Remote operation device

Abstract

The invention discloses a remote operation device, which comprises a data acquisition module for acquiring environmental parameters, judging the current environmental state according to the change trend of the environmental parameters, and adjusting the sampling frequency and gain parameters of a signal acquisition module by adopting a self-adaptive algorithm according to the current environmental state; the data processing module performs real-time verification and error correction on the signal data acquired by the acquisition module, analyzes and extracts the signal data by using a signal processing algorithm based on wavelet transform, and selects an optimal operation scheme by adopting a priority judgment mechanism based on weighted scoring; and the operation execution module completes full-process remote operation of opening and closing operation according to the optimal operation scheme. According to the invention, the signal acquisition module is adaptively adjusted to cope with a complex environment through an environmental parameter change trend, data is analyzed by using a wavelet transform algorithm, an optimal operation scheme is generated based on a power grid dispatching instruction and a weighted scoring mechanism, and the reliability and safety of a power system in the complex environment are improved.

Description

Technical Field

[0001] The present invention relates to the field of relay protection and control of power systems, and particularly to a remote operation device. Background Art

[0002] In the power system, the remote operation technology of the switching device is a crucial technology, which is directly related to the safety and stability of the power network. The efficient operation of the power system depends on the coordinated work of the switching devices, and the remote operation technology of these devices makes the maintenance, dispatching and emergency handling of power equipment more efficient and convenient. With the continuous expansion of the scale and the increasing complexity of the power system, how to achieve reliable remote operation of these devices and ensure the efficient and stable operation of the power grid has become a key issue in modern power systems.

[0003] However, since the switching devices are usually located outdoors or in remote areas and need to work under variable and complex environmental conditions, there are many challenges in realizing their remote operation. First of all, the environment where the devices are located often encounters various adverse weather conditions, such as extreme climate conditions like high temperature, low temperature, strong wind, humidity, ice and snow, and lightning. These natural factors not only pose a threat to the physical structure of the devices themselves, but also may have a significant impact on the communication and operation stability of the control system. Under high temperature conditions, the equipment may overheat and malfunction; in a low temperature environment, the working efficiency of the device may be inhibited, or even cause the system to fail to start normally. In addition, excessive humidity may cause equipment corrosion, and lightning may damage the power lines and the transmission of remote operation signals. The existence of these factors undoubtedly poses great challenges to the stability and reliability of the remote operation system. The existing control methods for remote operation devices have low control stability in extreme climate environments and are difficult to achieve reliable and stable remote switching control operations. Summary of the Invention

[0004] The present invention provides a remote operation device, a control method, an electronic device and a storage medium, which solve the problem that it is difficult to achieve reliable and stable remote switching control operations in extreme climate environments.

[0005] According to one aspect of the present invention, the present invention provides a method for controlling a remote operation device, including: acquiring environmental parameters, judging the current environmental state according to the change trend of the environmental parameters, and adopting an adaptive algorithm according to the current environmental state to adjust the sampling frequency and gain parameters of a signal acquisition module; performing real-time verification and error correction on the signal data acquired by the acquisition module, using a signal processing algorithm based on wavelet transform to analyze and extract the signal data, and combining historical operation records to judge whether the current switching operation device state meets the operation conditions. If the device state is normal, an operation decision is generated according to the power grid dispatching instruction and control strategy, and an optimal operation scheme is selected by using a priority judgment mechanism based on weighted scoring; the full-process remote operation of the switching operation is completed according to the optimal operation scheme.

[0006] Further, the acquiring of the environmental parameters, judging the current environmental state according to the change trend of the environmental parameters, and adopting an adaptive algorithm according to the current environmental state to adjust the sampling frequency and gain parameters of the signal acquisition module are specifically as follows: acquiring the environmental parameters, where the environmental parameters include temperature value, humidity value, and lightning occurrence probability value, calculating the change rate of the environmental parameters, and determining the current environmental state based on the change rate; adopting an adaptive algorithm based on gradient descent to calculate the optimal sampling frequency adjustment amount and gain parameter adjustment amount according to the current environmental state; configuring the sampling frequency adjustment amount and the gain parameter adjustment amount into the signal acquisition module, and calculating the signal-to-noise ratio index of the signal acquisition module; if the signal-to-noise ratio index is lower than a preset threshold, recalculate the change rate of the environmental parameters, re-evaluate the environmental state, and update the adjustment amount.

[0007] Further, the calculation formula of the signal-to-noise ratio index is:

[0008]

[0009] where SNR represents the signal-to-noise ratio index, Ps ignal represents the signal power, and Pnoise represents the noise power.

[0010] Further, the performing of real-time verification and error correction on the signal data acquired by the acquisition module, using a signal processing algorithm based on wavelet transform to analyze and extract the signal data, and combining historical operation records to judge whether the current switching operation device state meets the operation conditions are specifically as follows: encapsulating the signal data acquired by the acquisition module through an encryption protocol, transmitting the signal data through an anti-interference transmission channel, and performing real-time verification and error correction on the signal data during the transmission process; using a signal processing algorithm based on wavelet transform to analyze and extract the signal data to obtain an analysis value, comparing the analysis value with the historical value of the historical operation record, and judging whether the current switching operation device state meets the operation conditions.

[0011] Furthermore, the full - process remote operation of the opening and closing operation completed according to the optimal operation plan is specifically as follows: During the execution of the optimal operation plan, the execution status is monitored in real time to determine whether there is a response delay; when a response timeout is detected, a fault diagnosis is performed, and the execution status is matched with a fault database based on a rule engine to identify and analyze the cause of the fault; according to the analysis result of the cause of the fault, a corresponding compensation mechanism or alternative plan is triggered, and the full - process remote operation of the opening and closing operation is completed on the premise of ensuring system stability.

[0012] Furthermore, the control instruction of the optimal operation plan is sent to the actuator after passing through a two - factor authentication security verification mechanism. During the execution of the actuator, the instruction transmission delay and the execution status are monitored in real time.

[0013] Furthermore, during the execution of the alternative plan, the system stability index is continuously monitored. If the stability index is within the preset range, the opening and closing operation is continued; after the opening and closing operation is completed, a full - process data summary and analysis are performed. If the analysis result meets the preset conditions, the operation process is completed; according to the full - process analysis result, the fault database is updated. If the new data is different from the fault mode or the original rules of the fault database, the rule content of the fault database is corrected.

[0014] According to another aspect of the present invention, a remote operation device is provided, including: a data acquisition module, which is used to acquire environmental parameters, judge the current environmental state according to the change trend of the environmental parameters, and adopt an adaptive algorithm according to the current environmental state to adjust the sampling frequency and gain parameters of the signal acquisition module; a data processing module, which is used to perform real - time verification and error correction on the signal data collected by the acquisition module, use a signal processing algorithm based on wavelet transform to analyze and extract the signal data, combine historical operation records to judge whether the current state of the opening and closing operation device meets the operation conditions. If the device state is normal, an operation decision is generated according to the power grid dispatching instruction and control strategy, and an optimal operation plan is selected by using a priority judgment mechanism based on weighted scoring; an operation execution module, which is used to complete the full - process remote operation of the opening and closing operation according to the optimal operation plan.

[0015] According to another aspect of the present invention, an electronic device is provided, including: at least one processor, and a memory communicatively connected to the at least one processor;

[0016] Wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any remote operation device control method in the embodiments of the present invention.

[0017] According to another aspect of the present invention, there is provided a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute any of the remote operation device control methods in the embodiments of the present invention.

[0018] According to the technology of the present invention, the signal acquisition module is adaptively adjusted according to the change trend of environmental parameters to cope with complex environments. After ensuring the security and reliability of signal data through real-time verification, the wavelet transform algorithm is used to analyze the data, and the state of the switching operation device is evaluated in combination with historical records. Based on the power grid dispatching instructions and the weighted scoring mechanism, an optimal operation plan is generated, realizing the intelligent control of the entire process of switching operation, improving the reliability and security of the power system in complex environments, and providing strong support for power grid dispatching and fault handling.

[0019] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Description of the Drawings

[0020] The drawings are used to better understand the solution and do not constitute a limitation to the present invention. Among them:

[0021] Figure 1 is a flowchart of the remote operation device control method provided by the embodiment of the present invention;

[0022] Figure 2 is a schematic structural diagram of the remote operation device provided by the embodiment of the present invention;

[0023] Figure 3 is a schematic diagram of the electronic device and storage medium of the embodiment of the present invention.

[0024] In the figure, 100, remote operation device; 11, data acquisition module; 12, data processing module; 13, operation execution module; 200, electronic device; 201, computing unit; 202, ROM; 203, RAM; 204, bus; 205, I / O interface; 206, input unit; 207, output unit; 208, storage unit; 209, communication unit. Detailed Embodiments

[0025] The following describes exemplary embodiments of the present invention with reference to the drawings. Various details of the embodiments of the present invention are included to assist understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the present invention. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0026] As Figure 1 shown, an embodiment of the present invention discloses a control method for a remote operation device, including: S1, obtaining environmental parameters, judging the current environmental state according to the change trend of the environmental parameters, and adopting an adaptive algorithm according to the current environmental state to adjust the sampling frequency and gain parameters of the signal acquisition module; S2, performing real-time verification and error correction on the signal data collected by the acquisition module, using a signal processing algorithm based on wavelet transform to analyze and extract the signal data, and combining historical operation records to judge whether the current switching operation device state meets the operation conditions. If the device state is normal, an operation decision is generated according to the power grid dispatching instruction and control strategy, and an optimal operation plan is selected by using a priority judgment mechanism based on weighted scoring; S3, completing the full process of remote operation of the switching operation according to the optimal operation plan.

[0027] The control method for the remote operation device of the switching operation of this application adaptively adjusts the signal acquisition module through the change trend of environmental parameters to cope with complex environments. After ensuring the safety and reliability of signal data through real-time verification, the wavelet transform algorithm is used to analyze the data, and the switching operation device state is evaluated in combination with historical records. Based on the power grid dispatching instruction and weighted scoring mechanism, an optimal operation plan is generated, realizing the intelligent control of the full process of the switching operation, improving the reliability and safety of the power system in complex environments, and providing strong support for power grid dispatching and fault handling.

[0028] In an optional embodiment of the present invention, step S1 is specifically: obtaining environmental parameters, where the environmental parameters include temperature value, humidity value, and lightning occurrence probability value, calculating the change rate of the environmental parameters, and determining the current environmental state based on the change rate; adopting an adaptive algorithm based on gradient descent, calculating the optimal sampling frequency adjustment amount and gain parameter adjustment amount according to the current environmental state; configuring the sampling frequency adjustment amount and gain parameter adjustment amount into the signal acquisition module, and calculating the signal-to-noise ratio index of the signal acquisition module; if the signal-to-noise ratio index is lower than the preset threshold, recalculate the change rate of the environmental parameters, re-evaluate the environmental state and update the adjustment amount. Establish a mapping relationship table between the temperature value, humidity value, lightning occurrence probability value and the sampling frequency and gain parameters, and train and optimize the mapping table through a machine learning algorithm. Adopt a support vector machine algorithm to classify and predict the environmental complexity, and select the corresponding sampling frequency and gain parameter combination according to the prediction result. Monitor the change of environmental parameters in real time, and trigger the adaptive algorithm to re-optimize the parameters and update the configuration when the parameter fluctuation exceeds the set range.

[0029] Specifically, the sensors of the switching device collect environmental parameters such as temperature, humidity, and lightning occurrence probability values. These data reflect the environmental conditions where the equipment is located. For example, during thunderstorm weather in summer, the temperature fluctuates around 30°C, the humidity reaches over 90%, and the lightning occurrence probability value increases significantly. By calculating the change rates of these parameters, the dynamic changes of the environment can be captured in a timely manner. The environmental complexity judgment rule can be considered comprehensively based on multiple factors. For instance, when the temperature change rate exceeds 5°C / hour, the humidity change rate exceeds 10% / hour, and the lightning occurrence probability value breaks through the safety threshold, it can be determined as a complex environmental state. This judgment helps the system respond quickly to extreme weather conditions. For different environmental states, an adaptive algorithm based on gradient descent is used to optimize the acquisition parameters. In a complex environment, it is necessary to increase the sampling frequency to capture rapidly changing signals, and at the same time adjust the gain parameter to improve the signal quality. For example, the initial sampling frequency is 100Hz, and it is adjusted to 200Hz through the algorithm; the gain parameter is adjusted from 1.5 to 2.0 to cope with the decrease in signal strength.

[0030] By using the signal-to-noise ratio index to evaluate the signal quality, assuming that the preset signal-to-noise ratio threshold of the system is 20dB, if the actually calculated signal-to-noise ratio is 15dB, which is lower than the threshold, it is necessary to re-evaluate the environmental state and adjust the parameters. This process requires multiple iterations until the ideal signal quality is achieved. The calculation formula for the signal-to-noise ratio index is:

[0031]

[0032] where SNR represents the signal-to-noise ratio index, Ps ignal represents the signal power, and Pnoise represents the noise power.

[0033] By establishing the mapping relationship between environmental parameters and acquisition parameters, the response speed of the system can be accelerated. For example, through machine learning algorithm training, it is known that when the temperature is 25°C, the humidity is 60%, and there is no obvious lightning activity, the optimal sampling frequency is 150Hz, and the gain parameter is 1.8. This mapping relationship can be continuously optimized as the system runs to improve the ability to cope with various environmental conditions. The application of the support vector machine algorithm in environmental complexity classification can train a high-precision classification model based on historical data. For example, the environmental complexity is divided into three levels: low, medium, and high, and each level corresponds to different parameter combinations. This predictive adjustment can anticipate upcoming environmental changes in advance and enhance the stability of the system.

[0034] The real-time monitoring and adaptive adjustment mechanism ensure the system's rapid response ability in the face of sudden environmental changes. For example, when it is detected that the temperature rises sharply by 10°C within a short period, the system will immediately trigger the process of re-optimizing the parameters, increase the sampling frequency by 50%, and adjust the gain parameters accordingly to adapt to the new environmental conditions. The core advantage of this adaptive mechanism lies in its ability to dynamically adjust the system parameters according to the actual environment, improving the reliability and accuracy of the switching operation device in various complex environments. Through continuous learning and optimization, the system can continuously enhance its ability to cope with various environmental challenges, thus playing a key role in the safe operation of the power system.

[0035] In an alternative embodiment of the present invention, step S2 is specifically as follows: The signal data collected by the acquisition module is encapsulated through an encryption protocol, and the anti-jamming transmission channel is used to transmit the signal data. During the transmission process, real-time verification and error correction of the signal data are performed; The signal processing algorithm based on wavelet transform is used to analyze and extract the signal data to obtain the analysis value, and the analysis value is compared with the historical value of the historical operation record to determine whether the current state of the switching operation device meets the operation conditions. If the device state is normal, an operation decision is generated according to the power grid dispatching instruction and the control strategy, and the optimal operation plan is selected by using the priority judgment mechanism based on weighted scoring.

[0036] Specifically, the encryption algorithm for encapsulating the signal value is an important means to ensure data security. For example, the AES-256 algorithm can be used to convert the 25.6°C collected by the temperature sensor into the ciphertext "7Fxk9p3Q2m". This encryption not only protects the original data but also increases the security of transmission. When the anti-jamming channel transmits the encrypted value, spread spectrum communication technology can be used. Suppose there is a lot of electromagnetic interference in the industrial field. By spreading the encrypted data to a wider frequency band, such as from 2 MHz to 20 MHz, narrowband interference can be effectively resisted. At the same time, forward error correction coding, such as Reed-Solomon code, can automatically correct some error bits during the transmission process. At the receiving end, the wavelet transform algorithm can extract the useful signal. For example, for temperature data containing high-frequency noise, using the db4 wavelet basis function for 3-layer decomposition can effectively separate the smooth temperature change trend. This method can not only remove noise but also retain the important features of the signal.

[0037] By comparing the parsed value with the historical value, the device status is judged. Suppose the oil temperature of a certain power transformer fluctuates within the range of 50°C to 55°C in the past 24 hours. If the current parsed value suddenly reaches 65°C, it indicates that the device is overheated and cooling measures need to be taken immediately. This comparison mechanism can detect abnormalities in a timely manner and prevent equipment failures. When generating operation decisions according to grid commands and strategies, various factors can be considered. For example, during the peak grid load period, the output of the generator sets needs to be increased. At this time, the system will comprehensively consider the start-up time, fuel cost, environmental protection indicators, etc. of each unit to form a series of feasible dispatching plans. The weighted scoring algorithm is used to evaluate the decision value in order to find the optimal plan. Suppose there are three plans: Plan A has a low cost but a long start-up time, Plan B starts quickly but has a higher pollution level, and Plan C balances various indicators. By setting different weights (such as 30% for cost, 40% for response time, and 30% for environmental protection indicators), the comprehensive score of each plan can be calculated. Finally, the plan with the highest score is selected for execution, which not only ensures the stable operation of the power grid but also takes into account economic and environmental requirements. This series of steps constitutes a complete intelligent power grid control process. From data collection, transmission, processing to decision-making, advanced technologies are used in each link to ensure the safety, reliability, and efficiency of the entire system. This intelligent management method not only improves the operation efficiency of the power grid but also lays a foundation for the management of more complex energy systems in the future.

[0038] In an alternative embodiment of the present invention, step S3 is specifically as follows: The control instruction of the optimal operation plan is sent to the actuator after passing through the security verification mechanism of two-factor authentication. During the execution process of the actuator, the instruction transmission delay and the execution status are monitored in real time to determine whether there is a response delay; when a response timeout is detected, a fault diagnosis is performed, and the execution status is matched with the fault database based on the rule engine to identify and analyze the cause of the fault; according to the analysis result of the cause of the fault, the corresponding compensation mechanism or alternative plan is triggered, and the full-process remote operation of the switching operation is completed on the premise of ensuring the stability of the system.

[0039] Specifically, in a power system, two-factor authentication may include the operator's password and a dynamic token. When it is necessary to adjust the output of a certain generator set, the operator first enters the personal password and then enters the six-digit token generated in real time on the mobile phone. The combination of these two factors greatly reduces the risk of unauthorized operations. The verified instruction is sent to the actuator through an anti-interference transmission channel to ensure the accurate transmission of the instruction. In the high-voltage substation environment, electromagnetic interference is very common. Therefore, fiber-optic communication technology can be adopted. Optical signals are not affected by electromagnetic interference and can maintain stable transmission even in a strong electric field environment. For example, sending the control instruction "increase the load of transformer No. 3 by 20 MW" through the optical fiber can effectively avoid signal distortion caused by electromagnetic interference. Monitoring the transmission delay of the instruction in real time by the real-time monitoring system is the key to ensuring the timeliness of control. In a smart grid, the timeliness of the execution of control instructions is directly related to the stability of the system. Assuming that the preset maximum allowable delay is 100 milliseconds, the system will continuously monitor the time from the issuance of each instruction to its receipt by the actuator.

[0040] If it is detected that the transmission time of an instruction to increase the output of a generator set reaches 150 milliseconds, exceeding the preset threshold, the system will immediately issue an alarm. This delay monitoring mechanism can promptly detect network congestion or equipment failures. For example, if the transmission delays of consecutive instructions exceed the threshold, it means that there is a problem with the communication network and immediate troubleshooting is required. Another example is that if the delay in receiving an instruction by a specific actuator suddenly increases, it indicates that there is an abnormality in the device and maintenance is needed. The reason for adopting this composite security mechanism lies in the particularity and importance of the power system. Grid control involves a large number of critical infrastructures, and incorrect operations may lead to serious consequences such as large-scale power outages. Two-factor authentication ensures the legality of operations, anti-interference transmission guarantees the integrity of instructions, and delay monitoring ensures the real-time nature of control. These three protection mechanisms cooperate with each other to form a comprehensive security protection network. In terms of technical effects, this mechanism significantly improves the security and reliability of grid control. It can not only effectively prevent unauthorized access and malicious operations, but also ensure that control instructions are accurately transmitted to the actuator in a complex electromagnetic environment. At the same time, real-time delay monitoring enables the system to quickly respond to potential network or equipment problems, minimizing the risk of control failure caused by communication failures. The implementation of this security mechanism is of great significance for ensuring the stable operation of the power grid, improving the anti-interference ability of the system, and enhancing the defense ability against network attacks. It lays a solid security foundation for the intelligent and automated control of the power grid, enabling more complex and efficient control strategies to be implemented safely and reliably.

[0041] Fault analysis is carried out by obtaining the real-time status information of the system, such as key parameters like voltage, current, frequency, etc., and comparing the key parameters with the preset fault modes in the rule engine. For example, if it is detected that the current of a certain transmission line suddenly surges and exceeds 150% of the normal load, the system will immediately match this anomaly with the fault mode of "line overload". Based on the matching result, the system selects an appropriate coping strategy from the compensation mechanism library. In the case of line overload, a load transfer plan will be initiated to transfer part of the power demand to the standby line. If the fault level reaches the preset threshold, such as continuous overload for more than 10 minutes, the system will trigger a more stringent standby plan, including temporarily cutting off some non-critical loads. During the execution of the standby plan, the system continuously monitors key stability indicators, such as voltage stability and frequency deviation. Assuming that during normal operation, the allowable voltage fluctuation range is ±5% of the rated value, and the frequency deviation does not exceed ±0.2 Hz. As long as these indicators remain within the safe range, the system will continue to perform the scheduled switching operations.

[0042] Key parameters are collected in real time through switching operations in the core control link of the power system, such as switch operation time, contact temperature, etc. These data will be compared with the historical normal operation records. For example, if the opening time of a certain circuit breaker is 50 milliseconds longer than the normal value, the system will immediately issue a warning and record this abnormal situation, which indicates an early sign of mechanical failure. According to the real-time monitored system status, the parameters of the compensation mechanism need to be dynamically adjusted. For example, in the case of a power grid frequency drop, the system will increase the output power of the generator set. If the adjusted frequency tends to be stable and remains between 49.95 Hz and 50.05 Hz, the current settings will be maintained. After the entire operation process is completed, the system will conduct a comprehensive data analysis. This includes a complete review of the process of fault occurrence, development, and resolution. If the analysis result shows that all parameters have returned to the normal range and the system stability is guaranteed, it is determined that the operation process is successfully completed. Finally, based on the analysis result of this event, the system will update the fault database. If new fault modes or deficiencies in the original rules are found, such as the development speed of a certain fault being faster than expected, the rule library will be corrected accordingly. This self-learning and optimization mechanism can continuously improve the system's fault diagnosis and handling capabilities, providing a more reliable guarantee for the safe and stable operation of the power grid.

[0043] As Figure 2 shown, the remote operation device 100 may include:

[0044] A data acquisition module 11, which is used to acquire environmental parameters, judge the current environmental status according to the change trend of the environmental parameters, and adopt an adaptive algorithm according to the current environmental status to adjust the sampling frequency and gain parameters of the signal acquisition module;

[0045] The data processing module 12 is used to perform real-time verification and error correction on the signal data collected by the acquisition module, parse and extract the signal data using a signal processing algorithm based on wavelet transform, and combine historical operation records to determine whether the current on-off operation device state meets the operation conditions. If the device state is normal, an operation decision is generated according to the power grid dispatching instruction and control strategy, and an optimal operation plan is selected using a priority judgment mechanism based on weighted scoring.

[0046] The operation execution module 13 is used to complete the full-process remote operation of the on-off operation according to the optimal operation plan.

[0047] For the specific functions and examples of the modules and sub-modules of the device in the embodiments of the present invention, reference can be made to the relevant descriptions of the corresponding steps in the above method embodiments, which will not be elaborated here.

[0048] In the technical solution of the present invention, the acquisition, storage, and application of the user's personal information involved all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0049] According to the embodiments of the present invention, the present invention also provides an electronic device, a readable storage medium, and a computer program product.

[0050] Figure 2 FIG. shows a schematic block diagram of an exemplary electronic device 200 that can be used to implement the embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present invention described herein and / or claimed.

[0051] As Figure 3 shown, the device 200 includes a computing unit 201, which can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 202 or the computer program loaded from the storage unit 208 into the random access memory (RAM) 203. In the RAM 203, various programs and data required for the operation of the device 200 can also be stored. The computing unit 201, the ROM 202, and the RAM 203 are connected to each other through a bus 204. The input / output (I / O) interface 205 is also connected to the bus 204.

[0052] Multiple components in device 200 are connected to I / O interface 205, including: an input unit 206, such as a keyboard, a mouse, etc.; an output unit 207, such as various types of displays, speakers, etc.; a storage unit 208, such as a disk, an optical disc, etc.; and a communication unit 209, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 209 allows device 200 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0053] The computing unit 201 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 201 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 201 executes the various methods and processes described above, such as a remote operation device control method. For example, in some embodiments, a remote operation device control method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 208. In some embodiments, part or all of the computer program can be loaded and / or installed onto device 200 via the ROM 202 and / or the communication unit 209. When the computer program is loaded into the RAM 203 and executed by the computing unit 201, one or more steps of the remote operation device control method described above can be executed. Alternatively, in other embodiments, the computing unit 201 can be configured to execute a remote operation device control method in any other suitable way (e.g., by means of firmware).

[0054] The various embodiments of the systems and technologies described above in this article can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), systems-on-chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0055] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program codes can be executed entirely on the machine, partially on the machine, executed partially on the machine as an independent software package and partially on a remote machine, or executed entirely on a remote machine or server.

[0056] In the context of the present invention, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0057] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0058] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), and the Internet.

[0059] A computer system can include a client and a server. The client and the server are generally far from each other and typically interact through a communication network. The client - server relationship is created by computer programs running on the respective computers and having a client - server relationship with each other. The server can be a cloud server, a server of a distributed system, or a server incorporating blockchain.

[0060] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present invention can be achieved. No limitation is imposed herein.

[0061] The above - described specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub - combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A remote control device control method, characterized in that: include: Acquire environmental parameters, determine the current environmental state according to the change trend of the environmental parameters, and use an adaptive algorithm according to the current environmental state to adjust the sampling frequency and gain parameters of the signal acquisition module; The signal data collected by the acquisition module is verified and corrected in real time, and the signal data is analyzed and extracted using a signal processing algorithm based on wavelet transform. The current state of the opening and closing operation equipment is judged in combination with historical operation records to determine whether the operation conditions are met. If the equipment state is normal, an operation decision is generated according to the grid dispatching instructions and control strategies, and the optimal operation plan is selected using a priority judgment mechanism based on weighted scoring; The entire process of opening and closing the switch is remotely operated according to the optimal operation plan.

2. The method according to claim 1, characterized in that The environmental parameters are obtained, the current environmental state is determined according to the change trend of the environmental parameters, and an adaptive algorithm is used according to the current environmental state to adjust the sampling frequency and gain parameters of the signal acquisition module, specifically: Acquire the environmental parameters, which include temperature, humidity, and lightning occurrence probability, calculate the change rate of the environmental parameters, and determine the current environmental state based on the change rate; Adopting an adaptive algorithm based on gradient descent to calculate the optimal sampling frequency adjustment amount and the gain parameter adjustment amount according to the current environmental state; Configuring the sampling frequency adjustment amount and the gain parameter adjustment amount into the signal acquisition module, and calculating the signal-to-noise ratio index of the signal acquisition module; If the signal-to-noise ratio indicator is lower than a preset threshold, the rate of change of the environmental parameter is recalculated, the environmental state is re-evaluated and the adjustment amount is updated.

3. The method according to claim 2, characterized in that The calculation formula of the signal-to-noise ratio index is: Wherein, SNR represents the signal-to-noise ratio indicator, Psignal represents signal power, and Pnoise represents noise power.

4. The method according to claim 1, characterized in that: The signal data collected by the acquisition module is verified and corrected in real time, and the signal data is analyzed and extracted using a signal processing algorithm based on wavelet transform, and combined with historical operation records, it is determined whether the current state of the opening and closing operation device meets the operation conditions, specifically: The signal data collected by the acquisition module is encapsulated through an encryption protocol, the signal data is transmitted through an anti-interference transmission channel, and the signal data is verified and corrected in real time during the transmission process; The signal data is analyzed and extracted by using a signal processing algorithm based on wavelet transform to obtain an analysis value, and the analysis value is compared with the historical value of the historical operation record to determine whether the current state of the opening and closing operation device meets the operation conditions.

5. The method according to claim 1, characterized in that The full-process remote operation of completing the opening and closing operation according to the optimal operation plan is specifically as follows: During the execution of the optimal operation plan, the execution status is monitored in real time to determine whether there is a response delay; When a response timeout is detected, fault diagnosis is performed, the execution status is matched with a fault database based on a rule engine, and the cause of the fault is identified and analyzed; According to the analysis results of the fault cause, the corresponding compensation mechanism or backup plan is triggered to complete the full process remote operation of the opening and closing operation while ensuring the stability of the system.

6. The method according to claim 5, characterized in that The control instructions of the optimal operation plan are sent to the execution mechanism after passing the security verification mechanism of the two-factor authentication. During the execution process of the execution mechanism, the instruction transmission delay and execution status are monitored in real time.

7. The method according to claim 5, characterized in that During the execution of the backup plan, the system stability index is continuously monitored, and if the stability index is within a preset range, the opening and closing operations are continued; After the opening and closing operations are completed, the whole process data is summarized and analyzed. If the analysis results meet the preset conditions, the operation process is completed; According to the full-process analysis results, the fault database is updated. If there is a difference between the new data and the fault mode or original rules of the fault database, the rule content of the fault database is corrected.

8. A remote operation device, characterized in that: include: A data acquisition module, the data acquisition module is used to acquire environmental parameters, judge the current environmental state according to the change trend of the environmental parameters, and use an adaptive algorithm according to the current environmental state to adjust the sampling frequency and gain parameters of the signal acquisition module; A data processing module, which is used to perform real-time verification and error correction on the signal data collected by the acquisition module, parse and extract the signal data using a signal processing algorithm based on wavelet transform, and determine whether the current state of the opening and closing operation equipment meets the operation conditions in combination with historical operation records. If the equipment state is normal, an operation decision is generated according to the power grid dispatching instructions and control strategy, and the optimal operation plan is selected using a priority judgment mechanism based on weighted scoring; An operation execution module is used to complete the full-process remote operation of the opening and closing operations according to the optimal operation plan.

9. An electronic device, characterized in that: include: at least one processor, and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

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