CN106100580A - A kind of method that photovoltaic plant equipment fault monitors in real time - Google Patents
A kind of method that photovoltaic plant equipment fault monitors in real time Download PDFInfo
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- CN106100580A CN106100580A CN201610637409.3A CN201610637409A CN106100580A CN 106100580 A CN106100580 A CN 106100580A CN 201610637409 A CN201610637409 A CN 201610637409A CN 106100580 A CN106100580 A CN 106100580A
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- 238000000034 method Methods 0.000 title claims abstract description 22
- 230000007257 malfunction Effects 0.000 claims abstract description 18
- 238000012423 maintenance Methods 0.000 claims abstract description 14
- 230000002085 persistent effect Effects 0.000 claims abstract description 11
- 238000012544 monitoring process Methods 0.000 claims description 47
- 238000013024 troubleshooting Methods 0.000 abstract description 2
- 238000005070 sampling Methods 0.000 description 3
- 230000005611 electricity Effects 0.000 description 2
- 238000005299 abrasion Methods 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000003749 cleanliness Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
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
-
- 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
- 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
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
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Abstract
The method that a kind of photovoltaic plant equipment fault that the present invention relates to monitors in real time, it is characterised in that it comprises the steps: step one, calculates datum drift b；Step 2, calculating real-time offsets d；Whether step 3, judgment bias relative mistake are in range of tolerable variance, if in range of tolerable variance, are then judged to " passing through "；Otherwise it is judged to " not passing through ", the most tentatively judges this branch equipment suspected malfunctions；Then judging whether the suspected malfunctions persistent period is in range of tolerable variance, if in range of tolerable variance, being then judged to " passing through ", being otherwise judged to " not passing through "；Step 4, be judged to " not passing through " branch trouble report to the police, operation maintenance personnel processes in time.The present invention combines the relative value's associate feature between each branch road of electric power station system, utilizes and contrasts with each adjacent legs, it is possible to judge each equipment fault position, power station rapidly and accurately, reduce the fault discovery time, improves troubleshooting speed；And simple reduction operation maintenance personnel labor intensity, it is easy to operation.
Description
Technical field
The present invention relates to a kind of method that photovoltaic plant equipment fault monitors in real time.
Background technology
Petering out at traditional energy, today that environment goes from bad to worse, solar energy is because of its cleanliness without any pollution, inexhaustible use
The feature such as inexhaustible, be considered the most potential product substituting tradition fossil energy.Solaode is that solar radiation is straight
Switching through the device turning to electric energy, because the motion of solaode mechanical, the features such as service life is long, and maintenance cost is low, are mesh
Front optimal photoelectric conversion device.Current people have recognized the crisis of environment and the energy, in world's policies of various countries energetically
Under support, photovoltaic plant is developed rapidly.
Photovoltaic power station system, mainly by photovoltaic battery panel, cable, header box, inverter, transformator and monitor protective system
Deng composition.System connected mode is: the series connection of 20 pieces of cell panels is a group string, and 12-16 props up group connection in series-parallel and is pooled to one and confluxes
Case, 6-8 header box parallel connection is pooled to an inverter, and to be pooled to a transformator low by collecting line for two inverter parallels
Pressure side, some transformator outlets are pooled to high-tension switch cabinet and send into electrical network.
Photovoltaic power station system is in running, because of battery pollution, short circuit, switching damage, circuit abrasion, the problem such as aging
The generated energy that can cause photovoltaic plant declines.Photovoltaic power station monitoring system can monitor photovoltaic cell string voltage, electric current, header box electricity
Pressure, electric current, the parameter such as photovoltaic DC-to-AC converter, the input and output side voltage of transformator, electric current, frequency, humiture.Current monitoring system
System can only monitoring device real-time parameter, it is impossible to data are analyzed contrast.When certain branch equipment breaks down, it is real-time
Monitoring value can change, because each branch road of photovoltaic plant is by the environmental influence such as illumination, temperature, its real time data exists always
Constantly change, unless this branch road does not the most work, monitoring data are zero, and operation maintenance personnel is difficult to timely discovering device problem.Thus
The most only meticulous inspection by operation maintenance personnel and the working experience according to operation maintenance personnel, could the concrete fault of discovering device fault
Position.I.e. have thousands of the monitoring data in real-time change in the face of power station, operation maintenance personnel is difficult to timely discovering device problem,
Its inefficiency, needs substantial amounts of energy to realize, and fault location time is long, it will causing trouble is disliked further
Change.
Summary of the invention
It is an object of the invention to overcome above-mentioned deficiency, it is provided that the relative value between a kind of each branch road of combination electric power station system is closed
Connection characteristic, utilizes and the method for each adjacent legs contrast, it is achieved the method that photovoltaic plant equipment fault monitors in real time.
The object of the present invention is achieved like this:
A kind of method that photovoltaic plant equipment fault monitors in real time, it comprises the steps:
Step one, obtained the properly functioning lower each branch road of photovoltaic plant by on-line monitoring and monitor data, be stored in data base；By light
The same each branch road monitoring data collected in unit under overhead utility is properly functioning carry out obtaining standard average a；By photovoltaic electric
Stand properly functioning under each branch road monitoring data and standard average a contrast, using its ratio as datum drift b；
Step 2, obtained each branch road monitoring data under photovoltaic plant real-time running state by on-line monitoring, be stored in data base；
Carry out obtaining real-time meansigma methods c by the same each branch road monitoring data collected in unit under photovoltaic plant real time execution；By light
Each branch road monitoring data and real-time meansigma methods c under overhead utility real time execution contrast, using its ratio as real-time offsets d；
Step 3, the real-time offsets d that each branch road monitoring data in step 2 are calculated and each branch road monitoring data in step one
The ratio of datum drift b calculated is referred to as deviation relative mistake, it is judged that whether deviation relative mistake is in range of tolerable variance, if holding
In the range of difference, then it is judged to " passing through "；Otherwise it is judged to " not passing through ", the most tentatively judges this branch equipment suspected malfunctions；Continue
Contrast this branch road, then judge whether this branch equipment suspected malfunctions persistent period is in range of tolerable variance, if in range of tolerable variance
In, then it is judged to " passing through ", is otherwise judged to " not passing through "；
Step 4, being judged to that the branch road of " not by " provides failure alarm signal, operation maintenance personnel is made a concrete analysis of this branch road and is respectively monitored
Parameter and according to practical experience failure judgement equipment and type；And process in time；The most again contrast this branch road, as sentenced
Break as " passing through ", then alarm release.
Each branch road monitoring data are group string electric current, the electric current of header box, voltage, power, the electric current of inverter, voltage, merit
Rate.
Deviation relative mistake range of tolerable variance and suspected malfunctions persistent period range of tolerable variance set according to the concrete condition in each power station.
Compared with prior art, the invention has the beneficial effects as follows:
The relative value that the method that photovoltaic plant equipment fault of the present invention monitors in real time combines between each branch road of electric power station system associates spy
Property, utilize and contrast with each adjacent legs, it is possible to judge each equipment fault position, power station rapidly and accurately, when reducing fault discovery
Between, improve troubleshooting speed；And simple reduction operation maintenance personnel labor intensity, it is easy to operation.
Accompanying drawing explanation
Fig. 1 is the flow chart of the present invention.
Detailed description of the invention
Seeing Fig. 1, the method that a kind of photovoltaic plant equipment fault that the present invention relates to monitors in real time, it includes walking as follows
Rapid:
Step one, obtained the properly functioning lower each branch road of photovoltaic plant by on-line monitoring and monitor data, be stored in data base；By light
The same each branch road monitoring data collected in unit under overhead utility is properly functioning carry out obtaining standard average a；By photovoltaic electric
Stand properly functioning under each branch road monitoring data and standard average a contrast, using its ratio as datum drift b；
Step 2, obtained each branch road monitoring data under photovoltaic plant real-time running state by on-line monitoring, be stored in data base；
Carry out obtaining real-time meansigma methods c by the same each branch road monitoring data collected in unit under photovoltaic plant real time execution；By light
Each branch road monitoring data and real-time meansigma methods c under overhead utility real time execution contrast, using its ratio as real-time offsets d；
Step 3, the real-time offsets d that each branch road monitoring data in step 2 are calculated and each branch road monitoring data in step one
The ratio of datum drift b calculated is referred to as deviation relative mistake, it is judged that whether deviation relative mistake is in range of tolerable variance, if holding
In the range of difference, then it is judged to " passing through "；Otherwise it is judged to " not passing through ", the most tentatively judges this branch equipment suspected malfunctions；Continue
Contrast this branch road, then judge whether this branch equipment suspected malfunctions persistent period is in range of tolerable variance, if in range of tolerable variance
In, then it is judged to " passing through ", is otherwise judged to " not passing through "；
Step 4, being judged to that the branch road of " not by " provides failure alarm signal, operation maintenance personnel is made a concrete analysis of this branch road and is respectively monitored
Parameter and according to practical experience failure judgement equipment and type；And process in time；The most again contrast this branch road, as sentenced
Break as " passing through ", then alarm release.
Above-mentioned each branch road monitoring data can be group string electric current, the electric current of header box, voltage, power, the electricity of inverter
Stream, voltage, power etc..
Above-mentioned deviation relative mistake range of tolerable variance and suspected malfunctions persistent period range of tolerable variance can concrete according to each power station
Situation sets.Deviation relative mistake range of tolerable variance and suspected malfunctions persistent period range of tolerable variance are preferably set to 10% and 20 minutes.
Select the test interval as required, the test that cost is minimum, step optimum test for this, it is preferably generally 5
Minute.
Embodiment 1:
Taking the monitoring data of each of certain power station a certain header box A group string, have 16 group strings under this header box A, every group string is by 20
Block 250WPa cell panel is composed in series.
By each of this header box A group string current monitoring value object as a comparison, by contrast of once sampling in 5 minutes, partially
Difference relative mistake range of tolerable variance and suspected malfunctions persistent period range of tolerable variance are set as 10% and 20 minutes.The test result of step one
As listed in table 1, the test result of step 2 is as listed in table 2.
The monitoring value of certain moment each branch road under table 1. header box A normal operating condition
Certain moment each branch road monitoring value under table 2. header box A real-time status
The 7th branch road suspected malfunctions of this header box A can be tentatively judged according to table 2.
Persistently contrasting, in 20 minutes, the deviation relative mistake of this branch road remains at more than 10%.
Then providing the alarm signal of this branch road, according to warning bypass position, operation maintenance personnel is checked to scene, finds this branch road
Have on a block assembly and cover a black plastic bag, take off rear alarm release.
Embodiment 2:
Taking the monitoring data of each of certain power station a certain header box B group string, have 16 group strings under this header box B, every group string is by 20
Block 250WPa cell panel is composed in series.
By each of this header box B group string current monitoring value object as a comparison, by contrast of once sampling in 5 minutes, partially
Difference relative mistake range of tolerable variance and suspected malfunctions persistent period range of tolerable variance are set as 10% and 20 minutes.The test result of step one
As listed in table 3, the test result of step 2 is as listed by table 4.
The monitoring value of certain moment each branch road under table 3. header box B normal operating condition
Certain moment each branch road monitoring value under table 4. header box B real-time status
| Branch road | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| Electric current | 4.232 | 4.311 | 4.706 | 4.760 | 4.023 | 3.665 | 4.623 | 4.454 |
| Real-time offsets | 0.979 | 0.997 | 1.089 | 1.101 | 0.931 | 0.848 | 1.070 | 1.030 |
| Datum drift | 1.000 | 0.950 | 1.073 | 1.029 | 0.975 | 1.075 | 0.930 | 1.050 |
| Deviation relative mistake | -2.1% | 4.7% | 1.4% | 6.6% | -4.8% | -26.8% | 13.0% | -1.9% |
| Branch road | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 |
| Electric current | 4.087 | 4.112 | 4.765 | 4.356 | 4.378 | 4.065 | 4.543 | 4.078 |
| Real-time offsets | 0.946 | 0.951 | 1.102 | 1.008 | 1.013 | 0.940 | 1.051 | 0.943 |
| Datum drift | 0.990 | 0.905 | 1.053 | 0.938 | 1.033 | 0.985 | 1.003 | 1.010 |
| Deviation relative mistake | -4.7% | 4.8% | 4.5% | 6.9% | -2.0% | -4.7% | 4.6% | -7.1% |
The 6th branch road suspected malfunctions of this header box B can be tentatively judged according to table 4.
Persistently contrasting, in 20 minutes, the deviation relative mistake of this branch road remains at more than 10%.
Then providing the alarm signal of this branch road, according to warning bypass position, operation maintenance personnel is checked to scene, finds this branch road
A block assembly is had to crush, alarm release after replacing.
Embodiment 3:
Take certain power station high-voltage switch gear collect on line five transformators (every transformator connects two inverters) upper amount to ten inverse
Becoming the monitoring data of device, every inverter capacity is 500KW.
Each inverter power monitoring is worth object as a comparison, and by contrast of once sampling in 5 minutes, deviation relative mistake held
Difference scope and suspected malfunctions persistent period range of tolerable variance are set as 10% and 20 minutes.The test result of step one as listed in table 5,
The test result of step 2 is as listed by table 6.
The monitoring value of certain moment each branch road under table 5. normal operating condition
| Inverter is numbered | 1 | 2 | 3 | 4 | 5 |
| Power (KW) | 230.5 | 225.8 | 268.2 | 245.9 | 265.6 |
| Datum drift | 0.940 | 0.921 | 1.094 | 1.003 | 1.084 |
| Inverter is numbered | 6 | 7 | 8 | 9 | 10 |
| Power (KW) | 278.8 | 212.8 | 239.6 | 264.4 | 219.3 |
| Datum drift | 1.138 | 0.868 | 0.978 | 1.079 | 0.895 |
The monitoring value of certain moment each branch road under table 6. real-time running state
| Inverter is numbered | 1 | 2 | 3 | 4 | 5 |
| Power (KW) | 158.4 | 154.1 | 180.7 | 179.1 | 186.9 |
| Real-time offsets | 0.941 | 0.915 | 1.074 | 1.064 | 1.111 |
| Datum drift | 0.940 | 0.921 | 1.094 | 1.003 | 1.084 |
| Deviation relative mistake | 0.0% | -0.6% | -1.9% | 6.1% | 2.5% |
| Inverter is numbered | 6 | 7 | 8 | 9 | 10 |
| Power (KW) | 192.2 | 150.0 | 140.1 | 182.1 | 159.5 |
| Real-time offsets | 1.142 | 0.891 | 0.833 | 1.082 | 0.948 |
| Datum drift | 1.138 | 0.868 | 0.978 | 1.079 | 0.895 |
| Deviation relative mistake | 0.4% | 2.6% | -14.8% | 0.3% | 5.9% |
The 8th inverter suspected malfunctions can be tentatively judged according to table 6.
Persistently contrasting, in 20 minutes, the deviation relative mistake of this branch road remains at more than 10%.
Then providing the alarm signal of this branch road, according to warning bypass position, operation maintenance personnel is checked to scene, finds this branch road
The wherein inlet wire tripping operation of 8 header box inlet wires of inverter, checks alarm release after fault-free combined floodgate.
Claims (3)
1. the method that a photovoltaic plant equipment fault monitors in real time, it is characterised in that it comprises the steps:
Step one, obtained the properly functioning lower each branch road of photovoltaic plant by on-line monitoring and monitor data, be stored in data base；By light
The same each branch road monitoring data collected in unit under overhead utility is properly functioning carry out obtaining standard average a；By photovoltaic electric
Stand properly functioning under each branch road monitoring data and standard average a contrast, using its ratio as datum drift b；
Step 2, obtained each branch road monitoring data under photovoltaic plant real-time running state by on-line monitoring, be stored in data base；
Carry out obtaining real-time meansigma methods c by the same each branch road monitoring data collected in unit under photovoltaic plant real time execution；By light
Each branch road monitoring data and real-time meansigma methods c under overhead utility real time execution contrast, using its ratio as real-time offsets d；
Step 3, the real-time offsets d that each branch road monitoring data in step 2 are calculated and each branch road monitoring data in step one
The ratio of datum drift b calculated is referred to as deviation relative mistake, it is judged that whether deviation relative mistake is in range of tolerable variance, if holding
In the range of difference, then it is judged to " passing through "；Otherwise it is judged to " not passing through ", the most tentatively judges this branch equipment suspected malfunctions；Continue
Contrast this branch road, then judge whether this branch equipment suspected malfunctions persistent period is in range of tolerable variance, if in range of tolerable variance
In, then it is judged to " passing through ", is otherwise judged to " not passing through "；
Step 4, being judged to that the branch road of " not by " provides failure alarm signal, operation maintenance personnel is made a concrete analysis of this branch road and is respectively monitored
Parameter and according to practical experience failure judgement equipment and type；And process in time；The most again contrast this branch road, as sentenced
Break as " passing through ", then alarm release.
The method that a kind of photovoltaic plant equipment fault the most according to claim 1 monitors in real time, it is characterised in that each branch road
Monitoring data are group string electric current, the electric current of header box, voltage, power, the electric current of inverter, voltage, power.
The method that a kind of photovoltaic plant equipment fault the most according to claim 1 monitors in real time, it is characterised in that deviation phase
Difference range of tolerable variance and suspected malfunctions persistent period range of tolerable variance are set according to the concrete condition in each power station.
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| CN107086857A (en) * | 2017-06-09 | 2017-08-22 | 上海历挚机电设备有限公司 | A kind of photovoltaic plant monitoring system and method |
| CN108336968A (en) * | 2017-01-19 | 2018-07-27 | 上海紫凝新能源科技有限公司 | A kind of analysis monitoring system based on module data |
| CN108696249A (en) * | 2017-04-11 | 2018-10-23 | 丰郅(上海)新能源科技有限公司 | Photovoltaic module Fault Quick Diagnosis method |
| CN109298228A (en) * | 2018-09-13 | 2019-02-01 | 安徽天尚清洁能源科技有限公司 | A kind of Intelligence Diagnosis method and system based on photovoltaic group string current anomaly |
| CN110855241A (en) * | 2019-12-04 | 2020-02-28 | 合肥阳光新能源科技有限公司 | Photovoltaic system fault diagnosis method and device |
| CN111178779A (en) * | 2020-01-03 | 2020-05-19 | 河北因能科技股份有限公司 | Household photovoltaic power station fault monitoring and early warning method |
| CN114509105A (en) * | 2021-12-31 | 2022-05-17 | 国网青海省电力公司 | Function development and test method for operation and maintenance system of energy storage power station |
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Application publication date: 20161109 |