surveillance system

Abstract

The present invention provides a monitoring system that can extract and monitor power generation facilities in which serious anomalies may occur in the future.　This monitoring system comprises: a plurality of power generation facilities; an error information creating unit that creates error information on the power generation facilities; a data accumulation unit that accumulates installation information and error information on the power generation facilities; a prediction unit that predicts a failure sign group presenting a sign of a failure from among the plurality of power generation facilities on the basis of the error information on each power generation facility; and an extraction unit that identifies common specific information in the installation information on the power generation facilities predicted as the failure sign group and extracts, as a failure candidate group, the power generation facilities including the specific information in the installation information from among the plurality of power generation facilities.

Description

[Technical Field]

[0001] The present invention relates to a monitoring system that extracts and monitors power generation equipment that may be at risk of failure based on power generation equipment that shows signs of failure. [Background technology]

[0002] In recent years, photovoltaic power generation systems have rapidly become popular as a clean energy source that does not emit carbon dioxide. As solar power generation systems become more widespread, there have been rare cases of fires caused by malfunctions in solar power generation systems. Solar power generation systems and other power generation equipment often have their power generation modules installed outdoors, such as on roofs, and it takes a considerable amount of time for indoor fire detectors in buildings to respond. As a result, there are concerns that residents may not be able to escape in time, and that in the event of a fire, the response costs for home builders will be high.

[0003] Therefore, for example, Patent Document 1 discloses a method for early detection of failures that could cause serious accidents such as fires. The photovoltaic power generation system in Patent Document 1 detects a decrease in power generation due to contamination or failure of a photovoltaic panel, and compares the amount of power generation by the power generation panel in the past, or the amount of power generation by other power generation systems, or the amount of power generation by other power generation panels with the amount of power generation over a predetermined period close to the current time. This makes it possible to detect a decrease in the amount of power generation by a photovoltaic panel regardless of weather conditions or sunlight conditions, thereby reducing false detections. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2014-60365 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the solar power generation system of Patent Document 1 determines whether an abnormality occurs in each device after a serious abnormality occurs in that device, which poses a problem that the risk of fire cannot be determined unless a serious abnormality actually occurs.

[0006] Therefore, an object of the present invention is to provide a monitoring system that can extract and monitor power generation facilities that may experience a serious abnormality in the future. [Means for solving the problem]

[0007] One aspect of the present invention for solving the above-mentioned problems is a monitoring system comprising a plurality of power generation facilities, an error information creation unit that creates error information for each power generation facility, a data storage unit that stores installation information and error information for each power generation facility, a prediction unit that predicts a group of failure signs that indicate signs of a failure from among the plurality of power generation facilities based on the error information of each power generation facility, and an extraction unit that identifies specific information common to the group of failure signs and the installation information of the predicted power generation facilities, and extracts power generation facilities from the plurality of power generation facilities that include the specific information in their installation information as a group at risk of failure.

[0008] According to this aspect, common specific information is extracted from the installation information of power generation equipment belonging to a failure symptom group that has shown a failure symptom, and power generation equipment including the specific information as installation information is extracted as a failure potential group, so that failure potential groups that may experience a serious abnormality in the future can be monitored, and as a result, the occurrence of a serious abnormality in the future can be prevented.

[0009] A preferred aspect is to have a score assignment unit that assigns a score to each piece of error information, and the prediction unit accumulates the scores of each piece of error information for each power generation facility, and predicts that power generation facilities whose total score is greater than or equal to a predetermined threshold value are part of the group of failure symptoms.

[0010] According to this aspect, a score is assigned to each piece of error information to weight the error information, and a group of failure symptoms is predicted based on the total score, making it possible to more accurately identify power generation equipment that is likely to experience a serious abnormality in the future.

[0011] In a more preferred aspect, the error information includes an error code, the score assignment unit assigns a score to the error code, and the prediction unit accumulates the scores corresponding to each error code for each power generation facility, and predicts that the power generation facility for which the total score of the error information in the first period is equal to or greater than a predetermined threshold value is the group of failure symptoms from among the plurality of power generation facilities.

[0012] According to this aspect, a score is assigned to each error code, and the score can be weighted according to the cause of the error code, making it possible to more accurately identify power generation equipment that may experience a serious abnormality in the future.

[0013] In a more preferred aspect, the scores are weighted and set based on the safety of the power generation facility.

[0014] According to this aspect, different scores are assigned to different types of error information, and scores are assigned based on safety. For example, by assigning a high score to information with low safety (high probability of a failure occurring) and a low score to information with high safety (low probability of a failure occurring), it is possible to accurately detect signs of a failure.

[0015] In a more preferred aspect, the power generation facility is connected to a management server via a network, and the error information includes communication error information linked to an error code and communication information regarding the communication status between the power generation facility and the management server.

[0016] In a more preferred aspect, the power generation facility has one or more power generation modules, and the error information includes power generation error information that links an error code with power generation information regarding the power generation amount of the power generation module.

[0017] According to the above aspect, it is possible to more accurately identify power generation facilities that are likely to experience a serious abnormality in the future.

[0018] In a preferred aspect, the installation information includes at least one information selected from the group consisting of manufacturing information regarding the manufacture of each power generation facility, provision information regarding the provision of each power generation facility, construction information regarding the construction of the power generation facility, user information regarding users of the power generation facility, and environmental information regarding the installation environment of the power generation facility.

[0019] According to this aspect, it is easy to extract specific information from installation information.

[0020] In a preferred aspect, the system has a score assignment unit that assigns a score to each piece of error information, and for each power generation equipment belonging to the failure potential group, calculates a total score at predetermined time intervals by accumulating the scores of each piece of error information, and calculates a moving average value of the total score of the error information, and is equipped with a display unit that displays the time series changes of the moving average value of the power generation equipment belonging to the failure potential group.

[0021] According to this aspect, the display unit shows the transition of the moving average value of the total score of potential failures, making it easy to predict the tendency for serious abnormalities to occur in the future.

[0022] A preferred aspect is to have a score assignment unit that assigns a score to each piece of error information, and for each power generation equipment belonging to the failure potential group, to add up the scores of each piece of error information to calculate a total score for each specified time period, and to calculate an average value of the total scores for each second period, and to have a display unit that displays the time series change in the average value of the total scores for the power generation equipment belonging to the failure potential group.

[0023] According to this aspect, the display unit displays the transition of the average value of the total score of the potential failure group, so that if a failure occurs, it is easy to visually identify the point in time at which the failure occurred.

[0024] In a preferred aspect, the extraction unit identifies multiple pieces of specific information that are common to the group of failure symptoms and the installation information of the predicted power generation equipment, and extracts power generation equipment as a failure potential group for each piece of specific information from the multiple pieces of power generation equipment.

[0025] According to this aspect, a potential failure group is extracted for each piece of specific information, so that when a failure occurs, it is easy to link the cause of the failure to the specific information. [Effects of the Invention]

[0026] According to the monitoring system of the present invention, it is possible to extract and monitor power generation facilities that may experience a serious abnormality in the future. [Brief explanation of the drawings]

[0027] [Figure 1] 1 is a block diagram of a monitoring system according to a first embodiment of the present invention. [Figure 2] 2A and 2B are explanatory diagrams of the monitoring system of FIG. 1, in which FIG. 2A is an explanatory diagram for predicting a group of failure symptoms, and FIG. 2B is an explanatory diagram for extracting a group of potential failures. [Figure 3] 2 is a flowchart of a failure symptom group prediction operation of the monitoring system of FIG. 1. [Figure 4] 2 is a flowchart of the score calculation operation of the monitoring system of FIG. 1. [Figure 5] 2 is a flowchart of a potential failure monitoring operation of the monitoring system of FIG. 1. [Figure 6] FIG. 10 is an explanatory diagram showing the relationship between error codes, phenomena, and scores. [Figure 7] FIG. 10 is an explanatory diagram of an example of calculating the total score of a power generation facility. [Figure 8] FIG. 10 is an explanatory diagram of an example of extracted potential failures, showing the transition of time-series data of the moving average of the total score for each piece of specific information. [Figure 9] 10 is a flowchart of a potential failure monitoring operation of the monitoring system according to the second embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0028] Hereinafter, embodiments of the present invention will be described in detail.

[0029] As shown in Figure 1, the monitoring system 1 of the first embodiment of the present invention has a management server 2, multiple power generation facilities 3, and one or more client terminals 5, and the management server 2, each power generation facility 3, and the client terminals 5 are interconnected via a network 6 such as the Internet or an intranet.

[0030] As shown in Fig. 2(a), the monitoring system 1 predicts power generation facilities 3 that show signs of failure from among a plurality of power generation facilities 3 as a failure sign group, and extracts specific information (e.g., specific information b1 and specific information c3) that is common to the extracted power generation facilities 3. One of the features of the monitoring system 1 is that it then extracts power generation facilities 3 that have the extracted specific information (e.g., specific information b1 and specific information c3 in Fig. 2(b)) from among the plurality of power generation facilities 3 as a failure potential group and monitors them. With this in mind, the following will be explained in detail.

[0031] The management server 2 is a server that manages the operating status of each power generation facility 3 . The management server 2 is a computer with a hardware configuration that includes a central processing unit consisting of a control device that controls each device and an arithmetic unit that performs calculations on data, a memory device that stores data, an input device that inputs data from the outside, and an output device that outputs data to the outside. As shown in Figure 1, the management server 2 is composed of the following main components: a symptom prediction unit 10 (prediction unit), a reserve group extraction unit 11 (extraction unit), a score assignment unit 12, a data accumulation unit 13, an error information creation unit 14, a server-side display unit 16 (display unit), and a server-side communication unit 17.

[0032] The symptom prediction unit 10 is a component that predicts a group of failure symptoms that indicate symptoms of a failure from among the plurality of power generation facilities 3. The fault extracting unit 11 is a part that extracts fault potentials from the plurality of power generation facilities 3 that are likely to fail in the future. The score assigning unit 12 is a part that assigns a score for each piece of error information that occurs in each power generation facility 3, and specifically, a part that assigns a score according to the type of error code.

[0033] The data storage unit 13 is a section that stores information about each power generation facility 3, such as the score, error information, installation information, whether it belongs to a failure symptom group, whether it belongs to a failure potential group, and the like. The installation information is information relating to the installation conditions of each power generation facility 3, and includes, for example, identification information, manufacturing information, provision information, construction information, user information, and environmental information. The identification information is information relating to the identification of each power generation facility 3, and includes, for example, an identification code or an identification number of the power generation facility 3. The manufacturing information is information relating to the manufacturing of each power generation facility 3, and includes, for example, the model of the power generation module 60, the serial number of the power generation module 60, the model of the power conversion device 51, the serial number of the power conversion device 51, the model of the storage device 52, and the serial number of the storage device 52. The provided information is information held by the provider and is information relating to the provision of each power generation facility 3, such as the installation year of the power generation facility 3 and the warranty period of the power generation facility 3, for example. The construction information is information relating to the construction of each power generation facility 3, and includes, for example, information such as the name of the contractor of the power generation facility 3. The user information is information about the user of each power generation facility 3, and includes, for example, information such as the location of the power generation facility 3. The environmental information is information relating to the installation environment of each power generation facility 3, and includes, for example, information such as the number of power generation modules 60 installed in each power generation facility 3 and the inclination angle of the light receiving surface of the power generation module 60.

[0034] The error information creating unit 14 is a component that creates error information in which an error code is linked to the content of the error (error event). The error information creation unit 14 determines whether an equipment abnormality exists using the equipment information emitted from each device measured or collected by the data measurement unit 53, and if an equipment abnormality exists, it is able to create error information (equipment error information A described later) that links an error code to the equipment information emitted from each device of the power generation equipment 3. The error information creation unit 14 checks the communication status between the management server 2 and each power generation facility 3 by sending a communication confirmation command such as a Ping command to each power generation facility 3, and if a communication interruption is confirmed, it is possible to create error information (communication error information B described below) that links an error code with communication information regarding the communication status between the management server 2 and the power generation facility 3. The error information creation unit 14 determines whether there is an abnormality in the power generation amount using power generation information regarding the power generation amount of the power generation module 60 measured or collected by the data measurement unit 53 described later, and if there is an abnormality in the power generation amount, it is able to create error information (power generation amount error information C described later) that is linked to an error code and the power generation information regarding the power generation amount of the power generation module 60.

[0035] The server-side display unit 16 is a unit that displays the transition of the score of each power generation facility 3 belonging to the failure potential group extracted by the failure potential group extracting unit 11. The server-side communication unit 17 is a part that can perform mutual data communication with the network 6 wirelessly or via a wired connection. The server-side communication unit 17 of this embodiment is connected to a server-side router wirelessly or by wire, and is connected to the network 6 via the server-side router.

[0036] The power generation facility 3 is a solar power generation facility that generates electricity mainly from sunlight. As shown in Figure 1, the power generation equipment 3 is composed of, as its main components, a module group 50, a power conversion device 51, a power storage device 52, a data measurement unit 53, a power generation side display unit 56, and a power generation side communication unit 57. The module group 50 is made up of one or more power generation modules 60. The power generation module 60 is a photoelectric conversion device that converts light energy into electrical energy, and is a solar cell module that generates DC power using light such as sunlight. The power conversion device 51 is a device that converts power between DC power and AC power, and in this embodiment is a power conditioner that converts DC power generated by the power generation module 60 and DC power stored in the storage device 52 into AC power. The power storage device 52 is a device that has one or more built-in secondary batteries, temporarily stores the power generated by the power generation module 60, and supplies the stored power according to power demand.

[0037] The data measurement unit 53 is a part that measures or collects device information (device data) emitted from the module group 50, the power conversion device 51, and the storage device 52, and is also a part that measures or collects power generation information (power generation data) regarding the amount of power generated by the power generation module 60. The data measurement unit 53 processes the measured or collected device information and power generation information as needed, and can transfer the information to the management server 2. The power generation side display unit 56 is a section that displays the transition of the score of each power generation facility 3 belonging to the failure potential group extracted by the failure potential group extracting unit 11. The power generation side communication unit 57 is a part that is capable of mutual data communication with the network 6 wirelessly or via a wire. The power generation side communication unit 57 of this embodiment is connected to the power generation side router wirelessly or by wire, and is connected to the network 6 via the power generation side router. That is, the power generation facility 3 is capable of transmitting each piece of operating data measured by the data measurement unit 53 to the management server 2 via the power generation side communication unit 57.

[0038] The client terminal 5 is a mobile terminal or a fixed terminal owned by a maintenance worker or the like. The client terminal 5 is a computer having a hardware configuration including a central processing unit consisting of a control device that controls each device and an arithmetic unit that performs calculations on data, a memory device that stores data, an input device that inputs data from the outside, and an output device that outputs data to the outside. As shown in FIG. 1, the client terminal 5 includes a client-side display unit 80 and a client-side communication unit 81 as main components. The client-side display unit 80 is a part that displays the transition of the score of each power generation facility 3 belonging to the failure potential group extracted by the failure potential group extracting unit 11. The client-side communication unit 81 is a part that can perform mutual data communication with the network 6 wirelessly or via a wired connection. The client-side communication unit 81 of this embodiment is connected to a client-side router wirelessly or by wire, and is connected to the network 6 via the client-side router.

[0039] Next, an abnormality monitoring operation in the monitoring system 1 of the present invention will be described.

[0040] The abnormality monitoring operation of this embodiment is composed of a failure symptom group prediction operation and a failure potential group monitoring operation. The failure symptom group prediction operation is an operation executed for each power generation facility 3, and is an operation for predicting a failure symptom group from within the power generation facility 3.

[0041] In the failure symptom group prediction operation, first, as shown in FIG. 3, the first timer is turned on (step S1-1), and the score calculation operation is executed (step S1-2).

[0042] In the score calculation operation, as shown in FIG. 4, the second timer is turned on (step S2-1), and it is checked whether there is any error information (step S2-2).

[0043] At this time, the error information is linked to the error code and the content of the error (error event), as shown in Fig. 6. Specifically, the error information is created by the error information creation unit 14 by linking the date and time of the error occurrence and the content of the error measured or collected by the data measurement unit 53 with the error code. As shown in FIG. 6, the error information can be broadly divided into device error information A, communication error information B, and power generation amount error information C. The device error information A is error information that links an error code with device information issued from each device of the power generation facility 3. In other words, the device error information A is error information issued from each device of the power generation facility 3, and is error information set by the manufacturer of each device. The communication error information B is error information in which an error code and communication information relating to the communication state between the management server 2 and the power generation facility 3 are linked together. The communication error information B includes the following error information (1) to (4) related to communication interruptions. (1) Communication interruption between the power conversion device 51 and the data measurement unit 53 (2) Communication interruption between the data measurement unit 53 and the power generation side communication unit 57 (3) Communication interruption between the power generation side communication unit 57 and the power generation side router (4) Communication between the power generation router and management server 2 is interrupted The power generation error information C is error information in which an error code is linked to power generation information related to the power generation amount of the power generation module 60. That is, the power generation error information C is error information related to an abnormality in the power generation amount of the power generation module 60.

[0044] In step S2-2 of FIG. 4, if there is error information (Yes in step S2-2), the score assigning unit 12 assigns a score weighted based on safety to each error code in the error information (step S2-3).

[0045] At this time, in each power generation facility 3, a score is assigned to each error code included in the error information based on safety. For example, the error code A-01 in FIG. 6 corresponds to the fact that the temperature of the power electronics device 51 has exceeded a reference value, which is detected as an error. The high temperature of the power conversion device 51 is likely due to high ambient temperature around the power conversion device 51 or a short circuit within the power conversion device 51, and since there is a high possibility of serious abnormalities such as fire, it has a large impact on safety and has been given a high score (100 points). On the other hand, error code B-01 in Figure 6 corresponds to the detection of a communication outage lasting less than one day. The causes of communication outages include communication failures between the power generation equipment 3 and the network 6, or communication failures between the network 6 and the management server 2. In the short term, these are mostly temporary and do not significantly impair safety compared to errors such as the power conversion device 51 being too hot, so the impact on safety is small and the score is low (1 point). In the case of error code B-02 in Figure 6, this corresponds to the detection of a communication outage lasting for more than two weeks, which is a longer period of time than the case of error code B-01. Therefore, it is considered that there is a higher probability of an abnormality occurring than in the case of error code B-01, and a higher score (5 points) has been assigned than in the case of error code B-01. The error code C-01 in FIG. 6 corresponds to the detection that the power generation amount of the power generation facility 3 has fallen below the power generation amount abnormality threshold once. The decline in power generation is attributed to factors such as bad weather and snowfall, deterioration of the power generation equipment 3 over time, damage to the power generation module 60, and malfunctions in the wiring.If the decline is short-term, it is likely to be due to a temporary abnormality caused by weather or other factors, so it has been given a low score (5 points). In the case of error code C-02 in Figure 6, this corresponds to the detection that the power generation amount has been below the threshold for abnormal power generation for three consecutive months. This indicates that the power generation amount has been abnormal for a long period of time, and there is a possibility that the abnormality is not due to the weather, so a higher score (50 points) is assigned compared to error code C-01.

[0046] When the points are awarded in step S2-3 of FIG. 4, it is checked whether a predetermined time t1 has elapsed since the second timer was turned on (step S2-4).

[0047] The predetermined time t1 at this time is not particularly limited, but is preferably, for example, 10 minutes or more and 6 hours or less, and more preferably 30 minutes or more and 2 hours or less.

[0048] In step S2-4, if the predetermined time t1 has elapsed (Yes in step S2-4), the second timer is reset (step S2-5), and the score calculation operation is terminated.

[0049] If there is no error information in step S2-2, the process proceeds to step S2-4.

[0050] In step S2-4, if the predetermined time t1 has not elapsed (step S2-4), the process proceeds to step S2-2.

[0051] As shown in FIG. 3, when the score calculation operation is completed in step S1-2, it is checked whether the first period T1 has elapsed since the first timer was turned on (step S1-3).

[0052] The first period T1 is not particularly limited as long as it is longer than the predetermined time t1, but is preferably, for example, from one day to six months, and more preferably from one week to two months. In this embodiment, the first period T1 is 30 days.

[0053] In step S1-3, if the first period T1 has elapsed (Yes in step S1-3), the total score of the power generation facility 3 is calculated and it is confirmed whether the total score is equal to or greater than a threshold (step S1-4). That is, the symptom prediction unit 10 compares the total score linked to the error codes during the first period T1 with the threshold.

[0054] The threshold is a constant that is set appropriately depending on the number of points associated with the error code and the installation situation. Here, FIG. 7, which is a specific example of step S1-4, will be described. FIG. 7 shows error information that has occurred in the power generation facility 3 with the identification number No. 1 in chronological order. In the No. 1 power generation equipment 3, three types of errors occurred during the first period T1: high temperature of the power conversion device 51 (abnormal temperature of the power conversion device 51), a loss of communication between the management server 2 and the power generation equipment 3, and a decrease in the power generation output of the power generation module 60. Then, for the No. 1 power generation facility 3, points are added up for the error codes linked to each error, and the total points linked to the error codes during the first period T1 becomes 171 points. Here, for example, if the threshold is set to 150 points, the No. 1 power generation facility 3 is above the threshold because its total threshold exceeds 150 points. Also, for example, if the threshold is set to 180 points, the No. 1 power generation facility 3 is below the threshold because its total threshold falls below 180 points.

[0055] In step S1-4 of FIG. 3, if the total score is equal to or greater than the threshold (Yes in step S1-4), it is predicted to be a failure symptom group (step S1-5), the first timer is reset (step S1-6), and the failure symptom group prediction operation is terminated.

[0056] In step S1-4, if the total score is less than the threshold value (No in step S1-4), it does not correspond to the failure symptom group, so the first timer is reset (step S1-6) and the failure symptom group prediction operation is terminated.

[0057] In step S1-3, if the first period T1 has not elapsed, the process proceeds to step S1-2.

[0058] When a failure symptom group is predicted by the above-described failure symptom group prediction operation, a failure potential monitoring operation is executed. The potential failure monitoring operation is an operation for monitoring the time series transition of the potential failure score. In the failure potential monitoring operation, first, as shown in FIG. 5, the installation information is compared between the failure symptom group and the predicted power generation facility 3 (step S3-1), and it is confirmed whether there is common specific information (step S3-2).

[0059] In step S3-2, if there is one or more pieces of common specific information (Yes in step S3-2), the power generation facilities 3 having each piece of specific information are extracted as potential failure groups (step S3-3).

[0060] For example, Figure 8 shows the common specific information when extracting power generation equipment 3 whose user information is Tokyo as a potential failure group, when extracting power generation equipment 3 whose construction information is 〇×△ Construction Company as a potential failure group, and when extracting power generation equipment 3 whose manufacturing information is the model of power conversion device 51 as a potential failure group. In this way, in step S3-3, common specific information is extracted from the various types of information that make up the installation information, and the power generation facilities 3 having the extracted specific information are extracted as failure potential groups.

[0061] As shown in Figure 5, a score calculation operation is performed for power generation equipment 3 extracted as a failure potential group (step S3-4), the total scores of power generation equipment 3 belonging to the same failure potential group are calculated (step S3-5), and the moving average value of n terms of the total scores of the failure potential group is calculated (step S3-6).

[0062] The number of sections n at this time is set appropriately depending on the length of the predetermined time t1 and the like, but is preferably 3 or more and 10 or less.

[0063] When the moving average value of the total score is calculated in step S3-6, time series trend data representing the time series trend of the moving average value calculated for each failure potential group is created or updated (step S3-7), stored in the data accumulation unit 13, and it is checked whether there is a request to terminate operation (step S3-8).

[0064] At this time, the administrator acquires the time-series transition data and displays the time-series data on the server-side display unit 16. In this embodiment, as shown in Fig. 8, each piece of specific information, the number of power generation facilities 3 having each piece of specific information, and the transition of the moving average value of the total score per day for each piece of specific information are displayed as an image as time-series data. The administrator then checks the time series trend of the moving average value of the total score from the image displayed on the server side display unit 16, determines whether maintenance is necessary for each potential failure group, and if the total score is small or maintenance of the monitoring system 1 is necessary, inputs a request to end the operation and ends the potential failure group monitoring operation.

[0065] In step S3-8 of FIG. 5, if there is a request to end the operation (Yes in step S3-8), the operation of monitoring potential failures is ended.

[0066] In step S3-2, if there is no specific information common to the failure symptom group and the predicted power generation equipment 3 (No in step S3-2), a failure precursor cannot be extracted, so the failure precursor monitoring operation is terminated and the failure symptom group prediction operation is performed again.

[0067] In step S3-8, if there is no operation end request (No in step S3-8), the process proceeds to step S3-4.

[0068] According to the monitoring system 1 of this embodiment, common specific information in the installation information is identified among power generation facilities 3 belonging to an abnormality sign group in which abnormality signs have been observed, and for each specific information, power generation facilities 3 having the specific information are extracted as a potential failure group. Then, by a manager or the like monitoring the time series transition of the moving average value of the total score of the potential failure group, it is possible to predict power generation facilities 3 that are likely to experience a serious abnormality in the future and take measures.

[0069] According to the monitoring system 1 of this embodiment, the server-side display unit 16 displays the transition of the moving average value of the total score of potential failures at every predetermined time t1, so that it is possible to predict the tendency for serious abnormalities to occur in the future.

[0070] According to the monitoring system 1 of this embodiment, the management server 2, the power generation facility 3, and the client terminal 5 are each connected via a network 6, and the management server 2, the power generation facility 3, and the client terminal 5 are each provided with a display unit 16, 56, 80, so that an image displaying time series data of each specific information and the moving average value of the total score corresponding to each specific information can be viewed on each display unit 16, 56, 80.

[0071] Next, a monitoring system according to a second embodiment of the present invention will be described.

[0072] The monitoring system of the second embodiment differs from the first embodiment in the operation of monitoring a potential failure.

[0073] 9, the operation of monitoring a potential failure in the second embodiment has many steps in common with the operation of monitoring a potential failure in the first embodiment, but some steps are different from those in the operation of monitoring a potential failure in the first embodiment. Therefore, steps that are similar to those in the operation of monitoring a potential failure in the first embodiment are assigned the same step numbers, and descriptions thereof will be omitted.

[0074] In the failure potential monitoring operation of the second embodiment, as shown in Figure 9, first, the installation information is compared between the failure symptom group and the predicted power generation equipment 3 (step S3-1), and if there is specific information common to the installation information (Yes in step S3-2), the power generation equipment 3 having the specific information for each specific information is extracted as a failure potential group (step S3-3).

[0075] When a potential failure group is extracted, the third timer is turned on (step S4-1), a score calculation operation is executed (step S4-2), and the total score of each potential failure group is calculated (step S4-3).

[0076] Once the total score of each potential failure group has been calculated, it is checked whether the second period T2 has elapsed since the third timer was turned on (step S4-4).

[0077] The second period T2 is not particularly limited as long as it is longer than the predetermined time t1, but is preferably, for example, 6 hours or more and 1 week or less, and more preferably 12 hours or more and 2 days or less. The second period T2 in this embodiment is 1 day (24 hours).

[0078] In step S4-4, if the second period T2 has passed (Yes in step S4-4), the average value (arithmetic mean value) of the total score for each failure potential group in the second period T2 is calculated (step S4-5), and time series trend data representing the time series trend of the average value of the total score calculated for each failure potential group is created or updated and stored in the data accumulation unit 13 (step S4-6). Then, the third timer is reset (step S4-7), and it is checked whether there is a request to end the operation (step S4-8).

[0079] In step S4-8, if there is a request to end the operation (Yes in step S4-8), the failure potential monitoring operation is ended, and if there is no request to end the operation (No in step S4-8), the process returns to step S4-1.

[0080] In step S4-4, if the second period T2 has not elapsed since the timer was turned on, the process proceeds to step S4-2.

[0081] According to the monitoring system of the second embodiment, the change in the average value of the total score of the potential failure group can be displayed on the server side display unit 16 for each second period T2, so that if a failure occurs, it is easy to identify the point in time at which the failure occurred.

[0082] In the above embodiment, the total score for each power generation facility 3 is compared with a threshold, and power generation facilities 3 that are equal to or greater than the threshold are extracted as a group of failure symptoms, but the present invention is not limited to this. When a standard normal distribution is taken of the total scores for all power generation facilities 3, those that fall within the top X1% may be uniformly extracted as a group of failure symptoms. X1 is set appropriately depending on the total number of power generation facilities 3, but is preferably set within the range of 1 to 30, for example. Furthermore, when a standard normal distribution is taken for the total scores of all the power generation facilities 3, those that fall within the top X2 units may be uniformly extracted as a group of failure symptoms. X2 is set appropriately depending on the total number of power generation facilities 3, and is preferably set to a number in the range of 1% to 30% of the total number of power generation facilities 3, for example.

[0083] In the above embodiment, the threshold value is a fixed constant, but the present invention is not limited to this, and the threshold value may be a variable. For example, the threshold value may be a value in the range of the top 1% to the top 30% of the total score of all the power generation facilities 3.

[0084] In the above embodiment, the moving average value or the time series transition of the average value of the total points is displayed on the server-side display unit 16 of the management server 2, but the present invention is not limited to this. The moving average value or the time series transition of the average value of the total points may be displayed on another power generation-side display unit 56 or client-side display unit 80.

[0085] In the above embodiment, there are multiple types of specific information common to the power generation facilities 3 belonging to the failure symptom group, and a failure potential group is extracted for each type of specific information, but the present invention is not limited to this. Even if there are multiple types of specific information common to the power generation facilities 3 belonging to the failure symptom group, any specific information may be selected, and a failure potential group may be extracted for each selected specific information.

[0086] In the above embodiment, the error code and the score are linked by the error information creation unit 14 on the management server 2 side, but the present invention is not limited to this. An error information creation unit 14 may be provided on the power generation facility 3 side to link the error code and the score. That is, an error information creation unit 14 may be provided on the power generation facility 3 side, and the error information creation unit 14 may determine an error and create error information in which an error code is linked to the content of the error. In this case, it is preferable that the management server 2 be provided with an error information acquisition unit that acquires error information from the power generation facility 3 side. This allows error information to be centrally managed on the management server 2 side.

[0087] In the above embodiment, the management server 2 and the power generation facility 3 are provided separately, but the present invention is not limited to this. The management server 2 and the power generation facility 3 may be integrated.

[0088] In the second embodiment described above, the arithmetic mean value is used as the average value of the total points, but the present invention is not limited to this. An average value calculated by another calculation method may also be used as the average value of the total points. For example, a weighted average value or a geometric mean value may also be used as the average value of the total points.

[0089] In the above-described embodiment, the symptom prediction unit 10 and the reserve group extraction unit 11 are provided in the management server 2, but the present invention is not limited to this. The symptom prediction unit 10 and / or the reserve group extraction unit 11 may also be provided in the power generation facility 3.

[0090] In the above-described embodiment, the communication units 17, 57, and 81 are connected to the network 6 via a router, but the present invention is not limited to this. The communication units 17, 57, and 81 may be connected to the network 6 via a wireless base station.

[0091] In the above embodiment, the power generation facility 3 includes the power storage device 52, but the present invention is not limited to this. The power generation facility 3 does not necessarily have to include the power storage device 52.

[0092] In the above embodiment, the error information creation unit 14 determines whether an apparatus abnormality exists using the apparatus information emitted from each apparatus measured or collected by the data measurement unit 53, but the present invention is not limited to this. A management company that monitors the operating status of each apparatus may determine whether an apparatus abnormality exists using the apparatus information emitted from each apparatus measured or collected by the data measurement unit 53. In this case, if the management company's determination result is that there is an abnormality in the equipment, the error information creation unit 14 creates error information (equipment error information A) in which the error code and the equipment information issued from each device of the power generation facility 3 are linked together.

[0093] In the above-described embodiments, each component can be freely substituted or added between the respective embodiments as long as it falls within the technical scope of the present invention. [Explanation of symbols]

[0094] 1. Surveillance System 2 Management Server 3. Power generation facilities 6 Network 10 Symptom Prediction Unit (Prediction Unit) 11 Preliminary group extraction unit (extraction unit) 12. Score allocation section 13 Data storage unit 14 Error Information Creation Unit 16 Server side display unit (display unit) 56 Power generation side display unit (display unit) 60 Power Generation Module 80 Client side display unit (display unit)

Claims

1. Multiple power generation facilities, an error information creation unit that creates error information for each power generation facility; a data storage unit that stores installation information and error information of each power generation facility; a prediction unit that predicts a failure symptom group that indicates a failure symptom from among the plurality of power generation facilities based on error information of each power generation facility; A monitoring system comprising an extraction unit that identifies specific information common to the group of failure symptoms and installation information of the predicted power generation equipment, and extracts power generation equipment whose installation information includes the specific information from among the plurality of power generation equipment as a group at risk of failure.

2. a score assigning unit that assigns a score to each piece of error information; The monitoring system according to claim 1 , wherein the prediction unit accumulates the scores of each piece of error information for each piece of power generation equipment, and predicts that the power generation equipment whose total score is equal to or greater than a predetermined threshold is the failure symptom group.

3. the error information includes an error code; the score assigning unit assigns a score to the error code, The monitoring system of claim 2, wherein the prediction unit accumulates scores corresponding to each error code for each power generation facility, and predicts that the power generation facility for which the total score of the error information in the first period is equal to or greater than a predetermined threshold value is the group of failure symptoms from among the plurality of power generation facilities.

4. The monitoring system according to claim 2 or 3, wherein the scores are weighted and set based on the safety of the power generation facility.

5. the power generation facility is connected to a management server via a network; A monitoring system according to any one of claims 2 to 4, wherein the error information includes communication error information linked to an error code and communication information regarding the communication status between the power generation equipment and the management server.

6. The power generation facility includes one or more power generation modules, The monitoring system according to any one of claims 2 to 5, wherein the error information includes power generation error information in which an error code is linked to power generation information relating to the power generation amount of the power generation module.

7. The monitoring system of any one of claims 1 to 6, wherein the installation information includes at least one piece of information selected from the group consisting of manufacturing information regarding the manufacture of each power generation facility, provision information regarding the provision of each power generation facility, construction information regarding the construction of the power generation facility, user information regarding users of the power generation facility, and environmental information regarding the installation environment of the power generation facility.

8. a score assigning unit that assigns a score to each piece of error information; For each power generation facility belonging to the failure potential group, the points of each piece of error information are integrated to calculate a total point for each predetermined time period, and a moving average value of the total points of the error information is calculated, 8. The monitoring system according to claim 1, further comprising a display unit that displays a time series transition of the moving average value of the power generation equipment belonging to the potential failure group.

9. a score assigning unit that assigns a score to each piece of error information; for each power generation facility belonging to the failure potential group, a total score is calculated for each predetermined time period by accumulating the score of each piece of error information, and an average value of the total score is calculated for each second period; The monitoring system according to any one of claims 1 to 7, further comprising a display unit that displays a time series change in the average value of the total score of the power generation equipment belonging to the failure potential group.

10. the extraction unit identifies a plurality of pieces of specific information common to the group of failure symptoms and installation information of the predicted power generation facility; 10. The monitoring system according to claim 1, wherein a power generation facility is extracted as a potential failure group in each of the specific information from among the plurality of power generation facilities.

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