CN113095532A - Photovoltaic power station power generation real-time power prediction system and implementation method thereof - Google Patents
Photovoltaic power station power generation real-time power prediction system and implementation method thereof Download PDFInfo
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- CN113095532A CN113095532A CN201911320631.0A CN201911320631A CN113095532A CN 113095532 A CN113095532 A CN 113095532A CN 201911320631 A CN201911320631 A CN 201911320631A CN 113095532 A CN113095532 A CN 113095532A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
Compared with the prior art, the real-time power prediction of the component is calculated according to the real-time solar irradiation amount, the component temperature, the installation angle, the service life of the component and the parameters of the component, the power of the component real-time prediction marker post is compared with the power of each group of strings in the whole station, so that the specific position of the group of strings with a large missing power ratio is accurately obtained, operation and maintenance personnel are prompted to search for the missing power reason in time and remove faults, the operation and maintenance level and the operation and maintenance efficiency of field station personnel are improved, the generated energy is further improved, and the purpose of the invention is realized.
Description
Technical Field
The invention relates to a real-time power prediction system and an implementation method thereof, in particular to a photovoltaic power station power generation real-time power prediction system and an implementation method thereof.
Background
In a photovoltaic power station, the power generation capacity of a photovoltaic module has a great relationship with factors such as solar irradiation capacity, module temperature, module cleanliness and the like. The photovoltaic power prediction system is used for evaluating the power generation efficiency and the operation and maintenance management level of a photovoltaic power station and comparing the power generation amount of the power prediction system with the actual power generation amount of the power station. The photovoltaic power prediction system predicts the power generation capacity of the power station according to the local solar irradiation amount, the module temperature, the module cleanliness, the module parameters and other factors of the photovoltaic power station.
The existing photovoltaic power prediction system calculates and predicts the power generation amount of a photovoltaic power station in the whole time of the next year or month according to past meteorological data (the average synchronization of the last year or the historical years).
At present, the photovoltaic industry judges whether the generated energy of a photovoltaic power station reaches the maximum theoretical power or not and whether a space for increasing is available or not, and the following methods are mainly adopted: firstly, judging by referring to the data which can be researched; and secondly, predicting the generated power of a period of time in the future by adopting the characteristics of the existing photovoltaic power prediction system according to the local meteorological data of the station accumulated in the past year. 1) Meteorological data varies greatly each year. The difference of big light year, small light year and the like; 2) the predicted photovoltaic power plant power for a future period of time (a year or a month and a half month) cannot be specified to the power at a certain moment of a certain day; thirdly, comparing the generated energy with the generated energy of stations at the adjacent geographical positions; according to the level of the total station capacity, the method can not specifically use the cluster as a unit, and cannot achieve the effect of timely operation and maintenance on operation and maintenance personnel.
The methods have the disadvantages that the comparison time is long, the deficiency of the power generation amount of the power station cannot be accurately fed back in time, and a specific operation and maintenance scheme cannot be provided for the deficiency part of the power generation amount.
Therefore, a system for predicting real-time power generated by a photovoltaic power station and a method for implementing the same are particularly needed to solve the existing problems.
Disclosure of Invention
The invention aims to provide a photovoltaic power station power generation real-time power prediction system and an implementation method thereof, aiming at the defects of the prior art.
The technical problem solved by the invention can be realized by adopting the following technical scheme:
in a first aspect, the invention discloses a real-time power prediction system for power generation of a photovoltaic power station, which is characterized by comprising a control unit, a data communication unit, a meteorological environment monitoring unit and a data acquisition unit, wherein the control unit is respectively connected with the meteorological environment monitoring unit and the data acquisition unit through the data communication unit, the meteorological environment monitoring unit is used for monitoring environmental parameters and acquiring illumination intensity data and temperature data, and the data acquisition unit is used for respectively acquiring component characteristic parameters and group string data.
In one embodiment of the invention, the data communication unit and the control unit are communicatively connected with each other through a router.
In one embodiment of the present invention, the data communication unit includes, but is not limited to, a wired communication module and a wireless communication module.
In one embodiment of the present invention, the data acquisition unit includes, but is not limited to, a hall sensor, a dc current meter, and a SCADA data acquisition module.
In a second aspect, the invention discloses a method for realizing real-time power prediction of photovoltaic power station power generation, which is characterized by comprising the following steps:
(1) establishing a benchmark power model of a photovoltaic power station string through big data of meteorological geographic information and component parameter information to obtain theoretical real-time power generation data;
(2) acquiring meteorological parameters and parameters of the components in real time, calculating real-time marker post power of the photovoltaic power station string, and acquiring real-time power generation data;
(3) by comparing the real-time marker post power with the power of all the strings of the photovoltaic power station, the strings with power loss are accurately found out, operation and maintenance are carried out, the loss is eliminated, and the generating capacity is improved.
In one embodiment of the present invention, in the step (1), the meteorological geographic information (time, date, latitude, temperature, horizontal plane direct projection, horizontal plane scattering, component installation angle, etc.) is collected by various sensors, the component manufacturer provides component characteristic parameters (short-circuit current, open-circuit voltage, maximum power point current, maximum power point voltage, temperature coefficient, attenuation coefficient, etc.), and three different theoretical formulas are adopted to calculate the power generation data of the current power station under the current meteorological condition.
In an embodiment of the present invention, in step (3), after determining the formula of the power of the string marker, the power of each string of components in the total station is collected, and the marker power is compared with the power of the components in the total station to find out the power-missing string, and the position of the power-missing string can be accurately located, so as to timely maintain the power-missing of the string.
Compared with the prior art, the photovoltaic power station power generation real-time power prediction system and the implementation method thereof calculate the real-time power prediction of the component according to the real-time solar irradiation amount, the component temperature, the installation angle, the component service life and the component parameters, and the component predicts the benchmarking power and the power ratio of each group of the total station in real time, so that the specific position of the group with larger missing power ratio is accurately obtained, operation and maintenance personnel are prompted to search for the missing power reason in time and get rid of faults, the operation and maintenance level and the operation and maintenance efficiency of the station personnel are improved, the power generation amount is further improved, and the purpose of the invention is realized.
The features of the present invention will be apparent from the accompanying drawings and from the following detailed description of preferred embodiments.
Drawings
FIG. 1 is a schematic diagram of a photovoltaic power plant power generation real-time power prediction system of the present invention;
FIG. 2 is a schematic flow chart of a method for realizing real-time power prediction of photovoltaic power station power generation.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further explained below by combining the specific drawings.
Examples
As shown in fig. 1, the photovoltaic power plant power generation real-time power prediction system of the present invention includes a control unit 10, a data communication unit 20, a meteorological environment monitoring unit 30 and a data acquisition unit 40, wherein the control unit 10 is respectively connected to the meteorological environment monitoring unit 30 and the data acquisition unit 40 through the data communication unit 20, the meteorological environment monitoring unit 30 is configured to monitor environmental parameters and obtain illumination intensity data and temperature data, and the data acquisition unit 40 is configured to respectively obtain component characteristic parameters and group string data.
In the present embodiment, the data communication unit 20 and the control unit 10 are communicatively connected to each other through a router.
In the present embodiment, the data communication unit 20 includes, but is not limited to, a wired communication module and a wireless communication module.
In the present embodiment, the data acquisition unit 40 includes, but is not limited to, a hall sensor, a dc current meter, and a SCADA data acquisition module.
As shown in fig. 2, the method for predicting real-time power generated by a photovoltaic power station of the present invention comprises the following steps:
(1) establishing a benchmark power model of a photovoltaic power station string through big data of meteorological geographic information and component parameter information to obtain theoretical real-time power generation data;
(2) acquiring meteorological parameters and parameters of the components in real time, calculating real-time marker post power of the photovoltaic power station string, and acquiring real-time power generation data;
(3) by comparing the real-time marker post power with the power of all the strings of the photovoltaic power station, the strings with power loss are accurately found out, operation and maintenance are carried out, the loss is eliminated, and the generating capacity is improved.
In the step (1), meteorological geographic information (time, date, latitude, temperature, horizontal plane direct projection, horizontal plane scattering, component installation angle and the like) is collected through various sensors, component manufacturers provide component characteristic parameters (short-circuit current, open-circuit voltage, maximum power point current, maximum power point voltage, temperature coefficient, attenuation coefficient and the like), and three different theoretical formulas are adopted to calculate power generation data of the current power station under the current meteorological conditions.
In the step (3), after the formula of the string marker power is determined, the power of each string of components in the whole station is collected, the marker power is compared with the power of the components in the whole station, the power-missing string is found out, the position of the power-missing string can be accurately located, and the power missing of the string can be timely maintained.
The photovoltaic power station power generation real-time power prediction system collects meteorological geographic information (time, date, latitude, temperature, horizontal plane direct projection, horizontal plane scattering, component installation angle and the like) through various sensors, and meanwhile needs component manufacturers to provide component characteristic parameters (short-circuit current, open-circuit voltage, maximum power point current, maximum power point voltage, temperature coefficient, attenuation coefficient and the like). According to the information, three different theoretical formulas are adopted to calculate the power generation data of the current power station under the current meteorological conditions. Three different theoretical formulas are used for the reason: 1) the theoretical formula is not actually verified, and selection and correction can be carried out subsequently according to comparison with actually measured data; 2) the difference of the theoretical formula calculation method is possible to provide a basis for subsequent analysis.
The voltage and current of a string are measured simultaneously, and the voltage of each string component in the string is measured using a hall element. And verifying the theoretical formula by comparing the actual measurement data of the group of strings with the theoretical calculation data.
After verification, theoretical calculation data and actual measurement data are analyzed in detail, loss of the power station is quantitatively inspected, and decision basis is provided for a power station owner.
Calculating the illumination intensity of the assembly:
time angle ω is (t-12) × 15 °
Declination angle delta 23.45sin [360(284+ n)/365]
The ratio of the direct radiation amount of the inclined plane to the horizontal plane is
The direct radiation of the inclined plane is then ST,b＝SbRb
Scattering of the inclined surface is ST,d＝Sd(1+cosβ)/2
The intensity of the illumination received by the component is ST＝ST,b+ST,d
(3) Theoretical generated power calculation
And calculating the real-time theoretical generating power of the power station by adopting three methods.
1) Formula one
The nominal power and the irradiation intensity are directly calculated, and the formula is as follows:
Sref＝1000w/m2
△T＝Tcell-25
maximum output power of the module is P1'm＝ST/Sref×Wp(1+αI△T)(1+αU△T)
The calculation method of the formula is directly converted according to the power of the standard test condition, the maximum power point of the component under different illumination intensities is not calculated, and the conversion efficiency of the component under different illumination intensities is defaulted to be the same actually. This is not expected to be very accurate, but it is possible to reflect the information of the conversion efficiency of the component at different illumination intensities. And (4) whether the reaction can be actually performed or not, and processing according to the actual situation at the later stage.
2) Formula two
And calculating the voltage and the current of the maximum power point of the assembly according to the real-time illumination intensity by using a second formula so as to obtain the maximum output power, wherein the second formula is as follows:
△S＝ST/Sref-1
c＝0.5
maximum power point voltage U'm＝Um(1+c△S)(1+αU△T)
Maximum power point voltage I'm＝Im(S/Sref)(1+αI△T)
Maximum power P output by module2'm＝U'mI'm
2) Formula three
And a third formula is also used for calculating the voltage and the current of the maximum power point of the assembly according to the real-time illumination intensity so as to obtain the maximum output power, and the calculation method is as follows:
the maximum output power of the component is P'3m＝U'mI'm
The power after attenuation is further calculated according to the component attenuation parameters in table 3.1 as:
P′im＝P′imx subassemblyAttenuation coefficient i is 1,2,3
(3) Authentication
And comparing the formula calculation result with various measurement results to check the correctness of the formula or the measurement so as to correct the formula or the measurement.
1) Voltage verification
Measuring the voltage U of each module in a string by using Hall elementsi(i ═ 1-k), k being the number of components in the string, while the voltage U across the string was measured. In theory, it is possible to use,
and comparing the data on the left side and the right side, and if the error is not large, determining that the measurement is correct.
2) Formula validation
It is believed that the first block component in the string of groups is not PID attenuated, then theoretically P'1m、P′2m、P′3mAnd U1There should be no large gap between I. If a large difference occurs in the field measurement, the formula should be selected or corrected.
The formula II and the formula III calculate the maximum power point U 'under any illumination condition'2mAnd U'3m. Considering that the first block of the string is not PID attenuated, the voltage U of the first block is the maximum power point if the assembly is actually at1Should be and U'2m(or U'3m) Are equal. Through U1-U'2m(or U)1-U′3m) Can check whether the inverter has tracked the maximum power point.
Group string analysis:
here the analysis monitors the loss of strings and the result is used as a reference for the total station.
The power loss due to the inverter failing to track to the maximum power point is:
PMPPT＝k(U'2m-U1)I
the power loss due to PID decay (the first block component is considered to have no PID decay) is:
the power loss caused by the dust is then:
Pdust＝P′2m-P-PMPPT-PPID
will PMPPT、PPID、PdustAnd comparing to obtain the electric quantity loss conditions of the strings.
And integrating the losses of the groups in one day with the time to obtain the loss electric quantity of the groups in the day.
The loss of power generation due to failure to track the maximum power point is
The loss of power generation due to PID is
The loss of power generation due to dust is
Total station power analysis:
due to different environments of each group string or different components, except for the monitoring group string, losses of other group strings cannot be separated independently, only one total loss can be obtained, but data of the monitoring group string can be used as a reference.
Spatial data analysis:
the SCADA system can acquire real-time power generation power P of any group of stringsiThen the power generation power loss of the string set is Pi,lost＝P′2m-Pi. According to Pi,lostThe power loss of each group string of the whole station can be obtained quantitatively, and operation and maintenance personnel are guided to carry out corresponding treatment.
And (3) historical data analysis:
if P'1mIs calculated as reliable, P/P'1mReflecting the conversion efficiency of the assembly under different illumination intensities. Record P/P'1mIf a large change occurs at a certain time, the reason should be quickly found out. Similarly, P/P 'was recorded'2mThe history data of (a).
Loss of daily generated energy:
the amount of power sent by the components is not equal to the amount of power on the internet, and there is a lot of loss before reaching the gateway meter, as follows:
the theoretical daily power generation of the photovoltaic plant is then:
and subtracting the metering electric quantity of the gateway on the current day from the theoretical electric quantity to obtain the total station electric quantity loss on the current day.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are merely illustrative of the principles of the present invention, but that various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined by the appended claims and their equivalents.
Claims (7)
1. The photovoltaic power station power generation real-time power prediction system is characterized by comprising a control unit, a data communication unit, a meteorological environment monitoring unit and a data acquisition unit, wherein the control unit is respectively connected with the meteorological environment monitoring unit and the data acquisition unit through the data communication unit, the meteorological environment monitoring unit is used for monitoring environmental parameters and acquiring illumination intensity data and temperature data, and the data acquisition unit is used for respectively acquiring component characteristic parameters and group string data.
2. The photovoltaic power plant power generation real-time power prediction system of claim 1, wherein the data communication unit and the control unit are communicatively coupled to each other via a router.
3. The photovoltaic power plant power generation real-time power prediction system of claim 1, characterized in that the data communication unit includes but is not limited to a wired communication module and a wireless communication module.
4. The photovoltaic power plant power generation real-time power prediction system of claim 1, wherein the data acquisition units include, but are not limited to, hall sensors, dc current meters, and SCADA data acquisition modules.
5. A method for realizing real-time power prediction of photovoltaic power station power generation is characterized by comprising the following steps:
(1) establishing a benchmark power model of a photovoltaic power station string through big data of meteorological geographic information and component parameter information to obtain theoretical real-time power generation data;
(2) acquiring meteorological parameters and parameters of the components in real time, calculating the real-time benchmark power of the photovoltaic power station string, and acquiring real-time power generation data;
(3) by comparing the real-time marker post power with the power of all the strings of the photovoltaic power station, the strings with power loss are accurately found out, operation and maintenance are carried out, the loss is eliminated, and the generating capacity is improved.
6. The method for realizing the real-time power prediction of photovoltaic power station power generation as claimed in claim 5, wherein in the step (1), meteorological geographic information (time, date, latitude, temperature, horizontal plane direct projection, horizontal plane scattering, component installation angle and the like) is collected through various sensors, component manufacturers provide component characteristic parameters (short-circuit current, open-circuit voltage, maximum power point current, maximum power point voltage, temperature coefficient, attenuation coefficient and the like), and three different theoretical formulas are adopted to calculate the power generation data of the current power station under the current meteorological conditions.
7. The method of claim 5, wherein in step (3), after determining the formula of the string target power, the power of each string of components in the total station is collected, and the target power is compared with the power of the components in the total station to find out the power-missing string, and the position of the power-missing string can be accurately located to timely maintain the power-missing string.
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| CN116742716A (en) * | 2023-06-13 | 2023-09-12 | 安徽华晟新能源科技有限公司 | Photovoltaic power station output power adjusting method and device and computer equipment |
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| CN116742716A (en) * | 2023-06-13 | 2023-09-12 | 安徽华晟新能源科技有限公司 | Photovoltaic power station output power adjusting method and device and computer equipment |
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