CN105337575A - Method and system for state prediction and fault diagnosis of photovoltaic power station - Google Patents
Method and system for state prediction and fault diagnosis of photovoltaic power station Download PDFInfo
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- CN105337575A CN105337575A CN201510795939.6A CN201510795939A CN105337575A CN 105337575 A CN105337575 A CN 105337575A CN 201510795939 A CN201510795939 A CN 201510795939A CN 105337575 A CN105337575 A CN 105337575A
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- 230000005855 radiation Effects 0.000 claims description 10
- 238000012423 maintenance Methods 0.000 claims description 7
- 238000012544 monitoring process Methods 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 2
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- 230000032683 aging Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000010248 power generation Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 208000024891 symptom Diseases 0.000 description 2
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 1
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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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- 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
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
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Abstract
The invention relates to a method for state prediction and fault diagnosis of a photovoltaic power station. The method comprises the following steps: acquiring a maximum power point current and current meteorological data of a photovoltaic string; calculating a theoretical generating voltage and a theoretical generating current of the photovoltaic string according to the current meteorological data and factory factors of the photovoltaic string; calculating a real-time generating efficiency of the photovoltaic string according to the theoretical generating current and a real-time generating current of the photovoltaic string, and calculating a generating efficiency change rate of the photovoltaic string according to the real-time generating efficiency; and performing state prediction and fault diagnosis on the photovoltaic string according to the generating efficiency change rate and a preset data model. The method and the system improve the efficiency of the state prediction and fault diagnosis of the photovoltaic power station, and moreover, an additional investment is unnecessarily increased, and the cost is low.
Description
Technical field
The present invention relates to technical field of photovoltaic power generation, particularly relate to a kind of photovoltaic plant status predication and method for diagnosing faults and system.
Background technology
Photovoltaic generation is a kind of important generation mode.The nucleus equipment of photo-voltaic power generation station is photovoltaic module, and current most photo-voltaic power generation station adopts polycrystal silicon cell assembly.The annual aging characteristic of polysilicon photovoltaic module is First Year ageing rate 3%, and it is 0.7% that Second Year starts annual aging characteristic, and useful life is 25 years.Generally speaking, theoretical year rate of return on investment of photovoltaic plant is about 8% ~ 12%, and the photovoltaic plant owner wants to regain all investments, and power station needs failure-free operation about 8 ~ 13 years.But because photovoltaic generating system number of devices is huge, the reasons such as photovoltaic generating system distribution remote geographic location, current photovoltaic plant traffic-operating period is also pessimistic.For guaranteeing the reliability service of photovoltaic plant, need to carry out data acquisition and monitoring to photovoltaic module, to carry out failure diagnosis and state estimation to photovoltaic module.
Mainly there is following problem in the failure diagnosis of current photovoltaic generating system and state estimation:
(1) failure diagnosis and the state estimation of photovoltaic module will be realized, need in theory to monitor each assembly, but consider construction cost, the especially medium-and-large-sized photovoltaic plant of current photovoltaic plant is only monitored photovoltaic group string, the dynamics of monitoring is inadequate, therefore causes and cannot effectively diagnose and state estimation;
(2) monitor data amount is large, and supervisory control system only stores and real-time exhibition data, fails to carry out rationally effectively process to data, cannot realize carrying out state estimation and failure diagnosis to photovoltaic plant;
(3) system management lacks digitlization means.Monitor message simply gathers and presents, and mass data form is by the manual process of Excel, and aggregation of data analysis ability is poor, and generating performance analysis and improvement lack quantification means, cannot realize multisystem unified management;
(4) method such as outer image analytical method, FUSION WITH MULTISENSOR DETECTION method, direct-to-ground capacitance mensuration and Time Domain Reflectometry analytic approach all needs to increase additional investment, and realizability is not strong.
Therefore, current photovoltaic generating system failure diagnosis and state estimation efficiency is low, cost is high.
Summary of the invention
Based on this, be necessary the failure diagnosis for current photovoltaic generating system and state estimation efficiency is low, cost is high problem, a kind of photovoltaic plant status predication and method for diagnosing faults and system are provided.
A kind of photovoltaic plant status predication and method for diagnosing faults, comprise the following steps:
Gather maximum power point electric current and the current weather data of photovoltaic group string;
According to theoretical generating voltage and the theoretical generation current of the calculation of parameter photovoltaic group string that dispatches from the factory of described current weather data and photovoltaic group string;
Calculate the real-time generating efficiency of photovoltaic group string according to the real-time generation current of described theoretical generation current and photovoltaic group string, and calculate the generating efficiency rate of change of photovoltaic group string according to described real-time generating efficiency;
According to described generating efficiency rate of change and preset data model, status predication and failure diagnosis are carried out to photovoltaic group string.
A kind of photovoltaic plant status predication and fault diagnosis system, comprising:
Harvester, for gathering maximum power point electric current and the current weather data of photovoltaic group string;
First calculation element, for theoretical generating voltage and the theoretical generation current of the calculation of parameter photovoltaic group string that dispatches from the factory according to described current weather data and photovoltaic group string;
Second calculation element, for calculating the real-time generating efficiency of photovoltaic group string according to the real-time generation current of described theoretical generation current and photovoltaic group string, and calculates the generating efficiency rate of change of photovoltaic group string according to described real-time generating efficiency;
Predictive diagnosis device, for carrying out status predication and failure diagnosis according to described generating efficiency rate of change and preset data model to photovoltaic group string.
Described photovoltaic plant status predication and method for diagnosing faults and system, by gathering maximum power point electric current and the current weather data of photovoltaic group string, according to theoretical generating voltage and the theoretical generation current of the calculation of parameter photovoltaic group string that dispatches from the factory of described current weather data and photovoltaic group string, the real-time generating efficiency of photovoltaic group string is calculated according to the real-time generation current of described theoretical generation current and photovoltaic group string, and the generating efficiency rate of change of photovoltaic group string is calculated according to described real-time generating efficiency, according to described generating efficiency rate of change and preset data model, status predication and failure diagnosis are carried out to photovoltaic group string, improve the efficiency of photovoltaic plant status predication and failure diagnosis, and without the need to increasing additional investment, cost is low.
Accompanying drawing explanation
Fig. 1 is photovoltaic plant status predication and the method for diagnosing faults flow chart of an embodiment;
Fig. 2 is the method flow diagram that the employing experts database of an embodiment and diagnostic model carry out failure diagnosis;
Fig. 3 is the method flow diagram of the generated power forecasting of an embodiment;
Fig. 4 is the method flow diagram of the maintenance key point of an embodiment;
Fig. 5 is the photovoltaic plant status predication of an embodiment and the structural representation of fault diagnosis system.
Embodiment
Below in conjunction with accompanying drawing, technical scheme of the present invention is further elaborated.
Fig. 1 is photovoltaic plant status predication and the method for diagnosing faults flow chart of an embodiment.As shown in Figure 1, photovoltaic plant status predication of the present invention and method for diagnosing faults can comprise the following steps:
S1, gathers maximum power point electric current and the current weather data of photovoltaic group string;
S2, according to theoretical generating voltage and the theoretical generation current of the calculation of parameter photovoltaic group string that dispatches from the factory of described current weather data and photovoltaic group string;
S3, calculates the real-time generating efficiency of photovoltaic group string according to the real-time generation current of described theoretical generation current and photovoltaic group string, and calculates the generating efficiency rate of change of photovoltaic group string according to described real-time generating efficiency;
S4, carries out status predication and failure diagnosis according to described generating efficiency rate of change and preset data model to photovoltaic group string.
In one embodiment, maximum power point electric current and the current weather data of photovoltaic group string can first be gathered.Described current weather data can comprise surface temperature, wind speed and solar radiation degree.Current weather data are gathered by environment monitor.
After collecting related data, can according to the theoretical generating voltage of the calculation of parameter photovoltaic group string that dispatches from the factory of described current weather data and photovoltaic group string and theoretical generation current.Before calculating, pretreatment operation can be carried out to the data collected, such as, digital filtering process, validity check, the conversion of engineering value, signal contact jitter elimination and scale can be carried out to the data collected and calculate.The time cycle that can also preset calculates the mean value of pretreated photovoltaic group string characteristic value and current weather data, and it is for subsequent use that described mean value is saved in background data base.Can according to the theoretical generation current of following formulae discovery photovoltaic group string:
I＝I
m*(S/S
ref)*(1+a*(T-T
ref))
In formula, I is the theoretical generation current of photovoltaic group string, I
mfor the maximum power point electric current of photovoltaic group string, S is solar radiation degree, S
reffor specified solar radiation degree, T is surface temperature, T
reffor surface temperature ratingly, a is constant.In one embodiment, a=0.0025/ DEG C.
Then, the real-time generating efficiency of photovoltaic group string can be calculated according to the real-time generation current of described theoretical generation current and photovoltaic group string, and calculate the generating efficiency rate of change of photovoltaic group string according to described real-time generating efficiency.The generating efficiency rate of change that differential is converted to photovoltaic group string can be carried out to described real-time generating efficiency.In one embodiment, difference and the generating efficiency of described theoretical generation current and real-time generation current can be calculated, and obtain the generating efficiency rate of change of generating efficiency in predetermined period.
Finally, status predication and failure diagnosis can be carried out according to described generating efficiency rate of change and preset data model to photovoltaic group string.In one embodiment, rate of change threshold value can be set.When rate of change is greater than the first thresholding, can be judged to be that open circuit fault appears in photovoltaic group string; When rate of change is less than the first thresholding and is greater than the second thresholding, can be judged to be that short trouble appears in photovoltaic group string; When rate of change is less than the second thresholding and is greater than the 3rd thresholding, can be judged to be that hot spot fault appears in photovoltaic group string; When rate of change is less than the 3rd thresholding, can be judged to be that photovoltaic group string is normal condition.
As shown in Figure 2, experts database and diagnostic model can be adopted, status predication and failure diagnosis are carried out to photovoltaic module, generating prediction and maintenance policy optimization can be realized simultaneously.Described experts database can comprise knowledge base and interpreter, and wherein, described knowledge base is for accessing the Heuristics, professional knowledge and the inferenctial knowledge that obtain with administrative institute, and described interpreter is used for making an explanation to the knowledge in knowledge base, and obtains the failure symptom table of comparisons.The characteristic value of photovoltaic group string and the historical state data of system and equipment can be monitored, and contrast with the data in current weather data and described failure symptom table, draw diagnosis.
As shown in Figure 3, also can predict generated output.As mentioned above, maximum power point electric current and the meteorological data of photovoltaic group string can be gathered, and calculate generating efficiency.Then, generating efficiency model can be set up according to described generating efficiency.Also can set up radiation patterns according to history meteorological data, and adopt this radiation patterns to carry out energy predicting.Finally, Efficiency correction can be carried out according to described efficiency Model to the energy doped, obtain predicted power.
As shown in Figure 4, also can be system customization maintenance key point strategy.On-line monitoring can be carried out to the historical performance of photovoltaic group string and current performance, the variation characteristic of photovoltaic group string parameter is drawn according to historical performance, and set up the life model of photovoltaic group string according to described variation characteristic, and predict the residual life of photovoltaic group string according to the current performance of photovoltaic group string and described life model.The limiting performance of photovoltaic group string is substituted into described residual life, the generated output of photovoltaic group string can be drawn.Corresponding maintenance policy can be formulated to the maintenance cost of photovoltaic group string according to described generated output.
Described photovoltaic plant status predication and method for diagnosing faults, by gathering maximum power point electric current and the current weather data of photovoltaic group string, according to theoretical generating voltage and the theoretical generation current of the calculation of parameter photovoltaic group string that dispatches from the factory of described current weather data and photovoltaic group string, the real-time generating efficiency of photovoltaic group string is calculated according to the real-time generation current of described theoretical generation current and photovoltaic group string, and the generating efficiency rate of change of photovoltaic group string is calculated according to described real-time generating efficiency, according to described generating efficiency rate of change and preset data model, status predication and failure diagnosis are carried out to photovoltaic group string, improve the efficiency of photovoltaic plant status predication and failure diagnosis, and without the need to increasing additional investment, cost is low.
Be described further below in conjunction with the embodiment of accompanying drawing to photovoltaic plant status predication of the present invention and fault diagnosis system.
Fig. 5 is the photovoltaic plant status predication of an embodiment and the structural representation of fault diagnosis system.As shown in Figure 5, photovoltaic plant status predication of the present invention and fault diagnosis system can comprise:
Harvester 10, for gathering maximum power point electric current and the current weather data of photovoltaic group string;
First calculation element 20, for theoretical generating voltage and the theoretical generation current of the calculation of parameter photovoltaic group string that dispatches from the factory according to described current weather data and photovoltaic group string;
Second calculation element 30, for calculating the real-time generating efficiency of photovoltaic group string according to the real-time generation current of described theoretical generation current and photovoltaic group string, and calculates the generating efficiency rate of change of photovoltaic group string according to described real-time generating efficiency;
Predictive diagnosis device 40, for carrying out status predication and failure diagnosis according to described generating efficiency rate of change and preset data model to photovoltaic group string.
Described photovoltaic plant status predication and fault diagnosis system, by gathering maximum power point electric current and the current weather data of photovoltaic group string, according to theoretical generating voltage and the theoretical generation current of the calculation of parameter photovoltaic group string that dispatches from the factory of described current weather data and photovoltaic group string, the real-time generating efficiency of photovoltaic group string is calculated according to the real-time generation current of described theoretical generation current and photovoltaic group string, and the generating efficiency rate of change of photovoltaic group string is calculated according to described real-time generating efficiency, according to described generating efficiency rate of change and preset data model, status predication and failure diagnosis are carried out to photovoltaic group string, improve the efficiency of photovoltaic plant status predication and failure diagnosis, and without the need to increasing additional investment, cost is low.
Photovoltaic plant status predication of the present invention and fault diagnosis system and photovoltaic plant status predication of the present invention and method for diagnosing faults one_to_one corresponding, the technical characteristic of setting forth in the embodiment of above-mentioned photovoltaic plant status predication and method for diagnosing faults and beneficial effect thereof are all applicable to, in the embodiment of photovoltaic plant status predication and fault diagnosis system, hereby state.
Each technical characteristic of the above embodiment can combine arbitrarily, for making description succinct, the all possible combination of each technical characteristic in above-described embodiment is not all described, but, as long as the combination of these technical characteristics does not exist contradiction, be all considered to be the scope that this specification is recorded.
The above embodiment only have expressed several execution mode of the present invention, and it describes comparatively concrete and detailed, but can not therefore be construed as limiting the scope of the patent.It should be pointed out that for the person of ordinary skill of the art, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.Therefore, the protection range of patent of the present invention should be as the criterion with claims.
Claims (10)
1. photovoltaic plant status predication and a method for diagnosing faults, is characterized in that, comprises the following steps:
Gather maximum power point electric current and the current weather data of photovoltaic group string;
According to theoretical generating voltage and the theoretical generation current of the calculation of parameter photovoltaic group string that dispatches from the factory of described current weather data and photovoltaic group string;
Calculate the real-time generating efficiency of photovoltaic group string according to the real-time generation current of described theoretical generation current and photovoltaic group string, and calculate the generating efficiency rate of change of photovoltaic group string according to described real-time generating efficiency;
According to described generating efficiency rate of change and preset data model, status predication and failure diagnosis are carried out to photovoltaic group string.
2. photovoltaic plant status predication according to claim 1 and method for diagnosing faults, is characterized in that, described current weather data comprise surface temperature, wind speed and solar radiation degree.
3. photovoltaic plant status predication according to claim 1 and method for diagnosing faults, is characterized in that, after the step gathering photovoltaic group string characteristic value and current weather data, also comprises:
Perform pretreatment operation to photovoltaic group string characteristic value and current weather data, described pretreatment operation comprises digital filtering process, validity check, the conversion of engineering value, signal contact jitter elimination and scale and calculates.
4. photovoltaic plant status predication according to claim 3 and method for diagnosing faults, is characterized in that, after described pretreatment operation, further comprising the steps of:
The mean value of pretreated photovoltaic group string characteristic value and current weather data is calculated with the time cycle of presetting;
Described mean value is saved in background data base.
5. photovoltaic plant status predication according to claim 1 and method for diagnosing faults, is characterized in that, the step calculating the theoretical generation current of photovoltaic group string according to described current weather data and photovoltaic group string characteristic value comprises:
Theoretical generation current according to following formulae discovery photovoltaic group string:
I＝I
m*(S/S
ref)*(1+a*(T-T
ref))
In formula, I is the theoretical generation current of photovoltaic group string, I
mfor the maximum power point electric current of photovoltaic group string, S is solar radiation degree, S
reffor specified solar radiation degree, T is surface temperature, T
reffor surface temperature ratingly, a is constant.
6. photovoltaic plant status predication according to claim 1 and method for diagnosing faults, it is characterized in that, calculate the real-time generating efficiency of photovoltaic group string according to the real-time generation current of described theoretical generation current and photovoltaic group string, and the step calculating the generating efficiency rate of change of photovoltaic group string according to described real-time generating efficiency comprises:
Calculate difference and the generating efficiency of described theoretical generation current and real-time generation current;
Obtain the generating efficiency rate of change of generating efficiency in predetermined period.
7. photovoltaic plant status predication according to claim 1 and method for diagnosing faults, is characterized in that, comprises the step that photovoltaic group string carries out status predication and failure diagnosis according to described generating efficiency rate of change and preset data model:
When rate of change is greater than the first thresholding, be judged to be that open circuit fault appears in photovoltaic group string;
When rate of change is less than the first thresholding and is greater than the second thresholding, be judged to be that short trouble appears in photovoltaic group string;
When rate of change is less than the second thresholding and is greater than the 3rd thresholding, be judged to be that hot spot fault appears in photovoltaic group string;
When rate of change is less than the 3rd thresholding, be judged to be that photovoltaic group string is normal condition.
8. photovoltaic plant status predication according to claim 1 and method for diagnosing faults, is characterized in that, further comprising the steps of:
On-line monitoring history meteorological data, sets up radiation patterns according to described history meteorological data, and adopts the generated output of described radiation patterns to photovoltaic group string to predict;
Generating efficiency model is set up according to described generating efficiency;
According to described generating efficiency model, described generated output is revised.
9. photovoltaic plant status predication according to claim 1 and method for diagnosing faults, is characterized in that, further comprising the steps of:
The current performance parameters of on-line monitoring photovoltaic group string and historical performance parameter;
According to the Parameters variation characteristic of described historical performance parameter acquiring photovoltaic group string;
The life model of photovoltaic group string is set up according to described Parameters variation characteristic and current performance parameters;
According to the residual life of described life model prediction photovoltaic group string;
The limiting performance parameter of photovoltaic group string is substituted into described residual life, calculates the generated output of photovoltaic group string;
Maintenance cost according to described generated output and photovoltaic group string formulates maintenance policy.
10. photovoltaic plant status predication and a fault diagnosis system, is characterized in that, comprising:
Harvester, for gathering maximum power point electric current and the current weather data of photovoltaic group string;
First calculation element, for theoretical generating voltage and the theoretical generation current of the calculation of parameter photovoltaic group string that dispatches from the factory according to described current weather data and photovoltaic group string;
Second calculation element, for calculating the real-time generating efficiency of photovoltaic group string according to the real-time generation current of described theoretical generation current and photovoltaic group string, and calculates the generating efficiency rate of change of photovoltaic group string according to described real-time generating efficiency;
Predictive diagnosis device, for carrying out status predication and failure diagnosis according to described generating efficiency rate of change and preset data model to photovoltaic group string.
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| CN106705368A (en) * | 2016-12-30 | 2017-05-24 | 美的集团股份有限公司 | Method and device for prejudging domestic appliance faults and domestic appliance |
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| CN108418547A (en) * | 2018-05-07 | 2018-08-17 | 北京汉能光伏投资有限公司 | Domestic solar outgoing electrical measurement test system |
| CN108418547B (en) * | 2018-05-07 | 2024-03-08 | 东君新能源有限公司 | Solar outdoor power generation test system |
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| CN109271736A (en) * | 2018-10-12 | 2019-01-25 | 阳光电源股份有限公司 | The fault type judges method and device of photovoltaic module |
| CN109271736B (en) * | 2018-10-12 | 2023-02-03 | 阳光电源股份有限公司 | Fault type determination method and device for photovoltaic module |
| CN109743018A (en) * | 2018-11-21 | 2019-05-10 | 中国葛洲坝集团电力有限责任公司 | Photovoltaic power station grading forewarning system method based on big data statistics |
| CN112682972A (en) * | 2020-12-16 | 2021-04-20 | 苏州西热节能环保技术有限公司 | Quick performance diagnosis device for concentrating solar power station |
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