CN115879817A - Regional carbon reduction amount evaluation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention relates to the technical field of artificial intelligence algorithm models, in particular to a regional carbon reduction amount evaluation method, a device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring satellite map data of a region to be detected and establishing a database; inputting satellite map data in a database into a trained network model, and identifying a photovoltaic installation area through the network model; calculating a photovoltaic development area according to the identified photovoltaic installation area; and calculating the photovoltaic development potential and the annual carbon reduction amount of photovoltaic power generation according to the photovoltaic development area. According to the method, the photovoltaic installation areas are identified and calculated by combining remote sensing satellite map data with an artificial intelligence algorithm, the photovoltaic development potential and the photovoltaic carbon reduction amount are calculated according to different photovoltaic installation areas, and compared with the related technology, the method is higher in calculation efficiency and more accurate in area calculation.
Description
Technical Field
The invention relates to the technical field of artificial intelligence algorithm models, in particular to a regional carbon reduction amount evaluation method and device, electronic equipment and a storage medium.
Background
As a necessary way for promoting green transformation of an energy structure, how to calculate photovoltaic potential and regional carbon reduction becomes a problem to be solved urgently at present;
in the related technology known by the inventor, the regional photovoltaic potential and carbon reduction evaluation methods mostly adopt evaluation modes based on subjective experiences, such as average human photovoltaic density, regional photovoltaic power generation potential analogy of the same type and the like, however, on one hand, the modes need a large number of statistical analysis methods, the experience proportion difference is large, and more accurate data are difficult to obtain;
the information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art that is already known to a person skilled in the art.
Disclosure of Invention
In view of at least one of the above technical problems, the present invention provides a method, an apparatus, an electronic device and a storage medium for evaluating regional carbon reduction, which are used for efficiently and accurately evaluating the photovoltaic carbon reduction of a region to be measured by combining an artificial intelligence algorithm and satellite remote sensing map data.
According to an aspect of the present invention, there is provided a regional carbon reduction amount evaluation method including the steps of:
acquiring satellite map data of a region to be detected and establishing a database;
inputting satellite map data in a database into a trained network model, and identifying a photovoltaic installation area through the network model;
calculating a photovoltaic development area according to the identified photovoltaic installation area;
and calculating the photovoltaic development potential and the annual carbon reduction amount of photovoltaic power generation according to the photovoltaic development area.
In some embodiments, the training method of the network model comprises the following steps:
assigning class labels to photovoltaic installation areas with semantic information in satellite map data, wherein the photovoltaic installation areas comprise farmland plots, agricultural greenhouses, ponds, lakes, industrial plants, residential houses and the like;
performing data enhancement and pretreatment on the satellite map data endowed with the category labels to obtain a data set;
and building a model, and training and testing a part of the data set as a training set and the other part of the data set as a test set to obtain an optimal model.
The invention has the beneficial effects that: according to the method, the photovoltaic installation areas are identified and calculated by combining remote sensing satellite map data with an artificial intelligence algorithm, the photovoltaic development potential and the photovoltaic carbon reduction amount are calculated according to different photovoltaic installation areas, and compared with the related technology, the method is higher in calculation efficiency and more accurate in area calculation.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flowchart illustrating steps of a method for evaluating regional carbon reduction according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating steps of a method for training a network model according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a regional carbon reduction amount evaluation apparatus in an embodiment of the present invention.
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 only a part of the embodiments of the present invention, and not all of the embodiments.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only and do not represent the only embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. 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 herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The regional carbon reduction amount evaluation method shown in FIG. 1 comprises the following steps:
s10: acquiring satellite map data of a region to be detected and establishing a database, wherein in some embodiments of the invention, the satellite map is high-definition remote sensing map data, the spatial resolution is 0.1-2 m, and the original size is 10000 × 10000ppi;
s20: inputting satellite map data in a database into a trained network model, and identifying a photovoltaic installation area through the network model; it will be appreciated that in some embodiments of the invention, the network model may take many forms, and those skilled in the art may choose it according to the actual required accuracy and speed; in addition, in the embodiment of the invention, the photovoltaic installation area is selected not by a single mode of a conventional residential roof, but by a mode of identifying multiple photovoltaic areas, the calculation of the photovoltaic potential is enhanced by the mode, and the photovoltaic installation area is not limited to the single area of the residential roof;
s30: calculating a photovoltaic development area according to the identified photovoltaic installation area; when the photovoltaic development area is calculated, the various types of target areas are calculated respectively, and a data base is further made for the subsequent calculation of the photovoltaic development potential and the annual carbon reduction amount of photovoltaic power generation.
S40: and calculating the photovoltaic development potential and the annual carbon reduction amount of photovoltaic power generation according to the photovoltaic development area.
In the embodiment, the photovoltaic installation areas are identified and calculated by combining remote sensing satellite map data with an artificial intelligence algorithm, and the photovoltaic development potential and the photovoltaic carbon reduction amount are calculated according to different photovoltaic installation areas.
On the basis of the above embodiments, in the embodiment of the present invention, as shown in fig. 2, the training method of the network model includes the following steps:
s21: assigning class labels to photovoltaic installation areas with semantic information in satellite map data, wherein the photovoltaic installation areas comprise farmland plots, agricultural greenhouses, ponds, lakes, industrial plants, residential houses and the like; in the embodiment of the invention, the areas which are possibly used as photovoltaic installation in the future are labeled in a classified mode, and other labels refer to other areas except the six typical areas;
s22: performing data enhancement and pretreatment on the satellite map data endowed with the category labels to obtain a data set; when the specific processing is carried out, the satellite map data and the label map are respectively cut into images with 512 x 512 pixels by using a sliding window; then, each cut picture is rotated, turned over, subjected to Gaussian filtering, added with white noise and the like to obtain an enhanced data set;
s23: and building a model, and training and testing a part of the data set as a training set and another part of the data set as a test set to obtain an optimal model. In some embodiments of the invention, a Mask RCNN network is established to extract a region to be detected, resNet-50 is adopted to extract basic characteristics of the region to be detected, FPN (characteristic pyramid network) is further used to enrich multi-scale information, and then RPN (region candidate network) is adopted to extract a candidate region; and finally, optimizing a candidate region through ROIAlign, and executing candidate box classification, bounding box regression and Mask generation. And then carrying out classified collection statistics, and carrying out batch prediction on the images of the test set by using the trained Mask RCNN example segmentation model to obtain segmented and classified images.
S24: and restoring and splicing the predicted pictures according to a cutting mode, then combining an OpenCV module to classify and gather the pictures, calibrating the categories and the sequence numbers of the pictures, and counting the areas of 6 categories of farmland plots, agricultural greenhouses, ponds, lakes, industrial plants and residential houses.
In the embodiment of the present invention, when calculating the photovoltaic development area, the calculation method adopted for calculating the areas of the photovoltaic regions of the 6 categories is as follows:
S area1 ＝S FP *r 1 *r 2 *t 1 equation 1
In the formula, S area1 The exploitable area of the farmland plots of the areas to be detected; s FP The area of the farmland plot extracted in the region; r is a radical of hydrogen 1 The illumination demand coefficient of crops in the area; r is 2 The demand coefficient of the growth interval of crops in the area is set; t is t 1 Building and developing coefficients for the photovoltaic of farmland plots in the region;
S area2 ＝S FG *r 3 *r 4 *t 2 *q 1 equation 2
Equation 2
In the formula, S area2 The area of the agricultural greenhouse in the area to be detected can be developed; s. the FG The area of the agricultural greenhouse extracted in the region; r is 3 The illumination demand coefficient of greenhouse crops in the area; r is a radical of hydrogen 4 The demand coefficient of the growth interval of greenhouse crops in the area is set; t is t 2 Developing coefficients for photovoltaic construction of the agricultural greenhouse; q. q.s 1 The conversion coefficient of the area of the greenhouse roof in the area is obtained;
S area3 ＝S Po *d 1 *d 2 *t 3 equation 3
Equation 3
In the formula, S area3 The area of the pond to be tested can be developed; s PO The area of the pond extracted in the region; d1 is the illumination demand coefficient of the animals and plants in the pond in the region; d 2 The demand coefficient of the growth interval of the animals and plants in the pond in the area is set; t is t 3 Photovoltaic construction and development coefficients of the animals and plants in the pond are developed in the area;
S ar.ea4 ＝S LA *d 3 *d 4 *t 4 *q 2 equation 4
Equation 4
In the formula, S area4 The area of the pond to be tested can be developed; s LA The lake area extracted in the region; d 3 The illumination demand coefficient of the lake plants in the area is obtained; d is a radical of 4 The growth interval demand coefficient of the animals and plants in the pond in the area is set; t is t 4 Developing coefficients for photovoltaic construction of farmland plots; q. q.s 2 Correcting coefficients for irregular edges of lake ponds in the area;
S area5 ＝S IP *f 0 *f 1 *f 2 equation 5
Equation 5
In the formula, S area5 The area of the roof of the industrial factory building in the area to be detected can be developed; s IP The area of the industrial factory building roof extracted in the area is the area; f. of 0 The orientation coefficient of the industrial factory building roof is shown; f. of 1 Shading coefficient for industrial factory building roof; f. of 2 The occupancy coefficient of the roof equipment of the industrial factory building;
S area6 ＝S RB *f 3 *f 4 *f 5 *q 3 equation 6
Equation 6
In the formula, S area6 The area can be developed for the residential house roof of the area to be detected; s RB The residential house roof area extracted from the region; f. of 3 The orientation coefficient of the roof of the residential building; f. of 4 Shading coefficient for the residential house roof; f. of 5 The occupancy coefficient of the roof equipment of the residential building is increased. q. q.s 3 And the correction coefficient is the inclination angle of the residential house roof. Calculating the photovoltaic development potential according to the calculated areas of the six regions;
specifically, when the annual carbon reduction amount of photovoltaic power generation is calculated, the adopted calculation method is as follows:
calculating the photovoltaic development potential according to the photovoltaic development area, wherein the calculation formula is as follows:
in the formula, E j For photovoltaic power generation systems in photovoltaic development areas at jAnnual power production; a is the area of a single photovoltaic module; e f Receiving the solar radiation for the single photovoltaic module; eta f The photoelectric conversion efficiency of the photovoltaic module; eta p System efficiency of the photovoltaic power generation system; mu is the annual attenuation coefficient of the photovoltaic power generation system;
calculating annual carbon reduction amount of photovoltaic power generation according to photovoltaic development potential, wherein the calculation formula is as follows:
E c ＝f i，i＝1，2，3 *E j *(1-μ) j-1 equation 8
In the formula, E c The photovoltaic carbon reduction amount in the jth year area; f. of 1 The standard coal consumption coefficient is obtained; f. of 2 Is a standard coal consumption carbon emission coefficient; f. of 3 Is the standard coal consumption carbon dioxide emission coefficient. By the method, the identification of the photovoltaic installation area and the area calculation on the map are realized by combining the satellite remote sensing high-definition map data with the training of an intelligent network model, the photovoltaic potential is obtained through the area calculation, and the evaluation calculation method of the annual carbon reduction amount of photovoltaic power generation is obtained according to the photovoltaic potential; compared with the traditional statistical analysis, the evaluation method consumes more time, and the obtained areas are based on the real map data, so that the evaluation efficiency is higher, and the calculation precision is more accurate.
It should be understood by those skilled in the art that the embodiments of the present application may be provided as a method, an apparatus, an electronic device, a storage medium, or a computer program product, so that the embodiments of the present application may fully adopt a hardware embodiment, a combined hardware and software embodiment, or a pure software embodiment, and the regional carbon reduction amount evaluation apparatus in the embodiments of the present application is described below, the following embodiments of the apparatus correspond to the above embodiments of the method, and the following implementation processes may be understood by those skilled in the art based on the above description, and will not be described in detail herein;
according to another aspect of the embodiments of the present invention, there is also provided an area carbon reduction amount evaluation apparatus, as shown in fig. 3, which is a schematic diagram of the area carbon reduction amount evaluation apparatus in the embodiments of the present invention, and includes:
an obtaining unit 100, configured to obtain satellite map data of an area to be measured and establish a database;
the identification unit 200 is used for inputting satellite map data in a database into a trained network model and identifying a photovoltaic installation area through the network model;
a first calculation unit 300 for calculating a photovoltaic development area based on the identified photovoltaic installation area
And a second calculation unit 400 for calculating the photovoltaic development potential and the annual carbon reduction amount of photovoltaic power generation according to the photovoltaic development area.
In the embodiment of the present invention, in the identification unit 200, the training method of the network model includes the following steps:
assigning class labels to photovoltaic installation areas with semantic information in satellite map data, wherein the photovoltaic installation areas comprise farmland plots, agricultural greenhouses, ponds, lakes, industrial plants, residential houses and the like;
performing data enhancement and pretreatment on the satellite map data endowed with the category labels to obtain a data set;
and building a model, and training and testing a part of the data set as a training set and another part of the data set as a test set to obtain an optimal model.
In the embodiment of the present invention, in the first calculating unit 300, when calculating the photovoltaic development area, the adopted calculating method is:
S area1 ＝S FP *r 1 *r 2 *t 1 equation 1
In the formula, S area1 Developing the area of the farmland plot of the region to be detected; s. the FP The area of the farmland plot extracted in the region; r is a radical of hydrogen 1 The illumination demand coefficient of crops in the area; r is 2 The demand coefficient of the growth interval of crops in the area is set; t is t 1 Building and developing coefficients for the photovoltaic of farmland plots in the region;
S area2 ＝S FG *r 3 *r 4 *t 2 *q 1 equation 2
Equation 2
In the formula, S area2 To be testedThe exploitable area of the agricultural greenhouse in the region; s FG The area of the agricultural greenhouse extracted in the region; r is a radical of hydrogen 3 The illumination demand coefficient of greenhouse crops in the area; r is 4 The demand coefficient of the growth interval of greenhouse crops in the area is set; t2 is a photovoltaic construction development coefficient of the agricultural greenhouse; q. q.s 1 The conversion coefficient of the area of the greenhouse roof in the area is obtained;
S area3 ＝S PO *d 1 *d 2 *t 3 equation 3
Equation 3
In the formula, S are The exploitable area of the pond of the area to be detected; s Po The area of the pond extracted in the region; d 1 The illumination demand coefficient of animals and plants in the pond in the region is obtained; d 2 The demand coefficient of the growth interval of the animals and plants in the pond in the area is set; t is t 3 Photovoltaic construction and development coefficients of the animals and plants in the pond are developed in the area;
S ar . ea4 ＝S LA *d 3 *d 4 *t 4 *q 2 equation 4
Equation 4
In the formula, S area4 The area of the pond to be tested can be developed; s LA The lake area extracted in the region; d 3 The illumination demand coefficient of the lake plants in the area is obtained; d 4 The growth interval demand coefficient of the animals and plants in the pond in the area is set; t is t 4 Developing coefficients for farmland plot photovoltaic construction; q. q.s 2 Correcting coefficients for irregular edges of lake in the area;
S area5 ＝S IP *f 0 *f 1 *f 2 equation 5
Equation 5
In the formula, S area5 The area of the roof of the industrial factory building in the area to be detected can be developed; s. the IP The area of the industrial factory building roof extracted in the area is the area; f. of 0 The orientation coefficient of the industrial factory building roof is shown; f. of 1 Shading coefficient for industrial factory building roof; f. of 2 The occupancy factor of the roof equipment of the industrial factory building is increased;
S area6 ＝S RB *f 3 *f 4 *f 5 *q 3 equation 6
Equation 6
In the formula, S area6 The area of the developed roof of the residential building of the area to be tested is; s RB The area of the residential house roof extracted from the area is determined; f. of 3 The orientation coefficient of the residential house roof; f. of 4 Shading coefficient for the residential house roof; f. of 5 The occupancy coefficient of the equipment on the roof of the residential building is increased. q. q of 3 And the correction coefficient is the inclination angle of the residential house roof.
In the embodiment of the present invention, in the second calculation unit 400, when the annual carbon reduction amount of photovoltaic power generation is calculated, the calculation method adopted is:
calculating the photovoltaic development potential according to the photovoltaic development area, wherein the calculation formula is as follows:
in the formula, E j The method comprises the following steps of generating power for a photovoltaic power generation system in a photovoltaic development area in j years; a is the area of a single photovoltaic module; e f Receiving the solar radiation for the single photovoltaic module; eta f The photoelectric conversion efficiency of the photovoltaic module; eta p System efficiency of the photovoltaic power generation system; mu is the annual attenuation coefficient of the photovoltaic power generation system;
calculating annual carbon reduction amount of photovoltaic power generation according to photovoltaic development potential, wherein the calculation formula is as follows:
E c ＝f i，i＝1，2，3 *E j *(1-μ) j-1 equation 8
In the formula, E c The photovoltaic carbon reduction amount in the jth year area; f. of 1 The standard coal consumption coefficient is obtained; f. of 2 Is a standard coal consumption carbon emission coefficient; f. of 3 Is the standard coal consumption carbon dioxide emission coefficient.
In another aspect of the embodiments of the present invention, there is also provided a computer storage medium, where the storage medium includes a stored program, and where the program is executed to perform any one of the above methods for estimating regional carbon reduction amount.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, where the electronic device has a processor, and the processor is configured to execute a program, where the program executes any one of the above methods for estimating regional carbon reduction amount.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. A regional carbon reduction amount evaluation method is characterized by comprising the following steps:
acquiring satellite map data of a region to be detected and establishing a database;
inputting satellite map data in a database into a trained network model, and identifying a photovoltaic installation area through the network model;
calculating a photovoltaic development area according to the identified photovoltaic installation area;
and calculating the photovoltaic development potential and the annual carbon reduction amount of photovoltaic power generation according to the photovoltaic development area.
2. The regional carbon reduction amount evaluation method according to claim 1, wherein the training method of the network model comprises the following steps:
assigning class labels to photovoltaic installation areas with semantic information in satellite map data, wherein the photovoltaic installation areas comprise farmland plots, agricultural greenhouses, ponds, lakes, industrial plants, residential houses and the like;
performing data enhancement and pretreatment on the satellite map data endowed with the category labels to obtain a data set;
and building a model, and training and testing a part of the data set as a training set and the other part of the data set as a test set to obtain an optimal model.
3. The regional carbon reduction amount evaluation method according to claim 2, wherein in calculating the photovoltaic development area, a calculation method is adopted in which:
S area1 ＝S FP *r 1 *r 2 *t 1 equation 1
In the formula, S area Developing the area of the farmland plot of the region to be detected; s. the FP The area of the farmland plot extracted in the region; r is 1 The illumination demand coefficient of crops in the area; r is 2 The demand coefficient of the growth interval of crops in the area is set; t is t 1 Building and developing coefficients for the photovoltaic of farmland plots in the region;
S area2 ＝S FG *r 3 *r 4 *t 2 *q 1 equation 2
In the formula, S area2 The area of the agricultural greenhouse in the area to be detected can be developed; s. the FG The area of the agricultural greenhouse extracted in the region; r is 3 The illumination demand coefficient of greenhouse crops in the area; r is 4 The demand coefficient of the growth interval of greenhouse crops in the area is set; t is t 2 Developing coefficients for photovoltaic construction of the agricultural greenhouse; q. q of 1 The conversion coefficient of the area of the greenhouse roof in the area is obtained;
S area3 ＝S PO *d 1 *d 2 *d 3 equation 3
In the formula, S area The exploitable area of the pond of the area to be detected; s PO The area of the pond extracted in the region; d 1 The illumination demand coefficient of animals and plants in the pond in the region is obtained; d 2 The growth interval demand coefficient of the animals and plants in the pond in the area is set; t is t 3 Photovoltaic construction and development coefficients of the animals and plants in the pond are developed in the area;
S area4 ＝S LA *d 3 *d 4 *t 4 *q 2 equation 4
In the formula, S area4 The area of the pond to be tested can be developed; s LA The lake area extracted in the region; d 3 The illumination demand coefficient of the lake plants in the area is obtained; d 4 The demand coefficient of the growth interval of the animals and plants in the pond in the area is set; t is t 4 Developing coefficients for photovoltaic construction of farmland plots; q. q.s 2 Correcting coefficients for irregular edges of lake in the area;
S area5 ＝S IP *f 0 *f 1 *f 2 equation 5
In the formula, S area The area of the roof of the industrial factory building in the area to be detected can be developed; s IP The area of the industrial factory building roof extracted in the area is the area; f. of 0 The orientation coefficient of the industrial factory building roof is shown; f. of 1 Shading coefficient for industrial factory building roof; f. of 2 The occupancy factor of the roof equipment of the industrial factory building is increased;
S area6 ＝S RB *f 3 *f 4 *f 5 *q 3 equation 6
In the formula, S area6 The area can be developed for the residential house roof of the area to be detected; s RB The area of the residential house roof extracted from the area is determined; f. of 3 Is a living roomA residential roof orientation factor; f. of 4 Shading coefficient for the residential house roof; f. of 5 The occupancy coefficient of the roof equipment of the residential building is increased. q. q.s 3 And the correction coefficient is the inclination angle of the residential house roof.
4. The regional carbon reduction amount evaluation method according to claim 3, wherein in calculating the annual carbon reduction amount of photovoltaic power generation, the calculation method adopted is:
calculating the photovoltaic development potential according to the photovoltaic development area, wherein the calculation formula is as follows:
in the formula, E j The method comprises the steps of generating power for a photovoltaic power generation system in a photovoltaic development area in j years; a is the area of a single photovoltaic module; e f Receiving the solar radiation for the single photovoltaic module; eta f The photoelectric conversion efficiency of the photovoltaic module; eta p System efficiency of the photovoltaic power generation system; mu is the annual attenuation coefficient of the photovoltaic power generation system;
calculating annual carbon reduction amount of photovoltaic power generation according to photovoltaic development potential, wherein the calculation formula is as follows:
E c ＝f i，i＝1，2，3 *E j *(1-μ) j-1 equation 8
In the formula, E c The photovoltaic carbon reduction amount in the jth year area; f. of 1 The standard coal consumption coefficient is obtained; f. of 2 Is a standard coal consumption carbon emission coefficient; f. of 3 Is the standard coal consumption carbon dioxide emission coefficient.
5. An area carbon reduction amount evaluation apparatus, characterized by comprising:
the acquisition unit is used for acquiring satellite map data of an area to be detected and establishing a database;
the identification unit is used for inputting satellite map data in the database into a trained network model and identifying a photovoltaic installation area through the network model;
a first calculation unit for calculating a photovoltaic development area based on the identified photovoltaic installation area
And the second calculation unit is used for calculating the photovoltaic development potential and the annual carbon reduction amount of photovoltaic power generation according to the photovoltaic development area.
6. The regional carbon reduction amount evaluation device according to claim 5, wherein in the recognition unit, the training method of the network model comprises the steps of:
assigning class labels to photovoltaic installation areas with semantic information in satellite map data, wherein the photovoltaic installation areas comprise farmland plots, agricultural greenhouses, ponds, lakes, industrial plants, residential houses and the like;
performing data enhancement and pretreatment on the satellite map data endowed with the category labels to obtain a data set;
and building a model, and training and testing a part of the data set as a training set and another part of the data set as a test set to obtain an optimal model.
7. The regional carbon reduction amount evaluation device according to claim 6, wherein in the first calculation unit, when calculating the photovoltaic development area, a calculation method is employed that:
S area1 ＝S FP *r 1 *r 2 *t 1 equation 1
In the formula, S area The exploitable area of the farmland plots of the areas to be detected; s FP The area of the farmland plot extracted in the region; r is 1 The illumination demand coefficient of crops in the area; r is 2 The demand coefficient of the growth interval of crops in the area is set; t is t 1 Building and developing coefficients for the photovoltaic of farmland plots in the region;
S area2 ＝S FG *r 3 *r 4 *t 2 *q 1 equation 2
In the formula, S area2 The area of the agricultural greenhouse in the area to be detected can be developed; s FG The area of the agricultural greenhouse extracted in the region; r is 3 The illumination demand coefficient of greenhouse crops in the area; r is 4 The demand coefficient of the growth interval of greenhouse crops in the area is set; t is t 2 Developing coefficients for photovoltaic construction of the agricultural greenhouse; q. q of 1 The conversion coefficient is the area of the greenhouse roof in the area;
S area3 ＝S PO *d 1 *d 2 *t 3 equation 3
In the formula, S area3 The area of the pond to be tested can be developed; s PO The area of the pond extracted in the region; d 1 The illumination demand coefficient of animals and plants in the pond in the region is obtained; d is a radical of 2 The demand coefficient of the growth interval of the animals and plants in the pond in the area is set; t is t 3 Photovoltaic construction and development coefficients of the animals and plants in the pond are developed in the area;
S area4 ＝S LA *d 3 *d 4 *t 4 *q 2 equation 4
In the formula, S area4 The exploitable area of the pond of the area to be detected; s LA The lake area extracted in the region; d 3 The illumination demand coefficient of the lake plants in the area is obtained; d 4 The demand coefficient of the growth interval of the animals and plants in the pond in the area is set; t is t 4 Developing coefficients for farmland plot photovoltaic construction; q. q.s 2 Correcting coefficients for irregular edges of lake in the area;
S area5 ＝S IP *f 0 *f 1 *f 2 equation 5
In the formula, S area5 The area of the roof of the industrial factory building in the area to be detected can be developed; s IP The area of the roof of the industrial factory building extracted in the region is used as the area of the roof of the industrial factory building; f. of 0 The orientation factor of the industrial factory building roof is obtained; f. of 1 Shading coefficient for industrial factory building roof; f. of 2 The occupancy coefficient of the roof equipment of the industrial factory building;
S area6 ＝S RB *f 3 *f 4 *f 5 *q 3 equation 6
In the formula, S area6 The area can be developed for the residential house roof of the area to be detected; s RB For extraction within a regionResidential house roof area; f. of 3 The orientation coefficient of the residential house roof; f. of 4 Shading coefficient for the residential house roof; f. of 5 The occupancy coefficient of the equipment on the roof of the residential building; q. q.s 3 And the correction coefficient is the inclination angle of the residential house roof.
8. The regional carbon reduction amount evaluation device according to claim 7, wherein in the second calculation unit, in calculating the annual carbon reduction amount of photovoltaic power generation, a calculation method is employed that:
calculating the photovoltaic development potential according to the photovoltaic development area, wherein the calculation formula is as follows:
in the formula, E j The method comprises the following steps of generating power for a photovoltaic power generation system in a photovoltaic development area in j years; a is the area of a single photovoltaic module; e f Receiving the solar radiation for the single photovoltaic module; eta f The photoelectric conversion efficiency of the photovoltaic module; eta p System efficiency of the photovoltaic power generation system; mu is the annual attenuation coefficient of the photovoltaic power generation system;
calculating annual carbon reduction amount of photovoltaic power generation according to photovoltaic development potential, wherein the calculation formula is as follows:
E c ＝f i，i＝1，2，3 *E j *(1-μ) j-1 equation 8
In the formula, E c The photovoltaic carbon reduction amount in the jth year area; f. of 1 The standard coal consumption coefficient is obtained; f. of 2 Is a standard coal consumption carbon emission coefficient; f. of 3 Is the standard coal consumption carbon dioxide emission coefficient.
9. An electronic device, comprising:
a memory for storing executable instructions;
a processor for implementing the regional carbon reduction assessment method of any one of claims 1 to 4 when executing the executable instructions stored in the memory.
10. A computer storage medium having computer program instructions stored therein for execution by a processor to perform the regional carbon reduction assessment method of any of claims 1 to 4.
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| CN118053087A (en) * | 2024-04-15 | 2024-05-17 | 国家林业和草原局西北调查规划院 | Lin Caoguang V complementary evaluation and monitoring method based on unmanned aerial vehicle and model analysis |
| CN118246763A (en) * | 2024-04-07 | 2024-06-25 | 江苏省电力试验研究院有限公司 | Photovoltaic developable roof resource evaluation and carbon reduction potential evaluation method based on satellite image recognition |
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| CN118246763A (en) * | 2024-04-07 | 2024-06-25 | 江苏省电力试验研究院有限公司 | Photovoltaic developable roof resource evaluation and carbon reduction potential evaluation method based on satellite image recognition |
| CN118053087A (en) * | 2024-04-15 | 2024-05-17 | 国家林业和草原局西北调查规划院 | Lin Caoguang V complementary evaluation and monitoring method based on unmanned aerial vehicle and model analysis |
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