Integrated management system for real-time status monitoring and maintenance of offshore wind turbines and management method therefor

Abstract

To provide an integrated management system of an offshore wind power generator for real-time state monitoring and maintenance of the offshore wind power generator, configured to monitor various states to optimize a maintenance schedule.SOLUTION: An integrated management system of an offshore wind power generator, comprises: a maintenance worker and facility safety and state monitoring unit 100 for detecting state information about a maintenance worker and a facility; a real-time meteorological environment monitoring unit 200 for monitoring an environment surrounding the wind power generator; a wind power generator state monitoring unit 300 for monitoring a state of the wind power generator; a database server unit 400 for storing and transmitting / receiving measurement data from the monitoring units 100, 200, 300; a maintenance schedule optimization unit 500 for providing an optimal maintenance schedule based on the information received from the database server unit 400 and a failure history of the wind power generator; and a data transmitting / receiving and outputting unit 600 for transmitting / receiving or notifying a user and a worker of the information generated by the database server unit 400 and the maintenance schedule optimization unit 500.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an integrated management system and method for an offshore wind turbine, and more particularly to an integrated management system and method for a wind turbine that detects various information for maintenance of the wind turbine in real time, thereby enabling quick and efficient maintenance. [Background technology]

[0002] Recently, investment in new and renewable energy sources has been increasing due to the depletion of fossil energy and environmental issues such as climate change and greenhouse gas reduction. In particular, the domestic new and renewable energy market is growing rapidly due to the expansion of renewable energy, centered on solar and wind power, based on the Renewable Portfolio Standard (RPS) and the government's renewable energy transition plan.

[0003] In particular, wind power generation is a representative new renewable energy technology that has emerged as a technology that can reduce greenhouse gases, and the cumulative installed capacity of wind power generation worldwide as of 2022 is expected to reach 906GW, with the amount increasing every year. Wind power generation uses wind power to rotate a fan-equipped turbine to generate electricity, and is classified into large, medium, and small types depending on the amount of electricity generated, and into onshore and offshore wind power generation depending on the location of installation. There is a trend for wind power generation to become larger and to move from onshore to offshore, and due to these characteristics, various facilities, including wind turbines, are being built and operated separately.

[0004] Due to the nature of installation, large generators are used far from houses or on the sea, making them difficult to manage, and in the event of an accident such as a breakdown or damage to the generator, a large-scale accident is inevitable. In addition, wind turbines are constantly exposed to winds whose speed and direction change from time to time, and various parts of the wind turbine are damaged or broken due to factors such as vibrations, impacts, and uneven loads caused by such wind. When damage or breakage occurs, it is natural that the operation of the wind turbine is significantly strained, which adversely affects other parts other than the part where the damage or breakage occurred.

[0005] Therefore, it is obvious that it is better to repair or replace a part before damage or breakage occurs, when the part is almost at the end of its life, rather than repairing or replacing the part after damage or breakage has already occurred. However, if it is not possible to accurately grasp or predict how much life a part has left, excessively frequent repairs or replacements will be performed, which can unnecessarily increase the operating costs of the wind turbine.

[0006] As a result, various maintenance methods have been proposed, but most of them are limited to managing the amount of power generated and simply judging whether there is an abnormality. In other words, according to conventional technology, it is only possible to recognize the event status of the power generation facility through communication with the manager or user, and it is not possible to provide services such as a method and platform for comprehensive management. In addition, data analysis of the generator's failure history, parts supply and demand, and maintenance management has not been performed, and therefore, there has been no progress in considering efficient maintenance management and learning and prediction of failure occurrence. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Korean Patent Registration No. 10-2097772 (Announced on April 7, 2020) Summary of the Invention [Problem to be solved by the invention]

[0008] The present invention has been made in consideration of the above problems, and an object of the present invention is to monitor the status of workers, equipment, weather conditions, and wind turbines in real time, and to optimize maintenance schedules by utilizing the information obtained from the monitoring. In addition, the present invention aims to provide a digital-based offshore wind turbine integrated management system and method that can efficiently perform maintenance and predict and prepare for failures by learning and using the failure history data of the wind turbines. [Means for solving the problem]

[0009] The wind turbine integrated management system for real-time status monitoring and maintenance of an offshore wind turbine according to the present invention includes a worker and equipment monitoring unit that senses status information of a maintenance worker and equipment, a meteorological environment monitoring unit that monitors the environment around the wind turbine, a wind turbine monitoring unit that monitors the status of the wind turbine, a server unit that converts measurement data of the worker and equipment monitoring unit, the meteorological environment monitoring unit, and the wind turbine monitoring unit into a database and stores and transmits / receives the data, a maintenance schedule optimization unit that checks a maintenance schedule using data received from the server unit, and a data transmission / reception and output unit that transmits / receives information generated by the server unit and the maintenance schedule optimization unit, or notifies a user and a worker of the data.

[0010] The maintenance schedule optimization unit provides an optimal maintenance schedule by utilizing both the information received from the server unit and the failure history of the wind power generator.

[0011] The wind power generator monitoring unit includes a wind power generator data collection module, a life prediction module, and a temperature information providing module, the wind power generator data collection module collects power generation amount, part information, temperature, and noise data of the wind power generator, and establishes a maintenance strategy through the life prediction module, and the temperature information providing module provides temperature information to an operator, thereby enabling the operator to prepare for a fire in the wind power generator.

[0012] In addition, the data transmission / reception and output unit is linked to the manager's portable terminal, allowing the manager to check the weather environment, equipment, wind turbine and worker status in real time, and this status information is processed as big data and can be learned using data mining or deep learning technology, enabling predictive maintenance of the offshore wind turbine.

[0013] In addition, the data transmission / reception and output unit is characterized by the fact that it utilizes 5G LoRa (Long Range) communications infrastructure technology, eliminating the need for CDMA radio repeaters and ensuring a communications range of up to 11 km, thereby ensuring network stability and reliability of operational data.

[0014] In addition, the meteorological environment monitoring unit includes a meteorological environment data collection module and a short-term weather forecast module, and the meteorological environment data collection module collects humidity, temperature, illuminance, wave height, sunrise, and sunset data, and performs weather forecasting through the short-term weather forecast module, thereby making it possible to establish a maintenance schedule that takes into account the return time of workers currently undergoing maintenance.

[0015] In addition, the worker and equipment monitoring unit includes a worker status monitoring module, a worker status information transmission module, an equipment status confirmation module, and an equipment location confirmation module. The worker status monitoring module detects whether the worker is wearing a protective tool and a work tool and whether there is an abnormality using sensors attached to the protective tool and the work tool, and determines whether work can be performed and whether there is an abnormality by transmitting information collected through the worker's smart watch via the worker status information transmission module. The equipment status confirmation module checks the amount of fuel, oil leakage, battery, and coolant of the equipment to check the equipment status and the time available for maintenance support. The equipment location confirmation module uses GPS to allow work to be carried out at a pre-planned location during maintenance work.

[0016] The server unit further includes a data compilation module and a data analysis module, the data compilation module compiling data collected by the worker and equipment monitoring unit, the meteorological environment monitoring unit, and the wind power generator monitoring unit, and the compiled data is analyzed by the data analysis module using machine learning and statistical techniques.

[0017] In addition, the maintenance schedule optimization unit includes a maintenance cost calculation module and a maintenance schedule optimization module, the maintenance cost calculation module calculates worker labor costs, expenses, education and training costs, as well as equipment rental fees and maintenance costs, and the maintenance schedule optimization module provides an optimized maintenance schedule taking into consideration the cost calculation results, parts procurement time, access time of maintenance workers and equipment to the wind turbine generator, real-time weather environment data, and weather forecast data.

[0018] In addition, in order to utilize the fault history of the wind turbine, the system includes a fault history data acquisition unit that collects the fault history of the wind turbine, a fault history analysis unit that uses the data to analyze the fault history and error codes, a data correction unit that corrects the data, a fault prediction unit that learns the analysis results and predicts the occurrence of a fault, and an information provision unit that provides data and prediction information, and the data correction unit is characterized in that it analyzes and reflects whether the error code and the part match, and the weight and frequency depending on whether maintenance is performed or not, thereby increasing the reliability of the prediction information.

[0019] The integrated management method for an offshore wind power generator using the integrated management system according to the present invention includes a worker and equipment monitoring step of detecting status information of a maintenance worker and equipment, a meteorological environment monitoring step of monitoring the status of the environment around the wind power generator, a wind power generator monitoring step of monitoring the status of the wind power generator itself, a step of storing and transmitting measurement data obtained in the worker and equipment monitoring step, the meteorological environment monitoring step, and the wind power generator monitoring step in a database, a maintenance schedule optimization step of confirming an appropriate maintenance schedule for the wind power generator using the data and the database, and a data transmission / reception and output step of notifying a user and a worker of information generated in the maintenance schedule optimization step and transmitting and receiving information, and is characterized in that in the maintenance schedule optimization step, an optimal maintenance schedule is provided to a manager by utilizing the data and a failure history of the wind power generator together. Effect of the Invention

[0020] The present invention provides an integrated management system and method for monitoring and maintaining the status of a wind turbine generator, which obtains information on maintenance workers, equipment, the wind turbine generator, and the surrounding environment in real time and plans an optimized maintenance schedule using the information. Also, the present invention provides an integrated management system and method for a digital-based offshore wind turbine generator, which analyzes and corrects fault history data and error codes, improves reliability by learning from the data, and performs efficient maintenance and management, as well as predicts and prepares for faults. [Brief description of the drawings]

[0021] [Figure 1] 1 is an overall configuration diagram of a wind power generator integrated management system according to the present invention; [Diagram 2] FIG. 2 is an explanatory diagram of a configuration of a worker and equipment monitoring unit. [Diagram 3] FIG. 2 is an explanatory diagram of a configuration of a meteorological environment monitoring unit. [Figure 4] FIG. 2 is an explanatory diagram of a configuration of a wind power generator monitoring unit. [Diagram 5] FIG. 2 is an explanatory diagram of a configuration of a server unit. [Figure 6] FIG. 2 is an explanatory diagram of a configuration of a maintenance schedule optimization unit; [Figure 7] FIG. 2 is an explanatory diagram of a configuration of a data transmission / reception and output unit. [Figure 8] FIG. 1 is a diagram illustrating the configuration of an integrated management system that plans a maintenance schedule using the failure history of a wind power generator. [Figure 9] 9 is a flowchart illustrating a maintenance process of the integrated management system according to FIG. 8. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022] Hereinafter, an integrated management system and a management method for an offshore wind turbine according to an embodiment of the present invention will be described in detail so that those skilled in the art can easily implement the system and method. The present invention is not limited to the embodiments described herein, and may be embodied in various different forms.

[0023] In order to clearly explain the present invention, parts that are not relevant to the explanation will be omitted, and the same or similar components will be given the same reference numerals throughout the specification. The present invention relates to an integrated management system and management method for offshore wind power generators, and in terms of the terminology, a unit, an apparatus, and a system can be understood with the same meaning in terms of specific configurations, and the present invention includes inventions related to methods, steps, and processes, and the terms should be interpreted in light of reasonable common sense to understand the present invention. In addition, data, information, etc. can refer to the same object with a similar meaning, and can be interpreted reasonably within the limits of technical realization.

[0024] The purpose of the wind turbine integrated management system of the present invention is to monitor various surrounding conditions such as workers, equipment, weather conditions, and wind turbines in real time, acquire information, and use the acquired information and data to enable efficient and immediate maintenance of the wind turbines.

[0025] To this end, the wind power generator integrated management system according to the present invention includes a worker and equipment monitoring unit 100 that senses status information of maintenance workers and equipment, a meteorological environment monitoring unit 200 that monitors the environment around the wind power generator, a wind power generator monitoring unit 300 that monitors the status of the wind power generator, a server unit 400 that converts measurement data of the worker and equipment monitoring unit 100, the meteorological environment monitoring unit 200 and the wind power generator monitoring unit 300 into a database and stores and transmits / receives the data, and a maintenance schedule optimization unit 500 that checks the maintenance schedule using the data received from the server unit 400.

[0026] The system further includes a data transmission / reception and output unit 600 for transmitting / receiving information generated by the server unit 400 and the maintenance schedule optimization unit 500, or for notifying a user or worker of the information. The maintenance schedule optimization unit 500 provides an optimal maintenance schedule by utilizing not only the information received from the server unit 400 but also the failure history of the wind power generator.

[0027] Therefore, the wind power generator integrated management system according to the present invention monitors and senses the status of the worker performing the maintenance (health, location, etc.), the status of the equipment operated by the worker, the status of large equipment, etc. (operation or not, location, etc.), the surrounding environment and weather conditions where the wind power generator is installed, and the status of the wind power generator itself in real time to obtain information, and performs maintenance or plans a maintenance schedule based on the obtained information. At this time, it is intended to utilize the fault history data of the wind power generator in order to establish a more accurate and efficient maintenance schedule and perform maintenance.

[0028] The wind power generator monitoring unit 300 can select and use a variety of sensors (not shown) that detect all factors such as vibration, temperature, illuminance, and current, and preferably can use a sensor that is attached to the wind power generator and measures vibrations generated during operation.

[0029] At this time, the sensor uses a piezoelectric element to obtain electromotive force from the vibration of the wind turbine, and can determine the value of the electromotive force obtained at this time to check the status of the wind turbine. A solar cell is attached to one side of the sensor, and the power obtained at this time can be supplied to the sensor.

[0030] The wind power generator monitoring unit 300 includes a wind power generator data collection module 301, a life expectancy prediction module 302, and a temperature information providing module 303. The wind power generator data collection module 301 collects the amount of power generated, part information, temperature, and noise data of the wind power generator. The collected data is used to establish an appropriate maintenance strategy through the life expectancy prediction module 302, and the temperature information providing module 303 provides temperature information of the wind power generator to an operator, thereby enabling the operator to prepare for the occurrence of a fire in the wind power generator.

[0031] In addition, the data transmission / reception and output unit 600 is linked to a manager's portable terminal that controls and manages the manager or workers, allowing the manager to check the weather environment, equipment, wind turbine, and worker status in real time, and this status information is processed as big data and can be learned using data mining or deep learning technology, enabling predictive maintenance of the offshore wind turbine.

[0032] In addition, the data transmission / reception and output unit 600 utilizes 5G LoRa (Long Range) communication infrastructure technology, eliminating the need for CDMA wireless repeaters and ensuring a communication range of up to 11 km, thereby ensuring network stability and reliability of operational data.

[0033] In addition, all communications for storing, transmitting, receiving and analyzing status information and maintenance information of wind turbines, as well as remote control, can be established based on IoT or 5G LoRa communications, because the conventional CDMA method has the disadvantage of RF network interruption problems due to low-power wireless communications, and the functionality of individual WIFI / Zigbee terminals connected to it is limited when a wireless repeater malfunctions.

[0034] In addition, the conventional communication method uses CDMA and LTE wireless repeaters / amplifiers. In this case, the communication costs are somewhat high (50,000 to 60,000 won per year) and only the Group method is possible, making it less efficient. If RoLa communication is used to improve this, there are problems with inefficiency in terms of purchasing costs and management.

[0035] As a result, the communication method according to the present invention uses 5G LoRa (Long Range) communication infrastructure technology to omit CDMA wireless repeaters and ensure a maximum communication range of 11 km, thereby ensuring network stability and reliability of operational data. Also, the server unit 400 uses a big data-based cloud server method, which provides much higher network security, stability and server reliability than general systems.

[0036] In addition, the meteorological environment monitoring unit 200 includes a meteorological environment data collection module 201 and a short-term weather forecast module 202. The meteorological environment data collection module 201 collects humidity, temperature, illuminance, wave height, sunrise, and sunset data, and performs weather forecasting through the short-term weather forecast module 202, thereby making it possible to adjust the schedule of workers who are undergoing or scheduled for maintenance, and to establish a maintenance schedule that takes into account the safe return and travel time of workers.

[0037] In addition, since most of the wind turbines are installed on the sea, far from land, they are greatly affected by the weather environment, and weather information is a very important factor in access and movement for maintenance. Through this information and analysis, efficient maintenance of the wind turbines is possible.

[0038] The worker and equipment monitoring unit 100 includes a worker status monitoring module 101, a worker status information transmission module 102, an equipment status confirmation module 103, and an equipment position confirmation module 104. That is, the unit is capable of checking the location and health condition of a worker to obtain worker information, checking the status and position (movement or not) of equipment (small, medium, large), and promptly using or moving the equipment.

[0039] The worker status monitoring module 101 detects whether the worker is wearing protective tools and work tools and whether there is an abnormality using sensors attached to the worker's protective tools and work tools, and in some cases may detect the worker's status using the worker's smart watch (wearable device). The collected information is transmitted via the worker status information transmission module 102 to determine whether the work can be performed and whether there is an abnormality.

[0040] The data collected by the worker and equipment monitoring unit 100, the meteorological environment monitoring unit 200, and the wind power generator monitoring unit 300 is loaded into the data compilation module 401 of the server unit 400, and the data analysis module 402 performs data analysis using machine learning, statistical techniques, etc.

[0041] In addition, the analysis results of the maintenance worker and equipment safety status data can be useful for the maintenance worker to assign tasks according to their health status, to decide whether or not to use substitute manpower, and to provide safety education and training, and the maintenance efficiency can be maximized through continuous management of the equipment.

[0042] The results of the weather environment data analysis are used to manage short-term maintenance schedules as well as to establish mid- to long-term maintenance plans for wind turbines. The results of the wind turbine status data analysis are used to predict the remaining life span of each part of the wind turbine and estimate the probability of failure, which helps to prepare spare parts and establish a maintenance strategy for the wind turbine.

[0043] Furthermore, the equipment status confirmation module 103 checks the amount of fuel, the presence or absence of oil leakage, the battery, and the coolant to confirm the equipment status and the available time for maintenance support, and the equipment location confirmation module 104 uses GPS to ensure that maintenance work is carried out at a pre-planned location.

[0044] The server unit 400 includes a data compilation module 401 and a data analysis module 402. The data compilation module 401 compiles data collected by the worker and equipment monitoring unit, the meteorological environment monitoring unit, and the wind power generator monitoring unit, and the compiled data is analyzed by the data analysis module 402 using machine learning and statistical techniques.

[0045] The maintenance schedule optimization unit 500 includes a maintenance cost calculation module 501 and a maintenance schedule optimization module 502. The maintenance cost calculation module calculates the labor cost, expenses, education and training cost of workers, as well as the rental fee and maintenance cost of equipment. That is, one of the important factors in determining the maintenance schedule is the equipment usage fee and labor cost, and therefore the calculation of these is required.

[0046] In addition, the maintenance schedule optimization module 502 provides an optimized maintenance schedule taking into consideration the previously calculated cost results, parts procurement time, the time when maintenance workers and equipment can access the wind turbine generator, real-time meteorological environment data, and weather forecast data.

[0047] The offshore wind turbine integrated management system according to the present invention provides real-time information on the safety and status of the workers and equipment, the weather environment at sea, and the status of the wind turbine when offshore wind turbine maintenance workers and equipment perform maintenance work at sea, thereby supporting workers in safely maintaining offshore wind turbines and enabling wind turbine and maintenance managers to make various decisions.

[0048] In addition, this data is stored and analyzed by a server and becomes indicators and guidelines for current and future maintenance. Using the collected data, the company will present ways to maximize profits for wind power generation and maintenance companies and achieve sustainable management by optimizing maintenance schedules based on the results of cost calculations that arise during maintenance.

[0049] In addition, the wind power generator integrated management system according to the present invention can plan optimal maintenance progress and maintenance schedules using the fault history information of the wind power generator as described above, thereby maximizing the use of digital information.

[0050] To this end, the wind turbine integrated management system according to the present invention includes a fault history data acquisition unit that collects the fault history of the wind turbine, a fault history analysis unit that uses the data to analyze the fault history and error codes, a data correction unit that corrects the data, a fault prediction unit that learns the analysis results and predicts the occurrence of a fault, and an information provision unit that provides data and prediction information, and the data correction unit analyzes and reflects whether the error code matches the parts and the weight and frequency depending on whether maintenance is performed or not, thereby increasing the reliability of the prediction information.

[0051] In other words, the system obtains and analyzes fault history from wind turbines, performs corrections to increase reliability, and thereby provides fault prediction information or issues an alarm, making it possible to provide information to users or managers via their mobile devices, computers, tablets, etc. when necessary.

[0052] In particular, the data correction unit enhances the reliability of the prediction information by analyzing and reflecting whether the error code matches the parts, and the weight and frequency depending on whether maintenance is performed. That is, the data correction unit matches the acquired wind turbine fault history with the error code, and reflects the results of frequency and whether repairs are performed by analyzing existing data.

[0053] For example, by checking the failure history and the error codes of the main components to see if they match, and then comparing the results of the actual repairs and replacements, the weight of the necessity of the repairs and replacements can be obtained and used in the analysis process. In other words, if the frequency of actual repairs and replacements is high, the necessity of repairs and replacements will be higher in the maintenance process.

[0054] The failure history analysis unit analyzes the failure history of each part and error code, and performs matching with main components according to different error codes depending on the type of power plant and generator, and when an error occurs, it is possible to perform matching and data classification with main components such as nacelle, PCS, pitch system, yaw system, tower, drive train, generator, hub, etc. In other words, it is very important to predict the occurrence of failure based on the failure history and error code of the main components.

[0055] The fault history data acquisition unit can check the state of the wind power generator using a plurality of sensors (not shown) when necessary, and the checked information can be transmitted to a user using a communication unit (not shown). The sensors can be sensors that compare the applied and output current and voltage, or sensors that sense illuminance, temperature, etc., or sensors that physically detect the presence or absence of a fault.

[0056] In particular, for the purposes of the present invention, the data is processed and stored in a database or learned so that the state of the wind turbine generator and the presence or absence of a malfunction can be predicted and prepared for, and a correction process is important to increase the accuracy of such estimation and prediction.

[0057] The collected data, analyzed values, predicted values, information data, etc. are provided to the administrator or user, and at this time, an alarm can be set simultaneously according to a preset standard or selected. This allows the system to judge the importance of maintenance management by considering the urgency, necessity, and priority of the failure occurrence, and to directly alarm the user.

[0058] The biggest factor that impedes the stability and efficiency of wind power plant operation is the major failure of the wind turbine, which means the failure of the main components that make up the main parts of the wind turbine, such as the gear box, generator, hub, main bearing, and blade. Therefore, if the timing for inspection, repair, and replacement of the main components can be predicted based on the failure history data of the wind power plant, it can be used to increase the operation rate by realizing effective operation management of the wind turbine.

[0059] In addition, 60-65% of wind power generation operational improvement activity maintenance (O&M) costs are due to unplanned maintenance, and more than 40% of wind power generator failures are caused by component failures, so wind power generation status monitoring systems and predictive infrastructure development technology can be applied as an essential item for cost reduction.

[0060] The expected effects of the present invention include stable power generation operation and minimization of downtime through planned maintenance and centralized management of major components, and prevention of accident risks caused by failures and reduction of operation downtime by predicting failures in major components of the wind power generation system and preparing spare parts, manpower, and equipment in advance for replacement and repair.

[0061] In addition, by estimating the frequency of component inspection, repair, and replacement based on the wind turbine failure history, from an economic and industrial perspective, it will be possible to reduce O&M time, manpower, and O&M costs by identifying the causes of component failures in advance. From a social perspective, it will improve living conditions by reducing PM2.5, and contribute to the government's policy of moving away from nuclear power.

[0062] Incidentally, when sensing the presence or absence of a fault, the system can be designed to determine whether a part has failed by measuring the supply (connection / disconnection) and current or voltage of the ACV line connected to the part and transmitting the measured values ​​to the MCU. Here, if the sensor confirms that the ACV is connected, but that the DCV supply is cut off, the MCU will determine that the SMPS has failed for the time being, and then it will be designed to compare and analyze the measurements from various sensors such as temperature and illuminance sensors with the ACV / DCV sensor measurements to determine the exact location of the fault. In other words, it increases the accuracy and reliability of fault history data and information.

[0063] Here, the MCU is designed to enable self-diagnosis of software algorithms to determine failures in communication functions. For example, the self-diagnosis can confirm that the RSSI value, which measures the reception sensitivity of wireless communication, has not reached the reference value, that the noise value of wireless communication has increased, that transmission of transmission signals to and from the base station (repeater) is not possible due to coverage problems caused by simultaneous connections, or that the earth of the hardware wiring of LPWA, etc. is faulty.

[0064] The integrated management method for offshore wind turbines according to the present invention includes a worker and equipment monitoring step of detecting status information of maintenance workers and equipment, a meteorological environment monitoring step of monitoring the status of the surrounding environment where the wind turbine is installed, a wind turbine monitoring step of monitoring the status of the wind turbine itself, a step of storing and transmitting measurement data obtained in the worker and equipment monitoring step, the meteorological environment monitoring step, and the wind turbine monitoring step in a database, and a maintenance schedule optimization step of confirming an appropriate maintenance schedule for the wind turbine using the data and the database.

[0065] The method further includes a data transmission / reception and output step of notifying a user and an operator of the information generated in the maintenance schedule optimization step and transmitting and receiving information, and in the maintenance schedule optimization step, an optimal maintenance schedule is provided to a manager by utilizing the data and the failure history of the wind turbine generator together.

[0066] The present invention described above is not limited to the above-described embodiments and the accompanying drawings, and simple replacements, modifications and alterations within the technical spirit of the present invention are obvious to those skilled in the art. [Industrial Applicability]

[0067] The offshore wind turbine integrated management system and method according to the present invention monitors and collects various information in real time, and analyzes and utilizes the information to enable optimal maintenance. [Explanation of symbols]

[0068] 100 Worker and Equipment Monitoring Division 101 Worker status monitoring module 102 Worker status information transmission module 103 Equipment Status Check Module 104 Equipment Location Confirmation Module 200 Meteorological and Environmental Monitoring Department 201 Meteorological environment data collection module 202 Short-term Weather Forecast Module 300 Wind turbine monitoring unit 301 Wind Turbine Data Collection Module 302 Life Prediction Module 303 Temperature information module 400 Server 401 Data Collection Module 402 Data Analysis Module 500 Maintenance Schedule Optimization Department 501 Maintenance cost calculation module 502 Maintenance Schedule Optimization Module 600 Data transmission / reception and output unit 601 Data transmission and reception module 602 Visualization Output Module

Claims

1. A wind turbine integrated management system for real-time status monitoring and maintenance of an offshore wind turbine, comprising: a computerized worker and equipment monitoring unit that detects and acquires worker information, including the location and health condition of a maintenance worker, and equipment status information, using a sensor means; a meteorological environment monitoring unit of a computer that monitors and acquires information about the surrounding environment of the wind power generator using a sensor means; a wind power generator monitoring unit of a computer that monitors and acquires the state of the wind power generator using a sensor means; a computer server unit that converts real-time measurement data from the worker and equipment monitoring unit, the meteorological environment monitoring unit, and the wind power generator monitoring unit into a database and stores and transmits / receives the data; a computer-based maintenance schedule optimization unit that receives the data from the server unit and generates a maintenance schedule; a data transmission / reception and output unit which is a communication means for transmitting / receiving information generated by the server unit and the maintenance schedule optimization unit, or notifying the information to a user's or worker's terminal; Including, The server unit includes a data compilation module and a data analysis module; The data compilation module compiles data collected by the worker and equipment monitoring unit, the meteorological environment monitoring unit, and the wind power generator monitoring unit in real time, and the compiled data is analyzed by the data analysis module using machine learning and statistical techniques; The maintenance schedule optimization unit is This wind turbine integrated management system inputs the worker information, the equipment status information, the surrounding environment information, and the wind turbine status information, and provides a maintenance schedule that outputs, based on the machine learning results in the data analysis module, a work assignment according to the health condition of the maintenance worker, the time when the wind turbine can be accessed depending on the location of the maintenance worker and the equipment and the surrounding environment, and a determination of the importance of maintenance taking into account the urgency and necessity of a breakdown occurring and priority depending on the condition of the wind turbine.

2. 2. The wind power generator integrated management system according to claim 1, wherein the wind power generator monitoring unit utilizes a plurality of sensors as sensor means, and is attached to the wind power generator to monitor vibrations generated during operation by electromotive force sensing using piezoelectric elements, and supplies power to the sensors using solar elements.

3. The wind power generator monitoring unit includes a wind power generator data collection module, a life prediction module, and a temperature information providing module; 2. The wind power generator integrated management system according to claim 1, wherein the wind power generator data collection module collects power generation amount, part information, temperature, and noise data of the wind power generator to establish a maintenance strategy through the life prediction module, and the temperature information providing module provides temperature information to an operator to prepare for a fire outbreak in the wind power generator.

4. The wind turbine integrated management system according to claim 1, wherein the data transmission / reception and output unit is linked to a portable terminal of a manager, so that the manager can check the weather environment, the equipment, the wind turbine, and the status of the workers in real time, and the status information is processed as big data and is used and learned by data mining or deep learning technology, thereby enabling predictive maintenance of the offshore wind turbine.

5. The wind power generator integrated management system according to claim 4, characterized in that the data transmission / reception and output unit uses 5G LoRa (Long Range) communication infrastructure technology to omit a CDMA wireless repeater and ensure a communication range of up to 11 km, thereby ensuring network stability and reliability of operation data.

6. The meteorological environment monitoring unit includes a meteorological environment data collection module and a short-term weather forecasting module; 2. The wind power generator integrated management system according to claim 1, wherein the meteorological environment data collection module collects humidity, temperature, illuminance, wave height, sunrise, and sunset data, and performs weather forecasting through the short-term weather forecast module, thereby enabling the establishment of a maintenance schedule taking into account the return time of workers currently undergoing maintenance.

7. The worker and equipment monitoring unit includes a worker status monitoring module, a worker status information transmission module, an equipment status confirmation module, and an equipment position confirmation module; The worker status monitoring module detects whether the worker is wearing protective tools and work tools and whether there is an abnormality by using sensors attached to the worker's protective tools and work tools, and determines whether the worker can perform work and whether there is an abnormality by transmitting information collected through the worker's smart watch via the worker status information transmission module. The equipment status confirmation module checks the amount of fuel, oil leakage, battery, and coolant of the equipment to check the equipment status and the available time for maintenance support. The equipment location confirmation module checks the location of the equipment using GPS. The wind power generator integrated management system according to claim 1 .

8. In order to utilize the fault history of the wind turbine, The system includes a fault history data acquisition unit that collects a wind power generator fault history, a fault history analysis unit that uses the data to analyze the fault history and an error code, a data correction unit that corrects the data, a fault prediction unit that learns the analysis result and predicts the occurrence of a fault, and an information provision unit that provides data and prediction information, wherein the data correction unit obtains matching for each part in the fault history for each error code, and obtains a weight for the necessity of the repair or replacement by comparing the results of the actual repair or replacement of the part, thereby increasing the reliability of the prediction information from the matching between the error code and the part. The wind power generator integrated management system according to claim 1 .

9. A method for integrated management of offshore wind turbines using an integrated management system including the computer, the sensor means, and the communication means according to any one of claims 1 to 8, A worker and equipment monitoring step of detecting status information of a maintenance worker and equipment; A meteorological environment monitoring step of monitoring the state of the surrounding environment in which the wind turbine generator is installed; a wind turbine monitoring step for monitoring the state of the wind turbine itself; storing and transmitting the real-time measurement data obtained in the worker and equipment monitoring step, the meteorological environment monitoring step, and the wind power generator monitoring step in a database; A maintenance schedule optimization step of confirming an appropriate maintenance schedule for the wind turbine using the data and the DB; a data transmission / reception and output step of notifying a user and an operator of the information generated in the maintenance schedule optimization step and transmitting and receiving information; Including, The method for integrated management of offshore wind turbines, wherein the maintenance schedule optimization step provides an optimal maintenance schedule to a manager by utilizing the data and the failure history of the wind turbine together.

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