CN112327999A - Photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data - Google Patents

Photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data Download PDF

Info

Publication number
CN112327999A
CN112327999A CN202011204566.8A CN202011204566A CN112327999A CN 112327999 A CN112327999 A CN 112327999A CN 202011204566 A CN202011204566 A CN 202011204566A CN 112327999 A CN112327999 A CN 112327999A
Authority
CN
China
Prior art keywords
maximum power
voltage
photovoltaic
power point
points
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202011204566.8A
Other languages
Chinese (zh)
Other versions
CN112327999B (en
Inventor
张侃健
李晨曦
陈昕怡
方仕雄
谢利萍
张金霞
葛健
魏海坤
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Southeast University
Original Assignee
Southeast University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Southeast University filed Critical Southeast University
Priority to CN202011204566.8A priority Critical patent/CN112327999B/en
Publication of CN112327999A publication Critical patent/CN112327999A/en
Application granted granted Critical
Publication of CN112327999B publication Critical patent/CN112327999B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05F—SYSTEMS FOR REGULATING ELECTRIC OR MAGNETIC VARIABLES
    • G05F1/00—Automatic systems in which deviations of an electric quantity from one or more predetermined values are detected at the output of the system and fed back to a device within the system to restore the detected quantity to its predetermined value or values, i.e. retroactive systems
    • G05F1/66—Regulating electric power
    • G05F1/67—Regulating electric power to the maximum power available from a generator, e.g. from solar cell
    • 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
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers

Landscapes

  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Power Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Automation & Control Theory (AREA)
  • Photovoltaic Devices (AREA)

Abstract

The invention discloses a photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data, which comprises the following steps: detecting abnormality based on instantaneous current drop of a maximum power point, wherein the threshold setting simultaneously considers sampling intervals and disturbance step length; distinguishing shielding and line faults by using the number of key working points and extreme points on the characteristic curve, and further evaluating the fault degree; and according to the fault evaluation result, setting working voltage to distinguish a fault group string from a normal group string, thereby realizing fault positioning. The detection method provided by the invention does not need to install additional data acquisition equipment, can be conveniently embedded into a commercial inverter, is suitable for complex environments such as low irradiance, low mismatch level and blocking diode installation, and the like, and can effectively distinguish partial shielding and line faults with similar characteristics by the extracted inflection point characteristic, so that unnecessary power-off protection is avoided.

Description

Photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data
Technical Field
The invention relates to a photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data, and belongs to the technical field of new energy.
Background
Due to the unique advantages of photovoltaic power generation, photovoltaic power generation becomes one of the energy sources with the highest development speed at present, and is widely applied to various countries in the world in recent years. A basic photovoltaic system mainly comprises a photovoltaic array, a power regulator, an inverter and cables connected among all units, the abnormal and fault of any part caused by the series-parallel connection structure among the components can seriously affect the operation efficiency, the power output and the system safety and reliability of the system, and statistics show that the annual loss of the photovoltaic system caused by various faults can reach 18.9%. Therefore, condition monitoring and fault diagnosis are essential for safe, reliable and efficient operation of photovoltaic systems.
Conventional fault detection and protection methods require installation of overcurrent protection devices and ground fault detection devices in the array, however, unlike voltage-type power supplies, photovoltaic power generation systems have significant differences in fault characteristics, which in turn leads to partial failure of these protection devices under low irradiance conditions, low mismatch levels, the presence of maximum power point tracking modules, and the installation of blocking diodes.
In recent years, a large number of methods have been studied for detecting and diagnosing faults in photovoltaic arrays, the most basic and the most important method being realized by comparing measured values of maximum power point voltage and current with analog values, however, the operating point characteristics have similarities in various abnormal situations, which results in failure of category diagnosis based on the characteristics; in contrast, the current-voltage curve is wholly incorporated into the fault judgment basis to provide more information, and the calculation amount is increased, most importantly, the environment and electrical data acquisition problems required by the simulation process limit the implementable frequency of the algorithm, so that the hidden probability and time of the catastrophic fault in the system are increased.
The method based on the current and voltage signals and through time domain and frequency domain analysis, such as a grounding capacitance measuring method, a time domain reflection method and the like, can realize the detection and the positioning of specific faults, but is only suitable for off-line detection and needs additional signal input; the improved multi-scale signal decomposition method depends on high-frequency collected signals, and an algorithm needs additional software and hardware platform support.
In addition, statistical analysis of outliers is a common method for achieving fault detection and localization, but when the fault mismatch degree is low, the difference of the string currents is not obvious, so that the method fails, and in addition, the method depends on the arrangement of a large number of sensing devices for current detection, so that the operation cost is increased. Therefore, how to realize low-cost fault detection and diagnosis is an urgent problem to be solved in the current healthy operation of the photovoltaic system.
Disclosure of Invention
The technical problem is as follows:
the invention aims to solve the problems of untimely fault detection and positioning and high diagnosis cost in the conventional photovoltaic system, and provides a quick abnormal detection and accurate diagnosis method based on maximum power point tracking data.
The technical scheme is as follows:
in order to achieve the purpose, the method adopted by the invention is as follows: a photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data sequentially comprises the following steps:
s1: establishing a relation model of influence on output by common abnormal conditions such as serious faults, partial shielding and the like in a photovoltaic system, and considering the relation characteristics of different mismatch levels in the two systems of the presence/absence of installation of a blocking diode;
s2: detecting abnormal conditions based on current reduction between adjacent sampling intervals in the maximum power point tracking process, and determining a proper threshold value by considering sampling frequency and disturbance step length;
s3: scanning and acquiring a plurality of characteristic points of a short-circuit working point, an open-circuit working point, an inflection point and a local maximum value point by using a current-voltage characteristic curve triggered by an event, and recording the number of the extreme value points;
s4: distinguishing line faults from partial shielding based on the voltage and current of the characteristic points;
s5: analyzing the obtained inflection point and the new open-circuit voltage, and quantitatively evaluating the fault degree;
s6: and setting a specific voltage working range according to the mismatch grade evaluation result so as to maximally distinguish the currents in the fault group string and the normal group string.
Further, the specific steps of step S1 are as follows:
s1-1: establishing an influence relation model of abnormal conditions such as common line faults, open-circuit faults and partial shielding on output in the photovoltaic system;
s1-2: consider the characteristic variations that faults of different mismatch levels develop in both systems with and without the installation of blocking diodes, respectively.
Further, the specific steps of step S2 are as follows:
s2-1: a common method for tracking the maximum power point in the photovoltaic inverter is a disturbance observation method, instantaneous current reduction caused by normal irradiance fluctuation is calculated according to sampling frequency and disturbance step length, and a Threshold value Threshold is set to be
Threshold＝(i1+i2)·Npm (1)
In the above formula, i1For possible current drops between adjacent sampling instants due to irradiance fluctuations, i2The additional current drop created to cause the tracked operating point to deviate from the actual maximum power point due to the presence of the perturbation step size, NpmThe number of parallel strings of the photovoltaic array.
S2-2: recording current values of adjacent sampling moments in the tracking process, and calculating current variation;
s2-3: if the current drop value does not exceed the set threshold value, the normal tracking process is continued, otherwise, the scanning process of the current-voltage characteristic curve is triggered.
Further, in step S3, a plurality of feature points, such as short-circuit operating points, open-circuit operating points, inflection points, local maximum points, and the number of extreme points, on the characteristic curve are obtained, so as to overcome the problem of unnecessary power loss caused by timing scanning in the conventional diagnostic method.
Further, the specific steps of step S4 are as follows:
s4-1: aiming at a photovoltaic array without a blocking diode, identifying line faults and open-circuit faults by using the number of extreme points and the maximum power point voltage;
s4-2: aiming at a photovoltaic array provided with a blocking diode, firstly, identifying open-circuit faults and shielding conditions with large characteristic differences by utilizing the number of extreme points;
s4-3: for individual shelters with characteristics similar to line faults, distinguishing is achieved based on coordinates of inflection points, and therefore unnecessary power-off protection is avoided;
s4-4: further, faults inside the string groups and faults among the string groups are separated through the voltage of the extremely high power point on the right side.
Further, the specific steps of step S5 are as follows:
s5-1: aiming at the photovoltaic array without the blocking diode, the evaluation of the line mismatch level is realized by utilizing the relation between the new open-circuit voltage and the normal open-circuit voltage of a single component, wherein the mismatch level is NLLCan be expressed as
NLL＝Nsm-round(Voc/k·voc) (2)
In the above formula, NsmNumber of modules, V, connected in series in a string of photovoltaic modulesocFor new open circuit voltage, v, on the curve obtained by scanningocIs the open circuit voltage of a single component under normal conditions, and k is the characteristic curve of the single component obtained by simulation and the current is- (N)pm-1) the ratio between the voltage corresponding to the short-circuit current times and the open-circuit voltage of the individual components under normal conditions.
S5-2: aiming at the photovoltaic array provided with the blocking diode, the line mismatch and the like are realized by utilizing the relation between the inflection point voltage and the normal open-circuit voltage of a single componentEvaluation of the level, mismatch level NLLCan be expressed as
NLL＝Nsm-round(VInf/voc) (3)
In the above formula, VInfThe voltage of the inflection point on the curve obtained by scanning is obtained.
Further, in step S6, a specific voltage operating range is set according to the type of the fault diagnosed in step S4 and the result of the mismatch level evaluation in step S5, so as to maximally distinguish the currents in the fault string from the normal string, thereby more efficiently locating and isolating the fault.
Has the advantages that:
the anomaly detection method based on the maximum power point tracking data provided by the invention does not need to install additional sensing equipment, can be conveniently embedded into the conventional commercial inverter, realizes low-cost detection, and is suitable for complex operation environments such as low irradiance, low mismatch level and installation of blocking diodes; meanwhile, the characteristic curve scanning is triggered based on the detection result event, so that the problem that the power loss is easily caused by the timing scanning in the conventional diagnosis method can be solved; partial shielding and line faults with similar characteristics can be effectively distinguished by using key point features and pole numbers extracted from the curve, so that unnecessary power-off protection behaviors are avoided; in addition, the fault group string positioning method can quickly isolate faults, and therefore safe operation of the system is protected. Compared with the conventional overcurrent protection method and the tracking voltage-based abnormity detection method, the method is suitable for various operating conditions, the required detection time is shorter, the hidden time of faults in the system can be effectively reduced, the possibility of fire induction is reduced, and therefore the safe, reliable and efficient operation of the photovoltaic system is effectively maintained.
Drawings
FIG. 1 is a schematic diagram of the application of the method of the present invention in a photovoltaic power generation system;
FIG. 2 is a schematic diagram of key operating points on a characteristic curve selected in the method of the present invention;
FIG. 3 is a flow chart of the anomaly diagnosis proposed in the method of the present invention.
Detailed Description
The technical solution of the present invention is described in detail below, but the scope of the present invention is not limited to the embodiments. As shown in fig. 1, the method for photovoltaic fast detection and accurate diagnosis based on maximum power point tracking data of the present embodiment can be conveniently embedded into an existing commercial inverter, and the method sequentially includes the following steps:
s1: establishing a relation model of influence on output by common abnormal conditions such as serious faults, partial shielding and the like in a photovoltaic system, and considering the relation characteristics of different mismatch levels in the two systems of the presence/absence of installation of a blocking diode;
s2: detecting abnormal conditions based on current reduction between adjacent sampling intervals in the maximum power point tracking process, and determining a proper threshold value by considering sampling frequency and disturbance step length;
s3: scanning and acquiring a plurality of characteristic points of a short-circuit working point, an open-circuit working point, an inflection point and a local maximum value point by using a current-voltage characteristic curve triggered by an event, and recording the number of the extreme value points;
s4: distinguishing line faults from partial shielding based on the voltage and current of the characteristic points;
s5: analyzing the obtained inflection point and the new open-circuit voltage, and quantitatively evaluating the fault degree;
s6: and setting a specific voltage working range according to the mismatch grade evaluation result so as to maximally distinguish the currents in the fault group string and the normal group string.
In this embodiment, the specific steps of step S1 are as follows:
s1-1: establishing an influence relation model of abnormal conditions such as common line faults, open-circuit faults and partial shielding on output in the photovoltaic system;
s1-2: consider the characteristic variations that faults of different mismatch levels develop in both systems with and without the installation of blocking diodes, respectively.
In this embodiment, the specific steps of step S2 are as follows:
s2-1: a common method for tracking the maximum power point in the photovoltaic inverter is a disturbance observation method, instantaneous current reduction caused by normal irradiance fluctuation is calculated according to sampling frequency and disturbance step length, and a Threshold value Threshold is set to be
Threshold＝(i1+i2)·Npm (4)
In the above formula, i1For possible current drops between adjacent sampling instants due to irradiance fluctuations, i2The additional current drop created to cause the tracked operating point to deviate from the actual maximum power point due to the presence of the perturbation step size, NpmThe number of parallel strings of the photovoltaic array.
S2-2: recording current values of adjacent sampling moments in the tracking process, and calculating current variation;
s2-3: if the current drop value does not exceed the set threshold value, the normal tracking process is continued, otherwise, the scanning process of the current-voltage characteristic curve is triggered.
In this embodiment, in the step S3, a plurality of feature points, such as short-circuit operating points, open-circuit operating points, inflection points, local maximum points, and the number of the maximum points, on the characteristic curve are obtained, as shown in fig. 2, so as to overcome the problem of unnecessary power loss caused by the timing scanning in the conventional diagnostic method.
In this embodiment, as shown in fig. 3, the specific steps of step S4 are as follows:
s4-1: aiming at a photovoltaic array without a blocking diode, identifying line faults and open-circuit faults by using the number of extreme points and the maximum power point voltage;
s4-2: aiming at a photovoltaic array provided with a blocking diode, firstly, identifying open-circuit faults and shielding conditions with large characteristic differences by utilizing the number of extreme points;
s4-3: for individual shelters with characteristics similar to line faults, distinguishing is achieved based on coordinates of inflection points, and therefore unnecessary power-off protection is avoided;
s4-4: and the separation of the faults inside the group strings and the faults among the group strings is realized through the voltage of the extremely high power point on the right side.
In FIG. 3, num is the number of extreme points, IscFor array short-circuit current, iscFor normally generating a series short-circuit current, NpmNumber of parallel strings for array, NsmNumber of modules connected in series in strings, VInfIs knee voltage, vocIs normally the open circuit voltage of the individual components, IInfIs knee current, iscIs the short-circuit current of a single component under normal conditions, Vm_RIs the right maximum power point voltage, Im_RIs the right maximum power point current, vmIs the maximum power point voltage of a single component under normal conditions, imIs the maximum power point current of the single component under normal conditions.
In this embodiment, the specific steps of step S5 are as follows:
s5-1: aiming at the photovoltaic array without the blocking diode, the evaluation of the line mismatch level is realized by utilizing the relation between the new open-circuit voltage and the normal open-circuit voltage of a single component, wherein the mismatch level is NLLCan be expressed as
NLL＝Nsm-round(Voc/k·voc) (5)
In the above formula, NsmNumber of modules, V, connected in series in a string of photovoltaic modulesocFor new open circuit voltage, v, on the curve obtained by scanningocIs the open circuit voltage of a single component under normal conditions, and k is the characteristic curve of the single component obtained by simulation and the current is- (N)pm-1) the ratio between the voltage corresponding to the short-circuit current times and the open-circuit voltage of the individual components under normal conditions.
S5-2: aiming at a photovoltaic array provided with blocking diodes, the evaluation of the line mismatch level is realized by utilizing the relation between the inflection point voltage and the normal open-circuit voltage of a single component, wherein the mismatch level is NLLCan be expressed as
NLL＝Nsm-round(VInf/voc) (6)
In the above formula, VInfThe voltage of the inflection point on the curve obtained by scanning is obtained.
In this embodiment, in the step S6, a specific voltage operating range (see table 1) is set according to the type of the fault diagnosed in the step S4 and the result of the mismatch level evaluation in the step S5, so as to maximally distinguish the currents in the faulty string from the normal string, thereby more efficiently locating and isolating the fault.
TABLE 1 Voltage Range and Fault Current characteristics set for three types of faults
Figure BDA0002756612420000061
The feasibility of the abnormal detection method under various test conditions and the time required by detection are compared, the capability of distinguishing abnormal irradiance from normal irradiance reduction is tested, the tested photovoltaic system is a 4 x 8 array, the acquisition frequency of the used maximum power tracking algorithm is 5Hz, and the disturbance step length is 3V. The invention compares the performance with two common fault detection methods. The two methods are respectively as follows: conventional overcurrent detection devices [ from ZHao Y, De Palma J F, Mosesian J, et al. line-line fault analysis and protection schemes in solar photovoltaic array. IEEE Transactions on Industrial Electronics 2012,60(9): 3784-. The test result shows that the over-current detection device fails under the conditions of low mismatch, low irradiance and mismatch level and the installation of a blocking diode, and cannot play a role in protection; the maximum power tracking voltage based detection method proposed by pilai requires an average detection time of 3.65s, and the method will fail in systems where blocking diodes are installed; different from the two methods, the method can be operated under various complicated test conditions, and the detection time only needs 0.2s, so that the hidden time of the fault in the system is greatly reduced.
In addition, the effectiveness of the fault diagnosis method provided by the invention is further verified, and the accuracy of the mismatch level is quantitatively evaluated. In a system for installing a blocking diode, line faults and corresponding partial shielding conditions under seven mismatch levels are diagnosed, 50 sets of operating environment conditions are selected for each level, wherein irradiance and temperature data are generated randomly, 1050 sets of samples are counted, and the accuracy of classified diagnosis of the line faults and the partial shielding can reach 1048/1050-99.81% based on selected inflection point voltage characteristics, and under the condition, the accuracy of fault mismatch level assessment is 100%. In a system without a blocking diode, 100% of fault and shielding can be distinguished through the number of extreme points and the maximum power point voltage, and based on the selected new open-circuit voltage characteristic, 350 fault samples are subjected to mismatch grade evaluation, wherein the accuracy is 345/350-98.57%. The result shows that the diagnosis method provided by the invention can effectively distinguish the fault from the abnormal shielding, thereby avoiding unnecessary power-off protection actions, and the result of fault grade evaluation also provides accurate voltage setting reference for fault isolation in the following steps.

Claims (7)

1. The photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data is characterized by comprising the following steps of:
s1: establishing a relation model of influence of serious faults and partial shielding abnormal conditions on output in a photovoltaic system, and considering the relation characteristics of different mismatch levels in the two systems of installing or not installing a blocking diode;
s2: detecting abnormal conditions based on current reduction between adjacent sampling intervals in the maximum power point tracking process, and determining a threshold value by considering sampling frequency and disturbance step length;
s3: scanning and acquiring a plurality of characteristic points of a short-circuit working point, an open-circuit working point, an inflection point and a local maximum value point by using a current-voltage characteristic curve triggered by an event, and recording the number of the extreme value points;
s4: distinguishing line faults from partial shielding based on the voltage and current of the characteristic points;
s5: analyzing the obtained inflection point and the new open-circuit voltage, and quantitatively evaluating the fault degree;
s6: and setting a voltage working range according to the mismatch grade evaluation result so as to distinguish the current in the fault group string from the current in the normal group string.
2. The method for photovoltaic rapid detection and accurate diagnosis based on maximum power point tracking data according to claim 1, characterized in that: the specific steps of step S1 are as follows:
s1-1: establishing an influence relation model of line faults, open-circuit faults and partial shielding abnormal conditions in the photovoltaic system on output;
s1-2: consider the characteristic variations that faults of different mismatch levels develop in both systems with and without the installation of blocking diodes, respectively.
3. The method for photovoltaic rapid detection and accurate diagnosis based on maximum power point tracking data according to claim 1, characterized in that: the specific steps of step S2 are as follows:
s2-1: the maximum power point tracking method in the photovoltaic inverter is a disturbance observation method, instantaneous current reduction caused by normal irradiance fluctuation is calculated according to sampling frequency and disturbance step length, and a threshold value is set;
s2-2: recording current values of adjacent sampling moments in the tracking process, and calculating current variation;
s2-3: if the current drop does not exceed the set threshold, the normal tracking process is continued, otherwise, the scanning process of the current-voltage characteristic curve is triggered.
4. The method for photovoltaic rapid detection and accurate diagnosis based on maximum power point tracking data according to claim 1, characterized in that: in step S3, a plurality of feature points, such as short-circuit operating points, open-circuit operating points, inflection points, and local maximum points, on the characteristic curve, and the number of the extreme points are obtained.
5. The method for photovoltaic rapid detection and accurate diagnosis based on maximum power point tracking data according to claim 1, characterized in that: the specific steps of step S4 are as follows:
s4-1: aiming at a photovoltaic array without a blocking diode, identifying line faults and open-circuit faults by utilizing the number of extreme points and the maximum power point voltage;
s4-2: aiming at a photovoltaic array provided with a blocking diode, firstly, identifying open-circuit faults and shielding conditions with large characteristic differences by utilizing the number of extreme points;
s4-3: for individual shielding with characteristics similar to line fault characteristics, distinguishing is realized based on coordinates of inflection points, so that unnecessary power-off protection is avoided;
s4-4: and the separation of the faults inside the group strings and the faults among the group strings is realized through the voltage of the extremely high power point on the right side.
6. The method for photovoltaic rapid detection and accurate diagnosis based on maximum power point tracking data according to claim 1, characterized in that: the specific steps of step S5 are as follows:
s5-1: aiming at a photovoltaic array without a blocking diode, the evaluation of the line mismatch level is realized by utilizing the relation between the new open-circuit voltage and the open-circuit voltage of a single component under the normal condition;
s5-2: and aiming at the photovoltaic array provided with the blocking diode, the evaluation of the line mismatch level is realized by utilizing the relation between the inflection point voltage and the normal single-component open-circuit voltage.
7. The method for photovoltaic rapid detection and accurate diagnosis based on maximum power point tracking data according to claim 1, characterized in that: in step S6, a voltage operating range is set according to the result of the mismatch level evaluation in step S5 to distinguish the currents in the faulty string from the normal string.
CN202011204566.8A 2020-11-02 2020-11-02 Photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data Active CN112327999B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011204566.8A CN112327999B (en) 2020-11-02 2020-11-02 Photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011204566.8A CN112327999B (en) 2020-11-02 2020-11-02 Photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data

Publications (2)

Publication Number Publication Date
CN112327999A true CN112327999A (en) 2021-02-05
CN112327999B CN112327999B (en) 2022-03-11

Family

ID=74324322

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011204566.8A Active CN112327999B (en) 2020-11-02 2020-11-02 Photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data

Country Status (1)

Country Link
CN (1) CN112327999B (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113708726A (en) * 2021-09-24 2021-11-26 贵州理工学院 Photovoltaic array fault discrimination method based on real-time calculation and comparison of photovoltaic module voltage
CN113872526A (en) * 2021-09-24 2021-12-31 贵州理工学院 Photovoltaic array fault diagnosis method based on minimum mismatching fault current prediction
CN113985239A (en) * 2021-10-13 2022-01-28 合肥阳光智维科技有限公司 Method, device, equipment and storage medium for identifying faults of group string bypass diode
WO2023138132A1 (en) * 2022-01-21 2023-07-27 天合光能股份有限公司 Support tracking method and system, photovoltaic device, and medium

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106647921A (en) * 2017-01-19 2017-05-10 南通大学 Improved MPPT algorithm with reduced influence of partial shading on photovoltaic system
CN106774606A (en) * 2016-11-28 2017-05-31 国家电网公司 A kind of global MPPT method and apparatus under uneven illumination is even
CN108092622A (en) * 2017-12-14 2018-05-29 中国计量大学 A kind of photovoltaic string formation method for diagnosing faults based on resistance calculations
US20180238951A1 (en) * 2016-09-07 2018-08-23 Jiangnan University Decision Tree SVM Fault Diagnosis Method of Photovoltaic Diode-Clamped Three-Level Inverter
CN108923748A (en) * 2018-07-16 2018-11-30 河海大学常州校区 A kind of diagnosing failure of photovoltaic array method based on IV curved scanning

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180238951A1 (en) * 2016-09-07 2018-08-23 Jiangnan University Decision Tree SVM Fault Diagnosis Method of Photovoltaic Diode-Clamped Three-Level Inverter
CN106774606A (en) * 2016-11-28 2017-05-31 国家电网公司 A kind of global MPPT method and apparatus under uneven illumination is even
CN106647921A (en) * 2017-01-19 2017-05-10 南通大学 Improved MPPT algorithm with reduced influence of partial shading on photovoltaic system
CN108092622A (en) * 2017-12-14 2018-05-29 中国计量大学 A kind of photovoltaic string formation method for diagnosing faults based on resistance calculations
CN108923748A (en) * 2018-07-16 2018-11-30 河海大学常州校区 A kind of diagnosing failure of photovoltaic array method based on IV curved scanning

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113708726A (en) * 2021-09-24 2021-11-26 贵州理工学院 Photovoltaic array fault discrimination method based on real-time calculation and comparison of photovoltaic module voltage
CN113872526A (en) * 2021-09-24 2021-12-31 贵州理工学院 Photovoltaic array fault diagnosis method based on minimum mismatching fault current prediction
CN113985239A (en) * 2021-10-13 2022-01-28 合肥阳光智维科技有限公司 Method, device, equipment and storage medium for identifying faults of group string bypass diode
WO2023138132A1 (en) * 2022-01-21 2023-07-27 天合光能股份有限公司 Support tracking method and system, photovoltaic device, and medium

Also Published As

Publication number Publication date
CN112327999B (en) 2022-03-11

Similar Documents

Publication Publication Date Title
CN112327999B (en) Photovoltaic rapid detection and accurate diagnosis method based on maximum power point tracking data
Roy et al. An irradiance-independent, robust ground-fault detection scheme for PV arrays based on spread spectrum time-domain reflectometry (SSTDR)
Yi et al. Fault detection for photovoltaic systems based on multi-resolution signal decomposition and fuzzy inference systems
Braun et al. Signal processing for fault detection in photovoltaic arrays
Li et al. A fast MPPT-based anomaly detection and accurate fault diagnosis technique for PV arrays
CN108008176B (en) A kind of photovoltaic array real-time state monitoring and fault location system
CN109239517B (en) Novel method for identifying DC arc fault and type of photovoltaic system
Ma et al. Photovoltaic module current mismatch fault diagnosis based on IV data
Kumar et al. Identification and localization of array faults with optimized placement of voltage sensors in a PV system
Buddha et al. Signal processing for photovoltaic applications
Zaki et al. Fault detection and diagnosis of photovoltaic system using fuzzy logic control
CN112731087B (en) Fault arc detection system and method for photovoltaic field
CN106501668A (en) A kind of conventional electrical distribution net single-phase wire break fault-line selecting method
CN112924750B (en) Fault arc detection method and system
CN108092623A (en) A kind of photovoltaic array multisensor fault detecting and positioning method
Chouay et al. An intelligent method for fault diagnosis in photovoltaic systems
Eskandari et al. Optimization of SVM classifier using grid search method for line-line fault detection of photovoltaic systems
CN112083270A (en) Wind power plant current collection line single-phase earth fault line selection method based on correlation coefficient
Hare et al. A review of faults and fault diagnosis in micro-grids electrical energy infrastructure
CN102426671B (en) Optimal troubleshooting method based on comprehensive cost
CN112557950A (en) Fault line selection method for power distribution network resonance grounding system based on matrix similarity
CN116626439A (en) Power transmission and distribution line fault detection positioning method based on waveform similarity
Ghazali et al. A Comparative Analysis of Solar Photovoltaic Advanced Fault Detection and Monitoring Techniques.
KR102508632B1 (en) Detection of disconnection position of PV system using parasitic capacitor and the method using it
KR102448187B1 (en) the fault detection methods of PV panel using unit vector analysis for I-V curve

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant