Power distribution network optimization evaluation method and system based on distributed photovoltaic consumption capability

Abstract

The invention provides a power distribution network optimization evaluation method and system based on distributed photovoltaic absorption capability, and relates to the technical field of power distribution networks. The method comprises the following steps: S1, acquiring real-time load data and resource data of each node in the power distribution network; s2, matching the real-time load data with the distributed photovoltaic output, and calculating the consumption capability of the power distribution network; s3, judging whether the consumption capability of the power distribution network meets the requirement of power grid operation safety or not; s4, the distributed photovoltaic output is combined with various types of user loads, and the source load matching degree of each user of the power grid node is calculated; s5, generating a transformation optimization scheme of the power distribution network; s6, judging whether the transformation optimization scheme meets the optimization target of the optimal total investment of the project or not; and S7, outputting a power distribution network optimization scheme for improving the distributed photovoltaic absorption capability. According to the method and the system, effective connection of two levels of power system operation and optimization planning layout can be realized, and the distributed photovoltaic consumption capability of the power distribution network is improved.

Description

Technical Field

[0001] The present application relates to the technical field of distribution network, and in particular to a distribution network optimization evaluation method and system based on distributed photovoltaic absorption capacity. Background Art

[0002] Distributed photovoltaic power generation, as a clean and efficient way of energy utilization, brings many benefits. It not only helps to promote the transformation of energy structure, but also promotes the sustainable development of economy and society. It is the main power source form of new energy power generation.

[0003] However, in recent years, the scale of distributed photovoltaic installations has increased rapidly, and problems such as reverse power transmission to transformer overload and user overvoltage have gradually become prominent. At the same time, the grid connection and absorption of new distributed installation projects face challenges. On the one hand, with the surge in distributed photovoltaic installations, the access capacity space of 110kV and below distribution networks is getting smaller and smaller. In some areas, the transformer capacity is insufficient, and in some areas, there is sufficient transformer capacity but lack of load absorption, which leads to problems such as reverse power transmission and voltage overload in the transmission network, resulting in the inability of distributed photovoltaics to be connected to the grid in some areas. On the other hand, in the case of high penetration of household photovoltaics in some provinces, coupled with the low electricity load of the whole society during the Spring Festival, the actual situation that the power grid cannot meet the full absorption demand of new energy. At the current stage of development, the output of new energy in some areas is greater than the local load, and the inability to balance locally has become the first problem faced. Distributed energy should be absorbed locally as much as possible, which has become an important task for the development of distribution networks.

[0004] The traditional distribution network planning method is mainly aimed at meeting power supply demand. This planning method is relatively simple and achieves the active response of power supply to load. It cannot fully absorb the large-scale access of distributed photovoltaics and cannot give full play to the regulatory ability of distributed photovoltaics on the grid structure. Therefore, it is impossible to achieve the technical and economic optimization of the grid structure. Summary of the invention

[0005] The purpose of the embodiments of the present application is to provide a distribution network optimization evaluation method and system based on distributed photovoltaic absorption capacity, so as to achieve effective connection between the two levels of power system operation and optimized planning and layout, and to improve the distributed photovoltaic absorption capacity of the distribution network.

[0006] In a first aspect, the present invention provides a distribution network optimization evaluation method based on distributed photovoltaic absorption capacity, the method comprising:

[0007] S1: Obtain real-time load data and resource data of each node in the distribution network;

[0008] S2: Match the real-time load data with the distributed photovoltaic output to calculate the absorption capacity of the distribution network, where the distributed photovoltaic output is obtained based on the resource data;

[0009] S3: Determine whether the absorption capacity of the distribution network meets the requirements for safe operation of the power grid;

[0010] S4: Combine the distributed photovoltaic output with the loads of various types of users to calculate the source-load matching degree of each user at the grid node;

[0011] S5: Generate a transformation optimization plan for the distribution network based on the source-load matching degree;

[0012] S6: Determine whether the transformation optimization plan meets the optimization goal of the optimal total project investment;

[0013] S7: Output distribution network optimization plan to improve distributed photovoltaic absorption capacity.

[0014] In an optional embodiment, S2 includes:

[0015] Construct a distributed photovoltaic output model and calculate the distributed photovoltaic output coefficient P ij ;

[0016] Output coefficient P based on distributed photovoltaic ij , calculate the absorption capacity of the distribution network.

[0017] In an optional implementation, in S2, the output model of distributed photovoltaics is expressed by the following formula:

[0018] P i =η×S×I×[1-(T s -T i )]

[0019] Where: P i is the photovoltaic output at time i; η is the photovoltaic panel power conversion efficiency; S is the photovoltaic panel installation area; I is the solar radiation intensity under standard conditions; T S is the standard ambient temperature, T i is the actual ambient temperature at time i;

[0020] The output coefficient P of distributed photovoltaic is standardized ij :

[0021]

[0022] The calculation formula of the distribution network's absorption capacity is as follows:

[0023]

[0024] Where P PV is the consumption capacity of the jth node at time i, X ij is the real-time load of the j-th node at time i.

[0025] In an optional embodiment, S3 includes:

[0026] If the requirements are met, S4 is executed; if the requirements are not met, the capacity of the distributed photovoltaic equipment is optimized and the absorption capacity of the distribution network is recalculated, that is, after optimization, S2 is returned to execute until the requirements are met;

[0027] Among them, the requirements for safe operation of the power grid include that for three-phase power supply of 10 kV and below in the distribution network, the allowable deviation of the power supply voltage is ±7% of the rated value; the requirements for safe operation of the power grid also include that the three-phase imbalance of the distribution network does not exceed 2%.

[0028] In an optional embodiment, S4 includes:

[0029] Classify each user of the power grid node and obtain their load data;

[0030] According to the user load characteristics, the source-load matching degree of each user is calculated.

[0031] In an optional implementation, in S4, the calculation formula of the source-load matching degree S is:

[0032] S=s A ·s F

[0033] Where: s A is the horizontal matching degree; s F is the vertical matching degree.

[0034] In an optional embodiment, S5 includes:

[0035] Sort the transformation optimization plans from large to small according to the source-load matching degree, and select the transformation optimization plan that meets the threshold requirements.

[0036] In an optional embodiment, S6 includes:

[0037] If the transformation optimization scheme meets the optimization goal of the optimal total project investment, that is, the total project investment of the transformation optimization scheme does not exceed the limit value, then execute S7;

[0038] If the transformation optimization plan does not meet the optimization goal of the optimal total project investment, that is, the total project investment of the transformation optimization plan exceeds the limit, then optimize the matching of real-time load data and distributed photovoltaic output, recalculate the absorption capacity of the distribution network, and return to execute S2.

[0039] In an optional embodiment, S6 includes:

[0040] An optimization planning decision model with the best total project investment is constructed, and the optimal total project investment is calculated using the optimization planning decision model. The objective function of the optimization planning decision model is as follows:

[0041] min C=Cjs +C sg

[0042] Where: C represents the total investment of the project, C js represents the investment cost of distribution network construction equipment, C sg Represents the construction cost of the distribution network.

[0043] In a second aspect, the present invention provides a distribution network optimization evaluation system based on distributed photovoltaic absorption capacity, the system comprising:

[0044] A data acquisition module is used to obtain real-time load data and resource data of each node in the distribution network;

[0045] The absorption capacity calculation module is used to match the real-time load data with the distributed photovoltaic output to calculate the absorption capacity of the distribution network, where the distributed photovoltaic output is obtained based on the resource data;

[0046] Safety judgment module, used to judge whether the absorption capacity of the distribution network meets the requirements of grid operation safety;

[0047] The matching degree calculation module is used to combine the distributed photovoltaic output with various types of user loads and calculate the source-load matching degree of each user at the grid node;

[0048] The scheme generation module is used to generate the transformation optimization scheme of the distribution network based on the source-load matching degree;

[0049] The optimal judgment module is used to judge whether the transformation optimization plan meets the optimization goal of the optimal total project investment;

[0050] The solution output module is used to output distribution network optimization solutions to improve the distributed photovoltaic absorption capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 A flow chart of a distribution network optimization evaluation method based on distributed photovoltaic absorption capacity provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0054] In the context of new energy development and the requirements for improving the quality and efficiency of power grids, in response to the power grid carrying capacity and new energy absorption problems brought about by the surge in distributed photovoltaic installations, this embodiment proposes a distributed photovoltaic absorption capacity calculation method taking into account time series, and makes differentiated optimization combinations of sources and loads in the planning area. It proposes a distribution network optimization planning and layout method based on maximizing absorption capacity and taking the optimization of comprehensive construction cost as the goal, so as to achieve effective connection between the two levels of power system operation and optimized planning and layout, and improve the distributed photovoltaic absorption capacity of the distribution network.

[0055] Please refer to Figure 1 The present application embodiment provides a distribution network optimization evaluation method based on distributed photovoltaic absorption capacity (hereinafter referred to as: method), the method comprising the following steps:

[0056] S1: Obtain real-time load data and resource data of each node in the distribution network.

[0057] Specifically, by collecting the real-time load data of each node in the distribution network, a real-time load data matrix X containing m nodes at n moments is formed. n×m :

[0058]

[0059] In the formula, x n×m is the real-time load of the mth node at time n.

[0060] Resource data mainly include distributed photovoltaic light intensity, ambient temperature, photovoltaic equipment parameters, etc., from which the distributed photovoltaic output can be obtained.

[0061] S2: Match the real-time load data with the distributed photovoltaic output to calculate the distribution network’s absorption capacity.

[0062] First, the output model of distributed photovoltaics is constructed and the output coefficient of distributed photovoltaics is calculated.

[0063] The output of photovoltaic power is directly affected by the light intensity. The power generation of photovoltaic cells is positively correlated with the light intensity. According to the research on photovoltaic output, the output model of distributed photovoltaic can be expressed as follows:

[0064] P i =η×S×I×[1-(T s -T i )]

[0065] Where: P i is the photovoltaic output at time i; η is the photovoltaic panel power conversion efficiency; S is the photovoltaic panel installation area; I is the solar radiation intensity under standard conditions; T S is the standard ambient temperature, T i is the actual ambient temperature at time i.

[0066] The output coefficient P of distributed photovoltaic is obtained by standardization ij :

[0067]

[0068] Then, based on the output coefficient P of distributed photovoltaic ij , calculate the absorption capacity of the distribution network.

[0069]

[0070] Where P PV is the consumption capacity of the j-th node at time i.

[0071] Because real-time load data has seasonal and daily periodic characteristics, and distributed photovoltaic output has uncertainty and randomness, the distribution network's absorption capacity in different time periods is calculated by matching the real-time load data of the distribution network nodes with the distributed photovoltaic output in time series. This can identify weak links in absorption capacity, such as node voltage and power distribution, and more accurately judge the stability of the power system, providing a basic idea for subsequent source-load matching and optimization solutions.

[0072] S3: Determine whether the distribution network's absorption capacity meets the requirements for safe grid operation.

[0073] If the requirements are met, execute S4; if the requirements are not met, optimize the capacity of distributed photovoltaic equipment and recalculate the absorption capacity of the distribution network, that is, after optimization, return to execute S2 until the requirements are met.

[0074] Specifically, the absorption capacity of the distribution network under the voltage deviation rate and three-phase imbalance evaluation indicators are checked respectively, and the optimal absorption capacity of the distribution network based on timing considerations for the safety of grid operation is determined.

[0075] The requirements for safe operation of the power grid include that for three-phase power supply of 10 kV and below in the distribution network, the allowable deviation of the power supply voltage is ±7% of the rated value.

[0076] Node voltage deviation rate α ij :

[0077]

[0078] In the formula, is the supply voltage, U 标 is the voltage rating.

[0079] Three-phase imbalance: The distribution network usually uses three-phase voltage for power supply. When the three-phase imbalance occurs, negative sequence voltage and zero sequence voltage also appear successively. The three-phase imbalance is mainly calculated by calculating the degree of negative sequence voltage (the requirement for power grid operation safety also includes that the three-phase imbalance of the distribution network does not exceed 2%). Therefore, the three-phase imbalance is used as an indicator, and the three-phase imbalance β ij The calculation formula is as follows:

[0080]

[0081] Where U 负ij is the node negative sequence voltage, U 正ij is the node positive sequence voltage.

[0082] In this way, by verifying the voltage deviation rate and the three-phase imbalance evaluation index, the distribution network's absorption capacity is obtained, which is the optimal distribution network absorption capacity based on timing considerations for the safety of grid operation.

[0083] S4: Combine the distributed photovoltaic output with various types of user loads to calculate the source-load matching degree of each user at the grid node.

[0084] Specifically, first, classify each user at the grid node and obtain their load data; then, calculate the source-load matching degree of each user based on the user's load characteristics. In this way, by integrating the load types and absorption capacity of different power consumption characteristics, it is possible to comprehensively consider the voltage and power requirements at different time points, and use the optimization algorithm to adjust the distribution network construction optimization plan and the capacity of distributed photovoltaics, which helps to maximize the absorption capacity of distributed photovoltaics, reduce grid losses, and improve grid efficiency, thereby promoting the large-scale application of distributed photovoltaics.

[0085] Specifically, the source-load matching degree is composed of two indicators: horizontal matching degree and vertical matching degree. The horizontal matching degree refers to the ratio of the average value of the difference between the load size and the distributed photovoltaic output size at each moment to the maximum value of the difference. It reflects the stability of the grid supply load curve after the load curve and the distributed photovoltaic output curve are subtracted over a period of time. It can more realistically measure the degree of matching between the load and the distributed photovoltaic output. The calculation formula for horizontal matching degree is:

[0086]

[0087] Where: s A is the horizontal matching degree; t is the time number of the statistical cycle; ΔP ldi is the difference between the load size and the distributed photovoltaic output size at time i; ΔP ldmax It is the maximum value of the difference between the load and the distributed photovoltaic output.

[0088] Vertical matching refers to the ratio of the minimum to maximum value of the difference between the load size and the distributed photovoltaic output size at each moment, reflecting the maximum difference between the two over a period of time. The calculation formula for vertical matching is:

[0089]

[0090] Where: s F is the vertical matching degree, ΔP ldmin It is the minimum value of the difference between the load and the distributed photovoltaic output.

[0091] The horizontal matching degree and vertical matching degree are combined by cumulative multiplication to form the matching degree between load and distributed photovoltaic output. Assuming that the maximum value of each indicator is 1, the calculation formula of source-load matching degree S is:

[0092] S=s A ·s F

[0093] The larger the source-load matching degree S is, the higher the matching degree between the load and the distributed photovoltaic output is.

[0094] S5: Generate a transformation optimization plan for the distribution network based on the source-load matching degree.

[0095] Specifically, first, the transformation optimization plans are sorted from large to small according to the source-load matching degree, and then the transformation optimization plan that meets the threshold requirement is selected.

[0096] S6: Determine whether the transformation optimization plan meets the optimization goal of the optimal total project investment.

[0097] Specifically, an optimization planning decision model with the best total project investment is constructed, and the optimal total project investment is calculated using the optimization planning decision model. That is, the objective function of the optimization planning decision model is as follows:

[0098] minC=C js +C sg

[0099] Where: C represents the total investment of the project, C js represents the investment cost of distribution network construction equipment, C sg Represents the construction cost of the distribution network.

[0100] If the transformation optimization scheme meets the optimization goal of the optimal total project investment, that is, the total project investment of the transformation optimization scheme does not exceed the limit value, then execute S7;

[0101] If the transformation optimization plan does not meet the optimization goal of the optimal total project investment, that is, the total project investment of the transformation optimization plan exceeds the limit, the matching of real-time load data and distributed photovoltaic output is optimized, and the absorption capacity of the distribution network is recalculated, that is, return to execute S2. In this way, by quantifying the source-load correlation and identifying the link of supply and demand imbalance, corresponding measures can be taken to optimize and adjust in a targeted manner to achieve efficient use of energy and dynamic balance of supply and demand.

[0102] S7: Output distribution network optimization plan to improve distributed photovoltaic absorption capacity.

[0103] Based on the same technical concept, this embodiment also provides a distribution network optimization evaluation system based on distributed photovoltaic absorption capacity (hereinafter referred to as: system), the system comprising:

[0104] A data acquisition module is used to obtain real-time load data and resource data of each node in the distribution network, that is, to execute S1;

[0105] The absorption capacity calculation module is used to match the real-time load data with the distributed photovoltaic output to calculate the absorption capacity of the distribution network, wherein the distributed photovoltaic output is obtained based on the resource data, i.e., used to execute S2;

[0106] A safety judgment module is used to judge whether the absorption capacity of the distribution network meets the requirements of the safety of the power grid operation, that is, to execute S3;

[0107] A matching degree calculation module is used to combine the distributed photovoltaic output with various types of user loads and calculate the source-load matching degree of each user at the grid node, that is, to execute S4;

[0108] A scheme generation module is used to generate a transformation optimization scheme for the distribution network based on the source-load matching degree, i.e., to execute S5;

[0109] The optimal judgment module is used to judge whether the transformation optimization scheme meets the optimization goal of the optimal total investment of the project, that is, to execute S6;

[0110] The solution output module is used to output the distribution network optimization solution for improving the distributed photovoltaic absorption capacity, that is, for executing S7.

[0111] The beneficial effects of the distribution network optimization evaluation method and system based on distributed photovoltaic absorption capacity provided by this embodiment include:

[0112] 1. A method for calculating the absorption capacity of distributed photovoltaic power considering the time sequence is proposed. The load data of the distribution network nodes and the output power of distributed photovoltaic power are obtained and matched in the time sequence. The load of the distribution network and the absorption capacity of distributed photovoltaic power in different time periods are calculated. After the distributed photovoltaic power is connected, the voltage deviation does not exceed ±7%, and the three-phase imbalance does not exceed 2%. The distributed photovoltaic absorption capacity that meets the safe operation requirements of the power grid at different times is output.

[0113] 2. Propose an optimization evaluation strategy for the distribution network based on source-load matching. Combined with the output characteristics of distributed photovoltaics and the load characteristics of users, the complementary characteristics between distributed photovoltaics and loads, and the matching characteristics between distributed photovoltaic output and loads are analyzed. With the maximum absorption capacity of distributed photovoltaics as the goal, the correlation between distributed photovoltaics and multiple loads in the distribution network is analyzed.

[0114] 3. Propose a distribution network optimization plan with the goal of optimizing the comprehensive construction cost. Based on the supply and demand balance constraints, input load data with a high degree of matching between the source and load combination absorption capacity, and build a distribution network planning optimization plan with the goal of optimizing the comprehensive cost of system equipment investment, construction, etc. Under the premise of meeting the requirements for safe operation of the distribution network, conduct an economic evaluation of the configuration plan, and finally output the distributed photovoltaic absorption capacity and optimization plan with the best economic efficiency for the distribution network construction.

[0115] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0116] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0117] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0118] It should be noted that if the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can essentially be embodied in the form of a software product, or in other words, the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM) random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0119] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0120] The above are only embodiments of the present application and are not intended to limit the scope of protection of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the scope of protection of the present application.

Claims

1. A distribution network optimization evaluation method based on distributed photovoltaic absorption capacity, characterized in that: The method comprises: S1: Obtain real-time load data and resource data of each node in the distribution network; S2: Matching the real-time load data with the distributed photovoltaic output to calculate the absorption capacity of the distribution network, wherein the distributed photovoltaic output is obtained based on the resource data; S3: Determine whether the absorption capacity of the distribution network meets the requirements for safe operation of the power grid; S4: Combine the distributed photovoltaic output with the loads of various types of users to calculate the source-load matching degree of each user at the grid node; S5: Generate a transformation optimization plan for the distribution network based on the source-load matching degree; S6: Determine whether the transformation optimization plan meets the optimization goal of the optimal total project investment; S7: Output distribution network optimization plan to improve distributed photovoltaic absorption capacity.

2. The distribution network optimization evaluation method based on distributed photovoltaic absorption capacity according to claim 1 is characterized in that S2 include: Construct a distributed photovoltaic output model and calculate the distributed photovoltaic output coefficient P ij ; Output coefficient P based on distributed photovoltaic ij , calculate the absorption capacity of the distribution network.

3. The distribution network optimization evaluation method based on distributed photovoltaic absorption capacity according to claim 2 is characterized in that: In S2, the output model of distributed photovoltaics is expressed as follows: P i =η×S×I×[1-(T s -T i )] Where: P i is the photovoltaic output at time i; η is the photovoltaic panel power conversion efficiency; S is the photovoltaic panel installation area; I is the solar radiation intensity under standard conditions; T S is the standard ambient temperature, T i is the actual ambient temperature at time i; The output coefficient P of distributed photovoltaic is obtained by standardization ij : The calculation formula of the distribution network's absorption capacity is as follows: Where P PV is the consumption capacity of the jth node at time i, X ij is the real-time load of the j-th node at time i.

4. The distribution network optimization evaluation method based on distributed photovoltaic absorption capacity according to claim 1 is characterized in that S3 include: If the requirements are met, S4 is executed; if the requirements are not met, the capacity of the distributed photovoltaic equipment is optimized and the absorption capacity of the distribution network is recalculated, that is, after optimization, S2 is returned to execute until the requirements are met; Among them, the requirements for safe operation of the power grid include that for three-phase power supply of 10 kV and below in the distribution network, the allowable deviation of the power supply voltage is ±7% of the rated value; the requirements for safe operation of the power grid also include that the three-phase imbalance of the distribution network does not exceed 2%.

5. The distribution network optimization evaluation method based on distributed photovoltaic absorption capacity according to claim 1 is characterized in that S4 include: Classify each user of the power grid node and obtain their load data; According to the user load characteristics, the source-load matching degree of each user is calculated.

6. The distribution network optimization evaluation method based on distributed photovoltaic absorption capacity according to claim 1 is characterized in that: In S4, the calculation formula of source-load matching degree S is: S=s A ·s F Where: s A is the horizontal matching degree; s F is the vertical matching degree.

7. The distribution network optimization evaluation method based on distributed photovoltaic absorption capacity according to claim 1 is characterized in that S5 include: Sort the transformation optimization plans from large to small according to the source-load matching degree, and select the transformation optimization plan that meets the threshold requirements.

8. The distribution network optimization evaluation method based on distributed photovoltaic absorption capacity according to claim 1 is characterized in that S6 include: If the transformation optimization scheme meets the optimization goal of the optimal total project investment, that is, the total project investment of the transformation optimization scheme does not exceed the limit value, then execute S7; If the transformation optimization plan does not meet the optimization goal of the optimal total project investment, that is, the total project investment of the transformation optimization plan exceeds the limit, then optimize the matching of real-time load data and distributed photovoltaic output, recalculate the absorption capacity of the distribution network, and return to execute S2.

9. The distribution network optimization evaluation method based on distributed photovoltaic absorption capacity according to claim 8 is characterized in that S6 include: An optimization planning decision model with the best total project investment is constructed, and the optimal total project investment is calculated using the optimization planning decision model. The objective function of the optimization planning decision model is as follows: my C=C js +C sg Where: C represents the total investment of the project, C js represents the investment cost of distribution network construction equipment, C sg Represents the construction cost of the distribution network.

10. A distribution network optimization evaluation system based on distributed photovoltaic absorption capacity, characterized in that: The system comprises: A data acquisition module is used to obtain real-time load data and resource data of each node in the distribution network; An absorption capacity calculation module, used to match the real-time load data with the distributed photovoltaic output to calculate the absorption capacity of the distribution network, wherein the distributed photovoltaic output is obtained based on the resource data; Safety judgment module, used to judge whether the absorption capacity of the distribution network meets the requirements of grid operation safety; The matching degree calculation module is used to combine the distributed photovoltaic output with various types of user loads and calculate the source-load matching degree of each user at the grid node; The scheme generation module is used to generate the transformation optimization scheme of the distribution network based on the source-load matching degree; The optimal judgment module is used to judge whether the transformation optimization plan meets the optimization goal of the optimal total project investment; The solution output module is used to output distribution network optimization planning solutions to improve the distributed photovoltaic absorption capacity.

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