CN117277435A - Health assessment method, system and device for photovoltaic inverter - Google Patents
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Abstract
The application discloses a health assessment method, system and device of a photovoltaic inverter, and relates to the field of photovoltaic power generation. In the scheme, historical data of the photovoltaic inverter in a preset time period is obtained; calculating health indexes according to historical data, and establishing an evaluation system model according to each health index, wherein the health indexes used for establishing the evaluation system model at least comprise two indexes of indexes used for representing fault conditions, indexes used for representing power generation conditions and indexes used for representing equipment performance conditions; and calculating the health score of the photovoltaic inverter according to each health index and the evaluation system model. Therefore, factors such as historical fault data and power generation data of the inverter are fully considered, and the health degree of the inverter can be accurately estimated through quantitative analysis; meanwhile, by establishing an evaluation system model, the health condition of the inverter can be evaluated more accurately according to the weight of each health index.
Description
Technical Field
The present disclosure relates to the field of photovoltaic power generation, and in particular, to a method, a system, and a device for health evaluation of a photovoltaic inverter.
Background
The health evaluation of a photovoltaic inverter is a process of evaluating the operating state, performance and reliability level of the inverter. The purpose of the evaluation method is to find potential faults and problems in time and to take corresponding maintenance measures, thereby improving the reliability and efficiency of the equipment.
At present, the evaluation methods of inverter health degree are mainly divided into qualitative and quantitative methods. The qualitative method is mainly judged and summarized by experience and professional knowledge of a power station operation and maintenance engineer. The quantitative method is to carry out weighted calculation on the set health degree parameters. However, these methods do not quantitatively analyze historical failure data, power generation data, and the like of the inverter. In addition, factors such as equipment aging degree and illumination intensity of different power stations can generate different weights on the influence of health parameters. Therefore, it is difficult to obtain an accurate health degree evaluation result using the above method.
Disclosure of Invention
The invention aims to provide a health evaluation method, a system and a device for a photovoltaic inverter, which fully consider factors such as historical fault data, power generation data and the like of the inverter, and can evaluate the health degree of the inverter more accurately through quantitative analysis; meanwhile, by establishing an evaluation system model, the health condition of the inverter can be evaluated more accurately according to the weight of each health index.
To solve the above technical problem, in a first aspect, the present application provides a health evaluation method of a photovoltaic inverter, including:
acquiring historical data of the photovoltaic inverter in a preset time period;
calculating a health index according to the historical data;
establishing an evaluation system model according to each health degree index, wherein the health degree index used for establishing the evaluation system model at least comprises two indexes of an index used for representing fault conditions, an index used for representing power generation conditions and an index used for representing equipment performance conditions;
and calculating the health score of the photovoltaic inverter according to each health index and the evaluation system model.
In one embodiment, when the health indicator comprises a failure-free rate, calculating the health indicator from the historical data comprises:
calculating the time of the fault or the duty ratio of the time of the normal operation to the planned operation time of the photovoltaic inverter according to the time of the fault or the time of the normal operation of the photovoltaic inverter in the preset time period and obtaining the fault-free rate according to the duty ratio.
In one embodiment, when the health indicator comprises a frequency of failures, calculating the health indicator from the historical data comprises:
and counting the frequency of the faults of the photovoltaic inverter in the preset time period according to the historical data.
In one embodiment, when the health indicator comprises a communication reliability, calculating the health indicator from the historical data comprises:
and calculating the communication reliability according to the number of days when the communication of the photovoltaic inverter is interrupted and the number of days when the photovoltaic inverter is scheduled to operate in the preset time period.
In one embodiment, the process of determining whether an interruption in the photovoltaic inverter communication has occurred comprises:
acquiring real-time data of the daily power generation amount and the active power of the inverter;
and if the acquired real-time data of a plurality of continuous data are the same non-zero value, judging that the communication of the photovoltaic inverter is interrupted.
In one embodiment, when the health indicator includes a power generation amount fitness, calculating the health indicator from the historical data includes:
fitting an initial linear regression model on the daily power generation amount and the daily accumulated irradiance according to the daily power generation amount and the daily accumulated irradiance in the preset time period;
Determining linear parameters of the initial linear regression model according to known pairs of a plurality of groups of daily power generation amount-daily accumulated irradiance data so as to obtain a target linear regression model according to the linear parameters and the initial linear regression model;
and verifying the fitting degree of the target linear regression model through the fitting goodness.
In one embodiment, when the health indicator comprises a deviation rate, calculating the health indicator from the historical data comprises:
acquiring the total power generation amount and the total assembly machine capacity of a photovoltaic inverter which normally works in a power station every day;
determining a total station average power generation hour number per day according to the total power generation amount and the total loader capacity per day;
and determining the deviation rate of each day according to the current estimated power generation hours of the photovoltaic inverter and the total station average power generation hours, and taking the deviation rate average value in the preset time period as the deviation rate of the photovoltaic inverter.
In one embodiment, when the health indicator comprises a power loss rate, calculating the health indicator from the historical data comprises:
calculating the electricity consumption rate according to the daily input-side electricity generation amount and the daily output-side electricity generation amount of the photovoltaic inverter;
And taking the average value of the electric quantity loss in the preset time period as the electric quantity loss rate of the photovoltaic inverter.
In one embodiment, when the health indicator comprises a temperature influence coefficient, calculating the health indicator from the historical data comprises:
calculating the temperature influence coefficient according to the average value of the temperature of the photovoltaic inverter and the temperature of equipment with the same model as the photovoltaic inverter in a power station every day;
and taking the average value of the temperature influence coefficients in a preset time period as the temperature influence data of the photovoltaic inverter.
In one embodiment, establishing an evaluation system model according to each health index, and calculating a health score of the photovoltaic inverter according to each health index and the evaluation system model comprises:
calculating a first weight corresponding to each health index through an entropy weight method;
and calculating the health degree score of the photovoltaic inverter according to the score of each health degree index and the corresponding first weight.
In one embodiment, establishing an evaluation system model according to each health index, and calculating a health score of the photovoltaic inverter according to each health index and the evaluation system model comprises:
Calculating a second weight corresponding to each health index through an analytic hierarchy process;
and calculating the health degree score of the photovoltaic inverter according to the score of each health degree index and the corresponding second weight.
In one embodiment, establishing an evaluation system model according to each health index, and calculating a health score of the photovoltaic inverter according to each health index and the evaluation system model comprises:
calculating a first weight corresponding to each health index through an entropy weight method;
calculating a second weight corresponding to each health index through an analytic hierarchy process;
calculating the final weight of each health index according to the first weight and the second weight corresponding to each health index;
and calculating the health degree score of the photovoltaic inverter according to the score of each health degree index and the corresponding final weight.
In one embodiment, calculating the final weight of each health indicator according to the first weight and the second weight corresponding to each health indicator includes:
calculating the final weight of each health index by using a preset formula according to the first weight and the second weight corresponding to each health index;
The preset formula is as follows:wherein W is j Is the final weight of the j-th health index, alpha j First weight, beta, of the jth health index j And the second weight of the j-th health index is that n is the number of the health indexes.
In a second aspect, the present application also provides a health assessment system for a photovoltaic inverter, comprising:
the data acquisition unit is used for acquiring historical data of the photovoltaic inverter in a preset time period;
an index calculation unit for calculating a health index according to the history data;
the model building unit is used for building an evaluation system model according to each health degree index, and the health degree index used for building the evaluation system model at least comprises two indexes of an index for representing a fault condition, an index for representing a power generation condition and an index for representing a performance condition of equipment;
and the evaluation unit is used for calculating the health degree score of the photovoltaic inverter according to each health degree index and the evaluation system model.
In a third aspect, the present application further provides a health evaluation device of a photovoltaic inverter, including:
a memory for storing a computer program;
a processor for implementing the steps of the method for health assessment of a photovoltaic inverter as described above when storing a computer program.
In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method for health assessment of a photovoltaic inverter as described above.
The application provides a health assessment method, system and device of a photovoltaic inverter, and relates to the field of photovoltaic power generation. In the scheme, historical data of the photovoltaic inverter in a preset time period is obtained; calculating health indexes according to historical data, building an evaluation system model according to each health index, wherein the health indexes used for building the evaluation system model at least comprise two indexes of indexes used for representing fault conditions, indexes used for representing power generation conditions and indexes used for representing equipment performance conditions, and calculating health scores of the photovoltaic inverter according to each health index and the evaluation system model. Therefore, factors such as historical fault data and power generation data of the inverter are fully considered, and the health degree of the inverter can be accurately estimated through quantitative analysis; meanwhile, by establishing an evaluation system model, the health condition of the inverter can be evaluated more accurately according to the weight of each health index.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following description will briefly explain the drawings needed in the prior art and embodiments, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for evaluating health of a photovoltaic inverter provided in the present application;
fig. 2 is a block diagram of a health evaluation system of a photovoltaic inverter provided in the present application;
fig. 3 is a block diagram of a health evaluation device of a photovoltaic inverter provided in the present application.
Detailed Description
The core of the application is to provide a health evaluation method, a system and a device of a photovoltaic inverter, which fully consider factors such as historical fault data, power generation data and the like of the inverter, and can evaluate the health degree of the inverter more accurately through quantitative analysis; meanwhile, by establishing an evaluation system model, the health condition of the inverter can be evaluated more accurately according to the weight of each health index.
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
In a first aspect, the present application provides a method for health assessment of a photovoltaic inverter, as shown in fig. 1, the method comprising:
s11: acquiring historical data of the photovoltaic inverter in a preset time period;
the step refers to obtaining historical data of the photovoltaic inverter in a preset time period. In the photovoltaic inverter health evaluation method, firstly, historical data of the photovoltaic inverter in a preset time period needs to be acquired. These historical data may include operational data of the inverter, fault data, power generation data, and the like.
In the process of acquiring the historical data, the operation state of the photovoltaic inverter, such as current, voltage, frequency, temperature and other information, can be periodically acquired through monitoring equipment or sensors. Meanwhile, it is also considered to acquire a fault record of the inverter, such as a fault code, a fault type, a time when a fault occurs, and the like. In addition, the power generation data of the photovoltaic inverter can be obtained, and the power generation data comprise daily, monthly or yearly power generation amount, power generation efficiency and other information of the inverter.
By acquiring historical data of the photovoltaic inverter, the running state, fault condition and power generation condition of the inverter can be comprehensively known. These data will serve as the basis for the subsequent calculation of health indicators and the creation of an assessment system model.
S12: calculating a health index according to the historical data;
in this step, it is necessary to calculate the health index from the history data of the photovoltaic inverter. The health index is a key parameter for evaluating the health condition of the inverter, and can provide evaluation of inverter fault conditions, power generation conditions and equipment performance. The health indicator may include an indicator for characterizing a fault condition, an indicator for characterizing a power generation condition, and an indicator for characterizing a device performance condition. Wherein, the index for representing the fault condition: these metrics are used to measure the fault condition of the inverter and are calculated by analyzing historical fault data of the inverter. For example, the frequency of occurrence of faults, the time required for fault repair, etc. may be considered. These indices may reflect the reliability and stability of the inverter. The index for representing the power generation condition: these indices are used to evaluate the power generation capability and efficiency of the inverter. These indices may be calculated by analyzing historical power generation data of the inverter. For example, the generated power output of the inverter, the generation efficiency, and the like can be considered. These indicators may reflect the power generation capability and performance of the inverter. Index for characterizing device performance conditions: these indices are used to evaluate the overall performance and operating condition of the inverter. The operating temperature of the inverter, the input voltage range, the power factor, etc. may be considered. These metrics may help identify problems or potential performance degradation of the inverter.
In this embodiment, more health indicators may be selected to evaluate the health condition of the inverter according to actual needs. By comprehensively considering the indexes, the health score of the inverter can be calculated, so that the health condition of the inverter can be estimated more accurately. The assessment system model may incorporate weights for individual health indicators to more accurately reflect the overall health of the inverter.
S13: establishing an evaluation system model according to each health index, wherein the health index used for establishing the evaluation system model at least comprises two of an index used for representing a fault condition, an index used for representing a power generation condition and an index used for representing a performance condition of equipment;
s14: and calculating the health score of the photovoltaic inverter according to each health index and the evaluation system model.
This step describes the step of assessing the health of the photovoltaic inverter, wherein an important step is to build an assessment system model. The model is constructed according to various health indexes and other related parameters or factors and is used for calculating the health score of the photovoltaic inverter. In building the assessment architecture model, the following factors may be considered: weight of health index: different health indicators may be of different importance to the health assessment of the photovoltaic inverter. Thus, when building an assessment system model, the weights of the individual health indicators need to be determined to reflect their relative importance. Correlation between health indicators: different health indicators may affect each other or there may be a certain correlation. Therefore, when building an assessment system model, it is necessary to consider the correlations between health indicators and how to take these correlations into account in the model. Mathematical method of evaluating a system model: in modeling the evaluation system, appropriate mathematical methods, such as weighted summation, weighted averaging, etc., may be selected to combine the individual health indicators to calculate the health score of the photovoltaic inverter. The mathematical method should be able to reasonably reflect the change and importance of each index.
The health index for establishing the evaluation system model at least comprises two indexes of an index for representing a fault condition, an index for representing a power generation condition and an index for representing a performance condition of equipment, and the health score of the inverter can be calculated by comprehensively considering the indexes, so that the health condition of the inverter can be evaluated more accurately. The assessment system model may incorporate weights for individual health indicators to more accurately reflect the overall health of the inverter.
By establishing an evaluation system model, the health score of the photovoltaic inverter can be calculated according to the weight of each health index and the numerical value of the index. The health score quantitatively reflects the overall health of the photovoltaic inverter and provides a comparable index for assessing and comparing health between different inverters.
In one embodiment, when the health indicator comprises a failure-free rate, calculating the health indicator from the historical data comprises:
calculating the duty ratio of the time of failure or the time of normal operation to the scheduled operation time of the photovoltaic inverter according to the time of failure or the time of normal operation of the photovoltaic inverter and the scheduled operation time of the photovoltaic inverter in a preset time period, and obtaining the failure-free rate according to the duty ratio.
The present embodiment describes a method for calculating a health index in an embodiment, which includes an index for indicating whether a photovoltaic inverter is faulty, i.e. a failure-free rate. Specifically, the failure-free rate index may be calculated by: first, it is necessary to acquire the time when the photovoltaic inverter fails or the time of normal operation within a preset period of time, and the planned operation time of the photovoltaic inverter. Wherein the time of occurrence of the failure and the time of normal operation are relative, specifically expressed as time of occurrence of the failure+time of normal operation=total time of planned operation. Next, according to the time of the failure or the time of the normal operation of the photovoltaic inverter within the preset period, the ratio of the time of the failure or the time of the normal operation of the photovoltaic inverter to the total time (planned operation time) may be calculated. This can be calculated by dividing the time of failure or normal operation by the planned operation time.
For example, if the preset time period is one month, the time during which the photovoltaic inverter fails is 5 days, the time of normal operation is 25 days, the total planned operation time is 30 days, and the failure time ratio is 5/30=1/6. Finally, the failure-free rate of the photovoltaic inverter can be calculated by multiplying the failure time ratio by 100%.
Note that, equipment failure time=failure end time-failure start time (unit:
h) Photovoltaic inverter planning run time: last 30 days (24 points up to the previous day, unit: h),
In summary, the present embodiment describes a method for calculating a failure-free index in an embodiment, which evaluates the health condition of a photovoltaic inverter by calculating the failure time ratio of the photovoltaic inverter in a preset period of time. Such a calculation method may be used to evaluate the health of the photovoltaic inverter based on historical data.
In one embodiment, when the health indicator comprises a frequency of failures, calculating the health indicator from the historical data comprises:
and counting the frequency of the faults of the photovoltaic inverter in a preset time period according to the historical data.
In this embodiment, when the health index includes failure frequency, the health index is calculated by the following steps: first, it is necessary to acquire historical data of the photovoltaic inverter over a preset period of time. Such data may include a record of the operation of the inverter, a record of parameters such as temperature, voltage and current, and a record of the time stamp of the failure of the inverter. And counting the frequency of the faults of the photovoltaic inverter in a preset time period according to the historical data. The number of occurrences of the fault may be determined by analyzing the recorded time stamps. And obtaining the fault condition index of the photovoltaic inverter through counting the fault frequency. This index may be used to measure the health of the inverter, i.e. the higher the frequency of faults, the lower the health of the inverter.
The health index in this embodiment may also include other indexes such as a power generation condition index and a device performance condition index. According to the indexes, an evaluation system model can be established, and the health degree indexes and the evaluation system model are combined to calculate the health degree score of the photovoltaic inverter.
By analyzing and evaluating the historical data of the photovoltaic inverter, the fault condition, the power generation condition and the performance condition of the equipment can be found in time, and scientific basis is provided for equipment maintenance and management. In addition, such health assessment methods may also provide a reference for device manufacturers and operators to improve and optimize device performance.
In one embodiment, when the health indicator comprises a communication reliability, calculating the health indicator from the historical data comprises:
and calculating the communication reliability according to the number of days when the photovoltaic inverter communication is interrupted and the number of days when the photovoltaic inverter is scheduled to operate in a preset time period.
The present embodiment describes the inclusion of the communication reliability in the health index of the photovoltaic inverter. The communication reliability is an index for evaluating the communication condition of the photovoltaic inverter, which reflects the interruption of communication during a preset period of time. The interruption of communication may be due to equipment failure, network problems, or other reasons.
In order to calculate the communication reliability, it is necessary to acquire historical data of the photovoltaic inverter within a preset period of time. The historical data may include daily communications conditions, i.e., whether the photovoltaic inverter communications are operating properly. The communication reliability can be calculated by counting the number of days when the photovoltaic inverter communication is interrupted and the number of days when the photovoltaic inverter is scheduled to operate.
The calculation formula of the communication reliability can be as follows:
communication reliability= (number of days the photovoltaic inverter is scheduled to operate-number of days the photovoltaic inverter communication is interrupted)/number of days the photovoltaic inverter is scheduled to operate ×100%. Wherein, the photovoltaic inverter plans the day of operation: last 30 days (24 points up to the previous day, units: days); days when photovoltaic inverter communication was interrupted: whenever a communication interruption occurs on the same day, the time and the number of times of the communication interruption are accumulated for 1 day.
By calculating the communication reliability, the quality of the communication condition of the photovoltaic inverter can be known. The higher the communication reliability, the better the communication condition, and the higher the health of the photovoltaic inverter. The lower the communication reliability is, the worse the communication condition is, and the health degree of the photovoltaic inverter is relatively lower.
In one embodiment, the process of determining whether an interruption in the photovoltaic inverter communication has occurred comprises:
acquiring real-time data of the daily power generation amount and the active power of the inverter;
and if the acquired real-time data of a plurality of continuous data are the same non-zero value, judging that the communication of the photovoltaic inverter is interrupted.
The present embodiment describes a procedure for determining whether interruption of the photovoltaic inverter communication has occurred. An inverter is a device for converting direct current into alternating current, which is commonly used in solar photovoltaic power generation systems. For inverters, both daily power generation and active power are very important indicators. This process includes the steps of: real-time data of the daily power generation amount and the active power of the inverter are obtained. Real-time data is acquired several consecutive times and checked for identical non-zero values. At this step, the system will acquire real-time data of the inverter, for example, data collected every five minutes or hours. The system will then check whether the data acquired several consecutive times (e.g. 6 times) is the same non-zero value. This means that if the data acquired several times in succession are all the same non-zero value, it can be judged that the communication of the photovoltaic inverter is interrupted.
The daily power generation amount and the active power of the photovoltaic inverter at night are zero, so that the continuous same non-zero value is used as a standard for judging whether communication is interrupted.
By the judging mode, whether the communication of the photovoltaic inverter is interrupted or not can be timely detected. If the real-time data is unchanged for several consecutive times, it can be inferred that the inverter cannot normally transmit the data, and that there is a problem of communication interruption. This may be one of the important indicators of health assessment to help determine the status and performance of the inverter.
In one embodiment, when the health indicator includes a power generation amount fitness, calculating the health indicator from the historical data includes:
fitting an initial linear regression model about the daily power generation amount and the daily accumulated irradiance according to the daily power generation amount and the daily accumulated irradiance in a preset time period;
determining linear parameters of an initial linear regression model according to known pairs of a plurality of groups of daily power generation amount-daily accumulated irradiance data so as to obtain a target linear regression model according to the linear parameters and the initial linear regression model;
and verifying the fitting degree of the target linear regression model through the fitting goodness.
The present embodiment describes a health index in an embodiment, including a power generation amount fitness. In this embodiment, the method for calculating the health index from the history data is as follows: first, an initial linear regression model is constructed based on the daily power generation and the daily cumulative irradiance data over a predetermined period of time (e.g., one month), and the model is used to fit the relationship between the daily power generation and the daily cumulative irradiance. Then, linear parameters of the initial linear regression model are determined from the known sets of daily power generation-daily cumulative irradiance data. These parameters can be obtained by fitting known data points so that the initial linear regression model more accurately describes the relationship between daily power generation and daily cumulative irradiance. Next, a target linear regression model is obtained using the determined linear parameters and the initial linear regression model. The model can more accurately predict the relationship between the generated energy and irradiance. And finally, verifying the fitting degree of the target linear regression model through the fitting goodness. The goodness of fit is used to evaluate the degree of fit between the target linear regression model and the real data, and the value ranges from 0 to 1, and the closer the value is to 1, the better the degree of fit between the model and the real data is.
Such as: the initial linear regression model obtained by performing linear fitting on the daily power generation amount and the daily accumulated irradiance of the inverter for 30 days is: y=f (x, b1, b2, …, bn), where x is the daily cumulative irradiance, y is the daily power generation, b1-bn is a linear parameter, and the cumulative irradiance and daily power generation data (x 1, y 1), (x 2, y 2), …, (xm, ym) are obtained over 60 days; the optimal estimated value of the parameter b is sought through m groups of data, and then the target linear regression model is obtained. Then, verifying whether a target linear regression model established by the power station is suitable or not through the fitting goodness; the fitting goodness is the fitting degree of the regression equation to the observed value, the statistic of the measured fitting goodness is the judgment coefficient R2, the value range of R2 is [0,1], and the closer the value of R2 is to 1, the better the fitting degree of the regression equation to the observed value is; conversely, the closer the value of R2 is to 0, the worse the fitting of the regression equation to the observed value.
Fitting goodness formula:wherein, RSS: the sum of squares of the deviations of the actual values and the predicted values is represented, and the unknown variation degree of the variable is represented; TSS: the sum of squares of the deviations of the actual values from the desired values is expressed and represents the total extent of variation of the variable. />Representing y i Predicted value of +.>Representing y i Is a mean value of (c).
Through the steps, the generated energy fitting degree in the health degree index can be calculated according to the historical data. The index can be used for evaluating the power generation condition of the photovoltaic inverter, and further, the health score of the photovoltaic inverter is calculated through an evaluation system model. And the generated energy fitting goodness index is introduced to indirectly reflect the generated energy performance and the health level of the inverter. The higher the generated energy fitting goodness is, the better the fitted degree of the generated energy and irradiance of the inverter is, the stable the generated condition of the inverter is, and the generated level is high; and the lower the generated energy fitting goodness is, the worse the generated energy fitting degree of the inverter and irradiance is, and the generated energy condition of the inverter is unstable.
In one embodiment, when the health indicator comprises a deviation rate, calculating the health indicator from the historical data comprises:
acquiring the total power generation amount and the total assembly machine capacity of a photovoltaic inverter which normally works in a power station every day;
determining the average power generation hour number of the total station per day according to the total power generation amount per day and the capacity of the total assembly machine;
and determining the deviation rate of each day according to the current estimated power generation hours of the photovoltaic inverter and the total station average power generation hours, and taking the deviation rate average value in the preset time period as the deviation rate of the photovoltaic inverter.
The present embodiment is described in detail for the case where the health index includes the deviation rate. In such an embodiment, the step of calculating the health indicator from the historical data is as follows: 1. and acquiring the total power generation amount and the total capacity of the assembly machine of the photovoltaic inverter which normally works in the power station every day. In this step, the total power generation amount and the total capacity of the photovoltaic inverter that normally operates in the power station every day are obtained based on the history data. The total power generation amount refers to the total power generation amount of the photovoltaic inverter in the day, and the total capacity of the assembly machine refers to the total assembly capacity of the photovoltaic inverter. 2. And determining the average power generation hours of the total station every day according to the total power generation amount and the total capacity of the assembly machine every day. In this step, the total station average power generation hours per day is calculated from the total power generation amount per day and the total loader capacity. The average power generation hours at the total station refers to the number of hours that each inverter can operate during the day. 3. The daily deviation rate is determined according to the current estimated power generation hours of the photovoltaic inverter and the average power generation hours of the total station. In this step, the deviation rate per day is calculated from the current estimated number of power generation hours of the photovoltaic inverter per day and the total station average number of power generation hours. The deviation ratio refers to the difference between the actual power generation time of the photovoltaic inverter and the average power generation time of the total station. 4. And taking the deviation rate average value in the preset time period as the deviation rate of the photovoltaic inverter.
For example, total station average power generation hours = total power generation of a normally operating photovoltaic inverter/total capacity of a normally operating photovoltaic inverter 100%. Deviation rate per day= (number of power generation hours of photovoltaic inverter-number of average power generation hours of total station)/number of average power generation hours of total station is 100%.
In this step, the deviation rate of the photovoltaic inverter is obtained by calculating the average value of the deviation rates of each day in a preset period of time. This deviation rate can be used to measure the difference in the power generation performance of the photovoltaic inverter from the overall average level.
In one embodiment, when the health indicator comprises a power loss rate, calculating the health indicator from the historical data comprises:
calculating the electricity consumption rate according to the daily input side electricity generation amount and the daily output side electricity generation amount of the photovoltaic inverter;
and taking the average value of the electric quantity loss in the preset time period as the electric quantity loss rate of the photovoltaic inverter.
The present embodiment describes a method of considering the power loss rate in the health assessment. Specifically, the method calculates the electricity consumption rate by using the daily input side electricity generation amount and the daily output side electricity generation amount of the photovoltaic inverter, and takes the average value of the electricity consumption amounts in a preset time period as the electricity consumption rate of the photovoltaic inverter.
First, the electricity loss rate is calculated using the input-side electricity generation amount and the output-side electricity generation amount of the photovoltaic inverter per day in the history data. The power loss rate is obtained by calculating the ratio between the output-side power generation amount and the input-side power generation amount. This can be done by simply dividing the output-side power generation amount by the input-side power generation amount. For example, if one photovoltaic inverter generates 100kWh for the input side power generation and 90kWh for the output side power generation in one day, the power loss rate is 90% (90/100). Next, a mean value of the amount of power loss in the preset period of time is calculated. According to the historical data, the power loss rate of the photovoltaic inverter in a preset time period per day can be obtained. And averaging the electric quantity loss values to obtain the electric quantity loss rate of the photovoltaic inverter.
The method has the advantage that the health of the photovoltaic inverter can be more comprehensively evaluated by taking the electricity loss rate into consideration. The power loss rate reflects the efficiency of the photovoltaic inverter in converting solar energy on the input side into electrical energy on the output side. If the power loss rate is high, the photovoltaic inverter has a certain performance problem or fault. Therefore, by including the power loss rate index, the health condition of the photovoltaic inverter can be more accurately estimated, and potential problems can be timely found.
In one embodiment, when the health indicator comprises a temperature influence coefficient, calculating the health indicator from the historical data comprises:
calculating a temperature influence coefficient according to the average value of the temperature of the photovoltaic inverter every day and the temperature of equipment with the same model as the photovoltaic inverter in the power station;
and taking the average value of the temperature influence coefficients in the preset time period as temperature influence data of the photovoltaic inverter.
This embodiment describes a method of using temperature influence coefficients in health assessment. The method uses the temperature data of the photovoltaic inverter and the temperature data of the same type of equipment in the power station to obtain the temperature influence coefficient by calculating the average value of the temperature data and the temperature data. The coefficient may be used to evaluate the extent to which the photovoltaic inverter is affected by temperature over a preset period of time. Specifically, the method comprises the following steps: 1. and acquiring historical data of the photovoltaic inverter in a preset time period. 2. And calculating the average value of the daily temperature of the photovoltaic inverter and the temperature of the same type of equipment in the power station. 3. The calculated mean value is used as the temperature influence coefficient. 4. And taking the average value of the temperature influence coefficients in the preset time period as temperature influence data.
By this means, the temperature influence can be incorporated into the health assessment of the photovoltaic inverter. The temperature influence coefficient provides performance indexes of the photovoltaic inverter under different temperature conditions, and the calculated temperature influence data can be used for quantifying the influence degree of the photovoltaic inverter on the temperature so as to evaluate the health condition of the photovoltaic inverter.
It is noted that this step requires calculation in combination with other health indicators and assessment system models.
In one embodiment, establishing an evaluation system model according to each health index, and calculating a health score of the photovoltaic inverter according to each health index and the evaluation system model comprises:
calculating a first weight corresponding to each health index through an entropy weight method;
and calculating the health score of the photovoltaic inverter according to the scores of the health indexes and the corresponding first weights.
In this embodiment, the entropy weighting method is used to calculate the first weights corresponding to the health indexes. The entropy weight method is a multi-index weight determining method that can determine weights of indexes according to their differences and correlations. The first weight calculated by the entropy weight method will be used for the subsequent health score calculation. And finally, calculating the health degree score of the photovoltaic inverter according to the score of each health degree index and the corresponding first weight. Specifically, the scores of the respective health indicators may be multiplied by their corresponding first weights and then summed to obtain the health score of the photovoltaic inverter.
Specifically, the step of determining the weight of each index by using the entropy weight method is described as follows:
(1) Firstly, carrying out homodromous and dimensionless treatment on each index data, and supposing that m health indexes are given: x'. 1 ,X′ 2 ,X′ 3 ...X′ m ；
(2) Standardized treatment is carried out on each health index, X i ＝{X′ 1 ,X′ 2 ,X′ 3 ...X′ m }；
(3) The normalized values of the health index data are: x is X 1 ,X 2 ,X 3 ...X m ；
(4) Normalization processing is carried out on each index to obtain:
wherein X is ij The ith sample value of the jth health index is the number of samples, and n is the number of samples, namely n photovoltaic inverters in the power station.
(5) Calculating the proportion p of the ith sample value to the health index under the jth health index ij ：
(6) Calculating the entropy value e of the j-th health index j ：
Wherein,so satisfy e j ≥0；
(7) Calculating weight beta of each health index by entropy weight method j ：
In summary, the present embodiment provides a specific embodiment of a photovoltaic inverter health assessment method. The embodiment objectively evaluates the health of the photovoltaic inverter by establishing an evaluation system model and calculating weights by using an entropy weight method. This method can provide a useful reference for maintenance and management of the photovoltaic inverter.
In one embodiment, establishing an evaluation system model according to each health index, and calculating a health score of the photovoltaic inverter according to each health index and the evaluation system model comprises:
Calculating a second weight corresponding to each health index through an analytic hierarchy process;
and calculating the health score of the photovoltaic inverter according to the scores of the health indexes and the corresponding second weights.
In this embodiment, an evaluation system model is built according to each health index, a second weight corresponding to each health index is calculated by using a hierarchical analysis method, and then a health score of the photovoltaic inverter is calculated according to the score of each health index and the corresponding second weight. The analytic hierarchy process is a multi-factor weight calculation method, and multiple factors are compared and ordered by constructing a judgment matrix, so that weight values of the factors are obtained. Here, the importance degree of each health index with respect to other indexes can be determined by a hierarchical analysis method. Once the second weight value for each health indicator is obtained, a health score for the photovoltaic inverter may be calculated from the score for each indicator and the corresponding weight. The calculation method can adopt a mathematical model, a formula or an algorithm for calculation.
Specifically, the second weight is calculated using layer analysis as follows:
(1) The photovoltaic power station operation and maintenance engineer is adopted to carry out qualitative analysis on 7 health indexes of the inverter health and determine corresponding weights:
(2) The judgment matrix and the relevant definition of each health index in the inverter health evaluation system are as follows:
(3) Judgment matrix value and corresponding meaning of inverter health evaluation system:
| scale with a scale bar | Meaning of |
| 1 | Representing that the two factors are of equal importance in comparison |
| 3 | Representing that one factor is slightly more important than the other than two factors |
| 5 | Representing that one factor is significantly more important than the other than the two factors |
| 7 | Representing that one factor is more important than the other than two factors |
| 9 | Representing that one factor is extremely important than the other factor in comparison with two factors |
| 2、4、6、8 | Median of the above-mentioned adjacency judgments |
| Reciprocal count | If the A and B ratio is 3, the B and A ratio is 1/3 |
Different n values and their corresponding RI values (random consistency check):
| n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
| RI | 0 | 0 | 0.58 | 0.90 | 1.12 | 1.24 | 1.32 | 1.41 | 1.45 | 1.49 | 1.51 |
(4) After RI consistency test, further solving the feature vector of the maximum feature value and normalizing to obtain a second weight alpha of each health index j 。
In summary, in this embodiment, an analytic hierarchy process is used to calculate the weight of each health indicator, and calculate the health score of the photovoltaic inverter according to the weight and the indicator score. The method can further comprehensively consider the importance of different indexes, so that the health condition of the photovoltaic inverter can be estimated more accurately.
In one embodiment, establishing an evaluation system model according to each health index, and calculating a health score of the photovoltaic inverter according to each health index and the evaluation system model comprises:
calculating a first weight corresponding to each health index through an entropy weight method;
calculating a second weight corresponding to each health index through an analytic hierarchy process;
calculating the final weight of each health index according to the first weight and the second weight corresponding to each health index;
and calculating the health score of the photovoltaic inverter according to the scores of the health indexes and the corresponding final weights.
Specifically, the establishment of the evaluation system model and the calculation of the health score of the photovoltaic inverter in the present embodiment include the following steps: calculating a first weight corresponding to each health index through an entropy weight method: the entropy weight method is a method for determining each index weight by using information entropy. The larger the value of entropy, the more the corresponding index information amount, and the larger the weight. By calculating the entropy of the individual health indicators, the relative importance between them can be determined. Calculating a second weight corresponding to each health index through an analytic hierarchy process: the analytic hierarchy process is one method of solving complex decision problem, and it decomposes the problem layer by layer to determine the weight between the factors through judgment and comparison. Here, an analytic hierarchy process is used to determine the relative weights between the individual health indicators. Calculating the final weight of each health index according to the first weight and the second weight corresponding to each health index: and comprehensively calculating the first weight and the second weight to obtain the final weight of each health index. This allows for the relative importance of the different indicators and the degree of correlation with each other. Calculating the health score of the photovoltaic inverter according to the scores of the health indexes and the corresponding final weights: and multiplying the final weight by the score of each health index, and then summing to obtain the health score of the photovoltaic inverter.
In one embodiment, calculating the final weight of each health indicator according to the first weight and the second weight corresponding to each health indicator includes:
calculating the final weight of each health index by using a preset formula according to the first weight and the second weight corresponding to each health index;
the preset formula is:wherein W is j Is the final weight of the j-th health index, alpha j First weight, beta, of the jth health index j And n is the number of the health indexes, and is the second weight of the j-th health index.
Compared with the method for determining the weight by using only an entropy method or an analytic hierarchy process, the method for comprehensively determining the final weight by using the entropy method and the analytic hierarchy process is as follows: comprehensively considering the information quantity and the relative importance: the entropy method can measure the information content of the index, and the analytic hierarchy process can judge and compare the relative importance of each factor. The two methods are comprehensively used, so that the relation and importance among indexes can be more comprehensively considered, and the weight determination is more accurate and reasonable. Consider the degree of association between the metrics: both entropy and analytic hierarchy processes can take into account the degree of association between the indices. The entropy method measures the information amount by calculating the entropy of the index, and the analytic hierarchy process determines the importance of each factor by judgment and comparison. The two methods can be used comprehensively to better reflect the association degree between indexes, so that the weight determination is more scientific and reliable.
In summary, compared with the method of determining the weight by only using the entropy method or the analytic hierarchy process, the method of determining the final weight by using the entropy method and the analytic hierarchy process can more comprehensively consider the relation and the importance among the indexes, better reflect the association degree among the indexes, and enable the determination of the weight to be more accurate, reasonable, scientific and reliable, so that the evaluation result is more reliable when the final weight is used for evaluating the health degree of the photovoltaic inverter.
In a second aspect, the present application further provides a health evaluation system of a photovoltaic inverter, as shown in fig. 2, the system including:
a data acquisition unit 21 for acquiring historical data of the photovoltaic inverter in a preset time period;
an index calculation unit 22 for calculating a health index from the history data;
a model building unit 23, configured to build an evaluation system model according to each health degree index, where the health degree index used to build the evaluation system model at least includes two indexes of an index for characterizing a fault condition, an index for characterizing a power generation condition, and an index for characterizing a performance condition of the device;
and the evaluation unit 24 is used for calculating the health score of the photovoltaic inverter according to each health index and the evaluation system model.
For the description of the health evaluation system of the photovoltaic inverter, refer to the above embodiments, and the description is omitted herein.
In a third aspect, the present application further provides a health evaluation device of a photovoltaic inverter, as shown in fig. 3, the device includes:
a memory 31 for storing a computer program;
the processor 32 is configured to implement the steps of the method for health assessment of a photovoltaic inverter as described above when storing a computer program.
For the description of the health evaluation device of the photovoltaic inverter, refer to the above embodiments, and the description is omitted herein.
In a fourth aspect, the present application further provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of a method for health assessment of a photovoltaic inverter as described above. For the description of the computer-readable storage medium, refer to the above embodiments, and the description is omitted herein.
It should also be noted that in this specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (16)
1. A method for health assessment of a photovoltaic inverter, comprising:
acquiring historical data of the photovoltaic inverter in a preset time period;
calculating a health index according to the historical data;
establishing an evaluation system model according to each health degree index, wherein the health degree index used for establishing the evaluation system model at least comprises two indexes of an index used for representing fault conditions, an index used for representing power generation conditions and an index used for representing equipment performance conditions;
and calculating the health score of the photovoltaic inverter according to each health index and the evaluation system model.
2. The method of claim 1, wherein when the health indicator comprises a failure-free rate, calculating the health indicator from the historical data comprises:
calculating the time of the fault or the duty ratio of the time of the normal operation to the planned operation time of the photovoltaic inverter according to the time of the fault or the time of the normal operation of the photovoltaic inverter in the preset time period and obtaining the fault-free rate according to the duty ratio.
3. The method of claim 1, wherein when the health indicator comprises a frequency of failures, calculating the health indicator from the historical data comprises:
and counting the frequency of the faults of the photovoltaic inverter in the preset time period according to the historical data.
4. The method of claim 1, wherein when the health indicator comprises a communication reliability, calculating the health indicator from the historical data comprises:
and calculating the communication reliability according to the number of days when the communication of the photovoltaic inverter is interrupted and the number of days when the photovoltaic inverter is scheduled to operate in the preset time period.
5. The method of claim 4, wherein determining whether an interruption in the photovoltaic inverter communication occurred comprises:
acquiring real-time data of the daily power generation amount and the active power of the inverter;
and if the acquired real-time data of a plurality of continuous data are the same non-zero value, judging that the communication of the photovoltaic inverter is interrupted.
6. The method of claim 1, wherein when the health indicator comprises a power generation amount fitness, calculating a health indicator from the historical data comprises:
fitting an initial linear regression model on the daily power generation amount and the daily accumulated irradiance according to the daily power generation amount and the daily accumulated irradiance in the preset time period;
determining linear parameters of the initial linear regression model according to known pairs of a plurality of groups of daily power generation amount-daily accumulated irradiance data so as to obtain a target linear regression model according to the linear parameters and the initial linear regression model;
and verifying the fitting degree of the target linear regression model through the fitting goodness.
7. The method of claim 1, wherein when the health indicator comprises a deviation rate, calculating a health indicator from the historical data comprises:
Acquiring the total power generation amount and the total assembly machine capacity of a photovoltaic inverter which normally works in a power station every day;
determining a total station average power generation hour number per day according to the total power generation amount and the total loader capacity per day;
and determining the deviation rate of each day according to the current estimated power generation hours of the photovoltaic inverter and the total station average power generation hours, and taking the deviation rate average value in the preset time period as the deviation rate of the photovoltaic inverter.
8. The method of claim 1, wherein when the health indicator comprises a power loss rate, calculating the health indicator from the historical data comprises:
calculating the electricity consumption rate according to the daily input-side electricity generation amount and the daily output-side electricity generation amount of the photovoltaic inverter;
and taking the average value of the electric quantity loss in the preset time period as the electric quantity loss rate of the photovoltaic inverter.
9. The method of claim 1, wherein when the health indicator comprises a temperature influence coefficient, calculating a health indicator from the historical data comprises:
calculating the temperature influence coefficient according to the average value of the temperature of the photovoltaic inverter and the temperature of equipment with the same model as the photovoltaic inverter in a power station every day;
And taking the average value of the temperature influence coefficients in a preset time period as the temperature influence data of the photovoltaic inverter.
10. The method of any one of claims 1-9, wherein establishing an evaluation system model from each of the health indicators, and calculating a health score for the photovoltaic inverter from each of the health indicators and the evaluation system model, comprises:
calculating a first weight corresponding to each health index through an entropy weight method;
and calculating the health degree score of the photovoltaic inverter according to the score of each health degree index and the corresponding first weight.
11. The method of any one of claims 1-9, wherein establishing an evaluation system model from each of the health indicators, and calculating a health score for the photovoltaic inverter from each of the health indicators and the evaluation system model, comprises:
calculating a second weight corresponding to each health index through an analytic hierarchy process;
and calculating the health degree score of the photovoltaic inverter according to the score of each health degree index and the corresponding second weight.
12. The method of any one of claims 1-9, wherein establishing an evaluation system model from each of the health indicators, and calculating a health score for the photovoltaic inverter from each of the health indicators and the evaluation system model, comprises:
Calculating a first weight corresponding to each health index through an entropy weight method;
calculating a second weight corresponding to each health index through an analytic hierarchy process;
calculating the final weight of each health index according to the first weight and the second weight corresponding to each health index;
and calculating the health degree score of the photovoltaic inverter according to the score of each health degree index and the corresponding final weight.
13. The method of claim 12, wherein calculating a final weight for each of the health indicators based on the first weight and the second weight for each of the health indicators comprises:
calculating the final weight of each health index by using a preset formula according to the first weight and the second weight corresponding to each health index;
the preset formula is as follows:wherein W is j Is the final weight of the j-th health index, alpha j First weight, beta, of the jth health index j And the second weight of the j-th health index is that n is the number of the health indexes.
14. A health assessment system for a photovoltaic inverter, comprising:
The data acquisition unit is used for acquiring historical data of the photovoltaic inverter in a preset time period;
an index calculation unit for calculating a health index according to the history data;
the model building unit is used for building an evaluation system model according to each health degree index, and the health degree index used for building the evaluation system model at least comprises two indexes of an index for representing a fault condition, an index for representing a power generation condition and an index for representing a performance condition of equipment;
and the evaluation unit is used for calculating the health degree score of the photovoltaic inverter according to each health degree index and the evaluation system model.
15. A health assessment device for a photovoltaic inverter, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method for health assessment of a photovoltaic inverter according to any one of claims 1-13 when storing a computer program.
16. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the method for health assessment of a photovoltaic inverter according to any of claims 1-13.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117833824A (en) * | 2023-12-28 | 2024-04-05 | 北京东华博泰科技有限公司 | Performance analysis method, device and equipment of photovoltaic inverter and storage medium |
| CN118396194A (en) * | 2024-06-27 | 2024-07-26 | 浙江正泰智维能源服务有限公司 | Optimization judgment method, device and equipment of low-efficiency inverter and storage medium |
| CN118427732A (en) * | 2024-07-05 | 2024-08-02 | 浙江正泰智维能源服务有限公司 | Power station inverter state judging method and device, electronic equipment and medium |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117833824A (en) * | 2023-12-28 | 2024-04-05 | 北京东华博泰科技有限公司 | Performance analysis method, device and equipment of photovoltaic inverter and storage medium |
| CN118396194A (en) * | 2024-06-27 | 2024-07-26 | 浙江正泰智维能源服务有限公司 | Optimization judgment method, device and equipment of low-efficiency inverter and storage medium |
| CN118427732A (en) * | 2024-07-05 | 2024-08-02 | 浙江正泰智维能源服务有限公司 | Power station inverter state judging method and device, electronic equipment and medium |
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