CN114091905A - Photovoltaic module cleaning method and system considering irradiance - Google Patents
Photovoltaic module cleaning method and system considering irradiance Download PDFInfo
- Publication number
- CN114091905A CN114091905A CN202111389795.6A CN202111389795A CN114091905A CN 114091905 A CN114091905 A CN 114091905A CN 202111389795 A CN202111389795 A CN 202111389795A CN 114091905 A CN114091905 A CN 114091905A
- Authority
- CN
- China
- Prior art keywords
- index
- irradiance
- evaluation
- power station
- comprehensive evaluation
- 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
- 238000004140 cleaning Methods 0.000 title claims abstract description 66
- 238000000034 method Methods 0.000 title claims abstract description 55
- 238000011156 evaluation Methods 0.000 claims abstract description 190
- 238000003915 air pollution Methods 0.000 claims abstract description 19
- 238000004458 analytical method Methods 0.000 claims abstract description 10
- 239000011159 matrix material Substances 0.000 claims description 25
- 239000000428 dust Substances 0.000 claims description 18
- 238000004364 calculation method Methods 0.000 claims description 12
- 238000012545 processing Methods 0.000 claims description 7
- 230000005855 radiation Effects 0.000 claims description 7
- 238000010248 power generation Methods 0.000 claims description 6
- 238000011109 contamination Methods 0.000 claims description 5
- 239000002245 particle Substances 0.000 claims description 5
- 238000002310 reflectometry Methods 0.000 claims description 5
- 238000013077 scoring method Methods 0.000 claims description 4
- 238000001514 detection method Methods 0.000 claims description 3
- 239000002689 soil Substances 0.000 claims description 3
- 238000013480 data collection Methods 0.000 abstract description 3
- 230000006870 function Effects 0.000 description 15
- 238000003860 storage Methods 0.000 description 14
- 238000010586 diagram Methods 0.000 description 10
- 238000004590 computer program Methods 0.000 description 9
- RAHZWNYVWXNFOC-UHFFFAOYSA-N Sulphur dioxide Chemical compound O=S=O RAHZWNYVWXNFOC-UHFFFAOYSA-N 0.000 description 6
- 230000000694 effects Effects 0.000 description 4
- JCXJVPUVTGWSNB-UHFFFAOYSA-N nitrogen dioxide Inorganic materials O=[N]=O JCXJVPUVTGWSNB-UHFFFAOYSA-N 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 238000007726 management method Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 230000008021 deposition Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 239000006185 dispersion Substances 0.000 description 2
- 238000013210 evaluation model Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- MGWGWNFMUOTEHG-UHFFFAOYSA-N 4-(3,5-dimethylphenyl)-1,3-thiazol-2-amine Chemical compound CC1=CC(C)=CC(C=2N=C(N)SC=2)=C1 MGWGWNFMUOTEHG-UHFFFAOYSA-N 0.000 description 1
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 1
- YCKRFDGAMUMZLT-UHFFFAOYSA-N Fluorine atom Chemical compound [F] YCKRFDGAMUMZLT-UHFFFAOYSA-N 0.000 description 1
- CBENFWSGALASAD-UHFFFAOYSA-N Ozone Chemical compound [O-][O+]=O CBENFWSGALASAD-UHFFFAOYSA-N 0.000 description 1
- 230000000712 assembly Effects 0.000 description 1
- 238000000429 assembly Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 229910002091 carbon monoxide Inorganic materials 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000003344 environmental pollutant Substances 0.000 description 1
- 229910052731 fluorine Inorganic materials 0.000 description 1
- 239000011737 fluorine Substances 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000013618 particulate matter Substances 0.000 description 1
- 231100000719 pollutant Toxicity 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 238000011158 quantitative evaluation Methods 0.000 description 1
- 150000003254 radicals Chemical group 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000002834 transmittance Methods 0.000 description 1
Images
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
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- 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
- G06Q50/10—Services
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Tourism & Hospitality (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- General Engineering & Computer Science (AREA)
- Marketing (AREA)
- Algebra (AREA)
- Software Systems (AREA)
- Operations Research (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Databases & Information Systems (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Evolutionary Biology (AREA)
- Probability & Statistics with Applications (AREA)
- Game Theory and Decision Science (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Quality & Reliability (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computing Systems (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Photometry And Measurement Of Optical Pulse Characteristics (AREA)
Abstract
The invention discloses a photovoltaic module cleaning method and system considering irradiance.A irradiance evaluation index system is established according to an air pollution index, a module surface pollution index, a ground pollution index and other factors; data collection is carried out according to the established irradiance evaluation index system, the membership degree of each index in the irradiance evaluation index system is determined according to a membership degree function, and the weight value of the irradiance evaluation index system is calculated according to an entropy weight method; carrying out fuzzy comprehensive evaluation on the area by combining the weight value and the membership degree to obtain a fuzzy comprehensive evaluation result of the evaluation layer index i; calculating a comprehensive evaluation value and a weighted average evaluation value according to the fuzzy comprehensive evaluation result of the evaluation layer index i to obtain a score for evaluating the comprehensive evaluation of the irradiance of the photovoltaic power station; and determining the cleaning priority according to the grading analysis influence factors for evaluating the comprehensive evaluation of the irradiance of the photovoltaic power station, and giving a cleaning strategy. The photovoltaic power station energy-saving control system can recover economic loss caused by pollution of the photovoltaic module to the photovoltaic power station.
Description
Technical Field
The invention belongs to the technical field of photovoltaic system application, and particularly relates to a photovoltaic module cleaning method and system considering irradiance.
Background
In the research of a photovoltaic power generation system, besides panel materials and key technologies such as conversion efficiency, power prediction, inversion efficiency, Maximum Power Point Tracking (MPPT), off-grid and grid-connected control, island protection, power quality management and the like, for a photovoltaic power station which runs for a long time, the influence of surface dust deposition, underlying surface conditions, air quality, other geography, weather and the like on irradiance is a problem which cannot be ignored. The surface dust, the underlying surface condition, the air quality and other geographic and meteorological phenomena of the photovoltaic module have the functions of reflecting, scattering and absorbing solar radiation, namely the transmittance of the solar radiation is reduced, so that the amount of the solar radiation received by the photovoltaic panel is reduced, the output power is reduced, and the effect is more obvious along with the increase of the dust deposition thickness and the like. In addition, dust absorbs pollutants of corrosive chemical components in air, so that a certain degree of heat preservation and corrosion effects are formed on the photovoltaic panel, and the photoelectric conversion efficiency of the photovoltaic panel is reduced. Research shows that the accumulated dust can reduce the generated energy of the photovoltaic module by about 20% on average, which causes huge economic loss to the power station.
At present, the problems of difficult cleaning of components, difficult grasping of cleaning nodes, untimely cleaning and the like in a photovoltaic power station become problems which are urgently needed to be solved in the development of the photovoltaic industry; the photovoltaic power station is subjected to huge loss due to too frequent cleaning or lack of cleaning, and the module cleaning period is determined according to the influence of accumulated dust on the power generation capacity of the photovoltaic module.
On the other hand, due to the increasing of the loading amount of the photovoltaic power station in recent years, the establishment of the irradiance evaluation method of the photovoltaic power station is urgent. Although the continuous development of the photovoltaic power station brings huge social and economic benefits, the difference of irradiance of the power station often causes resource waste. Therefore, the utilization rate of the power station to the solar energy resources can be adjusted in a targeted manner through power station irradiance evaluation, namely, specific factors influencing comprehensive evaluation of the photovoltaic power station irradiance are known under the condition that the photovoltaic power station is continuously developed at the present stage, and the influencing factors are timely and effectively adjusted by establishing a proper evaluation method so as to effectively reduce waste of the solar energy resources and improve the generating capacity of the photovoltaic power station.
In conclusion, it is significant to understand irradiance of the photovoltaic power station, especially with the proposal of a 'dual carbon target' and the comprehensive evaluation and evaluation of irradiance of the photovoltaic power station with the increasing of photovoltaic loading. However, the current evaluation method for comprehensive evaluation of irradiance of the photovoltaic power station is lack of specification, and most of the evaluation method is research on a theoretical system. No consensus has been formed yet on systematic methods for comprehensive evaluation of irradiance of photovoltaic power stations and cleaning strategies.
Disclosure of Invention
The invention aims to solve the technical problem of providing a photovoltaic assembly cleaning method and system considering irradiance aiming at the defects in the prior art, which are suitable for calculating irradiance of photovoltaic power stations in different regions and can recover economic loss of the photovoltaic power stations caused by pollution of photovoltaic assemblies.
The invention adopts the following technical scheme:
a method of irradiance-aware photovoltaic module cleaning, comprising the steps of:
s1, establishing an irradiance evaluation index system according to the air pollution index, the component surface pollution index, the ground pollution index and other factors;
s2, collecting data according to the irradiance evaluation index system established in the step S1, determining the membership degree of each index in the irradiance evaluation index system according to a membership degree function, and calculating the weight value of the irradiance evaluation index system according to an entropy weight method;
s3, carrying out fuzzy comprehensive evaluation on the area by combining the weight value and the membership grade obtained in the step S2 to obtain a fuzzy comprehensive evaluation result of the irradiance of the power station;
s4, calculating to obtain a score of the comprehensive evaluation irradiance of the photovoltaic power station irradiance according to the power station irradiance fuzzy comprehensive evaluation result obtained in the step S3 and the corresponding score vector;
and S5, determining the cleaning priority according to the grading analysis influence factors of the comprehensive evaluation of the irradiance of the photovoltaic power station obtained in the step S4, and giving a cleaning strategy.
Specifically, in step S1, the air pollution index includes PM2.5、PM10、AQI、SO2、NO2CO and O3(ii) a The component surface contamination index comprisesThe dust particle size, the dust thickness and the shielding area ratio; the ground pollution index comprises the reflectivity of the underlying surface and the soil texture; other factors include geographically and weather-related rainfall, air temperature, wind speed, cloud cover, hours of sunshine, total solar radiation and visibility.
Specifically, in step S2, the membership degree R (V, x) represents the membership degree of the index x to the state rank V, data of each index in the area is obtained by an expert scoring method, and the state rank p to which each index belongs is selected according to the current situation to obtain the membership degree R (V, x) of each index to each state rank, where the state rank V is { V ═ V { (V, x) }1，v2，v3，v4，v5}，v1The quality is excellent; v. of2Is good; v. of3Is general; v. of4Mild contamination; v. of5The pollution is severe; the corresponding score vector is G ═ 1, 0.75, 0.50, 0.25, 0 }.
Specifically, in step S2, a judgment matrix is constructed according to an entropy weight method, and the weight value is calculated as:
s2021, m samples are formed, and n evaluation indexes have an evaluation matrix R ═ R (R)ij)m×n，rijIs the evaluation value of the ith sample under the jth index;
s2022, carrying out standardization processing on the evaluation matrix R in the step S2021 to obtain a standardization matrix B;
s2023, calculating entropy values H of evaluation indexesij；
S2024, calculating entropy weight W of each evaluation index;
s2025, determining the weight a of each index as follows:
wherein, w ″iObtained by expert scoring for subjective weights, wiThe weights obtained by the entropy weight method.
Further, in step S2023, the entropy values H of the evaluation indexesijComprises the following steps:
wherein, BijFor normalizing the calculation result, n is the index number.
Further, in step S2024, the entropy weight W of each evaluation index is:
wherein m is the number of samples, HjIs the entropy value and n is the index number.
Specifically, in step S3, the fuzzy comprehensive evaluation result V of the plant irradiance is obtainediThe following were used:
Vi=Wi×R′i
wherein Wi is a weight vector of each index; r' i is a membership matrix of all indexes under the evaluation layer i, and the membership matrix is obtained by calculating a membership function, wherein the smaller the better the type index:
Xij＝1-Xj(i-1)
for larger better type indicators:
Xij＝1-Xj(i-1)
wherein v isijThe j index belongs to the boundary value of the ith grade; v. ofj(i-1)The j index is subordinate to the boundary value of the (i-1) th grade; x is the number ofjIs the result of the detection of the j index,Xijand calculating the result of the index membership.
Specifically, in step S4, the comprehensive evaluation value score of each evaluation index is calculated based on each level of comprehensive evaluation matrix, and the score Zi for evaluating the comprehensive power generation performance of the photovoltaic power station is obtained as follows:
Zi=Vi×GT
wherein Vi is a fuzzy comprehensive evaluation result of the irradiance evaluation index i; g is the index rank vector and T is the transposed symbol.
Specifically, step S5 specifically includes:
s501, judging the irradiance level according to the grade obtained in the step S4 for evaluating the comprehensive evaluation of the irradiance of the photovoltaic power station;
s502, obtaining the influence degree of a certain index in an irradiance evaluation index system on irradiance according to an entropy weight method, and comparing to obtain an index with the maximum influence degree on the irradiance;
s503, judging the current situation of a certain index in the irradiance evaluation index system according to the comprehensive evaluation value in the step S4;
and S504, analyzing the cleaning priority by combining the comprehensive evaluation value, wherein the result of the preferential cleaning irradiance evaluation is the photovoltaic module with light pollution and severe pollution.
Another technical solution of the present invention is a photovoltaic module cleaning method system considering irradiance, including:
the system module is used for establishing an irradiance evaluation index system according to the air pollution index, the component surface pollution index, the ground pollution index and other factors;
the calculation module is used for collecting data according to the irradiance evaluation index system established by the system module, determining the membership degree of each index in the irradiance evaluation index system according to the membership degree function, and calculating the weight value of the irradiance evaluation index system according to an entropy weight method;
the evaluation module is used for carrying out fuzzy comprehensive evaluation on the area by combining the weighted value and the membership degree obtained by the calculation module to obtain a fuzzy comprehensive evaluation result of the irradiance of the power station;
the grading module is used for calculating a grade for evaluating the comprehensive irradiance evaluation of the photovoltaic power station irradiance according to the power station irradiance fuzzy comprehensive evaluation result obtained by the evaluation module and the corresponding score vector;
and the cleaning module determines the cleaning priority according to the grading analysis influence factors of the comprehensive evaluation of the irradiance of the photovoltaic power station obtained by the grading module and gives a cleaning strategy.
Compared with the prior art, the invention has at least the following beneficial effects:
the invention relates to a photovoltaic module cleaning method considering irradiance, which comprises the steps of firstly establishing an index system influencing the irradiance from 4 aspects, wherein 19 indexes are provided, evaluating the irradiance state of an air pollution index influencing the irradiance, a pollution index on the surface of a module, a ground pollution index and other geographic and meteorological factors on the basis of an entropy weight method and a fuzzy comprehensive evaluation model, and analyzing the priority of module cleaning, thereby establishing a photovoltaic module cleaning scheme in a targeted manner on the basis of the irradiance, providing a timely dust cleaning time point for the module and a power station at a management level, playing an instructive significance, and recovering economic loss brought to the photovoltaic by the pollution of the photovoltaic module in the power station.
Furthermore, researches show that a dust covering layer is formed on the surface of the photovoltaic glass by the dust effect, the light receiving quantity of the solar cell and the total electric energy output quantity of the photovoltaic module are obviously reduced, the reduction range of the generated energy reaches 5% -45%, and the dust covering layer is an important reason for influencing the working efficiency of the photovoltaic power generation system. In addition, a ground photovoltaic module with a high ground reflectivity will power down faster than a ground with a low reflectivity. The above conditions all affect the power generation condition of the power station by affecting irradiance, dust effects mainly come from air pollution and pollution on the surface of components, and the ground reflection condition is related to ground pollution. Meanwhile, the irradiance received by the power station can be influenced by factors such as geography and weather of the position of the power station. In summary, the present invention evaluates plant irradiance from an air pollution index, a component surface pollution index, a ground pollution index, and other factors.
Furthermore, in the invention, the membership degree is the corresponding degree of the test result of each index in the grading evaluation range. If the degree of membership is closer to 1, the index i belongs to the grade V1The higher the degree of (A), the closer the degree of membership is to 0, indicating that the index i belongs to V1The lower the degree of (c). The index belonging to V is represented by a membership function R' (x) which takes values in an interval (0, 1)iThe degree of (c) is high or low. The membership degree belongs to the concept in a fuzzy evaluation function, and the fuzzy comprehensive evaluation is a very effective multi-factor decision method for comprehensively evaluating things influenced by various factors.
Further, in the invention, the weight refers to the importance degree of a certain index relative to the irradiance, which is different from the general proportion, and represents the percentage of the certain index, and the emphasis is on the relative importance degree of the evaluation index, which is inclined to the contribution degree or importance degree of the index to the irradiance.
Further, "entropy" is an information management method, which is a measure of uncertainty. The larger the entropy is, the more disordered the information is, and the less the information is carried; the smaller the entropy is, the more ordered the information is, and the more information is carried. In the method, the entropy value is a judgment on the dispersion degree of the index, and the larger the dispersion degree of the index is, the larger the influence of the index on the irradiance is.
Further, the entropy weight, i.e. the weight of the index, is calculated according to the entropy value.
Further, irradiance comprehensive evaluation result ViThe comprehensive irradiance evaluation is used for evaluating the membership degree of different grades, and is a fuzzy set.
Furthermore, the irradiance comprehensive evaluation result obtained in the last step is a fuzzy set, and the comprehensive score for obtaining the irradiance is obtained by calculating the fuzzy set of the irradiance comprehensive evaluation result and the score vector. And a targeted cleaning strategy is formulated through the comprehensive scoring result, and the fuzzy set obtained in the S3 cannot accurately formulate the cleaning strategy.
Furthermore, whether a cleaning strategy needs to be cleaned is determined according to the obtained irradiance comprehensive scoring result, and the photovoltaic assembly is timely and purposefully cleaned. Reduce the economic loss to the power station caused by untimely component cleaning. .
In conclusion, the method is suitable for calculating the daily irradiance conditions of different photovoltaic power stations. And a photovoltaic assembly cleaning scheme is established in a targeted manner according to the irradiance condition, so that guidance is provided for cleaning the photovoltaic power station, and the economic loss of the photovoltaic power station caused by pollution of the photovoltaic assembly is saved.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is a schematic diagram of an irradiance evaluation index system of a photovoltaic power station.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be understood that the terms "comprises" and/or "comprising" indicate the presence of the stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Various structural schematics according to the disclosed embodiments of the invention are shown in the drawings. The figures are not drawn to scale, wherein certain details are exaggerated and possibly omitted for clarity of presentation. The shapes of various regions, layers and their relative sizes and positional relationships shown in the drawings are merely exemplary, and deviations may occur in practice due to manufacturing tolerances or technical limitations, and a person skilled in the art may additionally design regions/layers having different shapes, sizes, relative positions, according to actual needs.
The invention provides a photovoltaic module cleaning method considering irradiance, which comprehensively analyzes the influence on irradiance received by a photovoltaic module from factors such as an air pollution index, a pollution index of a module surface, a ground pollution index and other geographic and meteorological factors, establishes an evaluation method for the influence on the irradiance based on an entropy weight method-fuzzy comprehensive evaluation model, and establishes a photovoltaic module cleaning method considering the irradiance according to the evaluation result of the irradiance; firstly, establishing an expert grading Multi-level analysis (MAES) model, carrying out hierarchical decomposition on the irradiance comprehensive evaluation index of the photovoltaic power station, then determining the membership degree and the weight value of each index by adopting a fuzzy-entropy weight method, and finally obtaining the irradiance comprehensive evaluation value of the photovoltaic power station through fuzzy entropy weight calculation. And comparing the value with the index grading vector to obtain an irradiance comprehensive evaluation result of the whole photovoltaic power station.
Referring to fig. 1, a method for cleaning a photovoltaic module with irradiance consideration according to the present invention includes the following steps:
s1, establishing an index system framework
The method establishes an irradiance evaluation index system from the air pollution index, the pollution index of the surface of the component, the ground pollution index and other geographic and meteorological factors, combines the main factors influencing the irradiance together for analysis and evaluation to obtain the irradiance result, and determines the cleaning strategy of the photovoltaic component.
Referring to fig. 2, the index system is divided into four aspects, which are an air pollution index a, a component surface pollution index B, a ground pollution index C and other factors D;
the air pollution index A is the influence of air quality on irradiance; the component surface pollution index B is the influence of the component surface condition on irradiance; the ground pollution index C is the influence of the underlying surface condition on the irradiance; other factors D are some geographic and meteorological factors that affect irradiance.
Air pollution index a: selecting PM2.5(Fine particulate matter), PM10(respirable particles), AQI (air pollution index), SO2(Sulfur dioxide), NO2(Nitrogen dioxide), CO (carbon monoxide) and O37 indexes such as (ozone) are used as sub-elements for representing the air quality;
component surface contamination index B: selecting 3 indexes such as dust particle size, dust thickness and shielding area ratio as sub-factors for representing the state of the component;
ground pollution index C: selecting 2 indexes of the reflectivity of the underlying surface and the soil texture as sub-elements for representing the condition of the underlying surface;
other factors D: 7 indexes such as rainfall, air temperature, wind speed, cloud cover, sunshine duration, total solar radiation and visibility related to geography and weather are selected as the indexes for representing the influence of geography and weather factors.
S2, collecting data according to the index system established in the step S1 to obtain the membership degree and the weight value of each index in the index system;
s201, degree of membership
The membership degree of each index represents the membership degree of the current value of each index to the state grade, and the state grade is set as V, wherein V represents five states of the index, wherein V represents the superior state, the good state, the normal state, the light pollution state and the heavy pollution state, and V represents the five states of the index1The quality is excellent; v. of2Is good; v. of3Is general; v. of4Slight pollution is caused; v. of5Severe contamination; the corresponding score vector is G ═ {1, 0.75, 0.50, 0.25, 0 }; the degree of membership R (v, x) represents the degree of membership of the index x to the status level v, the closer R (v, x) is to 1, the higher the degree of membership of the index x to the status level v, the closer R (v, x) is to 0, and the higher the degree of membership of the index x to the status level vLow;
and obtaining data of each index in the region by an expert scoring method, literature data and the like, and selecting the state grade v to which each index belongs by an expert according to the current situation to obtain the membership degree R (v, x) of each index to each state grade.
S202, weight value
The weight value represents the size of the overall part occupied by each index and the importance degree of the influence on the overall capacity, the weight vector represents that a plurality of weight values are summarized in a single-row matrix form, and the weight matrix represents that a plurality of indexes are summarized in a matrix form of membership. And calculating the weight value according to an entropy weight method, and calculating to obtain the weight value by constructing a judgment matrix.
S2021, forming m samples, and n evaluation indexes having an evaluation matrix R (R)ij)m×n. Wherein r isijIs the evaluation value of the ith sample under the jth index;
s2022, the evaluation matrix in step S2021 is normalized to obtain a normalized matrix B.
The standardized calculation method is divided into the following 2 cases:
the larger and more preferred index:
the smaller the more optimal index:
wherein r ismax、rminThe maximum value and the minimum value of the same evaluation index are indicated.
S2023, calculating entropy values H of evaluation indexesij；
Wherein,
when f isijWhen equal to 0, lnfijIt is meaningless.
Suppose fijWhen equal to 0, fijlnfij＝0。
S2024, calculating entropy weight W of each evaluation index;
satisfies Σ wi＝1。
S2025, determining the weight a of each index.
Wherein, w ″iThe subjective weight is obtained by an expert scoring method.
S3, carrying out fuzzy comprehensive evaluation on the areas by combining the weight values and the membership degrees
The comprehensive evaluation method is characterized in that qualitative evaluation is converted into quantitative evaluation according to the membership theory of fuzzy mathematics, namely, the fuzzy mathematics is used for making overall evaluation on objects or objects which are restricted by various factors. The method applies a fuzzy comprehensive evaluation method, combines the membership degree and the weight value for operation to obtain a fuzzy comprehensive evaluation result of each evaluation layer, and finally obtains a fuzzy comprehensive evaluation result, namely the grade of the comprehensive evaluation of the irradiance of the photovoltaic power station.
Calculating a fuzzy comprehensive evaluation result of each evaluation layer according to a formula (1), namely a membership matrix of the evaluation layer:
Vi=Wi×R′i (1)
wherein v isiThe fuzzy comprehensive evaluation result is an evaluation layer index i; wi is a weight vector of each index; and R' i is a membership matrix of all indexes under the evaluation layer i.
The membership matrix is obtained by calculating a membership function according to the following specific process:
for smaller better type indicators:
Xij＝1-Xj(i-1)
for larger better type indicators:
Xij＝1-Xj(i-1)
wherein v isijThe j index belongs to the boundary value of the ith grade; the boundary value is calculated by the grading standard in the table 2, the grading standard for a single interval is the boundary value, and the grading boundary value for a double interval is the interval middle value; v. ofj(i-1)The j index is subordinate to the boundary value of the (i-1) th grade; x is a radical of a fluorine atomjThe j index is the detection result.
S4, calculating a comprehensive evaluation value and a weighted average evaluation value
The comprehensive evaluation value represents the current state of each index, and the current state value comprehensive score Zi of each evaluation index is calculated based on each level of comprehensive evaluation matrix according to the following formula.
Zi＝Vi×GT
Wherein Vi is a fuzzy comprehensive evaluation result of the irradiance evaluation index i; g is the index rank vector {1, 0.75, 0.50, 0.25, 0 }.
And S5, analyzing the influence factors and giving a cleaning strategy.
S501, judging the irradiance level according to the final fuzzy comprehensive evaluation result obtained in the step S3;
s502, obtaining the influence degree of a certain index in an index system on irradiance according to an entropy weight method, and obtaining an index with larger influence degree on irradiance through comparison;
s503, judging the current situation of a certain index in the index system according to the comprehensive evaluation value obtained in the step S4;
s504, analyzing the cleaning priority by combining the comprehensive evaluation value: the components with light and heavy pollution are obtained by preferentially cleaning the irradiance evaluation result.
In yet another embodiment of the present invention, a photovoltaic module cleaning system considering irradiance is provided, which can be used for implementing the above photovoltaic module cleaning considering irradiance, and specifically, the photovoltaic module cleaning system considering irradiance includes a system module, a calculation module, an evaluation module, a scoring module, and a cleaning module.
The system module establishes an irradiance evaluation index system according to the air pollution index, the component surface pollution index, the ground pollution index and other factors;
the calculation module is used for collecting data according to the irradiance evaluation index system established by the system module, determining the membership degree of each index in the irradiance evaluation index system according to the membership degree function, and calculating the weight value of the irradiance evaluation index system according to an entropy weight method;
the evaluation module is used for carrying out fuzzy comprehensive evaluation on the area by combining the weighted value and the membership degree obtained by the calculation module to obtain a fuzzy comprehensive evaluation result of the irradiance of the power station;
the grading module is used for calculating a grade for evaluating the comprehensive irradiance evaluation of the photovoltaic power station irradiance according to the power station irradiance fuzzy comprehensive evaluation result obtained by the evaluation module and the corresponding score vector;
and the cleaning module determines the cleaning priority according to the grading analysis influence factors of the comprehensive evaluation of the irradiance of the photovoltaic power station obtained by the grading module and gives a cleaning strategy.
In yet another embodiment of the present invention, a terminal device is provided that includes a processor and a memory for storing a computer program comprising program instructions, the processor being configured to execute the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable gate array (FPGA) or other Programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc., which is a computing core and a control core of the terminal, and is adapted to implement one or more instructions, and is specifically adapted to load and execute one or more instructions to implement a corresponding method flow or a corresponding function; the processor of the embodiment of the invention can be used for the operation of the photovoltaic module cleaning method considering irradiance, and comprises the following steps:
establishing an irradiance evaluation index system according to the air pollution index, the component surface pollution index, the ground pollution index and other factors; data collection is carried out according to the established irradiance evaluation index system, the membership degree of each index in the irradiance evaluation index system is determined according to a membership degree function, and the weight value of the irradiance evaluation index system is calculated according to an entropy weight method; carrying out fuzzy comprehensive evaluation on the areas by combining the weight values and the membership degrees to obtain a fuzzy comprehensive evaluation result of the irradiance of the power station; calculating to obtain a score of the comprehensive evaluation irradiance of the photovoltaic power station according to the fuzzy comprehensive evaluation result of the irradiance of the power station and the corresponding score vector; and determining the cleaning priority according to the grading analysis influence factors of the comprehensive evaluation of the irradiance of the photovoltaic power station, and giving a cleaning strategy.
In still another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a Memory device in a terminal device and is used for storing programs and data. It is understood that the computer readable storage medium herein may include a built-in storage medium in the terminal device, and may also include an extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also, one or more instructions, which may be one or more computer programs (including program code), are stored in the memory space and are adapted to be loaded and executed by the processor. It should be noted that the computer-readable storage medium may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as at least one disk memory.
One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to perform the corresponding steps of the above embodiments with respect to a method of cleaning a photovoltaic module that takes irradiance into account; one or more instructions in the computer-readable storage medium are loaded by the processor and perform the steps of:
establishing an irradiance evaluation index system according to the air pollution index, the component surface pollution index, the ground pollution index and other factors; data collection is carried out according to the established irradiance evaluation index system, the membership degree of each index in the irradiance evaluation index system is determined according to a membership degree function, and the weight value of the irradiance evaluation index system is calculated according to an entropy weight method; carrying out fuzzy comprehensive evaluation on the areas by combining the weight values and the membership degrees to obtain a fuzzy comprehensive evaluation result of the irradiance of the power station; calculating to obtain a score of the comprehensive irradiance evaluation of the photovoltaic power station irradiance according to the fuzzy comprehensive evaluation result of the power station irradiance and the corresponding score vector; and determining the cleaning priority according to the grading analysis influence factors of the comprehensive evaluation of the irradiance of the photovoltaic power station, and giving a cleaning strategy.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Selecting an irradiance evaluation index system, dividing state grades and specifying a corresponding cleaning strategy according to an evaluation result. The specific implementation process comprises the following steps:
TABLE 1 definition and introduction of the indices
TABLE 2 degree of membership of each index status
TABLE 3 weight of each index and critical value of current membership
Table 4 example verification-certain power station in Qinghai area
The fuzzy comprehensive evaluation result of irradiance of a certain photovoltaic power station in Qinghai:
Vi＝Wi×R′i
irradiance scoring of a certain photovoltaic power station in Qinghai:
Zi＝Vi×GT
wherein, Z ═ (0.582, 0.195, 0.192, 0.000, 0.031) (1, 0.75, 0.50, 0.25, 0)T0.824; the grading vector G according to the index reaches the excellent level {1, 0.75, 0.50, 0.25, 0}, and is consistent with the current situation.
As shown by the above-mentioned evaluation results: irradiance of a certain photovoltaic power station in Qinghai belongs to 'excellent', most indexes have excellent states, the index with the 'excellent' state is the most, and the indexes with the 'excellent' state are the next few in 'good', 'general' and the following index states; the main influencing factors are the total solar radiation, the sunshine hours and the dust particle size. And according to the evaluation result, the irradiance of the power station is 'excellent', and cleaning is not needed for the moment. And timely cleaning is needed when the evaluation result of irradiance reaches the normal value and below.
In conclusion, the photovoltaic module cleaning method and system considering irradiance are suitable for calculating irradiance of photovoltaic power stations in different regions, and the guiding value and the applicability of the method are verified through the empirical calculation result.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (10)
1. A method of irradiance-aware photovoltaic module cleaning, comprising the steps of:
s1, establishing an irradiance evaluation index system according to the air pollution index, the component surface pollution index, the ground pollution index and other factors;
s2, collecting data according to the irradiance evaluation index system established in the step S1, determining the membership degree of each index in the irradiance evaluation index system according to a membership degree function, and calculating the weight value of the irradiance evaluation index system according to an entropy weight method;
s3, carrying out fuzzy comprehensive evaluation on the area by combining the weight value and the membership grade obtained in the step S2 to obtain a fuzzy comprehensive evaluation result of the irradiance of the power station;
s4, calculating to obtain a score of the comprehensive evaluation irradiance of the photovoltaic power station irradiance according to the power station irradiance fuzzy comprehensive evaluation result obtained in the step S3 and the corresponding score vector;
and S5, determining the cleaning priority according to the grading analysis influence factors of the comprehensive evaluation of the irradiance of the photovoltaic power station obtained in the step S4, and giving a cleaning strategy.
2. The method according to claim 1, wherein in step S1, the air pollution index includes PM2.5、PM10、AQI、SO2、NO2CO and O3(ii) a The component surface pollution index comprises dust particle size, dust thickness and shielding area ratio; the ground pollution index comprises the reflectivity of the underlying surface and the soil texture; other factors include geographically and weather-related rainfall, air temperature, wind speed, cloud cover, hours of sunshine, total solar radiation and visibility.
3. The method of claim 1, wherein in step S2, the membership degree R (V, x) represents a membership degree of the index x to a status level V, data of each index in the region is obtained by an expert scoring method, and a status level p to which each index belongs is selected according to a current status to obtain the membership degree R (V, x) of each index to each status level, wherein the status levels V { V ═ x1，v2，v3，v4，v5}，v1The quality is excellent; v. of2Is good; v. of3Is general; v. of4Slight pollution is caused; v. of5Severe contamination; the corresponding score vector is G ═ {1, 0.75, 0.50, 0.25, 0 }.
4. The method according to claim 1, wherein in step S2, the weight value is calculated by constructing a judgment matrix according to an entropy weight method, and specifically is:
s2021, forming m samples, and n evaluation indexes having an evaluation matrix R (R)ij)m×n，rijIs the evaluation value of the ith sample under the jth index;
s2022, carrying out standardization processing on the evaluation matrix R in the step S2021 to obtain a standardization matrix B;
s2023, calculating entropy values H of evaluation indexesij；
S2024, calculating entropy weight W of each evaluation index;
s2025, determining the weight a of each index as follows:
wherein, wiObtained by expert scoring for subjective weighting, wiThe weights obtained by the entropy weight method.
5. The method according to claim 4, wherein in step S2023, the entropy value H of each evaluation indexijComprises the following steps:
wherein, BijFor normalizing the calculation result, n is the index number.
6. The method according to claim 4, wherein in step S2024, the entropy weight W of each evaluation index is:
wherein m is the number of samples, HjIs the entropy value and n is the index number.
7. The method as claimed in claim 1, characterized in that in step S3, the fuzzy comprehensive evaluation result V of the station irradiance is obtainediThe following were used:
Vi＝Wi×R′i
wherein Wi is a weight vector of each index; r' i is a membership matrix of all indexes under the evaluation layer i, and the membership matrix is obtained by calculating a membership function, wherein the smaller the better the type index is:
Xij＝1-Xj(i-1)
for larger better type indicators:
Xij＝1-Xj(i-1)
wherein v isijThe j index belongs to the boundary value of the ith grade; v. ofj(i-1)The j index is subordinate to the boundary value of the (i-1) th grade; x is the number ofjIs the detection result of j index, XijAnd calculating the result of the index membership.
8. The method according to claim 1, wherein in step S4, the comprehensive evaluation value score of each evaluation index is calculated based on each comprehensive evaluation matrix to obtain a score Zi for evaluating the comprehensive power generation performance of the photovoltaic power station as follows:
Zi＝Vi×GT
wherein Vi is a fuzzy comprehensive evaluation result of the irradiance evaluation index i; g is the index rank vector and T is the transposed symbol.
9. The method according to claim 1, wherein step S5 is specifically:
s501, judging the irradiance level according to the grade obtained in the step S4 for evaluating the comprehensive evaluation of the irradiance of the photovoltaic power station;
s502, obtaining the influence degree of a certain index in an irradiance evaluation index system on irradiance according to an entropy weight method, and comparing to obtain an index with the maximum influence degree on the irradiance;
s503, judging the current situation of a certain index in the irradiance evaluation index system according to the comprehensive evaluation value in the step S4;
and S504, analyzing the cleaning priority by combining the comprehensive evaluation value, wherein the result of the preferential cleaning irradiance evaluation is the photovoltaic module with light pollution and severe pollution.
10. A photovoltaic module cleaning method system considering irradiance, comprising:
the system module is used for establishing an irradiance evaluation index system according to the air pollution index, the component surface pollution index, the ground pollution index and other factors;
the calculation module is used for collecting data according to the irradiance evaluation index system established by the system module, determining the membership degree of each index in the irradiance evaluation index system according to the membership degree function, and calculating the weight value of the irradiance evaluation index system according to an entropy weight method;
the evaluation module is used for carrying out fuzzy comprehensive evaluation on the area by combining the weighted value and the membership degree obtained by the calculation module to obtain a fuzzy comprehensive evaluation result of the irradiance of the power station;
the grading module is used for calculating a grade for evaluating the comprehensive irradiance evaluation of the photovoltaic power station irradiance according to the power station irradiance fuzzy comprehensive evaluation result obtained by the evaluation module and the corresponding score vector;
and the cleaning module determines the cleaning priority according to the grading analysis influence factors of the comprehensive evaluation of the irradiance of the photovoltaic power station obtained by the grading module and gives a cleaning strategy.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111389795.6A CN114091905A (en) | 2021-11-22 | 2021-11-22 | Photovoltaic module cleaning method and system considering irradiance |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111389795.6A CN114091905A (en) | 2021-11-22 | 2021-11-22 | Photovoltaic module cleaning method and system considering irradiance |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114091905A true CN114091905A (en) | 2022-02-25 |
Family
ID=80302943
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111389795.6A Pending CN114091905A (en) | 2021-11-22 | 2021-11-22 | Photovoltaic module cleaning method and system considering irradiance |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114091905A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115446841A (en) * | 2022-10-26 | 2022-12-09 | 西安万飞控制科技有限公司 | Robot control method, system, terminal and medium for cleaning photovoltaic panel |
-
2021
- 2021-11-22 CN CN202111389795.6A patent/CN114091905A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115446841A (en) * | 2022-10-26 | 2022-12-09 | 西安万飞控制科技有限公司 | Robot control method, system, terminal and medium for cleaning photovoltaic panel |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Adedeji et al. | Wind turbine power output very short-term forecast: A comparative study of data clustering techniques in a PSO-ANFIS model | |
| Sun et al. | Urbanization, economic growth, and environmental pollution: Partial differential analysis based on the spatial Durbin model | |
| Ramsami et al. | A hybrid method for forecasting the energy output of photovoltaic systems | |
| CN105046374B (en) | A kind of power interval prediction technique based on core extreme learning machine model | |
| CN102184337B (en) | Dynamic combination analysis method of new energy generating capacity influenced by meteorological information | |
| CN109146161A (en) | Merge PM2.5 concentration prediction method of the stack from coding and support vector regression | |
| Dhiman et al. | Supervised machine learning in wind forecasting and ramp event prediction | |
| CN106845080B (en) | Based on the modified Scene Tourist meteorological disaster intelligent Forecasting of difference | |
| Yang et al. | Multi-dimensional scenario forecast for generation of multiple wind farms | |
| Chiteka et al. | A method to predict solar photovoltaic soiling using artificial neural networks and multiple linear regression models | |
| CN104408562A (en) | Photovoltaic system generating efficiency comprehensive evaluation method based on BP (back propagation) neural network | |
| CN109659972B (en) | Multi-point photovoltaic output probability prediction method and system based on Pair-copula theory | |
| CN114792156A (en) | Photovoltaic output power prediction method and system based on curve characteristic index clustering | |
| CN106526710A (en) | Haze prediction method and device | |
| Lee et al. | An efficient prediction for heavy rain from big weather data using genetic algorithm | |
| Wang et al. | Predicting ozone formation in petrochemical industrialized Lanzhou city by interpretable ensemble machine learning | |
| Obeidat et al. | Systematic Approach for Selecting a Cleaning Method to Solar Panels Based on the Preference Selection Index Approach. | |
| Khilar et al. | Improving the efficiency of photovoltaic panels using machine learning approach | |
| CN114611842A (en) | Whole county roof distributed photovoltaic power prediction method | |
| Akkoyunlu et al. | A neural network-based approach for the prediction of urban SO2 concentrations in the Istanbul metropolitan area | |
| Livingston et al. | An ensembled method for air quality monitoring and control using machine learning | |
| Chen et al. | A novel prediction model of PM2. 5 mass concentration based on back propagation neural network algorithm | |
| Choudhary et al. | Evaluating air quality and criteria pollutants prediction disparities by data mining along a stretch of urban-rural agglomeration includes coal-mine belts and thermal power plants | |
| CN114091905A (en) | Photovoltaic module cleaning method and system considering irradiance | |
| Klepac et al. | A case study and parametric analysis of predicting hurricane-induced building damage using data-driven machine learning approach |
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 |