A Configuration Change Verification Method and System Based on Virtual Connections of IED Devices

Abstract

The present invention relates to the technical field of intelligent substations. The present invention relates to a configuration change verification method and system based on virtual connections of IED devices. The method includes: collecting configuration data of the virtual connections of IED devices at historical moments, where the configuration data at historical moments includes configuration data transmitted multiple times during a historical time period; classifying the configuration data according to the average error rate and average error data length of each data item in the configuration data; for each type of data item, calculating the segment weight of each data item in this type of data item; segmenting the data to be verified according to the segment weight of each data item, and verifying each segment of data separately; for a certain item of data, the greater its segment weight, the shorter the corresponding data segment after segmentation. Using the method of the present invention to verify the configuration of the virtual connection of IED devices can improve the verification efficiency on the basis of ensuring the verification accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent substations. More specifically, the present invention relates to a method and system for verifying configuration changes based on virtual connections of IED devices. Background Art

[0002] As Figure 1 shown, in order to transmit the electric energy generated by a power plant over a long distance for users to use, it is usually necessary to set up a substation in the power system to convert the voltage, transmit the electric energy over a long distance through the power grid, and convert the voltage of the electric energy again after it is transmitted to the user side for the user to use. In today's era, in order to make the substation operate more stably, reliably and efficiently and save the labor cost of the substation, traditional substations are gradually being replaced by intelligent substations, and various IED devices are usually set in intelligent substations. In order to ensure the normal operation of each IED device, it is necessary to verify the configuration change of the virtual connection of the IED (intelligent electronic device) device.

[0003] In the current power industry and the construction of intelligent power grids, the method for verifying the configuration change of the virtual connection of IED (intelligent electronic device) devices is undergoing continuous evolution and improvement to meet the increasingly complex system requirements and technological developments. During the process of network transmission and data exchange, data errors often occur. In order to ensure the accuracy of the data transmission process, it is necessary to verify the data before and after transmission. Usually, the CRC check method is used to verify the data.

[0004] Due to the excessive amount of data to be verified, the data is usually segmented first. In the prior art, when verifying the configuration of the virtual terminals of IED devices through CRC check codes, the data to be verified is first obtained, then the data to be verified is evenly divided into multiple segments, and finally CRC checks are performed on each segment of data respectively.

[0005] However, during the process of data segmentation, since the data to be verified is evenly divided into multiple segments, there will be situations where the length of the data segment is too large or too small. If the length of the data segment is too large, it will lead to too much data to be checked after a data error, increasing the error cost, while if the length of the data segment is too small, there will be too many data verifications, resulting in low data verification efficiency. Summary of the Invention

[0006] To solve the technical problems in the prior art that when verifying the virtual connection configuration information of devices, there is too much data to be checked after a data error and the data verification efficiency is low, the present invention provides solutions in the following aspects.

[0007] In a first aspect, the present invention provides a method for verifying configuration changes based on virtual connections of IED devices, including:

[0008] Collect the configuration data at the historical moments of the virtual connections of the IED devices, where the configuration data at the historical moments includes the configuration data transmitted multiple times in a historical time period; and classify the configuration data according to the average error rate and the average error data length of each data item in the configuration data;

[0009] For each type of data item, calculate the segment weight of each data item in this type of data item, and the calculation expression is: ;

[0010] In the formula, represents the segment weight of the th data item in the th type of data item, represents the preset segment length, represents the average value of the error possibility of all items of data in the th type of data item, represents the average value of the error possibility of all items of data in all types of data, represents the th data item in the th type of data item,

[0011] Segment the data to be verified according to the segment weight of each data item, and verify each segment of data separately; for a certain data item, the greater its segment weight, the shorter the corresponding data segment after segmentation.

[0012] The beneficial effects of the present invention are as follows: The configuration change verification method based on the virtual connection of IED devices in the present invention, when verifying the configuration of the virtual connection of IED devices, first classifies the configuration data according to the average error rate and the average error data length, and groups those with similar average error rates and average error data lengths into one category; when calculating the segment weight of each data item, it comprehensively considers the error possibility of the data item category to which the data item belongs among all data item categories, and also considers the error possibility of the data item in the data item category to which the data item belongs; making the calculated segment weight proportional to both the error possibility of the data item category to which the data item belongs and the error possibility of the data item, thereby ensuring that the calculated segment weight is more accurate and objective; for data items with a greater segment weight, the greater the possibility of error, and the shorter the corresponding segment length, so as to achieve a higher frequency of verification for data items with a greater possibility of error and a lower frequency of verification for data items with a smaller possibility of error, thereby improving the verification efficiency on the basis of ensuring the verification accuracy.

[0013] Preferably, segmenting the data to be verified according to the segment weight of each data item includes:

[0014] Starting from the first data in the data to be verified, obtain the data items where each data is located, and use the segment weights of the data items where each data is located as the segment weights of the corresponding data;

[0015] Take the first data in the data to be verified as the starting data, and starting from the starting data, successively accumulate the segment weights of the subsequent data;

[0016] In response to the accumulated value being greater than or equal to 1, stop accumulating and divide the data between the data and the last accumulated data into a data segment; take the last accumulated data as the new starting data and re-accumulate to obtain the next data segment.

[0017] The effect is that: by using the data segmentation method of the present invention, the data to be verified can be quickly segmented according to the segment weights corresponding to each data, and the sum of the segment weights of each data in each segment is close to 1. After segmentation, for the data items with large segment weights, the corresponding data segments are shorter, and for the data items with small segment weights, the corresponding data segments are longer.

[0018] For the j-th data item, the calculation expression for its error probability is:

[0019] ;

[0020] In the formula, represents the error probability of the -th data item, represents the total number of data transmissions corresponding to the configuration data at the historical moment, represents the number of times the -th data item in the configuration data of the -th transmission is in error, represents the length of the -th data error of the -th data item in the configuration data of the -th transmission, represents the total length of the -th data item in the configuration data of the -th transmission.

[0021] The effect is that: when calculating the error probability of a certain data item using the calculation expression of the present invention, it measures the error probability of the data item based on the ratio of the sum of the data segment lengths corresponding to each data error in the same data transmission to the total data segment length of the data item. In addition, when measuring the error probability of the data item based on this ratio, the magnitudes of this ratio corresponding to multiple transmissions are comprehensively considered, so that the error probability of the data item can be calculated more accurately.

[0022] For the j-th item of data, the calculation expression for its error probability is as follows:

[0023] ;

[0024] In the formula, represents the error probability of the -th item of data, represents the total number of data transmissions corresponding to the configuration data at the historical moment, represents the number of errors of the -th item of data in the configuration data of the -th transmission, represents the length of the -th error data of the -th item of data in the configuration data of the -th transmission, represents the total length of the -th item of data in the configuration data of the -th transmission.

[0025] Its effect is that when calculating the error probability of a certain data item using the calculation expression of the present invention, not only the ratio of the length of the error data segment corresponding to each data transmission to the total data segment length of the data item is considered, but also the change of the virtual connection configuration data in different data transmissions is considered. A higher influence weight is given to the ratio corresponding to the data with a later transmission order, and a lower influence weight is given to the ratio corresponding to the data with an earlier transmission order, so that the calculation result of the error probability of the data item is more accurate.

[0026] For the j-th item of data, the calculation expression for its average error rate is as follows:

[0027] ;

[0028] In the formula, represents the average error rate of the j-th item of data, represents the total number of data transmissions corresponding to the configuration data at the historical moment, represents the number of errors of the -th item of data in the configuration data of the -th transmission, represents the length of the -th error data of the -th item of data in the configuration data of the -th transmission, represents the total length of the -th item of data in the configuration data of the -th transmission.

[0029] The effect is as follows: when calculating the error rate of a certain data item, the error rate of this data item in the data transmission process is measured based on the ratio of the sum of the data segment lengths corresponding to each data error in the same data transmission to the total data segment length of this data item, and the average value of the error rates of this data item in each data transmission process is used as the average error rate of this data item, so as to calculate the average error rate of this data item more accurately.

[0030] For the j-th data item, the method for obtaining its average error data length includes:

[0031] Calculate the data lengths of the j-th data item that are in error in the configuration data of each transmission respectively, and take the average value of them to obtain its average error data length; for the configuration data of a certain transmission, the data length of the j-th data item that is in error is equal to the sum of the lengths corresponding to each error of this item of data.

[0032] Classifying the configuration data according to the average error rate and average error data length of each data item in the configuration data includes: forming a feature vector with the average error data length and average error rate of each data item, and performing KMeans clustering on all data items according to the feature vectors of each data item.

[0033] The configuration data at the historical moment includes: device identification name, device type configuration, device IP address, subnet mask and gateway, virtual connection ID, source and destination nodes of data transmission, data object model, data type definition, and sampling frequency.

[0034] The preset segmented length takes a value of 100.

[0035] In the second aspect, the present invention provides a configuration change verification system based on the virtual connection of IED devices, including a memory and a processor. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the configuration change verification method based on the virtual connection of IED devices of the present invention is implemented.

[0036] In summary, the beneficial effect of the present invention is that: adopting the configuration change verification method based on the virtual connection of IED devices of the present invention can greatly improve the verification efficiency on the basis of ensuring the verification accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] By referring to the accompanying drawings and reading the following detailed description, the above and other objects, features, and advantages of the exemplary embodiments of the present invention will become easy to understand. In the drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, where:

[0038] Figure 1It is a schematic diagram showing the structure of a power system in the prior art;

[0039] Figure 2 It is a flowchart showing a configuration change verification method based on virtual connections of IED devices according to an embodiment of the present invention;

[0040] Figure 3 It is a schematic diagram showing the data sequence of a certain data item according to an embodiment of the present invention;

[0041] Figure 4 It is a schematic diagram showing the structure of a configuration change verification system based on virtual connections of IED devices according to an embodiment of the present invention. Detailed implementation manners

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0043] Next, the detailed implementation manners of the present invention will be described in conjunction with the accompanying drawings.

[0044] Embodiment of the configuration change verification method based on virtual connections of IED devices:

[0045] As Figure 2 shown, the configuration change verification method based on virtual connections of IED devices of the present invention includes:

[0046] S101. Collect configuration data at a historical moment and classify it. Specifically, collect the configuration data at the historical moment of the virtual connection of the IED device, where the configuration data at the historical moment includes the configuration data transmitted multiple times in a historical time period; and classify the configuration data according to the average error rate and average error data length of each data item in the configuration data.

[0047] In this embodiment, the configuration data at the historical moment of the virtual connection of the IED device includes: device identification name, device type configuration, device IP address, subnet mask and gateway, virtual connection ID, source and target nodes of data transmission, data object model, data type definition, and sampling frequency. In other embodiments, the historical configuration data may also include other types of data items.

[0048] After classifying the configuration data, data items with average error rates and average error data lengths that are close to each other are grouped into the same category. There are various classification methods. For example, numerical intervals corresponding to the average error rate and the average error data length can be set for each category respectively. For a certain item of data, if its average error rate and average error data length fall within the numerical intervals corresponding to the average error rate and the average error data length of a certain category respectively, then this item of data is classified into the corresponding category. Another example: A feature vector can be constructed based on the average error rate and average error data length of each data item, and a clustering algorithm can be used to classify the configuration data.

[0049] S102. Calculate the segment weight of each data item. Specifically: For each type of data item, calculate the segment weight of each data item in this type of data item. The calculation formula is: ;

[0050] In the formula, represents the segment weight of the th data item in the th type of data item, represents the preset segment length, represents the average value of the error probabilities of all data items in the th type of data item, represents the average value of the error probabilities of all data items in all types of data, represents the error probability of the th data item in the th type of data item. The part in the formula can represent the ratio of the average value of the error probabilities of all data items in the th type of data item to the average value of the error probabilities of all data items in all types of data. The larger this ratio is, the greater the error probability of this type of data. Therefore, shorter data segments should be used to verify this type of data, so as to increase the verification frequency of this type of data; By adding 1 to both the numerator and the denominator, the situation of it being 0 is avoided; The part in the formula weakens the gap between the error probability of each data item and the average error probability of its class through cubic calculation, and adds 1 to both the numerator and the denominator to avoid the situation of being 0.

[0051] When calculating the segment weight of a certain data item in a certain type of data items using this expression, the greater the average error probability of all data items in the data item category to which this data item belongs, the greater the calculated segment weight; in this data item category, the greater the error probability of this data item, the greater the calculated segment weight; when calculating the segment weight of this data item, not only the error probability of this type of data item among all data item categories is considered, but also the error probability of this data item in this type of data items is considered; making the calculated segment weight be directly proportional to both the error probability of the data item category to which this data item belongs and the error probability of this data item, thus ensuring that the calculated segment weight is more accurate and objective.

[0052] In this embodiment, the preset segment length is 100. In other embodiments, the preset segment length can also take other appropriate lengths.

[0053] S103. Segment and verify the data to be verified, specifically: segment the data to be verified according to the segment weight of each data item, and verify each segment of data separately; for a certain data item, the greater its segment weight, the shorter the data segment corresponding to this data item after segmentation.

[0054] Since the total length of each data item is constant, the shorter the data segment corresponding to this data item after segmentation, the more data segments corresponding to this data item there will be, and this data item will be verified at a higher frequency. By making the greater the segment weight, the shorter the data segment corresponding to this data item after segmentation, it is possible to perform a higher frequency of verification on data items with a high error probability and a lower frequency of verification on data items with a low error probability, thus greatly improving the verification efficiency on the basis of ensuring verification accuracy.

[0055] The configuration change verification method based on the virtual connection of IED devices of the present invention, when verifying the configuration of the virtual connection of IED devices, first classifies the configuration data according to the average error rate and the average error data length, and groups those with similar average error rates and average error data lengths into one category; when calculating the segment weight of each data item, it comprehensively considers the error probability of the data item category to which this data item belongs among all data item categories, and also considers the error probability of this data item in the data item category to which this data item belongs; making the calculated segment weight be directly proportional to both the error probability of the data item category to which this data item belongs and the error probability of this data item, thus ensuring that the calculated segment weight is more accurate and objective; for data items with a greater segment weight, the greater the error probability, and the shorter the corresponding segment length, thus realizing a higher frequency of verification for data items with a greater error probability and a lower frequency of verification for data items with a smaller error probability, thereby improving the verification efficiency on the basis of ensuring verification accuracy.

[0056] In one embodiment, segmenting the data to be verified according to the segment weights of each data item includes:

[0057] S201. Starting from the first data in the data to be verified, obtain the data items where each data is located, and use the segment weights of the data items where each data is located as the segment weights of the corresponding data;

[0058] S202. Use the first data in the data to be verified as the starting data, and sequentially accumulate the segment weights of the subsequent data starting from the starting data;

[0059] S203. In response to the accumulated value being greater than or equal to 1, stop accumulating and divide the data between the data and the last accumulated data into a data segment; use the last accumulated data as the new starting data and re-accumulate to obtain the next data segment.

[0060] In the last accumulation, if the accumulated value after accumulating the segment weights of the last few data in the data to be verified is less than 1, directly divide these data into a data segment.

[0061] Using the data segmenting method of this embodiment can quickly segment the data to be verified according to the corresponding segment weights of each data, and make the sum of the segment weights of each data in each data segment close to 1. After segmentation, for the data items with large segment weights, the corresponding data segments are shorter, and for the data items with small segment weights, the corresponding data segments are longer.

[0062] In one embodiment, for the j-th data item, the calculation expression of its error possibility is:

[0063] ;

[0064] In the formula, represents the error possibility of the -th data item, represents the total number of data transmissions corresponding to the configuration data at the historical moment, represents the number of times the -th data item in the configuration data of the -th transmission is in error, represents the data length of the -th error of the -th data item in the configuration data of the -th transmission, represents the total length of the -th data item in the configuration data of the -th transmission.

[0065] represents the The ratio of the total length of the error data segments in the nd item of the configuration data for a transmission to the total length of this item of data is used to measure the error rate of this item of data during this collection process. It should be noted that for the th transmission, if several consecutive data in the th item of the configuration data are all in error, then these several data are regarded as one data error. As Figure 3 shown, if a data sequence corresponding to a certain data item has seven data points, namely data point A, data point B, data point C, data point D, data point E, data point F, and data point G, and the data of data point A, data point C, data point D, and data point F are all in error, then it is considered that this data item has three errors.

[0066] When calculating the error possibility of a certain data item using the calculation expression of this embodiment, it is measured by the ratio of the sum of the data segment lengths corresponding to each data error in the same data transmission to the total data segment length of this data item. In addition, when measuring the error possibility of this data item based on this ratio, the magnitudes of this ratio corresponding to multiple transmissions are comprehensively considered, so that the error possibility of this data item can be calculated more accurately.

[0067] In one embodiment, for the jth item of data, the calculation expression for its error possibility is:

[0068] ;

[0069] In the formula, represents the error possibility of the th item of data, represents the total number of data transmissions corresponding to the configuration data at the historical moment, represents the number of errors of the th item of data in the configuration data for the th transmission, represents the data length of the th data error of the th item of data in the configuration data for the th transmission, represents the total length of the th item of data in the configuration data for the th transmission.

[0070] In the formula, represents the time sequence distance weight. Since the configuration data of the virtual connection changes during the data collection process, the closer the collected data is, the higher its reference significance, and a higher influence weight is given to the later collected data.

[0071] When calculating the error probability of a certain data item using the calculation expression of this embodiment, not only the ratio of the length of the error data segment corresponding to each data transmission to the total data segment length of the data item is considered, but also the change of the configuration data of the virtual connection during different data transmissions is considered. A higher influence weight is given to the ratio corresponding to the data with a later transmission order, and a lower influence weight is given to the ratio corresponding to the data with an earlier transmission order, so that the calculation result of the error probability of the data item is more accurate.

[0072] In one embodiment, for the j-th item of data, the calculation expression of its average error rate is:

[0073] ;

[0074] In the formula, represents the average error rate of the j-th item of data, represents the total number of data transmissions corresponding to the configuration data at the historical moment, represents the th time the th item of data in the configuration data of the th transmission is in error, represents the th item of data in the configuration data of the th transmission, and the data length of the th data error of the th item of data in the configuration data of the th transmission,

[0075] In this embodiment, when calculating the error rate of a certain data item, it is measured by the ratio of the sum of the data segment lengths corresponding to each data error in the same data transmission to the total data segment length of the data item, and the average value of the error rates of the data item in each data transmission process is used as the average error rate of the data item, so as to calculate the average error rate of the data item more accurately.

[0076] In one embodiment, for the j-th item of data, the method for obtaining its average error data length includes: calculating the data lengths of the j-th item of data in error in the configuration data of each transmission respectively, and taking the average value thereof to obtain its average error data length; for the configuration data of a certain transmission, the data length of the j-th item of data in error is equal to the sum of the lengths of the data corresponding to each error of this item of data.

[0077] In one embodiment, classifying the configuration data according to the average error rate and the average error data length of each data item in the configuration data includes: forming a feature vector from the average error data length and the average error rate of each data item, and performing KMeans clustering on all data items according to the feature vectors of each data item.

[0078] Embodiment of the configuration change verification system based on the virtual connection of IED devices:

[0079] The present invention also provides a configuration change verification system based on the virtual connection of IED devices. As Figure 4 shown, the configuration change verification system based on the virtual connection of IED devices includes a processor and a memory, and the memory stores computer program instructions, which implement the configuration change verification method based on the virtual connection of IED devices in the above embodiments when the computer program instructions are executed by the processor.

[0080] The configuration change verification system based on the virtual connection of IED devices further includes a communication bus, a communication interface and other components well known to those skilled in the art, and their settings and functions are known in the art, so they will not be described in detail here.

[0081] In the present invention, the foregoing memory may be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device. For example, the computer-readable storage medium may be any suitable magnetic storage medium or magneto-optical storage medium, such as resistive random access memory (RRAM), dynamic random access memory (DRAM), static random access memory, enhanced dynamic random access memory (EDRAM), high-bandwidth memory (HBM), hybrid memory cube (HMC), etc., or any other medium that can be used to store the required information and can be accessed by an application program, module, or both. Any such computer storage medium may be part of the device or accessible or connectable to the device. Any application or module described in the present invention can be implemented using computer-readable / executable instructions that can be stored or otherwise held by such a computer-readable medium.

[0082] In the description of this specification, the meanings of "a plurality" and "several" are at least two, such as two, three or more, unless otherwise specifically defined.

[0083] While this specification has shown and described several embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many variations, modifications, and alternative forms will occur to those skilled in the art without departing from the spirit and scope of the present invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention.

Claims

1. A configuration change verification method based on virtual connection of IED equipment, characterized in that: include: Collect the configuration data of the virtual connection of the IED device at the historical moment, and the configuration data at the historical moment includes the configuration data transmitted multiple times in the historical time period; and classifying the configuration data according to the average error rate and average error data length of each data item in the configuration data; For each type of data item, calculate the segment weight of each data item in this type of data item, and the calculation expression is: ; In the formula, Indicates Class data item The segment weights of the data items, Indicates the preset segment length, Indicates The average error probability of all items in the class data item, Represents the average error probability of all item data in all class data, Indicates Class data item The error probability of each data item; Segmenting the data to be verified according to the segment weight of each data item includes: starting from the first data of the data to be verified, obtaining the data items where each data is located, and using the segment weight of the data item where each data is located as the segment weight of the corresponding data; Take the first data in the data to be verified as the starting data, and accumulate the weights of subsequent data segments in sequence starting from the starting data; in response to the accumulated value being greater than or equal to 1, stop accumulating and divide the data between the data and the last accumulated data into a data segment; take the last accumulated data as the new starting data, re-accumulate to obtain the next data segment, and verify each data segment separately; for a certain data, the larger its segment weight is, the shorter the data segment corresponding to the segmented data is.

2. The configuration change verification method based on virtual connection of IED equipment according to claim 1, characterized in that: For the jth item of data, the calculation expression for the possibility of error is: ； In the formula, Indicates The possibility of error in the data item, Indicates the total number of data transmissions corresponding to the configuration data at the historical moment, Indicates The configuration data of the first transmission The number of times the item data is wrong, Indicates The configuration data of the first transmission The first The data length of the data error. Indicates The configuration data of the first transmission The total length of the item data.

3. The configuration change verification method based on virtual connection of IED equipment according to claim 1, characterized in that: For the j-th data, the calculation expression of its average error rate is: ； In the formula, represents the average error rate of the j-th data, Indicates the total number of data transmissions corresponding to the configuration data at the historical moment, Indicates The configuration data of the first transmission The number of times the item data is wrong, Indicates The configuration data of the first transmission The first The data length of the data error. Indicates The configuration data of the first transmission The total length of the item data.

4. The configuration change verification method based on virtual connection of IED equipment according to claim 1, characterized in that: For the j-th data, the method for obtaining the average length of the erroneous data includes: The data length of the j-th item of erroneous data in each transmission of the configuration data is calculated respectively, and the average is calculated to obtain the average erroneous data length; for the configuration data of a certain transmission, the data length of the j-th item of erroneous data is equal to the sum of the lengths corresponding to the erroneous data of each transmission of the data.

5. The configuration change verification method based on virtual connection of IED equipment according to claim 1, characterized in that: Classifying the configuration data according to the average error rate and average error data length of each data item in the configuration data includes: forming a feature vector from the average error data length and the average error rate of each data item, and performing KMeans clustering on all data items according to the feature vector of each data item.

6. The configuration change verification method based on virtual connection of IED equipment according to claim 1, characterized in that: The configuration data at the historical moment includes: device identification name, device type configuration, device IP address, subnet mask and gateway, virtual connection ID, source and target nodes of data transmission, data object model, data type definition and sampling frequency.

7. The configuration change verification method based on virtual connection of IED equipment according to any one of claims 1 to 6, characterized in that: The preset segment length is 100.

8. A configuration change verification system based on virtual connection of IED equipment, comprising a memory and a processor, wherein the memory stores computer program instructions, characterized in that: When the computer program instructions are executed by the processor, the configuration change verification method based on the virtual connection of the IED device according to any one of claims 1 to 7 is implemented.

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