Operation and maintenance management method and system for intelligent power station

Abstract

The invention relates to the technical field of power station operation and maintenance, in particular to an operation and maintenance management method and system for an intelligent power station, and the method comprises the steps: constructing a three-dimensional virtual model, collecting multi-source data in real time in combination with Internet of Things equipment, feeding back the data to the three-dimensional virtual model, integrating the multi-source data collected in real time, and carrying out the diagnosis and early warning of equipment faults. Parameters of the three-dimensional virtual model are updated according to conversion of the environment and the operation stage, the three-dimensional virtual model collects data by means of laser scanning and unmanned aerial vehicle aerial photography technologies, collection is more convenient, and the collection is closer to the actual situation on site; in combination with Internet of Things equipment, multi-source data are collected in real time, and the sensing network is more comprehensive; timely diagnosis and early warning can be carried out when faults occur and hidden dangers are found, so that the reliability and the safety of equipment are improved; the three-dimensional virtual model is updated in time by means of real-time sensing network data, the timeliness and accuracy of fault judgment are improved, and safe and stable operation of the power station is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of power station operation and maintenance, and particularly designs an operation and maintenance management method and system for a smart power station. Background Art

[0002] The operation and maintenance management of traditional substations is achieved through manual inspections. Maintenance personnel regularly conduct on-site inspections of substations, check the equipment status, and record data. This traditional manual inspection method often fails to monitor the operating status of power transformers in real time. Once a fault occurs, it may take until the next inspection to be discovered, resulting in an extended fault handling time. In addition, there are certain limitations in the accuracy of fault diagnosis using traditional methods. Often, only the surface symptoms of faults can be detected, and it is difficult to accurately diagnose some early-stage and highly concealed faults. Summary of the Invention

[0003] The technical problem to be solved by the present invention is: In order to overcome the deficiencies of the manual inspection operation and maintenance management of traditional substations, the present invention provides an operation and maintenance management method and system for a smart power station.

[0004] A substation is a key component in the power system, and its main function is to transmit electrical energy from the power generation station to the user side. The substation uses transformers to increase or decrease the voltage of electrical energy to adapt to long-distance transmission or meet the needs of different users. Power transformers play a crucial role in substations, being used to regulate voltage, transmit electrical energy, and ensure the stable operation of the power grid.

[0005] A smart power station refers to the intelligent transformation and upgrade of traditional substations using advanced information technologies such as the Internet of Things, big data, artificial intelligence, and cloud computing, to achieve the full digitization, automation, and intelligence of substation operation, maintenance, management, and decision-making. Its core goal is to improve the safety, reliability, economy, and environmental friendliness of the power station through data-driven and intelligent algorithms. A smart power station involves a large amount of equipment monitoring, data analysis, fault prediction, and resource optimization, collecting the operation data of the power station through various sensors and intelligent devices.

[0006] The technical solution adopted by the present invention to solve its technical problem is: An operation and maintenance management method for a smart power station, comprising the following steps:

[0007] Step 1: Collect three-dimensional data of the power station site through laser scanning and drone aerial photography technologies, and construct a three-dimensional virtual model of the power station site using digital twin technology for the collected data;

[0008] Step 2: Combine Internet of Things devices to collect multi-source data in real time and feedback the data into the three-dimensional virtual model, where the multi-source data includes environmental parameters and equipment operating status;

[0009] Step 3: Integrate the multi-source data collected in real time in Step 2 to diagnose and give early warnings of equipment failures;

[0010] Step 4: Update the parameters of the 3D virtual model according to the conversion of the environment and the operation stage, and establish a multi-time scale update mechanism, including real-time update, periodic update, and global update. When the equipment state changes suddenly, local parameters are used for real-time update; the period can be set to every 15 - 20 minutes, and periodic update is performed according to equipment-level parameters; when the environment changes significantly, global update is performed according to the parameters of the entire station.

[0011] In Step 4, compare and calculate the data monitored in Step 2 with the output data of the model operation, construct the distance objective function between the two using the particle swarm algorithm, and seek the optimal parameters to update the 3D virtual model.

[0012] In Step 1, first construct an equipment model according to the actual situation of the power equipment at the power station site, add equipment attributes according to the operation and maintenance requirements to realize the reconstruction of the electrical equipment model; then encode each module to realize the lightweight design of the data; finally, integrate the functional modeling to realize the construction of the entire 3D model.

[0013] Each location and electrical equipment in the power station plant area are mapped into the 3D virtual space.

[0014] In Step 3, collect the infrared thermal images on the surface of the electrical equipment, perform image enhancement and segmentation processing on the images, and then use the infrared thermal image analysis method to monitor the equipment failure location.

[0015] In Step 3, through the time series relationship and spatial distribution characteristics of the thermal images, combined with the operation monitoring sensor data of the electrical equipment, grid the equipment, monitor the temperature change trend of each grid, and judge potential hazards.

[0016] An operation and maintenance management system for a smart power station, including a data acquisition unit and an operation and maintenance management unit. The data acquisition unit includes Internet of Things devices, and the Internet of Things devices include multiple sensing networks, and the sensing networks are environmental perception networks, equipment perception networks, infrared video monitoring networks, or mobile monitoring devices; the multi-source data is collected in real time by the data acquisition unit and digitally processed on the real-time data and then sent to the operation and maintenance management unit, and the multi-source data includes environmental parameters and equipment operation status; the operation and maintenance management unit includes a database and a twin system. The 3D virtual model of the twin system is based on the 3D data modeling of the power station site, and the 3D virtual model is updated according to the conversion of the environment and the operation stage, and a multi-time scale update mechanism is established, including real-time update, periodic update, and global update. When the equipment state changes suddenly, local parameters are used for real-time update; the period can be set to every 15 - 20 minutes, and periodic update is performed according to equipment-level parameters; when the environment changes significantly, global update is performed according to the parameters of the entire station.

[0017] The electrical equipment at the power station site includes primary power transformation equipment and secondary auxiliary equipment. The primary power transformation equipment includes transformers, circuit breakers, cable joints, isolating switches, and compensating capacitors.

[0018] The infrared video monitoring network includes infrared thermal image probes to collect infrared thermal images of the surface of electrical equipment.

[0019] The three-dimensional virtual model is updated according to the conversion of the environment and operation stage. The data monitored by the data acquisition unit is compared and calculated with the output data of the model operation. The particle swarm optimization algorithm is used to construct the distance objective function between the two, and the optimal parameters are sought to update the three-dimensional virtual model.

[0020] The beneficial effects of the present invention are as follows. A method and system for operation and maintenance management of a smart power station according to the present invention. The three-dimensional virtual model collects data by means of laser scanning and unmanned aerial vehicle aerial photography technology, which is more convenient to collect and closer to the actual situation on site; combined with Internet of Things devices, multi-source data is collected in real time, and the sensing network is more comprehensive; it can diagnose and give early warnings in time when a fault occurs and potential hazards are found, improving the reliability and safety of the equipment; the three-dimensional virtual model is updated in time by means of real-time perception network data, improving the timeliness and accuracy of fault judgment and ensuring the safe and stable operation of the power station. Description of the Drawings

[0021] The present invention will be further described below in conjunction with the drawings and embodiments.

[0022] Figure 1 It is a schematic diagram of the operation and maintenance process of the operation and maintenance management method for a smart power station according to the present invention. Detailed Embodiments

[0023] The present invention will now be described in further detail with reference to the drawings. These drawings are all simplified schematic diagrams, only illustrating the basic structure of the present invention in a schematic manner, and therefore only showing the components related to the present invention.

[0024] A method for operation and maintenance management of a smart power station includes the following steps:

[0025] Step 1: Collect three-dimensional data of the power station site through laser scanning and unmanned aerial vehicle aerial photography technology, and construct a three-dimensional virtual model of the power station site through digital twin technology;

[0026] Step 2: Combine Internet of Things devices to collect multi-source data in real time and feed the data back into the three-dimensional virtual model. The multi-source data includes environmental parameters and equipment operation status, and the equipment operation status includes power generation;

[0027] Step 3: Integrate the multi-source data collected in real time in Step 2 to diagnose and give early warnings of equipment failures;

[0028] Step 4: Update the parameters of the 3D virtual model according to the conversion of the environment and the operation stage, and establish a multi-time scale update mechanism, including real-time update, periodic update, and global update. When the device status changes suddenly, local parameters are used for real-time update; the period can be set to every 15 - 20 minutes, and periodic update is performed according to the device-level parameters, where the period can be dynamically adjusted according to the device status; when the environment changes significantly, global update is performed according to the whole-station parameters, and the significant environmental change can be set according to the actual situation.

[0029] In Step 4, the data monitored in Step 2 is compared and calculated with the model operation output data, and the particle swarm algorithm is used to construct the distance objective function between the two, and the optimal parameters are sought to update the 3D virtual model. The specific implementation example is as follows:

[0030] s1: Determine the parameters

[0031] Objective: Adjust the model parameters to make the distance between specific point pairs close to the target value.

[0032] Optimize the parameters, objective function: Calculate the sum of the squared differences between the transformed points and the target points.

[0033] s2: Construct the objective function

[0034] Assume there are multiple point pairs in the model, and the objective function is: where T(θ) is the transformation (rotation + translation) corresponding to the parameter θ, P i and Q i are the point pairs, and d i is the target distance.

[0035] For multi-modal data fusion optimization, a multi-source data weight factor is added to the objective function: f(θ) = ∑ω_i * (||T(θ)Pi - Qi|| - di) 2 + ∑λ_j * (S_model_j - S_real_j) 2

[0036] where ω_i is the weight of the 3D point pair, λ_j is the weight of the device status parameters (temperature, vibration, etc.), and S is the device status parameter.

[0037] s3: Configure the particle swarm algorithm parameters

[0038] s4: Initialize the particle swarm

[0039] Each particle is randomly initialized within the parameter range

[0040] s5: Iterative optimization process

[0041] Evaluate the particles: Calculate the distance of the transformed points using the current parameters and evaluate the objective function.

[0042] Update the individual and the global optimum.

[0043] Update the speed and position constraint handling: Ensure that the parameters do not exceed the boundaries and truncate if necessary.

[0044] s6: Apply the optimal parameters

[0045] After the iteration ends, update the 3D model using the global optimal parameters.

[0046] In step 1, first, construct the equipment model according to the actual situation of the power equipment at the power station site, add equipment attributes according to the operation and maintenance requirements, and realize the reconstruction of the electrical equipment model; then encode each module to realize the lightweight design of the data; finally, integrate the functional modeling to realize the construction of the entire 3D model. Each location and electrical equipment in the power station plant area are mapped into the 3D virtual space.

[0047] In step 3, collect the infrared thermal images on the surface of the electrical equipment, perform image enhancement and segmentation processing on the images, and then use the infrared thermal image analysis method to monitor the equipment failure location. In step 3, through the temporal relationship and spatial distribution characteristics of the thermal images, combined with the operation monitoring sensor data of the electrical equipment, grid the equipment and monitor the temperature change trend of each grid to judge potential hazards.

[0048] An operation and maintenance management system for a smart power station, including a data acquisition unit and an operation and maintenance management unit. The data acquisition unit includes Internet of Things devices, and the Internet of Things devices include multiple sensing networks. The sensing networks are environmental perception networks, equipment perception networks, infrared video monitoring networks or mobile monitoring devices; the data acquisition unit collects multi-source data in real time, performs digital processing on the real-time data, and then sends it to the operation and maintenance management unit. The multi-source data includes environmental parameters and equipment operation status, and the equipment operation status includes power generation; the operation and maintenance management unit includes a database and a twin system. The 3D virtual model of the twin system is built based on the 3D data of the power station site, and the 3D virtual model is updated according to the conversion of the environment and the operation stage, and a multi-time scale update mechanism is established, including real-time update, periodic update and global update. When the equipment status changes suddenly, local parameters are used for real-time update; the period can be set to every 15 - 20 minutes, and periodic update is performed according to the equipment-level parameters; when the environment changes significantly, global update is performed according to the whole-station parameters.

[0049] The electrical equipment at the power station site includes primary substation equipment and secondary auxiliary equipment. The primary substation equipment includes transformers, circuit breakers, cable joints, isolating switches and shunt capacitors.

[0050] The infrared video monitoring network includes infrared thermal image probes to collect infrared thermal images on the surface of the electrical equipment.

[0051] The three-dimensional virtual model is updated according to the conversion of the environment and the operation stage. The data monitored by the data acquisition unit is compared and calculated with the output data of the model operation. The particle swarm algorithm is used to construct the distance objective function between the two, and the optimal parameters are sought to update the three-dimensional virtual model. The specific embodiments are as follows:

[0052] S1: Determine the parameters

[0053] Objective: Adjust the model parameters so that the distance between specific point pairs is close to the target value.

[0054] Optimize the parameters, objective function: Calculate the sum of the squared differences between the transformed points and the target points.

[0055] S2: Construct the objective function

[0056] Assume there are multiple point pairs in the model, and the objective function is: where T(θ) is the transformation (rotation + translation) corresponding to the parameter θ, P i and Q i are the point pairs, and d i is the target distance.

[0057] For multi-modal data fusion optimization, a multi-source data weight factor is added to the objective function: f(θ) = ∑ω_i * (||T(θ)Pi - Qi|| - di) 2 + ∑λ_j * (S_model_j - S_real_j) 2

[0058] where ω_i is the weight of the three-dimensional point pair, λj is the weight of the device state parameters (temperature, vibration, etc.), and S is the device state parameter.

[0059] S3: Configure the particle swarm algorithm parameters

[0060] S4: Initialize the particle swarm

[0061] Each particle is randomly initialized within the parameter range

[0062] S5: Iterative optimization process

[0063] Evaluate the particles: Calculate the distance of the transformed points using the current parameters and evaluate the objective function.

[0064] Update the individual and global optima.

[0065] Update the velocity and position constraint handling: Ensure that the parameters do not exceed the bounds and truncate if necessary.

[0066] S6: Apply the optimal parameters

[0067] After the iteration ends, update the three-dimensional model using the global optimal parameters.

[0068] Based on the above enlightenment from the ideal embodiments of the present invention, through the above description, relevant staff can completely make various changes and modifications without departing from the technical idea of this invention. The technical scope of this invention is not limited to the content in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. An operation and maintenance management method for a smart power station, characterized in that, It includes the following steps: Step 1: Collect 3D data of the power station site through laser scanning and UAV aerial photography technologies, and construct a 3D virtual model of the power station site with the collected data through digital twin technology; Step 2: Combine IoT devices to collect multi-source data in real time and feed the data back into the 3D virtual model. The multi-source data includes environmental parameters and equipment operation status; Step 3: Integrate the multi-source data collected in real time in Step 2 to diagnose and warn of equipment failures; Step 4: Update the parameters of the 3D virtual model according to the conversion of the environment and operation stage, and establish a multi-time scale update mechanism, including real-time update, periodic update and global update.

2. The operation and maintenance management method for an intelligent power station according to claim 1, wherein, In Step 4, compare and calculate the data monitored in Step 2 with the model operation output data, construct a distance objective function for the two using the particle swarm algorithm, and seek the optimal parameters to update the 3D virtual model.

3. The operation and maintenance management method for an intelligent power station according to claim 1, wherein, In Step 1, first construct an equipment model according to the actual situation of the power station site electrical equipment, add equipment attributes according to the operation and maintenance requirements to realize the reconstruction of the electrical equipment model; then encode each module to realize the lightweight design of the data; finally integrate the functional modeling to realize the construction of the entire 3D model.

4. The operation and maintenance management method for an intelligent power station according to claim 1, characterized in that, Each location and electrical equipment in the power station plant area are mapped into the 3D virtual space.

5. The operation and maintenance management method for an intelligent power station according to claim 1, characterized in that In Step 3, collect the infrared thermal images on the surface of the electrical equipment, perform image enhancement and segmentation processing on the images, and then use the infrared thermal image analysis method to monitor the equipment failure location.

6. The operation and maintenance management method for an intelligent power station according to claim 1, characterized in that, In Step 3, through the time series relationship and spatial distribution characteristics of the thermal images, combine with the operation monitoring sensor data of the electrical equipment, grid the equipment, monitor the temperature change trend of each grid, and judge potential hazards.

7. An operation and maintenance management system for a smart power station, characterized in that It includes a data collection unit and an operation and maintenance management unit. The data collection unit includes IoT devices. The IoT devices include multiple sensing networks. The sensing networks are environmental perception networks, equipment perception networks, infrared video monitoring networks or mobile monitoring devices; the multi-source data including environmental parameters and equipment operation status is collected in real time by the data collection unit and digitally processed on the real-time data and then sent to the operation and maintenance management unit. The operation and maintenance management unit includes a database and a twin system. The 3D virtual model of the twin system is modeled based on the 3D data of the power station site, and the 3D virtual model is updated according to the conversion of the environment and operation stage, and a multi-time scale update mechanism is established, including real-time update, periodic update and global update.

8. The operation and maintenance management system for a smart power station according to claim 7, wherein, The electrical equipment at the power station site includes primary substation equipment and secondary auxiliary equipment. The primary substation equipment includes transformers, circuit breakers, cable joints, isolating switches and shunt capacitors.

9. The operation and maintenance management system for an intelligent power station according to claim 7, characterized in that The infrared video monitoring network includes infrared thermal image probes to collect infrared thermal images on the surface of the electrical equipment.

10. The operation and maintenance management system for a smart power station according to claim 7, characterized in that, The 3D virtual model is updated according to the conversion of the environment and operation stage. Compare and calculate the data monitored by the data collection unit with the model operation output data, construct a distance objective function for the two using the particle swarm algorithm, and seek the optimal parameters to update the 3D virtual model.

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