LU505097B1 - Energy loss monitoring system for photovoltaic power generation systems - Google Patents
Energy loss monitoring system for photovoltaic power generation systems Download PDFInfo
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- 238000010248 power generation Methods 0.000 title claims abstract description 49
- 238000012544 monitoring process Methods 0.000 title claims abstract description 41
- 238000001514 detection method Methods 0.000 claims abstract description 50
- 238000000034 method Methods 0.000 claims abstract description 12
- 238000006243 chemical reaction Methods 0.000 claims description 59
- 239000003344 environmental pollutant Substances 0.000 claims description 23
- 231100000719 pollutant Toxicity 0.000 claims description 23
- 230000008569 process Effects 0.000 claims description 8
- 238000012935 Averaging Methods 0.000 claims description 5
- 230000001960 triggered effect Effects 0.000 claims description 5
- 238000012417 linear regression Methods 0.000 claims description 4
- 230000008859 change Effects 0.000 claims description 3
- 238000011109 contamination Methods 0.000 claims description 3
- 230000005611 electricity Effects 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 description 5
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- 230000014509 gene expression Effects 0.000 description 2
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Classifications
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
- H02S50/00—Monitoring or testing of PV systems, e.g. load balancing or fault identification
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
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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
- H02J13/00001—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 the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
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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
- H02J13/00002—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 monitoring
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
- H02S50/00—Monitoring or testing of PV systems, e.g. load balancing or fault identification
- H02S50/10—Testing of PV devices, e.g. of PV modules or single PV cells
Abstract
The present invention discloses an energy loss monitoring system for photovoltaic power generation systems, including a detection module, an analysis comparison module and a control module, wherein the detection module is connected to each photovoltaic assembly, and the analysis comparison module is connected to the detection module; a prediction module connected to the analysis and comparison module, a display alarm module connected to the prediction module; according to the method, the internal component factors and external weather and pollution factors of the photovoltaic power generation system are used for predicting the energy loss, a rule between historical power data and weather and pollution coverage areas is established, the energy loss data is predicted, the lost generating capacity is estimated, and the prediction accuracy is enhanced.
Description
ENERGY LOSS MONITORING SYSTEM FOR PHOTOVOLTAIC POWER | LU505097
GENERATION SYSTEMS
The invention relates to the technical field of photovoltaic power generation, in particular to an energy loss monitoring system for photovoltaic power generation systems.
China's photovoltaic industry has developed rapidly in recent years, but the research focuses on component technology and construction cost control, and the research on photovoltaic operation and maintenance technology is relatively inadequate. While the power generation industry is facing the opportunity of rapid development of photovoltaic industry, it is also facing the operating pressure brought by the cancellation of subsidies. Therefore, in the future photovoltaic development mode, high-quality development and high-speed growth are equally important; In the process of photovoltaic power generation, the energy loss has a great impact on the economy and reliability of the photovoltaic system; in the prior art, aiming at energy loss detection, a mode of detecting the working efficiency of each photovoltaic module in real time is often adopted for energy loss analysis; however, the efficiency of photovoltaic power generation is restricted by a plurality of factors, not only the loss of the photovoltaic module, but also external factors; Secondly, in the prior art, the expression of the monitoring result of the loss is not concise and clear enough, so that the situation that workers make mistakes in judgment occurs from time to time, and the loss has been caused when the detection result is obtained, thereby attacking the economy of the photovoltaic power generation system; therefore, how to realize an energy loss monitoring system capable of comprehensively detecting the energy loss of the photovoltaic power generation system, predicting in advance and alarming in time becomes a problem to be solved in the technical field.
In order to solve the above problems, the present invention provides the following technical solutions: an energy loss monitoring system for photovoltaic power generation systems, including: the detection module is connected to each photovoltaic module and used for detecting the efficiency of the photovoltaic module;
the analysis and comparison module is connected to the detection module and used fb}505097 comparing the difference between the detection result and the standard and analyzing and storing the comparison resu ; the prediction module is connected to the analysis and comparison module and is used for searching the rule of the efficiency change of the photovoltaic module according to the stored historical result and predicting the efficiency of the photovoltaic module according to the rule; and the display alarm module is connected to the prediction module, and is used for displaying the detection result and the prediction result, displaying the relation between the prediction result and the variable factors, and alarming when the prediction result exceeds a set value.
Preferably, in the above an energy loss monitoring system for photo voltaic power generation systems, the detection module comprises: the first detection unit is connected to the photovoltaic string and is used for detecting the light-electricity conversion efficiency data; and that detection unit 2 is connecte with the inverter and use for detecting the DC-AC conversion efficiency data.
Preferably, in the above an energy loss monitoring system for photo voltaic power generation systems, the detection module further comprises:
The meteorological monitoring unit is connected to a local meteorological system and is used for acquiring meteorological historical data and meteorological forecast data; and that pollution monitor unit is arranged on the photovoltaic str and is used for performing image scanning on the photovoltaic str in real time and generating pollutant coverage data according to a scanning result.
Preferably, in the above an energy loss monitoring system for photo voltaic power generation systems, the analysis and comparison module comprises: the standard storage unit is preset with working efficiency standard data of each component in each type of photovoltaic power generation system; the analysis unit is connected to the standard storage unit and is used for acquiring the light- electricity conversion efficiency standard of the photovoltaic string and the DC-AC conversion efficiency standard of the inverter according to the type of the photovoltaic power generation system; the comparison unit is connected to the analysis unit, the first detection unit and the second detection unit, and is used for comparing the detected optical-electric conversion efficiency with an optical-electric conversion efficiency standard, comparing the detected DC-AC conversion efficiency data with the DC-AC conversion efficiency standard, and generating comparison results which are optical-electrical conversion loss data and DC-AC conversion loss data respectively;
and that database is connecte with the comparison unit and used for store the comparisdi°05097 result and dividing the comparison result according to the detection date.
Preferably, in the above an energy loss monitoring system for photo voltaic power generation systems, the prediction module comprises: the drawing unit is connected to the database and is used for drawing the comparison result and the corresponding detection date in the database into a trend curve graph which takes the date as an abscissa and light-electricity conversion loss data and DC-AC conversion loss data as ordinates; and the trend prediction unit is connected to the drawing unit and used for predicting the trend of the curve graph by using a multiple linear regression algorithm, acquiring a prediction trend curve graph within a fixed time limit, and acquiring prediction loss data caused by internal factors according to coordinates on the prediction trend curve graph.
Preferably, in the above an energy loss monitoring system for photo voltaic power generation systems, the prediction module further comprises: and the factor prediction unit is connected to the database, the weather monitoring unit and the pollution monitoring unit, and is used for corresponding a comparison result to the weather historical data and the pollutant coverage data according to the detection date of the optical- electrical conversion loss data, searching for a rule among the optical-electrical conversion loss data, the weather historical data and the pollutant coverage data, And generating prediction loss data caused by external factors according to the weather forecast data in combination with the law and the pollutant coverage data in combination with the law.
Preferably, in the above an energy loss monitoring system for photovoltaic power generation systems, the prediction process of the factor prediction unit comprises the following steps:
Step 1, substituting meteorological historical data and optical-electrical conversion loss data into a meteorological factor prediction model, obtaining meteorological coefficients of each date, averaging a plurality of meteorological coefficients, wherein the meteorological factor prediction model comprises the following steps of: P = K, * Q Wherein, P Is the optical-to-electrical conversion loss data, K; Is the meteorological coefficient, QHistorical meteorological data;
Step 2, substitute that pollutant coverage data and the optical-electrical conversion loss data into a pollution factor prediction model to obtain a pollution coefficient of each date, and average a plurality of pollution coefficients to obtain an average value as an average pollution coefficient, wherein the pollution factor prediction model is as followsP = K, * AWherein, PIs the optical-to- electrical conversion loss data, K,Is the contamination coefficient,AOverlay data for pollutants;
Step 3, accord to that pollution coefficientK, And meteorological coefficientK, Tablishing an external factor prediction model, wherein the external factor prediction model P = forte Wherein, K, Is the average meteorological coefficient, K, Is the average pollution 505097 coefficient;
Tep 4, substituting the weather forecast data into the external factor forecast model Q The pollutant coverage data at this moment is substituted into the external factor prediction model. AThe predicted optical-electrical conversion loss data is obtained. P.
Preferably, in the above an energy loss monitoring system for photo voltaic power generation systems, the display alarm module comprises: the display unit is connected to the trend prediction unit and the factor prediction unit, and is used for displaying the predicted loss data caused by the internal factors, the predicted loss data caused by the external factors and a trend curve graph through a display; the alarm analysis unit is connected to the display unit, a loss limit value 1 is preset in the alarm analysis unit, and an alarm instruction is triggered when any one of the predicted loss data caused by the internal factor and the predicted loss data caused by the external factor does not meet the loss limit value 1; and that voice broadcast unit is connecte with the alarm analysis unit and is used for receive the alarm instruction and performing voice broadcast according to the alarm instruction.
Preferably, in the above an energy loss monitoring system for photo voltaic power generation systems, the alarm analysis unit further comprises: combining the predicted loss data caused by the intrinsic factors and the predicted loss data caused by the intrinsic factors into total loss data, wherein a loss limit value 2 is preset in the alarm analysis unit, and an alarm instruction is triggered when the total loss data does not conform to the loss limit value 2.
Preferably, in the an energy loss monitoring system for photovoltaic power generation systems, the lost power generation amount before the prediction time is calculated based on the total loss data.
According to the technical scheme, compared with the prior art, the invention has the advantages that: 1. The invention predicts the energy loss through the internal component factors and the external weather and pollution factors of the photovoltaic power generation system, thereby improving the comprehensiveness of loss detection; 2, the method establishes the law among the historical power data, the weather and the surface pollution coverage area of the photovoltaic panel, predicts the energy loss data according to the law, further estimates the lost generated energy, and enhances the prediction accuracy;
and 3, the invention alarms according to the prediction data, and personnel can freely selee#505097 the alarm premise, thereby improving the alarm flexibility.
In order to more clearly illustrate the embodiments of the present invention or the technical 5 solutions in the prior art, the following will briefly introduce the drawings used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only embodiments of the present invention. For those of ordinary skill in the art, Other figures may also be derived from the figures provided.
Fig. 1 is a flow chart of that system of the present invention.
In the following, the technical solutions of the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only a part of embodiments, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work are within the scope of the present invention. In the following, the technical solutions of the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only a part of embodiments, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work are within the scope of the present invention.
In the present invention, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance; the term "plurality" is intended to mean two or more, unless explicitly defined otherwise. The terms "mounted", "connected", "coupled", and "secured" are to be construed in a broad sense. For example, the term "coupled" may be a fixed connection, a detachable connection, or an integral connection, the term "coupled" may be a direct connection, or an indirect connection through an intermediary. Those of ordinary skill in the art can understand the specific meaning of the above terms in the present invention according to specific situations.
In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "upper," "lower," "left," and "right" are based on the orientation or positional relationship shown in the drawings, merely for convenience of description of the present invention and simplification of description, It is not intended to indicate or imply that the devices or elements referred to must have a particular orientation, be constructed artd}505097 operate in a particular orientation, and therefore, is not to be construed as limiting the invention.
In the description of this specification, the terms "one embodiment," "some embodiments," "specific embodiments," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In the present specification, schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Example 1
In one embodiment, referring to fig. 1, an energy loss monitoring system for photovoltaic power generation systems includes: the detection module is connected to each photovoltaic module and used for detecting the efficiency of the photovoltaic module; the analysis and comparison module is connected to the detection module and used for comparing the difference between the detection result and the standard and analyzing and storing the comparison resu; the prediction module is connected to the analysis and comparison module and is used for searching the rule of the efficiency change of the photovoltaic module according to the stored historical result and predicting the efficiency of the photovoltaic module according to the rule; and the display alarm module is connected to the prediction module and used for displaying the detection result and the prediction result, displaying the relation between the prediction result and the variable factors, and alarming when the prediction result exceeds a set value. the principle of the above embodiment is to obtain the energy loss data of the photovoltaic power generation system by comparing the difference between the efficiency of each photovoltaic module and the standard efficiency, predict the loss of each photovoltaic module according to the loss data and the law of date, and give an alarm according to the prediction result.
The beneficial effects of the embodiment are that the prediction analysis is established, the seamless connection of detection, prediction and alarm is realized, the real-time loss prediction is provided for personnel, and the economy and reliability of the photovoltaic system are improved.
Example 2
In one embodiment, referring to fig. 1, an energy loss monitoring system for photovoltaic power generation systems, the detection module includes a first detection unit and a second detection unit; And that detection unit 2 is connecte with the inverter and use for detecting the DC-
AC conversion efficiency data, wherein the detection method for the photo-electric conversids#505097 efficiency and the DC-AC conversion efficiency is the prior art means; the analysis and comparison module comprises a standard storage unit, an analysis unit, a comparison unit and a database, wherein the standard storage unit is preset with work efficiency standard data of each component in each type of photovoltaic power generation system; The analysis unit is connected to the standard storage unit and is used for acquiring the light-electricity conversion efficiency standard of the photovoltaic string and the DC-AC conversion efficiency standard of the inverter according to the category of the photovoltaic power generation system; the comparison unit is connected to the analysis unit, the first detection unit and the second detection unit, and is used for comparing the detected optical-electric conversion efficiency with an optical- electric conversion efficiency standard, comparing the detected DC-AC conversion efficiency data with the DC-AC conversion efficiency standard, and generating comparison results which are optical-electrical conversion loss data and DC-AC conversion loss data respectively; the database is connected to the comparison unit and is used for storing the comparison result and dividing the comparison result according to the detection date; the prediction module comprises a drawing unit and a trend prediction unit, wherein the drawing unit is connected to the database and is used for drawing the comparison result in the database and the corresponding detection date into a trend curve graph which takes the date as an abscissa and light-electricity conversion loss data and DC-AC conversion loss data as ordinates;
The trend prediction unit is connected to the drawing unit and is used for predicting the trend of the curve graph by using a multiple linear regression algorithm to obtain a prediction trend curve graph within a fixed time limit and obtaining prediction loss data caused by internal factors according to coordinates on the prediction trend curve graph. the beneficial effect of the embodiment is that the reasons for the energy efficiency loss of the photovoltaic module are analyzed from the aspects of a photovoltaic array, a direct current lead, an alternating current lead, an inverter, a transformer and other components, and an analysis mathematical model is established by adopting a multiple linear regression algorithm to predict the energy efficiency loss of the inherent factors of the photovoltaic module.
Example 3
In one embodiment, referring to fig. 1, an energy loss monitoring system for photovoltaic power generation systems, the detection module further includes: the meteorological monitoring unit is connected to a local meteorological system and is used for acquiring meteorological historical data and meteorological forecast data; the temperature data is preferred for the meteorological historical data and the meteorological forecast data. In high temperature weather, the temperature of the photovoltaic cell will rise, which will lead to a decrease in its conversion efficiency. When the temperature of the photovoltaic cd{H505097 rises by 1 degree Celsius, its conversion efficiency will decrease by about 0.5%. Therefore, in high temperature weather, the power generation efficiency of the photovoltaic power station will be inhibited to a certain extent; Secondly, the rise of ambient temperature will lead to the temperature rise of photovoltaic modules. This will further affect the output power of photovoltaic power plants.
According to the data of the National Renewable Energy Laboratory (NREL) of the United States, the output power of photovoltaic modules will decrease by 0.5% ~ 0.7% for every 1 degree Celsius increase in high temperature in summer. In high temperature weather, the environmental humidity of photovoltaic power plants will also decrease, which will lead to increased pollution of photovoltaic modules and further affect the power generation efficiency; In high temperature weather, the increase of internal ambient temperature of photovoltaic power plant will also aggravate the aging rate of equipment, resulting in the shortening of equipment life. Therefore, it is necessary to pay attention to reducing the internal temperature of the photovoltaic power station in the design and operation process to reduce the aging speed of the equipment; therefore, the temperature data is selected as the meteorological data; the pollution monitoring unit is arranged on the photovoltaic string and is used for performing image scanning on the photovoltaic string in real time and generating pollutant coverage data according to a scanning resu ; the detection process of the pollutant coverage data comprises the following steps:
S1, shoot a photovoltaic panel through a scanning device to obtain a surface image of that photovoltaic panel;
S2, extracting a shadow range of the image by using a depth intelligent analysis system;
S3, acquire that surface area and the shadow coverage area of the photovoltaic panel,
S4, calculating the ratio of the shadow coverage area to the surface area of the photovoltaic panel, wherein the obtained ratio is pollutant coverage data; the forecasting module also comprises a factor forecasting unit which is connected to the database, the meteorological monitoring unit and the pollution monitoring unit, and is used for corresponding the comparison result to the meteorological historical data and the pollutant coverage data according to the detection date of the optical-electrical conversion loss data, searching for the rules among the optical-electrical conversion loss data, the meteorological historical data and the pollutant coverage data, Nerating forecast loss data caused by external factors according to the weather forecast data in combination with the law and the pollutant coverage data in combination with the law; the prediction process of the factor prediction unit comprises the following steps:
Step 1, substituting meteorological historical data and optical-electrical conversion loss dakd/>05097 into a meteorological factor prediction model to obtain a meteorological coefficient of each date, averaging a plurality of meteorological coefficients, wherein the meteorological factor prediction model comprises the following steps of: P = K, * Q Wherein, P Is the optical-to-electrical conversion loss data, K; Is the meteorological coefficient, Q Historical meteorological data;
Step 2, substituting the pollutant coverage data and the optical-electrical conversion loss data into a pollution factor prediction model to obtain a pollution coefficient of each date, averaging a plurality of pollution coefficients to obtain an average value as an average pollution coefficient, wherein the pollution factor prediction model P = K, * AWherein, PIs the optical-to-electrical conversion loss data,K, Is the contamination coefficient, AOverlay data for pollutants;
Step 3, accord to that pollution coefficientK, And meteorological coefficientK, The external factor prediction model is established as follows: P = fered Wherein, K; Is the average meteorological coefficient, K,Is the average pollution coefficient;
Step 4, substituting the weather forecast data into the external factor forecast modelQ The pollutant coverage data at this moment is substituted into the external factor prediction model. AThe predicted optical-electrical conversion loss data is obtained. P.
The beneficial effects of the embodiment are as follows: the meteorological information and the surface pollution of the photovoltaic panel are analyzed, the relation coefficient between the meteorological information and the surface pollution and the loss is calculated through a prediction model, and the energy efficiency loss of the photovoltaic module due to external factors is predicted according to the relation coefficient.
Example 4
In one embodiment, referring to fig. 1, an energy loss monitoring system for photovoltaic power generation systems, the display alarm module includes a display unit, an alarm analysis unit, and a voice broadcast unit; The display unit is connected to the trend prediction unit and the factor prediction unit and is used for displaying the prediction loss data caused by the internal factors, the prediction loss data caused by the external factors and the trend curve graph through a display;
The alarm analysis unit is connected to the display unit, the alarm analysis unit is preset with a loss limit value I, and an alarm instruction is triggered when any one of predicted loss data caused by internal factors and predicted loss data caused by external factors does not meet the loss limit value I; and the voice broadcast unit is connected to the alarm analysis unit and used for receiving the alarm instruction and performing voice broadcast according to the alarm instruction.
The beneficial effects of the embodiment are that the curve image, the intrinsic factor loss data and the extrinsic loss data are displayed by the display unit, so that the transparency of data display is enhanced, the display is simple and clear, and the situation that a worker makes a wrog/505097 judgment and loss is caused when a detection result is obtained is avoided; Voice broadcast is used to alarm, which reduces the time for personnel to know the details of the loss and facilitates the timely treatment of personnel.
Example 5
In one embodiment, referring to fig. 1, an energy loss monitoring system for photovoltaic power generation systems, the alarm analysis unit further includes: combining the predicted loss data caused by the internal factors and the predicted loss data caused by the internal factors into total loss data, presetting a loss limit value 2 by an alarm analysis unit, and triggering an alarm instruction when the total loss data does not conform to the loss limit value 2; calculating a power generation amount lost before a prediction time according to the total loss data; wherein, the loss limit value 1 and the loss limit value 2 are manually set.
The embodiment has the beneficial effects that different alarm precondition adjustments are set, the alarm is carried out according to the emphasis of the photovoltaic power generation system, the flexibility of the alarm is enhanced, and the lost generated energy during the loss period is convenient to estimate; and accurate alarm modes can be given to different power stations by manually setting the limit value.
It should be noted that, the system provided by the above embodiments is only illustrated by the division of the above functional modules, and in practical applications, the above functions may be allocated to different functional modules as required, that is, the modules or steps in the embodiments of the present invention are decomposed or combined, for example, the modules in the above embodiments may be combined into one module. It may also be further split into a plurality of sub-modules to perform all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for the purpose of distinguishing each module or step, and are not regarded as an improper limitation to the present invention.
The terms "comprises," "comprising," or any other similar phrase are intended to cover a non- exclusive inclusion, such that a process, method, article, or apparatus/device 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/device.
The technical scheme of the present invention has been described with reference to the preferred embodiments shown in the drawings, but those skilled in the art will readily understand that the scope of protection of the present invention is obviously not limited to these specific embodiments. On the premise of not deviating from the principle of the present invention, tho4&/505097 skilled in the art may make equivalent modifications or substitutions to the relevant technical features, and the technical solutions after such modifications or substitutions will fall within the scope of protection of the present invention.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit and scope of the invention. Thus, itis intended that the present invention also include such modifications and variations in the above description of the disclosed embodiments to enable those skilled in the art to make and use the invention provided they are within the scope of the appended claims and their equivalents. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be implemented in 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 (10)
1. An energy loss monitoring system for photo voltaic power generation systems comprising: a detection module is connected to each photovoltaic module and used for detecting the efficiency of the photovoltaic module; an analysis and comparison module is connected to the detection module and used for comparing the difference between the detection result and the standard and analyzing and storing the comparison result; a prediction module is connected to the analysis and comparison module and is used for searching the rule of the efficiency change of the photovoltaic module according to the stored historical result and predicting the efficiency of the photovoltaic module according to the rule; and a display alarm module is connected to the prediction module, and is used for displaying the detection result and the prediction result, displaying the relation between the prediction result and the variable factors, and alarming when the prediction result exceeds a set value.
2. The energy loss monitoring system for photovoltaic power generation systems according to claim 1, wherein the detection module comprises: a first detection unit is connected to a photovoltaic string and is used for detecting the light- electricity conversion efficiency data; and a second detection unit is connected to an inverter and use for detecting the DC-AC conversion efficiency data.
3. The energy loss monitoring system for photovoltaic power generation systems according to claim 2, wherein the detection module further comprises: a meteorological monitoring unit is connected to a local meteorological system and is used for acquiring meteorological historical data and meteorological forecast data; and a pollution monitor unit is arranged on the photovoltaic str and is used for performing image scanning on the photovoltaic str in real time and generating pollutant coverage data according to a scanning result.
4. The energy loss monitoring system for photovoltaic power generation systems according to claim 3, wherein the analyzing and comparing module comprises: a standard storage unit is preset with working efficiency standard data of each component in each type of photovoltaic power generation system; an analysis unit is connected to the standard storage unit and is used for acquiring the light- electricity conversion efficiency standard of the photovoltaic string and the DC-AC conversion efficiency standard of the inverter according to the type of the photovoltaic power generation system;
a comparison unit is connected to the analysis unit, the first detection unit and the secodd/505097 detection unit, and is used for comparing the detected optical-electric conversion efficiency with an optical-electric conversion efficiency standard, comparing the detected DC-AC conversion efficiency data with the DC-AC conversion efficiency standard, and generating comparison results which are optical-electrical conversion loss data and DC-AC conversion loss data respectively; and a database is connected to the comparison unit and used for store the comparison result and dividing the comparison result according to the detection date.
5. The energy loss monitoring system for photovoltaic power generation systems according to claim 4, wherein the prediction module comprises: a drawing unit is connected to the database and is used for drawing the comparison result and the corresponding detection date in the database into a trend curve graph which takes the date as an abscissa and light-electricity conversion loss data and DC-AC conversion loss data as ordinates; and a trend prediction unit is connected to the drawing unit and used for predicting the trend of the curve graph by using a multiple linear regression algorithm, acquiring a prediction trend curve graph within a fixed time limit, and acquiring prediction loss data caused by internal factors according to coordinates on the prediction trend curve graph.
6. The energy loss monitoring system for photovoltaic power generation systems according to claim 5, wherein the prediction module further comprises: a factor prediction unit is connected to the database, the weather monitoring unit and the pollution monitoring unit, and is used for corresponding a comparison result to the weather historical data and the pollutant coverage data according to the detection date of the optical- electrical conversion loss data, searching for a rule among the optical-electrical conversion loss data, the weather historical data and the pollutant coverage data, and generating prediction loss data caused by external factors according to the weather forecast data in combination with the law and the pollutant coverage data in combination with the law.
7. The energy loss monitoring system for photovoltaic power generation systems according to claim 6, wherein the prediction process of the factor prediction unit comprises the following steps: Step 1, substituting meteorological historical data and optical-electrical conversion loss data into a meteorological factor prediction model, obtaining meteorological coefficients of each date, averaging a plurality of meteorological coefficients, wherein the meteorological factor prediction model comprises the following steps of. P = K, * Q wherein, P is the optical-to-electrical conversion loss data, K, is the meteorological coefficient, Q historical meteorological data;
Step 2, substituting that pollutant coverage data and the optical-electrical conversion loss dakd/>05097 into a pollution factor prediction model to obtain a pollution coefficient of each date, and averaging a plurality of pollution coefficients to obtain an average value as an average pollution coefficient, wherein the pollution factor prediction model is as followsP = K, * A wherein, P is the optical-to- electrical conversion loss data, K, is the contamination coefficient, A overlay data for pollutants; Step 3, according to that pollution coefficient K, and meteorological coefficient K, tablishing an external factor prediction model, wherein the external factor prediction model P = Bart wherein,K, is the average meteorological coefficient,K> is the average pollution coefficient; and Step 4, substituting the weather forecast data into the external factor forecast model Q the pollutant coverage data at this moment is substituted into the external factor prediction model.A the predicted optical-electrical conversion loss data is obtained P.
8. The energy loss monitoring system for photovoltaic power generation systems according to claim 7, wherein the display alarm module comprises: a display unit is connected to the trend prediction unit and the factor prediction unit, and is used for displaying the predicted loss data caused by the internal factors, the predicted loss data caused by the external factors and a trend curve graph through a display; an alarm analysis unit is connected to the display unit, a loss limit value 1 is preset in the alarm analysis unit, and an alarm instruction is triggered when any one of the predicted loss data caused by the internal factor and the predicted loss data caused by the external factor does not meet the loss limit value 1; and a voice broadcast unit is connected to the alarm analysis unit and is used for receive the alarm instruction and performing voice broadcast according to the alarm instruction.
9. The energy loss monitoring system for photovoltaic power generation systems according to claim 8, wherein the alarm analysis unit further comprises: combining the predicted loss data caused by the intrinsic factors and the predicted loss data caused by the intrinsic factors into total loss data, wherein a loss limit value 2 is preset in the alarm analysis unit, and an alarm instruction is triggered when the total loss data does not conform to the loss limit value 2.
10. The energy loss monitoring system for photovoltaic power generation systems according to claim 9, wherein a lost power generation amount before the prediction time is calculated based on the total loss data.
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