CN105577116A - Photovoltaic power generation data analysis-based abnormity and fault positioning method - Google Patents
Photovoltaic power generation data analysis-based abnormity and fault positioning method Download PDFInfo
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- CN105577116A CN105577116A CN201610018348.2A CN201610018348A CN105577116A CN 105577116 A CN105577116 A CN 105577116A CN 201610018348 A CN201610018348 A CN 201610018348A CN 105577116 A CN105577116 A CN 105577116A
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- 238000007405 data analysis Methods 0.000 title claims abstract description 15
- 238000000034 method Methods 0.000 title claims abstract description 15
- 238000010248 power generation Methods 0.000 title abstract 6
- 230000002159 abnormal effect Effects 0.000 claims abstract description 33
- 238000012423 maintenance Methods 0.000 claims abstract description 9
- 238000007689 inspection Methods 0.000 claims abstract description 7
- 238000004458 analytical method Methods 0.000 claims abstract description 4
- 238000012544 monitoring process Methods 0.000 claims abstract description 4
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 2
- 230000005856 abnormality Effects 0.000 abstract 3
- 238000012216 screening Methods 0.000 abstract 1
- 238000005516 engineering process Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010835 comparative analysis Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
Classifications
-
- 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
- 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 invention discloses a photovoltaic power generation data analysis-based abnormity and fault positioning method. The method comprises the following steps: (1) extracting photovoltaic power generation data from a photovoltaic operation monitoring database; (2) carrying out operation analysis by standard photovoltaic power generation data and other similar photovoltaic power generation data within a region, screening out an abnormal photovoltaic inverter and listing the abnormal photovoltaic inverter into an abnormality list; (3) manually checking abnormal photovoltaic power generation data, and issuing an abnormal photovoltaic maintenance task order; and (4) if the abnormal photovoltaic inverter restores normal operation after being maintained, shifting the abnormal photovoltaic inverter out of the abnormality list, if the abnormal photovoltaic inverter is determined to be normal operation photovoltaic inverter through inspection, analyzing the misjudgment reason and shifting the photovoltaic inverter out of the abnormality list. With the photovoltaic inverter as a basic unit, the abnormal photovoltaic inverter is accurately judged and positioned through data analysis, so that the automatic level of operation and maintenance of a large photovoltaic power station is improved.
Description
Technical field
The present invention relates to a kind of exception based on photovoltaic generation data analysis and Fault Locating Method, belong to photovoltaic generation O&M technical field.
Background technology
Photovoltaic generation is after going through upsurge in construction for many years, along with the quick increase of quantity and capacity, welcome focus, difficulties that quality control, operation management and improved efficiency etc. are urgently to be resolved hurrily, tradition operation management mode will be not suitable with the requirement of Industry Quick Development gradually, and the intelligent O&M pattern of building and perfecting has been trend of the times.
Tradition operation management means adopt human at periodic intervals to patrol mode to ensure the normal operation of photovoltaic apparatus, reduces equipment fault, take precautions against photovoltaic generation significant problem and accident.Along with the increase of power station installation scale, the operation maintenance personnel of a photovoltaic plant will reach tens of people.But artificial inspection is an expensive job of wasting time and energy, for large-scale power station, the comprehensive inspection of high frequency time is just infeasible on cost.
Summary of the invention
In order to solve the problems of the technologies described above, the invention provides a kind of exception based on photovoltaic generation data analysis and Fault Locating Method.
In order to achieve the above object, the technical solution adopted in the present invention is:
Based on exception and the Fault Locating Method of photovoltaic generation data analysis, comprise the following steps,
Step one, extracts photovoltaic generation data from photovoltaic operation monitoring database;
Described photovoltaic generation data comprise photovoltaic generation power data and energy output data;
Step 2, utilizes the standard photovoltaic generation data in region and other photovoltaic generation data of the same type to carry out operating analysis, filters out abnormal photovoltaic DC-to-AC converter, and list exception list in;
Step 3, the artificial photovoltaic generation data verifying exception, issue abnormal photovoltaic maintenance task work order;
Step 4, if recover normal operation after safeguarding, is then shifted out exception list; If be the normal photovoltaic DC-to-AC converter run on inspection, then analyze erroneous judgement reason and shift out exception list.
In step one, need to carry out preliminary treatment to it after extraction photovoltaic generation data, reject bad data.
Photovoltaic exception comprises energy output exception, photovoltaic generation power is abnormal and report to the police;
Energy output is abnormal: abnormal when energy output deviation exceeds setting threshold;
Photovoltaic generation power is abnormal: abnormal when generated output deviation exceeds setting threshold;
Described threshold value can regulate according to actual conditions;
Warning comprises generating fault alarm and metering fault is reported to the police.
Described photovoltaic generation power data are the average generated output data of minute level, and described energy output comprises daily generation, all energy output and the moon energy output.
The computing formula of energy output deviation is,
Wherein, η
mfor energy output deviation, W
mfor the energy output of target photovoltaic, W
m-standardfor the energy output of standard photovoltaic;
The computing formula of the average generated output deviation of n minute is,
Wherein, σ
nfor the average generated output deviation of n minute, P
nfor the average generated output of n minute of target photovoltaic, P
n-standardfor the average generated output of n minute of standard photovoltaic.
After judging by accident, by amendment threshold value, reduce erroneous judgement and occur.
The beneficial effect that the present invention reaches: the present invention take photovoltaic DC-to-AC converter as elementary cell, is accurately judged by data analysis and locates abnormal photovoltaic, thus improves the automatization level of large-sized photovoltaic power station O&M.
Accompanying drawing explanation
Fig. 1 is flow chart of the present invention.
Embodiment
Below in conjunction with accompanying drawing, the invention will be further described.Following examples only for technical scheme of the present invention is clearly described, and can not limit the scope of the invention with this.
As shown in Figure 1, based on exception and the Fault Locating Method of photovoltaic generation data analysis, comprise the following steps:
Step one, extracts photovoltaic generation data, and carries out preliminary treatment to it from photovoltaic operation monitoring database, rejects bad data, ensures the availability of data.
Photovoltaic generation data comprise photovoltaic generation power data and energy output data, here photovoltaic generation power data are the average generated output data of minute level, optional as 5 minutes, 10 minutes or 15 minutes average powers, energy output comprises daily generation, all energy output and the moon energy output.
Step 2, utilizes the standard photovoltaic generation data in region and other photovoltaic generation data of the same type to carry out operating analysis, filters out abnormal photovoltaic DC-to-AC converter, and list exception list in.
Photovoltaic exception comprises energy output exception, photovoltaic generation power is abnormal and report to the police.
Energy output is abnormal: abnormal when energy output deviation exceeds setting threshold; Threshold value can regulate according to actual conditions.
The computing formula of energy output deviation is,
Wherein, η
mfor energy output deviation, W
mfor the energy output of target photovoltaic, W
m-standardfor the energy output of standard photovoltaic.
Photovoltaic generation power is abnormal: abnormal when generated output deviation exceeds setting threshold; Threshold value can regulate according to actual conditions.
The computing formula of the average generated output deviation of n minute is,
Wherein, σ
nfor the average generated output deviation of n minute, P
nfor the average generated output of n minute of target photovoltaic, P
n-standardfor the average generated output of n minute of standard photovoltaic.
Warning comprises generating fault alarm and metering fault is reported to the police.
Step 3, the artificial photovoltaic generation data verifying exception, issue abnormal photovoltaic maintenance task work order.Special maintenance team precisely safeguards according to the abnormal photovoltaic DC-to-AC converter numbering in maintenance task work order and abnormal conditions, and feedback safeguards result.
Step 4, if recover normal operation after safeguarding, is then shifted out exception list; If be the normal photovoltaic DC-to-AC converter run on inspection, then analyze erroneous judgement reason and shift out exception list, simultaneously by amendment threshold value, reducing erroneous judgement and occur.
Said method runs comparative analysis by photovoltaic, is accurately positioned to abnormal photovoltaic DC-to-AC converter unit, purposively issues maintenance task, reduces the inspection workload of O&M, promotes the automatization level of O&M.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the prerequisite not departing from the technology of the present invention principle; can also make some improvement and distortion, these improve and distortion also should be considered as protection scope of the present invention.
Claims (6)
1., based on exception and the Fault Locating Method of photovoltaic generation data analysis, it is characterized in that: comprise the following steps,
Step one, extracts photovoltaic generation data from photovoltaic operation monitoring database;
Described photovoltaic generation data comprise photovoltaic generation power data and energy output data;
Step 2, utilizes the standard photovoltaic generation data in region and other photovoltaic generation data of the same type to carry out operating analysis, filters out abnormal photovoltaic DC-to-AC converter, and list exception list in;
Step 3, the artificial photovoltaic generation data verifying exception, issue abnormal photovoltaic maintenance task work order;
Step 4, if recover normal operation after safeguarding, is then shifted out exception list; If be the normal photovoltaic DC-to-AC converter run on inspection, then analyze erroneous judgement reason and shift out exception list.
2. the exception based on photovoltaic generation data analysis according to claim 1 and Fault Locating Method, is characterized in that: in step one, needs to carry out preliminary treatment to it, reject bad data after extraction photovoltaic generation data.
3. the exception based on photovoltaic generation data analysis according to claim 1 and Fault Locating Method, is characterized in that: photovoltaic exception comprises energy output exception, photovoltaic generation power is abnormal and report to the police;
Energy output is abnormal: abnormal when energy output deviation exceeds setting threshold;
Photovoltaic generation power is abnormal: abnormal when generated output deviation exceeds setting threshold;
Described threshold value can regulate according to actual conditions;
Warning comprises generating fault alarm and metering fault is reported to the police.
4. the exception based on photovoltaic generation data analysis according to claim 3 and Fault Locating Method, it is characterized in that: described photovoltaic generation power data are the average generated output data of minute level, described energy output comprises daily generation, all energy output and the moon energy output.
5. the exception based on photovoltaic generation data analysis according to claim 4 and Fault Locating Method, is characterized in that: the computing formula of energy output deviation is,
Wherein, η
mfor energy output deviation, W
mfor the energy output of target photovoltaic, W
m-standardfor the energy output of standard photovoltaic;
The computing formula of the average generated output deviation of n minute is,
Wherein, σ
nfor the average generated output deviation of n minute, P
nfor the average generated output of n minute of target photovoltaic, P
n-standardfor the average generated output of n minute of standard photovoltaic.
6. the exception based on photovoltaic generation data analysis according to claim 3 and Fault Locating Method, is characterized in that: after judging by accident, by amendment threshold value, reduces erroneous judgement and occur.
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Cited By (8)
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| CN107395119A (en) * | 2017-08-11 | 2017-11-24 | 中国计量大学 | A kind of Fault Locating Method of photovoltaic array |
| CN107589318A (en) * | 2016-07-06 | 2018-01-16 | 新疆金风科技股份有限公司 | The method for detecting abnormality and device of inverter in photovoltaic plant |
| CN108599724A (en) * | 2018-07-02 | 2018-09-28 | 中国电建集团江西省电力建设有限公司 | A kind of photovoltaic module on-line monitoring system and monitoring method |
| CN109067360A (en) * | 2018-09-21 | 2018-12-21 | 南通理工学院 | A kind of monitoring method and its device of the solar panel of automobile |
| CN109150651A (en) * | 2018-07-02 | 2019-01-04 | 北京市天元网络技术股份有限公司 | The monitoring method of transfer resource |
| CN110649887A (en) * | 2019-09-02 | 2020-01-03 | 徐州亿通光电有限公司 | Photovoltaic power generation management method |
| CN111798100A (en) * | 2020-06-09 | 2020-10-20 | 江苏蓝天光伏科技有限公司 | Power generation evaluation method and system for photovoltaic power generation operation and maintenance |
| CN113495199A (en) * | 2021-09-09 | 2021-10-12 | 深圳博润缘科技有限公司 | Power equipment safety monitoring method and system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107589318A (en) * | 2016-07-06 | 2018-01-16 | 新疆金风科技股份有限公司 | The method for detecting abnormality and device of inverter in photovoltaic plant |
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| CN109067360A (en) * | 2018-09-21 | 2018-12-21 | 南通理工学院 | A kind of monitoring method and its device of the solar panel of automobile |
| CN110649887A (en) * | 2019-09-02 | 2020-01-03 | 徐州亿通光电有限公司 | Photovoltaic power generation management method |
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