Power system switching station intelligent control system based on Internet of Things architecture

Abstract

A power system switching station intelligent control system based on an Internet of Things architecture comprises a sensing layer, a network layer, an application layer and a safety guarantee layer, and all the layers achieve information interaction and control through a wireless communication protocol. According to the automatic control scheme based on the Internet of Things architecture, through cooperative work of the sensing layer, the network layer, the application layer and the safety guarantee layer, equipment information is collected in real time, the equipment state is displayed, logic judgment is carried out, operation tasks are received, meanwhile, operation tickets are automatically generated, the operation process is simulated, and the one-key sequential control function is achieved; therefore, the safety, the automation degree and the execution efficiency of equipment operation are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of switch station control, and in particular to an intelligent control system for a power system switch station based on an Internet of Things architecture. Background Art

[0002] Traditional switchyard equipment management relies on manual operation, which not only carries the risk of operational errors but also increases management complexity and labor costs. As power grids grow larger, especially within switchyards, where multiple devices have interlocking relationships and operational sequence dependencies, traditional methods that rely on human control of equipment are unable to ensure safe and efficient operations. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide an intelligent control system for power system switch stations based on the Internet of Things architecture, which effectively improves the safety, automation level and execution efficiency of equipment operation.

[0004] To solve the above technical problems, the technical solution adopted by the present invention is: an intelligent control system for power system switch stations based on the Internet of Things architecture, including a perception layer, a network layer, an application layer, and a security layer. Each layer realizes information exchange and control through wireless communication protocols, as follows: Perception layer: IoT sensors and actuator feedback units are deployed to collect real-time data on the position, energy storage pressure, switch oil level, number of operations, voltage, current, temperature, and environmental conditions of switchyard equipment (switches, disconnect switches, grounding switches, and fast switches). The data also monitors the status of the protection plates in the relay room. The actuator execution units receive instructions from the monitoring system and execute equipment operations. Sensors and actuators communicate with the network layer via the NB-IoT protocol. Network layer: Uses industrial Ethernet to build a high-speed transmission network, enabling data from the perception layer devices to be uploaded to the application layer, and control instructions from the application layer to the execution unit of the perception layer, supporting real-time data transmission and two-way communication; Application layer: including information processing, status display, logic control, operation management and fault warning functions; Security layer: Adopting data encryption, access control, and identity authentication security mechanisms to ensure secure information transmission and reliable operation.

[0005] Preferably, the IoT sensors of the perception layer include position sensors, pressure sensors, oil level sensors, voltage sensors, current sensors and temperature sensors, covering full status monitoring of switch station equipment and relay room protection pressure plates, and the actuator execution unit supports the opening and closing of the equipment and the operation of the pressure plates.

[0006] Preferably, the information collection and processing module of the application layer performs burr removal and value filling processing on the real-time data: the previous value is taken to denoise the sudden change data, the interpolation method is used to fill the value of the occasionally missing data, and an alarm is triggered and processing is stopped for the continuously missing data; for the failure of equipment status collection, the post-fill method is used for the occasional failure, and the alarm is triggered and processing is stopped for the continuous failure.

[0007] Preferably, the device status display module of the application layer synchronously monitors the system screen, displays the equipment operation status, connection line topology and layout order in real time, and supports multi-dimensional status query, including the opening and closing status of the switch station equipment and the relay room pressure plate, and the activation status of the protection device.

[0008] Preferably, the device logic control module of the application layer presets the device locking logic as follows: (1) The opening and closing of the switches in the string requires judging the positions of the switches on both sides; (2) The opening and closing of the knife switch must meet the requirements of disconnecting the switch and pulling out the ground knife on the same electrical connection; (3) The opening and closing of the grounding switch must meet the requirements of the opening of the switch on the same connection, including the locking conditions of the busbar grounding switch and the inner and outer grounding switches of the incoming / outgoing lines.

[0009] Preferably, the operation management module of the application layer supports automatic generation, review, simulation and execution of operation tickets, as follows: (1) Generation methods include dispatch instruction parsing, simulated operation, manual target state, and LSTM model intelligent ticket generation; (2) Automatically review and verify the legitimacy of the operation ticket by combining equipment locking logic, operation sequence requirements and dispatching commands; (3) The simulation operation verifies the rationality of the process, and the one-button sequential control module links the monitoring system to execute according to the ticket and provide real-time feedback on the operation results.

[0010] Preferably, the LSTM model intelligent ticketing mode collects historical operation data to train the model, optimizes the hyperparameters and stores them in the system, and automatically generates an operation ticket that complies with the operation logic and locking rules when receiving a scheduling task.

[0011] Preferably, the fault warning module of the application layer builds a fault diagnosis model based on the LSTM model, collects historical operation data of the equipment and fault sample training, inputs time series data of voltage, current and pressure in real time, and performs real-time prediction and level warning of faults such as switch closing failure, three-phase parameter imbalance and SF6 pressure abnormality.

[0012] Preferably, the security layer adopts a double-layer encryption mechanism: link layer encryption is implemented between the perception layer and the network layer through the NB-IoT protocol, and AES-256 symmetric encryption and RSA asymmetric encryption are combined between the network layer and the application layer. The key is uniformly managed by the TPM security chip to ensure data transmission security.

[0013] Preferably, the application layer integrates the equipment status definition module to standardize the operation, hot standby, cold standby and maintenance status of the switch station equipment (busbar, line, transformer, etc.), clarify the status requirements of switches, circuit breakers, earth switches and protective devices in each state, and support the automatic analysis of equipment status conversion and generation of operation steps in dispatching instructions.

[0014] The present invention provides an intelligent control system for power system switch stations based on the Internet of Things architecture, which has the following beneficial effects: 1. Improve operational efficiency: Through IoT technology, power station switch stations can achieve real-time data collection and remote monitoring to optimize equipment operating status. The system can automatically detect the health of power station equipment and improve overall operational efficiency.

[0015] 2. Enhanced fault diagnosis and early warning capabilities: The intelligent system can monitor the operating parameters of electrical equipment in real time, such as current, voltage, temperature, etc., quickly detect potential faults and issue early warnings, reducing the probability of accidents and shortening fault handling time.

[0016] 3. Reduce operation and maintenance costs: Through the Internet of Things and intelligent technology, remote control and maintenance of equipment can be achieved, thereby saving human resources and maintenance costs.

[0017] 4. Data-driven decision support: With the help of IoT technology, power station switch stations can accumulate large amounts of data and assist decision makers in optimizing system configuration, operation and maintenance plans, and equipment update cycles based on big data analysis.

[0018] 5. Strong environmental adaptability: The intelligent system design can adapt to different power station environments. Combined with the distributed characteristics of the Internet of Things, it has strong flexibility and scalability and can be customized according to the actual needs of different power stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 It is a structural schematic diagram of the present invention; Figure 2 This is a schematic diagram of switch connections when the present invention is used. DETAILED DESCRIPTION

[0020] like Figure 1As shown in the figure, an intelligent control system for power system switch stations based on the Internet of Things architecture includes a perception layer, a network layer, an application layer, and a security layer. Each layer implements information exchange and control through wireless communication protocols, as follows: Perception layer: IoT sensors and actuator feedback units are deployed to collect real-time data on the position, energy storage pressure, switch oil level, number of operations, voltage, current, temperature, and environmental conditions of switchyard equipment (switches, disconnect switches, grounding switches, and fast switches). The data also monitors the status of the protection plates in the relay room. The actuator execution units receive instructions from the monitoring system and execute equipment operations. Sensors and actuators communicate with the network layer via the NB-IoT protocol. Network layer: Uses industrial Ethernet to build a high-speed transmission network, enabling data from the perception layer devices to be uploaded to the application layer, and control instructions from the application layer to the execution unit of the perception layer, supporting real-time data transmission and two-way communication; Application layer: including information processing, status display, logic control, operation management and fault warning functions; Security layer: Adopting data encryption, access control, and identity authentication security mechanisms to ensure secure information transmission and reliable operation.

[0021] Preferably, the IoT sensors of the perception layer include position sensors, pressure sensors, oil level sensors, voltage sensors, current sensors and temperature sensors, covering full status monitoring of switch station equipment and relay room protection pressure plates, and the actuator execution unit supports the opening and closing of the equipment and the operation of the pressure plates.

[0022] Preferably, the information collection and processing module of the application layer performs burr removal and value filling processing on the real-time data: the previous value is taken to denoise the sudden change data, the interpolation method is used to fill the value of the occasionally missing data, and an alarm is triggered and processing is stopped for the continuously missing data; for the failure of equipment status collection, the post-fill method is used for the occasional failure, and the alarm is triggered and processing is stopped for the continuous failure.

[0023] Preferably, the device status display module of the application layer synchronously monitors the system screen, displays the equipment operation status, connection line topology and layout order in real time, and supports multi-dimensional status query, including the opening and closing status of the switch station equipment and the relay room pressure plate, and the activation status of the protection device.

[0024] Preferably, the device logic control module of the application layer presets the device locking logic as follows: (1) The opening and closing of the switches in the string requires judging the positions of the switches on both sides; (2) The opening and closing of the knife switch must meet the requirements of disconnecting the switch and pulling out the ground knife on the same electrical connection; (3) The opening and closing of the grounding switch must meet the requirements of the opening of the switch on the same connection, including the locking conditions of the busbar grounding switch and the inner and outer grounding switches of the incoming / outgoing lines.

[0025] Preferably, the operation management module of the application layer supports automatic generation, review, simulation and execution of operation tickets, as follows: (1) Generation methods include dispatch instruction parsing, simulated operation, manual target state, and LSTM model intelligent ticket generation; (2) Automatically review and verify the legitimacy of the operation ticket by combining equipment locking logic, operation sequence requirements and dispatching commands; (3) The simulation operation verifies the rationality of the process, and the one-button sequential control module links the monitoring system to execute according to the ticket and provide real-time feedback on the operation results.

[0026] Preferably, the LSTM model intelligent ticketing mode collects historical operation data to train the model, optimizes the hyperparameters and stores them in the system, and automatically generates an operation ticket that complies with the operation logic and locking rules when receiving a scheduling task.

[0027] Preferably, the fault warning module of the application layer builds a fault diagnosis model based on the LSTM model, collects historical operation data of the equipment and fault sample training, inputs time series data of voltage, current and pressure in real time, and performs real-time prediction and level warning of faults such as switch closing failure, three-phase parameter imbalance and SF6 pressure abnormality.

[0028] Preferably, the security layer adopts a double-layer encryption mechanism: link layer encryption is implemented between the perception layer and the network layer through the NB-IoT protocol, and AES-256 symmetric encryption and RSA asymmetric encryption are combined between the network layer and the application layer. The key is uniformly managed by the TPM security chip to ensure data transmission security.

[0029] Preferably, the application layer integrates the equipment status definition module to standardize the operation, hot standby, cold standby and maintenance status of the switch station equipment (busbar, line, transformer, etc.), clarify the status requirements of switches, circuit breakers, earth switches and protective devices in each state, and support the automatic analysis of equipment status conversion and generation of operation steps in dispatching instructions.

[0030] LSTM (Long Short-Term Memory) is a model specifically designed for processing time series data. It can capture long-term dependencies, memorize historical states, and influence current decisions. Operation tickets require reference to device state changes over the past hours or even days, and LSTM can effectively model this sequential logic.

[0031] The core principle behind building an intelligent power system ticketing model using LSTM (Long Short-Term Memory) networks lies in capturing the temporal dependencies and complex rules of operational processes in the power system through time series modeling and dynamic memory mechanisms. The following is a breakdown of the specific principles.

[0032] LSTM solves the long-term dependency problem of traditional RNN through gating units and memory cells, and is suitable for modeling the timing characteristics of power systems.

[0033] Forget gate: decides whether to retain or discard historical information to determine whether the current device status needs to refer to the device status and change data of various physical quantities in the past.

[0034] Input gate: Select the information that needs to be updated in the current input, and based on the real-time current, voltage, temperature and other data, simultaneously determine and update the memory of the device status.

[0035] Memory cells: Store long-term status information (dynamically update and record the cumulative operating time, historical fault counts, action counts, current, voltage, temperature, pressure, and other key states of the device from history to the present through the forget gate and input gate).

[0036] Output gate: Generates the final output such as "open circuit breaker A" based on the current input and historical memory.

[0037] The LSTM model construction process is as follows: (1) Data preparation (a) Data collection Collect the location, energy storage pressure, switch oil level, number of operations, voltage, current, temperature, and environmental data of switchyard equipment (switches, disconnects, grounding switches, and fast switches) over a three-year period. Input the equipment model, topological connection relationships, and safety rule base. Simultaneously capture all operational sequence steps and dispatch instructions for the three-year period.

[0038] (b) Data cleaning Deburring: For sudden changes in data (such as voltage and current surges), the previous value replacement method is used to smooth the noise.

[0039] Missing value handling: Linear interpolation is used for values ​​that are missing by chance.

[0040] (c) Label production Encode the operation step sequence as a one-hot direction; Fault warning: label the binary label (0 / 1) based on the fault occurrence time.

[0041] (2) Model architecture design (a) Intelligent Ticketing Model (Using Encoder-Decoder Structure) Encoder layer: Input: Time series data of device status, such as voltage, current, and pressure, collected over a historical period. The architecture is a two-layer LSTM with 256 hidden layer nodes and the Tanh activation function.

[0042] Output: Context Vector, encoding historical state semantics.

[0043] Decoder layer: Input: context vector + generated operation steps. Its architecture is a single-layer LSTM with 256 hidden nodes, and its output is a Softmax probability distribution. A blocking logic mask (e.g., prohibiting hot closing) is added to the output layer. Bahdanau attention is used to focus on key time steps, such as when a fault occurs and when physical quantities change.

[0044] (b) Fault warning model (using time series classification structure) Input layer: equipment time series data (voltage, current, pressure, etc.).

[0045] LSTM layer: Two-layer stacked LSTM with 128 hidden layer nodes to capture long-term dependencies.

[0046] Fully connected layer: outputs failure probability (Sigmoid activation) and supports multi-label classification.

[0047] Output: Fault type and warning level (e.g. SF6 pressure abnormality, level 2). (3) Model training and optimization (a) Training strategy: Use cross entropy loss as the loss function, use Adam optimizer, initial learning rate 0.001, and use Dropout regularization to prevent overfitting (b) Hyperparameter tuning: Set the number of hidden layer nodes to {64, 128, 256} and the batch size to {32, 64}.

[0048] (c) Rule constraint injection: Illegal operation options are blocked at the decoder output layer, and positive rewards are given to operation steps that comply with regulations.

[0049] (4) Model verification and testing Use the BLEU score to measure the similarity between the intelligent ticket generation sequence and the real ticket to determine whether the trained model meets the requirements and whether the hyperparameters need to be updated. Use accuracy and warning response time to evaluate fault warnings, set specific coefficients, and judge and determine whether the trained model meets the requirements and whether the hyperparameters need to be updated. (5) Model deployment and application Intelligent ticket generation module: After receiving the dispatch instruction, the LSTM model is called to generate the operation ticket, which is then pushed to the one-key sequential control module after automatic review.

[0050] Fault warning module: Real-time stream data processing: Receive sensor data through Kafka and input it into the LSTM model to predict faults.

[0051] Example: The process of generating a switching operation ticket is as follows: 1. Input: Dispatch command "Transfer bus M1 to maintenance".

[0052] 2. Data preparation: Extract the timing status (voltage, switch position, etc.) of the devices associated with busbar M1.

[0053] Load the blocking rules (e.g. “closing the busbar earth switch requires all connected switches to be opened”).

[0054] 3. Model Reasoning: The Encoder encodes the historical state, and the Decoder generates the operation sequence step by step: Step 1: Open all connected switches (probability 0.95) Step 2: Open all connected switches (probability 0.93) Step 3: Close the busbar ground switch (probability 0.90) 4. Output: Generate an operation ticket and automatically verify the locking logic, and push it to the simulation operation module.

[0055] The application layer is the core of the system, responsible for data processing, control decision-making, instruction generation, error prevention and simulation operations, instruction issuance, etc. Specifically, it includes: 1. Information Collection and Processing Module: This module acquires device data in real time and performs preliminary data processing. It removes burrs from sudden changes by taking the previous value. It interpolates small amounts of missing data. For continuous missing data, it issues an alarm and stops processing. For occasional device status acquisition failures, it uses the post-addition method to fill in the missing state. For continuous data failures, it issues an alarm and stops processing the missing state.

[0056] 2. Display of equipment status: In the application layer, the equipment display page synchronizes the monitoring system screen, and can display the status of each device in the switch station and the feedback protection pressure plate, the status of the equipment connection line, and the equipment layout sequence in real time.

[0057] 3. Definition of Equipment Status: All switches, earthing switches, and knife switches in a switch station have two states: open and closed. At the same time, switches, earthing switches, and knife switches connect to other equipment in the switch station, such as busbars, lines, and transformers. During operation, the states of these switches, earthing switches, and knife switches are changed to change the state of these equipment. When power grid dispatchers issue commands, in addition to operating lines, individual switches, earthing switches, and knife switches, they typically issue status commands for busbars, lines, transformers, and other equipment, such as operating status, hot standby status, cold standby status, and maintenance status. Therefore, it is necessary to define equipment status.

[0058] The detailed requirements for switches, knife switches, and earth switches in each state are as follows: Switch state definition

[0059] Switches, knife switches, and earth switches are connected to lines, generator-transformer units, transformers, ice melters, high-voltage shunt reactors, busbars, and phase regulators. By changing the status of switches, knife switches, and earth switches, the status of the above devices can be changed. The status of the above devices is defined as follows: Switchyard Equipment Status Definition Lines, generator sets, transformers, ice melting:

[0060] High voltage shunt reactor:

[0061] Busbar, phase regulator:

[0062] All equipment in the switch station is defined in turn according to the requirements of the connected switches, circuit breakers and grounding circuit breakers according to the above equipment status.

[0063] 4. Equipment locking logic judgment Whether each switch, circuit breaker, and earthing switch can be opened or closed is affected by the status of the connected equipment. If the equipment is not operated according to the set logic, it may cause serious mechanical and electrical damage to the equipment. In severe cases, it may even cause additional damage to the equipment's input and output lines and generator sets. The specific locking logic of the equipment is as follows: The general principles of locking conditions are as follows: 1) Switch in series: Determine the position of the knife switches on both sides of the switch.

[0064] 2) 500kV knife switch needs to judge whether the switch on the same electrical connection is disconnected and the ground knife is pulled out, as follows: a) Knife switches on both sides of the switch in the string: disconnect the switch, open the ground switches on both sides of the switch, and open the ground switches on the same connection. That is, open the busbar ground switch on the knife switch close to the busbar, and open the ground switch on the side close to the incoming and outgoing lines; b) Incoming line switch: disconnect the two incoming line switches in the string, open the ground switch on the same connection, and open the ground switch on the low-voltage side of the main transformer (if any); c) Outgoing line switch: The two outgoing line switches in the string are disconnected and the ground switch on the same connection is pulled open.

[0065] 3) The grounding switch needs to determine whether the switch on the same connection is opened, as follows: a) Earth switches on both sides of the switch in the string: pull out the switches on both sides of the switch; b) Busbar ground switch: pull out the switches on each string close to the busbar; c) Incoming line inner side ground switch: open the incoming line switch, and open the two switches on both sides of the incoming line; d) Incoming line outer side ground switch: the incoming line switch is opened, the low-voltage side of the main transformer is without pressure, and the generator outlet switch 2**1 is opened; e) Outgoing line inner side ground switch: open the outgoing line switch, and open the two switches on both sides of the outgoing line; f) Outer side grounding switch of the outgoing line: the outgoing line switch is opened and the line has no pressure.

[0066] With this Figure 2 The 5111 switch and connected equipment are analyzed and explained as shown in the following table:

[0067] 3.5. Equipment operation sequence requirements: The operation sequence analysis is carried out based on the 4 / 3 wiring method. The 3 / 2 wiring principle is the same. The two switches on the side where the 4 / 3 wiring appears are defined as being close to the bottom. The 5112 switch in the above figure is the side switch, close to the top. The 5113 switch in the above figure is the middle switch.

[0068]

[0069] The above table only describes the process of equipment from operation to hot standby to cold standby to maintenance. The order from maintenance to cold standby to hot standby to operation is the opposite. If an intermediate state is required during operation, the operation is performed on the equipment according to the equipment state definition. After all equipment is operated to cold standby, the equipment protection device needs to be deactivated. After the protection device confirms the deactivation, the equipment is transferred to maintenance state. If the equipment is only transferred to cold standby, the decision on whether to deactivate the protection device is based on the dispatch order ticket. If the incoming or outgoing line is transferred to maintenance, but the switch in the string is operating, the short-lead protection between the switches needs to be activated before the protection of the relevant incoming line equipment (main transformer protection) and the outgoing line protection is deactivated, and then the response protection is deactivated. When deactivating operation, the order is reversed.

[0070] 6. Module for receiving operation instructions and automatically generating operation tickets: The system can automatically connect to the power grid command system. When the power grid issues an operation instruction in the command system and the operation instruction process reaches the dispatcher for confirmation, the system automatically obtains the dispatcher instruction and lists it in the latest operation task item column. The system has an automatic ticket generation function. There are four methods of automatic ticket generation. The first is to generate tickets according to the dispatcher instruction, automatically decomposing the operation task according to the requirements and operation logic. The second is to simulate the operation on the operation page and automatically generate tickets based on the simulated operation task. The third is for the staff to manually write the operation ticket. They can directly write the task that needs to be operated manually, or they can write the operation task through the target state, select the equipment that needs to be operated, and clarify the state of the equipment that needs to be operated. The system will automatically generate it. The fourth is to use the LSTM network model to write. The LSTM model is built into the system to collect relevant data in the historical operation process. The powerful memory function of the LSTM model is used to fully optimize the LSTM model hyperparameters through training, verification and testing, and obtain the LTSM intelligent ticket generation model and store it in the system. Every time an operation task issued by the dispatcher is received, the operation task is obtained into the LSTM model through the protocol interface to automatically generate an operation ticket.

[0071] 7. Automatic review of operation tickets: The completed operation ticket is submitted and associated with the operation task issued by the grid dispatcher. After submission, the system reviews the operation content in the operation ticket in combination with the locking logic of each device, the operation sequence requirements, and the content of the dispatch order ticket. The system will only transfer the ticket to the ready state after the review is completed and correct. Only in the ready state can the operation be ordered.

[0072] 8. Simulation Operation: Before actual operation, the entire operation process can be simulated to verify whether the operation steps are reasonable and avoid equipment damage or power grid failure caused by incorrect operation sequence. Therefore, on the interactive page of the system, according to the prepared operation ticket, the action simulation operation can be carried out. The staff will review the current operation task based on the simulated equipment action. In addition, the staff can also manually simulate the equipment to be operated to verify whether the operation is correct. The operation ticket can be automatically generated based on the manual operation process.

[0073] 9. One-key sequential control module: After the operation ticket is prepared, the system can be linked to the switch station monitoring system. Click to command the operation, and the monitoring system will operate the equipment according to the operation tasks listed in the operation ticket. After each device is operated, a feedback signal will be sent to the monitoring system and the interactive page.

[0074] 10. Fault warning: In addition to realizing the functions associated with the above-mentioned related operations, the system also has a major feature, which is fault warning. The current switch station mainly has switch closing failure, three-phase current, voltage imbalance, grounding current fault, operating mechanism indication fault, SF6 pressure abnormality, etc. When a fault occurs, it will be verified that it affects the power supply reliability. Since the special diagnostic data of switch station related faults has a strong time series, the LSTM model is continued to be used to build a switch station fault diagnosis model, collect historical data and sample data at the time of the fault, and obtain prediction models for various faults through training, verification, testing, and optimization. The real-time equipment operation data is collected as input value into the optimal fault prediction LSTM model to predict possible faults in the switch station in real time, guide staff to carry out equipment maintenance, enhance the reliability of equipment movement, and provide efficient and accurate equipment fault warnings to provide strong guarantees for the stable operation of the power system.

[0075] The present invention proposes an automation control solution based on the Internet of Things architecture. Through the collaborative work of the perception layer, network layer, application layer and security assurance layer, it collects equipment information in real time, displays equipment status, performs logical judgment and receives operation tasks, and automatically generates operation tickets, simulates the operation process and realizes one-button sequential control function, thereby effectively improving the safety, automation level and execution efficiency of equipment operation.

[0076] The above embodiments are merely preferred technical solutions of the present invention and should not be construed as limiting the present invention. The scope of protection of the present invention shall be the technical solutions set forth in the claims, including equivalent alternatives to the technical features of the technical solutions set forth in the claims. In other words, equivalent alternatives and improvements within this scope are also within the scope of protection of the present invention.

Claims

1. An intelligent control system for a power system switch station based on the Internet of Things architecture, characterized by: It includes the perception layer, network layer, application layer and security layer. Each layer realizes information exchange and control through wireless communication protocols, as follows: Perception layer: IoT sensors and actuator feedback units are deployed to collect real-time data on the switchyard equipment's location, energy storage pressure, switch oil level, number of operations, voltage, current, temperature, and environment, and simultaneously monitor the status of the relay room's protection plate. The actuator execution unit receives instructions from the monitoring system and executes equipment operations. Sensors and actuators communicate with the network layer via the NB-IoT protocol. Network layer: Uses industrial Ethernet to build a high-speed transmission network, enabling data from the perception layer devices to be uploaded to the application layer, and control instructions from the application layer to the execution unit of the perception layer, supporting real-time data transmission and two-way communication; Application layer: including information processing, status display, logic control, operation management and fault warning functions; Security layer: Adopting data encryption, access control, and identity authentication security mechanisms to ensure secure information transmission and reliable operation.

2. The power system switch station intelligent control system based on the Internet of Things architecture according to claim 1, characterized in that: The IoT sensors of the perception layer include position sensors, pressure sensors, oil level sensors, voltage sensors, current sensors and temperature sensors, covering full status monitoring of switch station equipment and relay room protection pressure plates. The actuator execution unit supports the opening and closing of equipment and the operation of pressure plate insertion and withdrawal.

3. The intelligent control system for power system switchyards based on the Internet of Things architecture according to claim 1, characterized in that: The information collection and processing module of the application layer performs burr removal and value filling processing on real-time data: the previous value is used to remove noise from sudden change data, interpolation is used to fill in the value of occasional missing data, and an alarm is triggered and processing is stopped for continuously missing data; if the equipment status collection fails, the post-fill method is used for occasional failures, and an alarm is triggered and processing is stopped for continuous failures.

4. The intelligent control system for power system switchyards based on the Internet of Things architecture according to claim 1, characterized in that: The device status display module of the application layer synchronously monitors the system screen, displays the equipment operation status, connection line topology and layout sequence in real time, and supports multi-dimensional status query, including the opening and closing status of the switch station equipment and the relay room pressure plate, and the activation status of the protection device.

5. The intelligent control system for power system switchyard based on the Internet of Things architecture according to claim 1, characterized in that: The device logic control module of the application layer presets the device locking logic as follows: (1) The opening and closing of the switches in the string requires judging the positions of the switches on both sides; (2) The opening and closing of the knife switch must meet the requirements of disconnecting the switch and pulling out the ground knife on the same electrical connection; (3) The opening and closing of the grounding switch must meet the requirements of the opening of the switch on the same connection, including the locking conditions of the busbar grounding switch and the inner and outer grounding switches of the incoming / outgoing lines.

6. The power system switch station intelligent control system based on the Internet of Things architecture according to claim 1, characterized in that: The operation management module of the application layer supports automatic generation, review, simulation and execution of operation tickets, as follows: (1) Generation methods include dispatch instruction parsing, simulated operation, manual target state, and LSTM model intelligent ticket generation; (2) Automatically review and verify the legitimacy of the operation ticket by combining equipment locking logic, operation sequence requirements and dispatching commands; (3) The simulation operation verifies the rationality of the process, and the one-button sequential control module links the monitoring system to execute according to the ticket and provide real-time feedback on the operation results.

7. The intelligent control system for power system switchyards based on the Internet of Things architecture according to claim 6, characterized in that: The LSTM model intelligent ticketing mode collects historical operation data to train the model, optimizes the hyperparameters and stores them in the system, and automatically generates an operation ticket that conforms to the operation logic and locking rules when receiving a scheduling task.

8. The power system switch station intelligent control system based on the Internet of Things architecture according to claim 1, characterized in that: The fault warning module of the application layer builds a fault diagnosis model based on the LSTM model, collects historical equipment operation data and fault sample training, and inputs real-time time series data of voltage, current, and pressure to perform real-time prediction and level warning of faults such as switch closing failure, three-phase parameter imbalance, and SF6 pressure abnormality.

9. The intelligent control system for a power system switch station based on the Internet of Things architecture according to claim 1, characterized in that: The security layer adopts a two-layer encryption mechanism: link layer encryption is implemented through the NB-IoT protocol between the perception layer and the network layer, and AES-256 symmetric encryption and RSA asymmetric encryption are combined between the network layer and the application layer. The key is uniformly managed by the TPM security chip to ensure data transmission security.

10. The intelligent control system for a power system switch station based on the Internet of Things architecture according to claim 1, characterized in that: The application layer integrates the equipment status definition module to standardize the operation, hot standby, cold standby and maintenance status of the switch station equipment, clarify the status requirements of switches, circuit breakers, ground switches and protective devices in each state, and support the automatic analysis and operation step generation of equipment status conversion in the dispatching instructions.

Images