The risk classification unit classifies the risks of the virtual power plant into technical risks, market and economic risks, and data privacy and security risks, and transmits them to the processing plan unit;

[0041] S62, the processing plan unit implements countermeasures for power grid security, data security, operation and maintenance security, environmental security, and regulatory and legal security according to risk classification, and transmits them to the automatic adjustment unit;

[0042] S63, the automatic adjustment unit monitors the operation status of the power grid in real time through the intelligent control system. If there is an abnormality, the system automatically adjusts the balance of power supply and demand and transmits it to the abnormality processing unit;

[0043] S64, the abnormality handling unit maintains the communication lines and repairs the system, adjusts the operator, cancels the regional restrictions, improves the market mechanism, and rationalizes the concepts, and passes it to the operation recovery unit;

[0044] S65, the operation recovery unit restores access to the electricity market and enables the virtual power plant to resume normal operation by integrating resources and improving demand response and emergency dispatch capabilities.

[0045] A virtual power plant anomaly detection system provided by the present invention also includes a computer device and a computer-readable storage medium; the computer device includes a memory and various functional modules, the memory stores a computer program, and the various functional modules implement the steps of any one of the above-mentioned virtual power plant anomaly detection methods when executing the computer program; the computer-readable storage medium stores a computer program, and the computer program implements the steps of any one of the above-mentioned virtual power plant anomaly detection methods when executed by the various functional modules.

[0046] The present invention also provides a virtual power plant anomaly detection control device, which is implemented by using the virtual power plant anomaly detection system and the virtual power plant anomaly detection method described above.

[0047] The beneficial effects of the present invention compared with the prior art are as follows:

[0048] By setting up the information collection module, the configuration number module, the data processing module, the identification and classification module, and the operation processing module, the anomalies of the virtual power plant can be automatically detected and classified, and various anomalies can be automatically processed to ensure the normal operation of the virtual power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or exemplary technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 It is a schematic diagram of the system module of the present invention;

[0051] Figure 2 This is a schematic diagram of the information collection module of the present invention;

[0052] Figure 3 It is a schematic diagram of the preparation numbering module of the present invention;

[0053] Figure 4 It is a schematic diagram of a data processing module of the present invention;

[0054] Figure 5 This is a schematic diagram of the recognition and classification module of the present invention;

[0055] Figure 6 It is a schematic diagram of the operation processing module of the present invention;

[0056] Figure 7 It is a schematic diagram of the method flow of the present invention;

[0057] Figure 8 This is a schematic diagram of the process decomposition of step S10 in the method flow of the present invention;

[0058] Fig. 9 This is a schematic diagram of the process decomposition of step S20 in the method flow of the present invention;

[0059] Fig.10 This is a schematic diagram of the process decomposition of step S30 in the method flow of the present invention;

[0060] Fig.11 This is a schematic diagram of the process decomposition of step S50 in the method flow of the present invention;

[0061] Fig.12 It is a schematic diagram of the program decomposition of step S60 in the method flow of the present invention. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0063] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments:

[0064] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0065] It should be noted that when a module is referred to as being "disposed" or "disposed on" another module, it can be directly on the other module or indirectly on the other module. When a module is referred to as being "connected to" or "connected to" another module, it can be directly connected to the other module or indirectly connected to the other module.

[0066] In the description of this application, "multiple" means two or more, unless otherwise clearly and specifically defined. "Several" means one or more, unless otherwise clearly and specifically defined.

[0067] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0068] Please refer to Figure 1 As shown, the present invention provides a virtual power plant abnormality detection system, including an information acquisition module, a configuration number module, a data processing module, an identification and classification module, an operation processing module, a wireless communication module, an alarm, a memory, a processing center, and a smart phone; the information acquisition module, the configuration number module, the data processing module, the identification and classification module, the operation processing module, the wireless communication module, the alarm, and the memory are respectively connected to the processing center; the smart phone is automatically networked with the wireless communication module within the range of a wireless network or the Internet.

[0069] The wireless communication module is provided with a wireless network unit, which is responsible for sending and receiving wireless network signals and automatically networking with a smart phone within the range of a wireless network or the Internet.

[0070] The alarm compares the actual operating data with the normal operating range of the virtual power plant preset in the memory, and automatically sounds an audible alarm and notifies for processing if there is any inconsistency.

[0071] The memory is responsible for storing information of the information acquisition module, the configuration numbering module, the data processing module, the identification and classification module, the operation processing module, the wireless communication module, and the alarm, as well as the normal operating range of the virtual power plant.

[0072] The processing center is responsible for the information collection module, numbering module, data processing module, identification and classification module, operation processing module, wireless communication module, alarm, and storage information transmission. It is the hub center of the system and compares the actual operation data with the normal operating range of the virtual power plant preset in the memory: if they are consistent, the operation continues; if they are inconsistent, the alarm is passed to the alarm and notified for processing.

[0073] See also Figure 2 As shown, the information collection module includes an information aggregation unit, a coordination optimization unit, and a data classification unit. It obtains the operating status data of the power generation equipment and power-consuming equipment of the virtual power plant through intelligent sensors and passes it to the configuration number module.

[0074] Furthermore, the information aggregation unit collects real-time data on the operating status, power generation, and load of various energy resources of distributed energy equipment through sensors and monitoring systems, and transmits it to the coordination optimization unit; the coordination optimization unit compares the real-time data with the historical data and reasonably allocates the power generation and load of each distributed energy equipment through intelligent algorithms and model predictions, and transmits it to the data classification unit; the data classification unit classifies the optimized data into power type, load type, energy storage type, and hybrid type to reflect the different roles and functions of virtual power plants in the power system.

[0075] See also Figure 3 As shown, the configuration numbering module includes an information acquisition unit, a group numbering unit, and a power acquisition unit, which are responsible for grouping and numbering the obtained information and dividing the detection cycle into multiple task intervals according to the device execution information, obtaining the detection frequency of each interval, and passing it to the data processing module.

[0076] Furthermore, the information acquisition unit monitors the operating status of the power plant's current information, time information, and power change information within a specific time period, and transmits them to the grouping and numbering unit; the grouping and numbering unit obtains the current value of each input and output and groups the same current into a group and numbers them to sum up the time value of each group, and transmits it to the power acquisition unit; the power acquisition unit obtains the power of each group based on the current value and the total time value to obtain the power input and output information of each group for subsequent analysis and processing.

[0077] See also Figure 4 As shown, the data processing module includes a data cleaning unit, a processing unit, and a feature extraction unit, which are responsible for performing data cleaning and feature extraction on the collected data to obtain identifiable operating data for subsequent analysis and transmission to the processing center.

[0078] Furthermore, the data cleaning unit purifies the collected real-time data of various energy resources through the industrial Internet of Things gateway and cloud computing technology for subsequent processing, and transmits it to the processing unit; the processing unit counts and checks the local power data, registers the identity information of the staff, counts the aggregated local data, and transmits it to the feature extraction unit; the feature extraction unit realizes the aggregation and coordinated optimization of various geographically dispersed distributed energy resources (DER) through advanced communication technology and software architecture.

[0079] See also Figure 5 As shown, the identification and classification module includes a matching identification unit, an abnormal classification unit, and a cause analysis unit, which is responsible for matching the abnormal information with the industry database and performing abnormal identification and classification to determine the type and cause of the abnormality and pass it to the operation processing module.

[0080] Furthermore, the matching and identification unit realizes the aggregation and coordinated optimization of energy resources of distributed power generation, energy storage system, controllable load and electric vehicles according to information and communication technology and software system, and transmits them to the abnormality classification unit; the abnormality classification unit classifies them into resource abnormality, communication abnormality, control abnormality, market abnormality and safety abnormality after matching and identification, and transmits them to the cause analysis unit; the cause analysis unit analyzes the causes of technical bottlenecks, imperfect market mechanism, low participation and lack of unified market access standards according to the abnormality classification to ensure the normal operation of the virtual power plant.

[0081] See also Figure 6 As shown, the operation processing module includes a risk classification unit, a processing plan unit, an automatic adjustment unit, an abnormality processing unit, and an operation recovery unit, which is responsible for performing risk assessment according to the severity of the abnormality and taking corresponding processing measures to ensure the stable operation of the power system.

[0082] Furthermore, the risk classification unit divides the risks of the virtual power plant into technical risks, market and economic risks, data privacy and security risks, and transmits them to the processing plan unit; the processing plan unit implements countermeasures for grid security, data security, operation and maintenance security, environmental safety, and regulatory and legal security according to the risk classification, and transmits them to the automatic adjustment unit; the automatic adjustment unit monitors the operating status of the grid in real time through the intelligent control system. If there is an abnormality, the system automatically adjusts the balance of power supply and demand and transmits it to the abnormality processing unit; the abnormality processing unit maintains the communication lines and repairs the system, adjusts the operator, cancels regional restrictions, improves the market mechanism, straightens out the concepts, and transmits them to the operation recovery unit; the operation recovery unit restores access to the power market through resource integration, improving demand response and emergency dispatch capabilities, and enables the virtual power plant to resume normal operation.

[0083] How the system works:

[0084] During detection, the information acquisition module obtains the operating status data of the power generation equipment and power-consuming equipment of the virtual power plant through intelligent sensors, and passes it to the numbering module; then the numbering module groups and numbers the obtained information and divides the detection cycle into multiple task intervals according to the equipment execution information, obtains the detection frequency of each interval, and passes it to the data processing module; the data processing module performs data cleaning and feature extraction on the collected data to obtain identifiable operating data for subsequent analysis and passes it to the processing center; then the processing center compares the actual operating data with the normal operating range of the virtual power plant preset in the memory: if they are consistent, the operation continues; if they are inconsistent, the alarm is passed to the alarm and notified for processing; the identification and classification module matches the abnormal information with the industry database and performs abnormal identification and classification to determine the type and cause of the abnormality, and passes it to the operation processing module; then the operation processing module conducts risk assessment according to the severity of the abnormality and takes corresponding treatment measures to ensure the stable operation of the power system.

[0085] When system managers are outdoors or away from home, they can use smartphones to automatically connect to the wireless communication module within the range of a wireless network or the Internet to control or monitor the detection status of the virtual power plant, thereby realizing intelligent and networked management and improving the detection efficiency of the virtual power plant.

[0086] See also Figure 7 As shown, the present invention also provides a virtual power plant detection method, which is applied to a virtual power plant anomaly detection system, and the method comprises the following steps:

[0087] S10, during detection, the information collection module obtains the operating status data of the power generation equipment and power consumption equipment of the virtual power plant through the intelligent sensor, and transmits it to the numbering module;

[0088] See also Figure 8 As shown, the step S10 comprises the following steps:

[0089] S11. The information aggregation unit collects real-time data of various energy resources such as the operating status, power generation, and load of distributed energy equipment through sensors and monitoring systems, and transmits it to the coordination and optimization unit;

[0090] It is further explained that the data of various energy resources such as solar photovoltaic power stations, wind turbines, batteries, and the output and consumption of various energy resources are collected in real time through various sensors and monitoring systems to accurately understand the current energy supply and demand status and transmit them to the intelligent management system of the virtual power plant. The collected data are analyzed and processed to provide monitoring and analysis of the overall operation of the virtual power plant. By predicting and optimizing the demand for energy production and consumption, as well as the price of the energy market and the needs of users, the system can formulate the best energy scheduling plan. It can also use big data analysis technology to conduct trend analysis on price fluctuations in the energy market to obtain the maximum economic benefit in the balance between supply and demand. The system will allocate energy to different users to maintain a stable supply of energy.

[0091] S12, the coordination and optimization unit compares the real-time data with the historical data and uses intelligent algorithms and models to predict and reasonably allocate the power generation and load of each distributed energy device, and transmits it to the data classification unit;

[0092] It is further explained that through advanced communication technology and software architecture, various geographically dispersed distributed loads are aggregated and coordinated and optimized to form a virtual equivalent external power regulation service. By collecting and analyzing a large amount of real-time data for subsequent detection and analysis, and combining market electricity prices and grid loads and other factors to conduct electricity market transactions and balance energy supply and demand, energy is optimized based on real-time information and historical data. For example, the system can intelligently adjust the operating status of solar photovoltaic power stations and wind turbines according to daily weather forecasts to maximize the use of natural energy. It can also intelligently manage the charging and discharging of batteries according to users' electricity usage habits and needs to avoid energy waste. The intelligent algorithm refers to determining the optimal scheduling strategy through analysis of equipment status and energy production and consumption data to achieve the optimal energy utilization effect, so as to promote the sustainable development of virtual power plants.

[0093] S13. The data classification unit classifies the optimized data into power source type, load type, energy storage type, and hybrid type to reflect the different roles and functions of the virtual power plant in the power system.

[0094] To further explain, the power type refers to virtual power plants that can provide electricity, which generate electricity by aggregating renewable energy resources such as solar energy and wind energy, with a focus on integrating distributed energy resources to cope with changes in electricity demand; the load type refers to the focus on managing and regulating power loads, by aggregating market-oriented power users with load regulation capabilities such as electric vehicles, adjustable loads, and interruptible loads, and providing flexible load-side response and regulation services to the outside world as a whole, playing an important role in demand-side management; the energy storage type refers to the application of energy storage technology, which balances supply and demand fluctuations in the power grid by storing and releasing electrical energy. By using battery energy storage systems, the stored electrical energy can be released during peak electricity demand, or excess electricity can be stored when there is an oversupply of electricity, thereby helping to stabilize the operation of the power grid; the hybrid type refers to a combination of the above types, which has the functions of power supply, load and energy storage at the same time, so as to more comprehensively respond to various challenges of the power system. For example, fuel vehicles can generate electricity, store energy and provide power loads.

[0095] S20, the numbering module groups and numbers the obtained information and divides the detection cycle into multiple task intervals according to the device execution information, obtains the detection frequency of each interval, and transmits it to the data processing module;

[0096] See also Fig. 9 As shown, the step S20 comprises the following steps:

[0097] S21, the information acquisition unit monitors the operating status of the power plant's current information, time information, and power change information within a specific time period, and transmits the information to the grouping numbering unit;

[0098] It is further explained that by monitoring the operating status of the power plant within a specific time period, including obtaining current information, time information and power change information, and obtaining the input current and output current during the operation of the power plant, including the input current value, the number of inputs, and the time value corresponding to the current value each time the input occurs, it is also necessary to obtain the output current value, the number of times, and the time value corresponding to each output current value; it also includes data such as production electricity, battery energy storage, and household electricity consumption, so that real-time monitoring and management of energy usage can be achieved; by conducting a detailed analysis of the distribution of various energy management and storage systems in different geographical areas, at different levels and scales, and at the same time predicting the energy supply and demand situation to obtain data, it is helpful to optimize the efficiency of energy use, ensure the rational allocation and use of energy, and realize the effective use of urban distributed energy; and take corresponding encryption measures to protect user data, prevent information leakage or unauthorized access, so as to ensure data security and privacy protection.

[0099] S22, the grouping and numbering unit obtains the current value of each input and output and groups the same current into a group and numbers it, sums the time value of each group, and transmits it to the power acquisition unit;

[0100] It is further explained that by obtaining the current values ​​of each input and output in sequence, and dividing the same current into a group, the time values ​​of each group of current production process are summed up to obtain the total production time, in order to analyze the usage of each group of electricity; including reading the execution sequence number, taking the execution device information and the execution device information of the acquisition device as a group of processing data, and generating a configuration number; different group numbers can be set according to distributed generators, controllable loads, distributed energy storage facilities, etc.; group numbering can also be carried out according to the requirements of the local power management department, or classified and numbered according to its size or region, or group numbering can be carried out according to specific implementation plans or management requirements, and group numbering can also be adjusted according to technological and market developments.

[0101] S23, the power acquisition unit acquires each group of power according to the current value and the total time value to obtain the input and output information of each group of power for subsequent analysis and processing.

[0102] It is further explained that by obtaining the input and output information of the power plant operation information and using it for the operation simulation and regional division of the virtual power plant, it not only involves the detailed recording and analysis of the current and power, but also requires the effective organization and processing of the data for subsequent risk detection and other analysis; setting a data transmission channel, and dividing the detection cycle into multiple task intervals according to the execution information of the equipment, and obtaining the detection frequency of each interval to ensure the accuracy and efficiency of abnormal detection; based on the pre-built charging constraints and discharging constraints of electric vehicles, the minimum charging amount and maximum discharging amount of the target virtual power plant for electric vehicles can be obtained, and combined with the minimum load power provided by the target virtual power plant to the load, a resource acquisition prediction model is constructed to optimize the power scheduling plan; through the resource acquisition prediction model, the virtual power plant can obtain the power scheduling plan when the resource acquisition is the largest according to the constraints, and can more reasonably allocate and manage power resources to ensure the stable operation of the power system, while improving the utilization efficiency of power resources.

[0103] S30, the data processing module performs data cleaning and feature extraction on the collected data to obtain identifiable operation data for subsequent analysis and transmits it to the processing center;

[0104] See also Fig.10 As shown, the step S30 includes the following steps:

[0105] S31. The data cleaning unit purifies the collected real-time data of various energy resources through the industrial Internet of Things gateway and cloud computing technology for subsequent processing and transmits it to the processing unit;

[0106] It is further explained that the data cleaning process of the virtual power plant involves multiple key steps and components to ensure the accuracy and completeness of the data, thereby supporting the effective operation and management of the virtual power plant. The industrial Internet of Things gateway plays a core role in data collection and processing. It can access multiple smart meters for real-time data collection and transmit the data to the management center platform. The built-in multi-network mutual backup and breakpoint resumption functions ensure the smooth communication network and data integrity. It also has edge computing functions, which can perform data cleaning and filtering locally, so as to better adapt to high-concurrency data transmission scenarios, while reducing the pressure and cost of platform operation; the computing power sharing achieved through cloud computing enables the application of big data cleaning technology to purify massive data, and can optimize the analysis that traditionally requires a lot of manpower in the time and space dimensions, thereby supporting the concept of integrating virtual power plants into new energy and low-carbon, flexible digital power grids, and using cloud computing technology to achieve computing power sharing and big data cleaning technology to ensure data accuracy and completeness, providing support for the operation and management of virtual power plants.

[0107] S32, the processing unit counts and checks the local power data, registers the identity information of the staff, counts the aggregated local data, and transmits it to the feature extraction unit;

[0108] It is further explained that by combining facial recognition and fingerprint recognition to identify the user's identity, user information is retrieved from the database, which is convenient for statistics on regional electricity users and user payment. By statistics on local power data and checking and verifying it, incorrectly entered data is eliminated, and the business visits the data household and re-enters the data to improve the accuracy of the power system. By investigating, locating and tracking suspicious electricity users, the occurrence of electricity theft is fundamentally eliminated; data on various energy resources, including solar photovoltaic power stations, wind turbines, batteries, etc., are collected in real time through sensors and monitoring systems and transmitted to the intelligent management system of the virtual power plant. The collected data is analyzed and processed, the demand for energy production and consumption is predicted and optimized, the best energy scheduling plan is formulated, and big data analysis technology is used to analyze the trend of price fluctuations in the energy market in order to obtain the maximum economic benefit in the balance between supply and demand.

[0109] S33, the feature extraction unit realizes the aggregation and coordinated optimization of various geographically dispersed distributed energy resources (DER) through advanced communication technology and software architecture.

[0110] It is further explained that the system implemented by advanced communication technology and software architecture can aggregate various geographically dispersed distributed energy resources (DER), and coordinate and optimize the use of these resources to achieve the purpose of improving the flexibility, reliability and efficiency of the power system. It not only helps to solve the stability and reliability problems of the power system, but also promotes the consumption of clean energy and reduces dependence on traditional coal-fired power, thereby supporting energy transformation and sustainable development. It aggregates dispersed DER (solar energy, wind energy, energy storage system, etc.) through technical means, and coordinates the use of these resources through optimization algorithms to achieve the best economic and environmental effects; DER is usually distributed in different geographical locations, It can be residential, commercial buildings, industrial facilities, etc., and can adapt to a variety of different environments and conditions; through intelligent management and optimized use of distributed energy, virtual power plants help balance supply and demand, reduce power outages, and improve the overall efficiency and reliability of the power system; it is also affected by the policy environment, including industry policy background, encouraging policy action plans, etc., which provide support and guidance for the technological development of virtual power plants; the risk detection center receives the detection data and detects and analyzes the data according to the preset normal operating range. If the data is within the normal operating range, the equipment is considered normal, otherwise it is considered abnormal. By comparing the actual data with the preset normal range, it is determined whether the equipment is in normal condition.

[0111] S40, the processing center compares the actual operation data with the normal operation range of the virtual power plant preset in the memory: if they are consistent, the operation continues; if they are inconsistent, the alarm is transmitted to the alarm and notified for processing;

[0112] It is further explained that the data is detected and analyzed to determine whether there are any abnormalities, including monitoring the operating status of power generation equipment and power-consuming equipment to ensure that they are within the normal operating range; the preset normal operating range refers to the current value, time value, and power change value of the virtual power plant during normal operation.

[0113] S50, the identification and classification module matches the abnormal information with the industry database and performs abnormal identification and classification to determine the type and cause of the abnormality, and transmits it to the operation processing module;

[0114] See also Fig.11 As shown, the step S50 comprises the following steps:

[0115] S51, the matching identification unit realizes the aggregation and coordinated optimization of energy resources of distributed generation, energy storage system, controllable load, and electric vehicle according to information communication technology and software system, and transmits it to the abnormal classification unit;

[0116] It is further explained that through the aggregation and coordination of these technologies, the virtual power plant can participate in the power market and power grid operation as a special power plant to achieve coordinated power management, which can be summarized as "communication" and "aggregation", that is, the connection of various distributed energy resources is achieved through communication technology, and these resources are integrated into a larger system through aggregation to more effectively manage and utilize these resources; through advanced communication technology and software architecture, the aggregation and coordinated optimization of various geographically dispersed DERs are achieved to improve the flexibility, reliability and economy of the power system. By aggregating these dispersed resources, the virtual power plant can make real-time adjustments according to the needs of the power grid and the price signals of the power market, thereby effectively balancing supply and demand, reducing dependence on traditional power plants, and promoting the use of renewable energy; with the acceleration of energy green transformation and the randomness, intermittency and volatility of new energy power generation, the virtual power plant, as a flexible power coordination management system, its operating mechanism and key technologies are also constantly developing and improving. By aggregating various distributed energy resources, it can better adapt to the challenges brought by new energy access, improve the flexible adjustment ability of the power system, and promote the efficient use of renewable energy.

[0117] S52, the abnormality classification unit matches and identifies the abnormalities into resource abnormalities, communication abnormalities, control abnormalities, market abnormalities, and security abnormalities, and transmits them to the cause analysis unit;

[0118] Further explanation: resource anomalies include distributed energy anomalies caused by a sudden drop or stop in power generation from renewable energy sources such as wind power generation and photovoltaic power generation, or due to weather changes, equipment failures, etc.; energy storage system anomalies caused by limited or failed charging and discharging capabilities of energy storage equipment, or battery aging, system failures, etc.; controllable loads at the user end fail to adjust as expected, or controllable load anomalies are caused by changes in user behavior, equipment failures, or communication interruptions; communication anomalies refer to interruptions or delays in communication with distributed resources, resulting in the control center being unable to obtain resource status information or send control instructions in a timely manner, and the power market, power grid dispatching center, and other factors causing communication anomalies. Abnormal communication between other systems may affect participation in market bidding, acceptance of dispatch instructions, etc.; the control abnormality refers to the failure or unreasonableness of the control strategy, which leads to the inability to effectively coordinate various resources and achieve the expected regulation effect, or equipment failure or software problems lead to the inability to correctly generate or execute control instructions; the market abnormality refers to the drastic fluctuations in electricity market prices, resulting in unstable returns from participating in market bidding, changes in market rules or policy adjustments, which affect the operating model and market participation method; the security abnormality refers to the network security threats such as hacker attacks and data leakage that may be faced during operation, and the security issues of distributed resources such as equipment theft and damage, which affect the operation of the virtual power plant.

[0119] S53. The cause analysis unit conducts cause analysis on technical bottlenecks, imperfect market mechanisms, low participation, and lack of unified market access standards based on abnormal classification to ensure the normal operation of the virtual power plant.

[0120] It is further explained that the technical bottleneck refers to the use of Internet of Things technology to aggregate adjustable loads, energy storage and power supply resources in different spaces to achieve coordinated sharing and autonomous optimization configuration, but in actual operation, it still faces technical challenges; the imperfect market mechanism refers to the fact that when participating in the spot market and ancillary service market, it is difficult for the user side to fully play its role due to the imperfect mechanism for participating in the spot market. In the medium and long-term market, the relevant rules for the participation of virtual power plants are still imperfect, which affects their enthusiasm for participating in the market; the low participation rate refers to the fact that most virtual power plants are organized by relevant government departments, power grid companies or dispatching agencies, and invitation signals are sent out, mainly focusing on load side regulation, with little participation from the power supply side and energy storage side; the lack of unified market access standards refers to the fact that when participating in different markets, virtual power plants need to meet different technical requirements such as frequency regulation, standby, moment of inertia, climbing, etc. according to different ancillary service transaction types, which increases the complexity and cost of their participation in the market.

[0121] S60: The operation processing module performs risk assessment according to the severity of the abnormality and takes corresponding processing measures to ensure the stable operation of the power system.

[0122] See also Fig.12 As shown, the step S60 comprises the following steps:

[0123] S61. The risk classification unit classifies the risks of the virtual power plant into technical risks, market and economic risks, and data privacy and security risks, and transmits them to the processing plan unit;

[0124] To further explain, the technical risk refers to the fact that virtual power plants involve the integration of multiple different types of energy facilities, intelligent control systems, data analysis technologies, and communication technologies. Failures, instabilities, or security vulnerabilities in these technologies may affect the operation of virtual power plants and the stability of energy supply. Rapid changes in technology may cause old technologies to quickly become obsolete, requiring continuous investment and updates, which increases technical risks. The market and economic risks refer to the fact that virtual power plants may participate in energy markets, such as electricity trading markets, but factors such as market price fluctuations and changes in supply and demand may have an impact on the economic benefits of virtual power plants. Market price volatility may lead to unstable income, thereby affecting investment returns. Policy changes and uncertainty in energy market policies may also have an impact on the sustainability of virtual power plants. The data privacy and security risks refer to the fact that virtual power plants need to process large amounts of energy data and user information, including production capacity, load conditions, market transactions, etc. These data are subject to unauthorized access, leakage, or hacker attacks, which may pose a threat to user privacy and energy security.

[0125] S62, the processing plan unit implements countermeasures for power grid security, data security, operation and maintenance security, environmental security, and regulatory and legal security according to the risk classification, and transmits the countermeasures to the automatic adjustment unit;

[0126] To further explain, the grid security refers to the connection and interaction between the virtual power plant and the grid, which involves risks such as grid collapse, voltage instability, and grid failure. Countermeasures are taken to ensure the safe and stable operation of the grid; the data security refers to the scheduling and control of various energy sources by the virtual power plant through the integrated energy management system, which involves a large amount of data exchange and processing. Corresponding security measures are taken for risks such as data transmission security, data privacy protection, and network attacks to ensure data security and privacy; the operation and maintenance security refers to the need for operation and maintenance of the equipment and systems of the virtual power plant, which requires consideration of factors such as the safety of the equipment, the safety of the automated control system, and the safety awareness of the operation and maintenance personnel to ensure the safety of the operation and maintenance process; the environmental safety refers to the scheduling and control of various energy sources by the virtual power plant, the increase in emissions, noise pollution, etc., which have a certain impact on the environment, and corresponding measures are taken to reduce the negative impact on the environment; the regulatory and legal security refers to the need for virtual power plants to comply with relevant laws, regulations, and regulatory standards to ensure compliance with electricity safety standards, environmental protection standards, etc., to ensure that the operation of the virtual power plant complies with legal and regulatory requirements.

[0127] S63, the automatic adjustment unit monitors the operation status of the power grid in real time through the intelligent control system. If there is an abnormality, the system automatically adjusts the power supply and demand balance and transmits it to the abnormality processing unit;

[0128] It is further explained that the virtual power plant aggregates a large number of distributed power sources and flexible and adjustable load resources through real-time data collection and IoT 5G transmission technology, participates in the power market and power grid operation, and allows the virtual power plant platform to scientifically regulate and control the control terminals installed in factory workshops, shopping malls, and charging stations without affecting the production of enterprises and the normal life of residents to achieve a balance between power generation and power consumption. For example: in sunny and windy weather, when there is excess photovoltaic and wind power generation, the virtual power plant increases power consumption by dispatching new energy vehicles and energy storage batteries for charging; a virtual power plant operation risk detection method is also adopted, including receiving registration requests, building multiple virtual power plants, sending configuration information, receiving detection data after configuration is completed, and performing detection analysis to obtain and send detection results, which helps to detect and analyze the operation risks of virtual power plants and ensure their stable operation; through the combination with smart grid technology, virtual power plants can also predict and respond to possible fluctuations in power demand to ensure the stability and reliability of the power system, which not only improves the efficiency and flexibility of the power system, but also alleviates the pressure on the traditional power system to a certain extent, and provides new ideas and methods for the future development of the power system.

[0129] S64, the abnormality handling unit maintains the communication lines and repairs the system, adjusts the operators, removes the regional restrictions, improves the market mechanism, rationalizes the concepts, and passes it to the operation recovery unit;

[0130] It is further explained that due to the damage of the external communication line, it is impossible to exchange trusted data with other entities in the virtual power plant, and it is impossible to know the status of the DER and perform communication line maintenance; re-authenticate the unauthorized DER to ensure the digitalization process on the user side, improve the implementation standards, and improve the trust of operators and other systematic repairs; when the virtual power plant cannot work, the distributed energy resources (DER) cannot receive the scheduling instructions such as the power generation plan for the next period, which causes the virtual power plant to fail to operate correctly, and eliminate the operator downtime; when the resource aggregation ability of the virtual power plant operator may be limited by geographical and administrative area constraints, resulting in limited profit margins and increased promotion and replication costs, the geographical and administrative area constraints are cancelled; the business model of the virtual power plant mainly relies on the ancillary service market, the demand response market and the electricity spot market, but at present, my country's electricity market trading mechanism is not yet fully mature, which restricts the development of virtual power plants, and therefore eliminates the immature market mechanism; the definition of the virtual power plant object is not clear, which can easily lead to repeated packaging of some projects, confusion of concepts, false negative control and other behaviors to defraud subsidies, approvals and valuations, and confusion of concepts and false negative control should be avoided.

[0131] S65, the operation recovery unit restores access to the electricity market and enables the virtual power plant to resume normal operation by integrating resources and improving demand response and emergency dispatch capabilities.

[0132] It is further explained that through the digital platform, the power resources distributed in different locations will be integrated, including but not limited to electric vehicle charging piles, energy storage systems, air conditioners, etc.; according to the market's power supply and demand situation, these resources will be uniformly allocated through the digital platform to meet the needs of the power grid and improve its demand response capabilities; in emergency situations, such as when the power grid pressure increases due to typhoons or high temperatures, the virtual power plant can enhance the emergency dispatch capability of the power grid and ensure the stable operation of the power grid to improve the emergency dispatch capability; as a special power plant, it will resume entering the power market and provide auxiliary services, such as demand response, power auxiliary services, etc., to generate social and economic benefits by optimizing operating concepts.

[0133] It is further explained that the various steps are displayed in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this document, there is no strict order restriction for the execution of these steps. These steps can also be executed according to other orders, and some steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed and completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0134] A virtual power plant anomaly detection system provided by the present invention also includes a computer device and a computer-readable storage medium; the computer device includes a memory and various functional modules, the memory stores a computer program, and the various functional modules implement the steps of any one of the above-mentioned virtual power plant anomaly detection methods when executing the computer program; the computer-readable storage medium stores a computer program, and the computer program implements the steps of any one of the above-mentioned virtual power plant anomaly detection methods when executed by the various functional modules.

[0135] It is further explained that the computer-readable storage medium includes a memory, which can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as the program and instructions corresponding to a virtual power plant anomaly detection method in an embodiment of the present invention, including information transmission instructions for each module; the memory executes various functional applications and data processing of each module by running the stored non-volatile software programs and instructions, that is, implements a virtual power plant anomaly detection method in the above method embodiment; one or more units are stored in the memory, and when executed by the one or more modules, a virtual power plant anomaly detection method in any of the above method embodiments is executed; the computer-readable storage medium stores computer executable instructions, which are executed by one or more modules, and can also be a virtual power plant anomaly detection method in any of the above method embodiments.

[0136] To further illustrate, the present invention is described according to the content implemented by a software program of a virtual power plant anomaly detection system. Each virtual power plant anomaly detection method is divided into several modules or units to implement the software program instructions generated by each step. The software program instructions include the virtual power plant anomaly detection method described above.

[0137] It is further explained that the contents described above in the present invention are written in accordance with the contents implemented by the software copyrights such as "Hanchi Virtual Power Plant Operation System (version number: V1.0, registration date: 2023.6.7.)", "Virtual Power Plant Operation Management System User Mobile Software (version number: V1.0, registration date: 2023.12.18.)", and "Virtual Power Plant Operation Management System (version number: V1.0, registration date: 2023.12.18.)" applied by our company.

[0138] The present invention also provides a virtual power plant anomaly detection control device, which is implemented by using the virtual power plant anomaly detection system and the virtual power plant anomaly detection method described above.

[0139] It is obvious to those skilled in the art that the present application is not limited to the details of the exemplary embodiments described above, and that the present application can be implemented in other specific forms without departing from the spirit or essential features of the present application. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present application is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present application.

[0140] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical solution of the present application can be modified or replaced by equivalents, and all should be included in the scope of protection of the present application.

Claims

1. A virtual power plant anomaly detection system, characterized in that : The detection system includes an information collection module, a numbering module, a data processing module, an identification and classification module, an operation processing module, a wireless communication module, an alarm, a memory, a processing center, and a smart phone; the information collection module, the numbering module, the data processing module, the identification and classification module, the operation processing module, the wireless communication module, the alarm, and the memory are respectively connected to the processing center; the smart phone is automatically connected to the wireless communication module within the range of a wireless network or the Internet; The wireless communication module is provided with a wireless network unit, which is responsible for sending and receiving wireless network signals and automatically networking with a smart phone within the range of a wireless network or the Internet; The alarm device compares the actual operating data with the normal operating range of the virtual power plant preset in the memory, and automatically sounds an audible alarm and notifies for processing if there is any inconsistency; The memory is responsible for storing information of the information collection module, the configuration number module, the data processing module, the identification classification module, the operation processing module, the wireless communication module, the alarm, and the normal operation range of the virtual power plant; The processing center is responsible for the information collection module, numbering module, data processing module, identification and classification module, operation processing module, wireless communication module, alarm, and storage information transmission. It is the hub center of the system and compares the actual operation data with the normal operation range of the virtual power plant preset in the storage: if they are consistent, the operation continues; if they are inconsistent, the alarm is transmitted to the alarm and notified for processing; The information collection module includes an information aggregation unit, a coordination optimization unit, and a data classification unit, which obtains the operating status data of the power generation equipment and power consumption equipment of the virtual power plant through intelligent sensors and transmits it to the numbering module; The configuration numbering module includes an information acquisition unit, a group numbering unit, and a power acquisition unit, which are responsible for grouping and numbering the acquired information and dividing the detection cycle into multiple task intervals according to the device execution information, obtaining the detection frequency of each interval, and passing it to the data processing module; The data processing module includes a data cleaning unit, a processing unit, and a feature extraction unit, which are responsible for performing data cleaning and feature extraction on the collected data to obtain identifiable operating data for subsequent analysis and transmission to the processing center; The identification and classification module includes a matching identification unit, an abnormality classification unit, and a cause analysis unit, which is responsible for matching the abnormality information with the industry database and performing abnormality identification and classification to determine the type and cause of the abnormality and pass it to the operation processing module; The operation processing module includes a risk classification unit, a processing plan unit, an automatic adjustment unit, and an exception processing unit, which are responsible for performing risk assessment according to the severity of the exception and taking corresponding processing measures to ensure the stable operation of the power system.

2. A virtual power plant anomaly detection method, applied to a virtual power plant anomaly detection system, characterized in that : The method described comprises the following steps: S10, during detection, the information collection module obtains the operating status data of the power generation equipment and power consumption equipment of the virtual power plant through the intelligent sensor, and transmits it to the numbering module; S20, the numbering module groups and numbers the obtained information and divides the detection cycle into multiple task intervals according to the device execution information, obtains the detection frequency of each interval, and transmits it to the data processing module; S30, the data processing module performs data cleaning and feature extraction on the collected data to obtain identifiable operation data for subsequent analysis and transmits it to the processing center; S40, the processing center compares the actual operation data with the normal operation range of the virtual power plant preset in the memory: if they are consistent, the operation continues; if they are inconsistent, the alarm is transmitted and notified for processing; S50, the identification and classification module matches the abnormal information with the industry database and performs abnormal identification and classification to determine the type and cause of the abnormality, and passes it to the operation processing module; S60: The operation processing module conducts risk assessment according to the severity of the abnormality and takes corresponding processing measures to ensure the stable operation of the power system.

3. A virtual power plant anomaly detection system according to claim 2, characterized in that: Described step S10, comprises the following steps: S11. The information aggregation unit collects real-time data of various energy resources such as the operating status, power generation, and load of distributed energy equipment through sensors and monitoring systems, and transmits it to the coordination and optimization unit; S12, the coordination and optimization unit compares the real-time data with the historical data and uses intelligent algorithms and models to predict and reasonably allocate the power generation and load of each distributed energy device, and transmits it to the data classification unit; S13. The data classification unit classifies the optimized data into power source type, load type, energy storage type, and hybrid type to reflect the different roles and functions of the virtual power plant in the power system.

4. A virtual power plant anomaly detection system according to claim 2, characterized in that: Described step S20, comprises the following steps: S21, the information acquisition unit monitors the operating status of the power plant's current information, time information, and power change information within a specific time period, and transmits the information to the grouping numbering unit; S22, the grouping and numbering unit obtains the current value of each input and output and groups the same current into a group and numbers it, sums the time value of each group, and transmits it to the power acquisition unit; S23, the power acquisition unit acquires each group of power according to the current value and the total time value to obtain the input and output information of each group of power for subsequent analysis and processing.

5. A virtual power plant anomaly detection system according to claim 2, characterized in that: The step S30 comprises the following steps: S31. The data cleaning unit purifies the collected real-time data of various energy resources through the industrial Internet of Things gateway and cloud computing technology for subsequent processing and transmits it to the processing unit; S32, the processing unit counts and checks the local power data, registers the identity information of the staff, counts the aggregated local data, and transmits it to the feature extraction unit; S33, the feature extraction unit realizes the aggregation and coordinated optimization of various geographically dispersed distributed energy resources (DER) through advanced communication technology and software architecture.

6. A virtual power plant anomaly detection system according to claim 2, characterized in that: The step S50 comprises the following steps: S51, the matching identification unit realizes the aggregation and coordinated optimization of energy resources of distributed generation, energy storage system, controllable load, and electric vehicle according to information communication technology and software system, and transmits it to the abnormal classification unit; S52, the abnormality classification unit matches and identifies the abnormalities into resource abnormalities, communication abnormalities, control abnormalities, market abnormalities, and security abnormalities, and transmits them to the cause analysis unit; S53. The cause analysis unit analyzes the causes of technical bottlenecks, imperfect market mechanisms, low participation, and lack of unified market access standards based on abnormal classification to ensure the normal operation of the virtual power plant.

7. A virtual power plant anomaly detection system according to claim 2, characterized in that: The step S60 comprises the following steps: S61. The risk classification unit classifies the risks of the virtual power plant into technical risks, market and economic risks, and data privacy and security risks, and transmits them to the processing plan unit; S62, the processing plan unit implements countermeasures for power grid security, data security, operation and maintenance security, environmental security, and regulatory and legal security according to risk classification, and transmits them to the automatic adjustment unit; S63, the automatic adjustment unit monitors the operation status of the power grid in real time through the intelligent control system. If there is an abnormality, the system automatically adjusts the balance of power supply and demand and transmits it to the abnormality processing unit; S64, the abnormality handling unit maintains the communication lines and repairs the system, adjusts the operator, cancels the regional restrictions, improves the market mechanism, and rationalizes the concepts, and passes it to the operation recovery unit; S65, the operation recovery unit restores access to the electricity market and enables the virtual power plant to resume normal operation by integrating resources and improving demand response and emergency dispatch capabilities.

8. The virtual power plant anomaly detection system according to claim 1 is characterized by: It also includes a computer device and a computer-readable storage medium; the computer device includes a memory and various functional modules, the memory stores a computer program, and when the various functional modules execute the computer program, the steps of a virtual power plant anomaly detection method as described in any one of claims 2 to 7 are implemented; the computer-readable storage medium stores a computer program, and when the computer program is executed by the various functional modules, the steps of a virtual power plant anomaly detection method as described in any one of claims 2 to 7 are implemented.

9. The virtual power plant anomaly detection system according to claim 1, characterized in that: It also includes a virtual power plant abnormality detection control device, which is implemented by a virtual power plant abnormality detection system as described in claims 1 and 8 above and a virtual power plant abnormality detection method as described in any one of claims 2-7 above.

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