Distributed load equipment centralized control system of power grid

Abstract

A centralized control system using distributed load equipment comprises the distributed load equipment and electric energy storage equipment which is dispersedly installed on user sides of nodes of a power grid line. The output end of the user side controller is connected with the input end of the distributed load equipment, and the user side controller is used for receiving the scheduling instruction and executing the real-time scheduling instruction; the output end of the centralized control server is connected with the input end of the encryption and decryption server, and the centralized control server is used for generating a scheduling instruction; the encryption and decryption server is used for performing hierarchical encryption operation on the scheduling instruction and sending the scheduling instruction to the communication network; full-automatic operation of the load equipment is realized through real-time instruction scheduling, and different instruction contents are deeply understood, so that more accurate classification is realized, and the effect of improving encryption security through accurate classification is further realized.

Description

Technical Field

[0001] The present invention relates to the technical field of distributed energy control, and in particular to a distributed load equipment centralized control system of a power grid. Background Art

[0002] In my country, an analysis of the actual situation on the electricity consumption side found that the actual electricity load of each user under the power grid line still has some surplus compared to the applied capacity. When this surplus is accumulated, the actual idle capacity of the line is very huge. At the same time, most of the electricity load is concentrated in daytime work, and a large amount of idle capacity will be released during the off-peak period, causing a great waste of the capacity resources of the power grid line. Distributed load equipment has been used as energy storage equipment in the existing technology. The existing distributed load equipment needs to participate in the grid dispatch, but its communication line is not specially set up at present, and the lack of dispatching security greatly restricts the timely regulation and operation according to the grid instructions.

[0003] As power equipment becomes more and more popular and widespread in daily applications, the security of power grid dispatching becomes particularly important. If the power grid dispatching information is intercepted and tampered with, it means the possibility of safety hazards. How to ensure the confidentiality of command data during transmission and ensure that the terminal receiving power command data receives real and safe information is a technical problem that needs to be solved in the current development and application of distributed load equipment. Summary of the invention

[0004] In view of the deficiencies in the prior art, an object of the present invention is to provide a centralized control system for distributed load equipment.

[0005] A centralized control system using distributed load equipment, characterized in that it includes:

[0006] Distributed load equipment is an electric energy storage device installed at the user end of each node of the power grid line;

[0007] A user-side controller, whose input end is connected to the output end of the distributed load device, is used to receive the dispatch instruction and execute the real-time dispatch instruction;

[0008] A centralized control server, whose output terminal is connected to the input terminal of the encryption and decryption server, is used to generate scheduling instructions;

[0009] The encryption and decryption server is used to perform hierarchical encryption operations on the scheduling instructions and send them to the communication network.

[0010] The beneficial effects of the present invention are:

[0011] Compared with the prior art, the present invention designs a centralized control system utilizing distributed load equipment, adopts a centralized control mode for the distributed load equipment, and realizes the full automatic operation of the load equipment through real-time scheduling instructions in the centralized control mode. Moreover, by performing semantic analysis and hierarchical classification on the instruction data, it is possible to deeply understand the contents of different instructions in real time, accurately identify the corresponding keywords in different instructions, and realize more accurate classification, thereby achieving the effect of accurate classification to improve encryption security. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a system connection diagram.

[0013] Figure 2 It is a schematic diagram of the encryption algorithm flow;

[0014] In the figure: distributed load equipment 1, user-side controller 2, communication access layer 3, tunnel network 4, encryption and decryption equipment 5, data management server 6, centralized control server 7, user application server 8, database 9. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0016] Figure 1 As shown, the distributed load devices and the user-side controller 2 constitute a plurality of distributed load devices (1, 2...N) distributed at each node of the power grid line. In this embodiment, the electric energy storage devices distributed at each node of the power grid line are used as the distributed load devices.

[0017] The user-side controller 2 is an electronic control component used to set storage device operating parameters, device protection parameters, execute local control strategies, and execute real-time scheduling instructions.

[0018] Figure 1The multiple distributed load devices (1, 2...N) shown in the figure belong to the same power grid line for power supply. This attribute information will be entered into the centralized control server 7. At a certain moment, the centralized control system receives a power grid dispatching instruction to participate in peak-shaving and the power grid line where the two distributed load devices are located is within the peak-shaving range. The multiple distributed load devices (1, 2...N) will be put into operation using real-time dispatching instructions. After the peak-shaving is completed, they will operate according to their respective dispatching plans. Under special circumstances, the power grid line needs to release part of its capacity to ensure line safety. The centralized control system will dispatch multiple distributed load devices (1, 2...N) to exit operation in real time according to the released capacity requirements, so as to provide protection for the safety of the power grid line. All operating data and dispatching data will be saved by the database 9 for data analysis and query. The operating status and control authority selection of the equipment will be published to the public through the user application server 8 in the form of app, web, etc., and provided to users.

[0019] The centralized control server 7 sends the scheduling instructions for different devices to the user-side controller 2 for execution. The scheduling instructions are encrypted by the encryption and decryption server 5 and then access the tunnel network 4 , and then enter the user-side controller 2 after passing through the communication access layer 3 .

[0020] The user-side controller 2 also collects operating data of multiple distributed load devices (1, 2...N). The operating data is accessed to the tunnel network 4 through the communication access layer 3 and enters the data management server 6 through the encryption and decryption device 5.

[0021] The processing flow of the encryption and decryption device 5 for encrypting and decrypting the instruction data is as follows:

[0022] 1) Analyze and classify the instruction data to obtain several types of data fragments;

[0023] The semantic algorithm model is obtained by training based on a deep learning model and a large amount of historical instruction data. The trained semantic algorithm model is used to extract the semantic features of each phrase in the instruction data, and the deep semantic information of the phrase is captured by using the features. The similarity of each phrase is analyzed according to the deep semantic information, and the similarity between different phrases is calculated, and the similarity results are integrated to form fragments;

[0024] The semantic algorithm model is obtained by training based on a deep learning model and a large amount of historical instruction data, and a large amount of instruction data is obtained and preprocessed. The preprocessing includes cleaning and segmenting the instruction data, removing invalid characters and redundant characters in the instruction data through cleaning, and performing format standardization operations on the data; cutting the instructions into independent words or phrases for segmentation to form different phrases, using a deep learning model to capture semantic information of the segmented phrases and converting them into word vectors, and integrating the phrases into fragments according to the similarity of the semantic information;

[0025] Define the similarity metric, calculate the similarity of different phrases, set the similarity threshold, and integrate the phrases with similarity higher than the threshold to form fragments; the similarity metric is an indicator used to measure the similarity between two phrases. Each word is mapped to a vector in a high-dimensional space through a pre-trained deep learning model. Semantically similar words should be closer in the vector space.

[0026] For two phrases A and B, when mapped to three-dimensional space vectors A(x1, y1, z1) and B(x2, y2, z2), the calculation formula for the segment similarity L between every two phrases is:

[0027]

[0028] Where x1 represents the X value of the first word; x2 represents the X value of the second word; y1 represents the Y value of the first word; y2 represents the Y value of the second word; z1 represents the Z value of the first word; z2 represents the Z value of the first word; L represents the segment similarity;

[0029] A similarity threshold is set, and phrases with similarity higher than the threshold are integrated to form fragments.

[0030] 2) Logically classify several types of data fragments;

[0031] All fragments are obtained, and importance and sensitivity assessment is performed on each fragment. The importance assessment is performed based on the impact of the phrase on the operation of the power grid. Generally, the impact on the operation of the power grid can be assessed based on the professional attributes of the phrase, and it can be determined whether the phrase belongs to professional vocabulary. The sensitivity assessment is performed based on whether key operating instructions are involved. Key operating instructions are set according to the part of speech and meaning of the phrase, for example, adjust and reduce, which can be designated as key operating instructions.

[0032] It is necessary to pre-generate a professional vocabulary data set and a key operation instruction set, and use the generated professional vocabulary data set to compare with the phrase data that needs to be judged. The phrase data in the data set is judged to be professional vocabulary; the obtained phrase data is compared with the key operation instruction set. If the content matches and is close to the position of the professional vocabulary, it is judged to have key data;

[0033] If it is a professional vocabulary with key data, it is considered that the phrase has the highest impact on the operation of the power grid and can be set to level four; if it is a professional vocabulary without key data, it is considered that the phrase has a relatively high impact on the operation of the power grid and can be set to level three; if it is a non-professional vocabulary with key data, it is considered that the phrase has a relatively low impact on the operation of the power grid and can be set to level two; if it is a non-professional vocabulary without key data, it is considered that the phrase has the lowest impact on the operation of the power grid and can be set to level one; accordingly, all fragments are divided into four security levels, from low to high: level one, level two, level three, and level four.

[0034] 3) Encrypt all the fragments one by one according to the step-by-step encryption method;

[0035] Set the first-level subkey and set the extraction position set C (c1, c2, c3); use the initial key to encrypt the first-level fragment set to obtain the first ciphertext; perform ciphertext extraction at c1 on the first ciphertext, and the extracted ciphertext continues to be used as the second subkey; use the second subkey to encrypt the second-level fragment set to obtain the second ciphertext; perform ciphertext extraction at c2 on the second ciphertext, and the extracted ciphertext continues to be used as the third subkey; use the third subkey to encrypt the third-level fragment set to obtain the third ciphertext; perform ciphertext extraction at c3 on the third ciphertext, and the extracted ciphertext continues to be used as the fourth subkey; use the fourth subkey to encrypt the fourth-level fragment set to obtain the fourth ciphertext; thus, all data fragments are encrypted and the first, second, third, and fourth subkeys are obtained;

[0036] Concatenate several subkeys into a string to generate a total key.

[0037] The receiving end decrypts the ciphertext with the master key, and restores the position of each level of fragments based on the data coordinates to obtain the instruction data content.

[0038] The data management server sends a master key to the user-side controller 2. The user-side controller 2 uses the master key to verify the validity and legality of the instruction data and executes the operation. The centralized control system can then uniformly operate the distributed load equipment in accordance with the real-time scheduling instructions.

[0039] The real-time dispatching instruction is issued to the user-side controller in real time after being adjusted according to the real-time information of the power grid line capacity, so that the controller performs real-time work.

[0040] The system and method will greatly improve the safety and utilization of power grid lines, and will be able to support distributed load equipment to implement more cooperative operation modes.

[0041] Finally, it should be noted that the above description is only an explanation of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail, those skilled in the art can still modify the technical solutions described above or replace some of the technical features with equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A centralized control system using distributed load equipment, characterized in that: include, Distributed load equipment is an electric energy storage device installed at the user end of each node of the power grid line; The user-side controller has an output end connected to an input end of the distributed load device and is used to receive a dispatch instruction and execute a real-time dispatch instruction; A centralized control server, whose output terminal is connected to the input terminal of the encryption and decryption server, is used to generate scheduling instructions; The encryption and decryption server is used to perform hierarchical encryption operations on the scheduling instructions and send them to the communication network.

2. The centralized control system using distributed load equipment according to claim 1, characterized in that: Also includes a data management server; The user-side controller collects the operating data of the distributed load equipment. The operating data is accessed to the tunnel network through the communication access layer and enters the data management server through the encryption and decryption device.

3. The centralized control system using distributed load equipment according to claim 2, characterized in that: The data management server sends a master key to the user-side controller, which uses the master key to verify the instruction data and execute the operation.

4. The centralized control system using distributed load equipment according to claim 3, characterized in that: The encryption algorithms executed by the encryption and decryption server include: Analyze and classify the instruction data to obtain several types of data fragments; Logically classify several types of data fragments; All fragments are encrypted one by one in a step-by-step encryption manner to obtain a number of subkeys and a number of ciphertexts; Several sub-keys are concatenated to generate a total key.

5. The centralized control system using distributed load equipment according to claim 4, characterized in that: The user-side controller decrypts the ciphertext with the master key, and restores the position of each type of fragment based on the data coordinates to obtain the instruction data content.

6. The centralized control system using distributed load equipment according to claim 4, characterized in that: The step-by-step encryption method is to further extract the key from the previous level of ciphertext for the next level of encryption.

7. The centralized control system using distributed load equipment according to claim 4, characterized in that: The semantic algorithm model is trained based on a deep learning model and a large amount of historical instruction data. The trained semantic algorithm model is used to extract the semantic features of each phrase in the instruction data, and the deep semantic information of the phrase is captured using the features. The similarity of each phrase is analyzed according to the deep semantic information, the similarity between different phrases is calculated, and the similarity results are integrated to form fragments.

8. The centralized control system using distributed load equipment according to claim 4, characterized in that: The logical classification is to classify all segments into four security levels based on a professional vocabulary data set and a key operation instruction set.

9. The centralized control system using distributed load equipment according to claim 2, characterized in that: It also includes a database, in which all operating data and scheduling data will be stored for data analysis and query.

10. The centralized control system using distributed load equipment according to claim 2, characterized in that: It also includes an application server. The operating status of the device is published to the outside world in the form of app and web through the user application server and provided to users.

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