KR102536112B1 - Apparatus and method for operating and maintaining solar power system using avatar - Google Patents

Abstract

An apparatus for operating and maintaining a solar power generation system according to the present invention is an apparatus for operating and maintaining a solar power generation system, which implements cyberspace, a virtual three-dimensional system space corresponding to the real space of the solar power generation system and uses a surveillance avatar as a virtual manager of the solar power generation system, which moves through cyberspace to manage the corresponding solar power generation system. The apparatus of the present invention comprises: a data collection unit collecting failure history information of the solar power generation system; a big data storage unit using the failure history information to generate and store big data for failure; a professional avatar management unit learning the big data for failure and creating and registering at least one professional avatar for each field; a real-time monitoring unit monitoring real-time operation information of any first reality device corresponding to the location of the surveillance avatar in response to the movement of the surveillance avatar; a failure diagnosis unit diagnosing whether a failure has occurred and the type of failure of the first reality device, based on preset failure diagnosis information and the real-time operation information; and a service provider selecting one of the professional avatars for each field, based on the failure diagnosis results and then providing operation and maintenance services using the selected professional avatar. Accordingly, people without professional knowledge can intuitively recognize the operating status of the solar power generation system and manage the system effectively.

Description

Operation and maintenance device and method of solar power generation system using learning and evolving avatar {APPARATUS AND METHOD FOR OPERATING AND MAINTAINING SOLAR POWER SYSTEM USING AVATAR}

The present invention relates to an operation maintenance system and method for a solar power generation system, and relates to an operation maintenance system and method for a solar power generation system using a cyber character (hereinafter referred to as 'avatar').

A photovoltaic power generation system is a power generation system that converts energy received from the sun into electrical energy, and its value is increasing as environmental demands for reduction of fossil energy and non-pollution increase.

In addition, the importance of operation and maintenance (O&M) is gradually being emphasized for long-term development of photovoltaic power generation systems and stable profit generation. In the case of a photovoltaic power plant, it is a long-term investment project that takes 20 to 25 years to install once, but it cannot be guaranteed that high profits will be guaranteed continuously in the operation of the power plant due to the high initial cost investment.

Photovoltaic operation and maintenance (O&M) is an essential element for maintaining stable power supply in power plant operation, and includes all tasks ranging from simple facility maintenance and repair in a narrow sense to life extension and performance improvement in a broad sense. can do.

Therefore, the purpose of O&M is to identify in advance the factors that hinder the optimal power generation of the photovoltaic power generation system or to minimize the loss of power generation through quick response in the event of a failure.

However, the factors that hinder the amount of power generation are very diverse. For example, discoloration, cracking, and hot spots of solar cells, natural degradation of solar cells, short lifespan of inverters, and myriad natural environments such as snow, wind, and dust are examples. . In addition, an increase in system failures and system aging due to an increase in the cumulative installed amount of photovoltaic facilities are also one of the factors that hinder the amount of power generation.

As such, numerous factors appear without notice in various facilities, so steady maintenance is essential in the operation of a photovoltaic power generation system. However, it is very difficult to visually check all of these various factors.

In order to compensate for this problem, Korea Patent Registration No. 10-1728692 discloses a failure prediction monitoring system and method of a photovoltaic module. According to the above patent, it is possible to accurately determine whether or not the solar power module is out of order by determining whether the amount of solar power generation, which changes every moment, changes according to the appropriate theoretical amount of power generation according to the season or real-time weather change. In addition, according to the above patent, if a failure or abnormality is predicted, it is transmitted to the user terminal in real time.

However, the conventional technologies as described above only predict whether the solar power generation system will fail and deliver it to the user, and whether the users who received the information actually responded appropriately to the system failure, and what beneficial effect this had on the amount of power generation. There is a limit to effectively performing operation and maintenance of the photovoltaic power generation system by not only not analyzing or managing the system, but also by not performing active processing for failure recovery.

In addition, conventional technologies transmit the operating state of the photovoltaic system to the user (eg, system operator or manager) only when a predetermined criterion or error occurs, and the operating state of the photovoltaic power generation system is displayed at a time desired by the user. There was a problem that could not be freely checked.

In addition, conventional technologies provide the operating state of the photovoltaic power generation system as an alarm or numerical value, so that a user (eg, a system operator) without expert knowledge about the system intuitively and quickly recognizes the operating state of the photovoltaic power generation system. There was a problem that couldn't be done.

Korean Patent Registration No. 10-1728692

Therefore, the present invention provides cyberspace, which is a virtual system space corresponding to the real space of the solar power generation system, and a cyber character (hereinafter referred to as 'surveillance avatar') moving in the cyberspace as a virtual manager of the solar power generation system. ) to monitor and control the power generation information of the corresponding photovoltaic power generation system, so that even users without professional knowledge can intuitively recognize and effectively manage the operation status of the photovoltaic power generation system It is intended to provide an operation maintenance device and method.

In addition, the present invention recommends an arbitrary failure by learning information on failures that have occurred in the past by type of failure and location of failure in the photovoltaic power generation system, the operator's work history for the failure, and the worker's work result. Photovoltaic technology that enhances the quality of photovoltaic power generation system management by generating at least one specialized avatar for each field that provides work information and operating and maintaining the photovoltaic power generation system using the information provided by the specialized avatar. It is intended to provide an operation maintenance device and method for a power generation system.

In addition, the present invention generates big data including fault information of the solar power generation system that occurred in the past and countermeasures for each type of fault, and learns the big data to create an algorithm that can automatically respond to software faults. It is intended to provide an operation and maintenance device and method for a photovoltaic power generation system that enables the professional avatar to automatically respond to diagnosis results in the event of a software failure by loading the system into the specialized avatar.

In order to achieve the above object, the operation and maintenance device of the solar power generation system provided by the present invention implements cyberspace, which is a virtual three-dimensional system space corresponding to the real space of the solar power generation system, and the solar power generation system In the solar power generation system operation and maintenance device that manages the corresponding photovoltaic power generation system using the monitoring avatar moving in cyberspace as a virtual manager of the solar power generation system, failures occurring in the photovoltaic power generation system and response by type of failure a data collection unit that collects failure history information including plans; a big data storage unit generating and storing failure big data using the failure history information collected during a preset information collection period; a professional avatar management unit that learns the failure big data to generate and register at least one professional avatar for each field; a real-time monitoring unit that monitors real-time operation information of an arbitrary first reality device corresponding to the location of the monitoring avatar in response to the movement of the monitoring avatar; a failure diagnosis unit for diagnosing whether or not a failure of the first reality device has occurred and the type of failure based on preset failure diagnosis information and the real-time operation information; and a service providing unit that selects one of the specialized avatars for each field based on the failure diagnosis result and provides operation maintenance service using the selected specialized avatar.

Preferably, the professional avatar management unit includes a big data classification unit that classifies the faulty big data according to at least one preset classification criterion; a big data learning unit learning the failure big data for each classification criterion; a professional avatar creation unit generating at least one piece of recommended work information for each classification criterion based on the learning result, and generating a specialized avatar for each field by matching the classification criterion with the recommended work information; and a professional avatar registration unit for registering the generated professional avatars for each field.

Preferably, the expert avatar creation unit generates an automatic response algorithm capable of automatically responding to a software failure based on the failure history information, and then mounts the automatic response algorithm on a professional avatar belonging to a software failure. can

Preferably, the service providing unit includes a candidate avatar selection unit that selects and displays at least one of the registered professional avatars for each field as a candidate avatar based on the failure diagnosis result; a service information detection unit for each professional avatar, which selects one of the candidate avatars based on user selection information and detects at least one of recommended work information or an automatic response algorithm matched to the selected professional avatar; and a service execution unit for each professional avatar that provides the recommended job information to the user using the selected professional avatar or executes the detected automatic response algorithm.

Preferably, the professional avatar management unit further includes a professional avatar evaluation unit that collects the recommended job information, user evaluation information for the execution result of the automatic response algorithm, and job result information, matches them with corresponding professional avatars, and stores the information; , The candidate avatar selection unit may select the candidate avatar based on evaluation information of the user who selected the professional avatar and evaluation results of the avatar including job result information.

Preferably, the data collection unit further collects real-time operation information for each real device of the photovoltaic system and failure diagnosis results accordingly, and the big data generator further collects the collected real-time operation information for each real device and failures accordingly. Diagnosis big data can be further generated by matching diagnosis results.

Preferably, the big data learning unit learns whether or not a failure has occurred and a diagnosis result of a failure type according to real-time operation information of each of the real devices based on the diagnostic big data, and the professional avatar generator learns the reality based on the learning result. A diagnosis avatar for each device may be created by matching the failure diagnosis result for each device's real-time operation information, and the expert avatar registration unit may register the diagnosis avatar for each device.

Preferably, the failure diagnosis unit calls a diagnosis avatar for diagnosing a failure of the first reality device, and diagnoses whether a failure occurs in the first reality device and a type of failure based on real-time operation information of the first reality device. can do.

On the other hand, in order to achieve the above object, the operation and maintenance method of the solar power generation system provided by the present invention implements cyberspace, which is a virtual three-dimensional system space corresponding to the real space of the solar power generation system, and In the operation and maintenance method of a photovoltaic power generation system that manages the corresponding photovoltaic power generation system using the monitoring avatar moving in cyberspace as a virtual manager of the power generation system, A data collection step of collecting failure history information including countermeasures for each type; a big data generation step of generating failure big data using the failure history information collected during a preset information collection period; a professional avatar management step of generating and registering at least one professional avatar for each field by learning the failure big data; a real-time monitoring step of monitoring real-time operation information of an arbitrary first reality device corresponding to a location of the monitoring avatar in response to movement of the monitoring avatar; a failure diagnosis step of diagnosing whether or not a failure of the first reality device has occurred and a failure type based on preset failure diagnosis information and the real-time operation information; and a service providing step of selecting one of the professional avatars for each field based on the failure diagnosis result and then providing operation maintenance service using the selected professional avatar.

Preferably, the expert avatar management step includes a breakdown big data classification step of classifying the breakdown big data according to at least one preset classification criterion; a failure big data learning step of learning the failure big data for each classification criterion; a professional avatar creation step of generating at least one piece of recommended work information for each classification criterion based on the learning result, and generating a specialized avatar for each field by matching the classification criterion with the recommended work information; and a professional avatar registration step of registering the generated professional avatars for each field.

Preferably, in the professional avatar creation step, an automatic response algorithm capable of automatically responding to a software failure is generated based on the failure history information, and then the automatic response algorithm is loaded into a professional avatar in a field to which the software failure belongs. It may further include steps to do.

Preferably, the service providing step includes a candidate avatar selection step of selecting and displaying at least one of the professional avatars for each field as a candidate avatar based on the failure diagnosis result; a service information detection step for each professional avatar, which selects one of the candidate avatars based on the user's selection information and detects at least one of recommended work information or an automatic correspondence algorithm matched to the selected professional avatar; and a service execution unit for each professional avatar that provides the recommended job information to the user using the selected professional avatar or executes the detected automatic response algorithm.

Preferably, the professional avatar management step further includes an avatar evaluation step of collecting the recommended job information, the user's evaluation information on the execution result of the automatic response algorithm, and the job result information, matching them with corresponding professional avatars, and storing the information. In the step of selecting the candidate avatar, the candidate avatar may be selected based on the avatar evaluation result including evaluation information of the user who has selected the professional avatar and work result information.

Preferably, the data collection step further collects real-time operation information for each real device of the photovoltaic power generation system and failure diagnosis results accordingly, and the big data generation step further collects the collected real-time operation information for each real device and the result thereof. Diagnostic big data can be further generated by matching the failure diagnosis results according to the method.

Preferably, the avatar management step includes a diagnostic big data learning step of learning whether or not a failure occurs and a diagnosis result of a failure type according to real-time operation information of each of the real devices based on the diagnostic big data; a diagnosis avatar generation step of generating a diagnosis avatar for each device by matching failure diagnosis results for each real-time operation information of the real device based on the learning result; and a diagnostic avatar registration step of registering the diagnostic avatar for each device.

Preferably, the failure diagnosis step calls a diagnosis avatar for diagnosing a failure of the first reality device, and determines whether or not a failure of the first reality device has occurred and the type of failure based on real-time operation information of the first reality device. can be diagnosed

As described above, the operation and maintenance device and method for a photovoltaic system provided by the present invention include cyber space, a virtual system space corresponding to the real space of the photovoltaic power generation system, and virtual space of the photovoltaic power generation system. As an administrator, by monitoring and controlling the power generation information of the corresponding photovoltaic power generation system using the surveillance avatar moving in the cyberspace, even users without professional knowledge can intuitively recognize the operation status of the photovoltaic power generation system and effectively There are advantages to managing it.

In addition, the present invention recommends an arbitrary failure by learning information on failures that have occurred in the past by type of failure and location of failure in the photovoltaic power generation system, the operator's work history for the failure, and the worker's work result. There is an advantage in that the quality of solar power generation system management can be improved by generating at least one professional avatar for each field that provides work information and operating and maintaining the solar power generation system using the information provided by the professional avatar. .

In addition, the present invention generates big data including fault information of the solar power generation system that occurred in the past and countermeasures for each type of fault, and learns the big data to create an algorithm that can automatically respond to software faults. Then, by installing it on the professional avatar, the professional avatar can automatically respond to the diagnosis result in case of a software failure, thereby simplifying the operation and maintenance procedure of the solar power generation system, and reducing the workload of managers or workers. There are advantages to reducing it.

1 is a schematic block diagram of an operation maintenance device for a photovoltaic power generation system according to an embodiment of the present invention.
2 is a schematic block diagram of a professional avatar management unit according to an embodiment of the present invention.
3 is a database structure diagram of a professional avatar management DB according to an embodiment of the present invention.
4 is a schematic block diagram of a service provider according to an embodiment of the present invention.
5 to 8 are schematic process flow charts for an operation maintenance method of a photovoltaic power generation system according to an embodiment of the present invention.
9 to 12 are diagrams for explaining examples of screens for an operation and maintenance device of a photovoltaic power generation system according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings, but will be described in detail so that those skilled in the art can easily practice the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein. On the other hand, in order to clearly describe the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification. In addition, even if detailed descriptions are omitted, descriptions of parts that can be easily understood by those skilled in the art are omitted.

Throughout the specification and claims, when a part includes a certain component, it means that it may further include other components, not excluding other components unless otherwise stated.

1 is a schematic block diagram of an operation maintenance device for a photovoltaic power generation system according to an embodiment of the present invention. Referring to FIG. 1 , an apparatus 100 for operation and maintenance of a photovoltaic system according to an embodiment of the present invention implements cyberspace, which is a virtual three-dimensional system space corresponding to the real space of the photovoltaic system, and , As a device for managing the corresponding solar power generation system using a cyber character (hereinafter referred to as 'surveillance avatar') moving in the cyberspace as a virtual manager of the solar power generation system, the monitoring avatar module 10 , data collection unit 110, big data generation unit 120, big data management DB 130, professional avatar management unit 140, professional avatar management DB 150, real-time monitoring unit 160, failure diagnosis unit ( 170), a service providing unit 180, and a control unit 190.

At this time, in the example of FIG. 1 , only configurations necessary for explaining the main characteristics of the operation and maintenance device 100 of a photovoltaic power generation system according to an embodiment of the present invention are illustrated, and general configurations are omitted. For example, in the example of FIG. 1, a system specification management DB for managing system specifications of a photovoltaic power generation system and field data management for managing field data collected in real time from each of the actual devices of the corresponding photovoltaic power generation system. Displaying a database, a cyber information management DB for managing cyber information including the cyberspace and monitoring avatars, a failure diagnosis reference information management DB for managing preset failure diagnosis reference information, and the cyberspace and monitoring avatars. Technical configurations for realizing an operation maintenance device of a general photovoltaic power generation system, such as a display device, a field data collection unit, and a user interface unit that receives a user's operation signal, are omitted from the illustration. Therefore, some of the components including the above-mentioned technical configuration are omitted for simplicity of description, and are excluded in order to implement the operation and maintenance device 100 of the photovoltaic power generation system according to an embodiment of the present invention. otherwise it is self-evident

The monitoring avatar module 10 manages and controls the monitoring avatar. That is, the surveillance avatar module 10 matches and manages the surveillance avatar with an arbitrary worker, and displays the surveillance avatar on a cyberspace displayed on a display device (not shown). To this end, the monitoring avatar module 10 uses coordinates in cyberspace designated by an external manipulation signal or the position of a worker carrying a communication terminal device equipped with the monitoring avatar module 10 (e.g., latitude/longitude coordinates, etc.) ), after determining the location of the surveillance avatar, the movement of the surveillance avatar in the cyberspace displayed on a display device (not shown) is controlled.

In addition, the monitoring avatar module 10 receives real-time power generation information (i.e., field data) (e.g., power generation amount in string units) from the real device of the photovoltaic power generation system corresponding to the position of the monitoring avatar in response to the movement of the monitoring avatar. etc.) is collected, or after detecting real-time development information of the corresponding real device from previously collected field data, it can be displayed on a display device (not shown) together with the monitoring avatar. To this end, the surveillance avatar module 10 may refer to information stored in a database unit (eg, a cyber information management DB (not shown)) that stores predefined cyberspace and surveillance avatar information.

The data collection unit 110 collects failure history information including failures occurring in the photovoltaic power generation system and countermeasures for each failure type. For example, the data collection unit 110 may collect failure information on a failure occurring in the photovoltaic power generation system, a worker's work history for the failure, and the worker's work result.

At this time, the failure information includes information on a device that has a failure/failure among actual devices constituting the photovoltaic power generation system, the level of the failure/failure, the installation location of the device where the failure/failure has occurred, the type of the failure/failure, and the failure/failure. It may include the time when the failure occurred, environment information around the device where the failure/failure occurred, and the like.

In addition, the operator's work history is the operator's work information for solving the failure/failure, and may include parts replacement or setting value change, registered by the operator's input information, or by a system management algorithm. can be automatically recognized.

On the other hand, the work result is a processing result for the work history, and may indicate completion of parts replacement or completion of setting value change, and may be registered by the operator's input information or automatically recognized by a system management algorithm. Alternatively, the operating state of the corresponding device before and after the work history may be compared/analyzed to indicate the degree of improvement of the failure or failure (eg, 80% recovery from failure state).

In addition, the data collection unit 110 may further collect real-time operation information for each actual device of the photovoltaic power generation system and failure diagnosis results accordingly.

To this end, the data collection unit 110 has a communication interface for communicating with each of the photovoltaic power generation systems, collects the information from each of the photovoltaic power generation systems through a communication network, or collects the previously collected information. Failure diagnosis results according to the failure information, work details, work results, and real-time operation information for each of a plurality of photovoltaic power generation systems may be collected from an external storage device (eg, USB) to be stored.

In particular, the data collection unit 110 may collect real-time generation information (eg, generation amount in string units, etc.) of the corresponding solar string from the string optima included in the solar power generation systems.

The big data generation unit 120 generates big data using the failure history information collected during a preset information collection period (eg, 1 month, 3 months, 6 months, etc.), and stores the results in a big data management DB. Save to (130).

At this time, the big data generating unit 120 provides the failure information, the work history, and the work result for each of all failures occurring in any one of the real devices constituting each of the at least one photovoltaic power generation system. Failure big data matching the photovoltaic power generation system or diagnosis big data matching the real-time operation information of each actual device of the photovoltaic system with the failure diagnosis result according thereto can be generated and stored in the big data management DB 130.

The professional avatar management unit 140 learns the big data, generates at least one professional avatar for each field for operating the solar power generation system, and registers the professional avatar in the professional avatar management DB 150.

At this time, the 'professional avatar' refers to an avatar specialized in various fields (eg, by device, by type of failure, etc.) for maintenance of the solar power generation system. An 'expert avatar' may be used as a concept of an expert in a specific field.

To this end, the professional avatar management unit 140 classifies the big data, including various types of failure occurrence details, work details, work results, failure diagnosis results by real-time power generation information, etc., according to various preset criteria, and data for each classification. After learning, as a result, it is possible to generate professional avatars for each field.

For example, the professional avatar management unit 140 classifies the failure big data by type of failure or by location where the failure occurred (type of device or physical location, etc.), learns data for each category, and as a result, classifies data by field. After creating an expert avatar or learning the diagnostic big data, a diagnostic avatar of a failure diagnosis expert may be created as a result. At this time, the 'diagnosis avatar' may be defined as an avatar specialized in diagnosis for each device for professionally diagnosing whether or not a failure is diagnosed based on real-time power generation information of each device constituting the solar power generation system.

That is, as a result of learning the failure big data, the professional avatar management unit 140 determines a professional avatar according to the type of device, such as a professional avatar in the solar module field or a string optima field, or a professional avatar for improving output degradation, leakage. At least one professional avatar, such as a professional avatar according to a technology field, such as a current improvement professional avatar, or the diagnostic avatar may be created and managed.

Meanwhile, after the professional avatars are created, the professional avatar management unit 140 determines the rating of each professional avatar or the career of each professional avatar based on service provision details for each professional avatar and evaluation details of users. You can perform follow-up management, such as management or changing the field of expertise.

An example of the configuration of the specialized avatar management unit 140 for this purpose is illustrated in FIG. 2 . 2 is a schematic block diagram of a professional avatar manager according to an embodiment of the present invention. Referring to FIG. 2, the professional avatar manager 140 includes a big data classification unit 141 and a big data learning unit 142. , a professional avatar creation unit 143, and a professional avatar registration unit 144.

The big data classification unit 141 classifies the big data according to at least one preset classification criterion. For example, the big data classification unit 141 may classify the failure big data by type of failure or location of failure in the photovoltaic system. At this time, the classification criterion of the big data may be a criterion for determining a specialized field for each professional avatar.

The big data learning unit 142 learns the big data for each classification criterion, and based on the classified failure big data, learns work contents and work results for each failure type or failure occurrence location, or the diagnosis big data Based on the data, it is possible to learn whether or not a failure has occurred and a result of diagnosing the failure type according to the real-time operation information of each of the real devices.

The expert avatar creation unit 143 generates the expert avatar based on the learning result. That is, the expert avatar generator 143 generates at least one piece of recommended work information for each classification criterion based on the learning result of the failure big data, and matches the classification criterion with the recommended work information to generate a specialized avatar for each field. . For example, the professional avatar creation unit 143 creates at least one piece of recommended work information for each type of failure or location where the failure occurs, and then matches the recommended work information for each type of failure or location where the failure occurs to provide a professional avatar for each field. can create

In addition, the professional avatar generation unit 143 generates an automatic response algorithm capable of automatically responding to software failures based on the failure history information collected for each solar power generation system, and then converts the automatic response algorithm to the software failure. It can be mounted on avatars specialized in the field. At this time, the automatic response algorithm may match and store work history information having the highest improvement efficiency or the highest evaluation result of the user among the work details performed by the operator for failure recovery for each type of failure by matching it to the corresponding failure. there is. Meanwhile, the automatic response algorithm may go through an approval procedure from the user before the automatic response, or store automatic response history information after the automatic response so that the user can check it. In addition, when an arbitrary first automatic correspondence algorithm is installed in the first professional avatar, the first automatic correspondence algorithm is executed in the background of the photovoltaic power generation system operation and maintenance device in response to selection of the first professional avatar. In addition, it is possible to automatically respond to software failures, such as detecting whether there is a software failure and automatically changing a preset setting value according to the result.

Alternatively, the expert avatar generation unit 143 may create a diagnostic avatar for each device by matching the failure diagnosis result for each real-time operation information of the real device based on the learning result of the diagnostic big data. For example, when a failure due to leakage current is diagnosed, replacement of the device is recommended, or when a change in the environment around the device (eg, change in temperature/humidity, etc.) is detected, a change in the set value for failure diagnosis (eg, current change of the reference value of humidity for determining leakage, etc.), the professional avatar creation unit 143 creates various tasks that can be tried for functional recovery for each type of malfunction as recommended work information for each type of malfunction, so that the professional avatar in the corresponding field You can create an avatar.

The specialized avatar registration unit 144 registers the generated specialized avatars for each field or diagnosis avatar for each device in the specialized avatar management DB 150 .

On the other hand, the professional avatar management unit 140 collects the recommended work information, the user's evaluation information on the execution result of the automatic response algorithm, and work result information (eg, improvement efficiency information, etc.) and matches them to the corresponding professional avatar. It may further include a specialized avatar evaluation unit (not shown) that stores the avatar by making it available.

In addition, the professional avatar management unit 140 may evolve the performance of a corresponding professional avatar by reflecting the inspection result using the previously created professional avatar. For example, the professional avatar management unit 140 assigns a weight to the recommended job information according to the level of improved improvement efficiency as a result of inspection of the previously created professional avatar or the user's evaluation score, and preferentially gives the recommended job information with a high weight. It is possible to evolve the performance of the corresponding specialized avatar by deleting recommended job information with a low weight or recommended as . Alternatively, the expert avatar management unit 140 may evolve the performance of the corresponding professional avatar by updating the contents of the automatic response algorithm according to the improvement efficiency of the processing result of the automatic response algorithm installed in a certain expert avatar or the user's evaluation score. can

3 is a database structure diagram of a professional avatar management DB according to an embodiment of the present invention, and an example of the database structure of the professional avatar management DB 150 registered by the professional avatar registration unit 144 is shown. Referring to FIG. 3, the professional avatar management DB 150 includes an identification code field 151, an avatar name field 152, a career field 153, a professional field 154, a matching worker information field 155, and and an evaluation score field 156.

The identification code field 151 stores an identification code for identifying an avatar, and the avatar name field 152 stores the name of the corresponding avatar. At this time, the identification code and the name of the avatar may be given from the specialized avatar creation unit 143 when the avatar is created, and the avatar name is preferably determined to predict the field of the avatar.

The career field 153 stores the career of the avatar, and the career can be managed by either the time elapsed from the time the avatar was first created or the time elapsed from the time the avatar was first called. .

The field of expertise 154 stores the field of expertise of the avatar, and the field of expertise can be determined by classification of big data learned to create the avatar. For example, in the case of an avatar determined by learning failure big data classified as failure information of string optima, its field of expertise may be string optima.

The matching worker information field 155 is information of a worker matched with a corresponding avatar, and may store expert information matched for each specialized avatar. At this time, the expert matched with the avatar is information on the worker who actually performed the recovery process for the failure of the solar power generation system based on the recommended work information of the avatar, and different experts are matched according to the operating time of the avatar. can

The evaluation score field 156 stores an evaluation score for a corresponding avatar, and may store a cumulative evaluation result by the professional avatar evaluation unit (not shown). For example, the evaluation score field 156 may store a user's cumulative evaluation score for a corresponding avatar.

Meanwhile, although not exemplified in FIG. 3 , the professional avatar management DB 150 may additionally include various pieces of information for managing professional avatars. For example, the professional avatar management DB 150 includes images of each of the professional avatars, information on recommended work matched to the corresponding professional avatar, an automatic response algorithm loaded in the corresponding professional avatar, or when the inspection service is used by calling the professional avatar. Cost information required may be further included.

The real-time monitoring unit 160 monitors real-time operation information of an arbitrary first reality device corresponding to the location of the monitoring avatar in response to the movement of the monitoring avatar. To this end, the real-time monitoring unit 160 receives location information of the monitoring avatar and real-time development information of a reality device (eg, first reality device) corresponding to the location information of the monitoring avatar from the monitoring avatar module 10, You can monitor that information.

The failure diagnosis unit 170 diagnoses whether or not a failure of the first reality device has occurred and the type of failure based on the real-time operation information being monitored by the real-time monitoring unit 160 . To this end, the failure diagnosis unit 170 diagnoses the failure of the first reality device by referring to the failure diagnosis information set in advance, or the failure of the first reality device among the diagnostic avatars for each device created by the professional avatar management unit 140. It is possible to diagnose a failure based on the real-time operation information of the first reality device by calling a diagnosis avatar generated to diagnose .

The service providing unit 180 provides a specialized avatar service based on the failure diagnosis result. To this end, the service providing unit 180 may select one of the professional avatars for each field and provide operation and maintenance services for the photovoltaic power generation system using the selected professional avatar.

An example of the configuration of the service provider 180 for this purpose is illustrated in FIG. 4 . 4 is a schematic block diagram of a service provider according to an embodiment of the present invention. Referring to FIG. 4, the service provider 180 includes a candidate avatar selection unit 181, a service information detection unit for each specialized avatar 182), and a service execution unit 183 for each specialized avatar.

The candidate avatar selector 181 selects and displays at least one of the specialized avatars for each field as a candidate avatar based on the failure diagnosis result of the failure diagnosis unit 170 . At this time, the candidate avatar selection unit 181 determines the type of failure or the occurrence location of the failure from the failure diagnosis result, and selects at least one corresponding professional avatar among the specialized avatars registered in the professional avatar management DB 150. can be selected as a candidate avatar. In particular, the candidate avatar selection unit 181 selects candidate avatars based on the professional avatar evaluation results, and selects a predetermined number of professional avatars whose evaluation scores of professional avatars are equal to or higher than a preset reference value, or a predetermined number of professional avatars having excellent evaluation results. It can be selected as a candidate avatar. To this end, the candidate avatar selector 181 may refer to the evaluation score field 156 of the specialized avatar management DB 150.

The service information detection unit 182 for each professional avatar selects one professional avatar among the candidate avatars based on the user's selection information, and recommends job information matched to the selected professional avatar from the professional avatar management DB 150. or at least one of the automatic correspondence algorithms. That is, the professional avatar-specific service information detection unit 182 may detect at least one of recommended work information or an automatic response algorithm matched to the avatar when the avatar is created.

The service execution unit 183 for each professional avatar provides the recommended job information to the user using the selected professional avatar or executes the detected automatic response algorithm. At this time, the professional avatar-specific service execution unit 183 detects and provides the information corresponding to the failure diagnosis result among the recommended work information matched to the selected professional avatar to the user, and displays the corresponding professional avatar on the display unit (not shown). The corresponding information can be provided to the user by displaying it together or by expressing it with the avatar's voice through a speaker unit (not shown). In addition, the service execution unit 183 for each professional avatar may execute an automatic response algorithm matched to the selected professional avatar, and cause the automatic response algorithm to operate in the background of the operation and maintenance device 100 of the photovoltaic power generation system. there is.

The control unit 190 controls the operation of the operation and maintenance device 100 of the solar power generation system based on a preset control algorithm, but the information collected through the data collection unit 110 or the monitoring avatar module 10 Reflecting the information transmitted through , each of the devices constituting the operation and maintenance device 100 of the photovoltaic power generation system is controlled to operate as described above.

5 to 8 are schematic process flow charts for an operation maintenance method of a photovoltaic power generation system according to an embodiment of the present invention. Referring to FIGS. 1 to 8 , a method for operating and maintaining a photovoltaic power generation system according to an embodiment of the present invention will be described.

First, in step S100, the big data generator 120 generates big data using various information collected from the photovoltaic power generation system. That is, in step S100, the big data generator 120 performs information collected by the data collector 110 during a preset information collection period (eg, 1 month, 3 months, 6 months, etc.) (ie, the photovoltaic power generation). Failure history information including failure information on failures occurring in the system, operator's work details for the failures, and the worker's work results, real-time operation information for each actual device of the photovoltaic power generation system, and failure diagnosis results accordingly ) to generate big data, and the result is stored in the big data management DB (130).

To this end, the method of the present invention, prior to step S100, may further include a step for collecting the data. That is, a data collection step of collecting failure history information including failures occurring in the photovoltaic power generation system and countermeasures for each failure type may be further performed. At this time, the data collection step is performed by the data collection unit 110 illustrated in FIG. 1, and since its specific details have been described with reference to FIG. 1, redundant description will be omitted.

Meanwhile, the big data generating unit 120 may generate failure big data in step S110 and diagnostic big data in step S120. That is, in step S110, the big data generating unit 120, for each of all failures occurring in any one of the real devices constituting each of the at least one solar power generation system, the failure information, the work details, and generating failure big data matching the work results, and in step S120, the big data generating unit 120 matches the real-time operation information of each real device of the photovoltaic system with the failure diagnosis result according to diagnosis big data. generate

In step S200, the professional avatar management unit 140 learns the big data, generates at least one professional avatar for each field for operating the solar power generation system, and stores the result in the professional avatar management DB 150. . To this end, the professional avatar management unit 140 classifies the failure big data in step S210, and classifies the failure big data according to various preset classification criteria (eg, by failure type or failure occurrence location). Classify, and in step S220, learn the big data for each classification criterion, based on the classified failure big data, learn work contents and work results for each failure type or failure occurrence location, and in step S230, A professional avatar is created based on the learning result.

To this end, in step S230, the professional avatar creation unit 143 generates at least one piece of recommended work information for each classification criterion based on the learning result of the failure big data, and matches the classification criterion and the recommended work information to create Create professional avatars. For example, the professional avatar creation unit 143 creates at least one piece of recommended work information for each type of failure or location where the failure occurs, and then matches the recommended work information for each type of failure or location where the failure occurs to provide a professional avatar for each field. can create

In addition, the professional avatar generation unit 143 generates an automatic response algorithm capable of automatically responding to software failures based on the failure history information collected for each solar power generation system, and then converts the automatic response algorithm to the software failure. It can be mounted on avatars specialized in the field. At this time, the automatic response algorithm may match and store work history information having the highest improvement efficiency or the highest evaluation result of the user among the work details performed by the operator for failure recovery for each type of failure by matching it to the corresponding failure. there is. Meanwhile, the automatic response algorithm may go through an approval procedure from the user before the automatic response, or store automatic response history information after the automatic response so that the user can check it. In addition, when an arbitrary first automatic correspondence algorithm is installed in the first professional avatar, the first automatic correspondence algorithm is executed in the background of the photovoltaic power generation system operation and maintenance device in response to selection of the first professional avatar. In addition, it is possible to automatically respond to software failures, such as detecting whether there is a software failure and automatically changing a preset setting value according to the result.

Alternatively, the expert avatar generation unit 143 may create a diagnostic avatar for each device by matching the failure diagnosis result for each real-time operation information of the real device based on the learning result of the diagnostic big data. For example, when a failure due to leakage current is diagnosed, replacement of the device is recommended, or when a change in the environment around the device (eg, change in temperature/humidity, etc.) is detected, a change in the set value for failure diagnosis (eg, current change of the reference value of humidity for determining leakage, etc.), the professional avatar creation unit 143 creates various tasks that can be tried for functional recovery for each type of malfunction as recommended work information for each type of malfunction, so that the professional avatar in the corresponding field You can create an avatar.

In addition, in step S240, the professional avatar management unit 140 registers the generated professional avatars for each field in the professional avatar management DB 150.

On the other hand, in step S250, the professional avatar management unit 140 learns whether or not a failure has occurred and the diagnosis result of the type of failure according to the real-time operation information of each of the real devices based on the diagnosis big data, and in step S260, the learning result Based on this, a diagnostic avatar for each device is created by matching the failure diagnosis result for each real-time operation information of the real device, and in step S270, the diagnostic avatar for each device is registered in the professional avatar management DB 150.

In addition, in step S280, the professional avatar management unit 140 collects the recommended job information, the user's evaluation information on the execution result of the automatic response algorithm, and job result information, matches them to the corresponding professional avatar, and stores them.

A more specific operation of the professional avatar manager 140 for this purpose has been described with reference to FIGS. 1 to 4, and therefore, redundant description will be omitted.

Meanwhile, in step S300, the real-time monitoring unit 160 monitors real-time operation information of an arbitrary first reality device corresponding to the position of the monitoring avatar in response to the movement of the monitoring avatar, and in step S400, the failure diagnosis unit 170 diagnoses whether or not a failure of the first reality device has occurred and the type of failure based on the real-time operation information, and calls a diagnostic avatar for diagnosing a failure of the first reality device or preset failure diagnosis information , Diagnose whether or not a failure of the first reality device has occurred and the type of failure based on the real-time operation information of the first reality device. For this purpose, since more specific operations of the real-time monitoring unit 160 and the failure diagnosis unit 170 have been described with reference to FIGS. 1 to 4, redundant description will be omitted.

In addition, in step S500, the service providing unit 180 provides a professional avatar service based on the failure diagnosis result. To this end, in step S500, the service providing unit 180 may select one of the professional avatars for each field, and then provide operation and maintenance services for the photovoltaic power generation system using the selected professional avatar.

To this end, in step S510, the candidate avatar selection unit 181 of the service provider 180 selects and displays at least one of the professional avatars for each field registered as a candidate avatar, based on the failure diagnosis result. The type or location of failure may be determined, and at least one corresponding professional avatar among the professional avatars registered in the professional avatar management DB 150 may be selected as a candidate avatar. In particular, the candidate avatar selection unit 181 selects candidate avatars based on the professional avatar evaluation results, and selects a predetermined number of professional avatars whose evaluation scores of professional avatars are equal to or higher than a preset reference value, or a predetermined number of professional avatars having excellent evaluation results. It can be selected as a candidate avatar. To this end, the candidate avatar selector 181 may refer to the evaluation score field 156 of the specialized avatar management DB 150.

In step S520, the service information detection unit 182 for each professional avatar of the service providing unit 180 selects one professional avatar among the candidate avatars based on the user's selection information, and from the professional avatar management DB 150, At least one of recommended work information matched with the selected professional avatar or an automatic correspondence algorithm is detected. That is, the professional avatar-specific service information detection unit 182 may detect at least one of recommended work information or an automatic response algorithm matched to the avatar when the avatar is created.

In step S530, the service execution unit 183 for each professional avatar of the service providing unit 180 provides the recommended job information to the user using the selected professional avatar or executes the detected automatic response algorithm. At this time, the professional avatar-specific service execution unit 183 detects and provides the information corresponding to the failure diagnosis result among the recommended work information matched to the selected professional avatar to the user, and displays the corresponding professional avatar on the display unit (not shown). The corresponding information can be provided to the user by displaying it together or by expressing it with the avatar's voice through a speaker unit (not shown). In addition, the service execution unit 183 for each professional avatar may execute an automatic response algorithm matched to the selected professional avatar, and cause the automatic response algorithm to operate in the background of the operation and maintenance device 100 of the photovoltaic power generation system. there is.

A more specific operation of the service providing unit 180 for this purpose is the same as described with reference to FIGS. 1 to 4, and therefore, redundant description will be omitted.

9 to 12 are diagrams for explaining examples of screens for the operation and maintenance device of a photovoltaic power generation system according to an embodiment of the present invention, and FIGS. A screen example for the case where the solar power generation system operation and maintenance device of the present invention is implemented is shown, and FIGS. 11 and 12 show screen examples of the display device included in the solar power generation system operation and maintenance device.

9 shows the failure diagnosis result of the reality device (eg, string #5) corresponding to the location of the worker, together with the monitoring avatar A, when the operator visits the site while carrying the communication terminal device. At the same time as displaying on the display unit of the device, a screen of a communication terminal device displaying candidate avatars selected to deal with the failure in a pop-up message (B) is illustrated, and FIG. 10 illustrates the candidate avatar displayed in the pop-up message (B). When the user selects one of them, the screen of the communication terminal device displaying the contents of inspection using the selected professional avatar is exemplified.

11 is provided in the solar power generation system operation and maintenance device, and displays real-time power generation information of the corresponding solar power generation system, but the failure of the reality device (eg, string # 5) corresponding to the position of the monitoring avatar (C) A screen displaying the diagnosis result together with the monitoring avatar (C) and displaying candidate avatars selected to deal with the failure in a pop-up message (D) is exemplified, and FIG. When the user selects one of the displayed candidate avatars, the screen of the display unit for displaying inspection details using the selected specialized avatar is exemplified.

At this time, the candidate avatars displayed in the pop-up message (B or D) may be specialized avatars in different fields to respond to the failure diagnosis result, or specialized avatars in the same field but having different experiences or evaluation scores.

Therefore, among the candidate avatars, the diagnosis result or recommended check content may differ within an allowable range according to the professional avatar selected by the user. In this case, the service cost may be set differently according to the diagnosis result or the accuracy of the inspection details or the evaluation score, so that the user can select an efficient diagnosis avatar.

In addition, the candidate avatars may be displayed in the form of a pop-up message as in the examples of FIGS. 9 and 11, or may be displayed at a pre-designated location on the screen.

On the other hand, as illustrated in FIG. 12 , when a setting value needs to be changed, the setting value can be automatically changed using an automatic response algorithm installed in the corresponding professional avatar.

As described above, the present invention uses cyberspace, which is a virtual system space corresponding to the real space of the photovoltaic power generation system, and a monitoring avatar moving in the cyberspace as a virtual manager of the photovoltaic power generation system. By monitoring and controlling the power generation information of the system, it has a feature that allows users without specialized knowledge to intuitively recognize and effectively manage the operating state of the photovoltaic power generation system.

In addition, the present invention recommends an arbitrary failure by learning information on failures that have occurred in the past by type of failure and location of failure in the photovoltaic power generation system, the operator's work history for the failure, and the worker's work result. At least one professional avatar providing job information is created, and the solar power generation system is operated and maintained using the information provided by the professional avatar, thereby enhancing the quality of solar power generation system management.

In addition, the present invention can simplify the operation and maintenance of the solar power generation system by allowing the professional avatar to automatically respond to the diagnosis result in the event of a software failure based on the automatic response algorithm installed in the professional avatar, , it has a feature that can reduce the workload of managers or workers.

In general, due to the wide-area installation environment of photovoltaic power generation facilities, it is difficult to easily find the point of failure when an error occurs, and even if the point of failure is found, if the type of accident is not immediately known, it is difficult to repair the failure in the state of live power generation. In the case of using the avatar of the present invention, daily inspection records (eg, sound, photo, video, sight, etc.) can be preserved based on big data by converting and storing diagnosis or inspection history using specialized avatars. Due to this, there is a feature that can easily obtain failure repair information.

In addition, by using the avatar management module of the present invention, data for each string level based on the location of the avatar may be comprehensively collected and transmitted to the administrator.

In the above, the embodiments of the present invention have been described, but the scope of the present invention is not limited thereto, and it is recognized that the present invention is easily changed from the embodiments to those of ordinary skill in the art to which the present invention belongs and is equivalent. including all changes and modifications within the scope of

10: surveillance avatar module 100: operation maintenance device
110: data collection unit 120: big data generation unit
130: Big data management DB 140: Professional avatar management department
141: big data classification unit 142: big data learning unit
143: professional avatar generation unit 144: professional avatar registration unit
150: professional avatar management DB 160: real-time monitoring unit
170: fault diagnosis unit 180: service provision unit
181: candidate avatar selection unit 182: service information detection unit for each professional avatar
183: professional avatar-specific service execution unit

Claims (16)

Implementing cyberspace, a virtual 3D system space corresponding to the real space of the photovoltaic power generation system, and using a monitoring avatar moving in the cyberspace as a virtual manager of the photovoltaic power generation system, the corresponding photovoltaic power generation system In the operation maintenance device of the photovoltaic power generation system to be managed,
a data collection unit that collects failure history information including failures occurring in the photovoltaic power generation system and countermeasures for each failure type;
a big data storage unit generating and storing failure big data using the failure history information collected during a preset information collection period;
a professional avatar management unit that learns the failure big data to generate and register at least one professional avatar for each field;
a real-time monitoring unit that monitors real-time operation information of an arbitrary first reality device corresponding to the location of the monitoring avatar in response to the movement of the monitoring avatar;
a failure diagnosis unit for diagnosing whether or not a failure of the first reality device has occurred and the type of failure based on preset failure diagnosis information and the real-time operation information; and
After selecting one of the professional avatars for each field based on the failure diagnosis result, operation and maintenance are performed using the selected professional avatar. Including a service provider that provides services,
The professional avatar management department
a big data classification unit that classifies the faulty big data according to at least one preset classification criterion;
a big data learning unit learning the failure big data for each classification criterion;
a professional avatar creation unit generating at least one piece of recommended job information for each classification criterion based on the learning result of the big data learning unit, and generating a professional avatar for each field by matching the classification criterion with the recommended job information; and
A professional avatar registration unit for registering the generated professional avatars for each field;
The professional avatar creation unit
After creating an automatic response algorithm capable of automatically responding to software failures based on the failure history information, the automatic response algorithm is installed on a specialized avatar in the field to which the software failure belongs. Solar power generation system, characterized in that of operation and maintenance devices. delete delete The method of claim 1, wherein the service provider
a candidate avatar selecting unit that selects and displays at least one of the professional avatars for each field as a candidate avatar based on the failure diagnosis result;
a service information detection unit for each professional avatar, which selects one of the candidate avatars based on user selection information and detects at least one of recommended work information matched to the selected professional avatar or an automatic response algorithm; and
and a service execution unit for each expert avatar that provides the recommended job information to the user using the selected expert avatar or executes the detected automatic response algorithm. The method of claim 4, wherein the professional avatar management unit
Further comprising a professional avatar evaluation unit that collects the recommended job information or the user's evaluation information for the execution result of the automatic response algorithm, and the job result information, matches them with corresponding professional avatars, and stores them;
The candidate avatar selection unit
The operation and maintenance device of the photovoltaic power generation system, characterized in that the candidate avatar is selected based on evaluation information of the user who has selected the professional avatar and evaluation results of the avatar including work result information. The method of claim 1, wherein the data collection unit
Further collecting real-time operation information for each actual device of the photovoltaic power generation system and failure diagnosis results accordingly,
The big data storage unit
The operation and maintenance device of the photovoltaic power generation system, characterized in that further generating diagnostic big data by matching the collected real-time operation information for each real device and the failure diagnosis result thereof. The method of claim 6, wherein the big data learning unit
Based on the diagnosis big data, learn whether or not a failure has occurred and a diagnosis result of a failure type according to real-time operation information of each of the real devices,
The professional avatar creation unit
Based on the learning result, a diagnosis avatar for each device is created by matching a failure diagnosis result for each real-time operation information of the real device;
The professional avatar registration unit
An operation maintenance device for a photovoltaic power generation system, characterized in that for registering the diagnosis avatar for each device. The method of claim 6, wherein the failure diagnosis unit
Solar energy characterized by calling a diagnosis avatar for diagnosing a failure of the first reality device, and diagnosing whether or not a failure of the first reality device has occurred and the type of failure based on real-time operation information of the first reality device Operation and maintenance device of power generation system. Implementing cyberspace, a virtual 3D system space corresponding to the real space of the photovoltaic power generation system, and using a monitoring avatar moving in the cyberspace as a virtual manager of the photovoltaic power generation system, the corresponding photovoltaic power generation system In the operation and maintenance method of the solar power generation system to be managed,
A data collection step of collecting failure history information including failures occurring in the photovoltaic power generation system and countermeasures for each failure type;
a big data generation step of generating failure big data using the failure history information collected during a preset information collection period;
a professional avatar management step of generating and registering at least one professional avatar for each field by learning the failure big data;
a real-time monitoring step of monitoring real-time operation information of an arbitrary first reality device corresponding to a location of the monitoring avatar in response to movement of the monitoring avatar;
a failure diagnosis step of diagnosing whether or not a failure of the first reality device has occurred and a failure type based on preset failure diagnosis information and the real-time operation information; and
A service providing step of selecting one of the professional avatars for each field based on the failure diagnosis result and then providing operation maintenance service using the selected professional avatar;
The professional avatar management step
a failure big data classification step of classifying the failure big data according to at least one preset classification criterion;
a failure big data learning step of learning the failure big data for each classification criterion;
a professional avatar creation step of generating at least one piece of recommended work information for each classification criterion based on the learning result, and generating a specialized avatar for each field by matching the classification criterion with the recommended work information; and
A professional avatar registration step of registering the generated professional avatars for each field;
The professional avatar creation step is
After creating an automatic response algorithm capable of automatically responding to software failures based on the failure history information, the automatic response algorithm is installed on a specialized avatar in the field to which the software failure belongs. Solar power generation system, characterized in that operation maintenance method. delete delete The method of claim 9, wherein the service providing step
a candidate avatar selection step of selecting and displaying at least one of the professional avatars for each field as a candidate avatar based on the failure diagnosis result;
a service information detection step for each professional avatar, which selects one of the candidate avatars based on the user's selection information and detects at least one of recommended work information or an automatic correspondence algorithm matched to the selected professional avatar; and
and a service execution step for each expert avatar providing the recommended job information to a user using the selected expert avatar or executing the detected automatic response algorithm. 13. The method of claim 12, wherein the professional avatar management step
Further comprising a professional avatar evaluation step of collecting the recommended job information, the user's evaluation information on the execution result of the automatic response algorithm, and the job result information, matching them with the corresponding professional avatars, and storing them;
The step of selecting the candidate avatar
and selecting the candidate avatar based on evaluation information of the user who has selected the professional avatar and evaluation results of the avatar including work result information. The method of claim 9, wherein the data collection step
Further collecting real-time operation information for each actual device of the photovoltaic power generation system and failure diagnosis results accordingly,
The big data generation step is
The operation and maintenance method of the photovoltaic power generation system, characterized in that further generating diagnostic big data by matching the collected real-time operation information for each real device and the failure diagnosis result thereof. 15. The method of claim 14, wherein the avatar management step
a diagnostic big data learning step of learning whether or not a failure has occurred and a result of diagnosing a failure type according to real-time operation information of each of the real devices based on the diagnostic big data;
a diagnosis avatar generation step of generating a diagnosis avatar for each device by matching failure diagnosis results for each real-time operation information of the real device based on the learning result; and
The operation and maintenance method of the photovoltaic power generation system, further comprising a diagnostic avatar registration step of registering the diagnostic avatar for each device. 15. The method of claim 14, wherein the failure diagnosis step
Solar energy characterized by calling a diagnosis avatar for diagnosing a failure of the first reality device, and diagnosing whether or not a failure of the first reality device has occurred and the type of failure based on real-time operation information of the first reality device Operation and maintenance method of power generation system.

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