CN112491142B - Photovoltaic power station performance analysis system and method - Google Patents
Photovoltaic power station performance analysis system and method Download PDFInfo
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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
- 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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- 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
- H02J50/00—Circuit arrangements or systems for wireless supply or distribution of electric power
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- 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
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
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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
- 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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- Photovoltaic Devices (AREA)
- Supply And Distribution Of Alternating Current (AREA)
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-power ratio of a photovoltaic group string accessed by the subsystem in real time by utilizing the edge calculation capability of an inverter and sends the full-power 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-power ratio of the photovoltaic group string accessed by each subsystem, and the subsystem with low efficiency is positioned, thereby controlling the action of a switching device of the subsystem with low efficiency. According to the invention, the cloud edge combination is used for realizing remote real-time performance analysis of the subsystem by the cloud service platform, and meanwhile, 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 high-speed development of the photovoltaic industry in China, the power generation performance of the photovoltaic power station is widely focused. Currently, the overall performance of a non-photoelectric conversion unit in a photovoltaic power plant system is typically analyzed by using a system performance ratio (PR, performance ratio) to achieve an overall evaluation of the photovoltaic power plant.
However, at present, the analysis object of the system performance ratio is the whole photovoltaic power station, and 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, so that the power generation performance of the photovoltaic power station can only be evaluated integrally, and the refined low-efficiency positioning can not be realized.
Disclosure of Invention
In view of the above, the invention provides a photovoltaic power station performance analysis system and a method for realizing the low-efficiency positioning of a subsystem of a photovoltaic power station.
In order to achieve the above purpose, the specific technical scheme provided by the invention is as follows:
a photovoltaic power plant performance analysis system, comprising: the cloud service platform and the at least one subsystem are 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 performing performance analysis on the subsystem according to the full-power 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 subsystem are string-type inverters;
the inverters in the second type of subsystem are centralized inverters.
Optionally, the full-power ratio of the photovoltaic group string accessed by the first type subsystem is: the ratio of the direct current instantaneous power of the connected photovoltaic string to the rated installed capacity.
Optionally, the full-emission ratio of the photovoltaic group string accessed by the second type subsystem is: the ratio of the direct current instantaneous current of the connected photovoltaic string to its nominal maximum power point current.
Optionally, the photovoltaic power station performance analysis system further comprises an automatic switching device corresponding to the subsystem, wherein the front end of the automatic switching device is connected with the photovoltaic group string accessed by the subsystem, and the rear end of the automatic switching device is connected with the inverter and accessory equipment 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 existence of the low-efficiency photovoltaic group string is detected, so that an inverter in the subsystem controls the switching device corresponding to the photovoltaic group string to act.
A photovoltaic power station performance analysis method is applied to the photovoltaic power station performance analysis system described in the above embodiment, and the method includes:
the subsystem calculates the full-power ratio of each photovoltaic group string accessed by the subsystem in real time, and sends the calculated full-power ratio to the cloud service platform;
and the cloud service platform performs performance analysis on the subsystem according to the full-power 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 subsystem are string-type inverters;
the inverters in the second type of subsystem are centralized inverters.
Optionally, when the photovoltaic power station performance analysis system includes the first type subsystem, the first type subsystem calculates, in real time, a full power ratio of each photovoltaic group string to which the first type subsystem is connected, including:
the first type subsystem obtains the direct current instantaneous power of each photovoltaic group string accessed by the first type subsystem;
and the first subsystem calculates the ratio of the direct current instantaneous power of each photovoltaic group string accessed by the first subsystem to the rated installed capacity of the first subsystem to obtain the full-power ratio of each photovoltaic group string accessed by the first subsystem.
Optionally, when the photovoltaic power station performance analysis system includes the second type subsystem, the second type subsystem calculates, in real time, a full power ratio of each photovoltaic group string to which the second type subsystem is connected, including:
the second type subsystem obtains the 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 accessed by the second type subsystem to the nominal maximum power point current of the second type subsystem to obtain the full-power ratio of each photovoltaic group string accessed by the second type subsystem.
Optionally, when the photovoltaic power station performance analysis system includes a plurality of the first-class subsystems, the cloud service platform performs performance analysis on the subsystems according to a full-power ratio of each photovoltaic group string accessed by the subsystems, and includes:
the cloud service platform determines the full-power ratio of each first type subsystem according to the full-power ratio of each photovoltaic group string accessed by each first type subsystem;
the cloud service platform judges whether outliers exist in the full-rate ratios of the first-class subsystems at the same moment;
if an outlier exists, the cloud service platform determines that the first type of subsystem corresponding to the outlier is inefficient, and positions the first type of subsystem with the inefficiency according to the topological structure of the photovoltaic power station;
and if the outlier does not exist, the cloud service platform determines that the inefficiency does not exist in all the first-type subsystems.
Optionally, the method further comprises:
when detecting that the full-power ratio of the first type subsystem with low efficiency in a preset noon period is smaller than that of other operation periods, the cloud service platform determines that the photovoltaic group strings accessed by the first type subsystem have an orientation problem;
the cloud service platform determines that the photovoltaic group strings accessed by the first type subsystem have power limitation when detecting that the full-power ratio of the first type subsystem with low efficiency is continuously smaller than a preset value in one day and the full-power ratio changes with time;
when the cloud service platform detects that the full-power ratio of the first type subsystem with low efficiency is continuously smaller than a preset value in one day and the full-power ratio is not changed with time, determining that dust accumulation exists in the photovoltaic group string accessed by the first type subsystem;
and when detecting that the full-rate of the first type subsystem with low efficiency exists in a specific period of the day, the cloud service platform determines that the photovoltaic group string accessed by the first type subsystem is fixedly shielded.
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 power ratio of each photovoltaic group string accessed by the subsystem, including:
the cloud service platform draws a full-power-ratio K line graph according to the full power ratio of all the access photovoltaic strings in the second type subsystem, wherein the opening, the disc height, the disc bottom and the receiving disc of the full-power-ratio K line graph respectively correspond to the average number, the maximum value, the minimum value and the median of the full power ratio of all the access photovoltaic strings in the subsystem, the median is larger than the average number when an expansion and drop column between the opening and the receiving disc is hollow, and the median is smaller than the average number when the expansion and drop column between the opening and the receiving disc is solid;
and the cloud service platform determines whether the second type subsystem is inefficient according to the trend of the full-power ratio K line graph.
Optionally, the cloud service platform determines whether the second type subsystem is inefficient according to the trend of the full-power-ratio K line graph, including:
when the cloud service platform detects that a hollow rising and falling column exists in the full-power-ratio K line graph of the second type subsystem, determining that the second type subsystem is inefficient, and positioning the second type subsystem with the inefficiency according to the topological structure of the photovoltaic power station;
when the cloud service platform detects that the hollow rising and falling columns exist in the full-power ratio K line graph of the second type subsystem in a preset midday period, the problem that the photovoltaic group strings accessed by the second type subsystem are inconsistent in orientation is determined.
Optionally, the method further comprises:
the cloud service platform respectively determines a photovoltaic group string with highest full-length ratio in each time stamp in each type of subsystem as a dynamic marker post group string;
and the cloud service platform calculates the generated energy loss through calculating the generated energy difference between the dynamic target rod group strings and other photovoltaic group strings in each type of subsystem at each time stamp.
Optionally, the method further comprises:
and the cloud service platform counts the accumulated irradiation quantity, temperature, total power generation amount and system performance ratio of each hour of the photovoltaic module in the photovoltaic power station in a preset analysis period, and the logarithmic change relation between the system performance ratio and the temperature of the photovoltaic module is associated and fitted to generate an inefficient calculation model between the temperature and the system performance ratio.
Optionally, the method further comprises:
the cloud service platform calculates the monthly system performance ratio of each subsystem according to the equivalent utilization hours and the monthly accumulated radiation of each subsystem in a preset analysis period;
the cloud service platform performs ascending order sequencing on the monthly system performance ratio of each subsystem to obtain N ranked subsystems serving as low-efficiency subsystems;
the cloud service platform calculates the performance ratio of a daily system of each low-efficiency subsystem, and counts the low-efficiency frequency of the low-efficiency subsystem in a month 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 comprises:
the cloud service platform counts the low-efficiency frequency of the low-efficiency subsystem in a preset analysis period, associates the low-efficiency event of the low-efficiency subsystem with an environmental factor, and generates a low-efficiency event probability distribution map marked with the corresponding relation between the environmental factor and the low-efficiency event of the low-efficiency subsystem.
Optionally, when the photovoltaic power station 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 subsystem with inefficiency under the condition that the subsystem with inefficiency is detected;
the subsystem with inefficiency controls the action of the switching device corresponding to the subsystem.
Compared with the prior art, the invention has the following beneficial effects:
according to the photovoltaic power station performance analysis system disclosed by the invention, the photovoltaic power station is divided into a plurality of subsystems, the full-power ratio of the photovoltaic group string accessed by each subsystem is calculated in real time by utilizing the edge calculation capability of the inverter, and the full-power ratio is sent to the cloud service platform, so that the cloud service platform performs performance analysis on each subsystem in real time according to the full-power ratio of the photovoltaic group string accessed by each subsystem, and the subsystem with low efficiency is positioned, so that the switching device of the subsystem with low efficiency is controlled to act. According to the invention, the cloud edge combination is used for realizing remote real-time performance analysis of the subsystem by the cloud service platform, and meanwhile, 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 that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a photovoltaic power station performance analysis system according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of another photovoltaic power station performance analysis system according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a photovoltaic power station performance analysis method according to an embodiment of the present invention;
FIG. 4 is a flow chart of a first class of subsystem performance analysis method according to an embodiment of the present invention;
FIG. 5 is a flow chart of a first class of subsystem performance analysis method according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of full-rate of a first type of subsystem at different analysis moments according to an embodiment of the present invention;
FIG. 7 is a flow chart of a second class of subsystem performance analysis method according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of a full-power K-ray diagram of a second class subsystem at 9:00 according to an embodiment of the present invention;
FIG. 9 is a schematic diagram of a full-power K-ray diagram of a second class subsystem at 12:00 according to an embodiment of the present invention;
FIG. 10 is a schematic diagram of a full-power K-ray diagram of a second class subsystem at 15:00 according to an embodiment of the present invention;
FIG. 11 is a flow chart of a method for generating an inefficiency event probability distribution map according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention discloses a photovoltaic power station performance analysis system, which comprises: the structure of the photovoltaic power station performance analysis system is shown in figure 1, N is more than or equal to 1, wherein each subsystem comprises an inverter with an edge calculation function, so that the full-power ratio of each photovoltaic group string accessed by the subsystem can be calculated in real time, and the cloud service platform is used for performing performance analysis on the subsystem according to the full-power ratio of each photovoltaic group string accessed by the subsystem.
The temporal granularity of the system performance analysis may be in the order of grade, month, day, hour, or even minute.
Further, subsystem classification is performed according to the topology structure of the photovoltaic power station, and the types of the subsystems include: the inverters in the first type subsystem are group string type inverters, and the inverters in the second type subsystem are centralized type inverters.
The inventor defines the full power ratio on the basis of the correlation between the current discrete rate of the low-efficiency subsystem and the system performance ratio by counting the current discrete rate of the low-efficiency subsystem, wherein the full power ratio in the embodiment 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 group string accessed by the first type subsystem is as follows: the ratio of the direct current instantaneous power of the connected photovoltaic string to the rated installed capacity. The full-emission ratio of the photovoltaic group string accessed by the second type subsystem is as follows: the ratio of the direct current instantaneous current of the connected photovoltaic string to its nominal maximum power point current.
The subsystem calculates the full-power ratio by carrying out secondary processing on the acquired data, reduces the data volume of real-time transmission between the subsystem and the cloud service platform, achieves the purpose of reducing communication pressure, and improves the performance analysis efficiency of the photovoltaic power station while realizing remote real-time performance analysis on the subsystem by the cloud service platform through 'cloud edge combination'.
Further, referring to fig. 2, the photovoltaic power station performance analysis system further includes an automatic switching device corresponding to the subsystem, wherein the front end of the automatic switching device is connected with the photovoltaic string connected with the subsystem, and the rear end of the automatic switching device is connected with the inverter and the auxiliary equipment of the subsystem;
the cloud service platform is also used for sending a switching instruction to a subsystem corresponding to the photovoltaic group string under the condition that the existence of the low-efficiency photovoltaic group string is detected, so that an inverter in the subsystem controls the action of a switching device corresponding to the photovoltaic group string, switching is automated, direct-current side connection of a photovoltaic power station is automatically optimized, the low-full-power-ratio subsystem is integrated into a Gao Man-power-ratio system, system performance is optimized, and the automatic technical-improvement optimizing effect of the direct-current side array of the photovoltaic power station is achieved.
Based on the above embodiment, the present embodiment correspondingly discloses a photovoltaic power station performance analysis method applied to the photovoltaic power station performance analysis system, please refer to fig. 3, the method includes the following steps:
s101: the subsystem calculates the full-power ratio of each photovoltaic group string accessed by the subsystem in real time, and sends the calculated full-power 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 subsystem obtains the direct current instantaneous power of each photovoltaic group string accessed by the first subsystem;
the first subsystem calculates the ratio of the direct current instantaneous power of each photovoltaic group string accessed by the first subsystem to the rated installed capacity of the first subsystem to obtain the full-power ratio of each photovoltaic group string accessed by the first 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 obtains the 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 accessed by the second type subsystem to the nominal maximum power point current of the second type subsystem to obtain the full-power ratio of each photovoltaic group string accessed by the second type subsystem.
S102: and the cloud service platform performs performance analysis on the subsystem according to the full-power ratio of each photovoltaic group string accessed by the subsystem.
Further, when the photovoltaic power station performance analysis system further includes an automatic switching device corresponding to the subsystem, referring to fig. 4, the embodiment further discloses a photovoltaic power station performance analysis method, which includes the following steps:
s201: the subsystem calculates the full-power ratio of each photovoltaic group string accessed by the subsystem in real time, and sends the calculated full-power ratio to the cloud service platform;
s202: and the cloud service platform performs performance analysis on the subsystem according to the full-power ratio of each photovoltaic group string accessed by the subsystem.
S203: the cloud service platform sends switching instructions to the subsystem with low efficiency under the condition that the subsystem with low efficiency is detected;
s204: there is an inefficiency in the subsystem to control the action of the switching device corresponding thereto.
Specifically, when the photovoltaic power station performance analysis system includes a plurality of first-class subsystems, referring to fig. 5, the cloud service platform performs performance analysis on the subsystems according to the full power ratio of each photovoltaic string accessed by the subsystems, including:
s301: the cloud service platform determines the full-power ratio of each first-class subsystem according to the full-power ratio of each photovoltaic group string accessed by each first-class subsystem;
s302: the cloud service platform judges whether outliers exist in the full-sending ratios of all the first-class subsystems at the same moment;
if there is an outlier, S303: the cloud service platform determines that the first type subsystem corresponding to the outlier is inefficient;
s304: the cloud service platform positions the first subsystem with low efficiency according to the topological structure of the photovoltaic power station;
if there is no outlier, S305: the cloud service platform determines that there is no inefficiency for all of the first type of subsystems.
Further, generally, because the radiation is stronger in the noon period, the power of the subsystem in the noon period is highest, and the full-power ratio is highest accordingly, if the cloud service platform detects that the full-power ratio of the first type of subsystem with low efficiency in the noon preset period is smaller than the full-power ratio of the first type of subsystem in other operation periods, the photovoltaic group string accessed by the first type of subsystem is determined to have an orientation problem.
In general, as irradiation data in one day changes in real time, the power of a subsystem in one day changes with time, the full-power ratio also changes with time, if no power limit exists, the full-power ratio in noon period or other periods with strong irradiation can be larger than a preset value, if the full-power ratio of a first subsystem with low efficiency is detected to be continuously smaller than the preset value in one day by the cloud service platform and changes with time, the power limit exists in a photovoltaic group string accessed by the first subsystem, and the full-power ratio of the subsystem is limited within the preset value range.
If dust accumulation exists in the photovoltaic string in the subsystem, the power of the photovoltaic string does not change with time, the power is lower, and the full power ratio of the subsystem does not change with time and is lower. Therefore, when the cloud service platform detects that the full-power ratio of the first-class subsystem with low efficiency is continuously smaller than a preset value in one day and the full-power ratio is not changed with time, the cloud service platform determines that dust accumulation exists in the photovoltaic group string accessed by the first-class subsystem.
In general, if there is a fixed shielding of the photovoltaic string, the power of the photovoltaic string is abnormal, such as abnormally low, and the full power ratio of the subsystem is also abnormal at a specific time period in the day. Therefore, when the cloud service platform detects that the full-rate of the first-class subsystem with low efficiency exists in a specific period of the day, the cloud service platform determines that the photovoltaic group string accessed by the first-class subsystem is fixedly shielded.
In a specific analysis process, in order to improve the accuracy of the analysis, the influence of weather conditions on an analysis result needs to be reduced to the greatest extent, and in this embodiment, a photovoltaic power station is used to observe the full-power ratio of each first-class subsystem at three times of the day at typical analysis times of 9:00, 12:00 and 15:00 of 13 of 2 months of 2017. And analyzing whether each photovoltaic group string in each first-class subsystem has an inefficiency condition or not by observing consistency of full-power ratio. For example, as shown in fig. 6, three curves from top to bottom correspond to the full power ratio of each first type subsystem of 12:00 noon, 15:00 pm and 9:00 a.m. on 13 days of 2 months.
FIG. 6 reflects that at lower 9:00 and 15:00 solar altitude, the full-rate between subsystems is truly large, suspected of occlusion problems; and when the solar altitude of 12:00 is higher, the consistency of the full-length ratio is better, and the shielding condition is reduced. And it can be seen from fig. 6 that there are some first type subsystems at 9:00 am that show significant full-hair ratios below average and median levels, and these representative first type subsystems can be further analyzed to identify the causes that specifically lead to subsystem inefficiency, such as orientation problems, occlusion problems, dust retention 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 connected into the second-class subsystems is far greater than that of the first-class subsystems. In the case of analyzing the second type subsystem, the number of the analysis objects is too large, which is not beneficial to comparison analysis, and the requirement on the data volume of communication transmission is high, which is not beneficial to high-density data analysis. Referring to fig. 7, the cloud service platform performs performance analysis on the subsystem according to the full-power ratio of each photovoltaic string accessed by the subsystem, including:
s401: and the cloud service platform draws a full-power ratio K line graph according to the full-power ratio of all the accessed photovoltaic group strings in the second type subsystem.
The horizontal axis of the full-power-ratio K line graph represents time, the opening, the disc height, the disc bottom and the closing disc of the full-power-ratio K line graph respectively correspond to the average number, the maximum value, the minimum value and the median of the full-power-ratio of all the connected photovoltaic group strings in the subsystem, the median is larger than the average number when an expansion and drop column between the opening disc and the closing disc is hollow, and the median is smaller than the average number when the expansion and drop column between the opening disc and the closing disc is solid;
s402: and the cloud service platform determines whether the second type subsystem is inefficient according to the trend of the full-power-ratio K line graph.
In the full-emission-ratio K line graph, when the number of middle bits is larger than the average number, namely, the hollow column is represented, the extremely low value of the low-efficiency photovoltaic group string is lower, and the serious low power generation capacity exists in a certain busbar box with the photovoltaic group string; when the number of the middle bits is smaller than the average number, namely the solid falling column is shown, the extreme value of the low-efficiency photovoltaic group strings is smaller, and the power generation capacity of each photovoltaic group string is balanced. The deviation degree can be judged by the length of the rising and falling column. The longer the rising and falling column is, the larger the total quantity of the extreme values is, the more the total quantity of the low-efficiency branches of a certain junction box is, and the more serious the situation is; the shorter the rising and falling column or the no rising and falling column is present, the more slight the extreme case is. Described in a more direct language, it can be stated that the shorter the straight line, the better the upper the straight line; the more and the shorter the solid posts, the better.
According to the length of the full-shot ratio K line graph and the combination time, abnormal conditions such as shielding can be judged; when the K line is still longer and the hollow columns are more and longer in the midday period, the problem that the photovoltaic group strings accessed by a certain junction box in the second type subsystem are inconsistent in orientation can be determined.
In analogy to the analysis process of the first type subsystem, 9:00, 12:00 and 15:00 of a certain photovoltaic power station on the 13 th 2 nd 2017 are still selected as typical analysis moments, and full-power ratio K line diagrams of the second type subsystems on the three moments of the same day are drawn. The full-rate K-line plot of 9:00 is shown in FIG. 8, the full-rate K-line plot of 12:00 is shown in FIG. 9, and the full-rate of 15:00 is shown in FIG. 10.
It can be seen that the lengths of K lines are generally longer and the hollow columns are more in the morning of 9:00 a.2 months and 13 a.m., which means that the currents of all branches of most of the junction boxes do not reach full distribution under the condition of low solar altitude in the morning, and mean and median fluctuation of all K lines are obvious, which means that the full distribution degree of all the junction boxes is unbalanced and the shielding condition occurs. The length of the K line is generally shorter at 12:00 PM in 13 days of 2 months, the average value and the median of the full-rate of most of the junction boxes can be read out from the left coordinate axis, the currents of all the branches of most of the junction boxes are close to full-rate, and the rising and falling columns are not obvious, so 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, i.e. the inefficient operation is again resumed after the 15:00 solar altitude has been reduced.
Further, in order to calculate the power generation loss caused by inefficiency, in this embodiment, the cloud service platform determines the photovoltaic string with the highest full-power ratio in each timestamp in each subsystem as the dynamic benchmarking string, that is, the dynamic benchmarking string in each subsystem can be determined in each timestamp. On the basis, the cloud service platform calculates the generated energy loss through calculating the generated energy difference between the dynamic marker post group strings and other photovoltaic group strings in each type of subsystem at each time stamp, and realizes the dynamic evaluation of the generated energy loss of the photovoltaic power station.
Further, in order to improve the performance analysis efficiency of the photovoltaic power station, the embodiment generates the low-efficiency event probability distribution map according to a preset analysis period, such as historical data in the photovoltaic power station in the past year, so as to realize key monitoring and analysis on the subsystem with higher low-efficiency frequency in the low-efficiency event probability distribution map.
Referring to fig. 11, the method for generating an inefficient event probability distribution map disclosed in the present 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 the monthly accumulated radiation of each subsystem in a preset analysis period.
The method for calculating the monthly system performance ratio of the subsystem can be a traditional system performance ratio calculating method, and can also calculate according to the low-efficiency calculation model disclosed by the embodiment.
The cloud service platform counts accumulated irradiation quantity, temperature, total power generation amount and system performance ratio of the photovoltaic module in the photovoltaic power station in each hour in a preset analysis period, and the logarithmic change relation between the system performance ratio and the temperature of the photovoltaic module is associated and fitted to generate an inefficient calculation model between the temperature and the system performance ratio.
S502: and the cloud service platform performs ascending order sequencing on the monthly system performance ratio of each subsystem to obtain N subsystems after ranking as low-efficiency subsystems.
N may be 5.
S503: the cloud service platform calculates the performance ratio of the day-level system of each low-efficiency subsystem, and counts the low-efficiency frequency of the low-efficiency subsystem in the month 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 low-efficiency frequency of the low-efficiency subsystem in a preset analysis period, correlates the low-efficiency event of the low-efficiency subsystem with the environmental factor, and generates a low-efficiency event probability distribution map marked with the corresponding relation between the environmental factor and the low-efficiency event of the low-efficiency subsystem.
In summary, the above embodiment discloses a method for analyzing the performance of a photovoltaic power station system, which uses a dynamic system Performance Ratio (PR) as a main line, analyzes the performance of the photovoltaic power station and subsystems in a hierarchical level, analyzes the system performance ratio in a time dimension at different time granularities, and performs sub-system level division refinement analysis granularity on the power station in an analysis object dimension. The cloud edge combination is used for realizing remote real-time performance analysis of the subsystem by the cloud service platform and improving the performance analysis efficiency of the photovoltaic power station.
Further, according to the environmental factors (inclined plane solar irradiation, photovoltaic module temperature) and the generated energy, the logarithmic change relation between the system performance ratio and the module temperature is correlated and fitted, and an inefficient calculation model between the temperature and the system performance ratio is generated and used for evaluating the overall inefficiency of the photovoltaic power station. The historical data is used for calculating and evaluating probability distribution conditions of areas which possibly have inefficiency or faults in the power station system, the probability distribution conditions are associated with meteorological data, a marked data set is formed, and data support is provided for system performance analysis.
According to the photovoltaic power station system performance analysis method disclosed by the embodiment, performance analysis on the whole photovoltaic power station and a subsystem level is realized, and when the existence of an inefficient photovoltaic group string is detected, a switching instruction is sent to a subsystem corresponding to the photovoltaic group string, so that an inverter in the subsystem controls a switching device corresponding to the inverter to act, switching is automated, direct-current side connection of the photovoltaic power station is automatically optimized, the subsystem with a low full-power ratio is integrated into a Gao Man transmission system, system performance is optimized, and an automatic technical improvement optimization effect of a direct-current side array of the photovoltaic power station is achieved.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
It is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The 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. The software modules may be disposed 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 may be combined in any manner, and features described in the embodiments in the present specification may be replaced or combined with each other in the above description of the disclosed embodiments, so as to enable one skilled in the art to make 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 (16)
1. A photovoltaic power plant performance analysis system, comprising: the cloud service platform and the at least one subsystem are in communication connection with the cloud service platform; wherein the types of the subsystems include: a first class and a second class; the inverters in the first subsystem are string-type inverters; the inverter in the second type subsystem is a centralized inverter;
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 full-power ratio represents the ratio between the direct current instantaneous output of a photovoltaic string or subsystem and the rated value of the photovoltaic string or subsystem;
the cloud service platform is used for performing performance analysis on the subsystem according to the full-power ratio of each photovoltaic group string accessed by the subsystem; according to the subsystem types included in the photovoltaic power station performance analysis system, the cloud service platform selectively determines whether the first type subsystem is low-efficiency by judging whether an outlier exists in the full-power ratio of the first type subsystem or whether the second type subsystem is low-efficiency by drawing a full-power ratio K line graph of the second type subsystem for performance analysis.
2. The system of claim 1, wherein the full ratio of strings of photovoltaic groups 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.
3. The system of claim 1, wherein the full ratio of strings of photovoltaic groups accessed by the second class of subsystems is: the ratio of the direct current instantaneous current of the connected photovoltaic string to its nominal maximum power point current.
4. The system of claim 1, wherein the photovoltaic power plant performance analysis system further comprises an automatic switching device corresponding to the subsystem, the front end of the automatic switching device is connected with the photovoltaic group string to which the subsystem is connected, and the rear end of the automatic switching device is connected with the inverter and auxiliary equipment 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 existence of the low-efficiency photovoltaic group string is detected, so that an inverter in the subsystem controls the switching device corresponding to the photovoltaic group string to act.
5. A method of photovoltaic power plant performance analysis, characterized in that it is applied to a photovoltaic power plant performance analysis system according to any one of claims 1 to 4, said method comprising:
the subsystem calculates the full-power ratio of each photovoltaic group string accessed by the subsystem in real time, and sends the calculated full-power ratio to the cloud service platform;
and the cloud service platform performs performance analysis on the subsystem according to the full-power ratio of each photovoltaic group string accessed by the subsystem.
6. The method of claim 5, wherein when the photovoltaic power plant performance analysis system includes the first type of subsystem, the first type of subsystem calculates in real time a full power ratio of each photovoltaic string to which it is connected, comprising:
the first type subsystem obtains the direct current instantaneous power of each photovoltaic group string accessed by the first type subsystem;
and the first subsystem calculates the ratio of the direct current instantaneous power of each photovoltaic group string accessed by the first subsystem to the rated installed capacity of the first subsystem to obtain the full-power ratio of each photovoltaic group string accessed by the first subsystem.
7. The method of claim 5, wherein when the photovoltaic power plant performance analysis system includes the second class subsystem, the second class subsystem calculates in real time a full-power ratio of each photovoltaic string to which it is connected, comprising:
the second type subsystem obtains the 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 accessed by the second type subsystem to the nominal maximum power point current of the second type subsystem to obtain the full-power ratio of each photovoltaic group string accessed by the second type subsystem.
8. The method of claim 5, wherein when the photovoltaic power plant performance analysis system includes a plurality of the first type of subsystems, the cloud service platform performs performance analysis on the subsystems according to a full power ratio of each photovoltaic string to which the subsystems are connected, including:
the cloud service platform determines the full-power ratio of each first type subsystem according to the full-power ratio of each photovoltaic group string accessed by each first type subsystem;
the cloud service platform judges whether outliers exist in the full-rate ratios of the first-class subsystems at the same moment;
if an outlier exists, the cloud service platform determines that the first type of subsystem corresponding to the outlier is inefficient, and positions the first type of subsystem with the inefficiency according to the topological structure of the photovoltaic power station;
and if the outlier does not exist, the cloud service platform determines that the inefficiency does not exist in all the first-type subsystems.
9. The method of claim 8, wherein the method further comprises:
when detecting that the full-power ratio of the first type subsystem with low efficiency in a preset noon period is smaller than that of other operation periods, the cloud service platform determines that the photovoltaic group strings accessed by the first type subsystem have an orientation problem;
the cloud service platform determines that the photovoltaic group strings accessed by the first type subsystem have power limitation when detecting that the full-power ratio of the first type subsystem with low efficiency is continuously smaller than a preset value in one day and the full-power ratio changes with time;
when the cloud service platform detects that the full-power ratio of the first type subsystem with low efficiency is continuously smaller than a preset value in one day and the full-power ratio is not changed with time, determining that dust accumulation exists in the photovoltaic group string accessed by the first type subsystem;
and when detecting that the full-rate of the first type subsystem with low efficiency exists in a specific period of the day, the cloud service platform determines that the photovoltaic group string accessed by the first type subsystem is fixedly shielded.
10. The method of claim 5, wherein when the photovoltaic power plant performance analysis system includes the second type of subsystem, the cloud service platform performs performance analysis on the subsystem according to a full power ratio of each photovoltaic string accessed by the subsystem, including:
the cloud service platform draws a full-power-ratio K line graph according to the full power ratio of all the access photovoltaic strings in the second type subsystem, wherein the opening, the disc height, the disc bottom and the receiving disc of the full-power-ratio K line graph respectively correspond to the average number, the maximum value, the minimum value and the median of the full power ratio of all the access photovoltaic strings in the subsystem, the median is larger than the average number when an expansion and drop column between the opening and the receiving disc is hollow, and the median is smaller than the average number when the expansion and drop column between the opening and the receiving disc is solid;
and the cloud service platform determines whether the second type subsystem is inefficient according to the trend of the full-power ratio K line graph.
11. The method of claim 10, wherein the cloud service platform determining whether the second type of subsystem is inefficient based on the trend of the full-power-ratio K-wire diagram comprises:
when the cloud service platform detects that a hollow rising and falling column exists in the full-power-ratio K line graph of the second type subsystem, determining that the second type subsystem is inefficient, and positioning the second type subsystem with the inefficiency according to the topological structure of the photovoltaic power station;
when the cloud service platform detects that the hollow rising and falling columns exist in the full-power ratio K line graph of the second type subsystem in a preset midday period, the problem that the photovoltaic group strings accessed by the second type subsystem are inconsistent in orientation is determined.
12. The method of claim 5, wherein the method further comprises:
the cloud service platform respectively determines a photovoltaic group string with highest full-length ratio in each time stamp in each type of subsystem as a dynamic marker post group string;
and the cloud service platform calculates the generated energy loss through calculating the generated energy difference between the dynamic target rod group strings and other photovoltaic group strings in each type of subsystem at each time stamp.
13. The method of claim 5, wherein the method further comprises:
and the cloud service platform counts the accumulated irradiation quantity, temperature, total power generation amount and system performance ratio of each hour of the photovoltaic module in the photovoltaic power station in a preset analysis period, and the logarithmic change relation between the system performance ratio and the temperature of the photovoltaic module is associated and fitted to generate an inefficient calculation model between the temperature and the system performance ratio.
14. The method of claim 5, wherein the method further comprises:
the cloud service platform calculates the monthly system performance ratio of each subsystem according to the equivalent utilization hours and the monthly accumulated radiation of each subsystem in a preset analysis period;
the cloud service platform performs ascending order sequencing on the monthly system performance ratio of each subsystem to obtain N ranked subsystems serving as low-efficiency subsystems;
the cloud service platform calculates the performance ratio of a daily system of each low-efficiency subsystem, and counts the low-efficiency frequency of the low-efficiency subsystem in a month range;
and the cloud service platform positions the low-efficiency subsystem according to the topological structure of the photovoltaic power station.
15. The method of claim 14, wherein the method further comprises:
the cloud service platform counts the low-efficiency frequency of the low-efficiency subsystem in a preset analysis period, associates the low-efficiency event of the low-efficiency subsystem with an environmental factor, and generates a low-efficiency event probability distribution map marked with the corresponding relation between the environmental factor and the low-efficiency event of the low-efficiency subsystem.
16. The method of claim 5, 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 subsystem with inefficiency under the condition that the subsystem with inefficiency is detected;
the subsystem with inefficiency controls the action of the switching device corresponding to the subsystem.
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