CN112491142A - Photovoltaic power station performance analysis system and method - Google Patents
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
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Abstract
The invention provides a photovoltaic power station performance analysis system and method, wherein a photovoltaic power station is divided into a plurality of subsystems, each subsystem calculates the full-emission ratio of a photovoltaic group string accessed by the subsystem in real time by utilizing the edge computing capability of an inverter and sends the full-emission ratio to a cloud service platform, so that the cloud service platform performs performance analysis on each subsystem in real time according to the full-emission ratio of the photovoltaic group string accessed by each subsystem, the inefficient subsystems are positioned, and the switching device action of the inefficient subsystems is further controlled. According to the invention, the cloud service platform is combined with the subsystem to perform remote real-time performance analysis, and the performance analysis efficiency of the photovoltaic power station is improved.
Description
Technical Field
The invention relates to the technical field of photovoltaic power generation, in particular to a photovoltaic power station performance analysis system and method.
Background
With the rapid development of the photovoltaic industry in China, the power generation performance of a photovoltaic power station is widely concerned. At present, the overall performance of a non-photoelectric conversion unit in a photovoltaic power station system is generally analyzed by using a system Performance Ratio (PR) to realize overall evaluation of the photovoltaic power station.
However, the analysis object of the system performance ratio is the whole photovoltaic power station, the system performance ratio of the whole photovoltaic power station is calculated according to the final capacity output of the photovoltaic power station system and the reference output of the photovoltaic power station system, the power generation performance of the photovoltaic power station can only be integrally evaluated, and the refined low-efficiency positioning cannot be achieved.
Disclosure of Invention
In view of this, the invention provides a system and a method for analyzing the performance of a photovoltaic power station, which realize the inefficient positioning of a subsystem of the photovoltaic power station.
In order to achieve the above purpose, the invention provides the following specific technical scheme:
a photovoltaic power plant performance analysis system, comprising: the system comprises a cloud service platform and at least one subsystem in communication connection with the cloud service platform; wherein:
the subsystem comprises an inverter with an edge calculation function, so that the subsystem can calculate the full power ratio of each photovoltaic group string accessed by the subsystem in real time;
the cloud service platform is used for carrying out performance analysis on the subsystem according to the full distribution ratio of each photovoltaic group string accessed by the subsystem.
Optionally, the types of the subsystems include: a first class and a second class;
the inverters in the first type subsystem are string inverters;
the inverters in the second type of subsystem are centralized inverters.
Optionally, the full power ratio of the photovoltaic string accessed by the first type of subsystem is as follows: the ratio of the direct current instantaneous power of the connected photovoltaic string to the rated installed capacity.
Optionally, the full power ratio of the photovoltaic string accessed by the second type of subsystem is as follows: the ratio of the direct instantaneous current of the connected photovoltaic string to the nominal maximum power point current thereof.
Optionally, the photovoltaic power station performance analysis system further includes an automatic switching device corresponding to the subsystem, a front end of the automatic switching device is connected to a photovoltaic group string to which the subsystem is connected, and a rear end of the automatic switching device is connected to an inverter and an accessory device of the subsystem;
the cloud service platform is further used for sending a switching instruction to the subsystem corresponding to the photovoltaic group string under the condition that the inefficient photovoltaic group string is detected to exist, so that the inverter in the subsystem controls the switching device corresponding to the inverter to act.
A photovoltaic power station performance analysis method is applied to the photovoltaic power station performance analysis system in the embodiment, and the method comprises the following steps:
the subsystem calculates the full distribution ratio of each photovoltaic group string accessed by the subsystem in real time and sends the calculated full distribution ratio to the cloud service platform;
and the cloud service platform performs performance analysis on the subsystem according to the full distribution ratio of each photovoltaic group string accessed by the subsystem.
Optionally, the types of the subsystems include: a first class and a second class;
the inverters in the first type subsystem are string inverters;
the inverters in the second type of subsystem are centralized inverters.
Optionally, when the photovoltaic power plant performance analysis system includes the first-type subsystem, the calculating, by the first-type subsystem, a full power ratio of each photovoltaic string accessed by the first-type subsystem in real time includes:
the first type subsystem acquires the direct current instantaneous power of each photovoltaic group string accessed by the first type subsystem;
and the first type subsystem calculates the ratio of the direct current instantaneous power of each photovoltaic group string accessed by the first type subsystem to the rated installed capacity of the first type subsystem to obtain the full power ratio of each photovoltaic group string accessed by the first type subsystem.
Optionally, when the photovoltaic power plant performance analysis system includes the second-class subsystem, the second-class subsystem calculates, in real time, a full power distribution ratio of each photovoltaic string accessed by the second-class subsystem, and includes:
the second type subsystem acquires direct current instantaneous current of each photovoltaic group string connected with the second type subsystem;
and the second type subsystem calculates the ratio of the direct current instantaneous current of each photovoltaic group string connected with the second type subsystem to the nominal maximum power point current of the photovoltaic group string to obtain the full power ratio of each photovoltaic group string connected with the second type subsystem.
Optionally, when the photovoltaic power station performance analysis system includes a plurality of first-type subsystems, the cloud service platform performs performance analysis on the subsystems according to a full distribution ratio of each photovoltaic group string accessed by the subsystem, including:
the cloud service platform determines the full distribution ratio of each first-class subsystem according to the full distribution ratio of each photovoltaic group string accessed by each first-class subsystem;
the cloud service platform judges whether an outlier exists in the full-emission ratio of each first-class subsystem at the same moment;
if an outlier exists, the cloud service platform determines that the first-class subsystem corresponding to the outlier has low efficiency, and positions the first-class subsystem with low efficiency according to a topological structure of the photovoltaic power station;
if no outlier exists, the cloud service platform determines that no inefficiency exists in all the first type subsystems.
Optionally, the method further includes:
when the cloud service platform detects that the full sending ratio of the first type of subsystem in the middle preset period is lower than the full sending ratio of other operation periods, the cloud service platform determines that the orientation problem exists in the photovoltaic group string accessed by the first type of subsystem;
the cloud service platform determines that power limitation exists in a photovoltaic group string accessed by the first type of subsystem when detecting that the full sending ratio of the first type of subsystem with low efficiency is continuously smaller than a preset value in one day and the full sending ratio changes along with time;
when the cloud service platform detects that the full emission ratio of the first type of subsystem with low efficiency is continuously smaller than a preset value in one day and the full emission ratio does not change along with time, determining that dust deposition exists in a photovoltaic group string accessed by the first type of subsystem;
the cloud service platform determines that a photovoltaic group string accessed by the first type subsystem has fixed occlusion when detecting that the full-emission ratio of the first type subsystem with low efficiency is abnormal in a specific time period in a day.
Optionally, when the photovoltaic power station performance analysis system includes the second-type subsystem, the cloud service platform performs performance analysis on the subsystem according to a full distribution ratio of each photovoltaic group string accessed by the subsystem, where the performance analysis includes:
the cloud service platform draws a full-emission ratio K line graph according to the full-emission ratios of all the accessed photovoltaic group strings in the second type subsystem, wherein the opening, the tray height, the tray bottom and the tray of the full-emission ratio K line graph respectively correspond to the average number, the maximum value, the minimum value and the median of the full-emission ratios of all the accessed photovoltaic group strings in the subsystem, when a rising and falling column between the opening tray and the tray is hollow, the median is larger than the average number, and when the rising and falling column between the opening tray and the tray is solid, the median is smaller than the average number;
and the cloud service platform determines whether the second type of subsystem has low efficiency according to the trend of the full emission ratio K line graph.
Optionally, the determining, by the cloud service platform, whether the second type of subsystem is inefficient according to the trend of the full emission ratio K-line graph includes:
when the cloud service platform detects that hollow rising and falling columns exist in the full-emission ratio K line graph of the second type of subsystem, determining that the second type of subsystem has low efficiency, and positioning the second type of subsystem with low efficiency according to a topological structure of a photovoltaic power station;
when the cloud service platform detects that a hollow rising and falling column exists in the full-power-generation ratio K line graph of the second type of subsystem in a preset time period at noon, the cloud service platform determines that the orientation of the photovoltaic group strings accessed by the second type of subsystem is inconsistent.
Optionally, the method further includes:
the cloud service platform determines the photovoltaic group string with the highest full-load ratio in each timestamp in each type of subsystem as a dynamic benchmark group string;
and the cloud service platform calculates the power generation amount loss amount by respectively calculating the power generation amount difference between the dynamic marker post group string and other photovoltaic group strings in each type of subsystem at each timestamp.
Optionally, the method further includes:
the cloud service platform counts the hourly accumulated irradiation quantity, the temperature, the hourly total power generation quantity and the hourly system performance ratio of a photovoltaic assembly in the photovoltaic power station in a preset analysis period, and correlatively fits the logarithmic change relationship between the system performance ratio and the temperature of the photovoltaic assembly to generate an inefficient calculation model between the temperature and the system performance ratio.
Optionally, the method further includes:
the cloud service platform calculates the monthly system performance ratio of each subsystem according to the equivalent utilization hours and monthly accumulated irradiation of each subsystem in a preset analysis period;
the cloud service platform carries out ascending sequencing on the monthly system performance ratio of each subsystem, and N ranked subsystems are obtained and serve as low-efficiency subsystems;
the cloud service platform calculates the daily system performance ratio of each low-efficiency subsystem, and counts the low-efficiency frequency of the low-efficiency subsystem in a monthly range;
and the cloud service platform positions the low-efficiency subsystem according to the topological structure of the photovoltaic power station.
Optionally, the method further includes:
the cloud service platform counts the inefficient frequency of the inefficient subsystem in a preset analysis period, associates the inefficient events of the inefficient subsystem with environmental factors, and generates an inefficient event probability distribution map marked with the corresponding relation between the environmental factors and the inefficient events of the inefficient subsystem.
Optionally, when the photovoltaic power plant performance analysis system further includes an automatic switching device corresponding to the subsystem, the method further includes:
the cloud service platform sends a switching instruction to the subsystems with low efficiency under the condition that the subsystems with low efficiency are detected to exist;
there is an inefficiency of the subsystem controlling the switching device action corresponding thereto.
Compared with the prior art, the invention has the following beneficial effects:
the photovoltaic power station performance analysis system disclosed by the invention divides the photovoltaic power station into a plurality of subsystems, each subsystem calculates the full-emission ratio of the photovoltaic group string accessed by the subsystem in real time by utilizing the edge computing capability of the inverter and sends the full-emission ratio to the cloud service platform, so that the cloud service platform performs performance analysis on each subsystem in real time according to the full-emission ratio of the photovoltaic group string accessed by each subsystem, positions the subsystems with low efficiency, and further controls the action of the switching device of the subsystems with low efficiency. According to the invention, the cloud service platform is combined with the subsystem to perform remote real-time performance analysis, and the performance analysis efficiency of the photovoltaic power station is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a photovoltaic power station performance analysis system disclosed in an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of another photovoltaic power plant performance analysis system disclosed in the embodiment of the present invention;
FIG. 3 is a schematic flow chart of a method for analyzing the performance of a photovoltaic power plant according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart illustrating a method for analyzing the performance of a first type subsystem according to an embodiment of the present invention;
FIG. 5 is a schematic flow chart illustrating a method for analyzing the performance of a first type subsystem according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of full-rate ratios of subsystems of a first type at different analysis times, according to an embodiment of the present invention;
FIG. 7 is a schematic flow chart illustrating a second type of subsystem performance analysis method according to an embodiment of the present invention;
FIG. 8 is a graphical illustration of a line plot of the full emission ratio K at 9:00 for a second type of subsystem disclosed in accordance with an embodiment of the present invention;
FIG. 9 is a graphical representation of a line plot of the full emission ratio K at 12:00 for a second type of subsystem disclosed in accordance with an embodiment of the present invention;
FIG. 10 is a graphical representation of a full emission ratio K at 15:00 for a second type of subsystem disclosed in accordance with an embodiment of the present invention;
fig. 11 is a flowchart illustrating a method for generating a probability distribution map of an inefficiency event according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention discloses a photovoltaic power station performance analysis system, which comprises: the photovoltaic power station performance analysis system comprises a cloud service platform and at least one subsystem in communication connection with the cloud service platform, the structure of the photovoltaic power station performance analysis system is shown in figure 1, N is larger than or equal to 1, each subsystem comprises an inverter with an edge computing function, so that the subsystem can compute the full-emission ratio of each photovoltaic group string accessed by the subsystem in real time, and the cloud service platform is used for performing performance analysis on the subsystem according to the full-emission ratio of each photovoltaic group string accessed by the subsystem.
The time granularity of the system performance analysis may be on the order of years, months, days, hours, or even minutes.
Further, the sub-systems are classified according to the topological structure of the photovoltaic power station, and the types of the sub-systems comprise: the inverter in the first type subsystem is a group string type inverter, and the inverter in the second type subsystem is a centralized inverter.
The inventor defines a full-emission ratio on the basis of counting the current dispersion rate of the low-efficiency subsystem and determining the correlation between the current dispersion rate of the low-efficiency subsystem and the system performance ratio, wherein the full-emission ratio represents the ratio between the direct current instantaneous output (direct current instantaneous power or direct current instantaneous current) of a certain photovoltaic string or subsystem and the rated value (actual rated installed capacity or maximum power point current) of the photovoltaic string or subsystem.
Specifically, the full power ratio of the photovoltaic string accessed by the first type of subsystem is as follows: the ratio of the direct current instantaneous power of the connected photovoltaic string to the rated installed capacity. The full power ratio of the photovoltaic group string accessed by the second type of subsystem is as follows: the ratio of the direct instantaneous current of the connected photovoltaic string to the nominal maximum power point current thereof.
The subsystem carries out secondary processing to the data collection, calculates the full-distribution ratio, has reduced the data bulk of real-time transmission between subsystem and the cloud service platform, reaches and reduces communication pressure, combines through "cloud limit" when realizing that the cloud service platform carries out long-range real-time performance analysis to subsystem, improves photovoltaic power plant performance analysis efficiency.
Further, referring to fig. 2, the photovoltaic power station performance analysis system further includes an automatic switching device corresponding to the subsystem, a front end of the automatic switching device is connected to a photovoltaic group string to which the subsystem is connected, and a rear end of the automatic switching device is connected to an inverter and an accessory device of the subsystem;
the cloud service platform is further used for sending a switching instruction to the subsystem corresponding to the photovoltaic group string under the condition that the inefficient photovoltaic group string is detected to exist, enabling an inverter in the subsystem to control the action of a switching device corresponding to the inverter, automatically switching, automatically optimizing the direct current side connection of the photovoltaic power station, enabling the low full-power-ratio subsystem to be integrated into a high full-power-ratio system, optimizing the system performance, and achieving the automatic technical improvement optimization effect of the direct current side array of the photovoltaic power station.
Based on the above-mentioned embodiment, the disclosed photovoltaic power station performance analysis system correspondingly discloses a photovoltaic power station performance analysis method applied to the photovoltaic power station performance analysis system, please refer to fig. 3, and the method includes the following steps:
s101: the subsystem calculates the full distribution ratio of each photovoltaic group string accessed by the subsystem in real time and sends the calculated full distribution ratio to the cloud service platform;
when the photovoltaic power station performance analysis system comprises a first type subsystem, the first type subsystem calculates the full power ratio of each photovoltaic group string accessed by the first type subsystem in real time, and the method comprises the following steps:
the first-class subsystem acquires the direct current instantaneous power of each photovoltaic group string accessed by the first-class subsystem;
and the first type subsystem calculates the ratio of the direct current instantaneous power of each photovoltaic group string accessed by the first type subsystem to the rated installed capacity of the first type subsystem to obtain the full power ratio of each photovoltaic group string accessed by the first type subsystem.
When the photovoltaic power station performance analysis system comprises a second type subsystem, the second type subsystem calculates the full power ratio of each photovoltaic group string accessed by the second type subsystem in real time, and the method comprises the following steps:
the second type subsystem acquires direct current instantaneous current of each photovoltaic group string connected with the second type subsystem;
and the second type subsystem calculates the ratio of the direct current instantaneous current of each photovoltaic group string connected with the second type subsystem to the nominal maximum power point current of the photovoltaic group string to obtain the full power ratio of each photovoltaic group string connected with the second type subsystem.
S102: and the cloud service platform performs performance analysis on the subsystem according to the full-sending ratio of each photovoltaic group string accessed by the subsystem.
Further, when the photovoltaic power plant performance analysis system further includes an automatic switching device corresponding to the subsystem, please refer to fig. 4, the embodiment further discloses a photovoltaic power plant performance analysis method, including the following steps:
s201: the subsystem calculates the full distribution ratio of each photovoltaic group string accessed by the subsystem in real time and sends the calculated full distribution ratio to the cloud service platform;
s202: and the cloud service platform performs performance analysis on the subsystem according to the full-sending ratio of each photovoltaic group string accessed by the subsystem.
S203: the cloud service platform sends a switching instruction to the subsystems with low efficiency under the condition that the subsystems with low efficiency are detected to exist;
s204: there is an inefficient subsystem control to its corresponding switching device action.
Specifically, when the photovoltaic power plant performance analysis system includes a plurality of first-class subsystems, please refer to fig. 5, the cloud service platform performs performance analysis on the subsystems according to a full-power-generation ratio of each photovoltaic group string accessed by the subsystem, including:
s301: the cloud service platform determines the full distribution ratio of each first-class subsystem according to the full distribution ratio of each photovoltaic group string accessed by each first-class subsystem;
s302: the cloud service platform judges whether an outlier exists in the full-emission ratio of each first-class subsystem at the same moment;
if an outlier exists, S303: the cloud service platform determines that the first type of subsystem corresponding to the outlier has low efficiency;
s304: the cloud service platform positions the first type of subsystem with low efficiency according to the topological structure of the photovoltaic power station;
if no outlier exists, S305: the cloud service platform determines that there is no inefficiency in all of the first class subsystems.
Further, in general, due to the fact that irradiation is strong in the noon time period, the power of the subsystem in the noon time period is the highest, the full emission ratio is also the highest, and if the cloud service platform detects that the full emission ratio of the first-class subsystem in the noon preset time period is lower than the full emission ratios of other operation time periods, which are low in efficiency, the orientation problem of the photovoltaic string accessed by the first-class subsystem is determined.
Generally, due to the fact that irradiation data in one day change in real time, the power of a subsystem in one day changes along with time, and the full-emission ratio also changes along with time, if no power limit exists, the full-emission ratio in the midday period or other periods with strong irradiation is larger than a preset value, if the cloud service platform detects that the full-emission ratio of the first type of subsystem with low efficiency is continuously smaller than the preset value in one day and the full-emission ratio changes along with time, it is determined that the photovoltaic group strings accessed by the first type of subsystem have power limit, and the full-emission ratio of the subsystem is limited within the range of the preset value.
If the photovoltaic string in the subsystem has dust accumulation, the power of the photovoltaic string does not change along with the time, the power is low, and the full power ratio of the subsystem does not change along with the time and is low. Therefore, when detecting that the full emission ratio of the first type of inefficient subsystem is continuously smaller than a preset value in one day and the full emission ratio does not change along with time, the cloud service platform determines that dust deposition exists in the photovoltaic group string accessed by the first type of subsystem.
Generally, if there is a fixed occlusion in the pv string, the power of the pv string is abnormal in a specific time period of the day, for example, the full power ratio of the subsystem is abnormal. Therefore, when detecting that the full-emission ratio of the first-class subsystem with low efficiency is abnormal in a specific time period in a day, the cloud service platform determines that the photovoltaic group string accessed by the first-class subsystem has fixed occlusion.
In a specific analysis process, in order to improve the accuracy of analysis, the influence of weather conditions on an analysis result needs to be reduced to the greatest extent, in the embodiment, a certain photovoltaic power station is used at typical analysis times of 9:00, 12:00 and 15:00 of 13 days 2 and 13 months 2017, and the full-power ratios of the first-class subsystems at the three times of the day are observed. And analyzing whether each photovoltaic group string in each first-class subsystem has an inefficiency condition or not by observing the consistency of the full-emission ratio. Fig. 6 shows the full-emission ratios of the first-class subsystems of a power station at 13/2 th day, wherein the three curves from top to bottom correspond to the full-emission ratios of the first-class subsystems of 13/2 th day at 12:00 am, 15:00 pm and 9:00 am.
FIG. 6 reflects that when the sun altitude is lower at 9:00 and 15:00, the fill-out ratio between the subsystems is really different, and the occlusion problem is suspected to exist; and when the 12:00 solar altitude is higher, the full-emission ratio consistency is better, and the shielding condition is lightened. And it can be seen from fig. 6 that a portion of the first type subsystems at 9:00 am exhibit a significant percentage of full-blown ratios below the mean and median levels, and these representative first type subsystems can be further analyzed to identify specific causes of subsystem inefficiency, such as heading problems, occlusion problems, dust accumulation problems, etc.
When the photovoltaic power station performance analysis system comprises a plurality of second-class subsystems, the working characteristics of electric energy collection are completed together with the direct current combiner box according to the requirements of the second-class subsystems, so that the number of photovoltaic strings accessed by the second-class subsystems is far larger than that of the first-class subsystems. In this case, when the second-class subsystem is analyzed, the number of the analyzed objects is too large, which is not favorable for comparative analysis, and the requirement for the data volume of the communication transmission is high, which is not favorable for high-density data analysis. Referring to fig. 7, the performance analysis of the subsystem is performed by the cloud service platform according to the full-sending ratio of each photovoltaic string accessed by the subsystem, and includes:
s401: and the cloud service platform draws a full-emission-ratio K line graph according to the full-emission ratios of all the accessed photovoltaic group strings in the second type of subsystem.
The horizontal axis of the full-power-generation-ratio K line graph represents time, the opening, the height, the bottom and the closing of the full-power-generation-ratio K line graph respectively correspond to the average number, the maximum value, the minimum value and the median of the full-power-generation ratio of all the accessed photovoltaic group strings in the subsystem, when a rising-falling column between the opening and the closing is hollow, the median is larger than the average number, and when the rising-falling column between the opening and the closing is solid, the median is smaller than the average number;
s402: and the cloud service platform determines whether the second type of subsystem has low efficiency according to the trend of the full-emission ratio K-line graph.
In a K line graph of a full power generation ratio, when the median is larger than the average number, namely a hollow 'column expansion' is presented, the extremely low value of the low-efficiency photovoltaic string is lower, and the photovoltaic string in a certain combiner box has serious low power generation capacity; when the median is smaller than the average number, namely a solid 'column drop' is presented, the extreme value of the inefficient photovoltaic string is less, and the power generation capacity of each photovoltaic string is more balanced. The degree of deviation can be determined by the length of the rising and falling column. The longer the rising and falling column is, the larger the total extreme value is, the more the total number of the inefficient branches of a certain combiner box is, and the more serious the situation is; the shorter or no rise and fall column is present, indicating that the extreme is milder. In more direct language, it can be stated that "the shorter the straight line, the better the straight line; the more solid columns, the shorter the better ".
According to the length of the full-emission ratio K line graph and the combination time, abnormal conditions such as shielding and the like can be judged; when the K line is still longer and the hollow columns are more and longer in the midday period, the problems that the orientation of a photovoltaic group string connected to a certain combiner box in the second type of subsystem is inconsistent can be determined.
Comparing with the analysis process of the first type of subsystem, still selecting 9:00, 12:00 and 15:00 of a certain photovoltaic power station in 2017, 2, 13 and month as typical analysis time, and drawing a full-emission ratio K line graph of each second type of subsystem at the three time of the current day. The full hair ratio K-line graph of 9:00 is shown in fig. 8, the full hair ratio K-line graph of 12:00 is shown in fig. 9, and the full hair ratio of 15:00 is shown in fig. 10.
It can be seen that, in the morning of 13 months at 9:00, the lengths of the K lines are generally longer, and the hollow columns are more, which indicates that the current of each branch of most of the combiner boxes does not reach full emission in the case of low solar altitude in the morning, and the mean value and the median of each K line fluctuate obviously, which indicates that the full emission degree of each combiner box is unbalanced, and a shielding condition occurs. At 12:00 noon in 13 days 2 months, the length of a K line is generally shorter, the average value and the median of the full-power-ratio of most of the confluence boxes can be read from the left coordinate axis and are close to or exceed 90%, the current of each branch of most of the confluence boxes is close to full power, and the fluctuation columns are not obvious, which shows that the shielding condition is relieved after the solar altitude at noon is increased. In fig. 10, a situation similar to that of fig. 8 is shown, in which the inefficient operation again occurs after the 15:00 solar altitude has decreased.
Further, in order to calculate the power generation loss caused by inefficiency, in the embodiment, the cloud service platform determines the photovoltaic string with the highest full-power ratio in each timestamp in each type of subsystem as the dynamic benchmarking string, that is, the dynamic benchmarking string in each type of subsystem can be determined at each timestamp. On the basis, the cloud service platform calculates the power generation amount difference between the dynamic marker post group string and other photovoltaic group strings in each type of subsystem through each timestamp, calculates the power generation amount loss amount, and achieves dynamic evaluation on the power generation amount loss of the photovoltaic power station.
Further, in order to improve the performance analysis efficiency of the photovoltaic power station, according to a preset analysis period, for example, historical data in the photovoltaic power station in the past year, the low-efficiency event probability distribution map is generated, so that the subsystem with a high low-efficiency frequency in the low-efficiency event probability distribution map is mainly monitored and analyzed.
Referring to fig. 11, the method for generating the probability distribution map of the low efficiency event disclosed in this embodiment includes the following steps:
s501: and the cloud service platform calculates the monthly system performance ratio of each subsystem according to the equivalent utilization hours and monthly accumulated irradiation of each subsystem in a preset analysis period.
The method for calculating the lunar system performance ratio of the subsystem may be a traditional system performance ratio calculation method, and may also be calculated according to the inefficient calculation model disclosed in this embodiment.
The cloud service platform counts the hourly accumulated irradiation quantity, the temperature, the hourly total power generation quantity and the hourly system performance ratio of a photovoltaic assembly in the photovoltaic power station in a preset analysis period, and correlatively fits the logarithmic change relationship between the system performance ratio and the temperature of the photovoltaic assembly to generate an inefficient calculation model between the temperature and the system performance ratio.
S502: and the cloud service platform performs ascending sequencing on the monthly system performance ratio of each subsystem, and acquires N ranked subsystems as low-efficiency subsystems.
N may be 5.
S503: the cloud service platform calculates the daily system performance ratio of each inefficient subsystem, and counts the inefficient frequency of the inefficient subsystem in a monthly range.
S504: and the cloud service platform positions the low-efficiency subsystem according to the topological structure of the photovoltaic power station.
S505: the cloud service platform counts the inefficient frequency of the inefficient subsystem in a preset analysis period, associates the inefficient events of the inefficient subsystem with the environmental factors, and generates an inefficient event probability distribution map marked with the corresponding relation between the environmental factors and the inefficient events of the inefficient subsystem.
In summary, the embodiments described above disclose methods for analyzing system performance of a photovoltaic power plant, which use a dynamic system Performance Ratio (PR) as a main line and perform hierarchical analysis on the performance of the photovoltaic power plant and the subsystems, perform different time granularities on the system performance ratio in a time dimension, and perform subsystem-level division and refinement analysis on the power plant in an analysis object dimension. The cloud side is combined, so that the performance analysis efficiency of the photovoltaic power station is improved while the cloud service platform carries out remote real-time performance analysis on the subsystem.
Further, according to environmental factors (inclined plane solar energy irradiation and photovoltaic module temperature) and power generation capacity, a logarithmic change relation between the system performance ratio and the module temperature is subjected to correlation fitting, and an inefficient calculation model between the temperature and the system performance ratio is generated and used for overall inefficient evaluation of the photovoltaic power station. Therefore, the historical data is used for calculating and evaluating the probability distribution condition of the areas with possible low efficiency or faults in the power station system, and the probability distribution condition is associated with the meteorological data to form a marked data set so as to provide data support for system performance analysis.
The method for analyzing the system performance of the photovoltaic power station disclosed by the embodiment is used for analyzing the performance of the whole photovoltaic power station and the performance of the subsystem, and under the condition that the low-efficiency photovoltaic group string is detected, the switching instruction is sent to the subsystem corresponding to the photovoltaic group string, so that the inverter in the subsystem controls the action of the switching device corresponding to the inverter, the switching is automatically carried out, the direct-current side connection of the photovoltaic power station is automatically optimized, the low-full-power-ratio subsystem is integrated into a high-full-power-ratio system, the system performance is optimized, and the automatic technical improvement optimization effect of the direct-current side array of the photovoltaic power station is achieved.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above embodiments can be combined arbitrarily, and the features described in the embodiments in the present specification can be replaced or combined with each other in the above description of the disclosed embodiments, so that those skilled in the art can implement or use the present application.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (18)
1. A photovoltaic power plant performance analysis system, comprising: the system comprises a cloud service platform and at least one subsystem in communication connection with the cloud service platform; wherein:
the subsystem comprises an inverter with an edge calculation function, so that the subsystem can calculate the full power ratio of each photovoltaic group string accessed by the subsystem in real time;
the cloud service platform is used for carrying out performance analysis on the subsystem according to the full distribution ratio of each photovoltaic group string accessed by the subsystem.
2. The system of claim 1, wherein the types of subsystems comprise: a first class and a second class;
the inverters in the first type subsystem are string inverters;
the inverters in the second type of subsystem are centralized inverters.
3. The system of claim 2, wherein the full-load ratio of the photovoltaic string accessed by the first type of subsystem is: the ratio of the direct current instantaneous power of the connected photovoltaic string to the rated installed capacity.
4. The system of claim 2, wherein the full-load ratio of the photovoltaic string accessed by the second type of subsystem is: the ratio of the direct instantaneous current of the connected photovoltaic string to the nominal maximum power point current thereof.
5. The system of claim 1, wherein the photovoltaic power plant performance analysis system further comprises an automatic switching device corresponding to the subsystem, a front end of the automatic switching device is connected with a photovoltaic group string accessed by the subsystem, and a rear end of the automatic switching device is connected with an inverter and an accessory device of the subsystem;
the cloud service platform is further used for sending a switching instruction to the subsystem corresponding to the photovoltaic group string under the condition that the inefficient photovoltaic group string is detected to exist, so that the inverter in the subsystem controls the switching device corresponding to the inverter to act.
6. A photovoltaic power plant performance analysis method applied to the photovoltaic power plant performance analysis system according to any one of claims 1 to 5, the method comprising:
the subsystem calculates the full distribution ratio of each photovoltaic group string accessed by the subsystem in real time and sends the calculated full distribution ratio to the cloud service platform;
and the cloud service platform performs performance analysis on the subsystem according to the full distribution ratio of each photovoltaic group string accessed by the subsystem.
7. The method of claim 6, wherein the type of subsystem comprises: a first class and a second class;
the inverters in the first type subsystem are string inverters;
the inverters in the second type of subsystem are centralized inverters.
8. The method of claim 7, wherein when the photovoltaic power plant performance analysis system includes the first type subsystem, the first type subsystem calculates, in real-time, a full-rate ratio for each string of photovoltaic groups to which it has access, including:
the first type subsystem acquires the direct current instantaneous power of each photovoltaic group string accessed by the first type subsystem;
and the first type subsystem calculates the ratio of the direct current instantaneous power of each photovoltaic group string accessed by the first type subsystem to the rated installed capacity of the first type subsystem to obtain the full power ratio of each photovoltaic group string accessed by the first type subsystem.
9. The method of claim 7, wherein when the photovoltaic power plant performance analysis system includes the second type of subsystem, the second type of subsystem calculates, in real-time, a full-rate for each string of photovoltaic groups it has access to, including:
the second type subsystem acquires direct current instantaneous current of each photovoltaic group string connected with the second type subsystem;
and the second type subsystem calculates the ratio of the direct current instantaneous current of each photovoltaic group string connected with the second type subsystem to the nominal maximum power point current of the photovoltaic group string to obtain the full power ratio of each photovoltaic group string connected with the second type subsystem.
10. The method of claim 7, wherein when the photovoltaic power plant performance analysis system comprises a plurality of subsystems of the first type, the cloud service platform performs performance analysis on the subsystems according to a full distribution ratio of each photovoltaic group string accessed by the subsystem, and the performance analysis comprises:
the cloud service platform determines the full distribution ratio of each first-class subsystem according to the full distribution ratio of each photovoltaic group string accessed by each first-class subsystem;
the cloud service platform judges whether an outlier exists in the full-emission ratio of each first-class subsystem at the same moment;
if an outlier exists, the cloud service platform determines that the first-class subsystem corresponding to the outlier has low efficiency, and positions the first-class subsystem with low efficiency according to a topological structure of the photovoltaic power station;
if no outlier exists, the cloud service platform determines that no inefficiency exists in all the first type subsystems.
11. The method of claim 10, further comprising:
when the cloud service platform detects that the full sending ratio of the first type of subsystem in the middle preset period is lower than the full sending ratio of other operation periods, the cloud service platform determines that the orientation problem exists in the photovoltaic group string accessed by the first type of subsystem;
the cloud service platform determines that power limitation exists in a photovoltaic group string accessed by the first type of subsystem when detecting that the full sending ratio of the first type of subsystem with low efficiency is continuously smaller than a preset value in one day and the full sending ratio changes along with time;
when the cloud service platform detects that the full emission ratio of the first type of subsystem with low efficiency is continuously smaller than a preset value in one day and the full emission ratio does not change along with time, determining that dust deposition exists in a photovoltaic group string accessed by the first type of subsystem;
the cloud service platform determines that a photovoltaic group string accessed by the first type subsystem has fixed occlusion when detecting that the full-emission ratio of the first type subsystem with low efficiency is abnormal in a specific time period in a day.
12. The method of claim 7, wherein when the photovoltaic power plant performance analysis system comprises the second type of subsystem, the cloud service platform performs performance analysis on the subsystem according to a full-distribution ratio of each photovoltaic group string accessed by the subsystem, and the method comprises:
the cloud service platform draws a full-emission ratio K line graph according to the full-emission ratios of all the accessed photovoltaic group strings in the second type subsystem, wherein the opening, the tray height, the tray bottom and the tray of the full-emission ratio K line graph respectively correspond to the average number, the maximum value, the minimum value and the median of the full-emission ratios of all the accessed photovoltaic group strings in the subsystem, when a rising and falling column between the opening tray and the tray is hollow, the median is larger than the average number, and when the rising and falling column between the opening tray and the tray is solid, the median is smaller than the average number;
and the cloud service platform determines whether the second type of subsystem has low efficiency according to the trend of the full emission ratio K line graph.
13. The method of claim 12, wherein the cloud service platform determining whether the second class of subsystem is inefficient based on the trend of the full emission ratio K-line graph comprises:
when the cloud service platform detects that hollow rising and falling columns exist in the full-emission ratio K line graph of the second type of subsystem, determining that the second type of subsystem has low efficiency, and positioning the second type of subsystem with low efficiency according to a topological structure of a photovoltaic power station;
when the cloud service platform detects that a hollow rising and falling column exists in the full-power-generation ratio K line graph of the second type of subsystem in a preset time period at noon, the cloud service platform determines that the orientation of the photovoltaic group strings accessed by the second type of subsystem is inconsistent.
14. The method of claim 7, further comprising:
the cloud service platform determines the photovoltaic group string with the highest full-load ratio in each timestamp in each type of subsystem as a dynamic benchmark group string;
and the cloud service platform calculates the power generation amount loss amount by respectively calculating the power generation amount difference between the dynamic marker post group string and other photovoltaic group strings in each type of subsystem at each timestamp.
15. The method of claim 6, further comprising:
the cloud service platform counts the hourly accumulated irradiation quantity, the temperature, the hourly total power generation quantity and the hourly system performance ratio of a photovoltaic assembly in the photovoltaic power station in a preset analysis period, and correlatively fits the logarithmic change relationship between the system performance ratio and the temperature of the photovoltaic assembly to generate an inefficient calculation model between the temperature and the system performance ratio.
16. The method of claim 6, further comprising:
the cloud service platform calculates the monthly system performance ratio of each subsystem according to the equivalent utilization hours and monthly accumulated irradiation of each subsystem in a preset analysis period;
the cloud service platform carries out ascending sequencing on the monthly system performance ratio of each subsystem, and N ranked subsystems are obtained and serve as low-efficiency subsystems;
the cloud service platform calculates the daily system performance ratio of each low-efficiency subsystem, and counts the low-efficiency frequency of the low-efficiency subsystem in a monthly range;
and the cloud service platform positions the low-efficiency subsystem according to the topological structure of the photovoltaic power station.
17. The method of claim 16, further comprising:
the cloud service platform counts the inefficient frequency of the inefficient subsystem in a preset analysis period, associates the inefficient events of the inefficient subsystem with environmental factors, and generates an inefficient event probability distribution map marked with the corresponding relation between the environmental factors and the inefficient events of the inefficient subsystem.
18. The method of claim 6, wherein when the photovoltaic power plant performance analysis system further comprises an automatic switching device corresponding to the subsystem, the method further comprises:
the cloud service platform sends a switching instruction to the subsystems with low efficiency under the condition that the subsystems with low efficiency are detected to exist;
there is an inefficiency of the subsystem controlling the switching device action corresponding thereto.
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