Remote operation and maintenance method of power equipment under virtual mapping

Abstract

The present invention relates to the technical field of electric power operation and maintenance management, and specifically includes a remote operation and maintenance method for electric power equipment under virtual mapping, the method comprising: monitoring electric power equipment, collecting parameters in real time and uploading them to the cloud; constructing a simulation space, dynamically simulating the state of the power grid; introducing a fault decision-making mechanism, outputting protection and operation and maintenance strategies according to the state of the equipment, and remotely sending the strategies to the control terminal, thereby solving the technical problem that the mutual influence between the equipment in the power grid is complex, the abnormal state of the electric power equipment cannot be identified and processed in time, thereby triggering a chain reaction and affecting the overall stability of the power grid, and realizes remote detection and identification of the abnormal state of the equipment, automatically generates the protection strategy and the operation and maintenance strategy of the electric power equipment, takes measures quickly when a fault occurs, reduces the impact of the equipment fault on the entire power grid, effectively improves the stability of the electric power equipment, prevents the fault from spreading within the power grid, and enhances the overall reliability and emergency response capability of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field related to power operation and maintenance management, and in particular to a remote operation and maintenance method for power equipment under virtual mapping. Background Art

[0002] With the advancement of global energy transformation, the proportion of renewable energy in the power system continues to increase, especially unstable renewable energy such as photovoltaic and wind power. Against this background, new standards are proposed for the operation and maintenance management of power systems. At present, modern technologies such as the Internet of Things are gradually being applied to the operation and maintenance of power systems. However, the operation and maintenance work in the power system mainly relies on periodic online inspections, and a certain amount of repair time is still required when facing abnormal equipment conditions. In addition, in large-scale distributed energy systems, such as photovoltaic power stations and wind farms, power equipment is widely distributed and the environment is harsh, and the ability to respond to sudden failures is limited.

[0003] In summary, the existing technology has the technical problem that the mutual influence between the devices in the power grid is complex, the abnormal status of the power equipment cannot be identified and handled in time, thereby triggering a chain reaction and affecting the overall stability of the power grid. Summary of the Invention

[0004] This application provides a remote operation and maintenance method for power equipment under virtual mapping, aiming to solve the technical problems in the existing technology that the mutual influence between equipment in the power grid is complex, the abnormal status of power equipment cannot be identified and processed in time, thereby triggering a chain reaction and affecting the overall stability of the power grid.

[0005] In view of the above problems, the technical solution to implement this application is:

[0006] The present application provides a remote operation and maintenance method for power equipment under virtual mapping, wherein the method includes: monitoring power equipment, collecting real-time operating parameters, and uploading them to a cloud data center in real time; in the cloud data center, setting a simulation space under virtual mapping in combination with the target power grid topology; based on the simulation space under the virtual mapping, synchronously and dynamically simulating power flow, load distribution and mutual influence between power equipment, and restoring the operating status of the power equipment; at the same time, introducing a fault decision mechanism, and virtually mapping to the power equipment protection connection layer and the power equipment operation and maintenance connection layer according to the operating status and abnormal status of the power equipment; connecting the power equipment protection connection layer and the power equipment operation and maintenance connection layer, and outputting the power equipment protection strategy and the power equipment operation and maintenance strategy, wherein the power equipment protection strategy is used to minimize the impact of the abnormal status of the power equipment on the stable operation of the power grid; based on the cloud data center, remotely sending the power equipment protection strategy and the power equipment operation and maintenance strategy to the control terminal.

[0007] In summary, the one or more technical solutions provided in this application solve the technical problems of complex mutual influences between devices in the power grid, the failure to timely identify and handle abnormal conditions of power equipment, and thus triggering chain reactions, affecting the overall stability of the power grid. It realizes remote detection and identification of abnormal conditions of equipment, automatically generates power equipment protection strategies and power equipment operation and maintenance strategies, takes quick measures when a fault occurs, reduces the impact of equipment failures on the entire power grid, effectively improves the stability of power equipment, prevents faults from spreading within the power grid, and enhances the overall reliability and emergency response capabilities of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A flowchart of a remote operation and maintenance method for power equipment under virtual mapping is provided for this application;

[0009] Figure 2 This application provides a flow chart of sending remote operation and maintenance instructions in a remote operation and maintenance method for power equipment under virtual mapping. DETAILED DESCRIPTION

[0010] The present application is described in detail below with reference to the accompanying drawings. Figure 1 As shown, the present application provides a remote operation and maintenance method for power equipment under virtual mapping, wherein the method includes:

[0011] S1: Monitor power equipment, collect real-time operating parameters, and upload them to the cloud data center in real time; S2: In the cloud data center, combine the target power grid topology to set up a simulation space under virtual mapping; S3: Based on the simulation space under the virtual mapping, synchronously and dynamically simulate the power flow, load distribution and the mutual influence between power equipment to restore the operating status of the power equipment.

[0012] Specifically, power equipment is used to characterize various types of equipment used to transmit, distribute and manage electric energy in the power system, such as transformers, switchgear, mutual inductors, etc.; real-time operating parameters refer to various types of data generated in real time by power equipment during operation, such as voltage, current, temperature, frequency, load, etc. These data can reflect the operating status of the power equipment; cloud data centers are remote data storage and computing platforms connected to the Internet, used to store, process and analyze data. Cloud data centers can provide powerful computing power and data storage space to support remote monitoring and analysis of power systems; virtual mapping refers to mapping power equipment and grid structures into virtual space for more convenient and intuitive analysis, simulation and decision-making; simulation space refers to the grid operation simulation environment created in the cloud data center based on virtual mapping technology. In the simulation space, various operating states and potential faults of the power system can be simulated to help analyze the behavior of power equipment and grids.

[0013] Execution steps: Monitor power equipment, that is, collect various operating parameters of power equipment in real time through sensors, smart metering devices, etc. For example, sensors installed on transformers can collect voltage, current, temperature, load and other data in real time to ensure the real-time and accuracy of these data; the collected real-time operating parameters will be uploaded to a cloud data center, which can store and process data from different power equipment and provide data support for subsequent simulation and analysis.

[0014] In a cloud data center, by analyzing the overall structure and equipment information of the power grid and combining it with the topology of the target power grid (for example, the connection relationships between substations, transmission lines, distribution stations, and other equipment in the power grid), a simulation space under virtual mapping can be created in the cloud data center. By mapping various types of equipment in the power grid and the power grid topology into a model, a virtual power system environment is created. In this power system environment, the power flow, load distribution, and other behaviors of the power grid during operation are simulated.

[0015] Power flow refers to the process by which electricity is transmitted from a power station through the transmission network and distribution network to the user. Power flow simulation helps analyze the operating status of the power grid by calculating the current and voltage distribution at each node in the power grid. Load distribution refers to the distribution of power load at each node in the power grid (such as substations, distribution stations, user terminals, etc.). By analyzing the load distribution, the load situation and power demand of the power grid can be understood. The mutual influence between power equipment refers to the relationship between various types of equipment in the power system, for example, the current and voltage relationship between transformers and switchgear, and the impact of load changes on power equipment. In the simulation space, based on parameters such as power flow and load distribution, the cloud system will perform dynamic power grid simulation in real time.

[0016] Power flow analysis determines the flow of electricity from power plants to end users and calculates parameters such as voltage and current at each node to ensure the safe and stable operation of the power grid. For example, simulations can be used to calculate the current load distribution in the power grid, such as which areas have higher loads and which equipment may be overloaded. By simulating different load changes and the interaction between power equipment, the operating status of power equipment can be restored, accurately reflecting whether the power equipment is operating normally or whether there is a potential failure risk. This process dynamically monitors the operating status of power equipment and provides timely feedback when anomalies occur in the power system, providing real-time data support for subsequent maintenance, fault diagnosis, and protection decisions.

[0017] S4: At the same time, a fault decision mechanism is introduced, and according to the operating status and abnormal status of the power equipment, virtual mapping is performed to the power equipment protection connection layer and the power equipment operation and maintenance connection layer; S5: The power equipment protection connection layer and the power equipment operation and maintenance connection layer are connected to output the power equipment protection strategy and the power equipment operation and maintenance strategy, wherein the power equipment protection strategy is used to minimize the impact of the abnormal status of the power equipment on the stable operation of the power grid; S6: Based on the cloud data center, the power equipment protection strategy and the power equipment operation and maintenance strategy are remotely sent to the control terminal.

[0018] Specifically, the fault decision mechanism is an intelligent decision-making mechanism used to analyze the operating status and abnormal status of power equipment and make corresponding decisions. The purpose is to promptly identify potential faults of power equipment and take measures to reduce the impact on the stability of the power system; the power equipment protection connection layer is a virtualization layer used to store the protection strategies, emergency response procedures and protection devices of power equipment to ensure that when equipment fails, the protection mechanism can be automatically triggered to prevent equipment damage and grid fault expansion; the power equipment operation and maintenance connection layer is another virtualization layer used to collect and manage equipment operation and maintenance information, including maintenance plans, fault repair strategies, operation steps, etc., which are related to the actual operation and maintenance operations of power equipment. , helping remote operation and maintenance personnel to make fault diagnosis, scheduling and maintenance decisions; the power equipment protection strategy is an automated protection measure set for possible fault situations of power equipment (such as overload, short circuit, voltage abnormality, etc.), which can avoid equipment damage and other equipment in the power grid system to the greatest extent; the power equipment operation and maintenance strategy refers to the maintenance and management strategy set to maintain the stable operation of power equipment, including regular inspection, fault detection, real-time monitoring, repair and replacement of parts, etc.; the control terminal refers to the remote control system or terminal device connected to the power equipment, which is used to receive data and policy instructions from the cloud and perform related operations, such as adjusting equipment operating parameters or starting protection mechanisms.

[0019] Execution steps: Introduce a fault decision mechanism. The function of this mechanism is to determine whether the equipment has a fault by analyzing the operating status and abnormal status of the power equipment (such as equipment overload, high temperature, load fluctuation, etc.), and trigger the corresponding processing mechanism. For example, if the temperature of a transformer exceeds the safe range, the fault decision mechanism will determine that the equipment has entered a potential fault state. Based on this, the fault decision mechanism will decide whether to start the protection strategy or operation and maintenance strategy according to the preset standards or rules. Specifically, the system will virtually map the abnormal status of the power equipment to two virtual connection layers: the power equipment protection connection layer and the power equipment operation and maintenance connection layer; the protection connection layer mainly focuses on the rapid response to equipment failures, such as power off protection and overload protection of the equipment, while the operation and maintenance connection layer focuses on equipment fault detection, analysis and repair operations, such as the dispatcher's maintenance instructions for the equipment.

[0020] When equipment enters a faulty or abnormal state, power equipment protection strategies and power equipment operation and maintenance strategies are automatically generated. Protection strategies typically include immediately disconnecting the equipment's power supply, switching to backup equipment, and limiting loads to prevent the fault from spreading further and affecting other equipment or the stability of the power grid. Operation and maintenance strategies are long-term maintenance plans generated based on the fault type and equipment status, including dispatching maintenance personnel, equipment inspections, and parts replacement. This provides automated protection for power equipment.

[0021] The generated power equipment protection strategy and power equipment operation and maintenance strategy will be sent to the corresponding control terminal through the cloud data center. The control terminal refers to the control equipment of the power dispatching center and substation. After receiving the instructions, the control terminal will perform corresponding operations according to the strategy requirements. Specifically, the power equipment protection strategy is adjusted using industrial control optimization rather than taking extreme measures immediately (such as completely cutting off power or immediately switching equipment). This can minimize interference with the power system and ensure stable operation of the system. For example, if the temperature of a transformer exceeds the preset safety range, more serious failures due to overheating can be avoided by reducing the load, adjusting the working status of parallel equipment, or temporarily activating the backup cooling system.

[0022] Through the power equipment protection connection layer, the system can execute these industrial control optimization measures, such as adjusting the transformer load, regulating the operating temperature, or starting auxiliary equipment, to ensure stable equipment operation and avoid serious damage caused by excessive equipment temperature or abnormal load. At the same time, the power equipment operation and maintenance connection layer will generate subsequent operation and maintenance plans, and propose maintenance plans for potential equipment problems, such as arranging inspections, equipment maintenance, and parts replacement. These operation and maintenance strategies not only repair the current abnormal status, but also take into account the long-term health status of the equipment, and prevent possible future failures through data analysis and prediction.

[0023] The instructions are then sent via the cloud data center to the corresponding control terminals (such as power dispatch centers and substation control equipment). Upon receiving the instructions, the control terminals perform real-time operations based on the policy requirements. For example, for transformers with abnormal loads, the control terminals will adjust the power load distribution, activate backup power supply equipment, or adjust other parts of the grid to share the excessive load, thereby preventing equipment overload or further temperature increases. In these steps, through the coordinated operation of virtual mapping, fault decision-making mechanisms, and remote command transmission, power equipment protection and operation and maintenance strategies can be executed in real time and efficiently. This not only improves the operational safety and stability of the power grid, but also ensures rapid response and handling of power equipment failures, and guarantees the long-term stable operation of the power grid system.

[0024] Furthermore, if Figure 2 As shown, a fault decision mechanism is introduced, and the application method includes:

[0025] Based on the fault case library, a fault decision mechanism is set up; according to the fault decision mechanism, the abnormal state response of the power equipment is used to determine whether it is in a potential fault state, and the abnormal state response includes temperature abnormality and load abnormality; when the power equipment is in a potential fault state, a remote operation and maintenance instruction is sent, and the remote operation and maintenance instruction is used to activate the control terminal.

[0026] Specifically, the fault case library is a database that integrates historical fault data of power equipment and related fault handling experience. It contains information such as the response, handling methods, repair time, and impact range of different types of equipment in various fault situations; abnormal state response refers to the detection of certain parameters (such as temperature, load, vibration, etc.) deviating from the normal range during the operation of power equipment. These abnormal responses are the basis for the fault decision mechanism to judge the potential fault of the equipment; potential fault state means that although the power equipment has not suffered a clear fault, its operating state is already abnormal or critical. Continuing in a potential fault state for a period of time will lead to the occurrence of a fault. For example, the equipment temperature is too high or the load fluctuates abnormally. Although it does not directly damage the equipment, these are signs of potential faults; the control terminal is a physical device connected to the power equipment and the remote operation and maintenance system. It usually includes a control panel, a data interface, and a communication module. The control terminal receives instructions from the remote system and performs necessary operations, such as starting the protection mechanism and adjusting the equipment working mode.

[0027] Implementation steps: Establish a fault case library, which stores the response strategies and handling experience of power equipment in different fault situations. For example, for transformer overload faults, the case library records the temperature change trend of the transformer during overload, common overload thresholds, how to adjust the load, and whether to switch to backup equipment. The fault case library will serve as the basic data for the fault decision-making mechanism to help the system identify faults.

[0028] The fault decision mechanism is an intelligent decision-making process used to determine whether a device is at risk of failure based on its operating status and abnormal indicators. Through a fault case library, the system can learn and accumulate common fault patterns, automatically determine whether the device is in a potential fault state, and decide whether protective measures need to be taken. During the execution of the fault decision mechanism, the status of power equipment is monitored in real time, and responses are made to abnormal conditions, such as abnormal equipment temperature (such as transformer temperature exceeding the safe value) and abnormal load (such as large load fluctuations). These abnormalities are usually indicators of potential faults. If the system monitors that certain indicators of the device deviate from the normal operating range, the fault decision mechanism will automatically determine whether the device is in a potential fault state. For example, if the transformer temperature exceeds the set value for 10 consecutive minutes, the device is considered to be in a potential fault state.

[0029] Once the system determines that a power device has entered a potential fault state, it triggers automated remote O&M instructions. These instructions are issued by a cloud or central system to control the power device to perform certain operations, such as powering off, adjusting parameters, or activating protection mechanisms. These instructions can be sent via the network to an on-site control terminal, which then executes the corresponding operation. Remote O&M instructions can include activating the device's protection mechanisms (such as disconnecting the power supply or starting the cooling system) and instructing the control terminal to perform the corresponding protection operation. For example, if the temperature is abnormal, the system instructs the control terminal to activate the cooling device; if the load is abnormal, the system instructs the control terminal to limit the device's load or switch to a backup power source. Remote O&M instructions are instantly transmitted to the device and executed, ensuring the reliable operation of the power system and minimizing further damage to the device or impact on the stability of the power grid. When a potential fault occurs, the introduction of a fault decision-making mechanism and remote O&M instructions enables intelligent and remote management of power equipment.

[0030] Furthermore, the present application method also includes:

[0031] The simulation space includes a transformer mapping unit, a switch device mapping unit, and a transformer mapping unit; the potential fault states are prioritized to obtain a fault decision sequence; the transformer mapping unit, the switch device mapping unit, and the transformer mapping unit in the simulation space are connected to classify the potential fault states and add fault type labels; based on the fault decision sequence and the fault type labels, the remote operation and maintenance instructions are generated.

[0032] Specifically, the simulation space refers to a simulation area established in a virtual environment to simulate power equipment and their interconnections. Based on the power grid topology, it can simulate power flows, load distribution, and the interactions between equipment in real time, thereby achieving dynamic simulation and monitoring of the operating status of power equipment. The transformer mapping unit is a module in the simulation space that corresponds to the transformer in real power equipment in the virtual environment. The transformer mapping unit receives real-time data (such as voltage, current, and temperature) from the actual transformer and performs simulation calculations to reflect the transformer's operating status and possible faults. The switchgear mapping unit is another module in the simulation space that reflects the operating status of switchgear (such as circuit breakers and load switches) in the power system. It simulates the switch status and current load changes of the switchgear through simulation models to enable real-time monitoring of device status and control instructions. The transformer mapping unit is used to simulate the operating status of transformers (such as current transformers and transformers). It is responsible for converting the electrical data (such as current and voltage) of the transformers in the actual power system into virtual signals to facilitate dynamic simulation and monitoring in the simulation space.

[0033] Execution steps: Based on the actual operating data of power equipment and the topology of the power grid, a virtual mapping environment is created in the simulation space. In this space, power equipment (such as transformers, switchgear, and mutual inductors) will have corresponding mapping units. These mapping units reflect the status of the equipment in real time by receiving data from real equipment. Specifically, the transformer mapping unit converts the transformer's electrical parameters (such as voltage, current, and temperature) into virtual signals, the switchgear mapping unit simulates the equipment's switch status, load, and other information, and the mutual inductor mapping unit handles the signal conversion and mapping of current and voltage.

[0034] A potential fault state refers to an abnormal operating state of power equipment. Although it may not directly lead to a fault, it carries a risk of failure. For example, equipment temperature exceeding a safety threshold or abnormal load may indicate that the equipment is about to fail. Furthermore, when the equipment enters a potential fault state, such as unstable current or excessively high equipment temperature, the system will analyze these abnormal states through a fault decision mechanism and generate a fault decision sequence. A fault decision sequence refers to a series of decision steps or instructions generated after prioritizing various types of faults based on the potential fault state of the equipment. The order of these instructions is arranged based on the urgency and impact scope of each fault to ensure that the most serious or most dangerous faults are handled first. The fault decision sequence will be sorted according to the urgency of the fault, the possible impact, and the priority of handling. For example, a high temperature abnormality of a transformer may be handled first because there is a certain probability that a high temperature abnormality of a transformer will cause serious damage to the equipment or even trigger a large-scale power failure.

[0035] Fault type labels are a way to classify and mark faults that occur in power equipment. By setting labels for different fault modes, specific types of faults can be quickly identified and handled. Specifically, fault type labels are added to different potential fault states. For example, excessive temperature can be marked as a high temperature fault, and load overload can be marked as a load abnormality. In this way, each fault state has a clear classification label, which facilitates subsequent fault handling and response.

[0036] After completing the fault type classification, the corresponding remote operation and maintenance instructions are generated based on the fault decision sequence and fault type label. The remote operation and maintenance instructions include specific operations for the equipment, such as starting protection mechanisms, limiting equipment load, or directly switching to backup equipment. For example, if the temperature of the transformer is too high, the system will issue an instruction to start the cooling device or reduce the load, thereby avoiding damage to the transformer, ensuring the safe operation of the power equipment, and preventing the fault from expanding.

[0037] Remote operation and maintenance instructions are operation commands sent by the cloud data system or monitoring platform to the on-site control terminal to trigger specific equipment protection actions or operation and maintenance tasks. Remote operation and maintenance instructions usually include enabling or disabling certain equipment, adjusting the equipment operating status, etc.; the remote operation and maintenance instructions are then transmitted to the on-site control terminal through the cloud system and executed by the control terminal. The control terminal will perform necessary operations on the equipment according to the instructions, such as adjusting equipment settings and starting the backup system. The entire process realizes intelligent monitoring and remote operation and maintenance of power equipment through the close cooperation of simulation space and fault decision-making mechanism.

[0038] Furthermore, the method of this application further includes: synchronously and dynamically simulating the power flow, load distribution, and the mutual influence between power equipment to restore the operating status of the power equipment;

[0039] Through photovoltaic power generation components, electric energy data is collected and an operating status mark is added; the electric energy data with the operating status mark is virtually mapped to the simulation space, and an external mapping node is added; based on the external mapping node, the first internal mapping node corresponding to the transformer mapping unit, the second internal mapping node corresponding to the switch device mapping unit, and the third internal mapping node corresponding to the mutual inductor mapping unit are combined to establish a target power grid model, which includes a power equipment protection connection layer and a power equipment operation and maintenance connection layer.

[0040] Specifically, a photovoltaic power generation component is a device that converts solar energy into electrical energy through the photovoltaic effect. Photovoltaic panels generate current by absorbing sunlight and provide renewable energy to the power system. Each photovoltaic power generation component generates real-time power data, such as voltage, current, power, etc.; operating status marking refers to the real-time recording and identification of the device status, usually by collecting key parameters of the power equipment (such as current, temperature, power, etc.) to judge the health status of the equipment. If the equipment is in normal operation, it is marked as normal. If an abnormality occurs (such as overload, overheating, etc.), it is marked as abnormal or faulty; external mapping node refers to the node used to map and represent data from external devices (such as photovoltaics) in the virtual simulation space. The node for inputting data of photovoltaic power generation components is an interface used to import the electric energy data of photovoltaic power generation components into the simulation space and associate them with the simulation models of other power equipment; the internal mapping node is a node representing power equipment (such as transformers, switchgear, mutual inductors, etc.) in the virtual simulation space. It is an interface connected to external equipment, capable of receiving data from external equipment and performing internal simulation calculations; the target power grid model refers to a power grid model constructed based on the simulation space, which includes various power equipment (such as transformers, switchgear, mutual inductors, etc.) and the connections between power equipment, reflecting the interconnection relationship, power flow, load distribution and other characteristics of power equipment in actual operation.

[0041] Execution steps: PV panels collect real-time power data, including voltage, current, power, and other related parameters. During power generation, PV panels output this data in real time, along with corresponding operating status tags to indicate the device's operating status. Under normal circumstances, the device is marked as normal; if a PV panel experiences a problem (such as a drop in output power), it is marked as abnormal. This PV power data, with its operating status tags, is virtually mapped into the simulation space. During this process, the PV power generation data is transmitted to the virtual simulation space via external mapping nodes and connected to the power equipment models within the simulation space. These external mapping nodes receive real-time data from the PV panels and transmit it to the corresponding device nodes in the simulation space. At this point, the PV data becomes part of the simulation space and can be integrated with other device states for simulation and analysis.

[0042] The simulation system will associate photovoltaic power generation components with other power equipment based on external mapping nodes. The specific operation is to combine the external nodes with the internal mapping nodes of devices such as transformer mapping units, switchgear mapping units, and mutual inductor mapping units. For example, the data of photovoltaic power generation components are connected with the internal mapping nodes of transformers through external mapping nodes to form a complete power grid model; in the target power grid model, the working status, current, voltage, etc. of the transformer are associated with the electric energy data of photovoltaic power generation, which can simultaneously reflect the working status of the equipment and the power flow.

[0043] By connecting these internal mapping nodes, the system establishes a complete target power grid model, which includes all power equipment (such as transformers, switchgear, and mutual inductors) and the connections between their protection and operation and maintenance layers. The power equipment protection connection layer is the layer where the power equipment protection mechanism resides. It is responsible for protecting power equipment from damage due to faults or abnormal conditions. It monitors the equipment's operating status in real time and outputs power equipment protection strategies when an abnormality occurs. The power equipment operation and maintenance connection layer is the operation and maintenance management layer that connects power equipment and is responsible for handling equipment operation, maintenance, and repair. It monitors the equipment's operating status in real time and outputs power equipment operation and maintenance strategies when an abnormality occurs. In the above steps, a target power grid model including the power equipment protection layer and the power equipment operation and maintenance layer is established. The simulation system can dynamically simulate power flow, load distribution, and the interactions between power equipment, thereby accurately reproducing the operating status of power equipment. It also analyzes the operating status of the entire power grid through a virtual simulation space, thereby improving the intelligent management level of the power system and ensuring stable operation of the power grid and timely response to faults.

[0044] Furthermore, to establish a target power grid model, the method of the present application further includes:

[0045] Introduce external influencing factors, wherein the external influencing factors include light intensity fluctuations; obtain a first operating control parameter corresponding to the photovoltaic inverter and a second operating control parameter corresponding to the energy storage unit; based on the external influencing factors and in combination with the first operating control parameter and the second operating control parameter, set a grid stability impact set, wherein the grid stability impact set is used to drive the update of the target grid model.

[0046] Specifically, external influencing factors refer to external environmental factors that affect the stability and operating status of the power grid, including natural factors such as fluctuations in light intensity. Changes in light intensity directly affect the output power of photovoltaic power generation, and thus affect the power balance and stability of the power grid; photovoltaic inverters are important equipment that convert the direct current generated by photovoltaic power generation systems into alternating current. Their operating control parameters include output power, frequency, voltage, etc. By monitoring these control parameters, the operating status of the inverter can be adjusted to ensure adaptability and stability with the power grid; energy storage units (such as battery energy storage systems) are used to store excess electricity generated by photovoltaic power generation so that it can be released when photovoltaic power generation is insufficient. The operating control parameters of energy storage units usually include battery charging and discharging power, capacity, voltage, etc.

[0047] Execution steps: Introduce external influencing factors, including light intensity fluctuations. Light intensity fluctuations are an important influencing factor of photovoltaic power generation systems because the intensity of light directly determines the power generation of photovoltaic modules. For example, on sunny days, the power of photovoltaic power generation is higher, while on cloudy days or when covered by clouds, the power generation power will drop significantly. To accurately simulate this change, the system will include light intensity fluctuations as external input factors in the simulation process of the target power grid model.

[0048] Obtain the operating control parameters of the photovoltaic inverter and the energy storage unit. The control parameters of the photovoltaic inverter usually include output power, voltage, frequency, etc. These parameters will automatically adjust according to changes in light intensity. For example, when the light intensity is low, the photovoltaic inverter will reduce the output power to avoid excessive output voltage affecting the power grid; the control parameters of the energy storage unit include the battery's charging and discharging power, voltage, and remaining power, etc. Changes in these control parameters are key factors in updating the power grid model, especially when photovoltaic power generation is insufficient, the energy storage unit will provide necessary power support.

[0049] Based on these external influencing factors and the operating control parameters of photovoltaic inverters and energy storage units, a grid stability impact set is established. The grid stability impact set is a data set used to describe the impact of external factors (such as light fluctuations) on grid stability. This data can be used as input parameters to influence the adjustment and update of the grid model, thereby helping to assess the stability of the grid in different scenarios. The grid stability impact set is used to reflect the impact of factors such as light intensity fluctuations and energy storage unit status on grid stability. For example, if light intensity suddenly drops, photovoltaic power generation will drop significantly, and the grid may face a power gap. In this case, the energy storage unit may need to release electricity to make up for the shortfall. The grid stability impact set records the combined effects of factors such as light changes and energy storage charging and discharging, providing the necessary parameter support for updating the grid model.

[0050] Based on the aforementioned grid stability impact set, the target grid model is updated. This refers to real-time adjustments and updates to the model's calculations to reflect the new grid state, based on changes in the current grid state, external factors, and equipment operating parameters. Updating the target grid model helps simulate grid performance under different operating conditions and predict potential failures or instability. Furthermore, the grid model is adjusted based on real-time external data (such as light intensity and battery charge and discharge status) and operational control parameters. For example, if light intensity fluctuates significantly, the target grid model will update key indicators such as power flow and load distribution by simulating changes in photovoltaic power generation and the response of energy storage units, thereby reflecting the latest grid operating status. Through these steps, the grid's operating status is captured in real time, and the grid model can be rapidly adjusted in the face of changes in external factors, ensuring grid stability and security.

[0051] Furthermore, the grid stability impact set is used to drive the update of the target grid model. The method of the present application includes:

[0052] A first update sub-cycle is set according to the external influencing factors; a second update sub-cycle is set according to the first operation control parameter and the second operation control parameter; and the first update sub-cycle and the second update sub-cycle are merged according to the grid voltage fluctuation and the grid frequency fluctuation to obtain the preset update cycle of the target grid model.

[0053] Specifically, the first update sub-cycle refers to the time period during which the grid model is updated based on external influencing factors (such as light intensity and temperature). During this period, the system will make preliminary adjustments to the grid model to adapt to changes in environmental factors. For example, if light intensity fluctuates significantly, the system will update the operating status of photovoltaic power generation and energy storage units within this sub-cycle to ensure grid stability. The second update sub-cycle is the time period during which the grid model is updated based on the operating control parameters of grid equipment (such as photovoltaic inverters and energy storage units). During this second update sub-cycle, the system will further adjust the grid model based on the actual operating conditions of the equipment (such as battery charge and discharge status, voltage and frequency changes), optimize power flow and load distribution, and ensure the continuous and stable operation of the grid. The preset update cycle is the model update cycle set after combining the first and second update sub-cycles based on key indicators such as grid voltage and frequency fluctuations. The preset update cycle is used to guide the update frequency of the grid model in different time periods to ensure that the grid is always in the optimal operating state. Generally, when grid stability requirements are high, the update cycle is short; when the grid operation is relatively stable, the update cycle is long.

[0054] Execution steps: By introducing external influencing factors (such as light intensity fluctuations, temperature changes, etc.), the system will set the first update sub-cycle. The goal of the first update sub-cycle is to make preliminary adjustments to the power grid model based on environmental factors to ensure that the power grid can adapt to fluctuations in the external environment. For example, changes in light intensity directly affect the output power of the photovoltaic power generation system. If the light intensity changes sharply in a short period of time, the power output of photovoltaic power generation will change accordingly. The system needs to quickly adjust the power grid model within the first update sub-cycle to compensate for the power gap caused by fluctuations in photovoltaic power generation and maintain the stability of the power grid.

[0055] The second update sub-cycle is set using the first and second operating control parameters (such as the output power of the photovoltaic inverter and the charging and discharging status of the energy storage unit). During the second update sub-cycle, the grid model is adjusted based on the operating control parameters of the equipment. For example, the energy storage unit automatically adjusts the charging and discharging power based on changes in photovoltaic power generation to compensate for fluctuations in photovoltaic power generation, while the photovoltaic inverter also adjusts its output power based on real-time voltage and current changes to ensure that the output power matches grid demand. At this time, the update of the second update sub-cycle focuses on device-level optimization to improve grid stability and power supply reliability.

[0056] Based on the voltage fluctuation and frequency fluctuation of the power grid, the first update sub-cycle and the second update sub-cycle are merged to obtain the preset update cycle of the power grid model. The voltage fluctuation and frequency fluctuation of the power grid are key indicators of power grid stability. By monitoring these two indicators, the system can determine whether the operating status of the power grid is within the normal range. Furthermore, when the voltage and frequency fluctuations of the power grid exceed the predetermined range, the system will adjust the merging strategy of the first update sub-cycle and the second update sub-cycle to obtain the preset update cycle. For example, if the power grid frequency fluctuates greatly, it means that the power grid load is unbalanced. The system will shorten the update cycle and perform more frequent model updates to ensure that the power grid can adjust the operating parameters in time, so that the power grid can recover stability in a short time; when the power grid is relatively stable, the system can extend the update cycle and reduce the frequency of model updates to improve computing efficiency.

[0057] For example, in a photovoltaic power generation system, as the light intensity changes, the power of photovoltaic power generation may drop rapidly at certain moments, resulting in insufficient power supply. During the first update sub-cycle, the system quickly adjusts the output power of the photovoltaic inverter based on the change in light intensity, and at the same time starts the discharge mode of the energy storage unit to make up for the power gap. During this process, the energy storage unit will charge and discharge according to the remaining battery power and the grid load to stabilize the grid output power. At the same time, based on the second operating control parameter, the system will further optimize the power flow according to the actual operating status of the photovoltaic inverter and the energy storage unit to ensure power balance. Through these steps, the system can flexibly adjust the update cycle of the power grid model according to external factors and the operating status of the equipment, thereby achieving efficient and stable operation of the power grid.

[0058] Furthermore, to obtain a preset update period of the target power grid model, the method of the present application further includes:

[0059] Based on the preset update cycle, the power grid stability index is re-evaluated after each iterative update; at the same time, during the iterative update process, the power equipment protection strategy and the power equipment operation and maintenance strategy are iteratively optimized with the power grid stability index as a constraint condition.

[0060] Specifically, the grid stability index is a comprehensive indicator used to evaluate the stability and reliability of the power grid. It is usually based on the comprehensive calculation of parameters such as the grid's voltage, frequency fluctuations, load distribution, and equipment operating status. Generally speaking, the higher the grid stability index, the better the stability of the grid. Conversely, it indicates that the grid faces the risk of instability. The grid stability index is used as a constraint in the iterative optimization process to ensure that the grid will not be in an unstable state when adjusting the equipment protection strategy and operation and maintenance strategy; the power equipment protection strategy refers to a series of protection measures taken when the power equipment is in an abnormal state in order to avoid the expansion of the fault and cause greater impact on the power grid system, including adjusting load distribution, activating backup equipment, etc.; the power equipment operation and maintenance strategy refers to the strategy of regular monitoring, maintenance, and optimization of power equipment.

[0061] Execution steps: After obtaining the preset update cycle, the iterative update phase of the power grid model begins. The preset update cycle has been set based on external influencing factors and equipment operating parameters. For example, the update frequency is determined based on factors such as light intensity, temperature changes, and load fluctuations. Each iterative update means that the power grid model undergoes an adjustment during this period. The purpose is to ensure that the power grid can adapt to new external and internal conditions. Through this periodic update, the power grid model can timely reflect the actual operating status of the power grid.

[0062] After each iterative update, the grid stability index will be re-evaluated. The calculation basis of the grid stability index includes factors such as voltage fluctuations, frequency fluctuations, and load changes. For example, assuming that the load on a certain part of the grid suddenly increases, the system will automatically update the grid model and derive a new stability index by calculating the impact of these new changes on grid stability. If the voltage fluctuations intensify or the frequency fluctuations exceed the set range during this update process, the stability index will decrease, indicating that there is a potential risk to the stability of the grid and triggering the fault decision mechanism.

[0063] However, under normal circumstances, the grid stability index should tend to increase. This is because optimization and adjustments are made based on the feedback information from each iteration. For example, when the system finds that a substation is overloaded, it will adjust the load distribution in that area, enable backup power supplies, or adjust equipment operating parameters to improve grid stability. In this process, the protection and operation and maintenance strategies of power equipment will be dynamically optimized based on changes in the grid stability index. The goal is to maintain the grid stability index at a high level to prevent overloads, equipment damage, or large-scale power outages.

[0064] During this iterative update process, the power equipment protection strategy and operation and maintenance strategy are adjusted as the grid stability index fluctuates. If the grid stability index is found to have decreased during a certain iteration, the system will promptly adjust the protection strategy based on the specific operating status of the power equipment (such as equipment temperature being too high or current being too large). Specific measures include adjusting equipment load, enabling backup equipment, and limiting the workload of certain equipment. These protection strategies help alleviate the pressure on the grid load and prevent more serious grid failures.

[0065] At the same time, the operation and maintenance strategies for power equipment will also be optimized simultaneously. For example, if a part of the power grid experiences voltage fluctuations due to excessive load, the system can arrange for inspection and repair of the equipment in that area, or replace equipment parts as needed. These adjustments to the operation and maintenance strategies are also based on changes in the grid stability index to ensure the long-term stable operation of the equipment.

[0066] Through a dynamic optimization process based on the Grid Stability Index, each iterative update not only reassesses the grid's stability but also adjusts the protection and maintenance strategies for power equipment based on the evaluation results, achieving continuous optimization of both power equipment and the grid. Through optimization at each update cycle, the system ensures the grid operates in a stable state, while also maximizing its efficiency and security.

[0067] Furthermore, based on the preset update cycle, after each iterative update, the grid stability index is re-evaluated. The method of the present application includes:

[0068] Grid voltage fluctuation calculation formula: ,in, Used to characterize grid voltage fluctuations, is the voltage at the i-th measurement point, is the average value of the voltage, is the total number of voltage measurement points; the grid frequency fluctuation calculation formula is: ,in, Used to characterize grid frequency fluctuations, is the frequency of the ith measurement point, is the average value of the frequencies, is the total number of frequency measurement points; grid stability index ,in, and is a weight coefficient used to balance the impact of voltage fluctuations and frequency fluctuations on grid stability.

[0069] Specifically, the grid voltage fluctuation calculation formula is used to calculate the degree of voltage fluctuation at each measuring point in the grid. Usually, the grid voltage fluctuation will change with factors such as load changes and power generation fluctuations. The difference between the voltage at each measuring point and the average voltage reflects the voltage fluctuation of the grid at that location; the grid frequency fluctuation calculation formula is used to calculate the degree of frequency fluctuation at each measuring point in the grid. The frequency fluctuation of the grid is usually affected by power generation and load imbalance. Similar to voltage fluctuation, it is based on the difference between the actual frequency and the average frequency of the frequency measurement point.

[0070] Execution steps: After each update cycle, the operating status of the power grid will change to a certain extent, especially the fluctuations of voltage and frequency. These fluctuations will directly affect the stability of the power grid. Therefore, these fluctuations need to be accurately calculated and comprehensively evaluated. Specifically, the calculation formula for power grid voltage fluctuation is established: At each measuring point in the power grid, the system collects voltage data and compares the voltage at each measuring point with the average voltage to establish a formula for calculating the power grid frequency fluctuation: ,At each measuring point in the power grid, the system collects frequency data, and compares the frequency of each ,measuring point with the average frequency.

[0071] Then, substitute into the grid stability index calculation formula: ,in, and It is a weight coefficient between 0 and 1, which is used to adjust the importance of voltage fluctuation and frequency fluctuation in the grid stability evaluation. The grid stability index is obtained by weighted calculation of voltage fluctuation and frequency fluctuation. The grid stability index characterizes the overall stability of the power grid during the update cycle. A calculation formula for the grid stability index is established. During the iterative optimization of the power equipment protection strategy and the power equipment operation and maintenance strategy, the grid stability index is calculated simultaneously, thereby effectively reducing the operational risks of the power grid and ensuring the long-term stable operation of the power system.

[0072] In summary, the beneficial effects of the embodiments of the present application are:

[0073] 1. Accurately restore the operating status of power equipment through virtual mapping and real-time monitoring, achieve remote real-time monitoring and rapid diagnosis, and improve the accuracy and response speed of equipment operation and maintenance.

[0074] 2. Under virtual mapping, by simulating power flow, load distribution and other grid operating conditions in real time, dynamic adjustment and optimization of power system stability can be achieved, ensuring grid stability under various loads and conditions.

[0075] 3. Based on the fault decision-making mechanism, it can respond to potential faults in a timely manner and initiate fault protection strategies, thereby minimizing the impact of faults on the power system.

[0076] 4. Through virtual mapping and simulation of power equipment, the self-regulation capability of the power system can be further enhanced, the grid dispatch strategy can be adjusted in real time, and the system's response to power fluctuations and load changes can be improved.

[0077] 5. Due to the adoption of the grid voltage fluctuation calculation formula: ,in, Used to characterize grid voltage fluctuations, is the voltage at the i-th measurement point, is the average value of the voltage, is the total number of voltage measurement points; the grid frequency fluctuation calculation formula is: ,in, Used to characterize grid frequency fluctuations, is the frequency of the ith measurement point, is the average value of the frequencies, is the total number of frequency measurement points; grid stability index ,in, and is a weighting factor used to balance the impact of voltage and frequency fluctuations on grid stability. A formula for calculating the grid stability index is established. This is calculated simultaneously during the iterative optimization of power equipment protection and operation and maintenance strategies, effectively reducing grid operational risks and ensuring the long-term stable operation of the power system.

[0078] In summary, any step can be stored as a computer instruction or program in an unlimited computer memory and can be called and recognized by an unlimited computer processor, without any unnecessary restrictions.

[0079] Furthermore, the above technical solution only reflects the preferred technical solution of the technical solution of the embodiment of the present application. Some changes that may be made to certain parts thereof by technical personnel in this technical field all reflect the novel principles of the embodiment of the present application. Obviously, technical personnel in this field can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. A remote operation and maintenance method for power equipment under virtual mapping, characterized in that: The method comprises: Monitor power equipment, collect real-time operating parameters, and upload them to the cloud data center in real time; In the cloud data center, a simulation space under virtual mapping is set in combination with a target power grid topology; Based on the simulation space under the virtual mapping, the power flow, load distribution and the mutual influence between the power equipment are simulated synchronously and dynamically to restore the operating status of the power equipment; At the same time, a fault decision mechanism is introduced to virtually map the faults to the power equipment protection connection layer and the power equipment operation and maintenance connection layer according to the power equipment operation status and abnormal status. Connecting the power equipment protection connection layer and the power equipment operation and maintenance connection layer, outputting a power equipment protection strategy and a power equipment operation and maintenance strategy, wherein the power equipment protection strategy is used to minimize the impact of abnormal states of power equipment on the stable operation of the power grid; Based on the cloud data center, remotely sending the power equipment protection strategy and the power equipment operation and maintenance strategy to the control terminal; The method of introducing a fault decision-making mechanism includes: Set up a fault decision-making mechanism based on the fault case library; According to the fault decision mechanism, whether the power equipment is in a potential fault state is determined by the abnormal state response, wherein the abnormal state response includes temperature abnormality and load abnormality; When the power equipment is in a potential fault state, sending a remote operation and maintenance instruction, wherein the remote operation and maintenance instruction is used to activate the control terminal; The simulation space includes a transformer mapping unit, a switchgear mapping unit, and a mutual inductor mapping unit; Prioritizing the potential fault states to obtain a fault decision sequence; Connecting the transformer mapping unit, the switchgear mapping unit, and the mutual inductor mapping unit in the simulation space, classifying the potential fault states, and adding fault type labels; The remote operation and maintenance instruction is generated based on the fault decision sequence and the fault type label.

2. The remote operation and maintenance method of power equipment under virtual mapping according to claim 1, characterized in that: Synchronously and dynamically simulating the power flow, load distribution, and the mutual influence between power equipment to restore the operating state of the power equipment, the method further includes: Collect power data through photovoltaic power generation components and add operating status tags; Virtually map the electric energy data with running status marks to the simulation space and add external mapping nodes; Based on the external mapping node, the first internal mapping node corresponding to the combined transformer mapping unit, the second internal mapping node corresponding to the switch device mapping unit, and the third internal mapping node corresponding to the mutual inductor mapping unit are used to establish a target power grid model, which includes a power equipment protection connection layer and a power equipment operation and maintenance connection layer.

3. The remote operation and maintenance method of power equipment under virtual mapping according to claim 2, characterized in that: Establishing a target power grid model, the method further includes: Introducing external influencing factors, wherein the external influencing factors include light intensity fluctuations; Obtaining a first operating control parameter corresponding to the photovoltaic inverter and a second operating control parameter corresponding to the energy storage unit; Based on the external influencing factors and in combination with the first operation control parameter and the second operation control parameter, a power grid stability impact set is set, and the power grid stability impact set is used to drive the update of the target power grid model.

4. The remote operation and maintenance method of power equipment under virtual mapping according to claim 3, characterized in that: The grid stability impact set is used to drive the update of the target grid model. The method includes: Setting a first update sub-period according to the external influencing factors; Setting a second update sub-period according to the first operation control parameter and the second operation control parameter; The first update sub-period and the second update sub-period are combined according to grid voltage fluctuations and grid frequency fluctuations to obtain a preset update period of the target grid model.

5. The remote operation and maintenance method of power equipment under virtual mapping according to claim 4, characterized in that: Obtaining a preset update period of the target power grid model, the method further includes: Based on the preset update cycle, after each iterative update, re-evaluate the grid stability index; At the same time, in the iterative updating process, the power equipment protection strategy and the power equipment operation and maintenance strategy are iteratively optimized with the power grid stability index as a constraint condition.

6. The remote operation and maintenance method of power equipment under virtual mapping according to claim 5, characterized in that: Based on the preset update cycle, after each iterative update, re-evaluating the grid stability index, the method includes: Grid voltage fluctuation calculation formula: ,in, Used to characterize grid voltage fluctuations, is the voltage at the i-th measurement point, is the average value of the voltage, is the total number of voltage measurement points; Grid frequency fluctuation calculation formula: ,in, Used to characterize grid frequency fluctuations, It is The frequency of the measurement points, is the average value of the frequencies, is the total number of frequency measurement points; grid stability index ,in, and is a weight coefficient used to balance the impact of voltage fluctuations and frequency fluctuations on grid stability.

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