COMPUTER DEVICE AND METHOD FOR DETERMINING WHETHER A SOLAR ENERGY PANEL ARRAY IS ABNORMAL

Embodiments relate to a computer device and a method for determining whether a solar energy panel array is abnormal. In the embodiments, the computer device uses a current power generation calculation model to calculate a set of current reference power generation parameters of the solar energy panel array according to a set of current environment parameters of the solar energy panel array. The computer device also defines a power generation indicator for the solar energy panel array according to a contrast between a set of current actual power generation parameters of the solar energy panel array and the set of current reference power generation parameters, and determines whether the solar energy panel array is abnormal according to the power generation indicator.

PRIORITY

This application claims priority to Taiwan Patent Application No. 106138151 filed on Nov. 3, 2017, which is hereby incorporated by reference in its entirety.

FIELD

Embodiments of the present invention relate to a computer device and a determining method. More particularly, the embodiments of the present invention relate to a computer device and a method for determining whether a solar energy panel array is abnormal.

BACKGROUND

Solar power generation is a method for power generation by converting energy of sunlight to electric energy. In order to achieve solar power generation, a solar energy system may practically comprise a plurality of solar energy panels connected in series, wherein each of the solar energy panels may comprise a plurality of solar energy cells, and these solar energy cells are configured to convert the energy of sunlight to the electric energy. Abnormality may occur during the operation of the solar energy system, and whether the solar energy system is abnormal is generally determined according to the total power generation of the solar energy system. For example, if the total power generation of the solar energy system is below a total power generation threshold, then it is determined that the solar energy system is abnormal. However, since whether the solar energy system is abnormal is determined according to the total power generation of the solar energy system, which part of the solar energy system is abnormal cannot be reflected explicitly.

On the other hand, the total power generation of the solar energy system is extremely sensitive to weather variation, so whether the solar energy system is abnormal is often misjudged due to the factor of weather variation when it is determined according to the total power generation of the solar energy system. For example, the solar energy system may be wrongly determined as abnormal if the total power generation of the solar energy system reduces because it has been under the environment without sunlight for a long time. In other words, the abnormality category caused by weather variation cannot be identified in this way. Therefore, it is not an effective and accurate method to determine whether the solar energy system is abnormal according to the total power generation of the solar energy system.

Accordingly, it is important in the art to determine whether the solar energy system is abnormal more effectively and identify the abnormal part and the abnormality category more accurately.

SUMMARY

In order to solve at least the aforesaid problem, the disclosure provides a computer device for determining whether a solar energy panel array is abnormal. The computer device may comprise a storage and a processor electrically connected to the storage. The storage may be configured to store a current power generation calculation model, and a set of current actual power generation parameters and a set of current environment parameters of the solar energy panel array. The processor may be configured to use the current power generation calculation model to calculate a set of current reference power generation parameters of the solar energy panel array according to the set of current environment parameters. The processor may be further configured to define a power generation indicator for the solar energy panel array by a contrast between the set of current actual power generation parameters and the set of current reference power generation parameters, and determine whether the solar energy panel array is abnormal according to the power generation indicator.

In order to solve at least the aforesaid problem, the disclosure also provides a method for determining whether a solar energy panel array is abnormal. The method may comprise the following steps:using a current power generation calculation model, by a computer device, to calculate a set of current reference power generation parameters of the solar energy panel array according to a set of current environment parameters of the solar energy panel array; anddefining, by the computer device, a power generation indicator for the solar energy panel array by a contrast between a set of current actual power generation parameters and the set of current reference power generation parameters of the solar energy panel array, and determining, by the computer device, whether the solar energy panel array is abnormal according to the power generation indicator.

In certain embodiments, it is determined whether respective solar energy panel arrays in the solar energy system are abnormal instead of determining whether the whole solar energy system is abnormal. Therefore, when it is determined that the solar energy system is abnormal, which solar energy panel array(s) in the solar energy system is/are abnormal can also be determined explicitly, and this will facilitate the subsequent repair of the abnormal solar energy panel array. On the other hand, in the embodiments of the present invention, a power generation indicator for determining whether a solar energy panel array is abnormal is relevant to a contrast between a set of current actual power generation parameters and a set of current reference power generation parameters of the solar energy panel array, and the set of current reference power generation parameters is relevant to a set of current environment parameters of the solar energy panel array. The set of environment parameters may comprise various parameters relevant to weather variation, so it is equivalent to that the power generation indicator for determining whether the solar energy panel array is abnormal has taken the factor of weather variation into consideration. Accordingly, in the embodiments of the present invention, the probability of wrongly determining that the solar energy panel array is abnormal can be effectively reduced. Moreover, during the identification of the abnormality categories, the embodiments of the present invention not only can identify the abnormality category caused by equipment damage, but also can identify other abnormality categories without the influence of weather variation (e.g., the sunshine amount variation).

It shall be appreciated that, this summary is not intended to encompass all embodiments of the present invention but is provided only to present certain examples of the present invention in a simple form and as an introduction to the following detailed description.

DETAILED DESCRIPTION

Embodiments of the present invention described in the examples below are not intended to limit the present invention to any specific example, embodiment, environment, applications, structures, processes or steps described in these example embodiments. In the attached drawings, elements unrelated to the present invention are omitted from depiction; and dimensions of elements and proportional relationships among individual elements in the attached drawings are only exemplary examples but not intended to limit the present invention. Unless stated particularly, same (or similar) element symbols may correspond to same (or similar) elements in the following description.

FIG. 1illustrates a solar energy system in one or more embodiments of the present invention. Contents shown inFIG. 1are only for purpose of illustrating embodiments of the present invention instead of limiting the present invention. Referring toFIG. 1, a solar energy system1may comprise a plurality of solar energy panels P, a plurality of maximum power point trackers MPPT, a plurality of inverters INV, a total power generation meter M and a sensor11.

As shown inFIG. 1, each solar energy panel P may comprise a plurality of solar energy cells (not shown) so as to convert energy of sunlight to electric energy through the photovoltaic effect. A plurality of solar energy panels P connected in series and one maximum power point tracker MPPT may form a solar energy panel string S to provide a direct current output. The maximum power point tracker MPPT in each solar energy panel string S may be a DC to DC converter, and it may calculate the maximum power point of the solar energy panel string S via various methods which are for example but not limited to: a perturbation and observation method, an incremental conductance method, a current scanning method, a constant voltage method or the like. Each maximum power point tracker MPPT may output direct-current output power generated by all solar energy panels P connected in series with the maximum power point tracker MPPT. A plurality of solar energy panel string S may form one solar energy panel array A and may be connected to one inverter INV. Each inverter INV may be an electronic element converting direct current into alternating current using a high-frequency bridge circuit, and it may be for example but not limited to: a half bridge inverter, a full bridge inverter and a three-phase bridge type inverter or the like. Therefore, each inverter INV may convert the direct-current output of the solar energy panel array A connected with the inverter INV into an alternating-current output, and transmit the alternating-current output to the total power generation meter M. In some embodiments, each inverter INV may further record the actual power generation of the solar energy panel array A connected with the inverter INV.

The sensor11may comprise one or more equipments for sensing various environment parameters of an environment where the solar energy system1is located. For example, the sensor11may arbitrarily comprise a thermometer, an illuminometer, a humidometer, an air quality monitor or the like, wherein the thermometer may be used to sense temperature parameters of the environment where the solar energy system1is located, the illuminometer may be used to sense illuminance parameters of the environment where the solar energy system1is located, the humidometer may be used to sense humidity parameters of the environment where the solar energy system1is located, and the air quality monitor may be used to sense air quality parameters of the environment where the solar energy system1is located.

The connection mentioned with reference toFIG. 1above may be direct connection (i.e., connection not via other elements with specific functions) or indirect connection (i.e., connection via other elements with specific functions) depending on different requirements.

FIG. 2illustrates a computer device for determining whether a solar energy panel array is abnormal in one or more embodiments of the present invention. Contents shown inFIG. 2are only for purpose of illustrating embodiments of the present invention instead of limiting the present invention. Referring toFIG. 2, a computer device2may comprise a storage21and a processor23. In some embodiments, the computer device2further comprises a data transmission interface25. The storage21, the processor23and the data transmission interface25may be connected with each other, and the connection among these three elements may be direct connection (i.e., connection not via other elements with specific functions) or indirect connection (i.e., connection via other elements with specific functions). For example, the storage21may be directly connected to the data transmission interface25or indirectly connected to the data transmission interface25via the processor23.

The processor23may be one of various microprocessors or microcontrollers capable of signal processing. The microprocessor or the microcontroller is a kind of programmable specific integrated circuit that is capable of operating, storing, outputting/inputting or the like. Moreover, the microprocessor or the microcontroller can receive and process various coded instructions, thereby performing various logical operations and arithmetical operations and outputting corresponding operation results.

The storage21may comprise primary memories (also called main memories or internal memories) which are usually called memories for short, and the memories at this level directly communicate with the processor23. The processor23may read instruction sets stored in the primary memories, and executes these instruction sets if needed. The storage21may further comprise secondary memories (which are also called external memories or auxiliary memories), and the secondary memories connect to the processor23through I/O channels of the memories instead of directly connecting to the processor23, and use a data buffer to transmit data to the primary memories. The data in the secondary memories does not disappear even in the case without power supply (i.e., is non-volatile). The secondary memories may for example be various types of hard disks, optical disks or the like. The storage21may also comprise a third-level storage device, i.e., a storage device that can be inserted into or pulled out from a computer directly, e.g., a mobile disk.

The data transmission interface25may comprise various network interfaces for connecting the computer device2to the solar energy system1shown inFIG. 1and/or to a network9(any wireless network and/or any wired network), which are for example but not limited to: an Ethernet communication interface, an Internet communication interface, a Wi-Fi network communication interface, an LTE network communication interface or the like.

In the case where the data transmission interface25connects to the solar energy system1shown inFIG. 1, the computer device2may directly receive various kinds of data (including data sensed by the sensor11) from the solar energy system1via the data transmission interface25. In the case where the data transmission interface25does not connect to the solar energy system1shown inFIG. 1but the network9connects to the solar energy system1shown inFIG. 1, the computer device2may receive various kinds of data (including data sensed by the sensor11) from the solar energy system1via the data transmission interface25and the network9.

In some embodiments, the computer device2may further comprise an input/output interface (not shown) which may be for example but not limited to: a mouse, a trace ball, a touch pad, a keyboard, a scanner, a microphone, a user interface, a screen, a touch screen, a projector or the like. The input/output interface may be directly or indirectly connected with the storage21, the processor23and the data transmission interface25. Through the input/output interface, the user may store external data into the storage21or output data stored in the storage21to the outside.

Still referring toFIG. 2, the storage21may be configured to store a current power generation calculation model811. The current power generation calculation model811may be a regression analysis model, and the regression analysis model may be represented as an equation relevant to the power generation and environment parameters of the solar energy panel array A. The environment parameters may include various parameter categories which are for example but not limited to at least one of the following parameter categories: illuminance, temperature, humidity, air quality or the like. For example, the current power generation calculation model811may be represented as the following equation in the case where only a certain environment parameter (e.g., the illuminance) of the solar energy panel array A is taken in consideration:

where x1is the illuminance, y is the power generation, while a1and a0are regression coefficients generated in advance through regression analysis.

As another example, the current power generation calculation model811may be represented as the following equation in the case where two environment parameters (e.g., the illuminance and the temperature) of the solar energy panel array A are taken in consideration:

where x1is the illuminance, x2is the temperature, y is the power generation, while b1, b2and b0are regression coefficients generated in advance through regression analysis.

In some embodiments, the processor23may not construct the current power generation calculation model811by itself. Instead, the current power generation calculation model811that has been constructed outside the computer device2is stored into the storage21directly. In some embodiments, the processor23may also construct the current power generation calculation model811by itself.

FIG. 3illustrates a time course of a solar energy panel array in one or more embodiments of the present invention. Contents shown inFIG. 3are only for purpose of illustrating embodiments of the present invention instead of limiting the present invention. Referring toFIG. 2andFIG. 3, if the processor23may be configured to construct a current power generation calculation model811for a solar energy panel array A, the storage21may be configured to store a set of historical actual power generation parameters833and a set of historical environment parameters853of the solar energy panel array A. The set of historical environment parameters853may include various parameter categories which are for example but not limited to at least one of the following parameter categories: illuminance, temperature, humidity, air quality or the like.

The set of historical actual power generation parameters833and the set of historical environment parameters853may include a plurality of historical actual power generation values and a plurality of historical environment values of the solar energy panel array A that are sampled within a second time period TD2respectively before a second time point t2. The length of the second time period TD2, the sampling number of the historical actual power generation values and the sampling number of the historical environment values may be set depending on different requirements. For example, if the second time point t2is the time point at which the current power generation calculation model811is constructed, then the length of the second time period TD2may be for example six months, one year, two years or the like, and the historical actual power generation values and the historical environment values may respectively comprise the power generation values at some specific time points of each day within the second time period TD2(e.g., the average power generation of each hour from 9:00 am to 3:00 pm) and the environment values at some specific time points of each day within the second time period TD2(e.g., the average environment value of each hour from 9:00 am to 3:00 pm).

The processor23may be configured to perform a regression analysis on the set of historical actual power generation parameters833and the set of historical environment parameters853to construct the current power generation calculation model811, and store the current power generation calculation model811into the storage21. Specifically, the processor23may utilize various regression analysis methods (e.g., a complex variable regression minimum square method) to input the set of historical actual power generation parameters833and the set of historical environment parameters853into a preset regression analysis model (e.g., the equation (1) or equation (2)), and then calculate regression coefficients of the preset regression analysis model (e.g., the regression coefficients aland a0in the equation (1) or the regression coefficients b1, b2and b0in the equation (2)), thereby constructing the current power generation calculation model811.

Still referring toFIG. 2andFIG. 3, the storage21may be configured to store a set of current actual power generation parameters831and a set of current environment parameters851of the solar energy panel array A. The set of current environment parameters851may include various parameter categories which are for example but not limited to at least one of the following parameter categories: illuminance, temperature, humidity, air quality or the like. The set of current actual power generation parameters831may comprise a plurality of current actual power generation values respectively corresponding to a plurality of specific time points within a first time period TD1after the second time point t2, and the set of current environment parameters851may comprise a plurality of current environment values respectively corresponding to the specific time points within the first time period TD1after the second time point t2. In the case where the current power generation calculation model811is constructed by the processor23, the second time point t2may be a certain time point after the current power generation calculation model811is constructed by the processor23. In the case where the current power generation calculation model811is not constructed by the processor23, the second time point t2may be a certain time point after the current power generation calculation model811is stored into the storage21.

The length of the first time period TD1and a plurality of time points comprised in the first time period TD1may be set depending on different requirements. For example, it is assumed that the second time point t2is 8:00 am of a certain day, the first time period TD1may be eight hours, and the first time period TD1may comprise eight time points which are respectively 9:00 am, 10:00 am, 11:00 am, 12:00 am, 1:00 pm, 2:00 pm, 3:00 pm and 4:00 pm. As another example, it is assumed that the second time point t2is 8:00 am of a certain day, the first time period TD1may be nine hours, and the first time period TD1may comprise three time points which are respectively 11:00 am, 2:00 pm and 5:00 pm.

The processor23may be configured to use the current power generation calculation model811to calculate a set of current reference power generation parameters of the solar energy panel array A according to the set of current environment parameters851. Specifically, the processor23may input a plurality of current environment values of a plurality of specific time points comprised in the first time period TD1respectively into the current power generation calculation model811(e.g., the equation (1) or the equation (2) of which the regression coefficients are known) to respectively calculate a plurality of current reference power generation values corresponding to the plurality of specific time points comprised in the first time period TD1(e.g., the power generation y in the equation (1) or the equation (2) of which the regression coefficients are known), thereby obtaining the set of current reference power generation parameters.

After calculating the set of current reference power generation parameters of the solar energy panel array A, the processor23may be configured to define a power generation indicator for the solar energy panel array A by a contrast between the set of current actual power generation parameters831and the set of current reference power generation parameters. For example, the processor23may define a curve presented by a plurality of ratios of the set of current actual power generation parameters831to the set of current reference power generation parameters (a plurality of ratios obtained through dividing the actual power generation values by the plurality of reference power generation values) corresponding to the specific time points within the first time period TD1as the power generation indicator. As described later, the processor23can determine whether the solar energy panel array A is abnormal and identify the abnormality category of the solar energy panel array A according to the power generation indicator.

Still referring toFIG. 2andFIG. 3, in some embodiments, the storage21may be further configured to store a previous power generation calculation model815and a set of previous environment parameters855of the solar energy panel array A. The set of previous environment parameters855may comprise a plurality of previous environment values corresponding to a plurality of specific time points within a third time period TD3between the first time point t1and the second time point t2. The set of previous environment parameters855may include various parameter categories which are for example but not limited to at least one of the following parameter categories: illuminance, temperature, humidity, air quality or the like.

The processor23may not construct the previous power generation calculation model815by itself, or the processor23may construct the previous power generation calculation model815by itself. In the case where the previous power generation calculation model815is constructed by the processor23, the first time point t1may be a certain time point after the previous power generation calculation model815is constructed by the processor23. In the case where the previous power generation calculation model815is not constructed by the processor23, the first time point t1may be a certain time point after the previous power generation calculation model815is stored into the storage21. The length of the third time period TD3and the sampling number of the previous environment values may be set depending on different requirements. For example, the length of the third time period TD3may be one month, three months, six months, one year, or more than one year. The previous environment values may comprise the environment values at some specific time points of each day within the third time period TD3(e.g., the average environment value of each hour from 9:00 am to 3:00 pm).

The processor23may be configured to use the current power generation calculation model811to calculate a set of first power generation parameters of the solar energy panel array A according to the set of previous environment parameters855, and use the previous power generation calculation model815to calculate a set of second power generation parameters of the solar energy panel array A according to the set of previous environment parameters855. Then, the processor23may determine whether to calculate the set of current reference power generation parameters of the solar energy panel array A by comparing the set of first power generation parameters and the set of second power generation parameters.

Specifically, the processor23may input a plurality of previous environment values sampled within the third time period TD3respectively into the current power generation calculation model811(e.g., the equation (1) or the equation (2) of which the regression coefficients are known) to calculate a plurality of first power generation values (e.g., the power generation y in the equation (1) or the equation (2) of which the regression coefficients are known), and these first power generation values are the set of first power generation parameters. Moreover, the processor23may input the plurality of previous environment values sampled within the third time period TD3respectively into the previous power generation calculation model815(e.g., the equation (1) or the equation (2) of which the regression coefficients are known) to calculate a plurality of second power generation values (e.g., the power generation y in the equation (1) or the equation (2) of which the regression coefficients are known), and these second power generation values are the set of second power generation parameters. Then, the processor23may calculate an average of a plurality of ratios of the set of first power generation parameters to the set of second power generation parameters (i.e., a plurality of ratios obtained through dividing the first power generation values by the second power generation values), and decide whether to calculate the set of current reference power generation parameters (i.e., whether to calculate the power generation indicator) of the solar energy panel array A according to the average.

If the difference between the set of first power generation parameters and the set of second power generation parameters is too large (i.e., the average exceeds a preset threshold), then it means that the difference between the current power generation calculation model811and the previous power generation calculation model815is too large, and thus the processor23may determine that the current power generation calculation model811is not suitable for calculating the set of current reference power generation parameters of the solar energy panel array A (i.e., is not suitable for calculating the power generation indicator of the solar energy panel array A). One reason for the difference between the current power generation calculation model811and the previous power generation calculation model815being too large may be that the degradation degree of the solar energy panel array A becomes abnormal. In this case, the processor23may identify the solar energy panel array A as having degradation abnormality.

The set of historical actual power generation parameters833, the set of historical environment parameters853, the set of current actual power generation parameters831, the set of current environment parameters851and the set of previous environment parameters855stored in the storage21may be provided through the data transmission interface25. The set of historical actual power generation parameters833, the set of historical environment parameters853, the set of current actual power generation parameters831, the set of current environment parameters851and the set of previous environment parameters855stored in the storage21may also be inputted into the computer device2by the user.

FIG. 4illustrates a method for determining abnormality categories of a solar energy panel array in one or more embodiments of the present invention, andFIG. 5illustrates a plurality of abnormality categories of a solar energy panel array in one or more embodiments of the present invention. Contents shown inFIG. 4andFIG. 5are only for purpose of illustrating embodiments of the present invention instead of limiting the present invention. Referring toFIG. 4toFIG. 5, the processor23may determine whether the solar energy panel array A is abnormal and identify the abnormality category thereof according to an identification method4.

An identification step401may be used to determine whether the degradation of the solar energy panel array A is abnormal. As described previously, the computer device2may calculate an average of ratios of the set of first power generation parameters to the set of second power generation parameters (i.e., a plurality of ratios obtained through dividing the first power generation values by the second power generation values), and determine whether the degradation of the solar energy panel array A is abnormal according to the average. If it is determined that the degradation of the solar energy panel array A is abnormal, then the power generation indicator may not be calculated. For example, if the average is smaller than a degradation threshold (e.g., smaller than 0.9), then the computer device2may determine that the solar energy panel array A is abnormal and identify the abnormal status thereof as degradation abnormality. The degradation abnormality described herein means that the degradation degree of the solar energy panel array A exceeds the normal degradation degree that is caused by natural wearing, and the reason of the degradation abnormality is not limited.

If the result of the identification step401is no, then another identification step403is further executed. However, in some embodiments, the identification step401may be omitted and the identification method4may directly begin from the identification step403.

As described above, the computer device2may use the current power generation calculation model811to calculate a set of current reference power generation parameters of the solar energy panel array A according to the set of current environment parameters851, and define a power generation indicator for the solar energy panel array A by a contrast between the set of current actual power generation parameters831and the set of current reference power generation parameters.

In the case where the sensor11is normal, the actual power generation of the solar energy panel array A is usually smaller than the reference power generation calculated according to the current power generation calculation model811. Therefore, in the identification step403, if the values of the power generation indicator at each of the time points within the first time period TD1and an average of the values are all greater than a first preset value, then it may mean that the actual power generation of the solar energy panel array A is greater than the reference power generation calculated according to the current power generation calculation model811. In this case, the computer device2can determine that the solar energy panel array A is abnormal and identify the abnormality category thereof as sensor abnormality. The sensor abnormality described herein encompasses the abnormality of the sensor11caused by various reasons which are for example but not limited to: smudges on the surface of the sensor11, failure in calibrating of the sensor11, or the malfunction of the sensor11or the like. For example, referring to (5A) inFIG. 5, if the values of the power generation indicator at each of the time points from the second time point t2and an average of the values are all greater than the first preset value (e.g., greater than 1), then the computer device2can determine that the solar energy panel array A is abnormal and identify the abnormality category thereof as sensor abnormality. If the result of the identification step403is no, then another identification step405is further executed.

In the identification step405, if the values of the power generation indicator at each of the time points within the first time period TD1are all smaller than the first present value but are all greater than a second preset value, then the computer device2can determine that the solar energy panel array A is abnormal and identify the abnormality category thereof as soft shading abnormality. The soft shading abnormality described herein refers to a kind of abnormality that it is hard for the solar energy panel array A to generate the hot spot effect due to dust or semi-transparent smudges on the surface of the solar energy panel array A. For example, referring to (5B) inFIG. 5, if the values of the power generation indicator at each of the time points from the second time point t2all range from the first preset value to the second preset value (e.g., each of the values is smaller than 1 but larger than 0.9), then the computer device2can determine that the solar energy panel array A is abnormal and identify the abnormality category thereof as soft shading abnormality. If the result of the identification step405is no, then another identification step407is further executed.

In the identification step407, if the value(s) of the power generation indicator at some time point(s) within the first time period TD1is/are smaller than the first present value but the values thereof at other time points are all close to the first preset value, then the computer device2can determine that the solar energy panel array A is abnormal and identify the abnormality category thereof as local abnormality and/or temporary abnormality. The local abnormality and/or temporary abnormality described herein refers to a kind of abnormality when the solar energy panel array A is locally or temporarily shaded, and it may encompass various reasons for the solar energy panel array A being locally or temporarily shaded, which are for example but not limited to: buildings, plants and clouds locally or temporarily shade the solar energy panel array A due to variation of the direction of sunlight illumination. For example, referring to (5C) inFIG. 5, if the value of the power generation indicator at only one time point from the second time point t2is smaller than the first preset value (e.g., smaller than 1) but the values thereof at other time points are all close to the first preset value (e.g., close to 1), then the computer device2can determine that the solar energy panel array A is abnormal and identify the abnormality category thereof as local abnormality and/or temporary abnormality. If the result of the identification step407is no, then another identification step409is further executed.

In the identification step409, if the values of the power generation indicator at each of the time points within the first time period TD1are all close to a particular value, and the particular value is an integral multiple of the value obtained through dividing the first preset value by the number of solar energy panel strings S comprised in the solar energy panel array A, then the computer device2can determine that the solar energy panel array A is abnormal and identify the abnormality category thereof as hard shading or open-circuit abnormality. If the solar energy panel array A includes three solar energy panel strings S, then the particular value may be an integral multiple of ⅓, i.e., ⅓ or ⅔. The hard shading or open-circuit abnormality described herein refers to a kind of abnormality that some solar energy panel string(s) S is/are out of operation due to the malfunction of some solar energy panel(s) P in the solar energy panel array A. For example, referring to (5D) inFIG. 5, if the solar energy panel array A comprises three solar energy panel strings S and the values of the power generation indicator at each of the time points from the second time point t2are all close to ⅔ or ⅓, then the computer device2can determine that the solar energy panel array A is abnormal and identify the abnormality category thereof as hard shading or open-circuit abnormality. If the values of the power generation indicator at each of the time points are all close to ⅔, then it means that hard shading or open-circuit abnormality occurs to a certain string among the three solar energy panel strings S comprised in the solar energy panel array A. If the values of the power generation indicator at each of the time points are all close to ⅓, then it means that hard shading or open-circuit abnormality occurs to two strings among the three solar energy panel strings S comprised in the solar energy panel array A. If the result of the identification step409is no, then another identification step411is further executed.

In the identification step411, if the values of the power generation indicator at each of the time points within the first time period TD1are all smaller than the second preset value, then the computer device2can determine that the solar energy panel array A is abnormal and identify the abnormality category as other abnormalities (which are for example but not limited to poor contact, short circuit, sub-fissure, electric arc, soft shading accumulation or various composite abnormalities). Otherwise, the computer device2can identify the solar energy panel array A as having no abnormality.

The order in which the identification steps403to411shown inFIG. 4are executed may be adjusted arbitrarily depending on different requirements. Additionally, in some embodiments, one or ones of the identification steps403to411shown inFIG. 4may be omitted depending on different requirements. In some embodiments, one or more identification steps satisfying other conditions may be added to the identification method4shown inFIG. 4.

In some embodiments, any of the preset values described above may also be replaced by a preset interval, and the preset interval may comprise an upper limit value and a lower limit value. Additionally, determining whether the power generation indicator is greater than a certain preset value may be changed into determining whether the power generation indicator is greater than the upper limit value of the corresponding preset interval; determining whether the power generation indicator is smaller than a certain preset value may be changed into determining whether the power generation indicator is smaller than the lower limit value of the corresponding preset interval; and determining whether the power generation indicator is close to a certain preset value may be changed into determining whether the power generation indicator falls within a corresponding preset interval. For example, a preset interval with a lower limit value of 0.95 and an upper limit value of 1.05 may be adopted to replace the preset value 1, thereby increasing the error tolerance of the determining operations.

FIG. 6illustrates a method for determining whether a solar energy panel array is abnormal in one or more embodiments of the present invention. Contents shown inFIG. 6are only for purpose of illustrating embodiments of the present invention instead of limiting the present invention. Referring toFIG. 6, a method6for determining whether a solar energy panel array is abnormal may comprise the following steps:using a current power generation calculation model, by a computer device, to calculate a set of current reference power generation parameters of the solar energy panel array according to a set of current environment parameters of the solar energy panel array (labeled as step601); anddefining, by the computer device, a power generation indicator for the solar energy panel array by a contrast between a set of current actual power generation parameters and the set of current reference power generation parameters of the solar energy panel array, and determining, by the computer device, whether the solar energy panel array is abnormal according to the power generation indicator (labeled as step603).

In some embodiments, the method6may further comprise the following step of: performing, by the computer device, a regression analysis on a set of historical actual power generation parameters and a set of historical environment parameters of the solar energy panel array to construct the current power generation calculation model.

In some embodiments, the method6may further comprise the following steps of: performing, by the computer device, a regression analysis on a set of historical actual power generation parameters and a set of historical environment parameters of the solar energy panel array to construct the current power generation calculation model; and receiving and storing, by the computer device, the set of current actual power generation parameters, the set of current environment parameters, the set of historical actual power generation parameters and the set of historical environment parameters from the solar energy panel array.

In some embodiments, the method6may further comprise the following steps of: using the current power generation calculation model, by the computer device, to calculate a set of first power generation parameters of the solar energy panel array according to a set of previous environment parameters of the solar energy panel array; using a previous power generation calculation model, by the computer device, to calculate a set of second power generation parameters of the solar energy panel array according to the set of previous environment parameters of the solar energy panel array; and determining, by the computer device, whether to calculate the set of current reference power generation parameters of the solar energy panel array by comparing the set of first power generation parameters and the set of second power generation parameters.

In some embodiments, in the method6, the set of current environment parameters may include at least one of the following parameter categories: illuminance, temperature and humidity.

In some embodiments, the method6may further comprise the following step of: identifying, by the computer device, an abnormality category of the solar energy panel array according to the power generation indicator.

In some embodiments, the method6may be implemented on the computer device2. All corresponding steps of the method6may be clearly appreciated by a person having ordinary skill in the art based on the above description of the computer device2, and thus will not be further described herein.

According to the above descriptions, in the embodiments of the present invention, it is respectively determined whether each of the solar energy panel arrays in the solar energy system is abnormal instead of determining whether the whole solar energy system is abnormal. Therefore, when it is determined that the solar energy system is abnormal, which solar energy panel array(s) in the solar energy system is/are abnormal can also be determined explicitly, and this will facilitate the subsequent repair of the abnormal solar energy panel array. On the other hand, in the embodiments of the present invention, a power generation indicator for determining whether a solar energy panel array is abnormal is relevant to a contrast between a set of current actual power generation parameters and a set of current reference power generation parameters of the solar energy panel array, and the set of current reference power generation parameters is relevant to a set of current environment parameters of the solar energy panel array. The set of environment parameters may comprise various parameters relevant to weather variation, so it is equivalent to that the power generation indicator for determining whether the solar energy panel array is abnormal has taken the factor of weather variation into consideration. Accordingly, in the embodiments of the present invention, the probability of wrongly determining that the solar energy panel array is abnormal can be effectively reduced. Moreover, during the identification of the abnormality categories, the embodiments of the present invention not only can identify the abnormality category caused by equipment damage, but also can accurately identify the abnormality category caused by weather variation.