CN117151696B - Photovoltaic operation and maintenance management system - Google Patents
Photovoltaic operation and maintenance management system Download PDFInfo
- Publication number
- CN117151696B CN117151696B CN202311401928.6A CN202311401928A CN117151696B CN 117151696 B CN117151696 B CN 117151696B CN 202311401928 A CN202311401928 A CN 202311401928A CN 117151696 B CN117151696 B CN 117151696B
- Authority
- CN
- China
- Prior art keywords
- module
- data
- processing unit
- central processing
- unmanned aerial
- 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.)
- Active
Links
- 238000012423 maintenance Methods 0.000 title claims abstract description 65
- 230000036541 health Effects 0.000 claims abstract description 60
- 238000012545 processing Methods 0.000 claims abstract description 49
- 238000007689 inspection Methods 0.000 claims abstract description 34
- 238000011156 evaluation Methods 0.000 claims abstract description 29
- 238000012544 monitoring process Methods 0.000 claims abstract description 28
- 238000004891 communication Methods 0.000 claims abstract description 14
- 238000010586 diagram Methods 0.000 claims abstract description 9
- 238000000034 method Methods 0.000 claims abstract description 8
- 238000013480 data collection Methods 0.000 claims abstract description 7
- 238000011179 visual inspection Methods 0.000 claims abstract description 4
- 238000003745 diagnosis Methods 0.000 claims description 24
- 238000005457 optimization Methods 0.000 claims description 22
- 230000007613 environmental effect Effects 0.000 claims description 18
- 230000006870 function Effects 0.000 claims description 12
- 230000003044 adaptive effect Effects 0.000 claims description 11
- 238000005286 illumination Methods 0.000 claims description 11
- 238000001453 impedance spectrum Methods 0.000 claims description 10
- 238000012360 testing method Methods 0.000 claims description 9
- 230000037072 sun protection Effects 0.000 claims description 8
- 238000013021 overheating Methods 0.000 claims description 7
- 238000010248 power generation Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000001556 precipitation Methods 0.000 claims description 6
- 230000002035 prolonged effect Effects 0.000 claims description 6
- 230000003595 spectral effect Effects 0.000 claims description 6
- 238000001228 spectrum Methods 0.000 claims description 6
- 238000007405 data analysis Methods 0.000 claims description 5
- 238000001514 detection method Methods 0.000 claims description 5
- 230000008569 process Effects 0.000 claims description 5
- 238000005516 engineering process Methods 0.000 claims description 4
- 230000008646 thermal stress Effects 0.000 claims description 4
- 230000015556 catabolic process Effects 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000012937 correction Methods 0.000 claims description 3
- 238000006731 degradation reaction Methods 0.000 claims description 3
- 230000017525 heat dissipation Effects 0.000 claims description 3
- 238000013178 mathematical model Methods 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 230000007246 mechanism Effects 0.000 claims description 3
- 230000000750 progressive effect Effects 0.000 claims description 3
- 230000004044 response Effects 0.000 claims description 3
- 230000000087 stabilizing effect Effects 0.000 claims description 3
- 238000012795 verification Methods 0.000 claims 1
- 238000000157 electrochemical-induced impedance spectroscopy Methods 0.000 abstract description 14
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000007257 malfunction Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000001931 thermography Methods 0.000 description 2
- 230000032683 aging Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000007664 blowing Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000013082 photovoltaic technology Methods 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/243—Classification techniques relating to the number of classes
- G06F18/2433—Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/254—Fusion techniques of classification results, e.g. of results related to same input data
- G06F18/256—Fusion techniques of classification results, e.g. of results related to same input data of results relating to different input data, e.g. multimodal recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Evolutionary Computation (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Marketing (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Tourism & Hospitality (AREA)
- Evolutionary Biology (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Photovoltaic Devices (AREA)
Abstract
The invention relates to the technical field of photovoltaic management, in particular to a photovoltaic operation and maintenance management system, a data collection module, a control module and a control module, wherein the data collection module is used for collecting operation data of a photovoltaic cell panel and an inverter; a central processing unit configured with a processor and a memory; the communication interface is used for transmitting the collected data to the central processing unit; the thermal imager module is provided with a thermal infrared imager and is used for periodically scanning a thermal distribution diagram of the photovoltaic cell panel; the micro-climate monitoring module is used for adjusting the working states of the inverter and the battery plate under different climate conditions; the unmanned aerial vehicle inspection module is provided with an unmanned aerial vehicle and a camera and is used for performing visual inspection; a battery health assessment module based on Electrochemical Impedance Spectroscopy (EIS) techniques. The invention applies various modules and algorithms, covers the full life cycle management of the photovoltaic power station, and provides a comprehensive and efficient operation and maintenance solution for users from battery health evaluation to self-adaptive sunshade and from unmanned aerial vehicle inspection to thermal imager modules.
Description
Technical Field
The invention relates to the technical field of photovoltaic management, in particular to a photovoltaic operation and maintenance management system.
Background
Photovoltaic (PV) technology is a renewable energy technology for converting solar energy into electric energy, and has advantages of environmental friendliness, sustainable development, and the like, however, since Photovoltaic power stations are generally subjected to various environmental and operation conditions, such as weather changes, equipment aging, faults, and the like, highly precise operation and maintenance management is required to ensure long-term and stable operation thereof.
Conventional photovoltaic operation and maintenance management generally relies on manual inspection, basic data analysis, and fixed-pattern maintenance strategies, which are often inadequate to handle complex and diverse operating environments, particularly when faced with photovoltaic power plants in large or remote areas, where conventional management approaches can be inefficient and costly.
In recent years, some advanced photovoltaic operation and maintenance management systems begin to employ more sensors, data analysis algorithms and automation equipment to optimize operation and maintenance activities, however, these systems are often focused on specific problems, such as energy optimization, fault diagnosis or predictive maintenance, but lack a comprehensive solution, and more importantly, few systems are able to adaptively adjust operation and maintenance strategies under different climate conditions and battery conditions to cope with potential environmental risks.
There is therefore an urgent need to develop a new photovoltaic operation and maintenance management system that not only enables health assessment and life prediction of panels, but also provides flexible and adaptive operation and maintenance solutions under different environmental conditions and operating conditions.
Disclosure of Invention
Based on the above objects, the present invention provides a photovoltaic operation and maintenance management system.
A photovoltaic operation and maintenance management system comprising:
the data collection module is used for collecting operation data of the photovoltaic cell panel and the inverter, including current, voltage, power and state information;
the central processing unit is configured with a processor and a memory and is used for executing a series of algorithms, including a fault diagnosis algorithm, a predictive maintenance algorithm and an energy efficiency optimization algorithm;
a communication interface for transmitting the collected data to the central processing unit, the communication interface supporting a plurality of communication protocols including MQTT, HTTP and CoAP;
the thermal imager module is configured with a thermal infrared imager and is used for periodically scanning a thermal distribution diagram of the photovoltaic cell panel so as to detect local overheating or an inefficient area;
the micro-climate monitoring module is used for adjusting the working states of the inverter and the battery plate under different climate conditions so as to cope with potential environmental risks;
the unmanned aerial vehicle inspection module is provided with an unmanned aerial vehicle and a camera, is used for visual inspection, and can be cross-verified with the data of the thermal imager module and the microclimate monitoring module;
the battery health evaluation module is used for periodically evaluating the health condition of the battery plate and predicting the residual service life of the battery plate by using an electrochemical impedance spectrum technology;
the data collection module also comprises sensors for temperature, humidity and illumination intensity, the data of the sensors are used for adjusting an energy efficiency optimization algorithm, and the communication interface is connected to the central processing unit in a wired or wireless mode.
Further, the series of algorithms of the central processing unit specifically includes:
the fault diagnosis algorithm adopts the following mathematical model to carry out fault identification:
wherein,is a fault diagnosis function, ++>Is current, < >>Is voltage, < >>Temperature, < >>And->Is a model parameter, +.>When the preset threshold is exceeded, the system triggers a fault alarm;
the predictive maintenance algorithm predicts maintenance requirements using the following formula:
wherein,is a predictive maintenance function, +.>And->The time derivatives of current, voltage and temperature respectively,,/>and->Is a model parameter, when->When a certain preset threshold is exceeded, the system recommends maintenance;
the energy efficiency optimization algorithm adopts the following optimization functions:
wherein,is an energy efficiency optimization function, +.>Is the inclination angle of the battery plate, ">Is current, < >>Is a resistor->And->Is a model parameter, the system is by maximizing +.>The angle of the battery plate is automatically adjusted to achieve the optimal energy efficiency.
Further, the thermal imager module specifically includes:
the thermal imager module consists of an infrared thermal imager and is provided with an adjustable focal length and an adjustable view angle so as to adapt to photovoltaic cell panels with different sizes and shapes;
the system determines the scanning period of the thermal imager module according to the data of the microclimate monitoring module and the battery health evaluation module through the central processing unit;
at the beginning of each scanning period, the thermal imager module automatically adjusts the focal length and the view angle of the thermal imager module to optimize the image quality;
thermal profile data captured by thermal imager in matrixForm store of>Represents->Line and->The temperature of the column pixel points;
detection of local overheating or inefficiency is performed by the following equation:
wherein,is to->Left upper corner, add->Local temperature differential fraction for sub-regions of size, +.>Is the average temperature of the subregion;
when (when)When the set threshold value is exceeded, the system marks the area as local overheat or inefficiency, and triggers corresponding maintenance or alarm programs through the central processing unit;
the results of the thermal imager module are used to fine tune model parameters in the fault diagnosis algorithm, the predictive maintenance algorithm, and the energy efficiency optimization algorithm.
Further, the microclimate monitoring module specifically includes:
the sensor network comprises a temperature sensor, a humidity sensor, a wind speed sensor, a wind direction sensor and a precipitation sensor;
the sensor network transmits data to the central processing unit in real time and is linked with a fault diagnosis algorithm, a predictive maintenance algorithm and an energy efficiency optimization algorithm;
the central processing unit calculates the following indexes according to the received microclimate data:
wherein,is an environmental risk index, < >>Temperature, < >>Humidity, & gt>Wind speed, & lt>Is wind direction, is (is) a combination of>Is precipitation amount->Is a weight parameter;
when (when)When the preset high risk threshold is exceeded, the central processing unit adjusts the inverter and the battery plate to a 'protection mode', reduces power output, reduces inverter conversion frequency, and starts additional heat dissipation and drainage equipment;
when (when)When the power supply is lower than a preset low risk threshold, the central processing unit can restore the inverter and the battery plate to a normal working mode so as to realize maximum energy efficiency and output;
under the condition of medium risk, the central processing unit adopts progressive adjustment measures;
the real-time data and the adaptability adjustment of the microclimate monitoring module are also used for fine adjustment of other modules, including a thermal imager module, an unmanned aerial vehicle inspection module and a battery health evaluation module.
Further, the unmanned aerial vehicle inspection module specifically includes:
a plurality of unmanned aerial vehicles, each unmanned aerial vehicle is provided with a high-resolution camera, a spectrum analyzer and a wind speed and direction sensor, and the thermal imager is integrated on the unmanned aerial vehicle;
the module is connected with the central processing unit and receives instructions of the inspection path and the focus area;
the central processing unit determines the optimal inspection time and path according to the data of the microclimate monitoring module and the battery health evaluation module;
the unmanned aerial vehicle performs inspection according to a preset flight path, and simultaneously captures high-resolution images, thermal distribution diagrams and spectrum data of the photovoltaic cell panel;
the wind speed and direction sensor of the unmanned aerial vehicle is used for dynamically adjusting a flight path and stabilizing flight, ensuring the accuracy of data under complex microclimate conditions, and identifying potential faults and low-efficiency areas;
the identified potential problem areas will be marked and analyzed by the central processing unit;
the data of the unmanned aerial vehicle inspection module can be used for a microclimate monitoring module, a thermal imager module, a battery health evaluation module and a fault diagnosis algorithm.
Further, the drone inspection module identifies potential malfunctions and areas of inefficiency using the following algorithm:
wherein,is positioned at->Coordinate sum->Latent fault or inefficiency index of spectral band, < +.>Is high resolution image data, < >>Is thermal profile data, +.>Is spectral data, +.>Is a weight coefficient.
Further, the battery health assessment module is equipped with an Electrochemical Impedance Spectroscopy (EIS) testing device consisting of an ac power source, current and voltage sensors, and a data analysis unit;
after a predetermined period or a trigger condition, the battery health assessment module activates an EIS test;
EIS test generates electrochemical impedance spectrum by applying a small amplitude alternating voltage or current to the panel and measuring its corresponding response;
the generated electrochemical impedance spectrum data will be transmitted to the central processing unit and used for health assessment and life prediction using the following algorithm:
wherein,is at the time +.>Health index of->Is at the frequency +.>Electrochemical impedance at>Andthe lowest and highest frequencies of the impedance spectrum, respectively.
Further, the saidAfter calculation, the remaining service life of the panel is predicted +.>:
Wherein,is a correction factor, optimized according to historical data and a model;
when the calculated health indexOr predicted remaining useful life +.>When the battery health evaluation module is lower than a preset threshold value, the battery health evaluation module triggers an early warning or maintenance process.
Further, an adaptive sunshade module is provided with a dynamically adjustable sunshade for adjusting the illumination intensity in an excessive illumination condition to prevent degradation of the panel from prolonged exposure to the excessive illumination condition.
Further, the adaptive sun protection module specifically includes:
a plurality of dynamically adjustable sun visors connected to the photovoltaic panel by a motor, chain or gear mechanism;
the module receives a sunshade instruction from the central processing unit, wherein the instruction is based on input data of a plurality of modules, and comprises a microclimate monitoring module, a battery health evaluation module and an unmanned aerial vehicle inspection module;
the angle and the position of the sun shield are dynamically adjusted according to real-time weather conditions so as to maximize the power generation efficiency of the photovoltaic cell panel;
when the battery health evaluation module detects that the health condition of a certain battery plate area is reduced, the self-adaptive sunshade module partially shields the area so as to lighten the thermal stress and prolong the service life of the area;
the adaptive sun protection module uses the following algorithm to determine the optimal position and angle of the sun protection panel:
wherein,is the sun shield at an angle +.>And position->Performance index at time,/->Is predicted power generation, +.>Is the predicted panel temperature, +.>Is a health index of the battery board,/->Is a weight coefficient;
by real-time calculationThe system dynamically adjusts the sun shield, optimizes the performance of the photovoltaic cell panel and prolongs the service life of the photovoltaic cell panel;
the module is also in communication with the fault diagnosis module and the predictive maintenance module to automatically adjust the visor to the protection mode upon detection of a potential fault or prediction of a high risk environmental factor.
The invention has the beneficial effects that:
according to the invention, a plurality of modules and algorithms are comprehensively applied, full life cycle management of a photovoltaic power station is covered, from battery health evaluation to self-adaptive sun shading and from unmanned aerial vehicle inspection to a thermal imager module, a comprehensive and efficient operation and maintenance solution is provided for a user, and by applying an advanced fault diagnosis algorithm, a predictive maintenance algorithm and an energy efficiency optimization algorithm, the system can automatically identify, predict and process various potential problems, and the requirement of human intervention is greatly reduced, so that the operation and maintenance efficiency is improved.
According to the invention, when facing different climatic conditions and battery states, the system can automatically adjust operation and maintenance strategies, for example, through the microclimate monitoring module, the system can adaptively adjust the working states of the inverter and the battery plate under different climatic conditions, potential environmental risks are reduced, the battery health evaluation module and the application of the adaptive sun-shading module can timely detect the health condition of the battery plate, and the thermal stress is relieved through adjusting the sun-shading plate, so that the service life of the battery plate is effectively prolonged, and the traditional manual inspection and maintenance requirements are greatly reduced through automatic and intelligent operation and maintenance management, so that the operation and maintenance cost is remarkably reduced.
According to the invention, through the microclimate monitoring module, the system can monitor environmental changes in real time, and automatically adjust operation and maintenance strategies according to different environmental conditions, so that the photovoltaic power station can be ensured to operate efficiently and stably in various environments.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only of the invention and that other drawings can be obtained from them without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a system module according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a sensor network according to an embodiment of the present invention.
Detailed Description
The present invention will be further described in detail with reference to specific embodiments in order to make the objects, technical solutions and advantages of the present invention more apparent.
It is to be noted that unless otherwise defined, technical or scientific terms used herein should be taken in a general sense as understood by one of ordinary skill in the art to which the present invention belongs. The terms "first," "second," and the like, as used herein, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", etc. are used merely to indicate relative positional relationships, which may also be changed when the absolute position of the object to be described is changed.
As shown in fig. 1-2, a photovoltaic operation and maintenance management system, comprising:
the data collection module is used for collecting operation data of the photovoltaic cell panel and the inverter, including current, voltage, power and state information;
the central processing unit is configured with a processor and a memory and is used for executing a series of algorithms, including a fault diagnosis algorithm, a predictive maintenance algorithm and an energy efficiency optimization algorithm;
a communication interface for transmitting the collected data to the central processing unit, the communication interface supporting a plurality of communication protocols including MQTT, HTTP and CoAP;
the thermal imager module is configured with a thermal infrared imager and is used for periodically scanning a thermal distribution diagram of the photovoltaic cell panel so as to detect local overheating or an inefficient area;
the micro-climate monitoring module is used for adjusting the working states of the inverter and the battery plate under different climate conditions so as to cope with potential environmental risks such as wind blowing, sand storm or flood;
the unmanned aerial vehicle inspection module is provided with an unmanned aerial vehicle and a camera, is used for visual inspection, and can be cross-verified with the data of the thermal imager module and the microclimate monitoring module;
a battery health assessment module that periodically assesses the health of the panel and predicts its remaining useful life using Electrochemical Impedance Spectroscopy (EIS) techniques;
the data collection module further comprises sensors for temperature, humidity and illumination intensity, the data of the sensors are used for adjusting an energy efficiency optimization algorithm, the communication interface is connected to the central processing unit in a wired or wireless mode, and the algorithm of the central processing unit can automatically adjust the working state of the inverter and the angle of the battery plate according to the collected data so as to achieve optimal energy efficiency.
By integrating various advanced hardware modules and sensor technologies, the system not only can realize highly accurate fault diagnosis and prediction maintenance, but also can carry out self-adaptive adjustment aiming at various environments and operating conditions, thereby greatly improving the running efficiency and stability of the photovoltaic system. Meanwhile, through the application of the thermal imager module, the microclimate monitoring module, the unmanned aerial vehicle inspection module and the battery health evaluation module, the invention solves the key technical problems in the operation and maintenance process of the photovoltaic system in multiple aspects.
The series of algorithms of the central processing unit specifically comprises:
the fault diagnosis algorithm adopts the following mathematical model to carry out fault identification:
wherein,is a fault diagnosis function, ++>Is current, < >>Is voltage, < >>Temperature, < >>And->Is a model parameter, +.>When the preset threshold is exceeded, the system triggers a fault alarm;
the predictive maintenance algorithm predicts maintenance requirements using the following formula:
wherein,is a predictive maintenance function, +.>And->The time derivatives of current, voltage and temperature respectively,,/>and->Is a model parameter, when->When a certain preset threshold is exceeded, the system recommends maintenance;
the energy efficiency optimization algorithm adopts the following optimization functions:
wherein,is an energy efficiency optimization function, +.>Is the inclination angle of the battery plate, ">Is current, < >>Is a resistor->And->Is a model parameter, the system is by maximizing +.>The angle of the battery plate is automatically adjusted to achieve the optimal energy efficiency.
The thermal imager module specifically comprises:
the thermal imager module consists of an infrared thermal imager and is provided with an adjustable focal length and an adjustable view angle so as to adapt to photovoltaic cell panels with different sizes and shapes;
the system determines the scanning period of the thermal imager module according to the data of the microclimate monitoring module and the battery health evaluation module through the central processing unit, for example, the scanning period can be shortened under the condition of high temperature or humidity so as to detect potential problems more frequently;
at the beginning of each scanning period, the thermal imager module automatically adjusts the focal length and the view angle of the thermal imager module to optimize the image quality;
thermal profile data captured by thermal imager in matrixForm store of>Represents->Line and->The temperature of the column pixel points;
detection of local overheating or inefficiency is performed by the following equation:
wherein,is to->Left upper corner, add->Local temperature differential fraction for sub-regions of size, +.>Is the average temperature of the subregion;
when (when)When the set threshold value is exceeded, the system marks the area as local overheat or inefficiency, and triggers corresponding maintenance or alarm programs through the central processing unit;
the result of the thermal imager module is used for fine tuning model parameters in a fault diagnosis algorithm, a prediction maintenance algorithm and an energy efficiency optimization algorithm;
through the series of steps, the thermal imager module can effectively and periodically scan the thermal distribution of the photovoltaic cell panel, so that the local overheating or low-efficiency area can be timely detected and treated, the operation efficiency of the system is improved, and the service lives of the cell panel and the whole photovoltaic system are obviously prolonged.
The microclimate monitoring module specifically comprises:
the sensor network comprises a temperature sensor, a humidity sensor, a wind speed sensor, a wind direction sensor and a precipitation sensor;
the sensor network transmits data to the central processing unit in real time and is linked with a fault diagnosis algorithm, a predictive maintenance algorithm and an energy efficiency optimization algorithm;
the central processing unit calculates the following indexes according to the received microclimate data:
wherein,is an environmental risk index, < >>Temperature, < >>Humidity, & gt>Wind speed, & lt>Is wind direction, is (is) a combination of>Is precipitation amount->Is a weight parameter;
when (when)When the preset high risk threshold is exceeded, the central processing unit adjusts the inverter and the battery plate to a 'protection mode', reduces power output, reduces inverter conversion frequency, and starts additional heat dissipation and drainage equipment;
when (when)Below a preset low risk threshold, at the centerThe processing unit can restore the inverter and the battery plate to a normal working mode so as to realize maximum energy efficiency and output;
under medium risk conditions (i.eBetween high risk and low risk thresholds), the central processing unit takes progressive adjustment measures, such as gradually increasing or decreasing the power output and the switching frequency of the inverter;
the real-time data and the adaptability adjustment of the microclimate monitoring module are also used for fine adjustment of other modules, including a thermal imager module, an unmanned aerial vehicle inspection module and a battery health evaluation module;
through the series of measures, the microclimate monitoring module can effectively adjust the working states of the inverter and the battery plate under different climatic conditions so as to cope with potential environmental risks, thereby improving the reliability and stability of the system and being beneficial to prolonging the service lives of the inverter and the battery plate.
Unmanned aerial vehicle module of patrolling and examining specifically includes:
the system comprises a plurality of unmanned aerial vehicles, a plurality of thermal imaging systems and a plurality of control units, wherein each unmanned aerial vehicle is provided with a high-resolution camera, a spectrum analyzer and a wind speed and direction sensor, and the thermal imaging systems are integrated on the unmanned aerial vehicles;
the module is connected with the central processing unit and receives instructions of the inspection path and the focus area;
the central processing unit determines the optimal inspection time and path according to the data of the microclimate monitoring module and the battery health evaluation module;
the unmanned aerial vehicle performs inspection according to a preset flight path, and simultaneously captures high-resolution images, thermal distribution diagrams and spectrum data of the photovoltaic cell panel;
the wind speed and direction sensor of the unmanned aerial vehicle is used for dynamically adjusting a flight path and stabilizing flight, ensuring the accuracy of data under complex microclimate conditions, and identifying potential faults and low-efficiency areas;
the identified potential problem areas will be marked and analyzed by the central processing unit;
the data of the unmanned aerial vehicle inspection module can be used for a microclimate monitoring module, a thermal imager module, a battery health evaluation module and a fault diagnosis algorithm;
through the measures, the unmanned aerial vehicle inspection module can provide high-efficiency, accurate and comprehensive photovoltaic cell panel inspection service under changeable environments and complicated operation and maintenance requirements, so that potential problems can be found and treated in time, and the automation and intelligent level of the whole photovoltaic operation and maintenance management system is further improved.
The drone inspection module uses the following algorithm to identify potential malfunctions and areas of inefficiency:
wherein,is positioned at->Coordinate sum->Latent fault or inefficiency index of spectral band, < +.>Is high resolution image data, < >>Is thermal profile data, +.>Is spectral data, +.>Is a weight coefficient.
The battery health assessment module is equipped with an Electrochemical Impedance Spectroscopy (EIS) test device consisting of an ac power source, current and voltage sensors, and a data analysis unit;
after a predetermined period or upon a triggering condition (e.g., a potential problem found by the drone inspection module), the battery health assessment module activates the EIS test;
EIS test generates electrochemical impedance spectrum by applying a small amplitude alternating voltage or current to the panel and measuring its corresponding response;
the generated electrochemical impedance spectrum data will be transmitted to the central processing unit and used for health assessment and life prediction using the following algorithm:
wherein,is at the time +.>Health index of->Is at the frequency +.>Electrochemical impedance at>Andthe lowest and highest frequencies of the impedance spectrum, respectively;
through the above measures, the battery health assessment module periodically assesses the health of the panel and predicts its remaining useful life using Electrochemical Impedance Spectroscopy (EIS) techniques. Therefore, the accuracy of prediction maintenance is enhanced, and the overall performance of the photovoltaic cell panel is optimized and the service life of the photovoltaic cell panel is prolonged.
After calculation, the remaining service life of the panel is predicted +.>:
Wherein,is a correction factor, optimized according to historical data and a model;
when the calculated health indexOr predicted remaining useful life +.>When the battery health evaluation module is lower than a preset threshold value, the battery health evaluation module triggers an early warning or maintenance process.
The solar cell panel also comprises an adaptive sun-shading module, wherein the adaptive sun-shading module is provided with a dynamically adjustable sun-shading board, and is used for adjusting the illumination intensity under the condition of excessive illumination so as to prevent the degradation of the solar cell panel due to long-time exposure to the high temperature of the excessive illumination condition.
The self-adaptive sun-shading module specifically comprises:
a plurality of dynamically adjustable sun visors connected to the photovoltaic panel by a motor, chain or gear mechanism;
the module receives a sunshade instruction from the central processing unit, wherein the instruction is based on input data of a plurality of modules, and comprises a microclimate monitoring module, a battery health evaluation module and an unmanned aerial vehicle inspection module;
the angle and the position of the sun shield are dynamically adjusted according to real-time weather conditions (such as solar altitude angle, cloud cover and the like) so as to maximize the power generation efficiency of the photovoltaic cell panel;
when the battery health evaluation module detects that the health condition of a certain battery plate area is reduced, the self-adaptive sunshade module partially shields the area so as to lighten the thermal stress and prolong the service life of the area;
the adaptive sun protection module uses the following algorithm to determine the optimal position and angle of the sun protection panel:
wherein,is the sun shield at an angle +.>And position->Performance index at time,/->Is predicted power generation, +.>Is the predicted panel temperature, +.>Is a health index of the battery board,/->Is a weight coefficient;
by real-time calculationThe system dynamically adjusts the sun shield, optimizes the performance of the photovoltaic cell panel and prolongs the service life of the photovoltaic cell panel;
the module is also in linkage with the fault diagnosis module and the predictive maintenance module to automatically adjust the sun visor to a protection mode when a potential fault is detected or a high risk environmental factor (such as a storm) is predicted;
through the measures, the self-adaptive sun-shading module can adjust the position and the angle of the sun-shading plate in real time so as to adapt to different environmental conditions and battery plate states, so that the power generation efficiency is improved, the service life of the battery plate can be effectively prolonged, and the maintenance cost is reduced.
Those of ordinary skill in the art will appreciate that: the discussion of any of the embodiments above is merely exemplary and is not intended to suggest that the scope of the invention is limited to these examples; the technical features of the above embodiments or in the different embodiments may also be combined within the idea of the invention, the steps may be implemented in any order and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.
The present invention is intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Therefore, any omission, modification, equivalent replacement, improvement, etc. of the present invention should be included in the scope of the present invention.
Claims (4)
1. A photovoltaic operation and maintenance management system, comprising:
the data collection module is used for collecting operation data of the photovoltaic cell panel and the inverter, including current, voltage, power and state information;
a central processing unit configured with a processor and a memory for executing a series of algorithms including a fault diagnosis algorithm, a predictive maintenance algorithm, and an energy efficiency optimization algorithm, wherein:
the fault diagnosis algorithm adopts the following mathematical model to carry out fault identification:
wherein,is a fault diagnosis function, ++>Is current, < >>Is electricPressure (F) of>Temperature, < >>And->Is a model parameter, +.>When the preset threshold is exceeded, the system triggers a fault alarm;
the predictive maintenance algorithm predicts maintenance requirements using the following formula:
wherein,is a predictive maintenance function, +.>And->The time derivatives of current, voltage and temperature respectively,, />and->Is a model parameter, when->When exceeding a certain preset threshold valueThe system recommends maintenance;
the energy efficiency optimization algorithm adopts the following optimization functions:
wherein,is an energy efficiency optimization function, +.>Is the inclination angle of the battery plate, ">Is current, < >>Is a resistor->And->Is a model parameter, the system is by maximizing +.>Automatically adjusting the angle of the battery plate to achieve optimal energy efficiency;
a communication interface for transmitting the collected data to the central processing unit, the communication interface supporting a plurality of communication protocols including MQTT, HTTP and CoAP;
the thermal imager module is configured with a thermal infrared imager and is used for periodically scanning a thermal distribution diagram of the photovoltaic cell panel so as to detect local overheating or an inefficient area;
the micro-climate monitoring module is used for adjusting the working states of the inverter and the battery plate under different climate conditions so as to cope with potential environmental risks, and specifically comprises the following steps:
the sensor network comprises a temperature sensor, a humidity sensor, a wind speed sensor, a wind direction sensor and a precipitation sensor;
the sensor network transmits data to the central processing unit in real time and is linked with a fault diagnosis algorithm, a predictive maintenance algorithm and an energy efficiency optimization algorithm;
the central processing unit calculates the following indexes according to the received microclimate data:
wherein,is an environmental risk index, < >>Humidity, & gt>Wind speed, & lt>Is wind direction, is (is) a combination of>Is precipitation amount->Is a weight parameter;
when (when)When the preset high risk threshold is exceeded, the central processing unit adjusts the inverter and the battery plate to a 'protection mode', reduces power output, reduces inverter conversion frequency, and starts additional heat dissipation and drainage equipment;
when (when)Below a preset lowWhen the risk threshold value is reached, the central processing unit can restore the inverter and the battery plate to a normal working mode so as to realize maximum energy efficiency and output;
under the condition of medium risk, the central processing unit adopts progressive adjustment measures;
the real-time data and the adaptability of the microclimate monitoring module are used for fine adjustment of other modules, including a thermal imager module, an unmanned aerial vehicle inspection module and a battery health evaluation module;
the unmanned aerial vehicle inspection module is provided with an unmanned aerial vehicle and a camera and is used for visual inspection and cross verification with data of the thermal imager module and the microclimate monitoring module, and specifically comprises the following steps:
a plurality of unmanned aerial vehicles, each unmanned aerial vehicle is provided with a high-resolution camera, a spectrum analyzer and a wind speed and direction sensor, and the thermal imager is integrated on the unmanned aerial vehicle;
the module is connected with the central processing unit and receives instructions of the inspection path and the focus area;
the central processing unit determines the optimal inspection time and path according to the data of the microclimate monitoring module and the battery health evaluation module;
the unmanned aerial vehicle performs inspection according to a preset flight path, and simultaneously captures high-resolution images, thermal distribution diagrams and spectrum data of the photovoltaic cell panel;
the unmanned aerial vehicle wind speed and direction sensor is used for dynamically adjusting a flight path and stabilizing flight, data accuracy is guaranteed under complex microclimate conditions, potential faults and low-efficiency areas are identified at the same time, and the unmanned aerial vehicle inspection module identifies the potential faults and the low-efficiency areas by using the following algorithm:
wherein,is positioned at->Coordinate sum->Latent fault or inefficiency index of spectral band, < +.>Is high resolution image data, < >>Is thermal profile data, +.>Is spectral data, +.>Is a weight coefficient;
the identified potential problem areas will be marked and analyzed by the central processing unit;
the data of the unmanned aerial vehicle inspection module are used for a microclimate monitoring module, a thermal imager module, a battery health evaluation module and a fault diagnosis algorithm;
a battery health assessment module periodically assessing the health condition of the battery panel and predicting the remaining service life thereof using EIS technology, the battery health assessment module being equipped with EIS test equipment consisting of an ac power source, current and voltage sensors, and a data analysis unit;
after a predetermined period or a trigger condition, the battery health assessment module activates an EIS test;
EIS test generates electrochemical impedance spectrum by applying a small amplitude alternating voltage or current to the panel and measuring its corresponding response;
the generated electrochemical impedance spectrum data will be transmitted to the central processing unit and used for health assessment and life prediction using the following algorithm:
wherein,is at the time +.>Health index of->Is at the frequency +.>Electrochemical impedance at>And->The lowest and highest frequencies of the impedance spectrum, respectively, said +.>After calculation, the remaining service life of the panel is predicted +.>:
Wherein,is a correction factor, optimized according to historical data and a model;
when the calculated health indexOr predicted remaining useful life +.>When the battery health evaluation module is lower than a preset threshold value, the battery health evaluation module triggers an early warning or maintenance process.
2. The photovoltaic operation and maintenance management system according to claim 1, wherein the thermal imager module specifically comprises:
the thermal imager module consists of an infrared thermal imager and is provided with an adjustable focal length and an adjustable view angle so as to adapt to photovoltaic cell panels with different sizes and shapes;
the system determines the scanning period of the thermal imager module according to the data of the microclimate monitoring module and the battery health evaluation module through the central processing unit;
at the beginning of each scanning period, the thermal imager module automatically adjusts the focal length and the view angle of the thermal imager module to optimize the image quality;
thermal profile data captured by thermal imager in matrixForm store of>Represents->Line and->The temperature of the column pixel points;
detection of local overheating or inefficiency is performed by the following equation:
wherein,is to->Left upper corner, add->Local temperature differential fraction for sub-regions of size, +.>Is the average temperature of the subregion;
when (when)When the set threshold value is exceeded, the system marks the area as local overheat or inefficiency, and triggers corresponding maintenance or alarm programs through the central processing unit;
the results of the thermal imager module are used to fine tune model parameters in the fault diagnosis algorithm, the predictive maintenance algorithm, and the energy efficiency optimization algorithm.
3. The photovoltaic operation and maintenance management system of claim 2, further comprising an adaptive sunshade module configured with a dynamically adjustable sunshade for adjusting the intensity of illumination under excessive illumination conditions to prevent degradation of the panel from prolonged exposure to excessive illumination conditions.
4. A photovoltaic operation and maintenance management system according to claim 3, characterized in that said adaptive sun protection module comprises in particular:
a plurality of dynamically adjustable sun visors connected to the photovoltaic panel by a motor, chain or gear mechanism;
the module receives a sunshade instruction from the central processing unit, wherein the instruction is based on input data of a plurality of modules, and comprises a microclimate monitoring module, a battery health evaluation module and an unmanned aerial vehicle inspection module;
the angle and the position of the sun shield are dynamically adjusted according to real-time weather conditions so as to maximize the power generation efficiency of the photovoltaic cell panel;
when the battery health evaluation module detects that the health condition of a certain battery plate area is reduced, the self-adaptive sunshade module partially shields the area so as to lighten the thermal stress and prolong the service life of the area;
the adaptive sun protection module uses the following algorithm to determine the optimal position and angle of the sun protection panel:
wherein,is the sun shield at an angle +.>And position->Performance index at time,/->Is the predicted amount of power generation,is the predicted panel temperature, +.>Is a health index of the battery board,/->Is a weight coefficient;
by real-time calculationThe system dynamically adjusts the sun shield, optimizes the performance of the photovoltaic cell panel and prolongs the service life of the photovoltaic cell panel;
the module is also in communication with the fault diagnosis module and the predictive maintenance module to automatically adjust the visor to the protection mode upon detection of a potential fault or prediction of a high risk environmental factor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311401928.6A CN117151696B (en) | 2023-10-27 | 2023-10-27 | Photovoltaic operation and maintenance management system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311401928.6A CN117151696B (en) | 2023-10-27 | 2023-10-27 | Photovoltaic operation and maintenance management system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117151696A CN117151696A (en) | 2023-12-01 |
| CN117151696B true CN117151696B (en) | 2024-01-23 |
Family
ID=88884545
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311401928.6A Active CN117151696B (en) | 2023-10-27 | 2023-10-27 | Photovoltaic operation and maintenance management system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117151696B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117650630B (en) * | 2023-12-04 | 2024-07-19 | 中国华电科工集团有限公司 | Photovoltaic power generation system |
| CN118171222B (en) * | 2024-05-15 | 2024-07-26 | 徐州日托光伏科技有限公司 | Photovoltaic module temperature monitoring method and system |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20160069374A (en) * | 2014-12-08 | 2016-06-16 | 이충석 | Multi channel mornitoring system for evaluating several solar modules |
| CN107483014A (en) * | 2017-06-16 | 2017-12-15 | 理光软件研究所（北京）有限公司 | A kind of photovoltaic panel failure automatic detection method |
| CN108009730A (en) * | 2017-12-05 | 2018-05-08 | 河海大学常州校区 | A kind of photovoltaic power station system health status analysis method |
| KR20200059704A (en) * | 2018-11-21 | 2020-05-29 | 안현철 | System of monitoring photovoltaic power generation using failure prediction algorithm |
| KR20200086146A (en) * | 2019-01-08 | 2020-07-16 | (주)에스엠소프트 | Farm-based photovoltaic management system that optimizes crop growth and photovoltaic environment |
| CN111444055A (en) * | 2020-04-26 | 2020-07-24 | 昆山润石智能科技有限公司 | System for health assessment and maintenance of equipment |
| KR20210037175A (en) * | 2019-09-27 | 2021-04-06 | 인피니티에너지주식회사 | Operation And Maintenance System of Solar Panel Power Plant Through IoT-based Smart Sensor |
| CN115293370A (en) * | 2022-05-16 | 2022-11-04 | 华能南京金陵发电有限公司 | Digital integrated operation and maintenance management system of distributed photovoltaic power station |
| CN115589187A (en) * | 2022-10-28 | 2023-01-10 | 浙江中新电力工程建设有限公司 | Photovoltaic power generation system and method for improving power generation efficiency of solar cell |
| CN115720080A (en) * | 2022-11-14 | 2023-02-28 | 苏州热工研究院有限公司 | Inspection control system and inspection control method for power generation area of photovoltaic power station |
| CN116205381A (en) * | 2023-05-05 | 2023-06-02 | 伊发控股集团有限公司 | Photovoltaic energy storage management method and related equipment |
| CN116452042A (en) * | 2023-04-04 | 2023-07-18 | 上海时觉物联网科技有限公司 | Intelligent Internet of things safety supervision method and system for photovoltaic power station |
-
2023
- 2023-10-27 CN CN202311401928.6A patent/CN117151696B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20160069374A (en) * | 2014-12-08 | 2016-06-16 | 이충석 | Multi channel mornitoring system for evaluating several solar modules |
| CN107483014A (en) * | 2017-06-16 | 2017-12-15 | 理光软件研究所（北京）有限公司 | A kind of photovoltaic panel failure automatic detection method |
| CN108009730A (en) * | 2017-12-05 | 2018-05-08 | 河海大学常州校区 | A kind of photovoltaic power station system health status analysis method |
| KR20200059704A (en) * | 2018-11-21 | 2020-05-29 | 안현철 | System of monitoring photovoltaic power generation using failure prediction algorithm |
| KR20200086146A (en) * | 2019-01-08 | 2020-07-16 | (주)에스엠소프트 | Farm-based photovoltaic management system that optimizes crop growth and photovoltaic environment |
| KR20210037175A (en) * | 2019-09-27 | 2021-04-06 | 인피니티에너지주식회사 | Operation And Maintenance System of Solar Panel Power Plant Through IoT-based Smart Sensor |
| CN111444055A (en) * | 2020-04-26 | 2020-07-24 | 昆山润石智能科技有限公司 | System for health assessment and maintenance of equipment |
| CN115293370A (en) * | 2022-05-16 | 2022-11-04 | 华能南京金陵发电有限公司 | Digital integrated operation and maintenance management system of distributed photovoltaic power station |
| CN115589187A (en) * | 2022-10-28 | 2023-01-10 | 浙江中新电力工程建设有限公司 | Photovoltaic power generation system and method for improving power generation efficiency of solar cell |
| CN115720080A (en) * | 2022-11-14 | 2023-02-28 | 苏州热工研究院有限公司 | Inspection control system and inspection control method for power generation area of photovoltaic power station |
| CN116452042A (en) * | 2023-04-04 | 2023-07-18 | 上海时觉物联网科技有限公司 | Intelligent Internet of things safety supervision method and system for photovoltaic power station |
| CN116205381A (en) * | 2023-05-05 | 2023-06-02 | 伊发控股集团有限公司 | Photovoltaic energy storage management method and related equipment |
Non-Patent Citations (1)
| Title |
|---|
| 用于光伏厂智能巡检的红外式无人机系统设计;陈明澍;仪器仪表用户;第24卷(第3期);28-32、70 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117151696A (en) | 2023-12-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117151696B (en) | Photovoltaic operation and maintenance management system | |
| Guerriero et al. | Monitoring and diagnostics of PV plants by a wireless self-powered sensor for individual panels | |
| KR20200059704A (en) | System of monitoring photovoltaic power generation using failure prediction algorithm | |
| JP5856294B2 (en) | Photovoltaic power generation monitoring method and solar power generation monitoring system used for the method | |
| KR102084784B1 (en) | Method for managing the operation of Photovoltaic Power Generation based on machine learning | |
| US20160190984A1 (en) | System and method for performance analysis and classification of losses for solar power systems | |
| KR20200059706A (en) | System of monitoring photovoltaic power generation using weather data | |
| KR101114240B1 (en) | Multi zone-inverter photovoltaic power generation system | |
| KR101720669B1 (en) | PV system control and monitoring integrated system | |
| CN107727145A (en) | A kind of distributed power source state monitoring apparatus and method based on Internet of Things | |
| CN114669569B (en) | Big data-based automatic cleaning system for photovoltaic module | |
| KR101647345B1 (en) | Apparatus for generating electricity using sunlight with monitoring function | |
| CN103712685B (en) | Photovoltaic array irradiance measurement identification method | |
| CN115589187A (en) | Photovoltaic power generation system and method for improving power generation efficiency of solar cell | |
| CA3230695A1 (en) | System and method for identifying defective solar panels and to quantify energy loss | |
| KR20160049764A (en) | System and method for notifying optimum slope angle of angle adjusting type solar panel | |
| CN117811495A (en) | Solar photovoltaic power supply monitoring system | |
| KR102228512B1 (en) | Photovoltaic Power Generation Apparatus with Remote Control Function and Function to Monitor the Failure of Solar Power Plant and Fire at Connection Board using Machine Learning | |
| KR101544713B1 (en) | Method and apparatus for deciding output power lowering of solar cell generator | |
| KR20060113053A (en) | System for measuring snowfall and method thereof | |
| CN116167514A (en) | Method and system for predicting electric energy transmission capacity of power transmission wire | |
| US20230275544A1 (en) | System, Device and Method for Determining Soiling of PV Modules | |
| KR20150076473A (en) | System for forcasting residual life of a solar photovoltaic power generation | |
| CN204334477U (en) | A kind of photovoltaic system and inverter energy output are estimated and environment monitoring device | |
| CN118410445B (en) | Distributed photovoltaic abnormal data detection method, system, electronic equipment and storage medium |
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 |