Earthquake prediction methods

Abstract

To provide a short-term earthquake forecasting method that can be implemented by anybody through a simple procedure, in the face of the fact that the electromagnetic earthquake forecasting method and the mechanical earthquake forecasting method have shortcomings, the one for the electromagnetic earthquake prediction method being that the level of difficulty in implementation does not allow the method to be easily implemented by anybody and that the method may fail to forecast an earthquake until the last moment or unless the earthquake is huge, and the one for the mechanical earthquake forecasting method being that the method is often not capable of making short-term forecasting of an earthquake.SOLUTION: Even through there are many difficulties in providing an earthquake forecasting method, providing an earthquake prediction method that is close to the level of earthquake forecasting using an earthquake prediction system that utilized a solar power generation system makes it possible even for non-experts to make short-term prediction of an earthquake through a simple procedure and the earthquake prediction system can be improved to realize earthquake forecasting in the future.SELECTED DRAWING: None

Description

[Technical field]

[0001] The present invention relates to an earthquake prediction method using a solar power generation system. [Background technology]

[0002] There are two types of earthquake prediction: electromagnetic earthquake prediction and mechanical earthquake prediction. Patent Document 1 and Non-Patent Document 1 below are electromagnetic earthquake prediction. Patent Document 1 clarifies the relationship between electromagnetic anomalies and earthquakes, measuring electromagnetic noise and stating that there is a high possibility of short-term earthquakes occurring near communication base stations with poor communication conditions. Considering the cost and difficulty of manufacturing the equipment, building the system, and analyzing the data, earthquake prediction using this method is not something that can be easily carried out by non-experts.

[0003] Non-Patent Document 1 states that before a huge earthquake, a disturbance occurred in the ionosphere, causing an abnormality in the total electron content of the ionosphere. It is said that an abnormality occurred in the total electron content of the ionosphere 40 minutes before the occurrence of the Tohoku Pacific Ocean Earthquake, so in the case of this earthquake, the abnormality occurred just before the earthquake. In addition, the occurrence of an abnormality in the total electron content of the ionosphere as a precursor to an earthquake may be limited to the occurrence of a huge earthquake, and it is not clear whether it is possible to predict a large earthquake that is not as large as a huge earthquake but is expected to cause damage. In this specification, a huge earthquake refers to an earthquake with a magnitude (hereinafter referred to as M) of 8.0 or more, a large earthquake refers to an earthquake with a magnitude of 7.0 or more but less than M8.0, and a small or medium earthquake refers to an earthquake with a magnitude of less than M7.0.

[0004] Non-Patent Document 2 is a mechanical earthquake research, which predicts earthquakes by analyzing strain. It is an effective method for identifying areas where earthquakes occur in the medium to long term, but it is considered to be difficult to predict short-term earthquakes. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent 5920810 [Non-patent literature]

[0006] [Non-Patent Document 1] Kosuke Heki, "Increasing ionospheric electrons just before a large earthquake," Earthquake Journal, No. 53, pp. 19-25, Earthquake Prediction Research Promotion Association, June 2012 [Non-Patent Document 2] Takuya Nishimura, "Strain accumulation in the Nankai Trough earthquake source region," Earthquake Journal No. 62, pp. 1-7, Earthquake Prediction Research Promotion Association, December 2016 Summary of the Invention [Problem to be solved by the invention]

[0007] The problem that the present invention aims to solve is to provide a method for easily predicting short-term earthquakes even by non-experts. If a solar power generation system is available, new investment is not required, and even non-experts can easily predict short-term earthquakes using numerical values. In the case of an abnormal value, it is estimated that there is a high probability that an earthquake of a certain magnitude or more will occur near Japan within two days. In addition, even non-experts can predict short-term earthquakes using numerical values ​​based on data from solar power generation systems (hereinafter referred to as multiple distributed systems) that are installed in multiple locations with clear solar cell capacity and can accurately measure solar radiation intensity and generated power. If the measurement results are determined to be in an abnormal state, it is possible to estimate that there is a high probability that an earthquake will occur in the short term in an area close to the abnormal value measurement location. Although both claims are short-term earthquake predictions, earthquake predictions are not possible until just before the occurrence of an earthquake, and in many cases predictions are possible before that. In addition, even if it is not a huge earthquake, it is often possible to predict large earthquakes and small and medium-sized earthquakes of M4.5 or more but less than M7. It cannot be said that the accuracy of when, where, and the scale of an earthquake will occur is high, and it is a prediction rather than a prediction, but there is a possibility that it can be improved to the level of prediction with regard to claims 2 and 3. Solar cell capacity is the total value of the nominal maximum output of the solar cell modules that make up a solar power generation system. [Means for solving the problem]

[0008] Photovoltaic power generation is a method of generating electricity by converting solar energy into electricity. The nominal maximum output of a solar cell module is 1.5 air mass and 1kW / m irradiance (solar radiation intensity) as specified in JIS C8918. 2 The values ​​are for a module temperature of 25°C. According to the product pamphlet of the manufacturer of the home solar power generation system (hereafter referred to as the home system), the generated power is at most 70% to 80% of the solar cell capacity due to solar cell losses, i.e. losses due to the rise in the surface temperature of the solar cell module, power conditioner losses, and other losses, and for a home system with a solar cell capacity of 3.7kW, the maximum generated power is about 2.59kW to 2.96kW.

[0009] In home systems, the power generation has been recorded to be much higher than 2.96kW, or 80% of the solar cell capacity, and although there are factors that affect the power generation, such as the intensity of solar radiation, the temperature and degree of dirt on the surface of the solar cell module, and the angle at which sunlight hits the solar cell module, it is unlikely that the power generation will be much higher than that stated in the manufacturer's product brochure, even if favorable conditions are met. In solar power generation systems from other manufacturers, the maximum power generation is said to be around 70% to 80% of the solar cell capacity, and it is unlikely that the power generation will be much higher than this.

[0010] Solar irradiance is the intensity of sunlight, and its unit is kW / m 2 The solar radiation intensity on a clear day is about 1kW / m 2 It is said that the power generated by a solar power generation system is roughly proportional to the intensity of solar radiation. In a solar power generation system, the power generated can be measured using an attached monitor, and in a system with multiple distributed installations, in addition to the power generated, the intensity of solar radiation can be measured using a pyranometer installed at the same angle as the solar cell module. The nominal maximum output of a solar cell module is an irradiance of 1kW / m 2 The power generated is approximately proportional to the solar radiation intensity, and the maximum power generated is 80% or less of the solar cell capacity. Therefore, in a multiple distributed installation system, the power generated is set at a solar radiation intensity of 1kW / m2 In this case, the ratio of the proportionally converted value to the solar cell capacity is usually 80% or less.

[0011] When solar power generation systems generate power that far exceeds what is stated in the manufacturer's brochure, this means that there are cases where even greater power can be generated at the same solar radiation intensity. In solar power generation systems in commercial facilities equipped with pyranometers, and in solar power generation systems equipped with pyranometers whose power generation data is available online, there is likely a mismatch in the timing of the measurement of the power generation and solar radiation intensity, and uneven solar radiation intensity due to the influence of clouds, and the measurement results of the power generation and solar radiation intensity may not be used directly for earthquake prediction. However, when looking at data in stores and online, it is clear that although the change in the ratio of power generation to solar radiation intensity is gradual, the range of fluctuation is large. It is clear that there is a large difference in power generation even at the same solar radiation intensity, and that when the power generation is calculated for a solar radiation intensity of 1kW / m 2 The large fluctuation in the ratio of the proportional conversion value to the solar cell capacity in this case cannot be theoretically explained, and suggests the existence of some unexplained cause that increases the generated power.

[0012] The device required in this invention is a general solar power generation system equipped with a monitor that displays the generated power, as described in claim 1. When the ratio of generated power to the capacity of the solar cell is equal to or greater than a preset first reference value, it is estimated that an earthquake of a certain magnitude or greater will occur in the short term.

[0013] A multiple distributed installation system requires multiple photovoltaic power generation systems with the ability to measure solar radiation intensity and generated power, a system to transmit data from each solar power generation system to a collection location, and a system to collect and calculate the data at the collection location and predict earthquakes. Even when solar radiation appears to be the same to the naked eye, the maximum value of generated power in the same time period from one day to the next can be significantly different. When abnormal values ​​appear, there is a high probability of a short-term earthquake occurring, so in a multiple distributed installation system, the generated power is calculated based on a solar radiation intensity of 1kW / m 2In the case of i or more photovoltaic power generation systems, the ratio of the proportionally converted value to the solar cell capacity is equal to or greater than a preset second reference value, and therefore it is estimated that an earthquake of a certain scale or greater will occur in the short term. Depending on how the second reference value is set, it is possible to predict earthquakes of a certain scale or greater, including small and medium-sized earthquakes, or to predict earthquakes limited to large earthquakes or greater. In addition, when the ratio of the number of measurement points with values ​​equal to or greater than a preset third reference value to the total number of measurement points is equal to or greater than a preset fourth reference value, it is estimated that an earthquake will occur in the short term. The third reference value is set to a value lower than the second reference value, and if the distribution of measurement points with values ​​equal to or greater than the third reference value is multiple and wide, it is estimated that an earthquake will occur in the short term. Depending on how the third reference value is set, it is possible to predict earthquakes of a certain scale or greater, including small and medium-sized earthquakes, or to predict earthquakes limited to large earthquakes or greater. In earthquake prediction in a multiple distributed installation system, the short term is often assumed to be until the day after tomorrow, but the precursors of an earthquake of a large scale or greater may appear earlier. Effect of the Invention

[0014] The present invention enables even non-experts to easily predict short-term earthquakes, and also enables public institutions to issue earthquake prediction information. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] The necessary matters for implementing the earthquake prediction method described in claim 1 are as follows. First, the solar power generation system must have a monitor that displays the generated power. Second, a power conditioner with a rated output power equal to or greater than the solar cell capacity must be used. A power conditioner with a sufficient rated output power is required to predict earthquakes based on the magnitude of the generated power relative to the solar cell capacity. A high-rated power conditioner is preferable, but since this is mainly intended for home solar power generation systems, the minimum realistic conditions are shown. Third, the solar cell module must be installed facing south or close to south. The further away from the south the installation direction is, the smaller the maximum daily generated power becomes, and it becomes difficult to determine whether the generated power is abnormal when comparing the generated power with the solar cell capacity. Fourth, the installation angle must be around 30°. In the vicinity of Japan, extreme angles such as 0° and 90° mean that there are seasons when the angle between the sunlight and the solar cell module is not suitable for optimal power generation, making it unsuitable for earthquake prediction throughout the year. In addition, if the angle is shallow, rainfall is less likely to wash away dirt on the surface of the solar cell module, and there is a possibility that surface dirt will cause a decrease in generated power. Fifth, all solar cell modules must be installed in the same direction and at the same inclination angle. If the installation direction or angle differs depending on the solar cell module, power generation data under different conditions will be mixed, and it will be difficult to accurately determine whether the generated power is abnormal. Sixth, the maximum generated power on the day can be grasped and measured to one decimal place. Some products have a function to record the maximum generated power on the day, but even if this function is not available, visual confirmation on the monitor is also possible. In addition, in order to obtain highly accurate data, it is necessary to be able to measure to one decimal place. Seventh, there is no output control by the power company. Eighth, the solar cell module must not be shaded. Although uneven solar radiation intensity on the solar cell module due to the influence of cloud shadows is unavoidable, shadows caused by nearby buildings, utility poles, large trees, etc. are not suitable for generating power measurement. Ninth, there must be little dirt on the surface of the solar cell module. Dirt is usually washed away by rain, and although snow accumulation is unavoidable, fallen leaves and bird droppings must be removed if they are found. Tenth, in order to obtain highly accurate data, the solar cell capacity should be approximately 3kW or more.Eleventh, the solar power generation system must be installed within the last 15 years and not have deteriorated over time.

[0016] The outline of the home system is that the solar cell module is installed facing south-southeast, with an inclination angle of 24.2°, the solar cell capacity is 3.7kW, the power conditioner rated output power is 4.0kW (actual value 4.1kW), and it is a polycrystalline silicon type, and it meets the necessary requirements. As a specific example, on the day of the Tohoku Pacific Ocean Earthquake of M9.0 that occurred at 14:46 on March 11, 2011, a power generation of 4.1kW was recorded just before noon before the earthquake. This is about 111% of the output of the solar cell capacity, and is the maximum value due to the constraints imposed by the rated output power of the home system's power conditioner, and is an abnormally high power generation that is not normally possible. If there were no constraints on the power conditioner, it is possible that the power generation would have been even higher. Measurements with the home system were only started on March 11, 2011, and it is possible that the abnormally high power generation had been occurring before the day before. In addition, many large aftershocks occurred after that, and even during those times a power generation of about 3.8kW was recorded. Based on the hypothesis that abnormally high power generation is related to earthquakes of a certain size or larger, the relationship between power generation and earthquake occurrence was examined. According to the manufacturer's pamphlet, the maximum power generation is 80% or less of the solar cell capacity, and even if favorable conditions are met, such as the angle of sunlight hitting the solar cell module being close to a right angle, low temperature, and little dirt on the surface of the solar cell module after rain, it is thought that it is impossible for a power generation of 111% of the solar cell capacity to occur under normal conditions. Power generation is roughly proportional to solar radiation intensity, and solar radiation intensity on a clear day is about 1kW / m 2 It is said that a solar radiation intensity of 1kW / m is a precursor to an earthquake. 2 Since the power generated does not exceed 111% of the solar cell capacity by a large margin, and various losses occur, the power generated does not usually reach 111% of the solar cell capacity.

[0017] Therefore, the power generation of 90% of the solar cell capacity of the home system, i.e., 3.4kW, was set as the first reference value in advance, and power generation of 3.4kW or more was defined as an abnormal value, and the relationship with earthquakes was examined. In addition, the power generation of less than 80% of the solar cell capacity, 2.9kW or less, was defined as a normal value even when the weather was fine and the measurement conditions were good near the home, and the relationship with earthquakes was examined. The earthquakes to be examined were earthquakes of M4.5 or more that occurred near Japan, including the four northern islands, Sakhalin, and Taiwan. The reason for targeting earthquakes of M4.5 or more is that there are many earthquakes near Japan, and if smaller earthquakes were included, the number of target earthquakes would increase, making it difficult to understand the relationship between abnormal values ​​and earthquakes. In addition, if the scale of the target earthquakes is increased, the number of target earthquakes would decrease, and earthquakes corresponding to abnormal values ​​are not necessarily large earthquakes, so in this case too, the relationship with earthquakes would be difficult to understand. For this reason, the scale of the target earthquakes for the examination was set to M4.5 or more.

[0018] The relationship between the occurrence of abnormal values ​​of generated power in a home system and earthquakes of a certain scale or larger is verified by three methods. When the generated power reaches 90% or more of the solar cell capacity, i.e., 3.4kW or more, which is the first reference value set in advance, there is a high probability that an earthquake of M4.5 or more will occur in the vicinity of Japan within two days. The first method is a comparison between the occurrence rate of earthquakes of M4.5 or more after the occurrence of an abnormal value and the occurrence rate of earthquakes of M4.5 or more after the occurrence of a normal value without abnormal values. The second method is a case study of individual cases of abnormal values ​​and earthquakes of M4.5 or more. The third method is an analysis of the relationship between the occurrence frequency of earthquakes of M4.5 or more and the occurrence frequency of abnormal values. According to the Japan Meteorological Agency, earthquake prediction is a prediction that accurately limits the three elements of time, place, and size of an earthquake. Claim 1 of the present invention does not fully meet this definition in terms of location and size, so it is earthquake forecast rather than earthquake prediction. However, since it is clear that there is a relationship between the occurrence of abnormal values ​​in a solar power generation system and the occurrence of earthquakes of a certain scale or larger, it is significant for the realization of future earthquake prediction.

[0019] First, we will examine the occurrence of earthquakes of magnitude 4.5 or greater after abnormal values ​​appear in the home system. Measurements were conducted on the home system on 253 days in 2020, of which 170 were sunny days with good measurement conditions. Of these, abnormal values ​​appeared on 60 days, and 57 days had good weather and good measurement conditions but the generated power was 2.9kW or less. After the abnormal value appeared, the number of days with earthquakes of magnitude 4.5 or greater on the day, the day after, and the day after that was 15 days, 31 days (15 on the day, 16 the day after), and 42 days (15 on the day, 16 the day after, 11 the day after), respectively, and the probability of an earthquake of magnitude 4.5 or greater occurring on the day was 25.0% (15 days out of 60 days), the probability of an earthquake occurring by the day after was 51.7% (31 days out of 60 days), and the probability of an earthquake occurring by the day after was 70.0% (42 days out of 60 days). In contrast, when the weather is good and the measurement conditions are good, but the generated power is 2.9kW or less, the number of days when earthquakes of M4.5 or more occur is 7 days on the day, 20 days until the next day (7 on the day, 13 the next day), and 30 days until the day after (7 on the day, 13 the next day, 10 the day after), and the occurrence probability is 12.3% (7 days out of 57 days), 35.1% (20 days out of 57 days), and 52.6% (30 days out of 57 days), respectively. In comparison, 25.0%>12.3%, 51.7%>35.1%, and 70.0%>52.6%, and in all cases, the occurrence rate of earthquakes of M4.5 or more is higher when abnormal values ​​appear in the home system than when normal values ​​appear. Note that if multiple earthquakes of M4.5 or more occur by the day after the abnormal value appears, only the first earthquake of M4.5 or more is counted.

[0020] Similar verification is continuing into 2021. Measurements were taken on the home system 204 days from January to October, of which 131 were days when measurement conditions were good, of which 49 were days when abnormal values ​​appeared, and 53 days when the power generation was 2.9kW or less despite good measurement conditions. After the abnormal values ​​appeared, the number of days when earthquakes of magnitude 4.5 or higher occurred on the day, up to the next day, and up to the day after that were 18 days, 38 days until the next day (18 on the day, 20 the next day), and 42 days until the day after that (18 on the day, 20 the next day, and 4 the day after that), respectively, and the probability of an earthquake of magnitude 4.5 or higher occurring on the day was 36.7% (18 out of 49 days), the probability of an occurrence by the next day was 77.6% (38 out of 49 days), and the probability of an occurrence by the day after that was 85.7% (42 out of 49 days). In contrast, when the measurement conditions are good but the generated power is 2.9kW or less, the number of days when an earthquake of M4.5 or greater occurs is 16 on the day, 32 days until the next day (16 on the day, 16 the next day), and 39 days until the day after (16 on the day, 16 the next day, 7 the day after), with occurrence probabilities of 30.2% (16 out of 53 days), 60.4% (32 out of 53 days), and 73.6% (39 out of 53 days), respectively. In comparison, the rates are 36.7% > 30.2%, 77.6% > 60.4%, and 85.7% > 73.6%, and in all cases the occurrence rate of earthquakes of M4.5 or greater is higher when abnormal values ​​appear in the home system than when normal values ​​appear.

[0021] Secondly, we will provide examples of the relationship between abnormal values ​​in a home system and earthquakes of a certain magnitude or larger. We have already mentioned the case where 4.1 kW (about 111% of the solar cell capacity) was recorded just before noon on the day before the Tohoku Pacific Ocean Earthquake occurred, but we will provide five other examples.

[0022] The first example is the M6.4 Hualien earthquake that occurred in eastern Taiwan at 00:50 on February 7, 2018 (Japan time), followed by a M6.1 earthquake in the early morning of February 8. Measurement results from this time showed that 3.8kW (approximately 103% of the original) was recorded on February 5, two days before the earthquake, 4.0kW (approximately 108% of the original) on February 6, the day before, and 3.8kW (approximately 103% of the original) on February 7, the day before the subsequent M6.1 earthquake, and these significantly abnormal values ​​are thought to have been precursors to the earthquake in question.

[0023] The second example is a magnitude 5.6 earthquake that occurred at 2:25 a.m. on April 28, 2019, in the southern Tokachi region. An abnormal value of 3.5 kW (approximately 95%) was recorded on the previous day, April 27.

[0024] The third example is a magnitude 5.8 earthquake that occurred off the east coast of Hokkaido at 6:23 a.m. on March 3, 2021, with an epicenter of 5.8. An abnormal value of 3.9 kW (approximately 105%) was recorded on the previous day, March 2.

[0025] The fourth example, although not of magnitude 4.5 or higher, is described below for an earthquake that occurred off the north coast of Nata, Higashi-ku, Fukuoka City, near my home, about 10km from my home to the epicenter. A magnitude 3.8 earthquake occurred at 20:42 on March 16, 2020, and my home system recorded a significant abnormal value of 4.0kW (about 108%) before the earthquake on that day. This is thought to be an example of an earthquake that, even if it is not large in scale, can have large precursors if the epicenter is close by.

[0026] The fifth example is a magnitude 6.6 earthquake that occurred at 00:45 on November 11, 2021, southeast of the main island of Okinawa, and recorded an abnormal value of 3.8 kW (approximately 103%) on the previous day, November 10. All five of the above examples indicate that when power generation exceeds the first preset reference value, a magnitude 4.5 or higher earthquake or something similar occurs near Japan within the next two days.

[0027] Thirdly, we will discuss the fact that there are more anomalous values ​​in months with more earthquakes of magnitude 4.5 or greater. In 2020, April and July are months with many earthquakes of a certain magnitude or greater. Conversely, November is a month with few earthquakes of a certain magnitude or greater. The situation for these months will be explained. These do not directly indicate a relationship between the occurrence of power generation above the first preset threshold and earthquakes of M4.5 or greater, but based on the relationship between the frequency of earthquakes of M4.5 or greater and the frequency of occurrence of abnormal values, they explain the certainty that when power generation above the first threshold occurs, there is a high probability that an earthquake of M4.5 or greater will occur near Japan within two days.

[0028] In April 2020, there were 22 earthquakes of magnitude 4.5 or greater. Of the days when measurements were taken at home, there were 17 days with good weather and good measurement conditions, of which 8 days saw abnormal values ​​in the home system, a high rate of 47.1%. Of the 170 days in 2020 when the weather was good and suitable for measurements near the home, abnormal values ​​occurred on 60 days, a rate of 35.3%, so the abnormal value occurrence rate of 47.1% can be said to be high.

[0029] Even in July 2020, there were 17 earthquakes of magnitude 4.5 or greater, and while there were 9 days when measurement conditions were good, there were 5 days when abnormal values ​​appeared in the home system, resulting in an abnormal value occurrence rate of 55.6%, which is high.

[0030] November 2020 corresponds to a month with few earthquakes of a certain magnitude or above, with eight earthquakes of magnitude 4.5 or above, and two days in which abnormal values ​​appeared in the home system compared to 14 days when measurement conditions were good, resulting in an abnormal value occurrence rate of only 14.3%, which is a low value. This is an example that shows that there are fewer abnormal values ​​in months with fewer earthquakes of a certain magnitude or above.

[0031] The three methods show that there is a correlation between the occurrence of abnormal values ​​in the home system and earthquakes of a certain size or larger. The above is an earthquake prediction method that estimates that an earthquake will occur when the ratio of generated power to solar cell capacity is equal to or greater than 90%, which is a preset first reference value. When generated power equal to or greater than the first reference value appears, it is possible to estimate that there is a high probability that an earthquake of magnitude 4.5 or greater will occur near Japan within two days. The high probability is 70.0% in 2020 and 85.7% from January to October 2021. Although this method has limitations in terms of making highly accurate earthquake predictions, the earthquake prediction that there is a high probability of an earthquake of magnitude 4.5 or greater will occur near Japan within two days when an abnormal value appears cannot be said to be earthquake prediction, but it can be said to be a meaningful earthquake prediction method that will lead to the realization of future earthquake predictions.

[0032] The earthquake prediction method described in claim 1 has several problems. First, because the weather is judged to be suitable for measurement by visual inspection, if this judgment is incorrect, accurate earthquake prediction is not possible. Second, because the solar radiation intensity is not measured, it is difficult to judge whether the generated power is abnormal in a time period when there is insufficient solar radiation or when there is solar radiation but the solar altitude is low and the generated power is small. However, for a time period when there is sufficient solar radiation and the solar altitude is not high, it is not impossible to predict by comparing with the past monthly and hourly generated power. Third, although this method is mainly intended for measurement at one location, the situation in other areas is unknown with measurement at one location, and it is not possible to grasp the precursors of a wide-area earthquake, and it cannot be said that the prediction accuracy is high, especially with regard to the scale and epicenter of the earthquake. Fourth, there are times when power is not generated depending on the direction of the sun, and power is not generated after sunset and before sunrise.

[0033] Earthquake prediction using a multiple distributed installation system solves many of these problems. By installing solar power generation systems that can measure solar radiation intensity and generated power at the same time over a wide area and at multiple locations, the following effects can be achieved. First, earthquake prediction using objective numerical values ​​is possible because values ​​calculated from generated power, solar radiation intensity, and solar cell capacity are used for earthquake prediction. Second, if power is generated by sunlight, measurement is possible regardless of weather, and measurement time can be extended. Third, multi-point measurement makes it possible to determine the presence or absence of earthquake precursors over a wide area, and comprehensive earthquake prediction improves prediction accuracy, improving prediction accuracy for the scale and epicenter of earthquakes. The fourth problem of the earthquake prediction method described in claim 1 is not solved because even with a multiple distributed installation system, no power is generated after sunset and before sunrise, making measurement impossible. In addition, in the case of a solar cell module with a fixed installation angle, there are time periods when power is not generated depending on the direction of the sun even if there is solar radiation, making measurement impossible, but with a solar tracking type, this problem can be solved.

[0034] It has been discovered that in solar power generation systems, the ratio of generated power to the capacity of the solar cells on a sunny day is not nearly constant, but varies widely, and that when the generated power exceeds 90% of the solar cell capacity, there is a high probability of an earthquake of a certain magnitude or greater occurring. It has also been discovered that the generated power is roughly proportional to the intensity of solar radiation, and that the nominal maximum output of a solar cell module is 1kW / m of irradiance (solar radiation intensity). 2 For this reason, in a solar power generation system equipped with a solar radiation meter, the generated power is calculated based on the solar radiation intensity of 1kW / m 2 In this case, the ratio of the proportionally converted value to the solar cell capacity is not nearly constant but fluctuates over a considerable range, and if the value is abnormal, there is a high probability that an earthquake of a certain magnitude or greater will occur. By installing multiple solar power generation systems equipped with pyranometers over a wide area using a multiple distributed installation system, it is possible to grasp the distribution of the relationship between solar radiation intensity and generated power at a certain time, making it possible to grasp the precursors of earthquakes.

[0035] The requirements for a multiple distributed installation system are as follows. First, in order to obtain reliable data by measuring under the same conditions, each system equipped with a solar photovoltaic power generation system and a solar pyranometer must have the same specifications. Second, the installation direction and inclination angle of the solar photovoltaic power generation system must be the same as that of the solar cell module. Third, in order to cover the earthquake prediction range and perform highly accurate earthquake prediction, as many solar photovoltaic power generation systems as possible must be installed in a wide area, including islands, with at least 20 solar photovoltaic power generation systems installed in Japan. Fourth, in order to generate more power than the solar cell capacity and to respond to the prediction of earthquakes of a magnitude larger than a major earthquake, a power conditioner with a rated output power of 130% or more of the solar cell capacity must be used. Fifth, the solar photovoltaic power generation system can be either a fixed type with a fixed solar cell module installation direction and angle, or a sun tracking type, but it must be unified into one of them. In the case of a fixed solar cell module, the installation angle must be the same for all solar cell modules, at an inclination angle of around 30°, and the installation direction of the solar cell module must face south. Sixth, the solar cell module must not be shaded by buildings, utility poles, large trees, etc. Seventh, the surface of the solar cell module must be kept clean. Eighth, it must not be subject to output control by the power company. Ninth, a thermometer must be installed. Since there is solar cell loss, that is, loss due to rises in the surface temperature of the solar cell module, a thermometer must be installed in preparation for making corrections. Tenth, in order to enable accurate observation according to Japan Standard Time, each solar power generation system must be capable of receiving standard radio waves, and the solar radiation intensity and generated power must be measured at exactly the same time, at a frequency of at least once per minute, and transmitted to the data collection location along with the measurement time and temperature. Eleventh, data collection and calculations must be possible at the data collection location. Twelfth, in order to obtain highly accurate data, the solar cell capacity must be approximately 50 kW or more. Thirteenth, generated power (unit: kW) must be reported to one decimal place, and solar radiation intensity (unit: kW / m 2) must be measurable to two decimal points. 14th, the solar power generation system must be installed within 15 years and not have deteriorated over time. 15th, in order to be able to respond to more advanced earthquake predictions in the future, a database of the direction and altitude of the sun by day and time at each measurement point must be kept at the collection site.

[0036] This paper describes a method for calculating the values ​​required for short-term earthquake prediction in multiple distributed installation systems. Let a be the solar cell capacity (kW) of each solar power generation system, and let a be the solar radiation intensity (kW / m 2 ) is b, and the generated power (kW) is c. Since the generated power is almost proportional to the solar radiation intensity, we will assume that it is perfectly proportional. 2 Let the value of "what percentage of the converted generated power (kW) is a (kW) relative to the solar cell capacity a (kW)" be d (%). The value of d can be calculated by d = ((c / b) / a)) x 100.

[0037] The nominal maximum output of a solar cell module is the irradiance, i.e. the solar radiation intensity, of 1kW / m 2 The power generated is approximately proportional to the solar radiation intensity, so the value of d is calculated as the power generated in 1kW / m 2 For example, if the solar cell capacity is 50 kW and the solar radiation intensity is 0.50 kW / m, the converted value indicates what percentage of the solar cell capacity it is. 2 If the generated power is 20.0kW, the value of d is 80.0%. d is calculated to one decimal place. Since the generated power is considered to be a maximum of 80% of the solar cell capacity, the value of d is usually 80% or less.

[0038] In order to maintain the accuracy of the value of d, the following two operations shall be carried out. First, when the solar radiation intensity is 0.10 kW / m 2Secondly, if the change in the value of d is not gradual and it is suspected that the solar radiation intensity and generated power are not measured at the same time, or if the solar radiation intensity on the solar cell module is suspected to be uneven due to the influence of cloud shadows, or if accurate data cannot be obtained due to snowfall or other reasons, the relevant data should be invalidated and excluded.

[0039] As for whether or not the value of d needs to be corrected to take into account solar cell losses, i.e. losses due to increases in the surface temperature of the solar cell module, there is insufficient data to be accumulated, so it is not possible to say definitively. Thermometers will be installed in each solar power generation system that constitutes a multiple distributed installation system, and temperature data will be transmitted to the collection location and used as necessary. Data will be accumulated, and if necessary, corrections will be made by setting correction coefficients for each region and month. In addition, since it is believed that there is some cause between the sun and the earth that increases the generated power before an earthquake, a database of the direction and altitude of the sun by date and time at each measurement point will be kept at the collection location, and will be used to correct the value of d in the future.

[0040] There are many unknowns, such as whether the distribution of d values ​​when an earthquake is imminent will be a contour line with a single peak or a scattered distribution of high values, how far above the ground the cause of the increase in power generation is, and in which direction from the epicenter the cause of the increase in power generation will be greatest. In any case, it is estimated that the larger the earthquake, the more locations there will be where the value of d as a precursor is high, and that there will be a greater number of locations showing high values, and that the precursors will appear earlier than for small and medium-sized earthquakes. The second and third reference values ​​can be set according to the scale of the earthquake to be predicted.

[0041] When predicting earthquakes of a magnitude greater than or equal to a major earthquake, based on the fact that a home system recorded a power generation of approximately 111% of the solar cell capacity before the Tohoku Pacific Coast Earthquake, as an example of a prediction, if there is a point where the value of d is 110% or more at a certain time, it can be assumed that an earthquake of a magnitude greater than or equal to a major earthquake will occur in a location relatively close to the point with the highest value of d in the short term. Also, if the number of points where the highest value of d does not reach 110% but is 100% or more is 25% or more of the total, it can be assumed that an earthquake of a magnitude greater than or equal to a major earthquake will occur in a location relatively close to the point with a high value of d in the short term. The 110% given as an example is the second standard value, 100% is the third standard value, and 25% is the fourth standard value. For example, if the value of d is 95.0% in Tokyo, 100.0% in Osaka, 120.0% in Kochi, and 110.0% in Miyazaki around noon on a certain day, there are points where the value of d is 110% or more, so it is predicted that an earthquake of a magnitude greater than a major earthquake will occur in the short term, and the epicenter is likely to be off the southern coast of Shikoku to the southern coast of Kyushu. Also, if the value of d is not 110% or more but 25% or more of the total measurement points have a measurement value of 100% or more, and there is a spread in the value of d, it is predicted that an earthquake of a magnitude greater than a major earthquake will occur in the short term. For example, if there are 20 measurement points, and around noon on a certain day, the value of d is 105% in Kochi and Miyazaki, and 100% in the other three measurement points west of Kinki, the maximum value of d is not 110% or more, but there are five measurement points with a value of 100% or more, which is 25% of the total, and it is predicted that an earthquake of a magnitude greater than a major earthquake will occur in the short term with its epicenter off the southern coast of Shikoku to the southern coast of Kyushu. Short-term often means up to two days later, but warning signs of a large or larger earthquake may appear earlier.

[0042] When predicting small and medium earthquakes of less than M7.0, for example, if the second standard value is set to 95%, it will be possible to estimate the occurrence of small and medium earthquakes of about M4.5 or more, and if the third standard value is set to 90% and the fourth standard value to 25%, it will also be possible to estimate the occurrence of small and medium earthquakes of about M4.5 or more. The scale of an earthquake is thought to be roughly linked to the maximum value of d, and the epicenter is thought to be close to a point with a high value of d.

[0043] Color-coded display according to the value of d is also one way to make earthquake predictions easier to understand. The level of the earthquake precursor is defined as follows: 110% or more is extremely abnormal, 100% to 110% is extremely abnormal, 95% to 100% is abnormal, 90% to 95% is slightly abnormal, 80% to 90% is high, 70% to 80% is normal, and less than 70% is low. The colors red, orange, yellow, yellow-green, green, light blue, and blue are assigned to the respective values, and the color display can be displayed on computers and smartphones via the Internet, or on television by public organizations and weather information companies, making it possible to inform the level of the precursor of a large earthquake or larger. In addition, the calculation results at the collection site can be used by public organizations to issue earthquake prediction information, and can be provided to weather information companies to provide earthquake prediction information services. Furthermore, the publication of the data allows even non-experts to easily make short-term earthquake predictions.

[0044] Regarding short-term earthquake predictions in multiple distributed installation systems, the use of data from commercial facility storefronts or online data is not permitted, so the concept of earthquake prediction is described here. It is not possible to state definitively what the appropriate standard value is, but the standard value will be revised as necessary based on the relationship between measurement results and earthquakes that have occurred, in order to improve the accuracy of earthquake predictions. Based on the measurement results of home systems, short-term does not mean that it is not possible to predict an earthquake of a magnitude greater than a major earthquake until it occurs, but rather that it is highly likely that it can be predicted before that, and the larger the earthquake, the earlier the precursors appear. Although claims 2 and 3 both state that they are earthquake predictions, not earthquake predictions, it is possible that the accuracy of earthquake predictions can be improved to earthquake predictions by adding corrections for the value of d and its distribution, as well as temperature, the direction of the sun, and altitude. [Industrial Applicability]

[0045] Not only will it enable weather information companies to provide earthquake prediction information services, but it will also be possible to provide home solar power generation systems with earthquake prediction functions. If it becomes possible to measure generated power and solar radiation intensity with high precision, it will lead to the commercialization of earthquake prediction devices such as watches, smartphones, and cars with earthquake prediction functions, which could have industrial applications.

Claims

1. An earthquake prediction method that measures the power generated by a solar power generation system and estimates that an earthquake will occur if the ratio of the power generated to the solar cell capacity of the solar power generation system is equal to or greater than a predetermined first reference value.

2. The power generation and solar radiation intensity are measured by photovoltaic power generation systems installed in multiple locations, and the measurement time, power generation, and solar radiation intensity data are transmitted to a data collection location. The power generation is calculated based on the solar radiation intensity of 1kW / m ２ An earthquake prediction method that estimates that an earthquake will occur when there is one or more solar power generation systems in which the ratio of the proportionally converted value to the solar cell capacity is equal to or greater than a predetermined second standard value.

3. The earthquake prediction method described in claim 2, which estimates that an earthquake will occur when the proportion of measurement points with values ​​equal to or greater than a predetermined third standard value to the total number of measurement points is equal to or greater than a predetermined fourth standard value.