Photovoltaic energy storage energy consumption monitoring method and system

Abstract

The present invention relates to the field of photovoltaic system monitoring technology, and in particular to a photovoltaic energy storage energy consumption monitoring method and system, the method comprising: obtaining parameters of a photovoltaic energy storage system; calculating the photovoltaic parameters of the photovoltaic energy storage system at each moment, constructing a state curve according to the photovoltaic parameters at each moment, and taking the product of the photovoltaic parameters and the slope of the data point on the state curve as the amount of damage; calculating the degree of damage of the data point on the state curve, the degree of damage of the data point is positively correlated with the cumulative sum of the difference in the amount of damage of adjacent data points within a preset time period; calculating the importance of the data point, and in response to the importance being greater than a preset threshold, storing and analyzing each parameter corresponding to the data point. The present invention can calculate the importance of the data point, store the parameters according to the importance of the data point, facilitate the identification and classification of the acquired parameter data, and provide great convenience for data analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic system monitoring, and in particular to a photovoltaic energy storage energy consumption monitoring method and system. Background Art

[0002] The photovoltaic energy storage energy consumption monitoring method and system are very important. The photovoltaic energy storage energy consumption monitoring system monitors the operating status of the photovoltaic power generation system and the battery energy storage system in real time through sensors installed in key locations. These sensors can measure the power generation power, voltage and other parameters of the photovoltaic panel array, as well as the charging status, current, voltage and other key data of the energy storage device. Through real-time data collection, the actual operation of the system can be understood, including power generation efficiency, efficiency of energy storage and release process, etc. Through data analysis, system anomalies or potential problems can be discovered in a timely manner, and decision support and optimization suggestions can be provided to improve the operating efficiency and stability of the system.

[0003] The Chinese patent with the announcement number CN103778041B discloses a data monitoring method and device for the Internet. The Internet data monitoring method includes: obtaining request data; writing the request data into a data table; performing statistics on the data in the data table according to a preset rule, and writing the statistical data into a result table; writing the data in the result table into a shared memory; and reporting the data in the shared memory.

[0004] The above scheme cannot identify the importance of the collected data during the data monitoring process, especially in the process of photovoltaic energy storage energy consumption monitoring, a large amount of data is generated, which causes great inconvenience to the analysis of photovoltaic energy storage energy consumption data. Summary of the invention

[0005] In order to solve the problem in the prior art that the importance of collected data cannot be identified and it is not convenient to analyze the data, the present invention provides a photovoltaic energy storage energy consumption monitoring method and system.

[0006] In a first aspect, the present invention provides a photovoltaic energy storage energy consumption monitoring method, which adopts the following technical solution:

[0007] At each moment, the photovoltaic parameters of the photovoltaic energy storage system are calculated, a state curve of the photovoltaic parameters and time is constructed, and the product of the photovoltaic parameters and the slope of the data point on the state curve is taken as the amount of damage;

[0008] Calculate the damage degree of the data point on the state curve, the damage degree of the data point is positively correlated with the cumulative sum of the damage amount differences of adjacent data points within a preset time period;

[0009] Calculate the importance of the data point on the state curve, and in response to the importance being greater than a preset threshold, store the parameters at the same moment corresponding to the data point;

[0010] The expression of photovoltaic parameters is:

[0011]

[0012] in, Indicates The photovoltaic parameters corresponding to the moment, Indicates The power generation efficiency of the photovoltaic panel at a certain moment, Indicates The charge and discharge efficiency at each moment, Indicates The maximum value of the photovoltaic panel temperature and the energy storage device temperature at a certain moment, Indicates The power generated by the photovoltaic panel at the moment, Indicates The light intensity corresponding to the moment.

[0013] The effect is that by calculating the photovoltaic parameters of the data points, the state curve is constructed through the photovoltaic parameters, and finally the importance of the data points is calculated, the parameters are stored according to the importance of the data points, which is convenient for identifying and classifying the acquired parameter data, providing great convenience for data analysis. At the same time, according to the importance of the data, it is convenient to understand the operating status of the photovoltaic energy storage energy consumption system and to monitor the photovoltaic energy storage energy consumption system.

[0014] Preferably, the method for calculating the damage degree of the data points on the state curve is:

[0015] The state curve is segmented into multiple time periods according to the preset time length, and a sliding window is constructed with the data point for which the damage degree needs to be calculated as the center to calculate the damage degree of the data point. The expression of the damage degree is:

[0016]

[0017] in, Indicates The degree of damage to the data point at a certain moment, Represents the difference between the maximum and minimum values ​​of the data in the sliding window. , Respectively represent The first sliding window constructed with the data point at the moment as the center and The slope of the tangent line at the data point, , Respectively represent The first sliding window constructed with the data point at the moment as the center and The photovoltaic parameters of the data points are is the number of data points in the sliding window.

[0018] Preferably, the method for calculating the damage degree of the data points on the state curve is:

[0019] The state curve is segmented into multiple time periods according to the preset time length, and a sliding window is constructed with the data point for which the damage degree needs to be calculated as the center to calculate the damage degree of the data point. The expression of the damage degree is:

[0020]

[0021] in, Indicates The degree of damage to the data point at a certain moment, represents the variance of the data in the sliding window, , Respectively represent The first sliding window constructed with the data point at the moment as the center and The slope of the tangent line at the data point, , Respectively represent The first sliding window constructed with the data point at the moment as the center and The photovoltaic parameter value of each data point, is the number of data points in the sliding window.

[0022] The effect is that the photovoltaic parameters at each moment can be accurately calculated through the above formula, which improves the accuracy of the photovoltaic parameters and facilitates the analysis of the acquired parameter data.

[0023] Preferably, the importance of a data point is calculated as follows:

[0024]

[0025] in, Indicates The importance of the data point at a certain moment, Indicates The mean of the difference in the degree of damage of the data points in the sliding window where the data points at the moment are located, Indicates the number of The mean of the difference in the degree of damage of the data points in the sliding window where the data point is located at the moment, Indicates The data point at the moment corresponds to the damage degree of the mth data in the sliding window. and Respectively represent the first The damage degree of the mth data in the sliding window corresponding to the data point at the moment, Indicates the number of data points in the sliding window.

[0026] Preferably, the importance of a data point is calculated as follows:

[0027]

[0028] in, Indicates The importance of the data point at a certain moment, Indicates The mean of the difference in the degree of damage of the data points in the sliding window where the data points at the moment are located, Indicates the number of The mean of the difference in the degree of damage of the data points in the sliding window where the data point is located at the moment, Indicates The data point at the moment corresponds to the damage degree of the mth data in the sliding window. and Respectively represent the first The damage degree of the mth data in the sliding window corresponding to the data point at the moment, Indicates the number of data points in the sliding window.

[0029] The effect is that the importance of data points can be accurately calculated through the above formula, which improves the accuracy of the accuracy, facilitates the identification and management of parameter data, and provides a basis for analyzing the operating status of the photovoltaic energy storage system.

[0030] Preferably, for continuous data points whose importance is less than or equal to a preset threshold, the mean of the same parameter data corresponding to each data point is calculated, and the mean of each parameter is stored separately.

[0031] The effect is that the acquired parameter data are stored separately according to their importance, and the parameter data with lower importance are stored lossily, which reduces the amount of data and further reduces the space required for storing data, making it easier to analyze the data.

[0032] Preferably, the method for calculating the mean of the same parameter data corresponding to each data point is: dividing the data points into segments according to a preset length, and calculating the mean of the same parameter in each segment.

[0033] The effect is that the data points are segmented according to the preset length, which improves the accuracy of the mean of each parameter and can intuitively reflect the changing trend of the data.

[0034] In a second aspect, a photovoltaic energy storage energy consumption monitoring system includes:

[0035] processor;

[0036] A memory stores computer instructions for safety early warning of photovoltaic power stations based on artificial intelligence. When the computer instructions are executed by the processor, the system executes the photovoltaic energy storage energy consumption monitoring method.

[0037] The present invention has the following technical effects:

[0038] By calculating the photovoltaic parameters of the data points and constructing the state curve, the importance of the data points is finally calculated. The parameters are stored according to the importance of the data points, which is convenient for identifying and classifying the acquired parameter data. The data with lower importance is stored by taking its mean value, which reduces the data storage volume and provides great convenience for data analysis. At the same time, according to the importance of the data, it is convenient to understand the operating status of the photovoltaic energy storage energy consumption system and to monitor the photovoltaic energy storage energy consumption system. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts.

[0040] Figure 1 The present invention is a method flow chart of a photovoltaic energy storage energy consumption monitoring method and system.

[0041] Figure 2 It is a structural block diagram of a photovoltaic energy storage energy consumption monitoring system of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0043] It should be understood that when the terms "first", "second", etc. are used in the claims, descriptions, and drawings of the present invention, they are only used to distinguish different objects, rather than to describe a specific order. The terms "include" and "comprise" used in the description and claims of the present invention indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their collections.

[0044] The embodiment of the present invention discloses a method for monitoring energy consumption of photovoltaic energy storage, such as Figure 1 As shown, it includes steps S1 to S5, which are specifically as follows:

[0045] S1: Obtain the parameters of the photovoltaic energy storage system, including the power generation efficiency, power generation power and temperature of the photovoltaic panels, the charging and discharging efficiency and temperature of the energy storage device, and the light intensity.

[0046] The power generation efficiency is the efficiency of the photovoltaic panel in converting light energy into electrical energy, the power generation is the electrical power output by the photovoltaic panel, the temperature is the average temperature of the surface of the photovoltaic panel, the charge and discharge efficiency of the energy storage device is the percentage of the discharge capacity of the energy storage device to the charge capacity under the charging and discharging conditions, the temperature of the energy storage device is the average temperature of the surface of the energy storage device, and the light intensity is the energy of visible light received per unit area of ​​the photovoltaic panel surface.

[0047] S2: At each moment, the photovoltaic parameters of the photovoltaic energy storage system are calculated, a state curve about the photovoltaic parameters and time is constructed, and the product of the photovoltaic parameters and the slope of the data point on the state curve is taken as the damage amount.

[0048] The calculation method of photovoltaic parameters is:

[0049]

[0050] in, Indicates The photovoltaic parameters corresponding to the moment, Indicates The power generation efficiency of the photovoltaic panel at a certain moment, Indicates The charge and discharge efficiency at each moment, Indicates The maximum value of the photovoltaic panel temperature and the energy storage device temperature at a certain moment, Indicates The power generated by the photovoltaic panel at the moment, Indicates The light intensity corresponding to the moment.

[0051] The power generation of photovoltaic panels is directly affected by the light intensity. Under good light conditions, the power generation is higher, while on cloudy days or at night, the power generation is lower. Under normal circumstances, the power generation and light intensity are positively correlated. Reflects the power generation capacity of photovoltaic panels.

[0052] The increase in temperature of the photovoltaic panel will reduce its power generation efficiency. The energy storage device will generate heat during the charging and discharging process. The increase in temperature will reduce its charging and discharging efficiency, affecting the efficiency of the energy storage device in storing and releasing electrical energy. It reflects the power generation and charging and discharging capabilities of the photovoltaic energy storage system. It reflects the working status of the photovoltaic energy storage system. The larger the value is, the better the system is in use.

[0053] The change of light intensity in a day is slow, steady and continuous, so the change of various parameters is continuous. The change is relatively gentle in normal state. When the system is abnormal or suddenly changed, the data will change suddenly, and the data characteristics generated by the abnormal change will not disappear instantly, but will last for a period of time. Therefore, the state curve is drawn for the photovoltaic parameters in chronological order. The construction method is as follows: the horizontal axis is time, the vertical axis is photovoltaic parameters, and the photovoltaic parameters corresponding to each moment are connected with a smooth curve. The slope of the state curve represents the rate of change of the parameters. The product of the photovoltaic parameters and the slope of the data point on the state curve is taken as the damage amount of the data point. The larger the damage amount, the greater the probability that the parameters at the same time as the data point are abnormal.

[0054] S3: Calculate the damage degree of the data point on the state curve. The damage degree of the data point is positively correlated with the cumulative sum of the damage amount differences of adjacent data points within a preset time period.

[0055] In one embodiment, the damage degree of a data point on the state curve is calculated as follows:

[0056] The state curve is segmented into multiple time periods according to the preset time length, and a sliding window is constructed with the data point for which the damage degree needs to be calculated as the center to calculate the damage degree of the data point. The expression of the damage degree is:

[0057] in, Indicates The degree of damage to the data point at a certain moment, Represents the difference between the maximum and minimum values ​​of the data in the sliding window. , Respectively represent The first sliding window constructed with the data point at the moment as the center and The slope of the tangent line at the data point, , Respectively represent The first sliding window constructed with the data point at the moment as the center and The photovoltaic parameters of each data point. In normal state, the changes are relatively slow. When an abnormality or sudden change occurs, the data will change suddenly. It reflects the growth of the damage of the data, thereby reflecting the growth trend of the damage state of the data point. The larger the value, the higher the possibility that the data point will be damaged, and the greater the probability of abnormality in the photovoltaic energy storage system.

[0058] For example, the state curve is segmented into multiple time periods according to one hour. Taking one of the time periods as an example, the slope of the curve corresponding to each data point in the time period is obtained, and then a 9×9 sliding window is established. The data point at the moment is taken as the center of the sliding window to calculate the damage degree of the data point.

[0059] In other embodiments, the expression of the damage degree is:

[0060]

[0061] in, Indicates The degree of damage to the data point at a certain moment, represents the variance of the data in the sliding window, , Respectively represent The first sliding window constructed with the data point at the moment as the center and The slope of the tangent line at the data point, , Respectively represent The first sliding window constructed with the data point at the moment as the center and The photovoltaic parameter value of each data point.

[0062] S4: Calculate the importance of data points.

[0063] In one embodiment, the importance of a data point is calculated as follows:

[0064]

[0065] in, Indicates The importance of the data point at a certain moment, Indicates The mean of the difference in the degree of damage of the data points in the sliding window where the data points at the moment are located, Indicates the number of The mean of the difference in the degree of damage of the data points in the sliding window where the data point is located at the moment, Indicates The data point at the moment corresponds to the damage degree of the mth data in the sliding window. and Respectively represent the first The damage degree of the mth data in the sliding window corresponding to the data point at the moment, Indicates the number of data points in the sliding window.

[0066] The larger the value of is, the greater the degree of abnormality or damage of the data point is, and the more important the parameter corresponding to the data point is. It reflects the difference in habitual rhythm from adjacent curves. The larger the value, the greater the degree of abnormality of the parameter, and the more important the data.

[0067] For example, Indicates the first time period of June 3 The mean of the difference in the degree of damage of the data points in the sliding window where the data points at the moment are located, then Indicates the first time period of No. 1 and No. 2. The mean of the difference in the degree of damage of the data points in the sliding window where the data point is located at a certain moment.

[0068] In other embodiments, the importance of a data point is calculated as follows:

[0069]

[0070] in, Indicates The importance of the data point at a certain moment, Indicates The mean of the difference in the degree of damage of the data points in the sliding window where the data points at the moment are located, Indicates the number of The mean of the difference in the degree of damage of the data points in the sliding window where the data point at the moment is located, Indicates The data point at the moment corresponds to the damage degree of the mth data in the sliding window. and Respectively represent the first The damage degree of the mth data in the sliding window corresponding to the data point at the moment, Represents the number of data points in the sliding window.

[0071] S5: In response to the importance being greater than a preset threshold, the parameters corresponding to the data point at the same moment are stored separately, and for continuous data points whose importance is less than or equal to the preset threshold, the mean of the same parameter data corresponding to each data point is calculated, and the mean of each parameter is stored separately. Specifically, the data points are segmented according to a preset length, and the mean of the same parameter in each segment is calculated.

[0072] By calculating the importance of each time data point, the parameters corresponding to the data points with an importance greater than the threshold are stored losslessly to facilitate data analysis. The parameters corresponding to the data points with an importance less than the threshold are calculated and stored, and then run-length encoding is compressed and stored in chronological order. In the case of data compression, the monitoring system can also realize accurate fault warning function, timely discover and diagnose system faults or abnormalities, and reduce system downtime or losses caused by undetected faults. The threshold is set according to experience based on actual conditions, for example, the threshold is 0.8.

[0073] For example, for the data point , , , , , , , , , , the threshold is 0.8, the data point The importance of is greater than the threshold, and the importance of the remaining data points is less than the threshold. The preset length of the data point is 3. , , The corresponding average power generation efficiency calculation , data points The corresponding power generation efficiency remains unchanged and is recorded as , , , The corresponding average power generation efficiency calculation , , , The corresponding average power generation efficiency calculation , and finally sort them in chronological order. , , , For storage, other parameters are stored in the same way as power generation efficiency.

[0074] The acquired parameter data are stored separately according to their importance. The parameter data with lower importance are stored lossily, which reduces the amount of data and further reduces the space required for storing data, making it easier to analyze the data. The parameter data with higher importance are stored losslessly, retaining the authenticity of the data, making it easier to monitor the photovoltaic energy storage system and understand the operating status of the photovoltaic energy storage system.

[0075] Figure 2The structural block diagram of a photovoltaic energy storage energy consumption monitoring system in this embodiment is schematically shown.

[0076] The present invention also provides a photovoltaic energy storage energy consumption monitoring system. Figure 2 As shown, the safety warning system includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a photovoltaic energy storage energy consumption monitoring method according to the present invention is implemented.

[0077] The safety warning system also includes other components familiar to those skilled in the art, such as a communication bus and a communication interface, whose settings and functions are known in the art and will not be described in detail here.

[0078] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus or device. For example, a computer-readable storage medium may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random-Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high-bandwidth memory HBM (High-Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc., or any other medium that can be used to store the required information and can be accessed by an application, a module, or both. Any such computer storage medium may be part of a device or accessible or connectable to a device. Any application or module described in the present invention may be implemented using computer-readable / executable instructions that may be stored or otherwise maintained by such a computer-readable medium.

[0079] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

[0080] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A photovoltaic energy storage energy consumption monitoring method, characterized in that: Includes steps: At each moment, the photovoltaic parameters of the photovoltaic energy storage system are calculated, a state curve of the photovoltaic parameters and time is constructed, and the product of the photovoltaic parameters and the slope of the data point on the state curve is taken as the amount of damage; Calculate the damage degree of the data point on the state curve, the damage degree of the data point is positively correlated with the cumulative sum of the damage amount differences of adjacent data points within a preset time period; Calculate the importance of the data points on the state curve. The calculation method of the importance of the data points is: in, Indicates The importance of the data point at a certain moment, Indicates The mean of the difference in the degree of damage of the data points in the sliding window where the data points at the moment are located, Indicates the number of The mean of the difference in the degree of damage of the data points in the sliding window where the data point is located at the moment, Indicates The data point at the moment corresponds to the damage degree of the mth data in the sliding window. and Respectively represent the first The damage degree of the mth data in the sliding window corresponding to the data point at the moment, Indicates the number of data points in the sliding window; In response to the importance being greater than a preset threshold, each parameter at the same moment corresponding to the data point is stored respectively, and for consecutive data points whose importance is less than or equal to the preset threshold, the mean of the same parameter data corresponding to each data point is calculated, and the mean of each parameter is stored respectively; The expression of photovoltaic parameters is: in, Indicates The photovoltaic parameters corresponding to the moment, Indicates The power generation efficiency of the photovoltaic panel at a certain moment, Indicates The charge and discharge efficiency at each moment, Indicates The maximum value of the photovoltaic panel temperature and the energy storage device temperature at a certain moment, Indicates The power generated by the photovoltaic panel at the moment, Indicates The light intensity corresponding to the moment, () is the normalization function.

2. A photovoltaic energy storage energy consumption monitoring method according to claim 1, characterized in that: The calculation method for the damage degree of the data point on the state curve is: The state curve is segmented into multiple time periods according to the preset time length, and a sliding window is constructed with the data point for which the damage degree needs to be calculated as the center to calculate the damage degree of the data point. The expression of the damage degree is: in, Indicates The degree of damage to the data point at a certain moment, Represents the difference between the maximum and minimum values ​​of the data in the sliding window. , Respectively represent The first sliding window constructed with the data point at the moment as the center and The slope of the tangent line at the data point, , Respectively represent The first sliding window constructed with the data point at the moment as the center and The photovoltaic parameters of the data points are is the number of data points in the sliding window.

3. A photovoltaic energy storage energy consumption monitoring method according to claim 1, characterized in that: The calculation method for the damage degree of the data point on the state curve is: The state curve is segmented into multiple time periods according to the preset time length, and a sliding window is constructed with the data point for which the damage degree needs to be calculated as the center to calculate the damage degree of the data point. The expression of the damage degree is: in, Indicates The degree of damage to the data point at a certain moment, represents the variance of the data in the sliding window, , Respectively represent The first sliding window constructed with the data point at the moment as the center and The slope of the tangent line at the data point, , Respectively represent The first sliding window constructed with the data point at the moment as the center and The photovoltaic parameter value of each data point, is the number of data points in the sliding window.

4. A photovoltaic energy storage energy consumption monitoring method according to claim 1, characterized in that: The importance of a data point can be calculated as follows: in, Indicates The importance of the data point at a certain moment, Indicates The mean of the difference in the degree of damage of the data points in the sliding window where the data points at the moment are located, Indicates the number of The mean of the difference in the degree of damage of the data points in the sliding window where the data point is located at the moment, Indicates The data point at the moment corresponds to the damage degree of the mth data in the sliding window. and Respectively represent the first The damage degree of the mth data in the sliding window corresponding to the data point at the moment, Indicates the number of data points in the sliding window.

5. A photovoltaic energy storage energy consumption monitoring method according to claim 1, characterized in that: The method for calculating the mean of the same parameter data corresponding to each data point is as follows: the data points are segmented according to a preset length, and the mean of the same parameter in each segment is calculated.

6. A photovoltaic energy storage energy consumption monitoring system, characterized in that: include: processor; A memory storing computer instructions for safety early warning of photovoltaic power stations based on artificial intelligence, wherein when the computer instructions are executed by the processor, the system executes a photovoltaic energy storage energy consumption monitoring method according to any one of claims 1 to 5.

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