CN114900124A - Photovoltaic power generation detection system and detection method thereof - Google Patents
Photovoltaic power generation detection system and detection method thereof Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
- H02S50/00—Monitoring or testing of PV systems, e.g. load balancing or fault identification
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/10—Devices for predicting weather conditions
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
Abstract
The application relates to a photovoltaic power generation detection method, which comprises the following steps: forming a power generation reference database by weather conditions, orientation postures of the photovoltaic module array and power generation data within a plurality of years; analyzing the weather conditions and the power generation data to obtain a plurality of groups of photovoltaic module array orientation gestures with better power generation capacity, and forming an orientation gesture set; acquiring a weather forecast on the test day, and matching the weather condition with a power generation reference database to obtain predicted power generation data and reference power generation data; acquiring and recording the actual weather conditions of the test day, and enabling the photovoltaic module arrays to generate power according to different postures in the orientation posture set to obtain the actual power generation data of each group of photovoltaic module arrays; and comparing the actual power generation data, the predicted power generation data and the reference power generation data to obtain an actual deviation value and the maximum power generation data which are used as the next predicted power generation amount and the orientation posture of the optimal photovoltaic module array. The method has the effect of predicting the power generation capacity of the photovoltaic module.
Description
Technical Field
The application relates to the field of power generation systems, in particular to a photovoltaic power generation detection system and a detection method thereof.
Background
The solar energy is used as a new energy with high efficiency and no pollution, has unique advantages and great development and utilization potential, and can keep the harmony and coordinated development between human and nature by fully utilizing the solar energy. Early human use of solar energy was primarily light and heat. The rise of photovoltaic power generation technology opens up a wide technology for the application of solar energy, and since the 90 s, the development of solar photovoltaic power generation is widely applied to aerospace, communication, traffic, the electricity consumption of residents in remote areas and the like.
In actual production, a plurality of photovoltaic modules are usually assembled into a photovoltaic module array, and the plurality of photovoltaic modules are used for generating power at the same time, so that the power generation amount of photovoltaic power generation is improved, and the use requirements of users are met.
However, since the photovoltaic module converts light energy into electric energy, in the conversion process, there are many external factors that affect the generated power of the photovoltaic module itself, such as ambient temperature conditions, orientation posture factors of the photovoltaic module array, and the like, and the power generation states at different times are different along with the change of the solar azimuth in one day. Therefore, it is difficult to maintain stable data of the generated power of the photovoltaic module, and it is difficult to accurately estimate the amount of generated power.
Disclosure of Invention
The invention aims to provide a photovoltaic power generation detection method which has the characteristic of accurately budgeting the generated energy of a photovoltaic module.
The above object of the present invention is achieved by the following technical solutions:
a method of photovoltaic power generation detection, the method comprising:
recording weather conditions, orientation postures of the photovoltaic module array and corresponding power generation data in a plurality of years to form a power generation reference database, wherein the weather conditions comprise weather temperature information, cloudy and sunny condition information and illumination intensity;
analyzing the weather conditions and the power generation data in the power generation reference database, obtaining orientation postures of a plurality of groups of photovoltaic module arrays with better power generation capacity under corresponding weather conditions under different weather conditions, and forming orientation posture sets of the plurality of groups of photovoltaic module arrays;
acquiring weather forecast of weather conditions on the test day, and respectively matching the weather conditions on the test day with past weather conditions in a power generation reference database to obtain predicted power generation data and reference power generation data;
acquiring and recording the actual weather condition of the test day, and enabling the plurality of photovoltaic module arrays to generate power according to different postures in the orientation posture set respectively to obtain the actual power generation data of each group of photovoltaic module arrays;
and comparing actual power generation data, predicted power generation data and reference power generation data among the multiple groups of photovoltaic module arrays to obtain actual deviation values, comparing the actual deviation values with a preset defined threshold value to obtain maximum power generation data serving as the next generation prediction of the generated energy of the photovoltaic module arrays under similar weather conditions and the orientation postures of the corresponding optimal photovoltaic module arrays.
By adopting the technical scheme, the past power generation data and the corresponding weather conditions are linked and recorded in the power generation reference database by recording the past weather conditions of a plurality of years, the orientation posture of the photovoltaic module and the corresponding power generation data. And then analyzing and classifying the weather conditions of different types, and summarizing the past weather condition types so as to retrieve the weather conditions subsequently and correspondingly classify the power generation data and the orientation posture data of the photovoltaic module under the weather conditions of different types.
The weather conditions of the photovoltaic module installation area on the test day are obtained in advance through a meteorological department, the predicted weather conditions are matched with the classified weather conditions in the power generation reference database, therefore, past weather conditions close to the weather conditions predicted on the test day are screened out, power generation data under similar weather conditions are analogized, the power generation data range on the test day is judged, meanwhile, the orientation postures of multiple groups of photovoltaic module arrays with larger power generation amount under similar weather conditions are called out, and an orientation posture set used on the test day is formed.
And recording the weather condition of the test day in real time, and accurately matching the weather condition of the test day with the screened past similar weather conditions, so as to further narrow the range of the power generation data. And recording power generation data of the photovoltaic module which generates power respectively in different orientation postures in the orientation posture set on the test day to obtain actual power generation data.
And finally, comparing the actual power generation data with the predicted power generation data and the reference power generation data respectively to obtain the accuracy between the predicted power generation data and the actual power generation amount, and simultaneously determining the orientation posture of the photovoltaic module corresponding to the optimal actual power generation amount on the test day so as to be referred next time.
The present invention in a preferred example may be further configured to: the weather conditions and the power generation data in the power generation reference database are analyzed, under the condition of different weather conditions, the orientation postures of the corresponding photovoltaic module arrays with better multiple groups of power generation quantities under the corresponding weather conditions are obtained, and the orientation posture set is formed by the orientation postures of the multiple groups of photovoltaic module arrays, and the orientation posture set comprises:
the weather conditions, the orientation postures of the photovoltaic module arrays and the power generation data are used as variables, the independent change of the weather conditions or the orientation postures of the photovoltaic module arrays is researched, the orientation postures of a plurality of groups of photovoltaic module arrays with more power generation under the corresponding weather conditions are obtained by combining the power generation data, and the orientation postures of the plurality of groups of photovoltaic module arrays form an orientation posture set.
Through adopting above-mentioned technical scheme, classify the past weather conditions that will take notes in the electricity generation reference database, the weather characterization that will have similar characteristic is same weather conditions, use weather conditions, photovoltaic module array's orientation gesture and electricity generation data as the variable respectively, when single variable changes, the influence to other variables is analyzed respectively, thereby when summarizing under different weather conditions, the orientation gesture of the photovoltaic module array that the more photovoltaic module of generated energy corresponds, arrange into orientation gesture set with the orientation gesture of multiunit photovoltaic module array in order, for the orientation gesture of the photovoltaic module array that supplies to test the day refers to.
The present invention in a preferred example may be further configured to: the weather forecast of the weather condition on the test day is obtained, the weather condition on the test day is respectively matched with the past weather condition in the power generation reference database, and the predicted power generation data and the reference power generation data are obtained by the method and the device, wherein the method comprises the following steps:
acquiring weather forecast data of a test day issued by a weather department in time, intercepting weather conditions of each time period in the weather forecast data, and respectively matching the weather temperature information, the cloudy-sunny condition information and the illumination intensity of each time period with a power generation reference database to obtain similar time period records of which the difference values between each item of the weather temperature information, the cloudy-sunny condition information and the illumination intensity in the past weather conditions and the corresponding information of the weather conditions of the test day are all smaller than a preset first threshold value;
and defining the maximum value in the power generation data in the records of the close time period as the expected power generation data of the test day, and acquiring the orientation posture of the corresponding photovoltaic module array.
By adopting the technical scheme, the weather conditions of the test points are obtained from the meteorological department in advance before the test day, the predicted weather conditions are analyzed, and the change of the weather conditions in the day is large, so that the complete weather conditions are divided according to time intervals, the change range of the weather conditions in each time interval is small, and the whole weather conditions are conveniently analyzed. And matching the divided weather conditions with the recorded weather conditions in the power generation reference database, enabling the matching difference value of each item of the weather temperature information, the cloudy and sunny condition information and the illumination intensity to be smaller than a first threshold value, screening out a similar time period record which is relatively similar to the weather condition on the test day, and taking the maximum value in the power generation data corresponding to the similar time period record as predicted power generation data and the orientation posture of the photovoltaic module array.
The present invention in a preferred example may be further configured to: the acquiring of weather forecast of weather conditions on the test day matches the weather conditions on the test day with past weather conditions in the power generation reference database respectively, and the obtaining of predicted power generation data and reference power generation data further includes:
respectively matching the weather temperature information, the cloudy and sunny condition information and the illumination intensity of each time interval with a power generation reference database, respectively and correspondingly comparing the weather temperature information, the cloudy and sunny condition information and the illumination intensity of each time interval with the past weather conditions, and respectively obtaining partial similar time interval records of which the difference value of any one of the weather temperature information, the cloudy and sunny condition information and the illumination intensity is smaller than a second threshold value;
the first threshold is greater than the second threshold;
acquiring the orientation posture and the power generation data of the photovoltaic module array in partial records of the similar time periods, and defining the power generation data in the partial records of the similar time periods as reference power generation data.
By adopting the technical scheme, the weather temperature information, the cloudy and sunny condition information and the illumination intensity in the weather condition of the test day are matched with the power generation reference database again, and the matching difference value of any one of the weather temperature information, the cloudy and sunny condition information and the illumination intensity is smaller than the second threshold value, so that partial similar time period records which are similar to one item in the weather condition are obtained, the power generation data corresponding to the partial similar time period records are defined as reference power generation data, and the orientation posture of the corresponding photovoltaic module array is recorded in the partial similar time period.
The present invention in a preferred example may be further configured to: the acquiring and recording the actual weather conditions on the test day, and enabling the plurality of photovoltaic module arrays to generate power according to different postures in the orientation posture set respectively, so as to obtain the actual power generation data of each photovoltaic module array on the test day includes:
acquiring the actual weather condition of each time period in the test day, and comparing the real-time weather condition with the expected weather condition to obtain a weather condition change difference value;
comparing the weather condition change difference with a preset third threshold value to obtain the accuracy of the weather condition information;
if the weather condition change difference is smaller than a preset third threshold value, enabling the multiple groups of photovoltaic module arrays to generate power according to different postures in the orientation posture set respectively, if the weather condition change difference is larger than the preset third threshold value, matching the weather condition information in the power generation reference database again to obtain a corrected orientation posture set, and enabling the multiple groups of photovoltaic module arrays to generate power according to different postures in the corrected orientation posture set respectively;
and recording the power generation data of each time interval, and summarizing the power generation data of each time interval according to a time sequence to obtain the actual power generation data of the test day.
By adopting the technical scheme, the weather condition is recorded in real time on the test day, the difference between the real-time weather condition and the predicted weather condition is judged, when the difference is smaller, the predicted weather condition is more accurate, and a plurality of groups of different photovoltaic modules are enabled to generate power respectively according to the orientation postures in the orientation posture set. And when the difference value is large, the predicted weather condition is inaccurate, the actual weather condition recorded in real time is uploaded to the power generation reference database, and the weather condition is matched again, so that more accurate weather condition matching data, power generation data and the orientation posture of the corresponding photovoltaic module array are obtained.
Because the orientation postures of the photovoltaic modules are different, the generated energy is different, and finally the generated energy of the photovoltaic modules with different orientation postures is gathered, so that the power generation data of each photovoltaic module can be calculated, and the actual power generation data can be obtained.
The present invention in a preferred example may be further configured to: the step of comparing the actual power generation data, the predicted power generation data and the reference power generation data among the multiple groups of photovoltaic module arrays to obtain the actual deviation value comprises the following steps:
comparing actual power generation data among the photovoltaic module arrays to obtain maximum power generation data on the test day;
comparing the maximum power generation data with the predicted power generation data on the test day to obtain an actual deviation value;
and comparing the maximum power generation data with the reference power generation data on the test day to obtain a reference deviation value.
By adopting the technical scheme, the power generation data of the photovoltaic modules in different orientation postures are compared, one group of data with the largest power generation amount is selected as the maximum power generation data on the test day, and the maximum power generation data on the test day is sequentially compared with the predicted power generation data and the reference power generation data, so that the actual deviation value and the reference deviation value about the prediction accuracy degree are respectively obtained, and whether the predicted result is accurate or not is conveniently analyzed.
The present invention in a preferred example may be further configured to: the actual deviation value is compared with a preset defined threshold value, the obtained maximum power generation data is used as the power generation amount of the photovoltaic module array under the similar weather condition in the next prediction, and the orientation posture of the corresponding optimal photovoltaic module array comprises the following steps:
comparing the actual deviation value, the reference deviation value and a preset defined threshold value to obtain an evaluation conformity between the predicted generated energy and the actual generated energy, and recording the maximum generated data and the evaluation conformity of the current day as the later reference data in a power generation reference database;
recording orientation attitude data of the optimal photovoltaic module array corresponding to the maximum power generation data on the test day and weather conditions on the test day in a power generation reference database;
and analyzing the influence of orientation posture factors on the generated energy under the same weather condition on the generated energy in the power generation reference database according to the generated power data of other different groups of photovoltaic module arrays.
By adopting the technical scheme, the actual deviation value and the reference deviation value are compared with the preset defined threshold, and when the obtained evaluation conformity is low, the fact that the deviation between the power generation data predicted in advance and the actual power generation data is large is shown, and the accuracy of the prediction mode is low; when the evaluation conformity is higher, the accuracy of the prediction mode is higher, and the prediction result is more consistent with the actual power generation amount, so that the evaluation conformity of a group of data with higher evaluation conformity is used as the reference weight of the maximum power generation data on the test day, and the reliability of the power generation data on the test day which can be referred is represented. And recording the maximum power generation data, the orientation posture data of the optimal photovoltaic module array and the weather condition in a power generation reference database on the test day for predicting next time.
The invention also aims to provide a photovoltaic power generation detection system.
The second aim of the invention is realized by the following technical scheme:
the database module is used for recording weather conditions, orientation postures of the photovoltaic module array and corresponding power generation data in a plurality of years to form a power generation reference database, wherein the weather conditions comprise weather temperature information, cloudy and sunny condition information and illumination intensity;
the data analysis module is used for analyzing the weather conditions and the power generation data in the power generation reference database, obtaining orientation postures of a plurality of groups of photovoltaic module arrays with better power generation capacity under corresponding weather conditions, and forming orientation postures of the plurality of groups of photovoltaic module arrays into an orientation posture set;
the prediction module is used for acquiring weather forecast of weather conditions on the test day, and respectively matching the weather conditions on the test day with past weather conditions in the power generation reference database to obtain predicted power generation data and reference power generation data;
the measuring and recording module is used for acquiring and recording the actual weather condition of the test day, and enabling the photovoltaic module arrays to generate power according to different postures in the orientation posture set respectively to obtain the actual power generation data of each photovoltaic module array;
the accuracy evaluation module is used for comparing the actual power generation data with the predicted power generation data and the reference power generation data respectively to obtain an actual deviation value, comparing the actual deviation value with a preset defined threshold value to obtain maximum power generation data serving as the next generated energy of the predicted photovoltaic module array under the similar weather condition and the orientation posture of the corresponding optimal photovoltaic module array;
wherein the accuracy evaluation module comprises
The generating capacity difference comparing unit is used for comparing actual generating data among the photovoltaic module arrays to obtain the maximum generating data of the test day, and comparing the maximum generating data of the test day with the predicted generating data and the reference generating data respectively to obtain an actual deviation value and a reference deviation value, so that the minimum of the actual deviation value and the reference deviation value is positioned as the actual deviation value;
the evaluation conformity unit is used for comparing the actual deviation value and the reference deviation value with a preset defined threshold value to obtain the evaluation conformity between the predicted power generation amount and the actual power generation amount, and recording the maximum power generation data and the evaluation value conformity on the test day as the later reference data in the power generation reference database;
and the attitude and weather condition recording unit is used for recording the orientation attitude data of the photovoltaic module array used by the maximum power generation data pair on the test day and the weather condition on the test day in the power generation reference database, analyzing the power generation data of different groups of photovoltaic module arrays, and analyzing the influence of the orientation attitude factors on the power generation amount under the same weather condition in the power generation reference database.
By adopting the technical scheme, the database module records the weather conditions of a plurality of years, the orientation posture of the photovoltaic module array and the corresponding power generation data in one day, and associates the weather conditions, the orientation posture of the photovoltaic module array and the corresponding power generation data in one day, so that the weather conditions, the orientation posture of the photovoltaic module array and the corresponding power generation data in one day are in one-to-one correspondence. The data analysis module is used for analyzing and classifying hiccup recorded data of the database module, so that records with similar weather conditions are classified into the same group of types, the weather conditions are conveniently retrieved and matched, and orientation postures and power generation data of the photovoltaic module arrays corresponding to the weather conditions of the same group of types are recorded. The forecasting module acquires the weather condition of the test day from the meteorological department and sends the weather condition to the data analysis module, the data analysis module searches and matches the forecasted weather condition and screens out records close to the forecasted weather condition, and therefore the range of the forecasted power generation data is obtained to serve as reference power generation data of the reference data. On the test day, the test and recording module records the weather conditions on the test day in real time and uploads the real-time weather conditions to the data analysis module, and meanwhile records the power generation data on the test day and uploads the orientation posture of the photovoltaic module array to the power generation reference database. After the electricity generation on the test day is finished, an electricity generation difference comparison unit in the accuracy evaluation module compares electricity generation data of a plurality of groups of photovoltaic module arrays with different orientations and postures so as to obtain maximum electricity generation data, the obtained maximum electricity generation data is defined as the maximum electricity generation data on the test day, the maximum electricity generation data on the test day is respectively used for being compared with expected electricity generation data and reference electricity generation data to obtain an actual deviation value and a reference deviation value, the actual deviation value and the reference deviation value are sent to an evaluation conformity unit, and the evaluation conformity unit compares the actual deviation value and the reference deviation value with a preset defined threshold value to obtain evaluation conformity which is used for representing the accuracy degree between the electricity generation amount of the prediction method and the actual electricity generation amount. And the final posture and weather condition recording unit analyzes and records the orientation posture of the photovoltaic module array on the test day and corresponds to the weather condition on the test day.
The third purpose of the invention is to provide an electronic device which has the function of storing and executing the photovoltaic power generation detection method so as to ensure the normal operation of the photovoltaic power generation detection function.
The third object of the invention is realized by the following technical scheme:
an electronic device comprising a memory and a processor, the memory having stored thereon a computer program that can be loaded by the processor and that executes any of the above-described photovoltaic power generation detection methods.
By adopting the technical scheme, the memory is used for storing the computer program using the photovoltaic power generation detection method, and the computer program stored in the memory can control the operation of each module through the processor.
The fourth purpose of the invention is to provide a computer storage medium which can store corresponding programs and has the characteristic of being convenient for implementing the energy monitoring method.
The fourth object of the invention is realized by the following technical scheme:
a computer readable storage medium storing a computer program that can be loaded by a processor and executed to perform any of the above-described photovoltaic power generation detection methods.
In summary, the invention includes at least one of the following beneficial technical effects:
when the photovoltaic module array generates electricity, the past recorded data in the electricity generation reference database is called, and electricity generation data on the test day is predicted under the similar conditions of the similar weather conditions, so that the prediction range of the actual electricity generation is obtained, and the electricity generation of the photovoltaic module array is conveniently predicted;
the data such as the power generation data, the weather conditions and the orientation posture of the photovoltaic module are uploaded to the power generation reference database, so that the data in the power generation reference database are more diversified, the matched data are more representative, and the predicted power generation data range is more accurate.
Drawings
FIG. 1 is an overall schematic block diagram of the present invention;
FIG. 2 is a schematic flow diagram of the present invention for obtaining predicted power generation data and reference power generation data;
fig. 3 is a schematic flow chart for processing the actual power generation amount in the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The embodiment of the invention provides a photovoltaic power generation detection method, which comprises the following steps of referring to fig. 1:
and S10, recording weather conditions in a plurality of years, orientation postures of the photovoltaic module arrays and corresponding power generation data to form a power generation reference database, wherein the weather conditions comprise weather temperature information, cloudy and sunny condition information and illumination intensity.
In order to better predict the power generation data of the photovoltaic component array, the weather conditions of different time periods in each day in the past several years, the orientation posture and the power generation data of the corresponding photovoltaic component array are collected, the weather conditions of the different time periods are sequentially associated with the orientation posture of the photovoltaic component array and the power generation data of the time periods one by one, and a power generation reference database is established.
S20, referring to fig. 1, analyzing the weather conditions and the power generation data in the power generation reference database, obtaining orientation postures of the plurality of sets of photovoltaic module arrays with better power generation amounts corresponding to the weather conditions under different weather conditions, and forming an orientation posture set from the orientation postures of the plurality of sets of photovoltaic module arrays.
Because the weather conditions include a plurality of factors influencing the power generation data, the influence of the weather conditions and the photovoltaic module array on the power generation data is researched by using a control variable method by taking the weather conditions, the orientation posture of the photovoltaic module array and the power generation data as variables.
The method comprises the steps of selecting similar weather conditions recorded in a power generation reference database as same-group weather condition variables, respectively enabling orientation postures of corresponding photovoltaic module arrays to change, researching the influence of the orientation postures of different photovoltaic module arrays on power generation data under certain weather conditions, obtaining orientation postures of a plurality of groups of photovoltaic module arrays with larger power generation capacity, arranging the orientation postures of the plurality of groups of photovoltaic module arrays with larger power generation capacity to form an orientation posture set, wherein the orientation posture set comprises the adjustment mode of the photovoltaic module arrays, and therefore the orientation posture of the optimal photovoltaic module array can be further analyzed.
Changing different weather conditions, and researching the orientation attitude set of the photovoltaic module array under different groups of weather condition variables.
S30, referring to fig. 1, acquiring weather forecast of weather conditions of the test day, and matching the weather conditions of the test day with past weather conditions in the power generation reference database, respectively, to obtain predicted power generation data and reference power generation data.
S31, referring to fig. 2, focusing on weather forecast data of the test day issued by the local weather department, acquiring weather conditions including weather temperature information, cloudy and sunny condition information, and illumination intensity in the illumination time, intercepting the whole illumination time according to time intervals, and recording the weather condition information in each time interval respectively.
In one day, the direct sunlight angle or the weather temperature and the like in the midday period are obviously higher than those in the morning and evening periods, so that the illumination time can be respectively intercepted into the three morning, middle and evening periods, and the weather conditions in the three morning, middle and evening periods are respectively recorded according to weather forecast data.
And S32, referring to FIG. 2, respectively matching the weather conditions of each time period of the test day with the past weather conditions recorded in the power generation reference database to obtain records of the similar time periods. And respectively matching each item of the weather temperature information, the cloudy and sunny condition information and the illumination intensity, and enabling the difference value between the weather temperature information, the cloudy and sunny condition information and the illumination intensity and the weather condition on the test day to be smaller than a preset first threshold value, so that a similar time period record similar to the weather condition on the test day is obtained, the weather condition recorded in the similar time period is similar to the weather condition on the test day, and the generated energy is possibly relatively close. And acquiring the orientation posture of the photovoltaic module array in the records of the similar time periods and the power generation data of the test day.
The records in the similar time periods may exist in a plurality, the maximum power generation amount in the records in the similar time periods is compared and defined as the expected power generation data on the test day, and the orientation posture of the photovoltaic module array corresponding to the day with the maximum power generation amount is recorded.
S33, referring to fig. 2, matching the weather temperature information, the cloudy and sunny condition information, and the illumination intensity again to obtain partial records of similar time periods. Because the influence factors of the generated energy are more, only the day which is similar to all items in the weather conditions on the test day is selected as a reference date, and the day may have unrepresentative conditions, and therefore the weather temperature information, the cloudy and sunny condition information and the illumination intensity are independently matched again, only the matching difference value of any one item of the weather temperature information, the cloudy and sunny condition information and the illumination intensity is required to be smaller than a preset second threshold value, so that the time period record which is similar to the weather conditions on the test day is obtained, and the first threshold value range is smaller than the second threshold value range.
And recording the similar time periods only with one item of weather temperature information, cloudy and sunny condition information and illumination intensity on the same test day, and is used for researching the influence relation on the power generation amount under a certain similar condition. And respectively acquiring the power generation data in partial similar time period records under different similar conditions and the orientation postures of the corresponding photovoltaic module arrays. Part of the power generation data recorded at the similar time period is defined as reference power generation data.
S40, referring to FIG. 1, acquiring and recording the actual weather conditions of the test day, and enabling the photovoltaic module arrays to generate power according to different postures in the orientation posture set respectively to obtain the actual power generation data of each group of photovoltaic module arrays.
And acquiring the actual weather condition of each time period in the test day, comparing the real-time weather condition with the expected weather condition to obtain a weather condition change difference value, and comparing the weather condition change difference value with a preset third threshold value to obtain the accuracy of the weather condition information. And recording and testing the weather conditions of the day from the sunrise sunlight shine on the photovoltaic module array to the sunset whole sunshine process in real time on the predicted day, dividing the weather conditions into three time periods of morning, noon and evening according to the time periods, comparing the weather conditions of the three time periods of morning, noon and evening with the predicted weather conditions one by one to obtain a weather condition change difference value, and measuring the accuracy degree between the weather forecast sent by a meteorological department and the local actual weather by utilizing a third threshold value.
And when the difference value of the weather condition change is smaller than the third threshold value, the weather forecast is identified to be more accurate. Because photovoltaic power generation mostly adopts the photovoltaic module array formed by connecting a plurality of groups of photovoltaic modules in parallel to generate power, different photovoltaic modules are opposite to the sun according to different postures in the orientation posture set, and therefore the influence of different orientation postures on the maximum power generation amount is explored.
And testing that when the difference value of the weather condition change is greatly different from the third threshold value, the unexpected weather condition is generated and is not consistent with the expected weather condition. Acquiring local real-time weather conditions, uploading the real-time weather conditions to a power generation reference database for re-matching, acquiring correction similar time period records similar to the real-time weather conditions, forming correction orientation posture sets by orientation postures of the photovoltaic module arrays corresponding to the correction similar time period records, correcting the orientation postures of the photovoltaic module arrays, and enabling the multiple groups of photovoltaic module arrays to generate power according to different orientation postures and different adjusting modes in the correction orientation posture sets.
When the test system is in a sunset, the power generation data of each group of photovoltaic module arrays in each time interval on the test day are recorded, and the three time intervals are sorted and summarized according to the time sequence, so that the total power generation data on the test day and the power generation data of the photovoltaic power generation modules in different postures in different time intervals are formed.
S50, referring to fig. 1, comparing the actual power generation data, the predicted power generation data, and the reference power generation data among the plurality of groups of photovoltaic module arrays to obtain an actual deviation value, comparing the actual deviation value with a preset defined threshold value to obtain the maximum power generation data, which is used as the next predicted power generation amount of the photovoltaic module array under the similar weather conditions, and the orientation posture of the corresponding optimal photovoltaic module array.
And S51, referring to FIG. 3, comparing the actual power generation data among the photovoltaic module arrays to obtain the maximum power generation data on the test day. And comparing power generation data among the photovoltaic modules among different groups, and defining the maximum power generation amount as the maximum power generation data in the day. And selecting a group of photovoltaic modules with the maximum generating capacity, and recording the orientation postures and the adjusting modes of the photovoltaic modules in different weather conditions in one day.
And respectively and sequentially comparing the maximum power generation data of the current day with the predicted power generation data and the reference power generation data so as to respectively obtain an actual deviation value and a reference deviation value. The actual deviation value is weighted more heavily than the reference deviation value, taking into account the reference value between the two.
S52, referring to fig. 3, comparing the actual deviation value, the reference deviation value and a predetermined defined threshold to obtain an estimated conformity between the predicted power generation amount and the actual power generation amount. And after the actual deviation value and the reference deviation value are obtained, comparing the actual deviation value and the reference deviation value with a preset defined threshold respectively to obtain an evaluation conformity for reflecting the deviation degree between the actual generated energy and the predicted generated energy, wherein if the evaluation conformity is lower, the accuracy of the predicted generated energy is lower, and the prediction method is inaccurate. When the evaluation conformity is higher, the prediction method is more accurate.
And S53, referring to FIG. 3, processing the actual power generation amount, the evaluation value conformity, the weather condition and the orientation posture data of the optimal photovoltaic module array on the test day. Making the evaluation value conformity as a reference weight of the maximum power generation data on the test day, and recording the maximum power generation data and the reference weight on the test day as the later reference data in a power generation reference database; and recording orientation posture data of the optimal photovoltaic module array corresponding to the maximum power generation data on the current test day and weather conditions on the current test day in a power generation reference database. And taking the maximum power generation amount on the day of the test as the optimal power generation amount on the day of the test, and taking the evaluation conformity degree as the reference weight of the maximum power generation data on the day of the test, wherein the evaluation conformity degree represents the conformity degree of the power generation value performed according to the preset orientation posture of the photovoltaic module array on the day of the test and the predicted power generation amount value, and the conformity degree is taken as the referenceable value of the power generation value of the photovoltaic module under the condition similar to the weather condition on the day of the test.
And simultaneously, recording the light orientation posture and the adjustment mode of the photovoltaic module of the maximum power generation data on the test day in a power generation reference database so as to extract the orientation posture of the photovoltaic module in the next test.
Example two:
an embodiment of the present invention provides a photovoltaic power generation detection system, including:
the database module is used for recording weather conditions, orientation postures of the photovoltaic module array and corresponding power generation data in a plurality of years to form a power generation reference database, wherein the weather conditions comprise weather temperature information, cloudy and sunny condition information and illumination intensity;
the data analysis module is used for analyzing the weather conditions and the power generation data in the power generation reference database, obtaining orientation postures of a plurality of groups of photovoltaic module arrays with better power generation capacity under corresponding weather conditions under different weather conditions, and forming an orientation posture set by the orientation postures of the plurality of groups of photovoltaic module arrays;
the prediction module is used for acquiring weather forecast of weather conditions on the test day, and respectively matching the weather conditions on the test day with past weather conditions in the power generation reference database to obtain predicted power generation data and reference power generation data;
the measuring and recording module is used for acquiring and recording the actual weather condition of the test day, and enabling the photovoltaic module arrays to generate power according to different postures in the orientation posture set respectively to obtain the actual power generation data of each photovoltaic module array;
the accuracy evaluation module is used for comparing the actual power generation data with the predicted power generation data and the reference power generation data respectively to obtain an actual deviation value, comparing the actual deviation value with a preset defined threshold value to obtain maximum power generation data serving as the next generated energy of the predicted photovoltaic module array under the similar weather condition and the orientation posture of the corresponding optimal photovoltaic module array;
wherein the accuracy evaluation module comprises
The generating capacity difference comparison unit is used for comparing actual generating data among the photovoltaic module arrays to obtain maximum generating data on the testing day, and comparing the maximum generating data on the testing day with predicted generating data and reference generating data respectively to obtain an actual deviation value and a reference deviation value, so that the minimum of the actual deviation value and the reference deviation value is positioned as the actual deviation value;
the evaluation conformity unit is used for comparing the actual deviation value, the reference deviation value and a preset defined threshold value to obtain the evaluation conformity between the predicted power generation amount and the actual power generation amount, and then taking the maximum power generation data and the evaluation conformity of the current test day as the reference weight of the maximum power generation data of the current test day as the subsequent reference data to be recorded in the power generation reference database;
the attitude and weather condition recording unit is used for recording the orientation attitude data of the photovoltaic module array used by the maximum power generation data pair on the test day and the weather condition on the test day in the power generation reference database;
and the attitude analysis unit is used for analyzing the power generation data of different groups of photovoltaic component arrays and analyzing the influence of the orientation attitude factors on the power generation amount under the same weather condition in the power generation reference database.
Example three:
an embodiment of the present invention provides an electronic device, which includes a memory and a processor, where the memory stores a computer program that can be loaded by the processor and execute any one of the above methods. Specifically, the electronic device includes a computer, a mobile phone, a tablet, a reader, and the like.
Example four:
the embodiment of the present invention provides a computer readable storage medium, which stores a computer program capable of being loaded by a processor and executing any one of the methods described above. It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions associated with a computer program, which may be stored in a non-volatile computer-accessible storage medium, and which, when executed, may comprise processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The present embodiment is only for explaining the present invention, and it is not limited to the present invention, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present invention.
Claims (10)
1. A method of photovoltaic power generation detection, the method comprising:
recording weather conditions, orientation postures of the photovoltaic module array and corresponding power generation data in a plurality of years to form a power generation reference database, wherein the weather conditions comprise weather temperature information, cloudy and sunny condition information and illumination intensity;
analyzing the weather conditions and the power generation data in the power generation reference database, obtaining orientation postures of a plurality of groups of photovoltaic module arrays with better power generation capacity under corresponding weather conditions under different weather conditions, and forming orientation posture sets of the plurality of groups of photovoltaic module arrays;
acquiring weather forecast of weather conditions on the test day, and respectively matching the weather conditions on the test day with past weather conditions in a power generation reference database to obtain predicted power generation data and reference power generation data;
acquiring and recording the actual weather condition of the test day, and enabling the plurality of photovoltaic module arrays to generate power according to different postures in the orientation posture set respectively to obtain the actual power generation data of each group of photovoltaic module arrays;
and comparing actual power generation data, predicted power generation data and reference power generation data among the multiple groups of photovoltaic module arrays to obtain actual deviation values, comparing the actual deviation values with a preset defined threshold value to obtain maximum power generation data serving as the next generation prediction of the generated energy of the photovoltaic module arrays under similar weather conditions and the orientation postures of the corresponding optimal photovoltaic module arrays.
2. The method of claim 1, wherein the analyzing the weather conditions and the power generation data in the power generation reference database, and under different weather conditions, deriving orientation postures of the plurality of sets of photovoltaic module arrays with better power generation capacity corresponding to the corresponding weather conditions, and grouping the orientation postures of the plurality of sets of photovoltaic module arrays into an orientation posture set comprises:
the weather conditions, the orientation postures of the photovoltaic module arrays and the power generation data are used as variables, the independent change of the weather conditions or the orientation postures of the photovoltaic module arrays is researched, the orientation postures of a plurality of groups of photovoltaic module arrays with more power generation under the corresponding weather conditions are obtained by combining the power generation data, and the orientation postures of the plurality of groups of photovoltaic module arrays form an orientation posture set.
3. The method of claim 2, wherein the obtaining weather forecast of weather conditions on the test day, and the matching of the weather conditions on the test day with past weather conditions in the power generation reference database respectively to obtain the predicted power generation data and the reference power generation data comprises:
acquiring weather forecast data of a test day issued by a weather department in time, intercepting weather conditions of each time period in the weather forecast data, and respectively matching the weather temperature information, the cloudy-sunny condition information and the illumination intensity of each time period with a power generation reference database to obtain similar time period records of which the difference values between each item of the weather temperature information, the cloudy-sunny condition information and the illumination intensity in the past weather conditions and the corresponding information of the weather conditions of the test day are all smaller than a preset first threshold value;
and defining the maximum value in the power generation data in the records of the close time period as the expected power generation data of the test day, and acquiring the orientation posture of the corresponding photovoltaic module array.
4. The method of claim 3, wherein obtaining weather forecasts of weather conditions on the test day, matching the weather conditions on the test day with past weather conditions in the power generation reference database, respectively, and deriving the predicted power generation data and the reference power generation data further comprises:
respectively matching the weather temperature information, the cloudy and sunny condition information and the illumination intensity of each time interval with a power generation reference database, respectively and correspondingly comparing the weather temperature information, the cloudy and sunny condition information and the illumination intensity of each time interval with the past weather conditions, and respectively obtaining partial similar time interval records of which the difference value of any one of the weather temperature information, the cloudy and sunny condition information and the illumination intensity is smaller than a second threshold value;
the first threshold is greater than the second threshold;
acquiring the orientation posture and the power generation data of the photovoltaic module array in partial records of the similar time periods, and defining the power generation data in the partial records of the similar time periods as reference power generation data.
5. The method according to claim 4, wherein the obtaining and recording the actual weather conditions on the test day, and the generating power by the plurality of photovoltaic module arrays according to different postures in the orientation posture set respectively, and the obtaining the actual power generation data on the test day of each photovoltaic module array comprises:
acquiring the actual weather condition of each time period in the test day, and comparing the real-time weather condition with the expected weather condition to obtain a weather condition change difference value;
comparing the weather condition change difference with a preset third threshold value to obtain the accuracy of the weather condition information;
if the weather condition change difference is smaller than a preset third threshold value, enabling the multiple groups of photovoltaic module arrays to generate power according to different postures in the orientation posture set respectively, if the weather condition change difference is larger than the preset third threshold value, matching the weather condition information in the power generation reference database again to obtain a corrected orientation posture set, and enabling the multiple groups of photovoltaic module arrays to generate power according to different postures in the corrected orientation posture set respectively;
and recording the power generation data of each time interval, and summarizing the power generation data of each time interval according to a time sequence to obtain the actual power generation data of the test day.
6. The method of claim 5, wherein comparing the actual power generation data, the predicted power generation data, and the reference power generation data between the plurality of photovoltaic module arrays to obtain the actual deviation value comprises:
comparing actual power generation data among the photovoltaic module arrays to obtain maximum power generation data on the test day;
comparing the maximum power generation data with the predicted power generation data on the test day to obtain an actual deviation value;
and comparing the maximum power generation data of the test day with the reference power generation data to obtain a reference deviation value.
7. The method of claim 6, wherein comparing the actual deviation value with a predetermined threshold value to obtain maximum power generation data as the next predicted power generation amount of the photovoltaic module array under similar weather conditions, and wherein the orientation of the corresponding optimal photovoltaic module array comprises:
comparing the actual deviation value, the reference deviation value and a preset defined threshold value to obtain an evaluation conformity between the predicted power generation amount and the actual power generation amount, and recording the maximum power generation data and the evaluation conformity on the test day as the subsequent reference data in a power generation reference database;
recording orientation attitude data of the optimal photovoltaic module array corresponding to the maximum power generation data on the test day and weather conditions on the test day in a power generation reference database;
and analyzing the influence of orientation posture factors on the generated energy under the same weather condition on the generated energy in the power generation reference database according to the generated power data of other different groups of photovoltaic module arrays.
8. Photovoltaic power generation detection system, its characterized in that includes:
the database module is used for recording weather conditions, orientation postures of the photovoltaic module array and corresponding power generation data in one day in the past several years to form a power generation reference database, wherein the weather conditions comprise weather temperature information, cloudy and sunny condition information and illumination intensity;
the data analysis module is used for analyzing the weather conditions and the power generation data in the power generation reference database, obtaining orientation postures of a plurality of groups of photovoltaic module arrays with better power generation capacity under corresponding weather conditions under different weather conditions, and forming an orientation posture set by the orientation postures of the plurality of groups of photovoltaic module arrays;
the prediction module is used for acquiring weather forecast of weather conditions on the test day, and respectively matching the weather conditions on the test day with past weather conditions in the power generation reference database to obtain predicted power generation data and reference power generation data;
the measuring and recording module is used for acquiring and recording the actual weather condition of the test day, and enabling the photovoltaic module arrays to generate power according to different postures in the orientation posture set respectively to obtain the actual power generation data of each photovoltaic module array;
the accuracy evaluation module is used for comparing the actual power generation data with the predicted power generation data and the reference power generation data respectively to obtain an actual deviation value, comparing the actual deviation value with a preset defined threshold value to obtain maximum power generation data serving as the next predicted power generation amount of the photovoltaic module array under the similar weather condition and the orientation posture of the corresponding optimal photovoltaic module array;
wherein the accuracy evaluation module comprises
The generating capacity difference comparison unit is used for comparing actual generating data among the photovoltaic module arrays to obtain maximum generating data on the testing day, comparing the maximum generating data on the testing day with predicted generating data and reference generating data respectively to obtain actual deviation and reference deviation, and defining the minimum of the actual deviation and the reference deviation as an actual deviation value and a reference deviation value;
the evaluation conformity unit is used for comparing the actual deviation value and the reference deviation value with a preset defined threshold value to obtain the evaluation conformity between the predicted power generation amount and the actual power generation amount, and recording the maximum power generation data and the evaluation value conformity on the test day as the later reference data in the power generation reference database;
and the attitude and weather condition recording unit is used for recording the orientation attitude data of the photovoltaic module array used by the maximum power generation data pair on the test day and the weather condition on the test day in the power generation reference database, analyzing the power generation data of different groups of photovoltaic module arrays, and analyzing the influence of the orientation attitude factors on the power generation amount under the same weather condition in the power generation reference database.
9. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program that can be loaded by the processor and that executes the photovoltaic power generation detection method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that a computer program is stored which can be loaded by a processor and which executes a method for photovoltaic power generation detection according to any one of claims 1 to 7.
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