JP6597425B2 - FACTOR ESTIMATION DEVICE, FACTOR ESTIMATION DEVICE CONTROL METHOD, CONTROL PROGRAM, AND RECORDING MEDIUM - Google Patents

Description

  The present invention relates to a factor estimation device that estimates a factor of an abnormality in a decrease in power generation amount of a solar power generation system.

  In recent years, solar power generation that uses solar energy, which is clean energy that is environmentally friendly and clean, is drawing attention. Components of a solar cell used in a solar power generation system for performing solar power generation will be described with reference to FIG. FIG. 13 is a schematic diagram illustrating the relationship among the solar cell array 1010, the solar cell string 1001, the solar cell module 1011, and the solar cell 1000.

  Hereinafter, a solar cell array, a solar cell string, a solar cell module, and a solar cell are respectively referred to as an array (component), a string (component), a module (component), and a cell (component). Abbreviated.

  As shown in FIG. 13, a cell 1000 that generates current by photoelectric effect when irradiated with sunlight is a minimum unit of constituent elements of a solar cell. The module 1011 includes a plurality of cells 1000. The string 1001 is obtained by connecting a plurality of modules 1011 in series. The array 1010 has a plurality of strings 1001 connected in parallel.

  Next, a typical configuration of a conventional photovoltaic power generation system will be schematically described with reference to FIG. FIG. 14 is a block diagram showing a schematic configuration of a conventional photovoltaic power generation system 1100. As illustrated, the photovoltaic power generation system 1100 is configured to include an array 1010, a power conditioner 1020, and a load 1030. The DC power output from the array 1010 is converted into AC power by an inverter 1021 built in the power conditioner 1020 and then supplied to the load 1030.

  Note that, as shown in FIG. 14, the solar power generation system 1100 may be configured to operate in conjunction with a commercial power system 1040 provided by the power company, or may not be coupled to the power system 1040 of the power company. Some systems operate as an independent system.

  The output of each cell 1000 varies depending on various factors such as its installation state (tilt angle, etc.), season (solar altitude), time (sun azimuth angle), weather (sunlight intensity (sunlight amount)), temperature, and the like. For this reason, even if the output (power generation amount) of the photovoltaic power generation system decreases, it is difficult to determine what is the cause of the abnormality in the power generation amount decrease. In particular, when a power generation amount decrease abnormality occurs due to an event that the power conditioner 1020 cannot monitor, there is a problem that the cause of the power generation amount decrease abnormality cannot be specified from the information output by the power conditioner 1020.

JP 2001-326375 A (published November 22, 2001) WO 2011/089999 A1 (International publication July 28, 2011)

  To solve this problem, for example, the diagnostic device described in Patent Document 1 considers the position of the sun when the measured power amount is significantly lower than the reference power amount only in the afternoon. It is possible to diagnose an abnormality in the output decrease due to.

  However, the configuration of Patent Document 1 has the following problems. Specifically, based on the fact that the amount of time during which power generation is decreasing is limited, if it is generally diagnosed as an abnormality due to a shadow (shadow), a specific time period is caused by factors other than shadows. Even in the case where the amount of power generation is reduced, there is a possibility that it is erroneously determined that the shadow is a factor. For example, even in the case where some kind of obstacle is on the solar panel around noon, it is determined that the cause of power generation abnormality is a shadow.

  When the cause of power generation abnormality is a shadow, it is considered that a non-removable shading object such as a building makes the shadow. Therefore, it is impossible to artificially remove the factor by a business operator or engineer who maintains the photovoltaic power generation system to improve the abnormality. That is, the case where the cause of the abnormality is a shadow is a case where it is meaningless to dispatch a maintenance worker to the site where the solar power generation system where the abnormality has occurred is laid.

  On the other hand, in the case where anomalies have occurred due to some kind of shielding (snow, weeds, dust, volcanic ash, or other flying objects) covering the solar panel, by removing the shielding manually , There is a possibility to improve the abnormality. In other words, this is a case where maintenance workers should be dispatched to the site. Alternatively, some types of shields may be removed naturally, and in some cases, it may be determined that it is not necessary to send a maintenance worker to the site.

  Therefore, it is not possible to appropriately determine whether maintenance workers should be dispatched to the site due to erroneous estimation of the factors as described above. As a result, the abnormality to be improved cannot be improved, human response is impossible, or human There is a problem that personnel are wasted in response to a case that does not require an appropriate response. Such a problem becomes particularly serious when it is necessary to remotely monitor a photovoltaic power generation system and to visit and maintain the site where the system is installed from a distance.

  The present invention has been made in view of the above problems, and its purpose is to estimate that when an abnormality in the amount of power generation is reduced, an artificial response requirement or an unnecessary failure is a cause of the abnormality. The object is to realize a factor estimating apparatus that performs with high accuracy.

  In order to solve the above-described problem, the factor estimation device (1) of the present invention uses the day as the target day based on the daily measured power generation amount of the solar power generation system (100, 100a, 100b). A factor estimation device for estimating a factor of power generation abnormality occurring in a photovoltaic power generation system, wherein a power generation achievement rate indicating a ratio of the actually measured power generation amount to an estimated power generation amount indicating an expected power generation amount Based on the distribution of the comparison unit (data comparison unit 32) that outputs for each time zone and the target unachieved time zone in which the power generation achievement rate is less than a predetermined value, the cause of power generation abnormality occurring on the target date is estimated The estimation unit (factor estimation unit 33), and the estimation unit has a common bias in the target unachieved time zone in the distribution of the target date and one or more days before the target date In addition, the shadow of the shading object is abnormal power generation It is estimated to be a factor.

  According to the above configuration, the time period during which the power generation amount has decreased (the time period during which the target power generation amount has not been achieved, hereinafter, the target unachieved time period) is a specific time out of the total operation time of the photovoltaic power generation system. In addition to being biased to the time zone, when the bias method (bias of the target unachieved time zone) has been common for many days, the cause of power generation abnormality on the target day is “shadow” It is estimated that.

  In the case where a non-removable shading object such as a building makes a shadow, it is not considered that the target unachieved time zone is biased for only one day of the target day. On the other hand, the case where the target unachieved time zone is equally biased for many days is considered to be a case where a non-removable light-shielding object such as a building is shadowing.

  By accurately estimating such factors that do not require (or impossible) human response, it is possible to avoid wasting personnel on abnormal incidents that cannot be improved. .

  The estimation unit calculates the estimated power generation amount and the actually measured power generation amount when there is no bias in the target unachieved time zone in the distribution of the target day, or when the bias is not common in each of the distributions. A factor of power generation abnormality that occurred on the target date is further estimated based on a power generation decrease amount indicating a difference, and in the solar power generation system, the constituent elements (array, string, module, or A breaker that cuts off a current for each cell), and the estimation unit is configured to detect the breaker when the power generation reduction amount is equal to an integral multiple of the estimated power generation amount of units united by one breaker. It is presumed that the breaker trip caused by

  According to the above-described configuration, the estimation unit is configured such that when there is no bias in the target unachieved time zone in the distribution of the target day, or when the bias is not common in the respective distributions, that is, a factor of power generation abnormality Is not “shadow”, another factor of power generation abnormality is estimated based on the power generation decrease amount. Specifically, when the power generation reduction amount matches an integer multiple of the estimated power generation amount in one string, it is estimated that the breaker trip due to the breaker is a cause of power generation abnormality. This is based on the idea that the ratio of strings operating with respect to all the strings constituting the solar cell array (string operating rate) and the power generation achievement rate will almost coincide.

  As described above, by accurately estimating that the breaker trip is a factor, it is possible to appropriately determine whether or not a maintenance worker should be dispatched to the site in response to an abnormality occurrence case.

  When the power generation reduction amount does not coincide with an integral multiple of the estimated power generation amount of a unit collected by a single breaker, the shield attached on the solar cell array is a cause of power generation abnormality. Presume that there is.

  According to the above configuration, the estimation unit determines that the power generation decrease amount does not coincide with an integer multiple of the estimated power generation amount in one string, that is, even if the cause of power generation abnormality is “shadow”, “breaker trip” If this is not the case, it is estimated that the “shielding object” adhering to the solar cell array is a cause of power generation abnormality.

  As a result, regarding the power generation abnormality on the target day, it is estimated that the factor is an artificial response necessary (or possible) factor after eliminating the possibility that the artificial response is unnecessary (or impossible). As a result, it is possible to appropriately dispatch a maintenance person to an appropriate abnormality without wasting personnel on an abnormality occurrence that cannot be improved.

  The estimation unit determines whether there is a correlation between the fluctuation in the actually measured power generation amount and the fluctuation in the external environment information that is information related to the environment around the photovoltaic power generation system. The estimated type of the shielding object is further estimated.

  The estimation unit estimates the type of shielding object based on the weather before the change when the timing at which the measured power generation amount changes coincides with the timing at which the weather on the target day changes.

  The estimation unit estimates that the shield that causes a power generation abnormality should be artificially removed when there is no correlation between the fluctuation of the actually measured power generation amount and the fluctuation of the external environment information. To do.

  According to each of the above-described configurations, the type of the shielding object is estimated based on the correlation between the external environment information (for example, but not limited to weather) and the actually measured power generation amount. As a result, the maintenance company can more appropriately determine whether or not an artificial response is necessary or unnecessary (or availability) in accordance with the estimated type of shielding. For example, when the shield is snow, it is considered that there is a correlation between the weather “snow” and the actually measured power generation amount (after snowfall, the actually measured power generation amount decreases). Snow as a shield is removed due to rainfall, temperature rise, etc., and if snow is still continuing, removing it artificially is temporary and meaningless. Accordingly, if the shielding object is estimated to be snow by the factor estimation device, the user can determine that no artificial response is necessary.

  Or, for example, when the shield is volcanic ash, there is a correlation between the geographical information “falling ash from eruption”, the weather “rain”, and the measured power generation amount (after the ash falls, the measured power generation amount decreases, It is thought that the amount of power generation increases slightly after rainfall). If the shielding object is estimated to be volcanic ash by the factor estimation device, the user can appropriately determine whether or not an artificial response is necessary according to the recovery state of the power generation amount.

  Or when there is no correlation between the fluctuation | variation of the said actual measurement electric power generation amount and the fluctuation | variation of the said external environment information, an estimation part estimates that the said shield should be removed artificially. For example, flying objects (garbage such as vinyl and cloth), weeds, and the like are considered as shielding objects that are not related to the weather. These can be removed by maintenance workers, and by this removal, a significant recovery in power generation is expected. If the factor is estimated by the factor estimating device as “another removable shield”, the user can determine that an artificial response is necessary.

  As described above, it is possible to appropriately dispatch a maintenance worker to an appropriate abnormality without wasting personnel on an abnormality occurrence case that has little effect of human response.

  In order to solve the above-mentioned problem, the control method of the factor estimating apparatus according to the present invention is based on the measured power generation amount per day of the solar power generation system, and the power generation generated in the solar power generation system with that day as the target day. A control method for a factor estimation device for estimating a factor of abnormality, wherein a power generation achievement rate indicating a ratio of the measured power generation amount to an estimated power generation amount indicating an expected power generation amount is determined for each predetermined time zone on the target day And an estimation step of estimating a factor of power generation abnormality that has occurred on the target day based on a distribution of a time zone in which the power generation achievement rate is less than a predetermined value. In the estimation step, In the distribution of the target date and one or more days prior to the target date, when the bias is common, it is estimated that the shadow of the light shielding object is a cause of power generation abnormality. According to this control method, the same operational effects as those of the factor estimating apparatus can be obtained.

  In addition, a control program that causes a computer to function as the factor estimation device by causing the computer to execute the steps described above, and a computer-readable recording medium that records the control program are also included in the scope of the present invention.

  According to the present invention, there is an effect that it is possible to accurately estimate that an artificial response necessity or unnecessary failure is a cause of an abnormality when an abnormality in a power generation amount decrease occurs.

It is a block diagram which shows the principal part structure of the factor estimation apparatus which concerns on one Embodiment of this invention. It is a block diagram which shows the outline | summary of the electric power generation monitoring system which concerns on one Embodiment of this invention. It is a figure which shows an example of the data structure of the comparison result data memorize | stored in the comparison result memory | storage part of the said factor estimation apparatus. It is a figure which shows an example of the data structure of the estimation result data memorize | stored in the estimation result memory | storage part of the said factor estimation apparatus. (A) And (b) is a figure explaining the positional relationship between a light-shielding object, an array, and the sun, and a mode that the shadow of a light-shielding object is applied on an array. (A) and (b) are graphs comparing the measured power generation amount and the estimated power generation amount of the photovoltaic power generation system, (a) is a graph of a day when the weather is cloudy or rainy, (b ) Is a graph of a day when the weather changes from cloudy to sunny. It is a graph which shows the relationship between the amount of solar radiation in a solar energy power generation system, and measurement power generation amount. (A) is a figure which shows typically the mode of an array and a breaker when the breaker trip of a string unit generate | occur | produces, (b) is the sunlight under the condition where the breaker trip shown to (a) occurred It is a graph which shows transition of the power generation achievement rate of a specific period in a power generation system. (A) is a figure which shows typically the mode of each string when the breaker trip of a string unit generate | occur | produces, (b) is a graph which shows the IV curve of each string shown to (a). It is a graph which shows transition of the power generation achievement rate in the specific period before and behind the generation | occurrence | production of a shield in the photovoltaic power generation system in the condition where the shield occurred. It is a flowchart which shows the flow of the data comparison process which a factor estimation apparatus performs. It is a flowchart which shows the flow of the factor estimation process which the factor estimation part of a factor estimation apparatus performs. It is a schematic diagram shown about the relationship of an array, a string, a module, and a cell in a solar energy power generation system. It is a block diagram which shows schematic structure of the conventional solar power generation system.

Embodiment 1
(System overview)
Hereinafter, an embodiment of the present invention will be described in detail. FIG. 2 is a block diagram showing an outline of the power generation monitoring system 900 according to one embodiment of the present invention. The power generation monitoring system 900 is a system for monitoring the solar power generation system 100 by collecting data related to the operation status of one or more solar power generation systems 100 and the external environment. The power generation monitoring system 900 includes one or more photovoltaic power generation systems 100 (100a, 100b,...) To be monitored and the measurement monitoring device 2 as a monitoring subject. The power generation monitoring system 900 may include the remote monitoring server 3 instead of or in addition to the measurement monitoring device 2. The power generation monitoring system 900 includes a factor estimation device 1 for estimating a factor of an abnormality when any abnormality occurs in the solar power generation system 100. The factor estimation device 1 of the present invention may be provided in the measurement monitoring device 2 or may be provided in the remote monitoring server 3. Alternatively, the functions performed by the factor estimation device 1 may be distributed and provided in each of the measurement monitoring device 2 and the remote monitoring server 3. In the following embodiment, although there is no intention to limit to this, the factor estimation apparatus 1 is demonstrated as what is provided in the measurement monitoring apparatus 2 as an example.

  The photovoltaic power generation system 100 receives sunlight and generates electric power, and has facilities for sending the generated electric power to the system. Specifically, the solar power generation system 100 is configured to include an array 4 (solar cell array), a connection box 6, a power conditioner 8 (hereinafter, abbreviated as a power converter 8), and a pyranometer 9. Furthermore, the solar power generation system 100 may include a measuring instrument 7 and a thermometer 10 as necessary.

  The connection box 6 is a device that collects wirings from the array 4 (solar panel) and sends them to the power conditioner 8. The connection box 6 includes a breaker 5 for cutting off current for each string constituting the array 4, and the breaker 5 controls the array 4 so that electricity does not flow backward or large current does not flow at once. be able to.

  The power conditioner 8 is for adjusting the power from the array 4 so that it can be supplied to a load (not shown). Specifically, direct current power is converted into alternating current power that can be used at home, and the operation of the entire photovoltaic power generation system 100 is controlled. A single power conditioner 8 can handle a plurality of pairs of arrays 4 and junction boxes 6.

  The measuring instrument 7 measures a current value and a voltage value supplied from the array 4 to the power conditioner 8 through the connection box 6 and has a configuration including an ammeter and a voltmeter (not shown). The current value and voltage value measured by the measuring instrument 7 are transmitted to the factor estimating apparatus 1 of the measurement monitoring apparatus 2 via the power conditioner 8. The solar radiation meter 9 measures the solar radiation intensity (amount of solar radiation) of the array 4. The solar radiation intensity means the amount of radiant energy per unit time and unit area from the sun. The pyranometer 9 transmits the measured amount of solar radiation to the power conditioner 8. The solar radiation intensity may be the amount of solar radiation indicated by the sunshine time × the solar radiation intensity. In the solar power generation system 100, an optional thermometer 10 measures the ambient temperature around the array 4 group. The thermometer 10 transmits the measured temperature to the power conditioner 8. When the thermometer 10 is provided, more accurate factor estimation can be performed using information on the measured temperature.

  Note that the measuring instrument 7, the pyranometer 9, and the thermometer 10 may transmit the measured physical quantity directly to the measurement monitoring apparatus 2 (factor estimation apparatus 1) without using the power conditioner 8. Further, the measuring instrument 7, the pyranometer 9, and the thermometer 10 may transmit the measured physical quantity periodically or in response to a request from the power conditioner 8 or the measurement monitoring device 2. The measuring instrument 7, the pyranometer 9, and the thermometer 10 may transmit the measured time to the power conditioner 8 or the measurement monitoring device 2 together with the measured physical quantity.

  The measurement monitoring device 2 is provided near the site where the solar power generation system 100 is laid, together with the power conditioner 8 that controls the solar power generation system 100. The measurement monitoring device 2 communicates with each power conditioner 8 and collects on-site information. Communication between the power conditioner 8 and the measurement / monitoring device 2 is performed by any wireless or wired communication means, a LAN (Local Area Network) or a LAN depending on the physical distance between the devices and the hardware installation environment. This is realized by an arbitrary communication network of a wide area network. The information collected by the measurement monitoring device 2 includes, for example, the amount of power generated by each solar power generation system 100, the weather at the place where the solar power generation system 100 is installed, the amount of solar radiation, the temperature, and the like. The weather information may be acquired from another service server via the network 11. Furthermore, when the power conditioner 8 has a function of detecting an abnormality of the photovoltaic power generation system 100, the measurement monitoring device 2 may collect information such as the time zone in which the abnormality has occurred and the type of abnormality. Good.

  The remote monitoring server 3 communicates with the measurement monitoring device 2 that monitors one or more photovoltaic power generation systems 100 in each region via the network 11, collects data of each photovoltaic power generation system 100, and performs remote monitoring. carry out.

  The factor estimation device 1 according to the present invention estimates a factor of an abnormality when an abnormality occurs in the photovoltaic power generation system 100. Here, the abnormality which the factor estimation apparatus 1 is subject to factor estimation is different from the abnormality notified from the power conditioner 8 described above. That is, the factor estimating apparatus 1 estimates the factor for an abnormality in which the factor cannot be specified by the monitoring function of the power conditioner 8. Specifically, the power conditioner 8 can record information indicating that an event has occurred when an abnormality or failure of the power conditioner 8 itself or a breaker trip performed by the power conditioner 8 occurs. In addition, the power conditioner 8 can suppress the output power of the array 4 in response to a rise in voltage or temperature, or for the purpose of intentionally suppressing the amount of power generation. When an abnormality in the amount of power generation is reduced due to these events, the cause of the abnormality can be specified based on the record of the power conditioner 8, the control log, and the like.

  On the other hand, due to an event that cannot be monitored by the power conditioner 8, there is a possibility that an abnormality in the amount of power generation may occur. Specifically, when a breaker trip that is performed on the connection box 6 side without control of the power conditioner 8 occurs, and when there is an object (shading object, shielding object) that blocks sunlight reaching the array 4, Thereby, although the electric power generation amount by the solar power generation system 100 falls, the cause of the abnormality of the electric power generation amount fall cannot be specified from the information which the power conditioner 8 outputs. The factor estimation device 1 estimates the factor when an abnormality in the amount of power generation is reduced due to an event that cannot be monitored by the power conditioner 8.

(Configuration of factor estimating apparatus 1)
FIG. 1 is a block diagram showing a main configuration of a factor estimating apparatus 1 according to an embodiment of the present invention. The factor estimating device 1 is configured to include a control unit 20 and a storage unit 21. The control unit 20 controls the operation of each unit of the factor estimation device 1 in an integrated manner. The storage unit 21 stores various types of information that the control unit 20 reads to execute the function of the factor estimation device 1. In addition, when the control part 20 and the memory | storage part 21 are provided in the measurement monitoring apparatus 2, the memory | storage part with which the control part and the measurement monitoring apparatus 2 which control the measurement monitoring apparatus 2 are each of the factor estimation apparatus 1 of this invention is each. You may serve as the control part 20 and the memory | storage part 21. FIG. Moreover, although the factor estimation apparatus 1 may be provided with a communication part, a display part, an operation part, etc., these are abbreviate | omitting illustration.

  The control unit 20 includes at least a data comparison unit 32 (comparison unit) and a factor estimation unit 33 (estimation unit) as functional blocks. In addition, you may further provide the control part 20, the data acquisition part 30, and the estimated data management part 31 as needed. The storage unit 21 includes a data storage unit 40, a comparison result storage unit 41, and an estimation result storage unit 42.

  The data acquisition unit 30 acquires actual measurement data of the photovoltaic power generation system 100 from the power conditioner 8 every day. The actual measurement data has the following data structure. The daily operating hours of the solar power generation system 100 are 12 hours between 6 o'clock and 18 o'clock, and the operating hours are divided into 12 hours every hour. In the actual measurement data, the actual measured power generation value in each time zone is stored for each time zone. Further, the actual measurement data is associated with a date. If necessary, the total power generation amount of the day (12 hours) may be further associated. Furthermore, the data acquisition unit 30 may acquire actual measurement data on the same day of the neighboring photovoltaic power generation systems 100a and 100b in addition to the photovoltaic power generation system 100 that is the target of factor estimation.

  Moreover, the data acquisition part 30 acquires the solar radiation amount of the measurement day of this measurement data with the said measurement data. More preferably, the data acquisition unit 30 may further acquire the temperature and weather on the measurement date. These pieces of information also preferably have a data structure in which values are stored for each of the 12 time zones. The data acquisition unit 30 may acquire weather information from another service server via the network 11 or the like. Thus, the information regarding the environment around the solar power generation system 100 acquired by the data acquisition unit 30 together with the actual measurement data is referred to as external environment information. In addition to the amount of solar radiation, temperature, and weather, the external environment information may include information such as geographical characteristics, climate, and season of the area where the photovoltaic power generation system 100 is installed.

  The data acquisition unit 30 associates the acquired actual measurement data, the amount of solar radiation, the temperature, and the weather on the target date (the target date of the factor estimation process) with the system ID of the photovoltaic power generation system 100 in the data storage unit 40. Store.

  The estimated data management unit 31 creates or manages estimated data indicating the maximum amount of power that can be generated by the solar power generation system 100, that is, the ideal (target) power generation amount of the solar power generation system 100. To do. The data structure of the estimated data is the same as that of the actually measured data in that the estimated ideal power generation value is stored for each of the 12 time zones.

Although the ideal power generation amount is not limited to this, for example, it is obtained as follows.
(1) The estimated data management unit 31 refers to the correlation between the past actual measured power generation amount of the target system (the photovoltaic power generation system 100 that is the target of the factor estimation process) and the solar radiation amount at that time, and the solar radiation amount of the target day Based on the above, the ideal power generation amount corresponding to the target date is estimated. The estimation data obtained in this way is referred to as solar radiation amount correlation estimation data. The solar radiation amount correlation estimation data is suitable for estimating a factor relating to power generation abnormality when a sufficient solar radiation amount is obtained but a power generation amount commensurate with it is not obtained.
(2) The estimated data management unit 31 estimates the ideal power generation amount of the target system based on the actual power generation amount on the same day as the target date in other systems in the vicinity of the target system. The estimated data management unit 31 may use the measured data of the system installed closest to the target system among the systems having the same performance and configuration as the target system as the estimated data, or installed around the target system. The estimated data may be created from the average value of the measured data of a plurality of systems. The estimation data obtained in this way is referred to as neighborhood comparison estimation data. Neighboring comparison estimation data is related to power generation abnormalities when the target system cannot produce the same amount of power generation as the surroundings even though it generates power under the same conditions (temperature, weather, season, month, day, etc.) as the surroundings. Suitable for estimating factors.
(3) The estimated data management unit 31 may calculate the amount of solar radiation on the target day in the corresponding area where the target system is laid, based on an image acquired from a weather satellite or the like. Then, instead of the actually measured solar radiation amount on the target day, the calculated solar radiation amount obtained as a result of the calculation is used, and the ideal power generation amount of the target system is estimated based on the correlation between the power generation amount and the solar radiation amount. . The estimation data obtained in this way is referred to as calculated solar radiation amount correlation estimation data.
(4) The estimated data management unit 31 further estimates the ideal power generation amount of the target system based on the past actual power generation amount of the target system that is close to the target date and the external environment information conditions. Also good. The estimation data obtained in this way is referred to as past performance estimation data.

  These estimation data may be created in advance and stored in the data storage unit 40. Alternatively, when the estimated data management unit 31 needs to estimate the factor, the estimated data management unit 31 is based on the target actual measurement data (actual measurement data to be subjected to the factor estimation process) or based on the solar radiation amount or the weather on the target day. You may create it.

  Furthermore, when a plurality of types of estimated data are stored in the data storage unit 40 with respect to the target actual measurement data, the estimated data management unit 31 sets the target date condition (external environment information), the purpose of the factor estimation process, and the like. Depending on the case, the optimum estimation data may be selected, and the selected estimation data may be delivered to the downstream data comparison unit 32 or the factor estimation unit 33. Details will be described later in the second embodiment.

  The data comparison unit 32 compares the actually measured data with the estimated data. Specifically, the data comparison unit 32 compares the power generation amounts in the same time period, and represents the ratio of the actually measured power generation amount to the ideal power generation amount (estimated power generation amount) as a percentage, Ask for each time zone. The data comparison unit 32 associates the date with the power generation achievement rate calculated for each time zone, and stores it in the comparison result storage unit 41 as comparison result data. The data comparison unit 32 may further associate information indicating “there is a power generation abnormality” in a time zone where the power generation achievement rate is less than 90% in the comparison result data.

  FIG. 3 is a diagram illustrating a specific example of the data structure of the comparison result data stored in the comparison result storage unit 41. In the table shown in the figure, one record corresponds to information for one day regarding the power generation amount for one solar power generation system 100. One cell in one record corresponds to one time zone of the day. The value stored in the cell is a numerical value calculated from the actually measured power generation amount / the estimated power generation amount, and means a power generation achievement rate. In the example shown in the figure, the power generation achievement rate is represented by a numerical value from 0 to a maximum of 1. A value of “1” indicates that the actually measured power generation amount matches the estimated power generation amount, that is, the target power generation amount has been achieved (the power generation achievement rate is 100%). Furthermore, in the present embodiment, the data comparison unit 32 determines that “the power generation abnormality” occurs when the power generation achievement rate is less than 90%. That is, the data comparison unit 32 associates information indicating “there is a power generation abnormality” with a time zone (target unachieved time zone) where the value in the cell is less than 0.9 (power generation achievement rate less than 90%). That is, the comparison result data output by the data comparison unit 32 is “information indicating the distribution of the time period in which the power generation achievement rate is less than a predetermined value in a certain day”.

  In FIG. 3, a gray marking is given to the cell “with power generation abnormality”. This is done only for the purpose of easy understanding and easy understanding of the invention, and there is no intention to limit the configuration of the data comparison unit 32 that provides information indicating “abnormality in power generation”.

  In addition, in order to grasp which photovoltaic power generation system 100 the comparison result data is, the ID (not shown) of the photovoltaic power generation system 100 (and the power conditioner 8) is tied to each comparison result data. It shall be attached.

  For example, in the comparison result data on the day “day 1”, since the power generation achievement rate is 94% or more for 1 hour in the 12 o'clock range, the data comparison unit 32 determines that power generation was normally performed for the time period. . On the other hand, since the power generation achievement rate is 86.2...% For less than 90% for 1 hour of “day 1” on the same day, it is determined that a power generation abnormality has occurred in that time zone.

  The factor estimating unit 33 estimates the factor of the power generation abnormality that occurred on the day of the comparison result data stored in the comparison result storage unit 41 for the comparison result data on the day including the power generation abnormality time zone. In the present embodiment, the factor estimating unit 33 (1) a shadow formed by a light-shielding object is applied to the array 4 (hereinafter, factor name “shadow”), ) The junction box 6 automatically performed a breaker trip (hereinafter referred to as a factor name “breaker trip”), and (3) some object / substance covers the array 4 (hereinafter referred to as a factor name “shielding object”). The following three types can be estimated.

  The factor estimating unit 33 analyzes various kinds of information stored in the data storage unit 40 by a method described later, and for the day including the power generation abnormality time zone, the factor of the abnormality is “shadow”, “breaker trip” ”Or“ shielding object ”, and the estimation result is stored in the estimation result storage unit 42 in association with the date.

  FIG. 4 is a diagram illustrating a specific example of the data structure of the estimation result data stored in the estimation result storage unit 42. For example, in FIG. 3, it is assumed that the factor estimating unit 33 estimates that the factor of the abnormality of the day “day1” including the power generation abnormality time zone is “shadow”. In this case, the factor estimation unit 33 associates the date “day1” with the factor name “shadow”, and stores this in the estimation result storage unit 42 as estimation result data.

  Next, a method in which the factor estimating unit 33 estimates whether the cause of the abnormality is “shadow”, “breaker trip”, or “shielding object” will be described in detail.

("Shadow" factor estimation method)
5A and 5B are views for explaining the positional relationship between the light shielding object, the array 4 and the sun, and the manner in which the shadow of the light shielding object is cast on the array 4. FIG. FIG. 5A shows an example of the positional relationship in which the light shielding object B is built on the west side of the array 4. In this case, the shadow C of the light-shielding object B is cast on the array 4 installed on the east side of the light-shielding object B in the afternoon time zone when the sun goes down. Thus, the direct solar radiation L1 is blocked from reaching the array 4, and only the scattered solar radiation L2 reaches the array 4 at most. As a result, in the example of the positional relationship shown in FIG. 5A, in the comparison result data obtained from the measured data, the power generation achievement rate is remarkable only in a specific time zone from 12:00 to sunset. The characteristic that it falls is seen. That is, the characteristic that “the time zone in which the power generation achievement rate is less than the predetermined value is unevenly distributed in the time zone from 12:00 to sunset” is seen.

  FIG. 5B shows an example of the positional relationship where the light shielding object B is built near the center of the array 4. In this case, in the morning time zone when the sun rises, the shadow C <b> 1 of the light shielding object B is cast on the west module of the light shielding object B in the array 4. On the other hand, in the afternoon time zone when the sun goes down, the shadow C2 of the light shielding object B is cast on the module on the east side of the light shielding object B. As a result, in the example of the positional relationship shown in FIG. 5B, in the comparison result data obtained from the measured data, the specific time zone from sunset to noon and the specification from noon to sunset It can be seen that the power generation achievement rate is remarkably reduced only during this time period. That is, “the time zone in which the power generation achievement rate is less than the predetermined value is unevenly distributed in part of the time zone from sunset to noon and part of the time zone from noon to sunset”. Features are seen.

  As described above, when a power generation abnormality caused by the shadow of a light-shielding object occurs, the comparison result data at that time states that “the time zone where the power generation amount reduction abnormality occurred is limited to a specific time zone”. Features are seen. Therefore, the factor estimating unit 33 estimates that the cause of the power generation abnormality determined by the data comparing unit 32 is “shadow” when the above characteristics are detected as a result of analyzing the comparison result data.

  Furthermore, the light-shielding object B that casts a relatively large shadow on the array 4 is likely to be permanently installed, and this feature is common to the daily comparison result data in units of weeks or months. It is thought to appear.

  Therefore, in order to increase the accuracy of the factor estimation of “shadow”, the factor estimating unit 33 further compares the comparison result data of the target date and the past few days (for example, the target date) in the target solar power generation system 100. It is preferable to estimate that the cause of the power generation abnormality on the target day is “shadow” when the time period in which the power generation abnormality has occurred is common.

  The factor estimating apparatus 1 of the present invention may be configured to further improve the estimation accuracy of “shadow” by using the following characteristics found in actual measurement data or comparison result data when the factor is “shadow”. .

  FIGS. 6A and 6B are graphs comparing the measured power generation amount and the estimated power generation amount of the photovoltaic power generation system 100. FIG. 6A is a graph of a day when the weather is cloudy or rainy. Yes, (b) is a graph of a day when the weather changes from cloudy to sunny. In any graph, the horizontal axis indicates the date and time when the actually measured power generation amount is measured, and the vertical axis indicates the power generation amount.

  On days when the weather is cloudy or rainy, there is little direct solar radiation, and only scattered solar radiation reaches the array 4, so there is almost no shadow of a light-shielding object on the array 4. Therefore, it is unlikely that power generation will decrease due to shadows. As shown in FIG. 6 (a), it can be seen that there is almost no difference between the measured power generation amount and the estimated power generation amount in the weather with little direct solar radiation, and the abnormality of the power generation amount decrease caused by “shadow” does not occur. . On the other hand, as described above, the light shielding object shields direct solar radiation that should reach the array 4. For this reason, a decrease in the amount of power generation caused by “shadows” is particularly noticeable on a sunny day when there is a lot of direct solar radiation. As shown in (b) of FIG. 6, the actually measured power generation amount affected by the “shadow” is conspicuous with respect to the estimated power generation amount in the afternoon time when the weather was sunny and the amount of solar radiation increased from the afternoon. The power generation achievement rate is below 90%.

  FIG. 7 is a graph showing the relationship between the amount of solar radiation and the actually measured power generation amount in a certain solar power generation system 100. The horizontal axis indicates the amount of solar radiation, and the vertical axis indicates the amount of power generation. The dark gray diamonds plot the relationship between the amount of solar radiation and the measured power generation when there is no shadow in the morning from 6:00 to 14:00. A light gray square point is a plot of the relationship between the amount of solar radiation and the actually measured power generation amount when a shadow is applied in the time zone from 14:00 to 19:00. As shown in this graph, in the time zone from morning to noon (6: 00 to 14:00) that is not affected by the shadow, the amount of solar radiation is greater than the time zone from noon to evening that is affected by the shadow. The more “the more, the greater the amount of power generation” becomes. In other words, the greater the amount of solar radiation, the greater the degree of divergence of the measured power generation between the time zone affected by the shadow and the time zone not affected by the shadow. This means that the greater the amount of solar radiation, the more noticeable the drop in power generation due to the influence of shadows.

  As described above, as a feature of the factor “shadow”, it can be said that the influence of the shadow on the decrease in the power generation amount is particularly great when the weather is fine and when the amount of solar radiation is large. Therefore, in addition to the condition that the time zone in which the abnormality occurred on the target day is limited to a specific time zone, the factor estimating unit 33 has a clear weather on the target day or the amount of solar radiation on the target day. When the value is equal to or greater than the predetermined threshold, it is preferable to estimate that the cause of power generation abnormality is “shadow”. Thereby, it is possible to further improve the accuracy of estimating that the factor is “shadow”.

(Factor estimation method for “breaker trip”)
FIG. 8A is a diagram schematically illustrating the state of the array 4 and the breaker 5 when a breaker trip in string units occurs. (B) of FIG. 8 shows the power generation achievement rate (with respect to the estimated power generation amount) in a specific period (several weeks) in the situation where the breaker trip shown in (a) occurs. It is a graph which shows transition of the ratio (measured power generation amount). The horizontal axis indicates the date and time when the actually measured power generation amount is acquired, and the vertical axis indicates the power generation achievement rate.

  For comparison, the transition of the power generation achievement rate in the solar power generation system 100 under normal conditions and the power generation achievement rate in the solar power generation system 100 under the situation where the shield covers a part of the array 4 are shown. The transition is shown in the same graph.

  As shown in FIG. 8A, it is assumed that the current from three of the eight strings is interrupted for some reason (breaker trip). In this case, the actual power generation amount from the connection box 6 is expected to be reduced to the power generation amount corresponding to the string operation rate (5/8) with respect to the estimated power generation amount when all eight are operating. That is, when the string operating rate is 5/8 pieces = 0.625 (62.5%), the power generation achievement rate is also expected to be 5/8 = 0.625 (62.5%). The As shown in FIG. 8 (b), the power generation achievement rate during the period from 6/13 to 8/7 in which breaker trips occurred in 3 out of 8 shifts around 0.625 (see broken line). And matches the string utilization rate. Therefore, when the characteristic that the power generation achievement rate matches the string operating rate is found, the factor estimating unit 33 estimates the factor of power generation abnormality as “breaker trip”.

  Note that the power conditioner 8 controls and controls a number of connection boxes 6, but the actual measurement data output from the power conditioner 8 to the factor estimation device 1 is integrated into one, and the power generation of each connection box 6 is performed. The amount cannot be grasped by the factor estimating apparatus 1. In this case, the factor estimating unit 33 determines the cause of power generation abnormality according to whether or not the power generation reduction amount is generated in units of one string (an integer multiple of the estimated power generation amount per string). "Breaker trip".

  As described above, the factor estimating apparatus 1 of the present invention can accurately estimate the factor of “breaker trip” based on the power generation reduction amount (= estimated power generation amount−actual power generation amount), and achieve power generation. Based on the rate (= measured power generation amount / estimated power generation amount) or the power generation decrease rate (= power generation decrease amount / estimated power generation amount), the factor of the “breaker trip” can be estimated with high accuracy.

  In addition, as one power controller 8 controls a larger number of arrays 4 (that is, strings), the power generation amount of one string with respect to the total power generation amount becomes a small difference, resulting in a power generation abnormality factor. However, it is difficult to determine whether it is a “breaker trip” or a “shielding object”. Therefore, in order to improve the accuracy of the determination, the factor estimating unit 33 may compare the IV curve shapes obtained by measuring the output of each string between the strings. As shown in FIG. 9B, the IV curve is obtained as a result of plotting the combination of the corresponding voltage and current in the graph showing the relationship between the voltage and current of the output power generation amount for each string. For example, as shown in FIG. 9A, in the array 4, when there is a shield in the string 1, an abnormality occurs in the IV curve of the string 1 as shown in FIG. 9B.

  The factor estimating unit 33 can estimate that there is some shielding object on the string that outputs such an abnormal IV curve. As described above, by referring to the IV curve, it is possible to further increase the accuracy of determining whether the factor is “breaker trip” or “shielding object”. A method for estimating the factor of the “shielding object” will be described in detail later.

  In the above example, the breaker 5 is provided to cut off current for each string. However, a breaker that cuts off current may be provided for each of the other components. For example, a current collection box (not shown) that controls all the connection boxes 6 in the photovoltaic power generation system 100 is provided, and a breaker that cuts off current in units of the array 4 is provided in the current collection box. Also good. In this case, the factor estimating unit 33 of the factor estimating apparatus 1 estimates that the factor of the power generation abnormality is “breaker trip (by array unit)” depending on whether or not the power generation reduction amount is generated by the array unit. That's fine.

(Method for estimating the factor of “shield”)
In the present embodiment, when the cause of the power generation abnormality does not correspond to “shadow” or “breaker trip”, the factor estimating unit 33 estimates that the factor is “shielding”.

  Furthermore, the type of the shield may be specified based on the correlation between the presence or absence of power generation abnormality due to the shield and the surrounding environment (weather, temperature, season, regional characteristics) and the like. Here, the shield means an object or substance that blocks the arrival of sunlight on the panel surface by contacting or adhering to the panel surface that receives sunlight in the array 4. Examples of the shield include volcanic ash, snow, weeds, dust, and yellow sand.

  FIG. 10 shows the power generation achievement rate (measured power generation amount with respect to the estimated power generation amount) in a specific period (approximately two months) before and after the occurrence of the shield in the photovoltaic power generation system 100 in a state where the shield (for example, volcanic ash) is generated. It is a graph which shows transition of the ratio). The horizontal axis indicates the measurement date of the actually measured power generation amount, and the vertical axis indicates the power generation achievement rate.

  As shown in FIG. 10, the power generation achievement rate in the period of 9/9 to 10/16 before the ash fall reaches almost 90%, and it can be seen that the power generation is not affected normally or is not adversely affected by the shielding. The power generation achievement rate during the period of 10/16 to 10/28 after the ash fall was observed on 10/16 and before the rainfall was maintained in a state where it fell to 60 to 70%. This is presumably because volcanic ash falls on the array 4 and blocks sunlight as a shield. Since 10/28 after rain was observed on 10/28, the power generation achievement rate has recovered to about 75 to 90%. This is probably because the volcanic ash that had covered the array 4 due to the rain was washed away, and the sunlight partially reached the array 4 so that the amount of power generation recovered slightly.

  In this way, the factor estimating unit 33 acquires weather information (weather, temperature, etc.) observed retroactively from the target day in units of several days or weeks, and changes in the weather information and the past days or weeks. It is possible to detect a correlation with the fluctuation of the total power generation amount per day, and specify the type of shielding object on the target day based on the correlation. Specifically, the following correlation is recognized in the example shown in FIG. The power generation amount was almost normal for several weeks before the ash fall, but after the day when the ash fall was observed, there was a significant decrease in the amount of power generation. As such, the timing of fluctuations in meteorological information and the amount of power generation are the same. In this case, the factor estimating unit 33 can estimate that the shield that has caused a significant decrease in power generation amount is volcanic ash.

  In addition, the factor estimation part 33 can pinpoint the kind of obstruction by a day unit depending on the case. For example, it is assumed that rainfall is observed around 15:00 after ash fall. In this case, according to the actual measurement data, it is assumed that the power generation amount is kept low until 15:00, and that the power generation amount gradually recovered after 15:00. In this case, the factor estimating unit 33 can confirm the correlation between the timing of rainfall and the timing when the power generation amount starts to recover, and can estimate the factor of power generation abnormality on the target day as “shielding-volcanic ash”. .

(Data comparison process)
With reference to FIG. 11, the flow of the data comparison process performed by the factor estimating apparatus 1 will be described. In the present embodiment, as an example, in the power generation monitoring system 900 of the present invention, the measurement monitoring device 2 including the factor estimating device 1 communicates with one or more power conditioners 8 that control one or more solar power generation systems 100. Then, it is assumed that the measured data including the measured power generation amount of the day is received once a day after 18:00 when the operation time of the photovoltaic power generation system 100 ends from each power conditioner 8. The factor estimation device 1 executes the factor estimation process of the power generation abnormality for each photovoltaic power generation system 100 managed by the power conditioner 8 based on the actual measurement data received from the power conditioner 8.

  First, the data acquisition unit 30 of the factor estimating apparatus 1 receives the actual measurement data and other surrounding environment information (sunlight amount, temperature, weather, region, season, etc.) transmitted from each power conditioner 8 at the end of the day. The data is received and stored in the data storage unit 40. Then, the data comparison unit 32 acquires the stored actual measurement data and the amount of solar radiation from the data storage unit 40 (S101). Next, based on the information acquired in S101, the estimated data management unit 31 creates estimated data corresponding to the actual measurement data to be subjected to factor estimation processing (S102). Note that when the estimation data is created in advance and stored in the data storage unit 40, the step of S102 may be omitted as appropriate.

  The data comparison unit 32 compares measured data and estimated data for one photovoltaic power generation system 100 (S103; comparison step). More specifically, in each data, the value of the power generation amount is stored for each hour zone, and the data comparison unit 32 compares the values of the power generation amount stored in the same time zone in each data. To do. That is, the ratio of the actually measured power generation amount to the estimated power generation amount is obtained. The data comparison unit 32 stores the obtained ratio, that is, the power generation achievement rate, in the comparison result storage unit 41 as comparison result data as shown in FIG. Subsequently, the data comparison unit 32 compares the ratio (power generation achievement rate) obtained for each time zone with a predetermined threshold (for example, 90%). When the power generation achievement rate is 90% or more (YES in S104), the data comparison unit 32 determines that the solar power generation system 100 is operating normally during that time period (S105). On the other hand, when the power generation achievement rate is less than 90% (less than the predetermined value) (NO in S104), the data comparison unit 32 determines that the target power generation amount has not been achieved and a power generation abnormality has occurred during that time period. (S106). In the comparison result data, the data comparison unit 32 may add a flag indicating that a power generation abnormality has occurred in a time zone determined as a power generation abnormality. The data comparison unit 32 repeats the comparison of the power generation amount and the abnormality presence / absence determination for all time zones of the actually measured data and the estimated data (NO in S107).

  When the data comparison unit 32 finishes the comparison and the presence / absence determination for all time zones (YES in S107), the comparison result storage unit reflects the comparison result data (for example, FIG. 3) reflecting the result of the comparison result and the abnormality determination presence / absence. 41 (S108). The comparison result data generated by the data comparison unit 32 is read by the factor estimation unit 33 when the factor estimation unit 33 executes the subsequent factor estimation process (S109).

  According to the above method, not only the total power generation amount per day, but also the power generation amount can be acquired and compared every hour for the operation time from 6:00 to 18:00. Therefore, it becomes possible to grasp the daily power generation achievement rate in units of one hour. If the comparison result data having such a data structure is used in the factor estimation process, the factor can be estimated in consideration of the time zone in which the abnormality has occurred, so that the factor estimation accuracy can be improved. .

(Factor estimation process)
With reference to FIG. 12, the flow of the factor estimation process which the factor estimation part 33 of the factor estimation apparatus 1 performs is demonstrated. In the present embodiment, as an example, the data comparison unit 32 generates the comparison result data in FIG. 3 every time the factor estimation device 1 acquires the actual measurement data transmitted from the power conditioner 8 at the end of the day. And the factor estimation part 33 shall perform the factor estimation process which estimates the factor of the electric power generation abnormality which generate | occur | produced on the target day, whenever the comparison result data are produced | generated by the data comparison part 32. FIG. However, the present invention is not limited to this, and the factor estimation unit 33 may execute factor estimation processing on comparison result data of a specific date in the past, for example, according to an instruction from the user, or for several days (for example, The factor estimation process may be periodically performed on the comparison result data for one week).

  First, when the comparison result data of a certain target date is generated by the data comparison unit 32, the factor estimation unit 33 acquires the comparison result data of the target date from the comparison result storage unit 41 (S201). In the present embodiment, the factor estimating unit 33 first starts verifying the possibility of the factor “shadow” (S202 to S205).

  Specifically, the factor estimating unit 33 identifies a time zone determined by the data comparing unit 32 as a power generation abnormality among the time zones included in the acquired comparison result data, and the power generation abnormality is in a part of the time zone. It is determined whether it occurred in a limited manner or continuously throughout the day (S202).

  If the factor estimating unit 33 determines that the power generation abnormality has occurred only in a part of the time zone (YES in S202), the factor may be “shadow” to increase the estimation accuracy. Proceed to the next verification. That is, the factor estimation unit 33 acquires comparison result data for the latest three days before the target date for the same solar power generation system 100 (S203). Then, it is determined whether or not the time period when the power generation abnormality occurs is common in the comparison result data for the target date and the comparison result data for the latest three days (S204). If the time period when power generation abnormality occurred is common to all four days, the power generation amount has declined for the same specific time period for four consecutive days, due to shadows caused by light-blocking objects that are not removed. It is believed that there is. Therefore, in this case (YES in S204), the factor estimation unit 33 estimates that the factor of power generation abnormality on the target day is “shadow” (S205; estimation step). In addition, regarding the determination of YES in S204, the time periods when power generation abnormality for four days has occurred may not all coincide completely, and some variation may be allowed.

  The factor estimating unit 33 determines that the power generation abnormality has occurred continuously throughout the day (NO in S202), or has determined that the time period in which the power generation abnormality for the past three days has not coincided. If this is the case (NO in S204), the possibility that the factor is “shadow” is low, and the possibility of the next factor is verified. In the present embodiment, the factor estimating unit 33 next starts verification about the possibility of the factor “breaker trip”.

  Specifically, the factor estimating unit 33 compares the estimated power generation amount in each time zone with the actually measured power generation amount, and determines whether or not the power generation decrease amount in each time zone is a string unit (S206). That is, it is determined whether or not the difference between the estimated power generation amount and the actually measured power generation amount is approximately the same in each time zone and is approximately equal to an integer multiple of the estimated power generation amount in one string. . Here, when the factor estimation unit 33 can acquire the measured data for each connection box 6, the power generation achievement rate (measured power generation / estimated power generation) in one connection box 6 (array 4) is You may determine whether it is in agreement with the string operation rate in the connection box 6 (array 4). Regarding the determination of YES in S206, the determination of “match” may not be a complete match of the numerical values, and a certain amount of error may be allowed.

  When the power generation reduction amount is a string unit, or when the power generation achievement rate of each array 4 matches the string operation rate of the array 4 (YES in S206), the factor estimating unit 33 It is estimated that the cause of power generation abnormality is “breaker trip” (S207; estimation step).

  If the power generation reduction amount or the power generation achievement rate does not satisfy the condition of S206 (NO in S206), the factor estimating unit 33 assumes that there is a low possibility that the factor is “shadow” or “breaker trip”. Is estimated to be a “shielding object” (S208; estimation step).

  Thereafter, more preferably, the factor estimating unit 33 further estimates the type of the shielding object. The factor estimating unit 33 determines whether or not there is a correlation between a change in the actually measured power generation amount and a change in external environment information such as weather. When there is a correlation, the factor estimating unit 33 estimates the type of the shielding object based on the detected correlation. For example, when the timing of ash fall coincides with the timing when the power generation amount falls, and the timing of rainfall coincides with the timing when the power generation amount slightly increases, it is estimated that the shielding object is “volcanic ash”. (Estimation step). Here, when there is no correlation, it is highly possible that the shielding object is a kind of shielding that requires an artificial response without specifying the type of the shielding object. Estimate that there is (estimation step).

  Finally, the factor estimation part 33 memorize | stores the result estimated in S205, S207, or S208 in the estimation result memory | storage part 42 as estimation result data, as shown in FIG. 4 (S209). The estimation result data shown in FIG. 4 may further include a column for storing the ID of the photovoltaic power generation system 100 that is the estimation target. A column for storing the type may be included.

  According to the above method, not only the total power generation amount per day, but also the power generation amount can be acquired and compared every hour for the operation time from 6:00 to 18:00. Therefore, it becomes possible to grasp the daily power generation achievement rate in units of one hour. If the comparison result data having such a data structure is used in the factor estimation process, the factor can be estimated in consideration of the time zone in which the abnormality has occurred. Thus, by using the feature extracted from the comparison result data, the factor estimation unit 33 can accurately estimate the factor when an abnormality in the amount of power generation is reduced due to an event that cannot be monitored by the power conditioner 8. It becomes possible.

[Embodiment 2]
As described in the first embodiment, the factor estimating apparatus 1 has three processes, that is, (1) a process for comparing the measured data with the estimated data to determine whether there is a power generation abnormality (data comparison process), (2) Process for estimating whether or not the cause of power generation abnormality is “shadow” (shadow estimation process), and (3) Process for estimating whether or not the cause of power generation abnormality is “breaker trip” ( Trip estimation processing) is executed using the estimated data. In the first embodiment, the factor estimation device 1 is configured to use one type of estimation data (the solar radiation amount correlation estimation data) when executing the three processes. In the second embodiment, a factor estimation device 1 that can further improve the accuracy of factor estimation processing by properly using a plurality of types of estimation data will be described.

  In the second embodiment, the estimated data management unit 31 of the factor estimating apparatus 1 creates solar radiation amount correlation estimation data based on the solar radiation amount on the target day. Furthermore, the estimated data management unit 31 creates neighborhood comparison estimated data based on the measured power generation amount on the same day as the target date in another system having the same conditions as the target system. Note that the actually measured power generation amount in another system is acquired from another power conditioner 8 installed in the vicinity of the power conditioner 8 having jurisdiction over the target system. Furthermore, the estimated data management unit 31 may create calculated solar radiation amount correlation estimation data based on the calculated solar radiation amount calculated based on the meteorological satellite image, if necessary. The past performance estimation data may be created based on the amount.

  Next, the estimated data management unit 31 selects estimated data to be used according to the purpose, and delivers it to the execution subject of the process. Specifically, when the purpose is to estimate the factor “shadow”, the estimated data management unit 31 uses the solar radiation amount correlation estimated data when the data comparison unit 32 executes the data comparison process. The data comparison unit 32 is instructed. Furthermore, the estimation data management unit 31 instructs the factor estimation unit 33 to use the solar radiation amount correlation estimation data when the factor estimation unit 33 executes the shadow estimation process. On the other hand, the estimation data management unit 31 instructs the factor estimation unit 33 to use the neighborhood comparison estimation data when the factor estimation unit 33 executes the trip estimation process.

  As described above, the solar radiation amount correlation estimation data is suitable for estimating factors relating to power generation abnormality when a sufficient solar radiation amount is obtained but a power generation amount commensurate with it is not obtained. For example, when a shadow due to a light shielding object (building such as a building) that cannot be removed is a factor, a similar abnormality may occur in a neighboring panel. Therefore, there is no conspicuous difference between the neighborhood comparison estimation data and the actual measurement data of the target system, and an abnormality of the target system cannot be captured. In addition, the decrease in power generation due to shadows is greatly related to the amount of solar radiation. In other words, the use of the solar radiation amount correlation estimation data can accurately capture the power generation abnormality caused by the “shadow”. Therefore, when the factor “shadow” is estimated, the estimation data management unit 31 instructs the data comparison unit 32 and the factor estimation unit 33 to use the solar radiation amount correlation estimation data, thereby estimating “shadow”. Accuracy can be improved.

  As described above, the neighborhood comparison estimation data estimates factors for power generation abnormality when the same power generation amount as the surroundings cannot be obtained only for the target system even though power generation is performed under the same external environment information conditions as the surroundings. Suitable for doing. For example, when a breaker trip is a factor, a remarkable abnormality occurs only in the corresponding array 4. Such an abnormality can be accurately captured by comparing with actual measurement data in other normally operating solar power generation systems 100 under the same conditions. Therefore, when the factor “breaker trip” is estimated, the estimated data management unit 31 instructs the data comparison unit 32 and the factor estimation unit 33 to use the neighborhood comparison estimation data, whereby “breaker trip” The estimation accuracy can be improved.

  As described above, it is possible to improve the accuracy of each factor estimation process by changing the type of estimated data to be referred to according to the purpose (type of factor to be estimated).

  Furthermore, it is preferable that the estimated data management unit 31 appropriately selects the estimated data used when the data comparison unit 32 determines the power generation abnormality according to the external environment information on the target date. Specifically, when the weather is not clear all day, for example, cloudy, rainy, snowy, etc., it is difficult to make a shadow, and it is unlikely that a power generation abnormality will occur due to the shadow. Therefore, when the weather on the target day is other than sunny, the estimation data management unit 31 instructs the data comparison unit 32 to use the neighborhood comparison estimation data or the past performance estimation data instead of the solar radiation amount correlation estimation data. Instruct. On the contrary, when the weather on the target day is clear, the data comparison unit 32 is instructed to perform the data comparison using the solar radiation amount correlation estimation data instead of the neighborhood comparison estimation data.

  Alternatively, in the first embodiment, it is assumed that the three processes are executed using neighborhood comparison estimation data instead of the solar radiation amount correlation estimation data. However, there are the following concerns in this case. Also in the photovoltaic power generation systems 100a, 100b... That the neighboring power control 8 has jurisdiction, when some kind of power generation abnormality has occurred or the solar power generation system 100 is placed under different conditions. The value of the neighborhood comparison estimation data is not accurate and may contain some errors. Even if the cause of the breaker trip is estimated using the neighborhood comparison estimation data whose values have shifted in this way, the power generation reduction amount is reduced by the string unit even though the factor is actually “breaker trip”. There is a problem that the situation does not become an integral multiple of the quantity and the factor estimation process cannot be performed with high accuracy.

  For such a problem, first, the estimated data management unit 31 compares the external environment information of the target system with the external environment information of the neighboring system. Here, if the external environment information does not match, it is not possible to accurately determine the presence or absence of power generation abnormality even if a comparison is made with a system that does not match the conditions relating to the power generation environment. Therefore, when the external environment information does not match with the neighboring system, the estimated data management unit 31 uses the solar radiation amount correlation estimated data instead of the neighboring comparative estimated data. To direct. Further, the estimated data management unit 31 acquires actual measurement data from the data storage unit 40 only for other systems with the same or at least similar external environment information on the target date, and based only on these actual measurement data , Generate neighborhood comparison estimation data. Thus, the neighborhood comparison estimation data generated so as to be suitable for comparison with the target system is transferred to the factor estimation unit 33, and the factor estimation unit 33 estimates the factor of “breaker trip” for the target system. To use.

  As described above, the estimated data management unit 31 can select optimal estimated data used by the data comparison unit 32 and the factor estimation unit 33 according to the purpose or external environment information. As a result, there is an effect that the accuracy of the factor estimation process is improved.

[Embodiment 3]
In each of the above-described embodiments, the factor estimating apparatus 1 is configured to first execute the factor estimation process of “shadow” and then execute the factor estimation process of “breaker trip”. That is, the order of the types of factors to be estimated is fixed. In the third embodiment, a factor estimation device 1 that can change the execution order of factor estimation processing for each type according to the external environment will be described.

  As described above, the characteristic of power generation abnormality caused by “shadow” becomes remarkable when the weather is clear or when the amount of solar radiation is large. That is, when the weather is clear, power generation abnormality due to “shadows” is likely to occur, and the factor estimation process can be executed with high accuracy using the solar radiation amount correlation estimation data. Therefore, the factor estimating unit 33 causes the “shadow” factor to precede the “breaker trip” factor estimation process when the weather on the target day is sunny or the amount of solar radiation on the target day is equal to or greater than a predetermined value. It is preferable to decide to perform the estimation process.

  On the other hand, when the weather is cloudy or rainy and is not sunny, it is difficult to make a shadow, and it is expected that the accuracy of the “shadow” factor estimation process will be reduced. Therefore, it is preferable that the factor estimation unit 33 executes the “breaker trip” factor estimation process prior to the “shadow” factor estimation process when the weather on the target day is not sunny.

  That is, in the factor estimating unit 33 of the factor estimating device 1 of the present invention, the power generation achievement rate and the power generation reduction amount are equivalent. Specifically, the factor estimation device 1 according to the present invention estimates a factor of power generation abnormality that has occurred in the solar power generation system, based on the measured power generation amount of the solar power generation system on the day, with that day as the target day. A data estimation unit 32 that is a factor estimation device, and outputs a power generation achievement rate indicating a ratio of the actually measured power generation amount to an estimated power generation amount indicating an expected power generation amount for each predetermined time zone on the target day; In place of the power generation achievement rate, a factor estimation unit 33 is provided that estimates a factor of power generation abnormality that has occurred on the target date based on a power generation decrease amount that indicates a difference between the estimated power generation amount and the actual power generation amount. Also good. In this case, the factor estimating unit 33 causes the breaker trip by the breaker to be a cause of power generation abnormality when the power generation decrease amount is equal to an integral multiple of the estimated power generation amount of units united by one breaker. Estimated.

  As described above, by estimating in order from the types of factors that can be accurately estimated, for example, the possibility of “breaker trip” is verified first, and then “shadow” may be the factor. By verifying the above, it is possible to accurately estimate the cause of power generation abnormality in all time zones.

[Embodiment 4]
In each of the above embodiments, an example in which one server (that is, the measurement monitoring device 2 or the remote monitoring server 3) is used to realize the factor estimation device 1 has been described. However, each function of the factor estimating apparatus 1 may be realized by a plurality of servers. For example, each function of the factor estimation device 1 may be realized by an individual server. Alternatively, some of the functions of the factor estimating device 1 may be realized by the measurement monitoring device 2 and the remaining functions may be realized by the remote monitoring server 3. In addition, as mentioned above, when applying a some server with respect to each function of the factor estimation apparatus 1, each server may be managed by the same provider, and is managed by a different provider. Also good.

[Modification]
The estimated data management unit 31 may create neighborhood comparison estimation data, calculated solar radiation amount correlation estimation data, or past performance estimation data instead of the solar radiation amount correlation estimation data. The data comparison unit 32 and the factor estimation unit 33 Based on the estimated data created by the estimated data management unit 31, data comparison processing and shadow and trip estimation processing may be executed, respectively. According to the said structure, estimation of a factor can be implemented accurately, without utilizing the solar radiation amount measured with the solar radiation meter. In the factor estimation process based on the amount of solar radiation, it is necessary to separately install a measuring instrument such as a pyranometer for factor estimation, and there is a problem that the installation cost of the photovoltaic power generation system 100 increases. According to the said structure, such a problem of cost can be avoided.

  In the power generation monitoring system 900 of the present invention, the measuring device 7 that measures the direct current and voltage of each connection box 6 communicates directly with the measurement monitoring device 2 (factor estimation device 1) without going through the power conditioner 8. May be. Alternatively, the measurement device 7 may not be provided, and the direct current and voltage of each connection box 6 may be notified directly to the measurement monitoring device 2. In this case, the factor estimating apparatus 1 can grasp the actually measured power generation amount for each connection box 6 of each array 4.

  Therefore, the data comparison unit 32 of the factor estimating apparatus 1 can execute a comparison between the estimated power generation amount and the actually measured power generation amount for one connection box 6. For this reason, the factor estimation unit 33 can compare in detail the power generation achievement rate and the string operation rate for each connection box 6 and verify whether or not the power generation decrease amount is in string units. Therefore, the estimation accuracy of the factor “breaker trip” can be greatly improved.

[Example of software implementation]
The control block (particularly, the data acquisition unit 30, the estimated data management unit 31, the data comparison unit 32, and the factor estimation unit 33) of the factor estimation device 1 is a logic circuit (hardware) formed in an integrated circuit (IC chip) or the like. It may be realized by software, or may be realized by software using a CPU (Central Processing Unit).

  In the latter case, the factor estimating apparatus 1 includes a CPU that executes instructions of a program that is software for realizing each function, and a ROM (Read Only Memory) in which the program and various data are recorded so as to be readable by a computer (or CPU). Alternatively, a storage device (these are referred to as “recording media”), a RAM (Random Access Memory) for expanding the program, and the like are provided. Then, the computer (or CPU) reads the program from the recording medium and executes it to achieve the object of the present invention. As the recording medium, a “non-temporary tangible medium” such as a tape, a disk, a card, a semiconductor memory, a programmable logic circuit, or the like can be used. The program may be supplied to the computer via an arbitrary transmission medium (such as a communication network or a broadcast wave) that can transmit the program. The present invention can also be realized in the form of a data signal embedded in a carrier wave, in which the program is embodied by electronic transmission.

  The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope shown in the claims, and embodiments obtained by appropriately combining technical means disclosed in different embodiments. Is also included in the technical scope of the present invention.

1 Factor estimation device 2 Measurement monitoring device (Factor estimation device)
3 Remote monitoring server (factor estimation device)
4 Array 5 Breaker 6 Junction box 7 Measuring instrument 8 Power conditioner (Power conditioner)
9 Pyrometer 10 Thermometer 11 Network 20 Control unit 21 Storage unit 30 Data acquisition unit 31 Estimated data management unit 32 Data comparison unit (comparison unit)
33 Factor estimation part (estimation part)
40 Data storage unit 41 Comparison result storage unit 42 Estimation result storage units 100, 100a, 100b Photovoltaic power generation system 900 Power generation monitoring system

Claims (7)

A factor estimation device that estimates a factor of power generation abnormality that has occurred in the photovoltaic power generation system based on the actual measured power generation amount of the solar power generation system on the day,
A comparison unit that outputs a power generation achievement rate indicating a ratio of the actually measured power generation amount to an estimated power generation amount indicating an expected power generation amount for each predetermined time zone of the target day;
Based on the distribution of the target unachieved time zone in which the power generation achievement rate is less than a predetermined value, an estimation unit that estimates a factor of power generation abnormality that has occurred on the target date,
In the solar power generation system, a breaker that cuts off current is provided for each component constituting the solar cell array,
In the distribution of the target date and one or more days before the target date, the estimation unit causes a shadow of the light shielding object to cause power generation when the target unachieved time zone has a common bias And
The estimation unit calculates the estimated power generation amount and the actually measured power generation amount when there is no bias in the target unachieved time zone in the distribution of the target day, or when there is no bias in each of the distributions. Based on the power generation reduction amount indicating the difference, the factor of power generation abnormality that occurred on the target date is further estimated,
The estimation unit estimates that the breaker trip by the breaker is a factor of power generation abnormality when the power generation decrease amount is equal to an integral multiple of the estimated power generation amount of a unit collected by one breaker, A factor estimation device characterized in that, when they do not coincide with each other, it is estimated that a shield attached on the solar cell array is a factor of power generation abnormality.   The estimation unit determines whether there is a correlation between the fluctuation in the actually measured power generation amount and the fluctuation in the external environment information that is information related to the environment around the photovoltaic power generation system. The factor estimation apparatus according to claim 1, further estimating the estimated type of the shielding object.   The estimation unit estimates the type of shielding object based on the weather before the change when the timing at which the measured power generation amount changes coincides with the timing at which the weather on the target day changes. The factor estimation apparatus according to claim 2.   The estimation unit estimates that the shield that causes a power generation abnormality should be artificially removed when there is no correlation between the fluctuation of the actually measured power generation amount and the fluctuation of the external environment information. The factor estimating device according to claim 2 or 3, wherein A control method of a factor estimating device that estimates a factor of power generation abnormality that has occurred in the photovoltaic power generation system based on the actual measured power generation amount of the photovoltaic power generation system on the day,
A comparison step of outputting a power generation achievement rate indicating a ratio of the actually measured power generation amount to an estimated power generation amount indicating an expected power generation amount for each predetermined time zone on the target day;
Estimating the factor of power generation abnormality that occurred on the target date based on the distribution of the target unachieved time zone in which the power generation achievement rate is less than a predetermined value,
In the solar power generation system, a breaker that cuts off current is provided for each component constituting the solar cell array,
In the estimation step, when the target day and the distribution of one or more days before the target day have a common bias in the target unachieved time zone, the shadow of the light shielding object is a cause of power generation abnormality. And
When there is no bias in the target unachieved time zone in the target day distribution, or when there is no common bias in each of the distributions, the power generation decrease indicating the difference between the estimated power generation amount and the actually measured power generation amount Based on the quantity, further estimate the cause of the power generation abnormality that occurred on the target date,
When the power generation decrease amount is equal to an integer multiple of the estimated power generation amount of units united by one breaker, it is estimated that the breaker trip by the breaker is a factor of power generation abnormality and does not match In addition, it is estimated that the shield attached on the solar cell array is a cause of power generation abnormality.   A control program for causing a computer to function as the factor estimating device by causing the computer to execute each step according to claim 5.   A computer-readable recording medium on which the control program according to claim 6 is recorded.

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