Method and system for evaluating photovoltaic bearing capacity of power distribution network

Abstract

The invention discloses a power distribution network photovoltaic bearing capacity evaluation method and system, and the method comprises the steps: collecting the multi-source heterogeneous data of a power grid, and building a power distribution network photovoltaic bearing capacity analysis boundary based on an electrical topological structure; according to the power grid multi-source heterogeneous data, a multi-level photovoltaic bearing capacity measuring and calculating model is constructed, in the multi-level photovoltaic bearing capacity measuring and calculating model, the boundary of the multi-level photovoltaic bearing capacity measuring and calculating model is determined according to the power distribution network photovoltaic bearing capacity analysis boundary, and key calculation parameters in the multi-level photovoltaic bearing capacity measuring and calculating model are calculated; according to the multi-level photovoltaic bearing capacity measuring and calculating model, calculating the distribution transformer-medium voltage line-main transformer three-level distributed photovoltaic bearing capacity under the two circles of variable topological structures by using a progressive algorithm; and calculating the three-level distributed photovoltaic bearing capacity under the three-loop transformer electrical topological structure by adopting a grouping comparison principle. According to the method, through a multi-level progressive algorithm, the precision and applicability of bearing capacity evaluation are improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power systems and new energy access, and relates to a power distribution network photovoltaic carrying capacity evaluation method and system based on electrical topology and administrative division. BACKGROUND

[0002] Distributed photovoltaic power generation has become an important part of building a clean, low-carbon, safe and efficient energy system. Distributed photovoltaic carrying capacity analysis refers to the precise evaluation, dynamic monitoring and intelligent decision-making of the carrying capacity of the power grid for distributed photovoltaic access through big data analysis, intelligent solving algorithm, combined with modern power grid planning theory and method. As a key infrastructure supporting the large-scale development of new energy, the power grid is highly dependent on the precise analysis and scientific evaluation of the carrying capacity of the power grid in terms of distributed photovoltaic large-scale access and safe and stable operation of the power grid. Therefore, carrying capacity analysis is a very important technical link in power system planning and operation. In actual work, due to the strict accuracy requirements of distributed photovoltaic access on power grid carrying capacity evaluation, the analysis method is difficult to accurately quantify, and simplifying the analysis may cause evaluation deviation, and detailed analysis may cause complex calculation, ultimately leading to limited photovoltaic access due to inaccurate carrying capacity evaluation, which has a huge impact on new energy development, power grid construction, energy transformation, etc.

[0003] In the field of power grid carrying capacity analysis, the existing technology uses static calculation or single index evaluation method, and the analysis scheme is mainly based on the past experience of planning personnel. With the continuous expansion of the scale of distributed photovoltaic access, relying only on manual and experience-based methods for carrying capacity analysis cannot meet the requirements of precise evaluation and dynamic monitoring. In the field of smart grid analysis, multi-source data fusion and edge computing technologies have been used in intelligent carrying capacity analysis systems, but the calculation method is not accurate enough and the hierarchical constraint conditions are not comprehensive enough. SUMMARY

[0004] The technical problem to be solved by the present application is that in the process of distributed photovoltaic carrying capacity analysis of the existing power distribution network, the model algorithm is not accurate enough, the hierarchical constraint conditions are not comprehensive enough, the complex electrical topology structure is difficult to process, and the administrative division dimension analysis is missing.

[0005] To solve the above technical problems, the present application provides a power distribution network photovoltaic carrying capacity evaluation method, which comprises:

[0006] Collecting power grid multi-source heterogeneous data, establishing a power distribution network photovoltaic carrying capacity analysis boundary based on electrical topology structure;

[0007] According to the multi-source heterogeneous data of the power grid, a multi-level photovoltaic carrying capacity calculation model is constructed, in which the boundary of the multi-level photovoltaic carrying capacity calculation model is determined according to the distribution network photovoltaic carrying capacity analysis boundary, and the key calculation parameters in the multi-level photovoltaic carrying capacity calculation model are calculated.

[0008] According to the multi-level photovoltaic carrying capacity calculation model, the distribution transformer-medium voltage line-main transformer three-level distributed photovoltaic carrying capacity under the two-loop variable topology structure is calculated by using the progressive algorithm.

[0009] The three-level distributed photovoltaic carrying capacity under the three-loop electrical topology structure is calculated by using the grouping comparison principle.

[0010] The foregoing method for evaluating the photovoltaic carrying capacity of a distribution network collects multi-source heterogeneous data of a power grid, and establishes a boundary for analyzing the photovoltaic carrying capacity of the distribution network based on an electrical topology structure, including:

[0011] The multi-source heterogeneous data of the power grid includes power grid basic data, operating state data, and photovoltaic power generation data.

[0012] The power grid basic data collects static topology information of electrical main wiring, equipment parameters, and connection relationships of substations from a PMS production management system, and obtains rated capacity, technical parameters, and operating state equipment account file data of substations, lines, and distribution transformers.

[0013] The operating state data collection obtains dynamic operating data of active power, load curve of substations, lines, and distribution transformers from a real-time monitoring system, and obtains time series data of typical daily load characteristics and seasonal variation rules from a historical database.

[0014] The photovoltaic power generation data includes statistical distributed photovoltaic installed capacity and power generation output data in a supply area.

[0015] The foregoing method for evaluating the photovoltaic carrying capacity of a distribution network, the boundary for analyzing the photovoltaic carrying capacity of the distribution network includes low-voltage side residential user distribution transformers, medium-voltage distribution lines, and 330kV, 220kV, 110kV, and 35kV voltage level substations.

[0016] The foregoing method for evaluating the photovoltaic carrying capacity of a distribution network, according to the equipment power transmission capacity and safe operation constraints in the multi-source heterogeneous data of the power grid, a multi-level photovoltaic carrying capacity calculation model is constructed, and a hierarchical modeling is performed according to the user-distribution transformer-line-main transformer membership relationship by using the principle of bottom-up and layer-by-layer tracing.

[0017] The foregoing method for evaluating the photovoltaic carrying capacity of a distribution network, the multi-level photovoltaic carrying capacity calculation model establishes a three-level model according to a photovoltaic power transmission path.

[0018] The distribution transformer hierarchical model takes the distribution transformer as the modeling object, and calculates the photovoltaic capacity that each distribution transformer can withstand when the photovoltaic reverse power is transmitted;

[0019] The line hierarchical model takes the medium-voltage distribution line as the modeling object, and calculates the ability of the line to transmit the photovoltaic reverse power;

[0020] The main transformer hierarchical model takes the transformer in the substation as the modeling object, and calculates the ability of the main transformer to transmit the photovoltaic power by boosting. The main transformer hierarchical carrying capacity is the minimum value of the total capacity of the main transformer and the sum of the carrying capacities of all outgoing lines. The key calculation parameters of the foregoing photovoltaic carrying capacity evaluation method for a power distribution network include:

[0021] The device power reverse sending allowable coefficient is calculated by the following formula:

[0022] (1)

[0023] Wherein, is the device power reverse sending allowable coefficient, is the device thermal stability basic coefficient, is the rated capacity of the device, is the current operating capacity of the device, is the ambient temperature, is the rated operating temperature, is the temperature correction coefficient;

[0024] The maximum output coefficient of the distributed photovoltaic is calculated by the following formula:

[0025] (2)

[0026] Wherein, is the maximum output coefficient of the distributed photovoltaic, is the local peak solar irradiance, is the standard test condition irradiance, is the inverter efficiency, is the cable transmission efficiency, is the shadow shielding correction coefficient, is the pollution correction coefficient;

[0027] The minimum daily net load of each level device is calculated by the following formula:

[0028] (3)

[0029] Wherein, is the minimum daily net load of the device, is the typical time, is the load power value at the t-th time, This represents the actual photovoltaic output at time t.

[0030] The simultaneous generation rate of distributed photovoltaic power generation is calculated using the following formula:

[0031] (4)

[0032] in, Simultaneity rate coefficient, For the actual output of the e-th photovoltaic unit at time t, Where N is the rated capacity and N is the number of statistical periods. The total actual photovoltaic output in the region at time t. Let t be the theoretical maximum output of photovoltaic power in the region at time t, and n be the total number of photovoltaic units in the region.

[0033] The aforementioned method for assessing the photovoltaic carrying capacity of a distribution network employs a progressive algorithm to calculate the distributed photovoltaic carrying capacity at three levels: distribution transformers, lines, and main transformers. This includes:

[0034] The formula for calculating the remaining available capacity of each distribution transformer is as follows:

[0035] (5)

[0036] in, Let i be the capacity that the i-th distribution transformer can connect to. Let be the allowable power backfeed coefficient of the i-th distribution transformer, obtained from formula (1). Let i be the rated capacity of the i-th distribution transformer. Let be the minimum net load of the i-th distribution transformer during the day, obtained from formula (3). The maximum output coefficient of distributed photovoltaic power within the power supply range of the i-th distribution transformer is obtained from formula (2). The simultaneity rate coefficient is obtained from formula (4);

[0037] The remaining available capacity at the distribution transformer level is obtained by summing the individual available capacities of each distribution transformer:

[0038] (6)

[0039] in, The remaining photovoltaic capacity at the distribution transformer level is available for connection. This represents the total number of distribution transformers.

[0040] The total photovoltaic carrying capacity of a distribution transformer is the sum of the remaining available grid-connected capacity and the already connected capacity.

[0041] (7)

[0042] in, This refers to the total load-bearing capacity of the distribution transformer. The photovoltaic installed capacity has been developed for the distribution transformers within the power supply area;

[0043] The remaining available capacity of the line itself is calculated using the following formula:

[0044] (8)

[0045] in, The remaining photovoltaic capacity that the j-th line can connect to is... Let be the allowable power backfeeding coefficient for the j-th line, obtained from formula (1). For the rated capacity of the j-th line, The minimum net load during the day for line j is obtained from formula (3). The maximum output coefficient of distributed photovoltaic power within the power supply range of the j-th line is obtained by formula (2);

[0046] The actual carrying capacity of the line level is taken as the smaller value according to the barrel effect principle, and is expressed as:

[0047] (9)

[0048] in, This represents the actual remaining connectable photovoltaic capacity at the j-th line level. The remaining photovoltaic capacity that the j-th line can connect to is... Let J be the set of all distribution transformers under the j-th line;

[0049] The total carrying capacity of the line is the sum of the remaining capacity and the developed capacity:

[0050] (10)

[0051] in, The total load-bearing capacity of the line, The photovoltaic capacity has been connected to this line and its distribution transformers;

[0052] The remaining available capacity of the main transformer itself is calculated using the following formula:

[0053] (11)

[0054] in, This represents the remaining photovoltaic capacity that the k-th main transformer can connect to. Let be the allowable factor for the backfeeding of the power of the k-th main transformer, obtained from formula (1). The rated capacity of the k-th main transformer is... The minimum net load of the k-th main transformer during the daytime is obtained from formula (3). The maximum output coefficient of distributed photovoltaic power within the power supply range of the k-th main transformer is obtained from formula (2);

[0055] The remaining available capacity at the substation level is constrained by the line level:

[0056] (12)

[0057] in, This refers to the remaining photovoltaic capacity that can be connected to the substation level. This refers to the number of main transformers in the substation. This refers to the number of outgoing circuits in the substation.

[0058] The total carrying capacity of the substation's service area is the sum of the remaining capacity and the developed capacity:

[0059] (13)

[0060] in, The total carrying capacity of distributed photovoltaic power generation in the substation supply area, The photovoltaic installed capacity has been developed for the substation supply area.

[0061] The aforementioned method for assessing the photovoltaic carrying capacity of a distribution network uses a group comparison principle to calculate the carrying capacity of the electrical topology of a three-circuit transformer, including:

[0062] First, calculate the bearing capacity of the high-voltage side (110kV), medium-voltage side (35kV), and low-voltage side (10kV) respectively;

[0063] The total carrying capacity of the 110kV substation is corrected using the following algorithm:

[0064] (14)

[0065] in, This refers to the remaining usable photovoltaic capacity after adjustments for the 110kV main transformer, including the actual usable capacity after the impact of photovoltaic access on the 35kV side. The original remaining photovoltaic capacity that can be connected to the 110kV main transformer. This refers to the photovoltaic power connected to the 35kV side.

[0066] Finally, the actual bearing capacity of the three-coil transformer was determined using the minimum value principle:

[0067] (15)

[0068] in, The actual load-bearing capacity of the three-ring transformer. , The calculated bearing capacity is for the medium-pressure side and the low-pressure side, respectively.

[0069] The aforementioned method for assessing the photovoltaic carrying capacity of a distribution network further aggregates carrying capacity according to the administrative region dimension. The method adopts a hierarchical aggregation approach, performing multi-dimensional hierarchical aggregation according to five levels: village, township, county, city, and province, to obtain carrying capacity data for each level.

[0070] The aforementioned method for assessing the photovoltaic carrying capacity of a distribution network also includes:

[0071] A multi-level distribution network photovoltaic carrying capacity dynamic evaluation platform with multiple time scales was constructed to calculate the total carrying capacity of the substation supply area and output the calculation results of the carrying capacity of the three levels of distribution transformers, lines and main transformers and the total carrying capacity of each level.

[0072] The aforementioned method for assessing the photovoltaic carrying capacity of a distribution network involves a multi-timescale dynamic assessment platform for the photovoltaic carrying capacity of a multi-level distribution network. This platform acquires real-time grid operation data through the grid operation monitoring center, including load curves, photovoltaic output, and key calculation parameters of equipment status. The multi-timescale carrying capacity calculation results include: short-term results, with a daily or weekly cycle; medium-term results, with a monthly or quarterly cycle; and long-term results, with an annual cycle.

[0073] The aforementioned method for assessing the photovoltaic carrying capacity of a distribution network further includes: verifying the consistency between the aggregated carrying capacity data and historical access data, and evaluating the reliability of the calculation results, including:

[0074] Check whether the calculated total load capacity of each level matches the historical maximum connected load. If the total load capacity is less than the historical actual connected load that has been operating safely, it means that the calculated load capacity value is too small. Correct the safety margin coefficient or photovoltaic output coefficient in the multi-level photovoltaic load capacity calculation model so that the error between the load capacity calculation result and the historical operating data is within the set value range.

[0075] A computer system includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described above.

[0076] A computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method described above. The beneficial effects achieved by this invention are: This invention provides a method for analyzing the carrying capacity of distributed photovoltaic (PV) power in a typical substation. Through a bottom-up, layer-by-layer tracing approach, it achieves accurate calculation of the PV carrying capacity of the distribution network, identifies bottlenecks in the auxiliary system, improves the grid's ability to absorb renewable energy, and promotes the optimization of the energy structure and the achievement of carbon peaking and carbon neutrality goals. It provides technical support for distributed PV project access decisions and grid planning and construction. Attached Figure Description

[0077] Figure 1This is a flowchart of the photovoltaic carrying capacity assessment method for distribution networks in Embodiment 1 of the present invention;

[0078] Figure 2 This is the main wiring diagram of the 110 kV substation in Embodiment 1 of the present invention;

[0079] Figure 3 This is a schematic diagram of the electrical topology hierarchy in Embodiment 1 of the present invention;

[0080] Figure 4 This is a flowchart of the photovoltaic load-bearing capacity calculation model in Embodiment 1 of the present invention;

[0081] Figure 5 This is a schematic diagram illustrating the calculation of the power supply relationship of the 110 kV three-circuit transformer in Embodiment 1 of the present invention;

[0082] Figure 6 This is a flowchart of the hierarchical early warning mechanism of the dynamic evaluation platform in Embodiment 1 of the present invention. Detailed Implementation

[0083] The present invention will be further illustrated below with reference to the accompanying drawings and specific examples. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the invention. After reading this invention, any modifications of the invention in various equivalent forms by those skilled in the art will fall within the scope defined by the appended claims.

[0084] Example 1

[0085] like Figure 1 As shown in the figure, this embodiment provides a method for assessing the photovoltaic carrying capacity of a distribution network, including the following steps:

[0086] S1: Collect multi-source heterogeneous data of the power grid and establish a boundary for analyzing the photovoltaic carrying capacity of the distribution network based on the electrical topology;

[0087] S2: Based on the multi-source heterogeneous data of the power grid, a multi-level photovoltaic carrying capacity calculation model is constructed. In the multi-level photovoltaic carrying capacity calculation model, the boundary of the multi-level photovoltaic carrying capacity calculation model is determined according to the photovoltaic carrying capacity analysis boundary of the distribution network, and the key calculation parameters in the multi-level photovoltaic carrying capacity calculation model are calculated.

[0088] S3: Based on the multi-level photovoltaic carrying capacity calculation model, the three-level distributed photovoltaic carrying capacity of the distribution transformer-medium voltage line-main transformer under the two-circuit transformer topology is calculated using a progressive algorithm;

[0089] S4: Since the progressive algorithm in step S3 is applicable to the calculation of distributed photovoltaic carrying capacity under the standard two-circuit transformer (110kV→10kV) topology, but cannot handle the calculation of distributed photovoltaic carrying capacity under the three-circuit transformer (110kV→35kV→10kV), in order to handle the multi-level power supply structure of complex topology that cannot be directly calculated in step S3, the group comparison principle is used to calculate the three-level distributed photovoltaic carrying capacity under complex electrical topology structures such as three-circuit transformers.

[0090] In step S1, multi-source heterogeneous data of the power grid are collected, and a boundary for analyzing the photovoltaic carrying capacity of the distribution network based on the electrical topology is established, including:

[0091] The multi-source heterogeneous data of the power grid includes three dimensions: power grid basic data, operation status data, and photovoltaic power generation data.

[0092] The power grid basic data is collected from the PMS (Production Management System) production management system, including substation electrical main wiring, equipment parameters, static topology information of connection relationships, rated capacity, technical parameters, and operating status of substations, lines, and distribution transformers, and integrated with equipment geographical coordinates, power supply area boundaries, and administrative division spatial location information.

[0093] The operational status data acquisition obtains dynamic operational data on active power and load curves of substations, lines, and distribution transformers from the real-time monitoring system, typical daily load characteristics and seasonal variation patterns from the historical database, and integrates user electricity consumption data and time-of-use load data from the electricity information acquisition system.

[0094] The photovoltaic power generation data includes the installed capacity and power output of distributed photovoltaic systems already in operation within the service area. Data formats include charts, text, JSON, and Excel spreadsheets, which are then processed to form a unified format.

[0095] In this embodiment, the main wiring diagram in the electrical topology is as follows: Figure 2 As shown, the substation's service area includes:

[0096] Substation hierarchy: 5 main transformers of 45MVA each; 110kV single busbar sectionalized connection with two incoming lines; 10kV single busbar sectionalized connection.

[0097] Line hierarchy: There are currently 24 outgoing lines, including 1 dedicated line, with a total line capacity of 214MVA, of which the dedicated line capacity is 9MVA;

[0098] Distribution transformer hierarchy: There are a total of 572 distribution transformers, of which 338 are dedicated transformers. The total capacity of the distribution transformers is 237MVA, of which the capacity of the dedicated transformers is 149MVA.

[0099] User level: A total of 23,200 low-voltage users are involved in the service area;

[0100] Photovoltaic situation: There are 945 photovoltaic users in the supply area, with a capacity of 58MW.

[0101] The external 110 kV power grid is connected to the substation's 110 kV single busbar segmented system via two incoming lines. The high-voltage side of the main transformer is connected to the 110 kV busbar, while the low-voltage side outgoing lines are connected to the 10 kV single busbar segmented system. 10 kV distribution lines are drawn from various sections of the busbar and connected to the busbar via outgoing switches to supply power to the designated area. The high-voltage side of the distribution transformer is connected to the 10 kV distribution lines, forming a tree-like power supply structure of "one line supporting multiple distribution transformers." The low-voltage side outputs 380 / 220 V to supply power to users. Distributed photovoltaic devices are connected to the low-voltage side user terminals, forming a progressively upward reverse power transmission path through the distribution transformer, distribution lines, and main transformer. The entire electrical topology follows a hierarchical relationship of "user-distribution transformer-medium voltage line-main transformer."

[0102] The boundary of the power distribution network carrying capacity analysis includes low-voltage residential user distribution transformers, medium-voltage distribution lines, and substations of various voltage levels (330 kV, 220 kV, 110 kV, and 35 kV), forming a complete electrical topology analysis system to ensure the comprehensiveness and accuracy of the carrying capacity analysis.

[0103] In step S2, a multi-level photovoltaic carrying capacity calculation model is established based on the equipment power transmission capacity and safe operation constraints in the multi-source heterogeneous data of the power grid. Adopting a bottom-up, layer-by-layer tracing principle, hierarchical modeling is performed according to the hierarchical relationship between users, distribution transformers, medium-voltage lines, and main transformers. The electrical topology hierarchy is as follows: Figure 3 As shown.

[0104] The multi-level photovoltaic load-bearing capacity calculation model establishes a three-layer model based on the photovoltaic power transmission path:

[0105] The distribution transformer hierarchy model takes the distribution transformer (low-voltage side 380 / 220V) as the modeling object and calculates the photovoltaic capacity that each distribution transformer can withstand during photovoltaic reverse power transmission.

[0106] The line hierarchy model takes medium-voltage distribution lines (10kV) as the modeling object and calculates the line's ability to transmit photovoltaic reverse power. While considering the line's own transmission capacity, it is constrained by the sum of the carrying capacities of all the lower-level distribution transformers.

[0107] The main transformer hierarchy model uses the substation's main transformer (110kV / 10kV) as the modeling object to calculate the main transformer's capacity to step up and transmit photovoltaic power. The main transformer hierarchy carrying capacity is taken as the minimum value of the sum of the main transformer's total capacity and the carrying capacity of all outgoing lines. Photovoltaic power is connected from the user side → stepped up by the distribution transformer → transmitted through the lines → collected by the main transformer.

[0108] In this embodiment, step S2 includes calculating the key calculation parameters, such as the power backfeed tolerance coefficient for each level of equipment, the maximum output coefficient of distributed photovoltaic power, the minimum net load during the day for each level of equipment, and the simultaneous generation rate of distributed photovoltaic power. The key calculation parameter tuning includes:

[0109] A1: Calculation of the allowable factor for reverse power transmission of equipment;

[0110] A2: Calculation of the maximum output coefficient of distributed photovoltaic power generation;

[0111] A3: Calculation of minimum net load for equipment at all levels during the day;

[0112] A4: Calculation of simultaneous rate of distributed photovoltaic power generation.

[0113] In step A1, the power backfeed tolerance coefficient for each level of equipment represents the safe carrying capacity of power equipment such as distribution transformers, lines, and main transformers during photovoltaic reverse power transmission. The equipment power backfeed tolerance coefficient comprehensively considers the equipment's thermal stability, insulation strength, and overload capacity. The formula for the equipment power backfeed tolerance coefficient is:

[0114] (1)

[0115] in This refers to the allowable factor for power backfeed in the equipment. This is the basic coefficient for the thermal stability of the equipment. For the rated capacity of the equipment, This represents the current operating capacity of the equipment. For ambient temperature, Rated operating temperature This is the temperature correction factor.

[0116] In step A2, the maximum output factor of distributed photovoltaic (PV) systems represents the degree of reduction in the theoretical maximum power generation capacity of a PV system under actual operating conditions. The maximum output factor of distributed PV is affected by multiple factors, including solar irradiance, ambient temperature, inverter efficiency, line loss, and shading. The formula for calculating the maximum output factor of distributed PV is:

[0117] (2)

[0118] in This represents the maximum output coefficient of distributed photovoltaic power. This represents the local peak solar irradiance. Irradiance under standard test conditions. For inverter efficiency, For cable transmission efficiency, Shadow occlusion correction factor, This is the pollution correction factor.

[0119] In step A3, the minimum net load of each level of equipment during the day refers to the minimum net power load borne by each level of power equipment during the photovoltaic output period, that is, the difference between the actual power load and the photovoltaic power generation output. The formula for predicting the minimum net load of each level of equipment during the day is as follows:

[0120] (3)

[0121] in, This represents the minimum net load for the equipment during the day. The typical time frame is 6:00-18:00. Let be the load power value at time t. The actual photovoltaic output value at time t; the minimum net load during the day can be calculated based on the local sunlight conditions during the photovoltaic output period, and the time accuracy can be minute-level, 15-minute-level, or hour-level data.

[0122] In step A4, the simultaneity rate of distributed photovoltaic (PV) power generation describes the probability that multiple distributed PV devices within a region will reach their maximum output at the same time. Since PV power generation is subject to randomness and fluctuations due to weather conditions, the simultaneity rate of distributed PV power generation is calculated using a statistical analysis method based on historical output data. The formula is:

[0123] (4)

[0124] in, Simultaneity rate coefficient, For the actual output of the e-th photovoltaic unit at time t, Where N is the rated capacity and N is the number of statistical periods. The total actual photovoltaic output in the region at time t. Let t be the theoretical maximum output of photovoltaic power in the region at time t, and n be the total number of photovoltaic units in the region.

[0125] Based on the above algorithm and actual substation operating data, a parameter tuning model was established. After data statistical analysis and engineering verification, the key calculation parameters were set as follows: Distribution transformer power backfeed tolerance coefficient. =0.8, Line power backfeed tolerance factor =0.8, Main transformer power backfeed tolerance factor =0.8, the maximum output coefficient of distributed photovoltaic power generation =0.7, Distributed photovoltaic power generation simulcast rate =1.0.

[0126] In step S3, a progressive algorithm is used to calculate the three-tiered distributed photovoltaic carrying capacity of the distribution transformer, transmission line, and main transformer. The process is as follows: Figure 4 As shown, it includes:

[0127] B1: Calculation of the load-bearing capacity of the distribution transformer layer;

[0128] B2: Line-level bearing capacity calculation;

[0129] B3: Calculation of the load-bearing capacity of the main transformer layer.

[0130] In step B1, the remaining available capacity of each distribution transformer is calculated using the following formula:

[0131] (5)

[0132] in, Let i be the capacity that the i-th distribution transformer can connect to. Let be the allowable power backflow factor of the i-th distribution transformer, obtained from formula (1), reflecting the reverse overload capacity of the equipment. Let i be the rated capacity of the i-th distribution transformer. Let be the minimum net load of the i-th distribution transformer during the day, obtained from formula (3). The maximum output coefficient of distributed photovoltaic power within the power supply range of the i-th distribution transformer is obtained from formula (2). The simultaneity coefficient is obtained from formula (4).

[0133] In step B1, the remaining available capacity at the distribution transformer level is obtained by summing the available capacities of each distribution transformer itself:

[0134] (6)

[0135] in, The remaining photovoltaic capacity at the distribution transformer level is available for connection. This represents the total number of distribution transformers.

[0136] In step B1, the total photovoltaic carrying capacity of the distribution transformer is the sum of the remaining available capacity and the already connected capacity:

[0137] (7)

[0138] in, This refers to the total load-bearing capacity of the distribution transformer. The photovoltaic installed capacity has been developed for the distribution transformers in the power supply area.

[0139] When calculating the carrying capacity at each level, it is necessary to properly handle the time-matching issue of existing photovoltaic (PV) installed capacity. Due to the dynamic nature of distributed PV installed capacity—for example, if the installed capacity is 500kW on the first day, 200kW is added on the second day, and more is added on the third day—the existing PV installed capacity exhibits a time-series variation. In carrying capacity calculations, there are two methods for determining the existing PV installed capacity: a static method, which uniformly selects the installed capacity at the end of the month within the calculation timescale as the benchmark; and a dynamic method, which determines the existing PV installed capacity based on the date corresponding to the selected minimum net load. For example, if the minimum net load occurs on a certain day, then the PV installed capacity of that day is used for carrying capacity calculation. The total system carrying capacity consists of the sum of the remaining connectable capacity and the existing PV installed capacity at the corresponding time, ensuring the time consistency and accuracy of the carrying capacity calculation results with the actual installed capacity.

[0140] Taking the No. 9 distribution transformer as an example, with a capacity of 360kVA and a typical active power of 4.60kW, the remaining connected capacity of the distribution transformer is 418kW.

[0141] In step B2, the transmission capacity of the line and the constraints of the downstream distribution transformer need to be considered. The remaining connectable capacity of the line itself is calculated using the following formula:

[0142] (8)

[0143] in, The remaining photovoltaic capacity that the j-th line can connect to is... Let be the allowable power backfeeding coefficient for the j-th line, obtained from formula (1). For the rated capacity of the j-th line, The minimum net load during the day for line j is obtained from formula (3). The maximum output coefficient of distributed photovoltaic power within the power supply range of the j-th line is obtained from formula (2). The simultaneity coefficient is obtained from formula (4).

[0144] Taking Line 2 as an example, its capacity is 9275kVA, and its active power at typical times is... The power rating is -1089kW, and considering the line's capacity is 80% heavy load, =0.8, then the remaining access capacity under this line is 9044.1kW.

[0145] In step B2, the actual carrying capacity of the line level is constrained by the capacity of the downstream distribution transformer. Following the principle of the weakest link, taking the smaller value ensures that the remaining connectable capacity of the line level will not exceed the actual carrying capacity of its downstream distribution transformer, expressed as:

[0146] (9)

[0147] in, This represents the actual remaining connectable photovoltaic capacity at the j-th line level. The remaining photovoltaic capacity that the j-th line can connect to is... Let J be the set of all distribution transformers under the j-th line.

[0148] In step B2, the total carrying capacity of the line is the sum of the remaining capacity and the developed capacity:

[0149] (10)

[0150] in, The total load-bearing capacity of the line, The photovoltaic capacity has been connected to this line and its distribution transformers.

[0151] A total of 11 public transformers and 7 private transformers are connected to Line 5. The sum of the remaining connectable capacity of the 11 public transformers is 8034kW, which is less than 11694kW. Therefore, the remaining connectable photovoltaic capacity of this line is limited by the distribution transformer link, and the actual value of the remaining connectable capacity at the line level is 8034kW.

[0152] The total remaining grid-connectable photovoltaic capacity of the 24 lines in the supply area is 44,559 kW. The details of each line are shown in Table 1.

[0153] Table 1: Calculation Results of Distributed Photovoltaic Bearing Capacity of 24 Lines in the 110kV Power Supply Area

[0154]

[0155] In step B3, following the same constraint optimization principle, the formula for calculating the remaining connectable capacity of the main transformer is:

[0156] (11)

[0157] in, This represents the remaining photovoltaic capacity that the k-th main transformer can connect to. Let be the allowable factor for the backfeeding of the power of the k-th main transformer, obtained from formula (1). The rated capacity of the k-th main transformer is... The minimum net load of the k-th main transformer during the daytime is obtained from formula (3). The maximum output coefficient of distributed photovoltaic power within the power supply range of the k-th main transformer is obtained from formula (2). The simultaneity coefficient is obtained from formula (4).

[0158] Taking the #2 main transformer as an example, with a capacity of 45000kVA, the active power at a typical moment (12:00 noon on January 1, 2024) is... The power output is 279kW, but the main transformer's capacity is 80% heavy load. =0.8, then the remaining connected capacity under main transformer #2 is 51827kW. According to the above calculation rules, the total remaining connected capacity of the two main transformers in the power supply area is 81822kW.

[0159] In step B3, the remaining available capacity at the substation level is constrained by the line level:

[0160] (12)

[0161] in, This refers to the remaining photovoltaic capacity that can be connected to the substation level. This refers to the number of main transformers in the substation. This refers to the number of outgoing circuits in the substation. This represents the actual remaining connectable photovoltaic capacity at the j-th line level.

[0162] There are 12 lines under the #2 main transformer, and the sum of the remaining access capacity at the line level is... The remaining photovoltaic (PV) capacity at the #2 main transformer level is 19065kW, which is less than 51827kW. Therefore, the remaining grid-connectable PV capacity at the #2 main transformer level is limited by the line connection, and the actual remaining grid-connectable capacity at the main transformer level is 19065kW. Based on this calculation, the remaining grid-connectable capacity at the #3 main transformer level is 25494kW. Therefore, the remaining grid-connectable distributed PV capacity within the 110kV substation's service area is 44559kW.

[0163] In step B3, the total carrying capacity of the substation's service area is the sum of the remaining capacity and the developed capacity:

[0164] (13)

[0165] in, The total carrying capacity of distributed photovoltaic power generation in the substation supply area, The photovoltaic installed capacity has been developed for the substation supply area.

[0166] In step S4, the three-level bearing capacity under the complex electrical topology is calculated using the group comparison principle, and a bearing capacity aggregation analysis is performed according to the administrative division dimension, including:

[0167] C1: The three-ring variable bearing capacity is calculated using the group comparison principle;

[0168] C2: And aggregate carrying capacity according to the administrative region dimension.

[0169] In this embodiment, in step C1, the complex electrical topology is a three-circuit transformer electrical topology. The 110 kV substation has a three-circuit transformer with a medium voltage side of 35 kV. The 110 kV main transformer of the substation simultaneously supplies power to the 10 kV low voltage line of the substation and to the 35 kV main transformer of the downstream 35 kV substation, forming a three-level power supply structure of high voltage side (110 kV), medium voltage side (35 kV), and low voltage side (10 kV).

[0170] The load-bearing capacity of the three-circuit transformer electrical topology is calculated using the group comparison principle. The load-bearing capacity of the 110kV high-voltage side is compared with the sum of the load-bearing capacities of the 35kV medium-voltage side and the 10kV low-voltage side. The actual usable load-bearing capacity is taken as the minimum value of the two.

[0171] The calculation steps are as follows: First, calculate the bearing capacity of the high-voltage side (110kV), the medium-voltage side (35kV), and the low-voltage side (10kV) respectively;

[0172] like Figure 5 As shown, in the three-circuit substation, the 110kV main transformer simultaneously supplies power to the 10kV low-voltage line on the substation's low-voltage side and to the downstream 35kV substation. If the carrying capacity of the 110kV side and the 35kV side are calculated separately and then directly statistically analyzed, the capacity of the 110kV main transformer would be counted twice. Therefore, when calculating the total carrying capacity of the 110kV substation, this double counting is corrected to avoid recalculating the main transformer capacity when statistically analyzing the total carrying capacity of the area.

[0173] Correction process for repeated calculations: When calculating the capacity of the 35kV main transformer on the medium-voltage side and the 110kV main transformer on the high-voltage side, a subtraction method is used to correct the main transformer capacity. When calculating the total carrying capacity of the 110kV substation, the already calculated capacity of the 35kV section of the main transformer needs to be deducted to ensure that the capacity of each main transformer segment is calculated only once when calculating the total carrying capacity of the area. The correction algorithm is as follows:

[0174] (14)

[0175] in, This refers to the remaining usable photovoltaic capacity after adjustments for the 110kV main transformer, including the actual usable capacity after the impact of photovoltaic access on the 35kV side. The original remaining photovoltaic capacity that can be connected to the 110kV main transformer. This refers to the photovoltaic access power on the 35kV side.

[0176] Finally, the actual bearing capacity of the three-coil transformer was determined using the minimum value principle:

[0177] (15)

[0178] in, The actual load-bearing capacity of the three-ring transformer. , The calculated bearing capacity is for the medium-pressure side and the low-pressure side, respectively.

[0179] During the aggregation of regional carrying capacity, a hierarchical statistical method is adopted for regions that include two-circuit and three-circuit substations: only the carrying capacity of the 10kV portion is calculated, while the carrying capacity of the 35kV portion is attributed to the superior two-circuit substation for aggregation; when multiple main transformer substations are involved, the duplicate calculation is deducted by substitution to ensure the accuracy of the total regional carrying capacity calculation.

[0180] For 220kV substations where the low-voltage side is directly 10kV, similar to a three-circuit transformer structure, the load-bearing capacity calculation method for three-circuit transformers described above shall be used.

[0181] The key to calculating the carrying capacity of a three-coil transformer topology lies in correctly identifying the power transfer relationship and constraint hierarchy between voltage levels. The integration of downstream photovoltaic capacity will consume the boost transmission capacity of the upstream main transformer, therefore, a corresponding deduction needs to be made in the carrying capacity calculation of the upstream main transformer. Simultaneously, the carrying capacity of a multi-level power supply system composed of three coil transformers is limited by the weakest link in the transmission path, reflecting the fundamental principle of the "weakest link" effect in power systems.

[0182] In step C2, during the carrying capacity aggregation process based on administrative regions, a hierarchical aggregation method is adopted, performing multi-dimensional hierarchical aggregation at five levels: village, township, county / district, prefecture / city, and province, to obtain carrying capacity data at each level. Village-level carrying capacity is the sum of the carrying capacities of distribution transformers within the village. Township-level carrying capacity requires handling the attribution of cross-boundary lines and distribution transformers, traversing all distribution transformers and lines in the corresponding township and taking the minimum value. At the county level and above, data is aggregated level by level according to the principle of minimizing the minimum value constrained by the lower level, achieving full coverage statistics from the equipment level to the administrative management level.

[0183] The aggregation of total carrying capacity in the substation power supply area involves summarizing the calculated remaining connectable capacity at the distribution transformer level, the line level, and the main transformer level. This aggregation includes listing the calculation results for each level, identifying outliers in the data at all three levels, checking for negative values, exceeding limits, or other abnormal data, and then verifying data consistency to ensure that the data for the same equipment is consistent across different levels. This ensures the accuracy and reliability of the aggregated results, ultimately forming the final usable total carrying capacity data for each level of distributed photovoltaic power supply in the substation power supply area.

[0184] Example 2

[0185] Based on the technical solution of Embodiment 1, it also includes:

[0186] S5: Construct a multi-level distribution network photovoltaic carrying capacity dynamic evaluation platform with multiple time scales to calculate the total carrying capacity of the substation supply area and output the calculation results of the three-level carrying capacity and the total carrying capacity.

[0187] In step S5, the multi-timescale dynamic assessment platform for photovoltaic carrying capacity of multi-level distribution networks acquires real-time grid operation data through the grid operation monitoring center, including key calculation parameters such as load curves, photovoltaic output, and equipment status. The multi-timescale carrying capacity calculation results include: short-term results, with a daily or weekly cycle, used for operation scheduling and real-time monitoring; medium-term results, with a monthly or quarterly cycle, used for grid connection planning and capacity reservation; and long-term results, with an annual cycle, used for grid planning and investment decisions. This achieves refined carrying capacity management and provides technical support for the orderly grid connection of distributed photovoltaics.

[0188] Taking a certain day as an example, the daily carrying capacity calculation uses the minimum net load of 4.60kW at 12:00 for distribution transformer No. 9. According to formula (5), the remaining access capacity for that day is 418kW. According to formulas (8) and (9), the remaining access capacity for line No. 2 is 9044.1kW. According to formula (11), the remaining access capacity for the day is 51827kW. The weekly carrying capacity calculation covers the minimum net load time of each day within a week, and selects the time point corresponding to the minimum value as the calculation benchmark. The quarterly and annual carrying capacity calculations take into account the impact of seasonal load changes and equipment maintenance plans, respectively, to ensure the accuracy of carrying capacity assessment at different time scales.

[0189] When calculating the line-level carrying capacity, the minimum net load of different distribution transformers occurs at different times. For example, one distribution transformer might have its minimum net load on May 30th, while another might have it on May 18th. Therefore, the minimum net load values ​​of all distribution transformers cannot be directly summed. A unified time scale is used in the line-level carrying capacity calculation process, i.e., a method of first summing and then taking the minimum value. First, the time scale is unified to the same calculation section, and the net load value of all distribution transformers under the line at each moment is calculated. Then, the net loads of all distribution transformers at the same moment are summed. Finally, the minimum value among all the summed values ​​is selected as the minimum net load of the line level. For example, if through traversal calculation, it is found that the sum of the net loads of all distribution transformers under the line at 14:00 on May 15th is the minimum value, then the summed result at that moment is used as the benchmark for the line-level carrying capacity calculation, improving the accuracy and safety of the calculation results.

[0190] According to formulas (3), (5), (8), and (11), the minimum net load during the day is a key parameter for calculating the remaining available capacity at each level. Identifying the minimum net load time means finding the time corresponding to the minimum net electricity load carried by the power equipment during the photovoltaic output period. The minimum net electricity load is the difference between the actual electricity load and the photovoltaic power generation output. The minimum net load time is the time with the greatest risk of photovoltaic backfeeding, and this is used as the calculation benchmark.

[0191] The multi-timescale dynamic evaluation platform includes a dynamic evaluation platform early warning module. This module establishes a three-color early warning system at both the equipment level and the region level. The equipment-level early warning system sets three warning standards based on the reverse power flow and load rate of the equipment. The green warning standard is that the high-voltage main transformer does not experience reverse power flow due to distributed photovoltaic power, or that the medium- and low-voltage main / distribution transformers and lines do not experience reverse power flow. The yellow warning standard is that the high-voltage main transformer or the medium- and low-voltage main / distribution transformer or line experiences reverse power flow but the reverse load rate is less than 80%. The red warning standard is that the high-voltage main transformer or the medium- and low-voltage main / distribution transformer or line experiences reverse power flow due to distributed photovoltaic power and the reverse load rate is greater than or equal to 80%. Simultaneously, the equipment-level early warning follows a hierarchical transmission principle. When the upper-level equipment (main transformer or line) is determined to be in a red warning state, the power supply range of the upper-level equipment... All lower-level equipment within the area is automatically identified as red alert, improving the consistency of hierarchical constraints in the early warning mechanism and the overall safety of the power grid operation. The regional early warning is managed in five administrative levels: village, township, county, city, and province. The early warning determination is based on the early warning status of distribution transformers within each level, as shown in Table 2. The green early warning standard is that there are no red alert distribution transformers within the administrative area and the proportion of yellow alert distribution transformers is less than 20%. The yellow early warning standard is that there are no red alert distribution transformers within the administrative area or there are red alert distribution transformers but the proportion is less than 10% and the total proportion of yellow and red alert distribution transformers is less than 70%. The red early warning standard is that the proportion of red alert distribution transformers within the administrative area is greater than or equal to 10% or the total proportion of yellow and red alert distribution transformers is greater than or equal to 70%.

[0192] Table 2: Regional Early Warning Judgment Criteria

[0193]

[0194] The dynamic assessment platform adopts a tiered early warning system, such as... Figure 6 As shown, the steps are as follows:

[0195] First, the capacity data of 220 / 330 kV main transformers under typical conditions is used as the starting point for analysis to assess the early warning level of 220 / 330 kV main transformers. When the assessment result is a red warning, the available capacity of the corresponding main transformer and its downstream main / distribution transformers is automatically set to 0, and the subsequent analysis process stops. When the assessment result is a green normal state, the process automatically proceeds to the next level of analysis, assessing the capacity of 110 / 66 kV and below main / distribution transformers level by level.

[0196] Then, the early warning levels of 110 / 66 kV and below main / distribution transformers are assessed step by step, and corresponding control measures are implemented based on the assessment results. When the assessment result is a red warning, the open capacity of the main / distribution transformer and its downstream main / distribution transformers is set to 0, and the processing of the corresponding branch's access application is terminated; the corresponding branch refers to the entire power supply path consisting of the red-warning main / distribution transformer and all its downstream lines and distribution transformers. When the assessment result is a yellow warning, a queuing early warning mechanism is established to manage and dynamically monitor the distributed photovoltaic power generation devices applying for access; when the assessment result is a green normal state, the grid connection application is accepted and enters the subsequent processing procedure.

[0197] Finally, during the grid connection application processing stage, the total distributed photovoltaic access capacity of the main / distribution transformers at this level shall not exceed the open capacity of the main / distribution transformers at the upper level, thus ensuring the safe operation of the power grid through a hierarchical constraint mechanism.

[0198] After the dynamic evaluation platform in this embodiment was put into use, the accuracy rate of load-bearing capacity analysis reached 91.2%, and the analysis efficiency was improved by 45.2%, providing technical support for the safe operation of the power grid and the orderly access of distributed photovoltaic power.

[0199] Example 3

[0200] Based on the technical solution of Embodiment 2, it also includes:

[0201] S6: Evaluate the calculation results data to assess the reliability of the calculation results.

[0202] In step S6, the result evaluation includes verifying the consistency between the aggregated carrying capacity data and historical access load data, and identifying the credibility of the calculation results, including:

[0203] Check whether the calculated total load capacity matches the historical maximum connected load. If the total load capacity is less than the historically actually safely operated connected load, it indicates that the calculated load capacity value is too small. In this case, it is necessary to adjust the key calculation parameters of the multi-level photovoltaic load capacity calculation model, including correcting the safety margin coefficient or photovoltaic output coefficient, so that the error between the load capacity calculation result and the historical operating data is within the set value range, so that the load capacity assessment is both safe and reliable and makes full use of grid resources.

[0204] Example 4

[0205] A computer system includes a memory, a processor, and a computer program stored in the memory, the processor executing the computer program to perform the steps of the methods described in Examples 1-3.

[0206] Example 5

[0207] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the methods described in Examples 1-3.

[0208] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0209] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0210] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0211] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for assessing the photovoltaic carrying capacity of a distribution network, characterized in that, include: Collect multi-source heterogeneous data from the power grid and establish a boundary for analyzing the photovoltaic carrying capacity of the distribution network based on the electrical topology. Based on the multi-source heterogeneous data of the power grid, a multi-level photovoltaic carrying capacity calculation model is constructed. In the multi-level photovoltaic carrying capacity calculation model, the boundary of the multi-level photovoltaic carrying capacity calculation model is determined according to the analysis boundary of the photovoltaic carrying capacity of the distribution network, and the key calculation parameters in the multi-level photovoltaic carrying capacity calculation model are calculated. Based on the multi-level photovoltaic carrying capacity calculation model, the three-level distributed photovoltaic carrying capacity of the distribution transformer-medium voltage line-main transformer under the two-circuit transformer topology is calculated using a progressive algorithm. The carrying capacity of a three-level distributed photovoltaic system under a three-circuit transformer electrical topology is calculated using the group comparison principle.

2. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 1, characterized in that, The steps for collecting multi-source heterogeneous data from the power grid and establishing the photovoltaic carrying capacity analysis boundary of the distribution network based on the electrical topology include: The multi-source heterogeneous data of the power grid includes basic power grid data, operating status data, and photovoltaic power generation data; The power grid basic data is collected from the PMS production management system, including substation electrical main wiring, equipment parameters, static topology information of connection relationships, and data on rated capacity, technical parameters, and operating status of substations, lines, and distribution transformers. The operational status data acquisition obtains dynamic operational data of active power and load curves of substations, lines, and distribution transformers from the real-time monitoring system, and time-series data of typical daily load characteristics and seasonal variation patterns from the historical database; The photovoltaic power generation data includes the installed capacity and power output of distributed photovoltaic systems already in operation within the power supply area.

3. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 1, characterized in that, The boundary of the power distribution network carrying capacity analysis includes low-voltage residential user distribution transformers, medium-voltage distribution lines, and substations of various voltage levels: 330 kV, 220 kV, 110 kV, and 35 kV.

4. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 1, characterized in that, A multi-level photovoltaic carrying capacity calculation model is established based on the equipment power transmission capacity and safe operation constraints in the multi-source heterogeneous data of the power grid, and hierarchical modeling is carried out according to the affiliation relationship of user-distribution transformer-line-main transformer.

5. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 4, characterized in that, The multi-level photovoltaic load-bearing capacity calculation model establishes a three-layer model based on the photovoltaic power transmission path: The distribution transformer hierarchy model takes distribution transformers as the modeling object and calculates the photovoltaic capacity that each distribution transformer can withstand during photovoltaic reverse power transmission. The line-level model uses medium-voltage distribution lines as the modeling object to calculate the line's ability to transmit photovoltaic reverse power. The main transformer hierarchy model takes the substation main transformer as the modeling object and calculates the main transformer's ability to step up and transmit photovoltaic power. The main transformer hierarchy bearing capacity is taken as the minimum value of the sum of the main transformer's total capacity and the bearing capacity of all outgoing lines.

6. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 5, characterized in that, The key calculation parameters include: The allowable factor for reverse power transmission of the equipment is calculated using the following formula: （1） in This refers to the allowable factor for power backfeed in the equipment. This is the basic coefficient for the thermal stability of the equipment. For the rated capacity of the equipment, This represents the current operating capacity of the equipment. For ambient temperature, Rated operating temperature This is a temperature correction factor; The maximum output factor of distributed photovoltaic power is calculated using the following formula: （2） in This represents the maximum output coefficient of distributed photovoltaic power. This represents the local peak solar irradiance. Irradiance under standard test conditions. For inverter efficiency, For cable transmission efficiency, Shadow occlusion correction factor, This is the pollution correction factor; The formula for predicting the minimum net load of equipment at all levels during the day is as follows: （3） in, This represents the minimum net load for the equipment during the day. This is a typical moment. Let be the load power value at time t. This represents the actual photovoltaic output at time t. The simultaneous generation rate of distributed photovoltaic power generation is calculated using the following formula: （4） in, Simultaneity rate coefficient, For the actual output of the e-th photovoltaic unit at time t, Where N is the rated capacity and N is the number of statistical periods. The total actual photovoltaic output in the region at time t. Let t be the theoretical maximum output of photovoltaic power in the region at time t, and n be the total number of photovoltaic units in the region.

7. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 6, characterized in that, A progressive algorithm is used to calculate the distributed photovoltaic carrying capacity of three levels: distribution transformer, transmission line, and main transformer, including: The formula for calculating the remaining available capacity of each distribution transformer is as follows: （5） in, Let i be the capacity that the i-th distribution transformer can connect to. Let be the allowable power backfeed coefficient of the i-th distribution transformer, obtained from formula (1). Let i be the rated capacity of the i-th distribution transformer. Let be the minimum net load of the i-th distribution transformer during the day, obtained from formula (3). The maximum output coefficient of distributed photovoltaic power within the power supply range of the i-th distribution transformer is obtained from formula (2). The simultaneity rate coefficient is obtained from formula (4); The remaining available capacity at the distribution transformer level is obtained by summing the individual available capacities of each distribution transformer: （6） in, The remaining photovoltaic capacity at the distribution transformer level is available for connection. This represents the total number of distribution transformers. The total photovoltaic carrying capacity of a distribution transformer is the sum of the remaining available grid-connected capacity and the already connected capacity. （7） in, This refers to the total load-bearing capacity of the distribution transformer. The photovoltaic installed capacity has been developed for the distribution transformers within the power supply area; The remaining available capacity of the line itself is calculated using the following formula: （8） in, The remaining photovoltaic capacity that the j-th line can connect to is... Let be the allowable power backfeeding coefficient for the j-th line, obtained from formula (1). For the rated capacity of the j-th line, The minimum net load during the day for line j is obtained from formula (3). The maximum output coefficient of distributed photovoltaic power within the power supply range of the j-th line is obtained by formula (2); The actual carrying capacity of the line level is taken as the smaller value according to the barrel effect principle, and is expressed as: （9） in, This represents the actual remaining connectable photovoltaic capacity at the j-th line level. The remaining photovoltaic capacity that the j-th line can connect to is... Let J be the set of all distribution transformers under the j-th line; The total carrying capacity of the line is the sum of the remaining capacity and the developed capacity: （10） in, The total load-bearing capacity of the line, The photovoltaic capacity has been connected to this line and its distribution transformers; The remaining available capacity of the main transformer itself is calculated using the following formula: （11） in, This represents the remaining photovoltaic capacity that the k-th main transformer can connect to. Let be the allowable factor for the backfeeding of the power of the k-th main transformer, obtained from formula (1). The rated capacity of the k-th main transformer is... The minimum net load of the k-th main transformer during the daytime is obtained from formula (3). The maximum output coefficient of distributed photovoltaic power within the power supply range of the k-th main transformer is obtained from formula (2); The remaining available capacity at the substation level is constrained by the line level: （12） in, This refers to the remaining photovoltaic capacity that can be connected to the substation level. This refers to the number of main transformers in the substation. This refers to the number of outgoing circuits in the substation. The total carrying capacity of the substation's service area is the sum of the remaining capacity and the developed capacity: （13） in, The total carrying capacity of distributed photovoltaic power generation in the substation supply area, The photovoltaic installed capacity has been developed for the substation supply area.

8. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 1, characterized in that, The load-bearing capacity of the three-circuit transformer electrical topology was calculated using the group comparison principle, including: Calculate the bearing capacity of the high-voltage side (110kV), medium-voltage side (35kV), and low-voltage side (10kV) respectively; The total bearing capacity of the 110kV substation is corrected, and the calculation formula is as follows: （14） in, This refers to the remaining usable photovoltaic capacity after adjustments for the 110kV main transformer, including the actual usable capacity after the impact of photovoltaic access on the 35kV side. The original remaining photovoltaic capacity that can be connected to the 110kV main transformer. This refers to the photovoltaic power connected to the 35kV side. The actual bearing capacity of the three-coil transformer is determined using the minimum value principle: （15） in, The actual load-bearing capacity of the three-ring transformer. , The calculated bearing capacity is for the medium-pressure side and the low-pressure side, respectively.

9. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 8, characterized in that, Then, carrying capacity is aggregated according to the administrative region dimension. The method is to adopt a hierarchical aggregation approach, and to perform multi-dimensional hierarchical aggregation according to five levels: village, township, county, city, and province, to obtain carrying capacity data for each level.

10. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 1, characterized in that, Also includes: A multi-level distribution network photovoltaic carrying capacity dynamic evaluation platform with multiple time scales was constructed to calculate the total carrying capacity of the substation supply area and output the calculation results of the carrying capacity of the three levels of distribution transformers, lines and main transformers and the total carrying capacity of each level.

11. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 10, characterized in that, The multi-timescale dynamic assessment platform for photovoltaic carrying capacity of multi-level distribution networks acquires real-time grid operation data through the grid operation monitoring center, including load curves, photovoltaic output, key calculation parameters of equipment status, and multi-timescale carrying capacity calculation results, including: short-term results, with a daily or weekly cycle; medium-term results, with a monthly or quarterly cycle; and long-term results, with an annual cycle.

12. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 10, characterized in that, Also includes: The consistency between the aggregated carrying capacity data and historical access data is verified, and the reliability of the calculation results is evaluated, including: Check whether the calculated total load capacity of each level matches the historical maximum connected load. If the total load capacity is less than the historical actual connected load that has been operating safely, it means that the calculated load capacity value is too small. Correct the safety margin coefficient or photovoltaic output coefficient in the multi-level photovoltaic load capacity calculation model so that the error between the load capacity calculation result and the historical operating data is within the set value range.

13. A computer system comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method as described in any one of claims 1-12.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method as described in any one of claims 1-12.

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