Space-time dynamic photovoltaic power generation emission reduction potential evaluation method under multiple development paths

Abstract

The invention provides a spatio-temporal dynamic photovoltaic power generation emission reduction potential evaluation method under multiple development paths, and belongs to the technical field of photovoltaic power generation, and the method comprises the steps: constructing a historical dynamic function # imgabs0 # of a target region in different years; based on a global change evaluation model and in combination with a linear interpolation mode, obtaining photovoltaic power generation installed capacity increments of all regions in each year in the future, and in combination with region attributes of each target region, constructing a future photovoltaic power generation development path matrix; and based on the historical dynamic function # imgabs1 #, a future photovoltaic power generation development path matrix and a carbon pollution emission reduction calculation mode, determining photovoltaic power generation emission and emission reduction potential under a development path scheme. The problems that in an existing evaluation method, the evaluation range is small, the evaluation technology is single, and dynamic characterization of differences of different years and regions is lacked are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation, and in particular to a method for evaluating the emission reduction potential of photovoltaic power generation in a spatiotemporal dynamic manner under multiple development paths. Background Art

[0002] Although renewable energy sources such as photovoltaic power generation can be regarded as zero-emission during the operation stage, the manufacturing process requires a large amount of fossil energy, non-renewable electricity and industrial product raw materials. The large-scale manufacturing and deployment of photovoltaic power generation under the background of photovoltaic "doubling" development will cause certain uncertainties in its emission reduction potential due to the carbon emissions in the industrial chain. Secondly, China has a vast territory and the cleanliness of electricity varies from province to province, which leads to differences in emissions during the manufacturing process of photovoltaic modules. Under different photovoltaic development paths, the penetration of photovoltaic power generation in the power grid will in turn affect the emission factors of the power grids in each province, thereby affecting the emissions of its production process. Thirdly, China's photovoltaic power generation potential resources are unevenly distributed. Deploying photovoltaic modules in different photovoltaic resource areas will cause significant differences in their power generation during operation, which will affect their unit power generation emissions and corresponding emission reduction potential throughout their life cycle.

[0003] Existing technologies have built a full life cycle assessment framework for the current emerging photovoltaic power generation technology - perovskite photovoltaic cells, but the assessment technology is still single and does not include multiple mainstream photovoltaic power generation technologies, and cannot reflect the differences between technologies.

[0004] Existing technology has also constructed a full life cycle assessment framework for three different solar energy utilization technologies (one of which is photovoltaic power generation), but it does not incorporate future development into the assessment framework, making it impossible to further explore the differences in technology combinations under different development scenarios.

[0005] Existing technologies have also constructed a full life cycle assessment scheme for renewable energy (including photovoltaic power generation) based on input and output, and included development scenarios. However, the temporal and spatial granularity of its assessment is relatively coarse, and it is unable to achieve the requirements for a detailed assessment of carbon emissions from photovoltaic power generation throughout its life cycle at high temporal and spatial resolution.

[0006] Therefore, it is necessary to develop a spatiotemporal dynamic assessment method that can effectively quantify the carbon footprint of the entire photovoltaic power generation industry chain, analyze the spatiotemporal characteristics of greenhouse gas and air pollutant emissions during the entire life cycle of photovoltaic power generation under different future production and deployment schemes, identify key emission links, and clarify their effective emission reduction potential, so as to provide a reference for the low-carbon production and deployment of photovoltaic power generation.

[0007] To this end, the present invention aims to provide a spatiotemporal dynamic photovoltaic power generation emission reduction potential assessment method under multiple development paths, to provide a basis for accurately assessing the carbon pollution emissions of photovoltaic power generation over its entire life cycle under different years and different development path combinations, and to combine a high-precision photovoltaic power generation resource potential assessment method to spatially characterize the emissions over its entire life cycle, and to accurately quantify the emission reduction potential of the future development of China's photovoltaic power generation industry. Summary of the invention

[0008] The present invention provides a spatiotemporal dynamic photovoltaic power generation emission reduction potential assessment method under multiple development paths, which is used to solve the problems existing in existing assessment methods, such as small temporal assessment scope, single assessment technology, and lack of dynamic characterization of differences between different years and regions.

[0009] The present invention provides a method for evaluating the emission reduction potential of photovoltaic power generation under multiple development paths in a spatiotemporal dynamic manner, comprising: Step 1: Construct the historical dynamic function of the target area in different years ,in, represents the set of greenhouse gas emissions of the corresponding target region in year t based on different photovoltaic power generation technologies manufactured in different regions; It represents the set of pollutant emissions corresponding to the target area in year t based on different photovoltaic power generation technologies manufactured in different regions; Step 2: Based on the global change assessment model and combined with the linear interpolation method, obtain the photovoltaic power generation installed capacity increment based on all regions in each future year, and combine the regional attributes of each target area to construct the future photovoltaic power generation development path matrix; Step 3: Dynamic function based on the history , the future photovoltaic power generation development path matrix and the carbon pollution reduction calculation method to determine the photovoltaic power generation emissions and emission reduction potential under the development path plan.

[0010] Preferably, before determining the photovoltaic power generation emissions and emission reduction potential under the development path plan, it also includes: based on the historical dynamic function Determine the historical potential of the target area, including: Construct a historical greenhouse gas reference sequence for the target area in year t based on the greenhouse gas emission set in, represents the greenhouse gas emissions from the i-th region excluding the target region to the target region based on the j-th photovoltaic power generation technology in year t; It represents the total greenhouse gas emissions from the ith region to non-self regions based on the jth photovoltaic power generation technology in year t; represents the greenhouse emission allocation of the i-th region to the target region in year t; ln represents the logarithmic function sign; Indicates the total number of regions; A unit setting amount representing greenhouse gas emissions; It indicates that the target area undertakes the historical greenhouse reference coefficient of the i-th area other than the target area based on the j-th photovoltaic power generation technology in year t; n2 indicates the total number of photovoltaic power generation technologies; Inputting the historical greenhouse reference sequence into a first sequence analysis model to obtain a first potential; Construct a historical pollutant reference sequence for the target area in year t based on the pollutant emission set in, It represents the pollutant emission from the i-th region other than the target region to the target region based on the j-th photovoltaic power generation technology in year t; It represents the total pollutant emissions from the ith region to non-self regions based on the jth photovoltaic power generation technology in year t; It represents the set pollutant allocation emission of the ith region to the target region in year t; represents the emission adjustment function from the i-th region excluding the target region to the target region based on the j-th photovoltaic power generation technology in year t; wherein, It indicates the unit set amount of pollutant emission; It indicates that the target area undertakes the historical pollutant reference coefficient of the i-th area other than the target area based on the j-th photovoltaic power generation technology in year t; represents the uniform radius of pollutant particles emitted by the j-th photovoltaic power generation technology in the i-th region; They represent the minimum radius and maximum radius of pollutant particles emitted by the j-th photovoltaic power generation technology; Inputting the historical pollutant reference sequence into a second sequence analysis model to obtain a second potential; Based on obtaining the first potentials and the second potentials of different historical years, determining the first variance for all the first potentials and the second variance for all the second potentials; The historical potential of the target area is obtained according to the first variance and the second variance.

[0011] Preferably, obtaining the historical potential of the target area according to the first variance and the second variance includes:

[0012] in, Indicate the historical potential of the target area; represents the adjustment coefficient; represent the average value of the first potential and the average value of the second potential respectively; Represent the first variance and the second variance respectively; Indicates n1 middle The number of Indicates the actual types and quantities of pollutants produced in the target area; Indicates the amount of pollutants allowed to be produced in the target area.

[0013] Preferably, based on the global change assessment model and in combination with a linear interpolation method, the photovoltaic power generation installed capacity increment based on all regions in each future year is obtained, including: The first curve is drawn based on the total greenhouse gas amount of all regions every year in the statistical history, and at the same time, the total greenhouse gas amount in adjacent historical years is subtracted to construct a first difference vector; The second curve is drawn based on the total pollutant amount of the entire region every year in the statistical history. At the same time, the total pollutant amount in adjacent historical years is subtracted to construct a second difference vector; Based on the linear interpolation method, the curve is linearly interpolated and linearly fitted to determine the fitting coefficient, and the corresponding difference vector is analyzed to obtain the increased variable range; Based on the variable range of greenhouse gas increase and pollutant increase, and combined with the power supply demand determined by the global change assessment model, the increase in photovoltaic power generation capacity in the next year is estimated.

[0014] Preferably, the variable range is increased, including: Calculate the left range bounds ;

[0015] in, represents the fitting coefficient; represents the average value of all quantities in the corresponding curve; Indicates the number of differences in the corresponding difference vector that are consistent with the positive and negative of r1; Indicates based on The variance of the differences; Representation and The average of the absolute values ​​corresponding to the differences; Indicates the total number of years involved; Calculate the right range bounds ;

[0016] in, Representation and Remainder The average of the absolute values ​​corresponding to the differences; Based on the left range boundary , right range boundary , which increases the variable range.

[0017] Preferably, the estimated incremental photovoltaic power generation capacity for the next year includes: Get the first increment based on the left range boundary and the right range from the greenhouse boundary-increment comparison table , second increment ; Obtain the third increment based on the left range boundary and the right range from the pollutant boundary-increase comparison table , the fourth increment ; Determine the future power required based on the power supply demand , and combined with the current electricity generated , first increment , second increment , the third increment And the fourth increment , estimate the photovoltaic power generation installed capacity increment NL in the next year;

[0018] in, Indicates the floor symbol; Indicates the electrical capacity generated by each photovoltaic power generation installation; express The variance of .

[0019] Preferably, the regional attributes include: clean electricity attribute and abundant resource attribute.

[0020] Preferably, determine the PV power generation emissions and emission reduction potential under the development path plan, including: Based on the historical dynamic function Determine the historical potential of the target area; Determine the production and installation scale of photovoltaic modules and the technology combination path of the target area in the future based on the future photovoltaic power generation development path matrix; Determine future potential based on production installation size and technology mix path; The historical potential and future potential are analyzed according to the carbon pollution reduction calculation method to determine the emission and reduction potential of photovoltaic power generation.

[0021] Compared with the prior art, the present invention has the following beneficial effects: It provides a basis for accurately evaluating the carbon pollution emissions of photovoltaic power generation throughout its life cycle in different years and under different development path combinations, and combines high-precision photovoltaic power generation resource potential assessment methods to spatially characterize the emissions of photovoltaic power generation throughout its life cycle, and accurately quantify the emission reduction potential of China's future photovoltaic power generation industry development.

[0022] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0023] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 The present invention is a flowchart of a method for evaluating the potential for emission reduction in photovoltaic power generation under multiple development paths in a spatiotemporal dynamic manner in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0026] The present invention provides a method for evaluating the emission reduction potential of photovoltaic power generation under multiple development paths in a spatiotemporal dynamic manner. Figure 1 As shown, including: Step 1: Construct the historical dynamic function of the target area in different years ,in, represents the set of greenhouse gas emissions of the corresponding target region in year t based on different photovoltaic power generation technologies manufactured in different regions; It represents the set of pollutant emissions corresponding to the target area in year t based on different photovoltaic power generation technologies manufactured in different regions; Step 2: Based on the global change assessment model and combined with the linear interpolation method, obtain the photovoltaic power generation installed capacity increment based on all regions in each future year, and combine the regional attributes of each target area to construct the future photovoltaic power generation development path matrix; Step 3: Dynamic function based on the history , the future photovoltaic power generation development path matrix and the carbon pollution reduction calculation method to determine the photovoltaic power generation emissions and emission reduction potential under the development path plan.

[0027] Preferably, the regional attributes include: a clean electricity attribute and a rich resource attribute.

[0028] In this embodiment, the target area refers to each province, and by determining the historical dynamic function of each province, a dynamic assessment of carbon pollution emissions from photovoltaic power generation can be performed in time and space.

[0029] In this embodiment, each parameter in the greenhouse gas emission set is based on Calculated, where Indicates that the product manufactured by the nth province in the tth year The life cycle greenhouse gas emissions of the mth photovoltaic technology; For deployment in the i-th grid The total electricity generated by photovoltaic power generation over its entire life cycle (25 years).

[0030] Each parameter in the pollutant emission set is based on Calculated, Indicates that the product manufactured by the nth province in the tth year Air pollutant emissions over the life cycle of the mth photovoltaic technology, the types of pollutants mainly include , NOx and primary PM2.5.

[0031] In this embodiment, the future photovoltaic power generation development path matrix is ​​as follows: .

[0032] The matrix represents different future PV module production, deployment and technology combinations in China. The business-as-usual scenario refers to the development of China's PV industry in line with historical trends; the average scenario refers to the production and deployment of PV modules being distributed according to the same share among provinces, while various PV technologies are developed in a balanced manner.

[0033] For example, assuming that China needs to add AkW of new photovoltaic capacity in a certain year, the photovoltaic production capacity allocated to a certain province X in that year according to the business-as-usual plan will be ,in represents the market share of photovoltaic modules produced by Province X obtained from public data; according to the business-as-usual plan, the installed capacity obtained by Province X in that year can be expressed as ,in represents the share of the historical photovoltaic installed capacity of Province X obtained from public data in the total photovoltaic installed capacity of the country. If the average allocation is followed, the photovoltaic capacity that Province X needs to produce and deploy in that year is , where n represents the number of all provinces. It should be noted that when allocating installed capacity shares, the installed capacity potential of each province must be considered at the same time. When the planned photovoltaic power generation installed capacity of a province exceeds its maximum photovoltaic installed capacity potential, the excess will continue to be deployed in other provinces according to the corresponding allocation principles.

[0034] In the "clean power province-led plan" in the production plan, the production of photovoltaic modules will be mainly produced by provinces with cleaner electricity. It is assumed that the top 30% of provinces with the lowest grid emission factors will produce 70% of China's photovoltaic module products in the future; in the "resource-rich province-led plan" in the deployment plan, photovoltaic power generation equipment will be mainly deployed in provinces with richer resources. Specifically, it is assumed that 70% of China's photovoltaic power generation equipment in the future will be deployed in provinces with the top 30% of photovoltaic average capacity factors. Similarly, in the above two deployment plans, the maximum deployment potential restrictions of each province need to be considered at the same time, that is, when the photovoltaic power generation installed capacity planned to be deployed in a province exceeds its maximum photovoltaic installed capacity potential, the excess will continue to be deployed in other provinces. At the same time, in all deployment plans, photovoltaic power generation will be deployed first in grid points with better resources. When the cumulative deployment capacity exceeds the maximum deployment potential of the grid point, it will be deployed in the second best grid point, and so on. Finally, in the technology combination scheme, the "silicon photovoltaic panel dominant scheme" means that the new photovoltaic installed capacity in the future will still be mainly composed of silicon-based photovoltaic modules. For example, if it is still assumed that the new photovoltaic installed capacity required in a certain year in the future is AkW, then the amount of silicon-based photovoltaic modules is , that is, assuming that the market share of silicon-based photovoltaic modules will be 70% in the future, and the remaining 30% will be thin-film photovoltaic technology; in the "average plan", the amount of each photovoltaic technology added in that year is , where m represents the type of photovoltaic technology; in the "thin-film photovoltaic dominant solution", the technology choice for future photovoltaic power generation will shift from silicon-based photovoltaic power generation technology to a new generation of thin-film photovoltaic power generation technology. Assuming that 70% of the new photovoltaic power generation technology in the future is a new generation of thin-film photovoltaic power generation technology, that is, , and the remaining 30% is silicon-based photovoltaic power generation technology.

[0035] Through the combination matrix of photovoltaic production, deployment and technology combination paths, a total of 27 future photovoltaic development paths can be combined, namely: production as usual - deployment as usual - silicon photovoltaic technology-dominated path, production as usual - deployment as usual - balanced development path of various photovoltaic technologies, production as usual - deployment as usual - thin-film photovoltaic technology-dominated path, production as usual - balanced deployment among provinces - silicon photovoltaic technology-dominated path, production as usual - balanced deployment among provinces - balanced development path of various photovoltaic technologies, production as usual - balanced deployment among provinces - thin-film photovoltaic technology-dominated path, production as usual - resource-rich provinces-dominated deployment - silicon photovoltaic technology-dominated path, production as usual - resource-rich provinces-dominated deployment - balanced development path of various photovoltaic technologies, production as usual - resource-rich provinces-dominated deployment - thin-film photovoltaic technology-dominated path, balanced production among provinces - deployment as usual - silicon photovoltaic technology-dominated path, balanced production among provinces - deployment as usual - balanced development path of various photovoltaic technologies, balanced production among provinces - deployment as usual - thin-film photovoltaic technology-dominated path, balanced production among provinces - balanced deployment among provinces - silicon photovoltaic technology-dominated path, balanced production among provinces - balanced deployment among provinces - balanced development path of various photovoltaic technologies, Balanced production-balanced deployment in all provinces-dominant path of thin-film photovoltaic technology, balanced production in all provinces-dominant deployment in resource-rich provinces-dominant path of silicon photovoltaic technology, balanced production in all provinces-dominant deployment in resource-rich provinces-balanced development path of various photovoltaic technologies, balanced production in all provinces-dominant deployment in resource-rich provinces-dominant path of thin-film photovoltaic technology, dominant production in clean electricity provinces-deployment remains the same-dominant path of silicon photovoltaic technology, dominant production in clean electricity provinces-deployment remains the same-balanced development path of various photovoltaic technologies, dominant production in clean electricity provinces-dominant deployment remains the same-dominant path of thin-film photovoltaic technology, dominant production in clean electricity provinces-balanced deployment in all provinces-dominant path of silicon photovoltaic technology, dominant production in clean electricity provinces-balanced deployment in all provinces-balanced development path of various photovoltaic technologies, dominant production in clean electricity provinces-balanced deployment in all provinces-dominant path of thin-film photovoltaic technology, dominant production in clean electricity provinces-dominant deployment in resource-rich provinces-dominant path of silicon photovoltaic technology, dominant production in clean electricity provinces-balanced deployment in all provinces-dominant path of thin-film photovoltaic technology, dominant production in clean electricity provinces-dominant deployment in resource-rich provinces-dominant path of silicon photovoltaic technology, dominant production in clean electricity provinces-dominant production in resource-rich provinces-balanced development path of various photovoltaic technologies, dominant production in clean electricity provinces-dominant deployment in resource-rich provinces-dominant path of thin-film photovoltaic technology.

[0036] In this example, the emission reduction brought about by the deployment of photovoltaics comes from the characterization of the electricity replaced by it, as follows:

[0037] in, represents the total greenhouse gas emission reduction of photovoltaic power generation equipment deployed in province p; represents the carbon emission factor of the power grid in province p; Represents the photovoltaic capacity factor of the i-th grid. Similarly, replacing the grid emission factor with the grid pollutant emission factor can obtain the pollutant emission reduction achieved by deploying photovoltaics in the corresponding province.

[0038] By combining the full life cycle emissions caused by PV module production and the carbon pollution reduction brought about by PV deployment, the net reduction in greenhouse gas and pollutant emissions achieved by PV deployment can be obtained as follows (taking greenhouse gases as an example):

[0039] in, represents the net greenhouse gas emission reduction obtained by deploying photovoltaic power generation in province p. Accordingly, the total greenhouse gas emission reduction and emission are replaced by pollutant emission reduction and emission to obtain the net pollutant emission reduction achieved by the deployment of photovoltaic power generation in the corresponding province.

[0040] As the deployment of photovoltaic power generation in various provinces progresses, the corresponding grid emission factors are also changing. Therefore, it is necessary to further dynamically characterize the grid emission factors of each province, as follows:

[0041] in, represents the emission factor of the fth fossil fuel power generation in year t; It represents the proportion of the f-th fossil fuel power generation in the p-th province power grid in the t-th year. This parameter can be obtained by sorting out the output data of the GCAM model.

[0042] In this embodiment, by constructing a spatiotemporal dynamic photovoltaic power generation emission reduction potential assessment method under multiple development paths, the photovoltaic power generation emission reduction potential at the national and provincial levels in China is accurately and dynamically assessed, effectively improving the comprehensiveness of the assessment. At the same time, the present invention improves the temporal resolution of the full life cycle assessment through a time-dynamic full life cycle inventory; improves the spatial resolution of the photovoltaic power generation full life cycle assessment by coupling a high-precision photovoltaic power generation resource assessment method; and improves the integrity of the photovoltaic power generation full life cycle assessment technology by comprehensively considering a variety of photovoltaic power generation technologies. In addition, the present invention makes up for the deficiency of the existing technology that cannot judge future trends by spatiotemporally quantifying the full life cycle emissions of photovoltaic power generation under different technology combinations and market shares in future years, and provides a reference for the coordinated governance of carbon pollution in the context of the future doubling of photovoltaic power generation.

[0043] The beneficial effects of the above technical solution are: it provides a basis for accurately evaluating the carbon pollution emissions of photovoltaic power generation throughout its life cycle under different years and different development path combinations, and combines it with a high-precision photovoltaic power generation resource potential assessment method to spatially characterize the emissions of photovoltaic power generation throughout its life cycle, and accurately quantify the emission reduction potential of China's future photovoltaic power generation industry development.

[0044] The present invention provides a method for evaluating the potential for photovoltaic power generation emission reduction under multiple development paths in terms of spatiotemporal dynamics. Before determining the photovoltaic power generation emissions and emission reduction potential under the development path scheme, the method further includes: based on the historical dynamic function Determine the historical potential of the target area, including: Construct a historical greenhouse gas reference sequence for the target area in year t based on the greenhouse gas emission set in, represents the greenhouse gas emissions from the i-th region excluding the target region to the target region based on the j-th photovoltaic power generation technology in year t; It represents the total greenhouse gas emissions from the ith region to non-self regions based on the jth photovoltaic power generation technology in year t; represents the greenhouse emission allocation of the i-th region to the target region in year t; ln represents the logarithmic function sign; Indicates the total number of regions; A unit setting amount representing greenhouse gas emissions; It indicates that the target area undertakes the historical greenhouse reference coefficient of the i-th area other than the target area based on the j-th photovoltaic power generation technology in year t; n2 indicates the total number of photovoltaic power generation technologies; Inputting the historical greenhouse reference sequence into a first sequence analysis model to obtain a first potential; Construct a historical pollutant reference sequence for the target area in year t based on the pollutant emission set in, It represents the pollutant emission from the i-th region other than the target region to the target region based on the j-th photovoltaic power generation technology in year t; It represents the total pollutant emissions from the ith region to non-self regions based on the jth photovoltaic power generation technology in year t; It represents the set pollutant allocation emission of the ith region to the target region in year t; represents the emission adjustment function from the i-th region excluding the target region to the target region based on the j-th photovoltaic power generation technology in year t; wherein, It indicates the unit set amount of pollutant emission; It indicates that the target area undertakes the historical pollutant reference coefficient of the i-th area other than the target area based on the j-th photovoltaic power generation technology in year t; represents the uniform radius of pollutant particles emitted by the j-th photovoltaic power generation technology in the i-th region; They represent the minimum radius and maximum radius of pollutant particles emitted by the j-th photovoltaic power generation technology; Inputting the historical pollutant reference sequence into a second sequence analysis model to obtain a second potential; Based on obtaining the first potentials and the second potentials of different historical years, determining the first variance for all the first potentials and the second variance for all the second potentials; The historical potential of the target area is obtained according to the first variance and the second variance.

[0045] Preferably, obtaining the historical potential of the target area according to the first variance and the second variance includes:

[0046] in, Indicate the historical potential of the target area; represents the adjustment coefficient; represent the average value of the first potential and the average value of the second potential respectively; Represent the first variance and the second variance respectively; Indicates n1 The number of Indicates the actual types and quantities of pollutants produced in the target area; Indicates the amount of pollutants allowed to be produced in the target area.

[0047] In this embodiment, the first sequence analysis model is obtained by training a neural network model based on greenhouse reference sequences of different combinations and potential evaluation results of the greenhouse reference sequences as samples, and therefore the first potential can be directly obtained.

[0048] The second sequence analysis model is obtained by training a neural network model based on samples of different combinations of pollutant reference sequences and potential assessment results for the pollutant reference sequences. Therefore, the second potential can be directly obtained.

[0049] In this embodiment, Ny is less than or equal to Sy.

[0050] The beneficial effect of the above technical solution is: by obtaining the historical temperature reference coefficient based on different years for each region, it is convenient to obtain the first potential, and by combining the pollutant reference coefficient based on different years, it is convenient to obtain the second potential, thereby ensuring the accuracy of the historical potential for the region and providing an accurate basis for subsequent evaluation.

[0051] The present invention provides a method for evaluating the potential for emission reduction of photovoltaic power generation under multiple development paths in a spatiotemporal dynamic manner. The method is based on a global change assessment model and combined with a linear interpolation method to obtain the incremental photovoltaic power generation installed capacity based on all regions in each future year, including: The first curve is drawn based on the total greenhouse gas amount of all regions every year in the statistical history, and at the same time, the total greenhouse gas amount in adjacent historical years is subtracted to construct a first difference vector; The second curve is drawn based on the total pollutant amount of the entire region every year in the statistical history. At the same time, the total pollutant amount in adjacent historical years is subtracted to construct a second difference vector; Based on the linear interpolation method, the curve is linearly interpolated and linearly fitted to determine the fitting coefficient, and the corresponding difference vector is analyzed to obtain the increased variable range; Based on the variable range of greenhouse gas increase and pollutant increase, and combined with the power supply demand determined by the global change assessment model, the increase in photovoltaic power generation capacity in the next year is estimated.

[0052] Preferably, the variable range is increased, including: Calculate the left range bounds ;

[0053] in, represents the fitting coefficient; represents the average value of all quantities in the corresponding curve; Indicates the number of differences in the corresponding difference vector that are consistent with the positive and negative of r1; Indicates based on The variance of the differences; Representation and The average of the absolute values ​​corresponding to the differences; Indicates the total number of years involved; Calculate the right range bounds ;

[0054] in, Representation and Remainder The average of the absolute values ​​corresponding to the differences; Based on the left range boundary , right range boundary , which increases the variable range.

[0055] In this example, the variable range is increased by , right range boundary ).

[0056] In this embodiment, the first curve is obtained by plotting the year as the horizontal axis and the total amount of greenhouse gases generated each year as the vertical axis, and the first difference vector = They represent the total greenhouse gas amounts corresponding to the 2nd year, the 1st year, the tth year, and the t-1th year respectively.

[0057] In this embodiment, the second curve is drawn with the year as the horizontal axis and the total amount of pollutants generated each year as the vertical axis, and the second difference vector They represent the total greenhouse gas amounts corresponding to the 2nd year, the 1st year, the tth year, and the t-1th year respectively.

[0058] In this embodiment, the linear interpolation method is used to fill in missing values ​​in the curve, which belongs to the prior art, and then the filled curve is linearly fitted, which also belongs to the prior art, and then the fitting coefficient can be directly obtained. When the fitting coefficient is greater than or equal to 0, it is regarded as a positive sign, and when the fitting coefficient is less than 0, it is regarded as a negative sign.

[0059] In this embodiment, the global change assessment model is obtained by training a neural network model based on annual electricity consumption and annual electricity consumption increase as samples, so the power supply demand can be directly obtained.

[0060] The beneficial effect of the above technical solution is: by drawing curves for temperature and pollutants and constructing differential vectors, the range of increased variables is determined to ensure the accuracy of the estimated incremental installed capacity of power generation, wherein the integrity of the numerical values ​​in the curve is ensured by linear interpolation of the curve, and the rationality of the increment is indirectly ensured by subsequently calculating the range boundaries on the left and right sides.

[0061] The present invention provides a method for evaluating the potential for emission reduction of photovoltaic power generation under multiple development paths in a spatiotemporal dynamic manner, and estimates the incremental photovoltaic power generation installed capacity in the next year, including: Get the first increment based on the left range boundary and the right range from the greenhouse boundary-increment comparison table , second increment ; Obtain the third increment based on the left range boundary and the right range from the pollutant boundary-increase comparison table , the fourth increment ; Determine the future power required based on the power supply demand , and combined with the current electricity generated , first increment , second increment , the third increment And the fourth increment , estimate the photovoltaic power generation installed capacity increment NL in the next year;

[0062] in, Indicates the floor symbol; Indicates the electrical capacity generated by each photovoltaic power generation installation; express The variance of .

[0063] In this embodiment, the greenhouse boundary-increment comparison table contains increments that match the left and right temperature boundaries, and the first increment and the second increment can be directly matched.

[0064] In this embodiment, the pollutant boundary-increment comparison table contains increments that match the left and right boundaries of the pollutant, and the third increment and the fourth increment can be directly matched.

[0065] The beneficial effect of the above technical solution is: by determining the increment based on greenhouse and pollutants, it is convenient to effectively estimate the increment of photovoltaic power generation installed capacity, and provide a data analysis basis for subsequent front-end potential assessment.

[0066] The present invention provides a method for evaluating the emission reduction potential of photovoltaic power generation under multiple development paths in a spatiotemporal dynamic manner, and determines the emission and emission reduction potential of photovoltaic power generation under development path schemes, including: Based on the historical dynamic function Determine the historical potential of the target area; Determine the production and installation scale of photovoltaic modules and the technology combination path of the target area in the future based on the future photovoltaic power generation development path matrix; Determine future potential based on production installation size and technology mix path; The historical potential and future potential are analyzed according to the carbon pollution reduction calculation method to determine the emission and reduction potential of photovoltaic power generation.

[0067] In this embodiment, the production installation scale and technology combination path are 27 results generated based on the matrix.

[0068] In this embodiment, the future potential is calculated by averaging each potential under the 27 outcomes.

[0069] In this embodiment, power generation emissions and emission reduction potential are obtained based on the average of historical potential and future potential.

[0070] The beneficial effect of the above technical solution is that by determining the historical potential and future potential, the emission and emission reduction potential of photovoltaic power generation can be effectively determined.

[0071] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A spatiotemporal dynamic photovoltaic power generation emission reduction potential assessment method under multiple development paths, characterized in that: include: Step 1: Construct the historical dynamic function of the target area in different years ,in, represents the set of greenhouse gas emissions of the corresponding target region in year t based on different photovoltaic power generation technologies manufactured in different regions; It represents the set of pollutant emissions corresponding to the target area in year t based on different photovoltaic power generation technologies manufactured in different regions; Step 2: Based on the global change assessment model and combined with the linear interpolation method, obtain the photovoltaic power generation installed capacity increment based on all regions in each future year, and combine the regional attributes of each target area to construct the future photovoltaic power generation development path matrix; Step 3: Dynamic function based on the history , the future photovoltaic power generation development path matrix and the carbon pollution reduction calculation method to determine the photovoltaic power generation emissions and emission reduction potential under the development path plan.

2. The method for evaluating the potential for emission reduction of photovoltaic power generation under multiple development paths in spatiotemporal dynamics according to claim 1 is characterized in that: Before determining the PV power generation emissions and emission reduction potential under the development path plan, it also includes: based on the historical dynamic function Determine the historical potential of the target area, including: Construct a historical greenhouse gas reference sequence for the target area in year t based on the greenhouse gas emission set in, represents the greenhouse gas emissions from the i-th region excluding the target region to the target region based on the j-th photovoltaic power generation technology in year t; It represents the total greenhouse gas emissions from the ith region to non-self regions based on the jth photovoltaic power generation technology in year t; represents the greenhouse emission allocation of the i-th region to the target region in year t; ln represents the logarithmic function sign; Indicates the total number of regions; A unit setting amount representing greenhouse gas emissions; It indicates that the target area undertakes the historical greenhouse reference coefficient of the i-th area other than the target area based on the j-th photovoltaic power generation technology in year t; represents the total number of photovoltaic technologies; Inputting the historical greenhouse reference sequence into a first sequence analysis model to obtain a first potential; Construct a historical pollutant reference sequence for the target area in year t based on the pollutant emission set in, It represents the pollutant emission from the i-th region other than the target region to the target region based on the j-th photovoltaic power generation technology in year t; It represents the total pollutant emissions from the ith region to non-self regions based on the jth photovoltaic power generation technology in year t; It represents the set pollutant allocation emission of the ith region to the target region in year t; represents the emission adjustment function from the i-th region excluding the target region to the target region based on the j-th photovoltaic power generation technology in year t; wherein, It indicates the unit set amount of pollutant emission; It indicates that the target area undertakes the historical pollutant reference coefficient of the i-th area other than the target area based on the j-th photovoltaic power generation technology in year t; represents the uniform radius of pollutant particles emitted by the j-th photovoltaic power generation technology in the i-th region; They represent the minimum radius and maximum radius of pollutant particles emitted by the j-th photovoltaic power generation technology; Inputting the historical pollutant reference sequence into a second sequence analysis model to obtain a second potential; Based on obtaining the first potentials and the second potentials of different historical years, determining the first variance for all the first potentials and the second variance for all the second potentials; The historical potential of the target area is obtained according to the first variance and the second variance.

3. The method for evaluating the potential for emission reduction of photovoltaic power generation under multiple development paths in spatiotemporal dynamics according to claim 2 is characterized in that: According to the first variance and the second variance, the historical potential of the target area is obtained, including: ； ； ； in, Indicate the historical potential of the target area; represents the adjustment coefficient; represent the average value of the first potential and the average value of the second potential respectively; Represent the first variance and the second variance respectively; Indicates n1 middle The number of Indicates the actual types and quantities of pollutants produced in the target area; Indicates the amount of pollutants allowed to be produced in the target area.

4. The method for evaluating the potential for emission reduction of photovoltaic power generation under multiple development paths in spatiotemporal dynamics according to claim 1 is characterized in that: Based on the global change assessment model and combined with the linear interpolation method, the photovoltaic power generation installed capacity increment based on all regions in each year in the future is obtained, including: The first curve is drawn based on the total greenhouse gas amount of all regions every year in the statistical history, and at the same time, the total greenhouse gas amount in adjacent historical years is subtracted to construct a first difference vector; The second curve is drawn based on the total pollutant amount of the entire region every year in the statistical history. At the same time, the total pollutant amount in adjacent historical years is subtracted to construct a second difference vector; Based on the linear interpolation method, the curve is linearly interpolated and linearly fitted to determine the fitting coefficient, and the corresponding difference vector is analyzed to obtain the increased variable range; Based on the variable range of greenhouse gas increase and pollutant increase, and combined with the power supply demand determined by the global change assessment model, the increase in photovoltaic installed capacity in the next year is estimated.

5. The method for evaluating the potential for emission reduction of photovoltaic power generation under multiple development paths in spatiotemporal dynamics according to claim 4 is characterized in that: Get increased variable scope, including: Calculate the left range bounds ; ； in, represents the fitting coefficient; represents the average value of all quantities in the corresponding curve; Indicates the number of differences in the corresponding difference vector that are consistent with the positive and negative of r1; Indicates based on The variance of the differences; Representation and The average of the absolute values ​​corresponding to the differences; Indicates the total number of years involved; Calculate the right range bounds ; ； in, Representation and Remainder The average of the absolute values ​​corresponding to the differences; Based on the left range boundary , right range boundary , which increases the variable range.

6. The method for evaluating the potential for emission reduction of photovoltaic power generation under multiple development paths in spatiotemporal dynamics according to claim 4 is characterized in that: The estimated increase in photovoltaic installed capacity in the next year includes: Get the first increment based on the left range boundary and the right range from the greenhouse boundary-increment comparison table , second increment ; Obtain the third increment based on the left range boundary and the right range from the pollutant boundary-increase comparison table , the fourth increment ; Determine the future power required based on the power supply demand , and combined with the current electricity generated , first increment , second increment , the third increment And the fourth increment , estimate the photovoltaic power generation installed capacity increment NL in the next year; ； in, Indicates the floor symbol; Indicates the electrical capacity generated by each photovoltaic power generation installation; express The variance of .

7. The method for evaluating the potential for emission reduction of photovoltaic power generation under multiple development paths in spatiotemporal dynamics according to claim 1 is characterized in that: The regional attributes include: clean electricity attribute and rich resource attribute.

8. The method for evaluating the potential for emission reduction of photovoltaic power generation under multiple development paths in spatiotemporal dynamics according to claim 1 is characterized in that: Determine the PV power generation emissions and emission reduction potential under the development path options, including: Based on the historical dynamic function Determine the historical potential of the target area; Determine the production and installation scale of photovoltaic modules and the technology combination path of the target area in the future based on the future photovoltaic power generation development path matrix; Determine future potential based on production installation size and technology mix path; The historical potential and future potential are analyzed according to the carbon pollution reduction calculation method to determine the emission and reduction potential of photovoltaic power generation.

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