New energy equipment remote coordination operation and maintenance management system based on data analysis

Abstract

The invention, which relates to the technical field of equipment operation and maintenance management, discloses a remote coordination operation and maintenance management system for new energy equipment based on data analysis, comprising a data acquisition module, a data storage module, a data processing module, a visualization module and an operation and maintenance management module. The data processing module comprises an efficiency evaluation unit, an early warning unit and an operation and maintenance optimization unit, and the efficiency evaluation unit has the functions of obtaining a fault early warning index F through the early warning unit in combination with the performance efficiency E and the new energy equipment data, and making effective preventive maintenance measures according to the fault early warning index F, so that the influence on the power generation amount and the risk during maintenance are reduced; and then the priority score J of the wind driven generator is calculated through the operation and maintenance optimization unit, maintenance can be carried out according to the priority score J from high to low, and the overall operation and maintenance management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment operation and maintenance management, and in particular to a remote coordinated operation and maintenance management system for new energy equipment based on data analysis. Background Art

[0002] In recent years, renewable energy power generation technology represented by wind power and solar energy has developed rapidly around the world. With the continuous development of social economy, electricity demand has increased rapidly, and the requirements for safety and diversity have become increasingly higher. These have put forward high requirements for the safe operation of the power grid economy. With the increase in the scale of use of new energy equipment, the difficulty of maintaining a large number of equipment has increased sharply, and centralized control has become a practical need for enterprises. The operation and maintenance management system uses Internet technology and data communication technology to remotely monitor and control the operating status of new energy equipment, and realize the coordinated operation and maintenance management of equipment. The system can improve the operating efficiency and reliability of equipment, reduce maintenance costs, and realize effective management of new energy equipment.

[0003] At present, in the operation and maintenance management of wind farms, repairs are usually carried out after a fault occurs, and there is a lack of effective preventive maintenance measures. Maintenance after a fault not only increases the maintenance cost, but also increases the safety hazards during maintenance. In addition, during maintenance, new energy equipment is not analyzed and ranked, and the importance of new energy equipment is not considered, thereby increasing the impact of new energy equipment failure on power generation. Summary of the invention

[0004] The purpose of the present invention is to provide a remote coordinated operation and maintenance management system for new energy equipment based on data analysis, which solves the problems raised in the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: A remote coordinated operation and maintenance management system for new energy equipment based on data analysis, comprising a data acquisition module, a data storage module, a data processing module, a visualization module and an operation and maintenance management module;

[0006] The data acquisition module is used to collect wind turbine data in the new energy equipment, and the wind turbine data includes output power P, temperature T, vibration intensity Z and wind speed V. The data storage module is used to store the wind turbine data collected by the data acquisition module;

[0007] The data processing module is used to monitor the operating status of the wind turbine and the fault risk warning according to the real-time wind turbine data, and to maintain the wind turbine in time. The data processing module includes an efficiency evaluation unit, an early warning unit and an operation and maintenance optimization unit;

[0008] The operation and maintenance management module is used to control replacement parts of the wind turbine;

[0009] The efficiency evaluation unit is used to perform efficiency evaluation on the input wind turbine data and obtain the performance efficiency E of the wind turbine. The early warning unit is used to perform early warning processing on the input wind turbine data and the performance efficiency E and obtain the fault early warning index F of the wind turbine. The operation and maintenance optimization unit is used to perform operation and maintenance optimization processing on the input wind turbine data and the fault early warning index F and obtain the priority score J of the wind turbine.

[0010] The visualization module provides a visualization report based on the processing results of the data processing module.

[0011] Optionally, the efficiency evaluation process of the efficiency evaluation unit is as follows:

[0012]

[0013] Where E is the performance efficiency, output as a percentage;

[0014] V is the wind speed;

[0015] P is the output power, P max(V) is the maximum output power at a given wind speed V;

[0016] T is the temperature, T y is the standard operating temperature;

[0017] α is the temperature influence coefficient, and the value range of α is between 0 and 1;

[0018] The performance efficiency E obtained by the efficiency evaluation unit reflects the operating status of the wind turbine, and a threshold is set for the performance efficiency E. When the performance efficiency E is lower than 50% of the threshold, an alarm mechanism is triggered and countermeasures are taken.

[0019] Optionally, the warning processing process of the warning unit is as follows:

[0020]

[0021] Where F is the fault warning index;

[0022] T is the temperature, T safe is the safety temperature threshold;

[0023] S is the generator speed, S y is the standard speed of the generator;

[0024] E is performance efficiency;

[0025] W1 is the temperature influence coefficient, W2 is the speed influence coefficient, and W3 is the performance efficiency influence coefficient. The value ranges of W1, W2 and W3 are all 0 to 1;

[0026] The fault warning index F threshold is set to 2. When the fault warning index F exceeds 2, it indicates that the wind turbine is currently in a fault warning state, an alarm is issued, and countermeasures are taken.

[0027] Optionally, the optimization process of the operation and maintenance optimization unit is as follows:

[0028]

[0029] Where J is the priority score;

[0030] Z is the vibration intensity, ranging from 0 to 1;

[0031] β is the vibration influence coefficient, ranging from 0 to 1;

[0032] C is the criticality coefficient, which indicates the importance of the wind turbine in the wind farm. The value of C ranges from 1 to 2, and the value of C is preset by the system.

[0033] (F-2) + Indicates a positive operation. If the value in the brackets is negative, the result is 0; if the value in the brackets is positive, the result is the value itself, where F is the fault warning index;

[0034] is the life influence coefficient, where A1 is the current operating time, A2 is the design life, The value range is 0 to 1;

[0035] when When it is less than 0.7, the W3 value is set to 0.4. When it is greater than 0.7, it means that the current operation time of the wind turbine is close to the design life, and the risk of failure increases. At this time, the performance efficiency influence coefficient W3 changes as follows;

[0036]

[0037] The higher the priority score J, the more important the wind turbine is to the wind farm and the greater the degree of failure. The priority score J enables the staff to more accurately identify which wind turbines need priority maintenance.

[0038] Optionally, the data acquisition module includes:

[0039] Sensors, data loggers, communications equipment and monitoring systems;

[0040] The sensor comprises:

[0041] Temperature sensor, vibration sensor, accelerometer, anemometer;

[0042] The data collector is used to collect signals sent by the sensor and perform preliminary data processing to convert analog signals into digital signals for storage in the data storage module and processing in the data processing module;

[0043] The monitoring system includes monitoring software and a monitoring server, which are used to remotely monitor the operating status and data collection status of the data collector.

[0044] Optionally, the communication device is used to transmit the collected wind turbine data, and the communication device includes a 5G wireless communication device;

[0045] The monitoring system includes monitoring software and a monitoring server, which are used to remotely monitor the operating status and data collection status of the data collector.

[0046] Optionally, the visualization module is used to visualize the data of each wind turbine;

[0047] The display method uses a combination of bar chart and line chart.

[0048] Optionally, the operation and maintenance management module includes:

[0049] A resource allocation unit and an instruction transmission unit, wherein the resource allocation unit is used to monitor the storage quantity of replacement parts of wind turbines in real time, and when replacement parts are used and purchased, instruction messages are sent to management personnel through the instruction transmission unit to ensure that replacement parts are sufficient.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] 1. The present invention obtains the performance efficiency E of the wind turbine through the efficiency evaluation unit, which affects the subsequent calculation of the fault warning index F. Wind turbines with low operating efficiency are more likely to fail. The warning unit can monitor the state changes of the generator by real-time collection and processing of the operating data of the wind turbine, and calculate the specific fault warning index F in combination with the performance efficiency E. By setting the threshold of the fault warning index F, the fault warning index can send a warning signal before the fault occurs, reminding the staff to take response measures such as shutdown and investigation, thereby reducing the downtime and power generation loss caused by the fault, and reducing the safety hazards during maintenance.

[0052] 2. The priority score J of the wind turbine is output through the operation and maintenance optimization unit. The life impact coefficient in the priority score J affects the fault warning index F. The priority score J includes the importance and fault degree of the wind turbine. In subsequent maintenance, it can be carried out in descending order according to the priority score J. The above units influence and relate to each other, continuously optimize the operation and maintenance management system, improve the power generation efficiency of new energy equipment, and reduce maintenance costs and risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a system module diagram of the present invention. DETAILED DESCRIPTION

[0054] Regarding this remote coordination and operation and maintenance management system for new energy equipment based on data analysis, when remotely monitoring new energy equipment in existing operation and maintenance management systems, passive maintenance is usually carried out after a failure occurs. There is a lack of early identification and prevention of potential risks, and it is impossible to determine which equipment needs priority maintenance during maintenance. There is a lack of data support, which increases the impact of new energy equipment failures on power generation. This system calculates the fault warning index by combining the real-time data of new energy equipment, and takes effective preventive maintenance measures in a timely manner based on the fault warning index. It then calculates the operation and maintenance priority of new energy equipment based on multiple data such as life and criticality, and determines the maintenance order of new energy equipment based on the operation and maintenance priority, thereby reducing the impact of equipment failures on overall power generation and reducing maintenance costs and risks.

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] For examples, see Figure 1 ,This implementation provides a remote coordination operation and maintenance management system for new energy equipment based on data analysis, including a data acquisition module, a data storage module, a data processing module, a visualization module and an operation and maintenance management module;

[0057] The data acquisition module is used to collect wind turbine data, including output power P, temperature T, vibration intensity Z and wind speed V;

[0058] The data acquisition module includes sensors, data collectors, communication equipment and monitoring systems. The sensors include temperature sensors, vibration sensors, accelerometers and anemometers. The data collectors are used to collect signals sent by the sensors and perform preliminary data processing to convert analog signals into digital signals for storage in the data storage module and processing in the data processing module. The data storage module uses a combination of SSD solid state drives and cloud storage.

[0059] Specifically, the data acquisition module can collect the operating data of wind turbines in real time through multiple sensors, and provide support for subsequent data transmission and storage through data collectors and communication equipment. Cloud storage has the advantages of large storage capacity, secure and reliable data, and convenient access. Data can be backed up through cloud storage, and the solid-state hard drive has a fast access speed, which reduces waiting time and improves data processing efficiency.

[0060] The communication equipment is used to transmit the collected data of new energy equipment. The communication equipment gives priority to the use of 5G wireless communication equipment. The monitoring system includes monitoring software and monitoring server, which are used to remotely monitor the operating status and data collection status of the data collector.

[0061] Specifically, by setting up a monitoring system, the data of new energy equipment can be displayed in real time, allowing staff to quickly understand the operation status of the equipment. 5G wireless communication equipment is flexible and easy to deploy, with fast transmission speed and low latency. It can speed up the processing of subsequent wind turbine data and improve the operation and maintenance management efficiency of the system.

[0062] The data storage module is used to store the wind turbine data collected by the data collection module;

[0063] The data processing module is used to monitor the operating status of wind turbines and provide early warning of fault risks based on real-time wind turbine data, and to perform timely maintenance on wind turbines;

[0064] The data processing module includes:

[0065] An efficiency evaluation unit, used for evaluating the input wind turbine data and obtaining the performance efficiency E of the wind turbine;

[0066] An early warning unit is used to perform early warning processing on the input wind turbine data and performance efficiency E, and obtain a fault early warning index F of the wind turbine;

[0067] The operation and maintenance optimization unit is used to optimize the input wind turbine data and the fault warning index F, and obtain the priority score J of the wind turbine.

[0068] Specifically, by collecting wind turbine equipment data through the data acquisition module and calculating the performance efficiency of the wind turbine through the efficiency evaluation unit, the staff can understand the power generation performance of the wind turbine. By calculating the performance efficiency of multiple wind turbines, the power generation quality of this model of wind turbine can be obtained.

[0069] The fault warning index F is then derived through the early warning unit in combination with the performance efficiency E and the wind turbine equipment data. The higher the fault warning index F, the greater the risk of failure of the wind turbine. Effective preventive maintenance measures can be made according to the fault warning index F to handle equipment failure before it occurs, thereby reducing the impact on power generation and reducing the risk during maintenance.

[0070] Finally, the priority score J of the wind turbine is calculated through the operation and maintenance optimization unit. The priority score J includes the importance and fault degree of the wind turbine. In subsequent maintenance, it can be carried out in descending order according to the priority score J, thereby reducing the impact of wind turbine failure on the overall power generation, optimizing resource allocation, and improving the overall operation and maintenance efficiency.

[0071] Furthermore, the performance efficiency calculation process of the wind turbine in the efficiency evaluation unit is as follows:

[0072]

[0073] Where E is the performance efficiency, output as a percentage;

[0074] V is the wind speed;

[0075] P is the output power, P max(V) is the maximum output power at a given wind speed V;

[0076] T is the temperature, T y It is the standard operating temperature, ranging from -20℃ to 50℃. When the wind turbine operates within the range of -20℃ to 50℃, its performance is relatively stable and its power generation efficiency is high.

[0077] α is the temperature influence coefficient, and the value range of α is between 0 and 1;

[0078] The efficiency evaluation unit can calculate the current performance efficiency in real time based on the operating data of the wind turbine, so that the staff can understand the operating status of the wind turbine in a timely manner.

[0079] Specifically, by real-time monitoring and calculation of the performance efficiency E of wind turbines, we can understand whether the wind turbines are in the best operating state. If the performance efficiency E is too low, it may mean that there is performance degradation or potential failure, which will affect the subsequent calculation of the fault warning index. In actual use, a threshold value can be set for the performance efficiency E. For example, the performance efficiency E threshold can be set to 50%. When the performance efficiency E is lower than 50%, the alarm mechanism is triggered and countermeasures are taken.

[0080] Furthermore, the fault warning index calculation process in the warning unit is as follows:

[0081]

[0082] Where F is the fault warning index;

[0083] T is the temperature, T safe is the safety temperature threshold;

[0084] S is the generator speed, S y It is the standard speed of the generator. The rotor speed of a large wind turbine is usually 19 to 30 rpm. This speed is the speed generated by the wind turbine directly driven by wind.

[0085] E is performance efficiency;

[0086] W1 is the temperature influence coefficient, W2 is the speed influence coefficient, and W3 is the performance efficiency influence coefficient. The value ranges of W1, W2 and W3 are all 0 to 1;

[0087] The fault warning index F threshold is set to 2. When the fault warning index F exceeds 2, it indicates that the wind turbine is currently in a fault warning state. Even if the wind turbine is still working at this time, an alarm will be issued and countermeasures will be taken to avoid waiting until the failure to perform maintenance. The possible causes of the failure can be checked in advance, such as component aging, and the maintenance cost can be greatly reduced by replacing them.

[0088] Specifically, by collecting and processing the operating data of wind turbines in real time, the fault warning index F can monitor the status changes of the generators. By setting the threshold of the fault warning index F, the fault warning index F can send out a warning signal before a fault occurs, reminding the staff to take response measures such as shutdown and investigation, thereby reducing the downtime and power generation loss caused by the fault, and avoiding the impact of sudden faults on power generation efficiency and safety.

[0089] Furthermore, the operation process of the operation and maintenance optimization unit is as follows:

[0090]

[0091] Where J is the priority score;

[0092] Z is the vibration intensity, ranging from 0 to 1;

[0093] β is the vibration influence coefficient, ranging from 0 to 1;

[0094] C is the criticality coefficient, which indicates the importance of the wind turbine in the wind farm. The value of C ranges from 1 to 2, and the value of C is preset by the system.

[0095] (F-2) + Indicates a positive operation. If the value in the brackets is negative, the result is 0; if the value in the brackets is positive, the result is the value itself, where F is the fault warning index;

[0096] is the life influence coefficient, where A1 is the current operating time, A2 is the design life, The value range is 0 to 1;

[0097] when When it is less than 0.7, the W3 value is set to 0.4. When it is greater than 0.7, it means that the current operation time of the wind turbine is close to the design life, and the risk of failure increases. At this time, the performance efficiency impact coefficient W3 changes as follows:

[0098]

[0099] The higher the priority score J, the more important the wind turbine is to the wind farm and the greater the degree of failure. The priority score J enables the staff to more accurately identify which wind turbines need to be maintained first.

[0100] Specifically, the operation and maintenance optimization unit comprehensively considers the criticality coefficient C, vibration intensity Z, and life impact coefficient The wind turbine rating system is based on the real-time monitoring data and historical data of wind turbines, and the fault warning index F and other factors are combined to make the rating of wind turbines more comprehensive and accurate. In actual use, each wind turbine can be sorted according to its priority score J, making it easier for staff to determine which wind turbines need priority maintenance, thereby improving the operating efficiency and reliability of the entire wind farm and reducing the impact of equipment failures on power generation.

[0101] Furthermore, the visualization module is used to visualize the data of each wind turbine using a combination of a bar chart and a line chart.

[0102] Specifically, when a bar chart and a line chart are used in combination, the advantages of both charts can be fully utilized. The mixed use of bar charts and line charts takes advantage of the advantages of line charts in showing data change trends and the advantages of bar charts in comparing the numerical sizes of different groups, making it possible to more effectively compare and analyze data in the same view. This combination of charts can not only help staff better understand the distribution and change trends of wind turbine data, but also improve the readability and comprehensibility of the data, making it easier for subsequent manual decisions based on the data.

[0103] The operation and maintenance management module is used to control the replacement parts of wind turbines.

[0104] The operation and maintenance management module includes a resource allocation unit and a command transmission unit. The resource allocation unit monitors the storage volume of replacement parts for wind turbine equipment in real time. When replacement parts are needed or purchased, the command transmission unit sends command messages to management personnel to ensure that there are sufficient replacement parts.

[0105] Specifically, when replacement parts for wind turbine equipment are put into storage or used, the staff will change the number of replacement parts and set a threshold for the number of replacement parts. For example, when the number of replacement parts is less than 5, the reminder mechanism will be automatically triggered, and the purchasing staff will be notified through the instruction transmission unit to purchase them in time, thereby avoiding equipment maintenance delays due to insufficient replacement parts, reducing downtime caused by equipment failures, and improving system stability.

[0106] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A remote coordination and operation and maintenance management system for new energy equipment based on data analysis, characterized in that: include: A data acquisition module is used to collect wind turbine data, including output power P, temperature T, vibration intensity Z and wind speed V; A data storage module, used for storing the wind turbine data collected by the data collection module; The data processing module is used to monitor the operating status of wind turbines and provide early warning of fault risks based on real-time wind turbine data, and to perform timely maintenance on wind turbines; Visualization module, used to provide visualization reports; Operation and maintenance management module, used to control replacement parts of wind turbines; The data processing module comprises: An efficiency evaluation unit, used for evaluating the input wind turbine data and obtaining the performance efficiency E of the wind turbine; An early warning unit is used to perform early warning processing on the input wind turbine data and performance efficiency E, and obtain a fault early warning index F of the wind turbine; The operation and maintenance optimization unit is used to optimize the input wind turbine data and the fault warning index F, and obtain the priority score J of the wind turbine.

2. The remote coordination and operation and maintenance management system for new energy equipment based on data analysis according to claim 1 is characterized in that: The data acquisition module comprises: Sensors, data loggers, communications equipment and monitoring systems; The sensor comprises: Temperature sensor, vibration sensor, accelerometer, anemometer; The data collector is used to collect signals sent by the sensor and perform preliminary data processing to convert analog signals into digital signals for storage in the data storage module and processing in the data processing module; The monitoring system includes monitoring software and a monitoring server, which are used to remotely monitor the operating status and data collection status of the data collector.

3. The remote coordination and operation and maintenance management system for new energy equipment based on data analysis according to claim 2 is characterized in that: The communication device is used to transmit the collected wind turbine data, and the communication device includes a 5G wireless communication device; The monitoring system includes monitoring software and a monitoring server, which are used to remotely monitor the operating status and data collection status of the data collector.

4. The remote coordination and operation and maintenance management system for new energy equipment based on data analysis according to claim 3 is characterized in that: The efficiency evaluation process of the efficiency evaluation unit is as follows: Where E is the performance efficiency, output as a percentage; V is the wind speed; P is the output power, P max(V) is the maximum output power at a given wind speed V; T is the temperature, T y is the standard operating temperature; α is the temperature influence coefficient, and the value range of α is between 0 and 1; The performance efficiency E obtained by the efficiency evaluation unit reflects the operating status of the wind turbine, and a threshold is set for the performance efficiency E. When the performance efficiency E is lower than 50% of the threshold, an alarm mechanism is triggered and countermeasures are taken.

5. The remote coordination and operation and maintenance management system for new energy equipment based on data analysis according to claim 4 is characterized in that: The warning processing of the warning unit is as follows: Where F is the fault warning index; T is the temperature, T safe is the safety temperature threshold; S is the generator speed, S y is the standard speed of the generator; E is performance efficiency; W1 is the temperature influence coefficient, W2 is the speed influence coefficient, and W3 is the performance efficiency influence coefficient. The value ranges of W1, W2 and W3 are all 0 to 1; The fault warning index F threshold is set to 2. When the fault warning index F exceeds 2, it indicates that the wind turbine is currently in a fault warning state, an alarm is issued, and countermeasures are taken.

6. The remote coordination and operation and maintenance management system for new energy equipment based on data analysis according to claim 5 is characterized in that: The operation and maintenance optimization process of the operation and maintenance optimization unit is as follows: Where J is the priority score; Z is the vibration intensity, ranging from 0 to 1; β is the vibration influence coefficient, ranging from 0 to 1; C is the criticality coefficient, which indicates the importance of the wind turbine in the wind farm. The value of C ranges from 1 to 2, and the value of C is preset by the system. (F-2) + Indicates a positive operation. If the value in the brackets is negative, the result is 0. If the value in the brackets is positive, the result is the value itself. F is the fault warning index. is the life influence coefficient, where A1 is the current operating time, A2 is the design life, The value range is 0 to 1; when When it is less than 0.7, the W3 value is set to 0.4; when When it is greater than 0.7, it means that the current operation time of the wind turbine is close to the design life, and the risk of failure increases. At this time, the performance efficiency impact coefficient W3 changes as follows; The higher the priority score J, the more important the wind turbine is to the wind farm and the greater the degree of failure. The priority score J enables the staff to more accurately identify which wind turbines need priority maintenance.

7. The remote coordination and operation and maintenance management system for new energy equipment based on data analysis according to any one of claims 1 to 6, characterized in that: The visualization module is used to visualize the data of each wind turbine; The display method uses a combination of bar chart and line chart.

8. The remote coordination and operation and maintenance management system for new energy equipment based on data analysis according to claim 7 is characterized in that: The operation and maintenance management module includes: A resource allocation unit and an instruction transmission unit, wherein the resource allocation unit is used to monitor the storage quantity of replacement parts of wind turbines in real time, and when replacement parts are used and purchased, instruction messages are sent to management personnel through the instruction transmission unit to ensure that replacement parts are sufficient.

Images