DESC:FIELD OF INVENTION
[001] The field of the invention generally relates to cloud-covered solar modules. More specifically, it relates to a method of determining shading loss over the cloud-covered solar modules.

BACKGROUND
[002] Solar panels use sunlight as an energy source and generate electricity i.e., convert light energy from sunlight into electrical energy. Performance of solar module arrays are affected due to non-uniform irradiations, dust covered panels and various cloud-shading conditions. Commonly, multiple solar modules are constructed and connected in series and parallel combination to form a solar module array. Due to such construction, the performance of the entire solar module array is affected when cloud covers or other shading conditions affect the performance of a single solar module.
[003] Other existing systems have tried to address this problem. However, their scope was limited to determining cloud cover using cloud sensors. These cloud sensors are configured to determine the cloud cover for an entire solar power plant system. However, determining cloud cover for every single solar module in a solar power plant system continues to be difficult. Other existing systems depict installing such cloud sensors in large numbers, which is neither convenient, feasible nor economically viable. The problem is aggravated in cases where large-scale solar power plants are involved.
[004] Thus, in light of the above discussion, it is implied that there is a need for a method for determining shading loss over the cloud covered solar modules, which is reliable and does not suffer from the problems discussed above.

OBJECT OF INVENTION
[005] The principal object of this invention is to provide a method for determining shading loss over cloud-covered solar modules, which are finally connected to SMBs.
[006] Another object of the invention is to provide a method for tracking cloud cover over solar modules at any point in time. during solar radiation hours.
[007] Another object of the invention is to provide a method for identifying low performing SMBs connected to one or more solar modules.
[008] A further object of the invention is to provide a reliable and economical method to determine shading losses suitable for small and large-scale solar power generation systems.
[009] Yet another object of the invention is to provide a method for tracking cloud cover on solar modules without any additional installation of sensors.

BRIEF DESCRIPTION OF FIGURES
[0010] This invention is illustrated in the accompanying drawings, throughout which, like reference letters indicate corresponding parts in the various figures.
[0011] The embodiments herein will be better understood from the following description with reference to the drawings, in which:
[0012] Figure 1A depicts/illustrates an exemplary representation of a system for determining shading loss due to cloud-covered solar modules associated with a single SMB, in accordance with an embodiment of the invention;
[0013] Figure 1B depicts/illustrates an exemplary representation of the system for determining shading loss due to cloud-covered solar modules associated with multiple SMBs, in accordance with an embodiment of the invention;
[0014] Figure 2 depicts/illustrates modules comprised in the system for determining shading losses, in accordance with an embodiment of the invention;
[0015] Figure 3 illustrates a flowchart of a method for determining shading loss in solar module arrays due to cloud-covered solar modules, in accordance with an embodiment of the invention.

STATEMENT OF INVENTION
[0016] The present invention discloses a system and method for determining shading loss incurred in cloud-covered solar modules in solar power plants. At least one pyranometer is used to determine a plane of array irradiance (PoA) data i.e., solar irradiance on a planar surface. Multiple solar modules are attached to form a solar module array and are connected to a string-monitoring box (SMB). One or more SMBs are configured to measure and/or record electrical data from multiple connected solar modules.
[0017] At least one output data from the SMBs and the pyranometer is transferred to an output meter. The data received by the output meter is then transferred to a computing unit for further processing. The computing unit processes the received data to determine at least one of cloud cover over the solar modules at any interval of a day, and instances at which the solar modules connected to SMBs which were under the cloud cover. The at least one output data shared with the output meter comprises at least one of SMB current, voltage and PoA irradiance data.
[0018] The determined cloud cover instances allow users to track individual performance of each SMB, which in turn easily helps to determine and optimize low performing SMBs with which the solar modules are connected.

DETAILED DESCRIPTION
[0019] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and/or detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0020] The present invention discloses a method for determining cloud cover over solar modules, and shading losses incurred by the solar modules due to the cloud cover. Solar panels work most efficiently when they are not affected by any shading parameters. In the context of the present invention, the shading parameters that affect the performance of solar panels includes non-uniform irradiation from the sun, as well as obstructions such as cloud cover, trees, tall buildings, dust, and the like.
[0021] In the present invention, the disclosed method is implemented for determining shading losses over the cloud-covered solar modules and for determining variations in the performance of the solar modules. This, in turn, provides a method for collectively determining performance of the solar panels.
[0022] In the present invention, determination of the cloud cover can be achieved by the disclosed method for various instances, viz., (i) cloudy solar modules with non-cloudy pyranometers, (ii) cloudy pyranometers with non-cloudy solar modules, and (iii) both the solar modules and the pyranometers being under cloudy or non-cloudy instances. Further, the cloud cover can be determined for multiple sessions in a day. In particular, the day may be divided into three sessions for convenience, by dividing the day into three intervals, i.e., rising sun, setting sun, and peak radiation hours. Each interval may provide a minimum resolution equivalent to the output data of SMBs and Pyranometers.
[0023] Additionally, the method disclosed in the present invention may also be able to determine shading losses of the solar power plants under other environmental conditions apart from the aforementioned conditions.
[0024] In an embodiment, recording may also comprise measuring data signals or values, in the context of the invention. Further, one or more wired connections may be implemented by using wireless connections, without foregoing the functions of the connections.
[0025] In the present invention, one or more pyranometers are configured to measure solar irradiance on a planar surface i.e., a plane of array (PoA) irradiance. Additionally, electrical data such as current, and voltage of the solar module array are measured and/or recorded in a string-monitoring box (SMB) through wired connections.
[0026] In an embodiment, the measured and/or recorded electrical SMB data and the PoA irradiance data are transferred to an output meter through one or more wired connections. The output meter tracks one or more parameters of the transferred data. Further, SMB current values from the tracked electrical SMB data and the PoA irradiance data values are transferred to a computing unit. The received SMB current values and PoA irradiance values are processed in the computing unit to determine the cloud cover for the aforementioned various instances.
[0027] The determined cloud cover values are then transmitted to a monitoring device in order to enable a user to track and monitor the performance of the solar modules and, in turn, the performance of the solar panels.
[0028] Referring now to the drawings, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments.
[0029] Figure 1A depicts/illustrates an exemplary representation of a system 100 for determining shading loss due to a cloud-covered solar module 102 associated with an SMB 108, in accordance with an embodiment of the invention.
[0030] In different weather scenarios, the solar module 102 may be partially or fully covered by a depicted cloud 106. The system 100 is configured to determine shading loss in the solar module 102, by using the SMB 108 and a pyranometer 104 located near the solar module 102.
[0031] In the present invention, the SMB 108 is configured to measure and/or record at least one electrical data of the solar module 102 of the cloud-covered solar module 102. The at least one electrical data measured and/or recorded by the SMB 108 comprises at least one of input current, input voltage, input temperature, digital input, analog current input, analog voltage input, supply, ambient conditions such as operating temperature and working temperature, among other data typically measured and/or recorded by SMBs. The at least one electrical data of the solar module 102 measured and/or recorded by the SMB 108 may be termed as SMB data.
[0032] The SMB 108 may further comprise one or more of a fuse assembly to protect the SMB 108 from damaging factors, viz., abnormal current, a surge protector to limit the voltage supply from/to the SMB 108, and a combined bus to transfer data from the SMB 108.
[0033] Further, the SMB may also comprise one or more DC disconnects to provide or to interrupt a flow of DC electricity between the SMB 108, solar module 102, etc., and an output wire to provide electrical wire connections between the SMB 102 and an output meter 110. The output meter 110 may be one or more of a multimeter, electric meter, and a power meter.
[0034] In an embodiment, the pyranometer 104 is configured to measure solar irradiance over a plane of array (PoA), which may be located near the solar module 102. The pyranometer 104 converts the measured temperature-related parameters into a voltage/ current output in order to measure solar irradiance over the PoA. The data measured by the pyranometer 104 is termed as PoA irradiance data.
[0035] In an embodiment, a temperature measuring sensor or solar irradiance measuring sensor such as a thermopile sensor may be present in the pyranometer 104 to measure the PoA irradiance data. In an embodiment, a photovoltaic pyranometer may also be used, based on user requirements.
[0036] In an embodiment, the pyranometer 104 comprises at least one of a temperature measuring sensor, thermopile sensor, pyrgeometer, pyrheliometer, thermopile, thermocouple and silicon photocells, or other equivalent devices with a pyranometer function.
[0037] Further, the measured PoA irradiance data and the measured/recorded SMB data are transferred to the output meter 110 through one or more wired connections. Thereafter, the data received by the output meter 110 is tracked and transferred to a computing unit 112 for processing the data.
[0038] In an embodiment, the output meter 110 and computing unit 112 may be comprised in separate hardware components, or they may be combined together to form a single hardware component, based on user convenience.
[0039] The computing unit 112 is further configured to determine the cloud cover for one or more instances, viz., (i) cloudy solar module 102 with non-cloudy pyranometer 104, (ii) cloudy pyranometer 104 with non-cloudy solar module 102, and (iii) both the solar module 102 and the pyranometer 104 being under either cloudy or non-cloudy instances.
[0040] In an embodiment, the computing unit 112 determines the presence of cloud cover by determining a real-time rate of change of SMB current, PoA irradiance data values, incremental values of the rate of change of the SMB current, and the PoA irradiance. Further, a mean value is obtained by analyzing and/or combining both the real-time and incremental values of the rate of change of both the SMB current and the PoA irradiance data values.
[0041] In an embodiment, the determination of one or more data values, such as the real-time and incremental values of the rate of change of both the SMB current and the PoA irradiance data values, and the mean value can be made by at a real-time instance or at a later point as desired.
[0042] At the outset, in the present invention, each instance of output value of the solar modules 102 and the pyranometer 104 measured is compared with the previous and next measured output values. Further, depending upon the instance for which the data is to be ascertained, i.e., cloudy/non-cloudy solar modules 102 and/0r pyranometer 104, the measured values are processed accordingly.
[0043] The three instances are described hereinafter:
(i) Determination of cloudy solar module 102 with non-cloudy pyranometer 104:
[0044] Solar arrays in different locations receive different values of solar irradiation. Hence, different solar array locations provide the computing unit 112 with differing values of measured/recorded SMB data, comprising rate of change of SMB current output and other measured SMB data.
[0045] In an embodiment, the computing unit 112 is configured to determine a first type of instance where the solar module 102 may have been under cloud cover and where the pyranometer may not have been under cloud cover.
[0046] This first instance determination is accomplished by processing variations in the SMB data measured by the SMBs 108 and the PoA irradiance data measured by the pyranometer 104.
[0047] The determination of instances of cloudy solar modules 102 is achieved by processing/analyzing normal rates of change of output values of the SMB current and other SMB data. Further, instances of cloudy solar modules 102 are determined by the computing unit 112 by analyzing the output values of the SMB current, i.e., decreased values of the SMB current. The computing unit 112 also processes the output values of the pyranometer 104, to determine/confirm whether the pyranometer 104 output values may have little to no variation, due to not being under cloud cover.
(ii) Determination of non-cloudy solar module 102 with cloudy pyranometer 104:
[0048] In an embodiment, the computing unit 112 determines a second instance of non-cloudy solar module 102 with cloudy pyranometer 104 by processing the SMB data and the PoA irradiance data. In case the computing unit 112 determines incremental values of output of the SMB current and the PoA irradiance data, the computing unit 112 confirms an indication of non-cloudy solar modules 102.
[0049] Further, in such second instances, the output values measured from the SMB 108 may not be at par with the non-cloudy pyranometer 104 values. Thus, the computing unit 112 processes this variation in the pyranometer 104 values, along with the incremental SMB current values, to indicate non-cloudy solar modules 102 and a cloudy pyranometer 104.

(iii) Determination of (a) cloudy combination of solar module 102 and pyranometer 104, (b) non-cloudy combination of solar module 102 and pyranometer 104:
[0050] In an embodiment, the computing unit 112 determines a third instance wherein both the solar modules 102 and the pyranometer 104 may have been cloudy, or instances wherein both the solar modules 102 and the pyranometer 104 may have been non-cloudy.
[0051] The computing unit 112 combines and/or processes the information generated in the first instance and second instance, to determine instances of both the solar modules 102 and the pyranometer 104 being cloudy or non-cloudy.
[0052] Since the first and second instances comprise information of both cloudy and non-cloudy instances for both the solar modules 102 and the pyranometer 104, a user may easily use the computing unit 112 to determine the information for the third instance.
[0053] Advantageously, the computing unit 112 is also further configured to determine cloud cover during peak radiation hours which is derived from the working disclosed in the foregoing description.
[0054] In an event where the cloud cover is calculated for solar modules 102 during peak radiation hours, the computing unit 112 implements concepts of non-linearity between two or more successive values of the SMB data, i.e., the SMB current output.
[0055] For determining cloud cover during peak hours in this method and approach, the computing unit 112 analyses and compares successive values of the SMB current output data and the PoA irradiance data with each other, from a point where non-linearity between said factors may have commenced.
[0056] The computing unit 112 makes this analysis based on an assumption that the current data of SMBs 108 does not always follow a standard curve of PoA irradiance, due to variations in technical designs of the solar panels or the solar power plants, as a whole.
[0057] Further, in the present invention, the computing unit 112 combines information generated at the first and second instances, as well as the information of cloud cover during peak radiation hours, to enable a user to determine final instances when the SMBs 108 or solar modules 102 may have been under cloud cover.
[0058] In an embodiment, the determined cloud cover data is then communicated to a monitoring device 114 comprising one or more displays to display the determined cloud cover value. The monitoring device 114 may comprise one or more of a computer device, a laptop, a palm-top, a personal digital assistant device, and a smartphone device.
[0059] The monitoring device 114 enables one or more users or other administrators/ persons-in-charge to track the performance of each SMB 108, to which the multiple solar modules 102 are attached. The monitoring device 114 also helps the users to determine and identify low performing SMBs 108 connected with multiple solar modules 102. Such a determination may, in turn, enable the users to devise methods for optimizing low performing solar modules 102, if any, for better performances. Advantageously, the overall performance of the solar power plants is also improved effectively.
[0060] Figure 1B depicts/illustrates an exemplary representation of the system 100 for determining shading loss due to a cloud-covered solar module associated with multiple SMBs 108/1, 108/2, and 108/3 as is depicted at 100, in accordance with an embodiment. As aforementioned, the SMBs 108/1, 108/2, and 108/3 record electrical SMB data such as, but not limited to, current, voltage, and temperature of the corresponding solar modules 102/1, 102/2, and 102/3, which is termed as SMB data.
[0061] In the depicted exemplary situation, the solar module 102/1 may be partially/fully covered by a cloud 106/1, and the solar modules 102/2 and 102/3 are free from the cloud covers 106/1 and 106/2. Further, pyranometer 104 is configured to measure solar irradiance over a plane of array (PoA), which is partially/fully covered by the cloud 106/2.
[0062] Similar to the working disclosed in the foregoing description, the measured PoA irradiance data and the recorded electrical SMB data is transferred to be tracked by an output meter 110, through one or more wired connections.
[0063] In an embodiment, the received data in the output meter 110 is transferred to the computing unit 112 for determining the cloud cover for various instances, viz., (i) cloudy solar module 102/1 with non-cloudy pyranometer 104, (ii) cloudy pyranometer 104 with non-cloudy solar modules 102/2 and 102/3, and (iii) both the solar modules 102 and the pyranometer 104 being under cloudy or non-cloudy instances.
[0064] In an embodiment, the determined cloud cover data is then communicated to the monitoring device 114. The monitoring device 114 is configured with at least one display to indicate the determined cloud cover values so that the cloud cover instance of each SMBs 108/1, 108/2, and 108/3 can be monitored and tracked by a user in real-time condition.
[0065] In an embodiment, the measured current data of SMBs 108 does not always follow the standard curve of PoA irradiance, due to differing technical designs of solar power plants, which may vary in each solar power plant. Additionally, during peak radiation hours, the solar plant starts drawing less current from SMBs 108, to maintain the solar grid capacity. This low-drawn current is typically misinterpreted as cloud-cover.
[0066] Advantageously, the computing unit 112 determines the cloud cover during peak radiation hours by using a unique and specific algorithmic approach, which overcomes any adverse onset of inverters’ current limitation function.
[0067] Figure 2 depicts/illustrates various modules comprised within the system 100 for determining cloud cover over solar modules as is depicted at 200. The modules comprised within the system 100 for determining the cloud cover over the solar modules may comprise the pyranometer 104, the SMB 108, the output meter 110, and the computing unit 112.
[0068] In an embodiment, the pyranometer 104 comprises a thermopile sensor 202. The thermopile sensor 202 is configured to measure temperature-related parameters corresponding to received solar radiation. Further, the pyranometer 104 converts the measured temperature-related parameters into a voltage/ current output in order to measure solar irradiance over a plane of array (PoA).
[0069] In an embodiment, the SMB 108 comprises a fuse assembly 204, a surge protector 206, a combined bus 208, an output wire 212, and one or more DC disconnects 210.
[0070] In an embodiment, the fuse assembly 204 protects the SMB 108 from high-currents. The surge protector 206 limits incoming and outgoing voltages of the SMB 108. In the same embodiment of the invention, the combined bus 208 transfers the measured PoA irradiance data value and the measured/recorded SMB current value to be tracked by an output meter 110. The output wire 212 provides electrical wire connections to the SMBs 108 to connect to the pyranometer 104 and the solar modules 102 (as depicted in Figures 1A and 1B). The DC connects 210 provides or interrupts electricity flow between the SMBs 108 and solar modules 102.
[0071] In an embodiment, the output meter 110 receives the electrical data from the SMB 108 and the radiation data from the pyranometer 104 through one or more electrical wired connections. The output meter 110 further transfers the data to the computing unit 112 for processing and determining the cloud cover.
[0072] In an embodiment, the computing unit 112 comprises a control unit 214, a storage memory 216, and a communication unit 218.
[0073] In an embodiment, the storage memory 216 is configured to store the data that is received from the output meter 110. The storage memory 216 may comprise or be connected to at least one of a read-only memory, a random-access memory, a non-volatile memory, and a cloud memory.
[0074] In an embodiment, the control unit 214 is configured to process the received data that is stored in the storage memory 216 and to determine the cloud cover during any point of time.
[0075] The cloud cover can be determined by processing real-time values and incremental values of rate of change of SMB current data and PoA irradiance data; and obtaining a mean value by analyzing and/or combining both the real-time values and incremental values as disclosed in the foregoing description.
[0076] The control unit 214 is further configured to determine the cloud cover during peak hours by comparing successive values of both the SMB current and the PoA irradiance with determined values at which non-linearity starts between the SMB current data and the PoA irradiance data.
[0077] In an embodiment, daily soiling levels, which could also cause low current in SMBs, do not affect the accuracy of determining cloud-clover. This is due to the calculation being done on instantaneous values of both the current and radiation. Further, any change caused due to other factors will cause a homogenous impact that will be inherent in the instantaneous values being utilized.
[0078] In an embodiment, the determined cloud cover data may be in a form of an analog or digital data or combination of both analog and digital data.
[0079] In a further embodiment of the invention, the determined cloud cover data may also be provided to the user through their monitoring device 114, in the form of one or more statistical representations comprising at least one of charts, graphs, plots, histograms, and scatter plots, among others.
[0080] In an embodiment, the communication unit 218 is configured to transmit the determined cloud cover data over any type of wired or wireless network such as through the Internet, Wi-Fi, telephone, external server, etc., to one or more monitoring devices 114.
[0081] The monitoring device 114 present in the invention (refer Figures 1A and 1B) is configured to display the cloud cover instance in real-time, to the user.
[0082] Figure 3 illustrates a flowchart of a method 300 for determining shading loss over cloud-covered solar modules.
[0083] In an embodiment, the method 300 begins with measuring PoA irradiance data by using pyranometers, as depicted at step 302. Subsequently, the method 300 discloses tracking of SMB data and the PoA irradiance data through an output meter, as depicted at step 304. Further, as shown in step 306, real-time values of rate of change of SMB current and PoA irradiance are determined. Furthermore, as shown in step 308, the incremental value of the rate of change of the SMB current and the PoA irradiance is determined.
[0084] In an embodiment, a mean value is obtained by comparing the determined real-time and incremental value of the rate of change of the SMB current and PoA irradiance as depicted in step 310. Further, as depicted at step 312, the cloud cover data during peak hours are determined by comparing successive values of the SMB current and the PoA irradiance with values at which non-linearity starts between both SMB current data and PoA irradiance data, due to essential design parameters.
[0085] In an embodiment, the determined cloud cover data during peak hours is then combined with the obtained mean value to determine instances at which solar modules were under cloud covers, as depicted at step 314. Thereafter, the determined cloud cover instances of the solar modules can be displayed through a monitoring device, so that performance of each SMBs can be tracked and monitored, as depicted at step 316.
[0086] An important advantage of the present invention is the determination of the cloud covers over the solar modules, as well as variations of the performance of the solar modules incurred due to the cloud covers, in real-time. Additionally, the disclosed method does not require large quantities of or high-end sensors for determination of several solar modules related parameters.
[0087] Owing to the simplicity of the system, the disclosed invention is economical and cost-effective.
[0088] Moreover, since the disclosed method does not require installation of any new systems or sensors, the present invention is also efficient in terms of maintenance required for the system, and resources such as time, energy, manpower, etc., that may be required to ensure smooth functioning of the disclosed system.
[0089] The present invention also enables large-scale solar power system users to improvise the performance of the power generation easily by identifying and optimizing the specific low performing SMBs with which the solar modules were connected.
[0090] Another advantage of the present invention is that the performance of each solar array associated with the SMBs can be tracked and monitored at any point of time during a day.
[0091] An additional advantage of the present invention is that the method which is reliable, economical, and suitable for all types such as from small-scale solar power systems to large-scale solar power systems.
[0092] Applications of the current invention include determining the shading losses over the cloud covered solar modules, tracking and monitoring the performance of each SMBs, and identifying and optimizing the performance of the low performing SMBs.
[0093] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the scope of the embodiments as described here.
,CLAIMS:We claim:
1. A system (100) for determining shading loss of at least one solar power plant, comprising:
at least one string-monitoring box (SMB) (108/1, 108/2, 108/3) connected to at least one solar module (102/1, 102/2, 102/3) located in the solar power plant, wherein the string-monitoring box (SMB) (108/1, 108/2, 108/3) is configured to measure at least one electrical SMB data of each solar module (102/1, 102/2, 102/3);
at least one pyranometer (104) configured to measure at least one PoA irradiance data associated with the solar power plant;
an output meter (110) connected to the string-monitoring box (108/1, 108/2, 108/3) and the at least one pyranometer (104), to track and communicate the electrical SMB data and the PoA irradiance data with a computing unit (112); and
the computing unit (112) configured to process the tracked electrical SMB data and PoA irradiance data to determine the shading loss due to at least one determined cloud cover instance of the solar module (102/1, 102/2, 102/3).

2. The system (100) for determining shading losses as claimed in claim 1, wherein the electrical SMB data comprises at least one of current, output current, voltage and temperature of the at least one solar module (102/1, 102/2, 102/3).

3. The system (100) for determining shading losses as claimed in claim 1, wherein the output meter (110) comprises at least one of a multimeter, an electric meter, and a power meter.

4. The system (100) for determining shading losses as claimed in claim 1, wherein the pyranometer (104) converts the PoA irradiance data comprising one or more measured temperature-related parameters into a voltage or current output, and wherein the at least one pyranometer (104) comprises at least one of a temperature measuring sensor, thermopile sensor, pyrgeometer, pyrheliometer, thermopile, thermocouple and silicon photocells.

5. The system (100) for determining shading losses as claimed in claim 1, wherein the at least one determined cloud cover instance comprises at least one instance of:
a cloudy solar module (102/1, 102/2, 102/3) with a non-cloudy pyranometer (104),
a non-cloudy solar module (102/1, 102/2, 102/3) with a cloudy pyranometer (104), and
both the solar module (102/1, 102/2, 102/3) and the pyranometer (104) being under cloudy or non-cloudy instances.

6. The system (100) for determining shading losses as claimed in claim 1, wherein the computing unit (112) comprises:
a storage memory (216) configured to receive and store at least one of the electrical SMB data and the PoA irradiance data from the output meter (110);
a control unit (214) configured to determine the at least one shading loss due to at least one cloud cover instance, by processing the stored data; and
a communication unit (218) configured to communicate the determined shading loss due to at least one cloud cover instance, to at least one monitoring device (114), wherein the at least one monitoring device (114) is configured to enable at least one user to track shading loss and performance of at least one of the string-monitoring box (108/1, 108/2, 108/3) and the at least one solar module (102/1, 102/2, 102/3).

7. The system (100) for determining shading losses as claimed in claim 1, wherein the computing unit (112) is configured to determine at least one real-time value and at least one incremental value of rate of change of the processed data comprising the electrical SMB data and the PoA irradiance data, and wherein the computing unit (112) is configured to determine a mean value by comparing the determined at least one real-time value and the at least one incremental value.

8. The system (100) for determining shading losses as claimed in claim 7, wherein the computing unit (112) is configured to determine cloud cover data during peak hours, by comparing successive values of the electrical SMB data and the PoA irradiance data, with values of non-linearity between the electrical SMB data and the PoA irradiance data.

9. The system (100) for determining shading losses as claimed in claim 8, wherein the computing unit (112) is configured to analyze the determined cloud cover data during peak hours with the determined mean value, to determine the at least one cloud cover instance.

10. The system (100) for determining shading losses as claimed in claim 1, wherein the determined shading loss due to at least one cloud cover instance is communicated in form of at least one of an analog data, a digital data, combination of both the analog data and the digital data, and a statistical representation.

11. A method (300) for determining shading loss of at least one solar power plant, comprising:
measuring at least output current of SMB having at least one solar module (102/1, 102/2, 102/3) located in the solar power plant, by using at least one string-monitoring box (SMB) (108/1, 108/2, 108/3) connected to each solar module (102/1, 102/2, 102/3);
measuring at least one PoA irradiance data associated with the solar power plant, by using at least one pyranometer (104);
tracking and communicating the electrical SMB data and the PoA irradiance data through an output meter (110) to a computing unit (112), by connecting the output meter (110) to the string-monitoring box (SMB) (108/1, 108/2, 108/3) and the pyranometer (104); and
determining the shading loss due to at least one determined cloud cover instance of the solar module (102/1, 102/2, 102/3), by processing the tracked electrical SMB data and PoA irradiance data by using a computing unit (112).

12. The method (300) for determining shading losses as claimed in claim 11, wherein measuring the at least one electrical SMB data comprises measuring at least one of current, output current, voltage and temperature of the at least one solar module (102/1, 102/2, 102/3).

13. The method (300) for determining shading losses as claimed in claim 11, wherein tracking the electrical SMB data and the PoA irradiance data through an output meter (110) comprises using at least one of a multimeter, an electric meter and a power meter.

14. The method (300) for determining shading losses as claimed in claim 11, wherein measuring at least one PoA irradiance data comprises converting the PoA irradiance data comprising one or more measured temperature-related parameters into a voltage or current output, and wherein the at least one pyranometer (104) comprises at least one of a temperature measuring sensor, thermopile sensor, pyrgeometer, pyrheliometer, thermopile, thermocouple and silicon photocells.

15. The method (300) for determining shading losses as claimed in claim 11, wherein determining at least one cloud cover instance comprises determining at least one instance of:
a cloudy solar module (102/1, 102/2, 102/3) with a non-cloudy pyranometer (104),
a non-cloudy solar module (102/1, 102/2, 102/3) with a cloudy pyranometer (104), and
both the solar module (102/1, 102/2, 102/3) and the pyranometer (104) being under cloudy or non-cloudy instances.

16. The method (300) for determining shading losses as claimed in claim 11, comprising:
receiving and storing data comprising the at least one electrical SMB data and the PoA irradiance data from the output meter (110), by using a storage memory (216) associated with the computing unit (112);
determining the shading loss due to at least one cloud cover instance, by using a control unit (214) associated with the computing unit (112); and
communicating the determined shading loss due to at least one cloud cover instance, to at least one monitoring device (114), by using a communication unit (218) of the computing unit (112); wherein the at least one monitoring device (114) is configured to enable at least one user to track shading loss and performance of at least one of the string-monitoring box (108/1, 108/2, 108/3) and the at least one solar module (102/1, 102/2, 102/3).

17. The method (300) for determining shading losses as claimed in claim 11, comprising:
determining at least one real-time value and at least one incremental value of rate of change of the processed data comprising the electrical SMB data and the PoA irradiance data; and
determining a mean value by comparing the determined at least one real-time value and the at least one incremental value, by using the computing unit (112).

18. The method (300) for determining shading losses as claimed in claim 17, comprising determining cloud cover data during peak hours, by comparing successive values of the electrical SMB data and the PoA irradiance data, with values of non-linearity between the electrical SMB data and the PoA irradiance data.

19. The method (300) for determining shading losses as claimed in claim 18, comprising analyzing the determined cloud cover data during peak hours with the obtained mean value to determine the at least one cloud cover instance, by using the computing unit (112).

20. The method (300) for determining shading losses as claimed in claim 11, comprising communicating the determined shading loss due to at least one cloud cover instance, in form of at least one of an analog data, a digital data, combination of both the analog data and the digital data, and a statistical representation.