Method and system for analyzing output power of photovoltaic system in non-uniform illumination environment

Abstract

The invention discloses a photovoltaic system output power analysis method and system in a non-uniform illumination environment, and belongs to the field of photovoltaic power generation control. According to the technical scheme, a test period is divided into a plurality of sampling time domains according to a time sequence, and output power values and output power influence factor characteristic data at the tail end moments of the sampling time domains in the operation process of a photovoltaic system are collected; calculating an output power value at the starting moment of the next test period and a correlation coefficient between the influence factor characteristic data and the output power value according to the obtained data, and screening out all influence factors which are strongly correlated with the output power value through a correlation threshold value as output power deviation degree induction factors; the early warning level of the output power deviation degree is set, when the output power deviation degree exceeds a threshold value, output power deviation degree induction factor characteristic data is called, and the reason for deviation of the output power of the photovoltaic system and the submodule area are determined according to the obtained data.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic power generation control, and in particular to a method and system for analyzing output power of a photovoltaic system under a non-uniform illumination environment. Background Art

[0002] Photovoltaic energy is an important component of new energy. Improving the popularity and utilization rate of solar power generation will help alleviate the energy supply crisis and improve the current situation of my country's long-term reliance on thermal power generation. In recent years, with the continuous development of the photovoltaic industry and the continuous updating of photovoltaic power generation technology, small off-grid photovoltaic power generation systems have been increasingly used in remote areas and homes, public equipment, street lights, areas with incomplete infrastructure, etc., which can solve the energy supply problem in the above areas to a certain extent.

[0003] During the use of small-scale off-grid photovoltaic power generation systems, local shadows caused by trees, clouds, dust, changes in environmental conditions, uneven sunlight and other factors often cause them to work in an environment with non-uniform light intensity. Affected by the non-uniform light intensity, the output power of the system's photovoltaic sub-modules does not match, and the affected photovoltaic sub-modules stop converting light energy into electrical energy, acting as external loads, and continuously consuming the energy generated by other photovoltaic sub-modules, thereby reducing the photovoltaic system's power generation energy, resulting in a reduction in output power, leading to a deterioration in the power generation effect of the entire photovoltaic system, and in severe cases it can lead to a "hot spot effect", causing irreversible damage to the photovoltaic cells.

[0004] Due to various restrictions, the existing small off-grid photovoltaic power generation systems have complex operating environments, long maintenance cycles, lack of operating status supervision, and are prone to failures. Not only can they not achieve the goal of energy conservation, but they also cause difficulties in maintenance and high maintenance costs, restricting their development. To this end, we propose a method and system for analyzing the output power of photovoltaic systems under non-uniform illumination environments. Summary of the invention

[0005] The main purpose of the present invention is to provide a method and system for analyzing the output power of a photovoltaic system under a non-uniform illumination environment, which can effectively solve the problems in the background technology.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A method for analyzing output power of a photovoltaic system under a non-uniform illumination environment, comprising:

[0008] The test period T is divided into i sampling time domains according to the time sequence, and the end time of each sampling time domain is t 1 , t 2 ,...,t i, where the test period T and the number of sampling time domains i satisfy the relationship T = (9-15)i;

[0009] The output power values ​​of the photovoltaic system at the end of the sampling time domain are collected and recorded as P 1 , P 2 , ..., P i , the output power value P' at the start time of the next test cycle is calculated by the model, wherein the expression of the model is:

[0010] P'=αP i +α(1-α)P i-1 +α(1-α) 2 P i-2 +...+α(1-α) t-1 P 1 +(1-α) t P i '

[0011] Where P i ' is t calculated by the model i The output power value at time , α is a constant coefficient, and α∈(0,1];

[0012] Collect the output power influencing factor characteristic data at the end of the sampling time domain within the test period T, and calculate the correlation coefficient between the influencing factor characteristic data and the output power value, wherein the calculation formula of the correlation coefficient is:

[0013]

[0014] In the formula, ξ ij is the correlation coefficient between the jth influencing factor and the output power value at the end of the i-th sampling time domain, x ij is the characteristic data value of the jth influencing factor at the end of the i-th sampling time domain, is the mean value of the characteristic data value of the jth influencing factor at the end of the i-th sampling time domain, is the mean of the output power sample values ​​at the end of the i-th sampling time domain;

[0015] By using the correlation threshold [-1,ξ 1 ]∪[ξ 2 , 1] select all influencing factors that are strongly correlated with the output power value as the output power deviation inducing factors, where ξ 1 The value range of ξ is [-0.9,-0.7], 2 The value range of is [0.6,1], and the calculation formula of the output power deviation is:

[0016]

[0017] Where Dd T→T+1 is the output power deviation between the Tth test cycle and the T+1th test cycle, and λ is the environmental correction coefficient;

[0018] The warning level of the output power deviation is set. When the output power deviation exceeds the threshold, characteristic data of the output power deviation inducing factors are retrieved, and the cause of the deviation of the output power of the photovoltaic system and the submodule area are determined based on the acquired data.

[0019] A photovoltaic system output power analysis system under a non-uniform illumination environment, the system comprising a data acquisition module, a data storage module, an output power prediction module, a data processing module, an influencing factor screening module, a central control module, and an early warning module;

[0020] The data acquisition module is used to collect the output power value and characteristic data of the factors affecting the output power at the end of the sampling time domain in any test cycle T during the operation of the photovoltaic system;

[0021] The data storage module is connected to the data acquisition module and is used to store the acquired output power value and characteristic data of various output power influencing factors;

[0022] The output power prediction module is connected to the data acquisition module, and is used to build a prediction model based on the output power value data at the end of the sampling time domain in the test cycle T, and calculate the output power value at the start of the next test cycle through the model, wherein the expression of the model is:

[0023] P'=αP i +α(1-α)P i-1 +α(1-α) 2 P i-2 +...+α(1-α) t-1 P 1 +(1-α) t P i '

[0024] Where P i ' is t calculated by the model i The output power value at time , α is a constant coefficient, and α∈(0,1];

[0025] The data processing module is connected to the data acquisition module and is used to calculate the correlation coefficient between the influencing factor characteristic data and the output power value;

[0026] The influencing factor screening module is connected to the data processing module, and is used to set a correlation threshold, and screen out all influencing factors that are strongly correlated with the output power value as output power deviation inducing factors through the correlation threshold;

[0027] The central control module is connected to the data acquisition module and the influencing factor screening module, and is used to calculate the output power deviation, and divide the safety level of the output power deviation obtained within the test period T into a stable state, a normal state and a warning state by setting the warning level of the output power deviation, and generate a warning signal when the output power deviation is in the warning state;

[0028] The early warning module is connected to the central control module. In response to the early warning signal generated by the central control module, the early warning module retrieves the characteristic data of the output power deviation inducing factor, and determines the cause of the deviation of the photovoltaic system output power and the submodule area according to the acquired data;

[0029] The system further includes a memory, a processor, and an electronic program stored in the memory and capable of running on the processor.

[0030] The present invention has the following beneficial effects:

[0031] Compared with the prior art, the technical solution of the present invention divides a test cycle into several sampling time domains according to the time sequence, collects the output power value and the characteristic data of the output power influencing factors at the end of the sampling time domain during the operation of the photovoltaic system, calculates the output power value at the start of the next test cycle and the correlation coefficient between the characteristic data of the influencing factors and the output power value according to the acquired data, screens out all the influencing factors that are strongly correlated with the output power value as the output power deviation inducing factors through the correlation threshold, and sets the early warning level of the output power deviation. When the output power deviation exceeds the threshold, the characteristic data of the output power deviation inducing factors is retrieved, and the cause of the deviation of the output power of the photovoltaic system and the sub-module area are determined according to the acquired data, thereby achieving the purpose of automatic supervision of the output power of a small off-grid photovoltaic power generation system, and reducing the risk of the photovoltaic system operating in a non-uniform lighting environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a flow chart of a method for analyzing output power of a photovoltaic system under a non-uniform illumination environment according to the present invention;

[0033] Figure 2 The overall structural block diagram of a photovoltaic system output power analysis system under a non-uniform illumination environment according to the present invention. DETAILED DESCRIPTION

[0034] The present invention will be further described below in conjunction with specific implementation methods, wherein the accompanying drawings are only used for exemplary descriptions and represent only schematic diagrams rather than actual drawings, and should not be understood as limiting the present invention. In order to better illustrate the specific implementation methods of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product.

[0035] Example 1

[0036] like Figure 1 The flowchart of the method for analyzing the output power of a photovoltaic system under a non-uniform illumination environment of the present invention is shown in FIG. Figure 2 The figure shows an overall structural block diagram of a photovoltaic system output power analysis system in a non-uniform illumination environment according to the present invention.

[0037] The specific implementation process of the technical solution of the present invention includes the following steps:

[0038] Step 1: Divide the test period T into i sampling time domains according to the time sequence, and record the end time of the sampling time domain as t 1 , t 2 ,...,t i , wherein the test period T and the number of sampling time domains i satisfy the relationship T=(9-15)i, and the output power value and characteristic data of the output power influencing factors at the end of the sampling time domain in any test period T during the operation of the photovoltaic system are collected through the data acquisition module. It should be added that the output power influencing factors involved in this embodiment may be one or more of solar radiation, photovoltaic module temperature, ambient temperature, wind speed, relative humidity, cloud cover, and air pressure.

[0039] Step 2: construct a prediction model based on the acquired data through the output power prediction module, and calculate the output power value at the start of the next test cycle through the model, where the expression of the model is:

[0040] P'=αP i +α(1-α)P i-1 +α(1-α) 2 P i-2 +...+α(1-α) t-1 P 1 +(1-α) t P i '

[0041] Where P i ' is t calculated by the model i The output power value at time t is α, α is a constant coefficient, and α∈(0,1], where the value of α is determined according to the deviation of the output power within the test period T, specifically:

[0042] First, the output power deviation is calculated by the central control module, and the calculation formula is:

[0043]

[0044] Where Dd T→T+1 is the output power deviation between the Tth test cycle and the T+1th test cycle, λ is the environmental correction factor, and the value of the environmental correction factor λ is based on the average wind speed w in the test cycle T. v And the average air quality index value AQI is determined, specifically:

[0045] When v When ≤4.5m / s and AQI≥200, λ is 0.75;

[0046] When v >7m / s and AQI≤100, λ is 1.25;

[0047] Divide the above average wind speed w v When the average air quality index value AQI is outside the range, λ is 1.05;

[0048] Then the calculation result of the output power deviation is used to divide the output power deviation into levels. The specific method includes the following steps:

[0049] S21, obtaining the output power value at the end of the sampling time domain in the test cycle T, and obtaining the output power deviation between the T-th test cycle and the test cycles at the end of the sampling time domain at the t-1st and tth test cycles by a calculation formula, the calculation formula is:

[0050]

[0051] Where Dd t-1→t is the output power deviation between the Tth test cycle and the t-1th and tth sampling time domain end moments, t is an integer greater than or equal to 1, P t-1 , P t are the measured values ​​of the output power at the end of the t-1th and tth sampling time domains respectively;

[0052] S22, using the obtained output deviation value in the Tth test cycle to create a sample set, denoted as {Dd 0→t ,Dd 1→2 ,,,,,Dd t-1→t};

[0053] S23, obtain the mean and standard deviation of the sample set, and use the mean and standard deviation to standardize the data. The standardization formula is: In this formula, z is the standard parameter, σ is the variance of the sample data, and μ is the mean of the sample data;

[0054] S24, after completing the standardization, the standard parameters are used The numerical interval is adjusted to [0,1], and the output power deviation is classified using the function value of f(k). The classification mechanism is:

[0055] when When , the output power deviation is in a stable state;

[0056] when When , the output power deviation is in normal state;

[0057] when When , the output power deviation is in the warning state; where f(k) min 、f(k) max are the minimum and maximum function values ​​of f(k) respectively;

[0058] Then, determine the value range of α. The specific principles are:

[0059] When the output power deviation is in a stable state, the value range of α is α∈(0,0.2];

[0060] When the output power deviation is in normal state, the value range of α is α∈[0.1,0.4];

[0061] When the output power deviation is in the warning state, the value range of α is α∈[0.3,1].

[0062] Step 3: Calculate the correlation coefficient between the influencing factor characteristic data and the output power value through the data processing module. The calculation formula of the correlation coefficient is:

[0063]

[0064] In the formula, ξ ij is the correlation coefficient between the jth influencing factor and the output power value at the end of the i-th sampling time domain, x ij is the characteristic data value of the jth influencing factor at the end of the i-th sampling time domain, is the mean value of the characteristic data value of the jth influencing factor at the end of the i-th sampling time domain, is the mean of the output power sample values ​​at the end of the i-th sampling time domain.

[0065] Step 4: Set the correlation threshold [-1,ξ 1 ]∪[ξ 2 , 1], where ξ 1 The value range of ξ is [-0.9,-0.7], 2The value range of is [0.6, 1], and all influencing factors that are strongly correlated with the output power value are screened out through the correlation threshold as the output power deviation inducing factors.

[0066] Step 5: The central control module calculates the output power deviation between the Tth test cycle and the T+1th test cycle. The calculation formula is:

[0067]

[0068] Where Dd T→T+1 is the output power deviation between the Tth test cycle and the T+1th test cycle, λ is the environmental correction coefficient, and when the calculated output power deviation level is in the warning state, a warning signal is generated by the central control module.

[0069] Step six, in response to the warning signal generated by the central control module, the warning module retrieves the characteristic data of the output power deviation inducing factors, and determines the cause of the deviation in the output power of the photovoltaic system and the sub-module area based on the acquired data, so as to determine the output power abnormal point and the cause of the output power abnormality. The specific implementation method can be determined by checking the collection timestamp of the data acquisition module and the coordinates of the installation location point of the photovoltaic system.

[0070] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for analyzing the output power of a photovoltaic system under a non-uniform illumination environment, characterized in that: include: The test period T is divided into i sampling time domains according to the time sequence, and the end time of the sampling time domain is respectively recorded as t1, t2, ..., t i ; The output power values ​​of the photovoltaic system at the end of the sampling time domain are collected and recorded as P1, P2, ..., P i , the output power value P' at the start time of the next test cycle is calculated by the model, wherein the expression of the model is: P'=αP i +α(1-α)P i-1 +a(1-a) 2 P i-2 +...+a(1-a) t-1 P1+(1-a) t P i ' Where P i ' is t calculated by the model i The output power value at time , α is a constant coefficient, and α∈(0,1]; Collect characteristic data of the factors affecting output power at the end of the sampling time domain within the test period T, and calculate the correlation coefficient between the characteristic data of the factors affecting output power and the output power value; Through the correlation threshold [-1,ξ1]∪[ξ2,1], all influencing factors that are strongly correlated with the output power value are screened as output power deviation inducing factors; The warning level of the output power deviation is set. When the output power deviation exceeds the threshold, characteristic data of the output power deviation inducing factors are retrieved, and the cause of the deviation of the output power of the photovoltaic system and the submodule area are determined based on the acquired data.

2. The method for analyzing the output power of a photovoltaic system under a non-uniform illumination environment according to claim 1, characterized in that: The calculation formula of the output power deviation is: Where Dd T→T+1 is the output power deviation between the Tth test cycle and the T+1th test cycle, and λ is the environmental correction coefficient.

3. The method for analyzing the output power of a photovoltaic system under a non-uniform illumination environment according to claim 1, characterized in that: The calculation formula of the correlation coefficient is: In the formula, ξ ij is the correlation coefficient between the jth influencing factor and the output power value at the end of the i-th sampling time domain, x ij is the characteristic data value of the jth influencing factor at the end of the i-th sampling time domain, is the mean value of the characteristic data value of the jth influencing factor at the end of the i-th sampling time domain, is the mean of the output power sample values ​​at the end of the i-th sampling time domain.

4. The method for analyzing the output power of a photovoltaic system under a non-uniform illumination environment according to claim 1, characterized in that: The value of the environmental correction factor λ is based on the average wind speed w in the test period T. v And the average air quality index value AQI is determined, specifically: When v When ≤4.5m / s and AQI≥200, λ is 0.75; When v >7m / s and AQI≤100, λ is 1.25; Divide the above average wind speed w v When the average air quality index value AQI is outside the range, λ is taken as 1.

05.

5. The method for analyzing the output power of a photovoltaic system under a non-uniform illumination environment according to claim 1, characterized in that: The method for classifying the warning levels of output power deviation comprises the following steps: S1, obtain the output power value at the end of the sampling time domain in the test cycle T, and obtain the output power deviation between the T-th test cycle and the test cycles at the end of the sampling time domain at the t-1st and tth test cycles by the calculation formula. The calculation formula is: Where Dd t-1→t is the output power deviation between the Tth test cycle and the t-1th and tth sampling time domain end moments, t is an integer greater than or equal to 1, P t-1 , P t are the measured values ​​of the output power at the end of the t-1th and tth sampling time domains respectively; S2, using the output deviation value obtained in the Tth test cycle to create a sample set, denoted as {Dd 0→t ,Dd 1→2 ,,,,,Dd t-1→t }; S3, obtain the mean and standard deviation of the sample set, and use the mean and standard deviation to standardize the data. The standardization formula is: In this formula, z is the standard parameter, σ is the variance of the sample data, and μ is the mean of the sample data; S4, after completing the standardization, use the standard parameters The numerical interval is adjusted to [0,1], and the output power deviation is classified using the function value of f(k). The classification mechanism is: when When , the output power deviation is in a stable state; when When , the output power deviation is in normal state; when When , the output power deviation is in the warning state; Among them, f(k) min 、f(k) max are the minimum and maximum function values ​​of f(k) respectively.

6. The method for analyzing the output power of a photovoltaic system under a non-uniform illumination environment according to claim 1, characterized in that: The value of α is determined as follows: When the output power deviation is in a stable state, the value range of α is α∈(0,0.2]; When the output power deviation is in normal state, the value range of α is α∈[0.1,0.4]; When the output power deviation is in the warning state, the value range of α is α∈[0.3,1].

7. The method for analyzing the output power of a photovoltaic system under a non-uniform illumination environment according to claim 1, characterized in that: The test period T and the number of sampling time domains i satisfy the relationship T=(9-15)i.

8. The method for analyzing the output power of a photovoltaic system under a non-uniform illumination environment according to claim 1, characterized in that: The value range of ξ1 is [-0.9,-0.7], and the value range of ξ2 is [0.6,1].

9. A photovoltaic system output power analysis system under non-uniform illumination environment, characterized in that: The system includes a data acquisition module, a data storage module, an output power prediction module, a data processing module, an influencing factor screening module, a central control module, and an early warning module; The data acquisition module is used to collect the output power value and characteristic data of the factors affecting the output power at the end of the sampling time domain in any test cycle T during the operation of the photovoltaic system; The data storage module is connected to the data acquisition module and is used to store the acquired output power value and characteristic data of various output power influencing factors; The output power prediction module is connected to the data acquisition module, and is used to build a prediction model based on the output power value data at the end of the sampling time domain in the test cycle T, and calculate the output power value at the start of the next test cycle through the model, wherein the expression of the model is: P'=αP i +α(1-α)P i-1 +a(1-a) 2 P i-2 +...+a(1-a) t-1 P1+(1-a) t P i ' Where P i ' is t calculated by the model i The output power value at time , α is a constant coefficient, and α∈(0,1]; The data processing module is connected to the data acquisition module and is used to calculate the correlation coefficient between the influencing factor characteristic data and the output power value; The influencing factor screening module is connected to the data processing module, and is used to set a correlation threshold, and screen out all influencing factors that are strongly correlated with the output power value as output power deviation inducing factors through the correlation threshold; The central control module is connected to the data acquisition module and the influencing factor screening module, and is used to calculate the output power deviation, and divide the safety level of the output power deviation obtained within the test period T into a stable state, a normal state and a warning state by setting the warning level of the output power deviation, and generate a warning signal when the output power deviation is in the warning state; The early warning module is connected to the central control module. In response to the early warning signal generated by the central control module, the early warning module retrieves the characteristic data of the output power deviation inducing factor, and determines the cause of the deviation of the photovoltaic system output power and the sub-module area based on the acquired data.

10. The photovoltaic system output power analysis system under non-uniform illumination environment according to claim 9, characterized in that: The system also includes a memory, a processor, and an electronic program stored in the memory and capable of running on the processor, wherein the processor can implement the steps of the method according to any one of claims 1 to 8 when running the electronic program.

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