CN117633617A - Method and device for diagnosing power generation efficiency of distributed photovoltaic power station - Google Patents
Method and device for diagnosing power generation efficiency of distributed photovoltaic power station Download PDFInfo
- Publication number
- CN117633617A CN117633617A CN202311575714.0A CN202311575714A CN117633617A CN 117633617 A CN117633617 A CN 117633617A CN 202311575714 A CN202311575714 A CN 202311575714A CN 117633617 A CN117633617 A CN 117633617A
- Authority
- CN
- China
- Prior art keywords
- diagnosis
- data
- generation efficiency
- power generation
- distributed photovoltaic
- 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.)
- Pending
Links
- 238000010248 power generation Methods 0.000 title claims abstract description 70
- 238000000034 method Methods 0.000 title claims abstract description 51
- 238000003745 diagnosis Methods 0.000 claims abstract description 227
- 238000004364 calculation method Methods 0.000 claims abstract description 33
- 238000007781 pre-processing Methods 0.000 claims abstract description 13
- 238000005259 measurement Methods 0.000 claims description 34
- 238000005457 optimization Methods 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 9
- 238000012544 monitoring process Methods 0.000 claims description 7
- 238000013523 data management Methods 0.000 abstract description 3
- 230000008901 benefit Effects 0.000 description 5
- 238000012423 maintenance Methods 0.000 description 5
- 238000012545 processing Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000007792 addition Methods 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000009194 climbing Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000005215 recombination Methods 0.000 description 1
- 230000006798 recombination Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000002269 spontaneous effect Effects 0.000 description 1
Landscapes
- Photovoltaic Devices (AREA)
Abstract
The invention provides a method and a device for diagnosing the power generation efficiency of a distributed photovoltaic power station, wherein the method comprises the following steps: collecting initial diagnosis data of the measuring points according to the configured measuring points and the collecting frequency; preprocessing the initial diagnosis data to generate effective diagnosis data of the measuring points; calculating a calculation result of the configured diagnostic index according to the effective diagnostic data; generating a power generation efficiency diagnosis result according to the calculation result and the configured power generation efficiency diagnosis rule. The method and the device can automatically collect the operation data of the measuring points, automatically perform on-line diagnosis through the configured power generation efficiency diagnosis rules after data management, give out diagnosis results, further give out diagnosis suggestions for the diagnosis results, solve the problems of large workload, low efficiency and high error rate of the traditional distributed photovoltaic power generation efficiency diagnosis through an off-line manual mode, and can greatly improve the power generation efficiency of the distributed photovoltaic power station.
Description
Technical Field
The present invention relates to the field of power data analysis, and more particularly, to a method and apparatus for diagnosing the power generation efficiency of a distributed photovoltaic power plant.
Background
With the rapid development of the distributed photovoltaic industry, research on how to improve the power generation efficiency of each distributed photovoltaic station becomes a main work task of current distributed photovoltaic development research. The distributed photovoltaic field stations are distributed on the roof and the open space and used for generating electricity to realize spontaneous self-use and residual electricity surfing, so that certain economic benefits can be brought to enterprises, but due to the influence of the running environment of the distributed photovoltaic field stations, the conditions of breaking photovoltaic panels, generating light spots or shielding floating dust and the like are easy to occur, and the generating efficiency is reduced. Because distributed photovoltaic is distributed on places such as roofs and the like which are not suitable for climbing, the abnormal difficulty of the components with low power generation efficiency is manually checked, and the reason for the low power generation efficiency is required to be diagnosed by means of an informatization system so as to improve the power generation efficiency of the station.
The prior art relates to a method for diagnosing the power generation efficiency of a centralized photovoltaic gate, which mainly aims at centralized photovoltaic and is mainly used for a centralized photovoltaic station. The centralized photovoltaic power station is characterized in that the scale of the station exceeds 6MW, the power of the inverter used is high, the power of the inverter is more than 500kW, and the grid-connected voltage level of the centralized photovoltaic power station is generally more than 10 kV. The distributed photovoltaic power station is characterized in that the scale is smaller than 6MW, the power of the used inverter is not high and is not more than 1000kW, the grid-connected voltage level of the distributed photovoltaic power station is generally 380V-10 kV, the voltage level and the power difference of the distributed photovoltaic power station are large, so that links of electric losses generated by the distributed photovoltaic power station and the grid-connected voltage level are different, the electric losses of the distributed photovoltaic power station are lower than those of the distributed photovoltaic power station due to the fact that the voltage level of the centralized photovoltaic power station is higher, the electric losses of the distributed photovoltaic power station are not the main analysis object, and therefore a large difference is generated due to the fact that the difference of circuit characteristics is needed, and a new method is needed to be specially provided for diagnosing the electric power generation efficiency of the distributed photovoltaic power station.
Disclosure of Invention
In order to solve the technical problems that in the prior art, distributed photovoltaic is distributed in a place which is not easy to climb, and the components with low power generation efficiency are difficult to manually check, the method for diagnosing the power generation efficiency of the centralized photovoltaic power station is not suitable for the distributed photovoltaic power station, the invention provides a method and a device for diagnosing the power generation efficiency of the distributed photovoltaic power station.
According to one aspect of the invention, there is provided a method of diagnosing power generation efficiency of a distributed photovoltaic power plant, the method comprising:
collecting initial diagnosis data of the measuring points according to the configured measuring points and the collection frequency, wherein the measuring points are operation parameters of monitoring objects to be collected in the distributed photovoltaic power station;
preprocessing the initial diagnosis data to generate effective diagnosis data of the measuring points;
calculating a calculation result of the configured diagnostic index according to the effective diagnostic data;
generating a power generation efficiency diagnosis result according to the calculation result and the configured power generation efficiency diagnosis rule.
According to another aspect of the present invention, there is provided an apparatus for diagnosing power generation efficiency of a distributed photovoltaic power plant, the apparatus comprising:
the data acquisition module is used for acquiring initial diagnosis data of the measuring points according to the configured measuring points and the acquisition frequency, wherein the measuring points are operation parameters of a monitoring object to be acquired in the distributed photovoltaic power station;
the preprocessing module is used for preprocessing the initial diagnosis data to generate effective diagnosis data of the measuring points;
the data calculation module is used for calculating the calculation result of the configured diagnosis indexes according to the effective diagnosis data;
and the diagnosis result module is used for generating a power generation efficiency diagnosis result according to the calculation result and the configured power generation efficiency diagnosis rule.
According to a further aspect of the present invention there is provided a computer readable storage medium storing a computer program for performing the method of any one of the above aspects of the present invention.
According to still another aspect of the present invention, there is provided an electronic device including: a processor; a memory for storing the processor-executable instructions; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any of the above aspects of the present invention.
The invention discloses a device for diagnosing the generation efficiency of a distributed photovoltaic power station, wherein the method comprises the following steps: collecting initial diagnosis data of the measuring points according to the configured measuring points and the collection frequency, wherein the measuring points are operation parameters of monitoring objects to be collected in the distributed photovoltaic power station; preprocessing the initial diagnosis data to generate effective diagnosis data of the measuring points; calculating a calculation result of the configured diagnostic index according to the effective diagnostic data; generating a power generation efficiency diagnosis result according to the calculation result and the configured power generation efficiency diagnosis rule. The method and the device can automatically collect the operation data of the measuring points, automatically perform on-line diagnosis through the configured power generation efficiency diagnosis rules after data management, give out diagnosis results, further give out diagnosis suggestions for the diagnosis results, solve the problems of large workload, low efficiency and high error rate of the traditional distributed photovoltaic power generation efficiency diagnosis through an off-line manual mode, and can greatly improve the power generation efficiency of the distributed photovoltaic power station.
Drawings
Exemplary embodiments of the present invention may be more completely understood in consideration of the following drawings:
FIG. 1 is a flow chart of a method of diagnosing power generation efficiency of a distributed photovoltaic power plant in accordance with a preferred embodiment of the present invention;
FIG. 2 is a schematic structural view of an apparatus for diagnosing power generation efficiency of a distributed photovoltaic power plant according to a preferred embodiment of the present invention;
fig. 3 is a schematic structural view of an electronic device according to a preferred embodiment of the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the examples described herein, which are provided to fully and completely disclose the present invention and fully convey the scope of the invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, like elements/components are referred to by like reference numerals.
Unless otherwise indicated, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. In addition, it will be understood that terms defined in commonly used dictionaries should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
Exemplary method
Fig. 1 is a flowchart of a method of diagnosing the power generation efficiency of a distributed photovoltaic power plant in accordance with a preferred embodiment of the present invention. As shown in fig. 1, the method for diagnosing the power generating efficiency of the distributed photovoltaic power plant according to the preferred embodiment starts in step 101.
In step 101, initial diagnostic data of the measurement points are acquired according to the configured measurement points and the acquisition frequency, wherein the measurement points are operation parameters of a monitoring object to be acquired in the distributed photovoltaic power station.
Preferably, the method further comprises, before acquiring the initial diagnostic data of the measurement points according to the configured measurement points and the acquisition frequency:
according to the topological structure of the distributed photovoltaic power station, configuring a measuring point and a normal interval of measuring point data and collecting frequency of collecting the measuring point data;
and configuring a power generation efficiency diagnosis rule according to the topological structure of the distributed photovoltaic power station, wherein the power generation efficiency diagnosis rule comprises diagnosis categories and diagnosis logics corresponding to each diagnosis category.
Preferably, the configuring the normal interval of the measurement point and the measurement point data and the collecting frequency of the collection of the measurement point data according to the topology structure of the distributed photovoltaic power station includes:
when the circuit topology of the distributed photovoltaic power station is a component-string inverter-alternating current combiner box-box transformer-grid-connected cabinet, wherein:
the configured measuring points comprise three-phase current and voltage of an alternating current side of the inverter, current and voltage of a combiner box, combiner current and voltage and ground faults;
configuring a normal section of the measuring point data according to the rated value of the measuring point data and the allowable fluctuation range;
the acquisition frequency of the configured measurement point data is in the order of minutes or seconds.
In a preferred embodiment, a normal value interval is required to be set for the measurement point data, so that when the collected data is preprocessed, the measurement point instantaneous data which is not in line with the requirements can be removed. The normal interval of the measurement point data is generally determined by the fluctuation of the rated value of the voltage and the current in a certain fluctuation range. For example, the normal interval of the three-phase voltage on the ac side of the inverter is determined by fluctuation of the voltage rating in the range of 3% to 5%.
In the preferred embodiment, after the measuring points are determined, data are collected in real time, and the collected initial diagnosis data are collected through a SCADA (supervisory control and data acquisition) system, a metering instrument and other communication data systems and the metering instrument, transmitted through a DTU (digital television) and a gateway and stored in a database.
Preferably, the configuring the power generation efficiency diagnosis rule according to the topology structure of the distributed photovoltaic power station includes:
when the circuit topology of the distributed photovoltaic power station is a component-string inverter-alternating current combiner box-box transformer-grid-connected cabinet, wherein:
the configuration diagnosis categories are inverter electrical losses, combiner box electrical losses, string electrical losses and ground electrical losses;
configuring diagnostic logic corresponding to each diagnostic category, comprising:
setting a power generation efficiency diagnosis index and a diagnosis grade number of each diagnosis class, wherein the diagnosis index is the electric loss rate of each diagnosis class, and the diagnosis grade number is not less than 2;
setting an index threshold for each diagnostic level of each diagnostic category;
determining a diagnosis interval corresponding to each diagnosis grade of each diagnosis class according to the index threshold corresponding to each diagnosis grade of each diagnosis class;
and determining the power generation efficiency diagnosis result of each diagnosis class according to the diagnosis interval in which the calculation result of the diagnosis index of each diagnosis class is positioned, wherein the power generation efficiency diagnosis result of each diagnosis class is the diagnosis grade corresponding to the diagnosis interval of the diagnosis class.
In the preferred embodiment, when the diagnosis class is ground loss, the measurement point is ground fault, and the collected measurement point data is ground fault state value, which is a boolean variable, and 0 indicates no ground fault and 1 indicates ground fault. Therefore, when the diagnosis class is the ground loss, the diagnosis index ground loss rate corresponds to only 2 diagnosis classes, one is the ground loss, and the other is the no ground loss. For the other three diagnostic categories, the diagnostic index electrical loss rate can be calculated according to the collected measurement point data, so that the diagnostic grade can be divided into a plurality of 0 to 100 percent. For example, when the diagnosis category is the inverter electric loss, three diagnosis levels may be set, respectively, of which the inverter electric loss rate is high, and the inverter electric loss rate is low, and the corresponding index thresholds are respectively 20%,15%, and 10%, respectively, three diagnosis intervals are obtained to be greater than 20%, greater than 15%, and not greater than 20%, and greater than 10%, and not greater than 15%, that is, when the calculated inverter electric loss rate exceeds 20%, the output power generation efficiency diagnosis result is that the diagnosis level is the inverter electric loss rate high, when the calculated inverter electric loss rate exceeds 15%, the output power generation efficiency diagnosis result is that the diagnosis level is the inverter electric loss rate, and when the calculated inverter electric loss rate exceeds 10%, the output power generation efficiency diagnosis result is that the diagnosis level is the inverter electric loss rate low.
In step 102, the initial diagnostic data is preprocessed to generate valid diagnostic data for the measurement site.
Preferably, the preprocessing the initial diagnostic data to generate valid diagnostic data of the measurement point includes:
when the measuring point is the three-phase current and the voltage of the alternating current side of the inverter, removing any one of the data of the three-phase current and the voltage of the alternating current side of the inverter in the initial diagnosis data as 0;
removing null data in the initial diagnostic data;
and removing overrun data in the initial diagnosis data, wherein the overrun data is the initial diagnosis data exceeding a normal section of the configured measuring point data.
In the preferred embodiment, the overrun data in the initial diagnostic data is deleted in accordance with the normal section of the arranged station data, and for example, when the voltage acquired on the ac side of the inverter exceeds 5% of the rated value, the station data is deleted. By preprocessing the initial diagnosis data, the data processing amount is reduced, and the accuracy of the power generation efficiency diagnosis is improved.
In step 103, the calculation result of the configured diagnostic index is calculated according to the effective diagnostic data.
Preferably, calculating a calculation result of the configured diagnostic index according to the effective diagnostic data includes:
when the diagnosis categories are inverter electric loss, bus box electric loss and group series electric loss, calculating an average value of effective diagnosis data of measuring points of each diagnosis category in a set time period, wherein the average value comprises average current and average voltage;
calculating the electric loss rate of each diagnosis class according to the average value of the effective diagnosis data of the measuring point of each diagnosis class in the time period, wherein the calculation formula of the electric loss rate is as follows:
wherein K is the electrical loss rate of each diagnostic class, I a And I ref Respectively the average current and the rated current in the time period, U a And U ref Respectively an average voltage and a rated voltage in the time period;
and when the diagnosis type is the ground loss, outputting a ground loss calculation result according to the ground fault state value.
In the preferred embodiment, since the collection frequency of the measured data is in the order of minutes or seconds, in order to reduce the data amount of analysis and improve the diagnosis efficiency, and simultaneously reduce the influence of the data fluctuation caused by the working condition change on the diagnosis result, the collected data in one hour can be accumulated and divided by the collection times in one hour, specifically, when the diagnosis type is the inverter electric loss, the junction box electric loss and the box electric loss, the average voltage and the average current in one hour can be obtained by summing the voltage and the current data in one hour and dividing by the collection times in the normal operation state of the distributed photovoltaic power station. It should be noted that the time period is set to one hour is merely an example, and does not constitute a limitation of the present invention.
In step 104, a power generation efficiency diagnosis result is generated according to the calculation result and the configured power generation efficiency diagnosis rule.
Preferably, the method further comprises:
configuring an optimization strategy corresponding to the diagnosis grade of each diagnosis class;
when the diagnosis level of each diagnosis category is determined, the diagnosis level of each diagnosis category and the optimization strategy corresponding to the diagnosis level are output.
In the preferred embodiment, according to the set diagnosis level of each diagnosis category, corresponding optimization suggestions can be set according to experience, when the diagnosis result of the electric loss of the inverter is that the diagnosis level is that the electric loss rate of the inverter is high, the distributed photovoltaic power station can be given as the optimization suggestion to stop operation, and when the diagnosis result of the electric loss of the inverter is that the diagnosis level is that the electric loss rate of the inverter is low, the given optimization suggestion is that the distributed photovoltaic power station continues to operate, and the inverter is checked. By outputting the diagnosis result of the diagnosis type of the power generation efficiency, the corresponding optimization suggestion is given, so that operation and maintenance personnel can conduct targeted maintenance conveniently, and the power generation efficiency is improved. Further, the method may also save historical diagnostic results. For example, for inverter loss, after diagnosis, a label for forming a diagnosis result of the power generation efficiency of the inverter is formed, such as low power loss rate of 1 time, high power loss rate of 2 times and the like of the inverter, so that operation and maintenance staff can conveniently grasp the state of the equipment, and the maintenance is carried out in a state described by the label in a key way during maintenance.
In summary, the method for diagnosing the power generating efficiency of the distributed photovoltaic power station according to the preferred embodiment automatically collects the operation data of the measuring points, performs automatic online diagnosis according to the configured power generating efficiency diagnosis rules after data management, gives out a diagnosis result, and further gives out a diagnosis suggestion for the diagnosis result, thereby solving the problems of large workload, low efficiency and high error rate of the traditional distributed photovoltaic power generating efficiency diagnosis by an offline manual analysis method and greatly improving the power generating efficiency of the distributed photovoltaic power station.
Exemplary apparatus
Fig. 2 is a schematic structural view of an apparatus for diagnosing power generation efficiency of a distributed photovoltaic power plant according to a preferred embodiment of the present invention. As shown in fig. 2, a diagnostic distributed photovoltaic power plant power generation efficiency 200 according to the present preferred embodiment includes:
the data acquisition module 201 is configured to acquire initial diagnostic data of a measurement point according to the configured measurement point and an acquisition frequency, wherein the measurement point is an operation parameter of a monitoring object to be acquired in the distributed photovoltaic power station;
the preprocessing module 202 is configured to preprocess the initial diagnostic data and generate valid diagnostic data of a measurement point;
a data calculation module 203, configured to calculate a calculation result of the configured diagnostic index according to the valid diagnostic data;
and a diagnosis result module 204, configured to generate a power generation efficiency diagnosis result according to the calculation result and the configured power generation efficiency diagnosis rule.
Preferably, the device further comprises a diagnosis knowledge base module, which is used for configuring the measuring points and the normal intervals of the measuring point data and collecting the collecting frequency of the measuring point data according to the topological structure of the distributed photovoltaic power station; and configuring a power generation efficiency diagnosis rule according to the topological structure of the distributed photovoltaic power station, wherein the power generation efficiency diagnosis rule comprises diagnosis categories and diagnosis logic corresponding to each diagnosis category.
Preferably, the diagnosis knowledge base module configures a normal interval of the measurement point and the measurement point data and acquires the acquisition frequency of the measurement point data according to the topology structure of the distributed photovoltaic power station, and the diagnosis knowledge base module comprises:
when the circuit topology of the distributed photovoltaic power station is a component-string inverter-alternating current combiner box-box transformer-grid-connected cabinet, wherein:
the configured measuring points comprise three-phase current and voltage of an alternating current side of the inverter, current and voltage of a combiner box, combiner current and voltage and ground faults;
configuring a normal section of the measuring point data according to the rated value of the measuring point data and the allowable fluctuation range;
the acquisition frequency of the configured measurement point data is in the order of minutes or seconds.
Preferably, the diagnosis knowledge base module configures a diagnosis rule of power generation efficiency according to a topological structure of the distributed photovoltaic power station, and the diagnosis knowledge base module comprises:
when the circuit topology of the distributed photovoltaic power station is a component-string inverter-alternating current combiner box-box transformer-grid-connected cabinet, wherein:
the configuration diagnosis categories are inverter electrical losses, combiner box electrical losses, string electrical losses and ground electrical losses;
configuring diagnostic logic corresponding to each diagnostic category, comprising:
setting a power generation efficiency diagnosis index and a diagnosis grade number of each diagnosis class, wherein the diagnosis index is the electric loss rate of each diagnosis class, and the diagnosis grade number is not less than 2;
setting an index threshold for each diagnostic level of each diagnostic category;
determining a diagnosis interval corresponding to each diagnosis grade of each diagnosis class according to the index threshold corresponding to each diagnosis grade of each diagnosis class;
and determining the power generation efficiency diagnosis result of each diagnosis class according to the diagnosis interval in which the calculation result of the diagnosis index of each diagnosis class is positioned, wherein the power generation efficiency diagnosis result of each diagnosis class is the diagnosis grade corresponding to the diagnosis interval of the diagnosis class.
Preferably, the preprocessing module 202 preprocesses the initial diagnostic data to generate valid diagnostic data of the measurement point, including:
when the measuring point is the three-phase current and the voltage of the alternating current side of the inverter, removing any one of the data of the three-phase current and the voltage of the alternating current side of the inverter in the initial diagnosis data as 0;
removing null data in the initial diagnostic data;
and removing overrun data in the initial diagnosis data, wherein the overrun data is the initial diagnosis data exceeding a normal section of the configured measuring point data.
Preferably, the data calculating module 203 calculates a calculation result of the configured diagnostic index according to the valid diagnostic data, including:
when the diagnosis categories are inverter electric loss, bus box electric loss and group series electric loss, calculating an average value of effective diagnosis data of measuring points of each diagnosis category in a set time period, wherein the average value comprises average current and average voltage;
calculating the electric loss rate of each diagnosis class according to the average value of the effective diagnosis data of the measuring point of each diagnosis class in the time period, wherein the calculation formula of the electric loss rate is as follows:
wherein K is the electrical loss rate of each diagnostic class, I a And I ref Respectively the average current and the rated current in the time period, U a And U ref Respectively an average voltage and a rated voltage in the time period;
and when the diagnosis type is the ground loss, outputting a ground loss calculation result according to the ground fault state value.
Preferably, the diagnosis knowledge base module is further configured to configure an optimization strategy corresponding to a diagnosis level of each diagnosis class;
correspondingly, the diagnosis result module 204 is further configured to output, when determining the diagnosis level of each diagnosis category, and an optimization strategy corresponding to the diagnosis level.
The device for diagnosing the power generating efficiency of the distributed photovoltaic power station according to the preferred embodiment collects the initial diagnostic data of the measurement points according to the configured measurement points and the collection frequency, pre-processes the initial diagnostic data to obtain effective diagnostic data, calculates the calculation result of the diagnostic index according to the effective diagnostic data, and generates the power generating efficiency diagnostic result according to the calculation result and the configured power generating efficiency diagnostic rule, wherein the step of the method for diagnosing the power generating efficiency of the distributed photovoltaic power station is the same as the step of the method for diagnosing the power generating efficiency of the distributed photovoltaic power station according to the invention, and the achieved technical effects are the same and are not repeated herein.
Exemplary electronic device
Fig. 3 is a schematic structural view of an electronic device according to a preferred embodiment of the present invention. The electronic device may be either or both of the first device and the second device, or a stand-alone device independent thereof, which may communicate with the first device and the second device to receive the acquired input signals therefrom. Fig. 3 illustrates a block diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 3, the electronic device includes one or more processors 301 and memory 302.
The processor 301 may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities and may control other components in the electronic device to perform desired functions.
Memory 302 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like. One or more computer program instructions may be stored on the computer readable storage medium that can be executed by the processor 301 to implement the enterprise energy space-based energy usage anomaly diagnostic method and/or other desired functionality of the various embodiments disclosed above. In one example, the electronic device may further include: an input device 303, and an output device 304, which are interconnected by a bus system and/or other forms of connection mechanisms (not shown).
In addition, the input device 303 may also include, for example, a keyboard, a mouse, and the like.
The output device 304 can output various information to the outside. The output device 304 may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, etc.
Of course, only some of the components of the electronic device relevant to the present disclosure are shown in fig. 3 for simplicity, components such as buses, input/output interfaces, etc. being omitted. In addition, the electronic device may include any other suitable components depending on the particular application.
Exemplary computer program product and computer readable storage Medium
In addition to the methods and apparatus described above, embodiments of the present disclosure may also be a computer program product comprising computer program instructions which, when executed by a processor, cause the processor to perform steps in a method of diagnosing power generation efficiency of a distributed photovoltaic power plant according to various embodiments of the present disclosure described in the "exemplary methods" section of this specification.
The computer program product may write program code for performing the operations of embodiments of the present disclosure in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present disclosure may also be a computer-readable storage medium, having stored thereon computer program instructions, which when executed by a processor, cause the processor to perform the steps described in the above-mentioned "exemplary methods" section of the present description in diagnosing the power generating efficiency of a distributed photovoltaic power plant according to various embodiments of the present disclosure.
The computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The basic principles of the present disclosure have been described above in connection with specific embodiments, however, it should be noted that the advantages, benefits, effects, etc. mentioned in the present disclosure are merely examples and not limiting, and these advantages, benefits, effects, etc. are not to be considered as necessarily possessed by the various embodiments of the present disclosure. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, since the disclosure is not necessarily limited to practice with the specific details described.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that the same or similar parts between the embodiments are mutually referred to. For system embodiments, the description is relatively simple as it essentially corresponds to method embodiments, and reference should be made to the description of method embodiments for relevant points.
The block diagrams of the devices, apparatuses, devices, systems referred to in this disclosure are merely illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, apparatuses, devices, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.
The methods and apparatus of the present disclosure may be implemented in a number of ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present disclosure may also be implemented as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.
It is also noted that in the apparatus, devices and methods of the present disclosure, components or steps may be disassembled and/or assembled. Such decomposition and/or recombination should be considered equivalent to the present disclosure. The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the disclosure to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.
Claims (10)
1. A method of diagnosing power generation efficiency of a distributed photovoltaic power plant, the method comprising:
collecting initial diagnosis data of the measuring points according to the configured measuring points and the collection frequency, wherein the measuring points are operation parameters of monitoring objects to be collected in the distributed photovoltaic power station;
preprocessing the initial diagnosis data to generate effective diagnosis data of the measuring points;
calculating a calculation result of the configured diagnostic index according to the effective diagnostic data;
generating a power generation efficiency diagnosis result according to the calculation result and the configured power generation efficiency diagnosis rule.
2. The method of claim 1, further comprising, prior to acquiring initial diagnostic data for the measurement points according to the configured measurement points and the acquisition frequency:
according to the topological structure of the distributed photovoltaic power station, configuring a measuring point and a normal interval of measuring point data and collecting frequency of collecting the measuring point data;
and configuring a power generation efficiency diagnosis rule according to the topological structure of the distributed photovoltaic power station, wherein the power generation efficiency diagnosis rule comprises diagnosis categories and diagnosis logics corresponding to each diagnosis category.
3. The method according to claim 2, wherein configuring the normal interval of the measurement points and the measurement point data and the collection frequency of the collection of the measurement point data according to the topology of the distributed photovoltaic power station comprises:
when the circuit topology of the distributed photovoltaic power station is a component-string inverter-alternating current combiner box-box transformer-grid-connected cabinet, wherein:
the configured measuring points comprise three-phase current and voltage of an alternating current side of the inverter, current and voltage of a combiner box, combiner current and voltage and ground faults;
configuring a normal section of the measuring point data according to the rated value of the measuring point data and the allowable fluctuation range;
the acquisition frequency of the configured measurement point data is in the order of minutes or seconds.
4. A method according to claim 3, wherein configuring the power generation efficiency diagnostic rules according to the topology of the distributed photovoltaic power plant comprises:
when the circuit topology of the distributed photovoltaic power station is a component-string inverter-alternating current combiner box-box transformer-grid-connected cabinet, wherein:
the configuration diagnosis categories are inverter electrical losses, combiner box electrical losses, string electrical losses and ground electrical losses;
configuring diagnostic logic corresponding to each diagnostic category, comprising:
setting a power generation efficiency diagnosis index and a diagnosis grade number of each diagnosis class, wherein the diagnosis index is the electric loss rate of each diagnosis class, and the diagnosis grade number is not less than 2;
setting an index threshold for each diagnostic level of each diagnostic category;
determining a diagnosis interval corresponding to each diagnosis grade of each diagnosis class according to the index threshold corresponding to each diagnosis grade of each diagnosis class;
and determining the power generation efficiency diagnosis result of each diagnosis class according to the diagnosis interval in which the calculation result of the diagnosis index of each diagnosis class is positioned, wherein the power generation efficiency diagnosis result of each diagnosis class is the diagnosis grade corresponding to the diagnosis interval of the diagnosis class.
5. The method of claim 4, wherein preprocessing the initial diagnostic data to generate valid diagnostic data for a site comprises:
when the measuring point is the three-phase current and the voltage of the alternating current side of the inverter, removing any one of the data of the three-phase current and the voltage of the alternating current side of the inverter in the initial diagnosis data as 0;
removing null data in the initial diagnostic data;
and removing overrun data in the initial diagnosis data, wherein the overrun data is the initial diagnosis data exceeding a normal section of the configured measuring point data.
6. The method of claim 4, wherein calculating a calculation of the configured diagnostic index from the valid diagnostic data comprises:
when the diagnosis categories are inverter electric loss, bus box electric loss and group series electric loss, calculating an average value of effective diagnosis data of measuring points of each diagnosis category in a set time period, wherein the average value comprises average current and average voltage;
calculating the electric loss rate of each diagnosis class according to the average value of the effective diagnosis data of the measuring point of each diagnosis class in the time period, wherein the calculation formula of the electric loss rate is as follows:
wherein K is the electrical loss rate of each diagnostic class, I a And I ref Respectively the average current and the rated current in the time period, U a And U ref Respectively an average voltage and a rated voltage in the time period;
and when the diagnosis type is the ground loss, outputting a ground loss calculation result according to the ground fault state value.
7. The method according to claim 1, wherein the method further comprises:
configuring an optimization strategy corresponding to the diagnosis grade of each diagnosis class;
when the diagnosis level of each diagnosis category is determined, the diagnosis level of each diagnosis category and the optimization strategy corresponding to the diagnosis level are output.
8. An apparatus for diagnosing power generation efficiency of a distributed photovoltaic power plant, the apparatus comprising:
the data acquisition module is used for acquiring initial diagnosis data of the measuring points according to the configured measuring points and the acquisition frequency, wherein the measuring points are operation parameters of a monitoring object to be acquired in the distributed photovoltaic power station;
the preprocessing module is used for preprocessing the initial diagnosis data to generate effective diagnosis data of the measuring points;
the data calculation module is used for calculating the calculation result of the configured diagnosis indexes according to the effective diagnosis data;
and the diagnosis result module is used for generating a power generation efficiency diagnosis result according to the calculation result and the configured power generation efficiency diagnosis rule.
9. A computer readable storage medium, characterized in that the storage medium stores a computer program for executing the method of any of the preceding claims 1-7.
10. An electronic device, the electronic device comprising:
a processor;
a memory for storing the processor-executable instructions;
the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method of any of the preceding claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311575714.0A CN117633617A (en) | 2023-11-23 | 2023-11-23 | Method and device for diagnosing power generation efficiency of distributed photovoltaic power station |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311575714.0A CN117633617A (en) | 2023-11-23 | 2023-11-23 | Method and device for diagnosing power generation efficiency of distributed photovoltaic power station |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117633617A true CN117633617A (en) | 2024-03-01 |
Family
ID=90026254
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311575714.0A Pending CN117633617A (en) | 2023-11-23 | 2023-11-23 | Method and device for diagnosing power generation efficiency of distributed photovoltaic power station |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117633617A (en) |
-
2023
- 2023-11-23 CN CN202311575714.0A patent/CN117633617A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109146093B (en) | Power equipment field investigation method based on learning | |
| CN102063651B (en) | Urban power grid risk evaluation system based on on-line data acquisition | |
| CN110796368B (en) | Bayesian network-based dynamic risk assessment method and device for community power distribution network | |
| EP2537222B1 (en) | Energy generating system and control thereof | |
| CN112803592A (en) | Intelligent fault early warning method and system suitable for distributed power station | |
| CN109993665B (en) | Online safety and stability assessment method, device and system for power system | |
| CN104821789A (en) | Method for detecting reliability of photovoltaic power generation system | |
| CN103246939A (en) | Security and stability margin based on-line identification method for power network operating safety risk incidents | |
| US11451053B2 (en) | Method and arrangement for estimating a grid state of a power distribution grid | |
| Zhang et al. | Quantitative frequency security assessment method considering cumulative effect and its applications in frequency control | |
| Guo et al. | Evidence-based approach to power transmission risk assessment with component failure risk analysis | |
| Livera et al. | Failure diagnosis of short-and open-circuit fault conditions in PV systems | |
| CN109613372B (en) | Power grid fault diagnosis method based on multi-element power grid database | |
| CN117374978B (en) | Grid-connected scheduling management method and system constructed by combining knowledge graph | |
| CN113238890B (en) | Current sampling loop abnormity diagnosis method and device based on dynamic record data | |
| CN116308306B (en) | New energy station intelligent management system and method based on 5G | |
| Shokrollahi et al. | Reliability assessment of distribution system using fuzzy logic for modelling of transformer and line uncertainties | |
| CN112436542A (en) | Steady-state safety emergency control online pre-decision method considering stability control strategy | |
| GU et al. | Research on intelligent early warning algorithm for distribution network considering extreme climate conditions | |
| CN113990057B (en) | Broadband oscillation station terminal early warning method, system, storage medium and server | |
| CN117633617A (en) | Method and device for diagnosing power generation efficiency of distributed photovoltaic power station | |
| Yue et al. | Development of a risk-informed decision-making capability using standard electric power industry planning tools | |
| CN114765451A (en) | Photovoltaic power station fault detection method based on fault knowledge graph | |
| CN117951633B (en) | Photovoltaic power generation equipment fault diagnosis method and system | |
| Liu et al. | Risk assessment of a generator rejection scheme implemented in a wind farm |
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 |