Power distribution area equipment state sensing method and device considering new energy, and terminal

Abstract

The invention provides a power distribution area equipment state sensing method and device considering new energy, and a terminal, and relates to the technical field of power system equipment monitoring. The method comprises the following steps: acquiring real-time operation data of each non-new energy device in a power distribution area, and performing feature extraction according to the real-time operation data of the non-new energy devices to obtain basic operation state features of the non-new energy devices; according to the operation state characteristics of the new energy equipment connected with the non-new energy equipment, obtaining the operation state confidence of the non-new energy equipment; according to the basic operation state feature and the operation state confidence coefficient, obtaining an operation state feature of the non-new energy equipment; and performing equipment state sensing according to the operation state characteristics of the non-new energy equipment to obtain a state sensing result of each non-new energy equipment in the power distribution area. According to the invention, the non-new energy operation state of the equipment in the power distribution area can be sensed more accurately after the new energy equipment is accessed.

Description

Technical Field

[0001] This invention relates to the field of power system equipment monitoring technology, and in particular to a method, device and terminal for sensing the status of distribution substation equipment that takes into account new energy sources. Background Technology

[0002] Distribution transformer substations are a crucial link between substations and users in a power system, and their operational status directly affects power supply quality and reliability. With the development of smart grids, higher demands are placed on the condition monitoring and comprehensive perception of distribution transformer substation equipment.

[0003] Currently, monitoring of equipment in distribution substations mainly involves collecting various signals such as AC power, DC power, analog voltage, switching signals, and pulse signals, and using modern communication technologies to monitor widely distributed voltage detection points. However, with the increasing integration of renewable energy equipment into the distribution network, the randomness and uncertainty of renewable energy generation have also affected the operating status of non-renewable energy equipment within the distribution substation to varying degrees. Therefore, relying solely on real-time collected voltage and current data is insufficient to accurately assess the status of non-renewable energy equipment within the distribution substation after the integration of renewable energy equipment.

[0004] For example, Chinese patent CN119315701A, published on January 14, 2025, discloses a method and system for intelligent analysis of equipment monitoring in a distribution transformer substation. This method mainly collects and preprocesses real-time operating data of the equipment in the distribution transformer substation, uses a deep learning model to extract features from the real-time operating data to obtain operating status feature vectors, and then obtains equipment status evaluation results based on the operating status feature vectors. However, it does not consider the impact of the access of new energy equipment on the operating status of non-new energy equipment in the distribution transformer substation. Summary of the Invention

[0005] This invention provides a method, device, and terminal for sensing the status of distribution transformer area equipment that takes into account new energy sources, in order to solve the problem that it is difficult to accurately sense the status of non-new energy equipment in the distribution transformer area after new energy equipment is connected.

[0006] In a first aspect, embodiments of the present invention provide a method for sensing the status of distribution substation equipment considering new energy sources, including:

[0007] The real-time operating data of each non-new energy equipment in the distribution area is obtained, and feature extraction is performed based on the real-time operating data of the non-new energy equipment to obtain the basic operating status characteristics of the non-new energy equipment.

[0008] Based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment, the operating status confidence level of the non-new energy equipment is obtained;

[0009] Based on the basic operating state characteristics and the operating state confidence level, the operating state characteristics of the non-new energy equipment are obtained;

[0010] Based on the operating status characteristics of the non-new energy equipment, the equipment status is perceived to obtain the status perception results of each non-new energy equipment in the distribution area.

[0011] In one possible implementation, before obtaining the operating status confidence level of the non-new energy equipment based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment, the method further includes:

[0012] Acquire real-time operating data and environmental data of each new energy device within the distribution area;

[0013] Feature extraction is performed based on the real-time operating data and environmental data of the new energy equipment to obtain the operating status characteristics of the new energy equipment.

[0014] In one possible implementation, feature extraction is performed based on the real-time operating data and environmental data of the new energy equipment to obtain the operating status characteristics of the new energy equipment, including:

[0015] Calculate the fluctuation value of the operating data of the new energy equipment based on the real-time operating data of the new energy equipment;

[0016] Calculate the environmental data fluctuation value of the new energy equipment based on the environmental data of the new energy equipment;

[0017] Calculate the operational status coordination coefficient of the new energy equipment based on the fluctuation values ​​of the operational data and the fluctuation values ​​of the environmental data;

[0018] The operating status characteristics of the new energy equipment are obtained based on the fluctuation values ​​of the operating data, the fluctuation values ​​of the environmental data, and the operating status coordination coefficient.

[0019] In one possible implementation, the operational status coordination coefficient of the new energy equipment is calculated based on the operational data fluctuation value and the environmental data fluctuation value, including:

[0020] Calculate the similarity between the operational data fluctuation value and the environmental data fluctuation value;

[0021] Based on the similarity, the operational status coordination coefficient of the new energy equipment is obtained.

[0022] In one possible implementation, calculating the similarity between the operational data fluctuation value and the environmental data fluctuation value includes:

[0023] The fluctuation values ​​of the operating data are normalized to obtain normalized operating data fluctuation values;

[0024] The environmental data fluctuation values ​​are normalized to obtain normalized environmental data fluctuation values;

[0025] The similarity between the normalized operational data fluctuation value and the normalized environmental data fluctuation value is calculated and used as the similarity between the operational data fluctuation value and the environmental data fluctuation value.

[0026] In one possible implementation, the operational state coordination coefficient of the new energy equipment is obtained based on the similarity, including:

[0027] Calculate the similarity between the operational data fluctuation value and the load fluctuation value within the distribution area, and record it as the basic similarity.

[0028] Based on the basic similarity and the similarity, the operational state coordination coefficient of the new energy equipment is obtained.

[0029] In one possible implementation, the confidence level of the operating status of the non-new energy equipment is obtained based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment, including:

[0030] Based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment, the normal operating status coefficient of each new energy equipment is obtained;

[0031] Based on the normal operating status coefficient of each new energy device, the operating status confidence level of the non-new energy device is obtained.

[0032] In one possible implementation, the operating state characteristics of the non-new energy equipment are obtained based on the basic operating state characteristics and the operating state confidence level, including:

[0033] Determine whether the confidence level of the operating status is less than a preset threshold;

[0034] If the confidence level of the operating status is greater than or equal to the preset threshold, then the basic operating status feature is determined as the operating status feature of the non-new energy equipment;

[0035] If the confidence level of the operating status is less than the preset threshold, the operating status characteristics of the non-new energy equipment are obtained by multiplying the basic operating status characteristics and the confidence level of the operating status.

[0036] Secondly, embodiments of the present invention provide a distribution area equipment status sensing device considering new energy sources, comprising:

[0037] The first processing module is used to acquire real-time operating data of each non-new energy equipment in the distribution area, and to extract features based on the real-time operating data of the non-new energy equipment to obtain the basic operating status features of the non-new energy equipment.

[0038] The second processing module is used to obtain the operating status confidence level of the non-new energy equipment based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment.

[0039] The third processing module is used to obtain the operating status characteristics of the non-new energy equipment based on the basic operating status characteristics and the operating status confidence level.

[0040] The status perception module is used to perceive the status of the equipment based on the operating status characteristics of the non-new energy equipment, and obtain the status perception results of each non-new energy equipment in the distribution area.

[0041] Thirdly, embodiments of the present invention provide a terminal device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect or any possible implementation of the first aspect.

[0042] In this embodiment of the invention, real-time operating data of each non-new energy device within the distribution transformer area is acquired, and feature extraction is performed based on this data to obtain the basic operating status characteristics of the non-new energy devices. Then, based on the operating status characteristics of the new energy devices connected to the non-new energy devices, the operating status confidence level of the non-new energy devices is obtained. Based on the basic operating status characteristics and the operating status confidence level, the operating status features of the non-new energy devices are obtained. Furthermore, based on these operating status features, device status perception is performed to obtain the status perception results of each non-new energy device within the distribution transformer area. Therefore, after new energy devices are connected to the distribution transformer area, the impact of the new energy devices on the operating status of the connected non-new energy devices is considered and transformed into the operating status confidence level of the non-new energy devices. This allows for a more accurate acquisition of the operating status features of the non-new energy devices based on the operating status confidence level, and consequently, a more accurate determination of the status of each non-new energy device after the new energy devices are connected to the distribution transformer area. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating the implementation of the distribution area equipment status sensing method considering new energy sources provided in this embodiment of the invention.

[0044] Figure 2 This is a schematic diagram of the structure of the distribution area equipment status sensing device considering new energy sources provided in an embodiment of the present invention;

[0045] Figure 3This is a schematic diagram of a terminal device provided in an embodiment of the present invention. Detailed Implementation

[0046] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0047] See Figure 1 The document illustrates a flowchart of the implementation of the distribution area equipment status sensing method considering new energy sources provided in an embodiment of the present invention, which is described in detail below:

[0048] Step 101: Obtain real-time operating data of each non-new energy device in the distribution area, and extract features based on the real-time operating data of the non-new energy devices to obtain the basic operating status features of the non-new energy devices.

[0049] For example, non-new energy equipment within a distribution transformer area may include transformers, switchgear, capacitors, circuit breakers, etc. Real-time operating data for these non-new energy equipment may include data characterizing their operation, such as transformer voltage and current, and switchgear switching status. After acquiring the real-time operating data of each non-new energy device within the distribution transformer area, key indicators that can assess the device's operating status can be extracted from the real-time operating data for each device, serving as its basic operating status characteristics.

[0050] For example, based on the real-time operating data and historical operating data of non-new energy equipment, the current change rate, voltage change rate, and switching frequency of non-new energy equipment can be calculated as basic operating status characteristics of non-new energy equipment.

[0051] Step 102: Based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment, obtain the operating status confidence level of the non-new energy equipment.

[0052] Optionally, prior to step 102, the following may also be included:

[0053] Obtain real-time operating data and environmental data of each new energy device in the distribution area.

[0054] Feature extraction is performed based on real-time operating data and environmental data of new energy equipment to obtain the operating status characteristics of new energy equipment.

[0055] For example, new energy equipment connected within a distribution substation may include photovoltaic power generation equipment, wind power generation equipment, energy storage equipment, and charging piles. For photovoltaic power generation equipment, real-time operating data may include power generation, electricity generation, DC input current, AC output current, DC input voltage, AC output voltage, active power, reactive power, and inverter internal temperature, while environmental data may include ambient temperature, ambient humidity, and solar irradiance. For wind power generation equipment, real-time operating data may include the start-stop status data of each wind turbine, electricity generation data, and environmental data may include wind speed, wind direction, temperature, and vibration.

[0056] Optionally, feature extraction can be performed based on real-time operating data and environmental data of the new energy equipment to obtain the operating status characteristics of the new energy equipment, which may include:

[0057] Calculate the fluctuation value of the operating data of new energy equipment based on the real-time operating data of the new energy equipment.

[0058] Calculate the environmental data fluctuation value of new energy equipment based on the environmental data of the new energy equipment.

[0059] The operational status coordination coefficient of new energy equipment is calculated based on the fluctuation values ​​of operational data and environmental data.

[0060] Based on the fluctuation values ​​of operating data, environmental data, and the coordination coefficient of operating status, the operating status characteristics of new energy equipment are obtained.

[0061] In this embodiment, the fluctuation values ​​of the operating data of the new energy equipment, the fluctuation values ​​of the environmental data, and the operating status coordination coefficient are all used as the operating status characteristics of the new energy equipment. This makes it easier to perceive the operating status of the new energy equipment more accurately based on these characteristics, and thus to more accurately assess the impact of the new energy equipment connected in the distribution area on the operating status of non-new energy equipment.

[0062] For example, calculating the operational status coordination coefficient of new energy equipment based on operational data fluctuations and environmental data fluctuations may include:

[0063] Calculate the similarity between the fluctuation values ​​of operational data and the fluctuation values ​​of environmental data.

[0064] Based on the similarity, the operational status coordination coefficient of the new energy equipment is obtained.

[0065] In this embodiment, considering that the real-time operating data of the new energy equipment is affected by environmental data, the degree to which the operating status of the new energy equipment changes with the environment can be assessed based on the real-time operating data and environmental data (i.e., the operating status coordination coefficient of the new energy equipment). If the operating status coordination coefficient of the new energy equipment is large, it indicates that most of the changes in the real-time operating data of the new energy equipment are caused by environmental changes, and the probability that the new energy equipment is in normal operating condition is high. If the operating status coordination coefficient of the new energy equipment is small, it indicates that in addition to environmental changes, other factors have caused the changes in the real-time operating data of the new energy equipment. These other factors may be factors such as equipment failure, and the probability that the new energy equipment is in normal operating condition is low.

[0066] For example, the similarity between the fluctuation values ​​of operational data and environmental data can be obtained by calculating the Euclidean distance and Pearson correlation coefficient between them. This embodiment does not limit this.

[0067] Optionally, calculating the similarity between operational data fluctuations and environmental data fluctuations may include:

[0068] The fluctuation values ​​of the operating data are normalized to obtain normalized operating data fluctuation values.

[0069] The environmental data fluctuation values ​​are normalized to obtain normalized environmental data fluctuation values.

[0070] The similarity between the normalized operational data fluctuation value and the normalized environmental data fluctuation value is calculated and used as the similarity between the operational data fluctuation value and the environmental data fluctuation value.

[0071] In this embodiment, by normalizing the fluctuation values ​​of operational data and environmental data, the fluctuation values ​​of operational data and environmental data can be transformed into the same dimension, thereby more accurately measuring the similarity between the fluctuation values ​​of operational data and environmental data.

[0072] Optionally, based on the similarity, the operational state coordination coefficient of the new energy equipment can be obtained, including:

[0073] The similarity between the fluctuation value of the operating data and the load fluctuation value within the distribution area is calculated and denoted as the basic similarity.

[0074] Based on the basic similarity and similarity, the operational status coordination coefficient of new energy equipment is obtained.

[0075] In this embodiment, considering that the fluctuation value of the operating data of the equipment in the distribution area is also affected by the load fluctuation, the similarity between the operating data fluctuation value and the load fluctuation value in the distribution area is also calculated as the basic similarity. Through the basic similarity and the similarity, the operating status coordination coefficient of the new energy equipment can be obtained more accurately.

[0076] For example, the operational state coordination coefficient of new energy equipment can be obtained by weighted summation of basic similarity and similarity.

[0077] This allows us to obtain the operating status characteristics of new energy equipment connected within the distribution area, and to determine the operating status characteristics of new energy equipment connected to non-new energy equipment.

[0078] Optionally, based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment, the operating status confidence level of the non-new energy equipment can be obtained, which may include:

[0079] Based on the operating status characteristics of new energy equipment connected to non-new energy equipment, the normal operating status coefficient of each new energy equipment is obtained.

[0080] Based on the normal operating status coefficient of each new energy device, the operating status confidence level of non-new energy devices is obtained.

[0081] Specifically, the more new energy devices connected to non-new energy equipment that are in normal operating condition, the smaller the impact of new energy equipment on the operating condition of non-new energy equipment, and the higher the confidence level of the operating condition of non-new energy equipment. Conversely, the fewer new energy devices connected to non-new energy equipment that are in normal operating condition, the greater the impact of new energy equipment on the operating condition of non-new energy equipment, and the lower the confidence level of the operating condition of non-new energy equipment.

[0082] Therefore, we can first assess the probability that each new energy device is in a normal operating state (i.e., the normal operating state coefficient of each new energy device) based on the operating state characteristics of the new energy devices connected to non-new energy devices. Then, based on the normal operating state coefficient of each new energy device, we can obtain the confidence level of the operating state of the non-new energy devices.

[0083] For example, based on the operating status characteristics of new energy equipment connected to non-new energy equipment, the normal operating status coefficient of each new energy equipment can be obtained through methods such as pattern recognition and classification. After obtaining the normal operating status coefficient of each new energy equipment, the operating status confidence of the non-new energy equipment can be obtained through summation, weighted summation, or other methods.

[0084] Step 103: Based on the basic operating status characteristics and operating status confidence, obtain the operating status characteristics of non-new energy equipment.

[0085] Optionally, based on basic operating state characteristics and operating state confidence levels, the operating state characteristics of non-new energy equipment can be obtained, which may include:

[0086] Determine whether the confidence level of the running status is less than a preset threshold.

[0087] If the confidence level of the operating status is greater than or equal to the preset threshold, the basic operating status characteristics will be determined as the operating status characteristics of non-new energy equipment.

[0088] If the confidence level of the operating status is less than the preset threshold, the operating status characteristics of non-new energy equipment are obtained by multiplying the basic operating status characteristics and the operating status confidence level.

[0089] In this embodiment, the impact of the operating status characteristics of new energy devices connected to non-new energy devices on the operating status of non-new energy devices is considered. If most of the new energy devices connected to non-new energy devices are in a normal operating state, it indicates that the confidence level of identifying the operating status of non-new energy devices based on their basic operating status characteristics is higher. That is, when the confidence level of the operating status of non-new energy devices is greater than or equal to a preset threshold, their basic operating status characteristics can be determined as the operating status characteristics of non-new energy devices, so as to further identify the operating status of non-new energy devices based on their basic operating status characteristics. If a considerable portion of the new energy devices connected to non-new energy devices are in an abnormal operating state, it indicates that the reliability of identifying the operating status of non-new energy devices based solely on their basic operating status characteristics is poor. That is, when the confidence level of the operating status of non-new energy devices is less than a preset threshold, their basic operating status characteristics need to be further corrected. For example, the product of the basic operating status characteristics and the operating status confidence level can be calculated to more accurately determine the operating status characteristics of non-new energy devices, and then the operating status of non-new energy devices can be further identified based on the corrected basic operating status characteristics.

[0090] In obtaining the operating status characteristics of non-new energy equipment, this embodiment considers the basic operating status characteristics of the non-new energy equipment itself and the operating status characteristics of the new energy equipment connected to the non-new energy equipment, thereby obtaining the operating status characteristics of the non-new energy equipment more accurately, and thus more accurately assessing the operating status of each non-new energy equipment in the distribution area after the new energy equipment is connected.

[0091] Step 104: Based on the operating status characteristics of non-new energy equipment, perform equipment status perception to obtain the status perception results of each non-new energy equipment in the distribution area.

[0092] In this embodiment, after accurately obtaining the operating status characteristics of each non-new energy device, the device status can be perceived through methods such as pattern recognition and classification, and the status perception results of each non-new energy device in the distribution area can be obtained.

[0093] For example, based on the above steps, after obtaining the operating status characteristics of each new energy device in the distribution transformer area, this embodiment can also obtain the status perception results of each new energy device in the distribution transformer area through methods such as pattern recognition and classification.

[0094] In this embodiment of the invention, real-time operating data of each non-new energy device within the distribution transformer area is acquired, and feature extraction is performed based on this data to obtain the basic operating status characteristics of the non-new energy devices. Then, based on the operating status characteristics of the new energy devices connected to the non-new energy devices, the operating status confidence level of the non-new energy devices is obtained. Based on the basic operating status characteristics and the operating status confidence level, the operating status features of the non-new energy devices are obtained. Furthermore, based on these operating status features, device status perception is performed to obtain the status perception results of each non-new energy device within the distribution transformer area. Therefore, after new energy devices are connected to the distribution transformer area, the impact of the new energy devices on the operating status of the connected non-new energy devices is considered and transformed into the operating status confidence level of the non-new energy devices. This allows for a more accurate acquisition of the operating status features of the non-new energy devices based on the operating status confidence level, and consequently, a more accurate determination of the status of each non-new energy device after the new energy devices are connected to the distribution transformer area.

[0095] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0096] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0097] Figure 2 A schematic diagram of the state sensing device for distribution substation equipment considering new energy sources, provided in an embodiment of the present invention, is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below:

[0098] like Figure 2 As shown, the status sensing device for distribution area equipment considering new energy sources includes: a first processing module 21, a second processing module 22, a third processing module 23, and a status sensing module 24.

[0099] The first processing module 21 is used to acquire real-time operating data of each non-new energy equipment in the distribution area, and to extract features based on the real-time operating data of the non-new energy equipment to obtain the basic operating status features of the non-new energy equipment.

[0100] The second processing module 22 is used to obtain the operating status confidence level of the non-new energy equipment based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment.

[0101] The third processing module 23 is used to obtain the operating status characteristics of the non-new energy equipment based on the basic operating status characteristics and the operating status confidence level.

[0102] The status perception module 24 is used to perceive the status of the equipment based on the operating status characteristics of the non-new energy equipment, and obtain the status perception results of each non-new energy equipment in the distribution area.

[0103] In one possible implementation, the first processing module 21 can also be used to acquire real-time operating data and environmental data of each new energy device in the distribution area; and to extract features based on the real-time operating data and environmental data of the new energy devices to obtain the operating status features of the new energy devices.

[0104] In one possible implementation, the first processing module 21 can be used to calculate the operating data fluctuation value of the new energy equipment based on the real-time operating data of the new energy equipment; calculate the environmental data fluctuation value of the new energy equipment based on the environmental data of the new energy equipment; calculate the operating state coordination coefficient of the new energy equipment based on the operating data fluctuation value and the environmental data fluctuation value; and obtain the operating state characteristics of the new energy equipment based on the operating data fluctuation value, the environmental data fluctuation value, and the operating state coordination coefficient.

[0105] In one possible implementation, the first processing module 21 can be used to calculate the similarity between the fluctuation value of the operating data and the fluctuation value of the environmental data; and obtain the operating state coordination coefficient of the new energy equipment based on the similarity.

[0106] In one possible implementation, the first processing module 21 can be used to normalize the operational data fluctuation value to obtain a normalized operational data fluctuation value; normalize the environmental data fluctuation value to obtain a normalized environmental data fluctuation value; and calculate the similarity between the normalized operational data fluctuation value and the normalized environmental data fluctuation value as the similarity between the operational data fluctuation value and the environmental data fluctuation value.

[0107] In one possible implementation, the first processing module 21 can be used to calculate the similarity between the operating data fluctuation value and the load fluctuation value within the distribution area, denoted as the basic similarity; and to obtain the operating state coordination coefficient of the new energy equipment based on the basic similarity and the similarity.

[0108] In one possible implementation, the second processing module 22 can be used to obtain the normal operating status coefficient of each new energy device based on the operating status characteristics of the new energy devices connected to the non-new energy devices; and to obtain the operating status confidence of the non-new energy devices based on the normal operating status coefficient of each new energy device.

[0109] In one possible implementation, the third processing module 23 can be used to determine whether the confidence level of the operating state is less than a preset threshold; if the confidence level of the operating state is greater than or equal to the preset threshold, then the basic operating state feature is determined as the operating state feature of the non-new energy equipment; if the confidence level of the operating state is less than the preset threshold, then the operating state feature of the non-new energy equipment is obtained by multiplying the basic operating state feature and the confidence level of the operating state.

[0110] Figure 3 This is a schematic diagram of a terminal device provided in an embodiment of the present invention. Figure 3 As shown, the terminal device 3 in this embodiment includes a processor 30 and a memory 31. The memory 31 stores a computer program 32. When the processor 30 executes the computer program 32, it implements the steps in the various method embodiments described above. Alternatively, when the processor 30 executes the computer program 32, it implements the functions of each module / unit in the various device embodiments described above.

[0111] For example, computer program 32 can be divided into one or more modules / units, which are stored in memory 31 and executed by processor 30 to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 32 in terminal device 3.

[0112] Terminal device 3 may include, but is not limited to, processor 30 and memory 31. Those skilled in the art will understand that... Figure 3 This is merely an example of terminal device 3 and does not constitute a limitation on terminal device 3. It may include more or fewer components than shown, or combine certain components, or different components. For example, terminal device 3 may also include input / output devices, network access devices, buses, etc.

[0113] For the sake of simplicity and clarity, only the above-described functional modules / units are used as examples. In practical applications, the functions described above can be assigned to different functional modules / units as needed. These modules / units can be implemented in hardware, software, or a combination of both.

[0114] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not detailed or described in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Unless otherwise specified or in conflict with logic, the terminology and / or descriptions between different embodiments are consistent and can be referenced interchangeably. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0115] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for sensing the status of distribution transformer area equipment considering new energy sources, characterized in that, include: The real-time operating data of each non-new energy equipment in the distribution area is obtained, and feature extraction is performed based on the real-time operating data of the non-new energy equipment to obtain the basic operating status characteristics of the non-new energy equipment. Based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment, the operating status confidence level of the non-new energy equipment is obtained; Based on the basic operating state characteristics and the operating state confidence level, the operating state characteristics of the non-new energy equipment are obtained; Based on the operating status characteristics of the non-new energy equipment, the equipment status is perceived to obtain the status perception results of each non-new energy equipment in the distribution area.

2. The method for sensing the status of distribution transformer area equipment considering new energy sources according to claim 1, characterized in that, Before obtaining the confidence level of the operating status of the non-new energy equipment based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment, the process further includes: Acquire real-time operating data and environmental data of each new energy device within the distribution area; Feature extraction is performed based on the real-time operating data and environmental data of the new energy equipment to obtain the operating status characteristics of the new energy equipment.

3. The method for sensing the status of distribution transformer area equipment considering new energy sources according to claim 2, characterized in that, Based on the real-time operating data and environmental data of the new energy equipment, feature extraction is performed to obtain the operating status characteristics of the new energy equipment, including: Calculate the fluctuation value of the operating data of the new energy equipment based on the real-time operating data of the new energy equipment; Calculate the environmental data fluctuation value of the new energy equipment based on the environmental data of the new energy equipment; Calculate the operational status coordination coefficient of the new energy equipment based on the fluctuation values ​​of the operational data and the fluctuation values ​​of the environmental data; The operating status characteristics of the new energy equipment are obtained based on the fluctuation values ​​of the operating data, the fluctuation values ​​of the environmental data, and the operating status coordination coefficient.

4. The method for sensing the status of distribution transformer area equipment considering new energy sources according to claim 3, characterized in that, Based on the fluctuation values ​​of the operational data and the fluctuation values ​​of the environmental data, the operational status coordination coefficient of the new energy equipment is calculated, including: Calculate the similarity between the operational data fluctuation value and the environmental data fluctuation value; Based on the similarity, the operational status coordination coefficient of the new energy equipment is obtained.

5. The method for sensing the status of distribution substation equipment considering new energy sources according to claim 4, characterized in that, Calculating the similarity between the operational data fluctuation value and the environmental data fluctuation value includes: The fluctuation values ​​of the operating data are normalized to obtain normalized operating data fluctuation values; The environmental data fluctuation values ​​are normalized to obtain normalized environmental data fluctuation values; The similarity between the normalized operational data fluctuation value and the normalized environmental data fluctuation value is calculated and used as the similarity between the operational data fluctuation value and the environmental data fluctuation value.

6. The method for sensing the status of distribution transformer area equipment considering new energy sources according to claim 4, characterized in that, Based on the similarity, the operational state coordination coefficient of the new energy equipment is obtained, including: Calculate the similarity between the operational data fluctuation value and the load fluctuation value within the distribution area, and record it as the basic similarity. Based on the basic similarity and the similarity, the operational state coordination coefficient of the new energy equipment is obtained.

7. The method for sensing the status of distribution transformer area equipment considering new energy sources according to claim 1, characterized in that, Based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment, the operating status confidence level of the non-new energy equipment is obtained, including: Based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment, the normal operating status coefficient of each new energy equipment is obtained; Based on the normal operating status coefficient of each new energy device, the operating status confidence level of the non-new energy device is obtained.

8. The method for sensing the status of distribution transformer area equipment considering new energy sources according to claim 1, characterized in that, Based on the basic operating state characteristics and the operating state confidence level, the operating state characteristics of the non-new energy equipment are obtained, including: Determine whether the confidence level of the operating status is less than a preset threshold; If the confidence level of the operating status is greater than or equal to the preset threshold, then the basic operating status feature is determined as the operating status feature of the non-new energy equipment; If the confidence level of the operating status is less than the preset threshold, the operating status characteristics of the non-new energy equipment are obtained by multiplying the basic operating status characteristics and the confidence level of the operating status.

9. A status sensing device for distribution substation equipment considering new energy sources, characterized in that, include: The first processing module is used to acquire real-time operating data of each non-new energy equipment in the distribution area, and to extract features based on the real-time operating data of the non-new energy equipment to obtain the basic operating status features of the non-new energy equipment. The second processing module is used to obtain the operating status confidence level of the non-new energy equipment based on the operating status characteristics of the new energy equipment connected to the non-new energy equipment. The third processing module is used to obtain the operating status characteristics of the non-new energy equipment based on the basic operating status characteristics and the operating status confidence level. The status perception module is used to perceive the status of the equipment based on the operating status characteristics of the non-new energy equipment, and obtain the status perception results of each non-new energy equipment in the distribution area.

10. A terminal device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method as described in any one of claims 1 to 8.

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