A power distribution network photovoltaic carrying capacity evaluation method and system

Abstract

The application discloses a kind of power distribution network photovoltaic carrying capacity evaluation method and system, comprising: collecting power grid multi-source heterogeneous data, establish the power distribution network photovoltaic carrying capacity analysis boundary based on electrical topology structure;According to the power grid multi-source heterogeneous data, construct multilevel photovoltaic carrying capacity measurement model, in the multilevel photovoltaic carrying capacity measurement model, according to the power distribution network photovoltaic carrying capacity analysis boundary determines the boundary of multilevel photovoltaic carrying capacity measurement model, and the key calculation parameter in multilevel photovoltaic carrying capacity measurement model is calculated;According to multilevel photovoltaic carrying capacity measurement model, the carrying capacity of three levels of distributed photovoltaic under the distribution transformer-medium voltage line-main transformer three-level of two circle variable topology structure is calculated using progressive algorithm;Adopt grouping comparison principle to calculate the carrying capacity of three levels of distributed photovoltaic under the three-level of three circle variable electrical topology structure.The method of the application improves the precision and applicability of carrying capacity evaluation by multilevel progressive algorithm.

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 from bottom to top 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, is the actual output value of the photovoltaic at the t th moment;

[0030] The distributed photovoltaic simultaneous rate, the calculation formula is:

[0031] (4)

[0032] wherein, is the simultaneous rate coefficient, is the actual output of the e th photovoltaic unit at t moment, is the rated capacity, N is the number of statistical period, is the total actual output of photovoltaic in the region at t moment, is the theoretical maximum output of photovoltaic in the region at t moment, n is the total number of photovoltaic units in the region.

[0033] The foregoing photovoltaic carrying capacity evaluation method of distribution network adopts progressive algorithm to calculate the three-level distributed photovoltaic carrying capacity of distribution transformer, line and main transformer, including:

[0034] The residual accessible capacity of each distribution transformer is calculated, and the formula is:

[0035] (5)

[0036] wherein, is the accessible capacity of the i th distribution transformer, is the power reverse sending allowable coefficient of the i th distribution transformer, which is obtained from formula (1), is the rated capacity of the i th distribution transformer, is the minimum net load of the i th distribution transformer during the day, which is obtained from formula (3), is the maximum output coefficient of distributed photovoltaic in the power supply range of the i th distribution transformer, which is obtained from formula (2), is the simultaneous rate coefficient, which is obtained from formula (4);

[0037] The residual accessible capacity of the distribution transformer level is obtained by summing the accessible capacity of each distribution transformer:

[0038] (6)

[0039] wherein, is the residual accessible photovoltaic capacity of the distribution transformer level, is the total number of distribution transformers;

[0040] The total photovoltaic carrying capacity of the distribution transformer is the sum of the residual accessible capacity and the accessed capacity:

[0041] (7)

[0042] wherein, For the total carrying capacity of distribution transformer, For the developed photovoltaic installed capacity of distribution transformer in the area;

[0043] The remaining accessible capacity of the line itself is calculated by the formula:

[0044] (8)

[0045] Wherein, The remaining accessible photovoltaic capacity of the jth line itself, The power reverse sending allowable coefficient of the jth line, obtained from formula (1), The rated capacity of the jth line, The minimum net load of the jth line during the day, obtained from formula (3), The maximum output coefficient of distributed photovoltaic in the power supply range of the jth line, obtained from formula (2);

[0046] The actual carrying capacity of the line level is the smaller value according to the principle of the barrel effect, which is represented by:

[0047] (9)

[0048] Wherein, The actual remaining accessible photovoltaic capacity of the jth line level, The remaining accessible photovoltaic capacity of the jth line itself, The set of all distribution transformers under the jth line;

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

[0050] (10)

[0051] Wherein, The total carrying capacity of the line, The accessible photovoltaic capacity of the line and the distribution transformer belonging to it;

[0052] The remaining accessible capacity of the main transformer itself is calculated by the formula:

[0053] (11)

[0054] Wherein, The remaining accessible photovoltaic capacity of the kth main transformer itself, The power reverse sending allowable coefficient of the kth main transformer, obtained from formula (1), The rated capacity of the kth main transformer, The minimum net load of the kth main transformer during the day, obtained from formula (3), The maximum output coefficient of the distributed photovoltaic in the power supply range of the kth main transformer is obtained from formula (2);

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

[0056] (12)

[0057] wherein, is the substation level remaining accessible photovoltaic capacity, is the number of main transformers in the substation, is the number of outgoing line loops of the substation;

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

[0059] (13)

[0060] wherein, is the total carrying capacity of the distributed photovoltaic in the substation supply area, is the developed photovoltaic installed capacity in the substation supply area.

[0061] The foregoing power distribution network photovoltaic carrying capacity evaluation method calculates the carrying capacity of the three-circle transformer substation topology by using the grouping comparison principle, comprising:

[0062] First, the carrying capacity of the high-voltage side 110kV, the medium-voltage side 35kV, and the low-voltage side 10kV is calculated respectively;

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

[0064] (14)

[0065] wherein, is the corrected remaining accessible photovoltaic capacity of the 110kV main transformer, including the actual available capacity after the influence of the 35kV side photovoltaic access, is the original remaining accessible photovoltaic capacity of the 110kV main transformer, is the 35kV side photovoltaic access power;

[0066] Finally, the minimum value principle is used to determine the actual carrying capacity of the three-circle transformer:

[0067] (15)

[0068] wherein, is the actual carrying capacity of the three-circle transformer, , are the calculated carrying capacities of the medium-voltage side and the low-voltage 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 1A flow chart of the power distribution network photovoltaic carrying capacity evaluation method in Embodiment 1 of the present application;

[0078] Figure 2 A 110-kilovolt electrical main wiring diagram in Embodiment 1 of the present application;

[0079] Figure 3 An electrical topology level schematic diagram in Embodiment 1 of the present application;

[0080] Figure 4 A photovoltaic carrying capacity measurement model flow chart in Embodiment 1 of the present application;

[0081] Figure 5 A 110-kilovolt three-circle transformer power supply relationship calculation schematic diagram in Embodiment 1 of the present application;

[0082] Figure 6 A dynamic evaluation platform hierarchical early warning mechanism flow chart in Embodiment 1 of the present application. DETAILED DESCRIPTION

[0083] The present application will be further illustrated below in conjunction with the accompanying drawings and specific examples, which should be understood as merely illustrating the present application and not limiting the scope of the present application, and after reading the present application, those skilled in the art can make various equivalent modifications to the present application, which all fall within the scope defined by the appended claims of the present application.

[0084] Embodiment 1

[0085] As shown in Figure 1 , the present embodiment provides a power distribution network photovoltaic carrying capacity evaluation method, comprising the following steps:

[0086] S1: Collecting power grid multi-source heterogeneous data, and establishing a power distribution network photovoltaic carrying capacity analysis boundary based on an electrical topology structure;

[0087] S2: According to the power grid multi-source heterogeneous data, constructing a multi-level photovoltaic carrying capacity measurement model, in which the boundary of the multi-level photovoltaic carrying capacity measurement model is determined according to the power distribution network photovoltaic carrying capacity analysis boundary, and the key calculation parameters in the multi-level photovoltaic carrying capacity measurement model are calculated;

[0088] S3: According to the multi-level photovoltaic carrying capacity measurement model, the distribution transformer-medium voltage line-main transformer three-level distributed photovoltaic carrying capacity under the two-circle transformer topology structure is calculated by using a progressive algorithm;

[0089] S4: Since the progressive algorithm of step S3 is applicable to the distributed photovoltaic carrying capacity calculation under the standard two-loop (110 kV→10 kV) topology, and cannot handle the three-loop (110 kV→35 kV→10 kV) distributed photovoltaic carrying capacity calculation, in order to handle the multi-level power supply structure of the complex topology which cannot be directly calculated by step S3, the grouping comparison principle is used to calculate the three-level distributed photovoltaic carrying capacity under the three-loop complex electrical topology structure.

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

[0091] The power grid multi-source heterogeneous data includes three dimensions of power grid basic data, operating state data and photovoltaic power generation data.

[0092] The power grid basic data collects the substation electrical main wiring, equipment parameters, connection relationship static topology information from the PMS (Production Management System) production management system, obtains the substation, line, distribution transformer rated capacity, technical parameters, operating state equipment account file data, and integrates the device geographic coordinates, power supply area boundary, administrative division attribution spatial location information.

[0093] The operating state data collection obtains the active power, load curve dynamic operating data of the substation, line and distribution transformer from the real-time monitoring system, obtains the typical daily load characteristics, seasonal variation law time series data from the historical database, and fuses the user power consumption data and time-sharing load data of the power consumption information collection system.

[0094] The photovoltaic power generation data includes the statistical distributed photovoltaic installed capacity and power generation output data in the supply area. The data formats include charts, text, JSON format, Excel table and the like, which are converted into a unified format through data processing.

[0095] In this embodiment, the main wiring diagram in the electrical topology structure is as shown in Figure 2 The substation supply area includes:

[0096] The substation level: 5 45MVA main transformers, 110kV single bus section wiring, two-way incoming line, 10kV single bus section wiring;

[0097] The line level: there are 24 outgoing lines in total, including 1 special line, and the total capacity of the line is 214MVA, including 9MVA of the special line capacity;

[0098] The distribution transformer level: there are 572 distribution transformers in total, including 338 special transformers, and the total capacity of the distribution transformers is 237MVA, including 149MVA of the special transformer capacity;

[0099] User level: 23,200 households of low-voltage users in the supply area;

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

[0101] The external 110-kilovolt power grid is connected to the substation 110-kilovolt single-bus section system through two incoming lines. The high-voltage side of the main transformer is connected to the 110-kilovolt bus, and the low-voltage side is connected to the 10-kilovolt single-bus section system. The 10-kilovolt distribution line is connected to the bus from each section, and after being connected to the bus through the outgoing switch, it supplies power to the power supply area. The high-voltage side of the distribution transformer is connected to the 10-kilovolt distribution line, forming a tree-shaped power supply structure of "one line with multiple distribution transformers". The low-voltage side outputs 380 / 220-volt voltage to supply power to users. The distributed photovoltaic device is connected to the low-voltage user end, and forms a step-by-step upward reverse power transmission path through the distribution transformer, distribution line, and main transformer. The entire electrical topology is a hierarchical relationship of "user-distribution transformer-medium-voltage line-main transformer".

[0102] The distribution network carrying capacity analysis boundary includes low-voltage residential user distribution transformers, medium-voltage distribution lines, and 330-kilovolt, 220-kilovolt, 110-kilovolt, and 35-kilovolt voltage level substations, 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 according to the device power transmission capacity and safe operation constraints in the power grid multi-source heterogeneous data. The principle of bottom-up and layer-by-layer tracing is adopted, and hierarchical modeling is performed according to the user-distribution transformer-medium-voltage line-main transformer hierarchical relationship. The electrical topology hierarchy is shown in Figure 3 .

[0104] The multi-level photovoltaic carrying capacity calculation model establishes a three-layer model according to the photovoltaic power transmission path:

[0105] The distribution transformer hierarchical model takes the distribution transformer (low-voltage 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 hierarchical model takes the medium-voltage distribution line (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 also subject to the constraint of the sum of the carrying capacities of all distribution transformers at the lower level;

[0107] The main transformer hierarchical model takes the substation main transformer (110 kV / 10 kV) as the modeling object, and calculates the ability of the main transformer to transmit photovoltaic power through voltage transformation. The main transformer level 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. Photovoltaic power is accessed from the user side, is boosted through the distribution transformer, is transmitted through the line, and is collected at the main transformer.

[0108] In this embodiment, in step S2, the key calculation parameters include the power reverse transmission allowable coefficient calculation of each level of equipment, the maximum output coefficient calculation of distributed photovoltaic power, the daily minimum net load calculation of each level of equipment, and the distributed photovoltaic power generation simultaneous rate calculation. The key calculation parameter setting includes:

[0109] A1: Equipment power reverse transmission allowable coefficient calculation;

[0110] A2: Distributed photovoltaic maximum output coefficient calculation;

[0111] A3: Daily minimum net load calculation of each level of equipment;

[0112] A4: Distributed photovoltaic power generation simultaneous rate calculation.

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

[0114] (1)

[0115] wherein is the power reverse transmission allowable coefficient of the equipment, is the thermal stability base coefficient of the equipment, is the rated capacity of the equipment, is the current operating capacity of the equipment, is the ambient temperature, is the rated operating temperature, is the temperature correction coefficient.

[0116] In step A2, the distributed photovoltaic maximum output coefficient represents the degree of reduction of the photovoltaic power generation system relative to the theoretical maximum power generation capacity under actual operating conditions. The distributed photovoltaic maximum output coefficient is influenced by multiple factors such as solar irradiance, ambient temperature, inverter efficiency, line loss, and shadow shielding. The formula for the distributed photovoltaic maximum output coefficient is:

[0117] (2)

[0118] wherein is the distributed photovoltaic maximum output coefficient, is the local peak solar irradiance, is the standard test condition irradiance, is the inverter efficiency, is the cable transmission efficiency, is the shadow shading correction factor, is the soiling correction factor.

[0119] In step A3, the daily minimum net load of each level of equipment refers to the minimum net power load borne by each level of power equipment during the photovoltaic output period, i.e., the difference between the actual power load and the photovoltaic power output. The daily minimum net load of each level of equipment is predicted, and the calculation formula is:

[0120] (3)

[0121] wherein, is the daily minimum net load of equipment, is the typical time period of 6:00-18:00, is the load power value at the t time, is the actual photovoltaic output value at the t time. The daily minimum net load can be calculated according to the local lighting conditions during the photovoltaic output period, and the time accuracy can adopt minute-level, 15-minute-level or hour-level data.

[0122] In step A4, the simultaneous rate of distributed photovoltaic power generation describes the probability that multiple distributed photovoltaic devices in the region reach the maximum output at the same time. Since photovoltaic power generation is affected by weather conditions and has randomness and volatility, the simultaneous rate of distributed photovoltaic power generation is calculated by using a statistical analysis method based on historical output data, and the formula is:

[0123] (4)

[0124] wherein, is the simultaneous rate coefficient, is the actual output of the e photovoltaic unit at the t time, is the rated capacity, and N is the number of statistical periods, is the total actual output of photovoltaic power in the region at the t time, is the theoretical maximum output of photovoltaic power in the region at the t time, and n is the total number of photovoltaic units in the region.

[0125] Based on the above algorithm, a parameter setting model is established according to the actual operation data of the substation. Through data statistical analysis and engineering verification, the key calculation parameters are set as follows: the power reverse feeding allowable coefficient of the distribution transformer =0.8, the line power reverse feeding allowable coefficient =0.8, the main transformer power reverse feeding allowable coefficient =0.8, and the maximum output coefficient of distributed photovoltaic power =0.7, distributed photovoltaic power generation simultaneous rate =1.0.

[0126] In step S3, the three-level distributed photovoltaic carrying capacity of distribution transformers, lines, and main transformers is calculated using a progressive algorithm, as shown in the flowchart of Figure 4 , which includes:

[0127] B1: Distribution transformer level carrying capacity calculation;

[0128] B2: Line level carrying capacity calculation;

[0129] B3: Main transformer level carrying capacity calculation.

[0130] In step B1, the remaining accessible capacity of each distribution transformer itself is calculated, and the formula is:

[0131] (5)

[0132] wherein, is the accessible capacity of the i-th distribution transformer itself, is the power reverse sending allowable coefficient of the i-th distribution transformer, obtained from formula (1), reflecting the reverse overload capacity of the equipment, is the rated capacity of the i-th distribution transformer, is the minimum net load of the i-th distribution transformer during the day, obtained from formula (3), is the maximum output coefficient of distributed photovoltaic power in the power supply range of the i-th distribution transformer, obtained from formula (2), is the simultaneous rate coefficient, obtained from formula (4).

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

[0134] (6)

[0135] wherein, is the remaining accessible photovoltaic capacity of the distribution transformer level, is the total number of distribution transformers.

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

[0137] (7)

[0138] wherein, is the total carrying capacity of the distribution transformer, is the developed photovoltaic installed capacity of the distribution transformer in the supply area.

[0139] In the calculation of the carrying capacity of each level, the time matching problem of the existing photovoltaic installed capacity needs to be reasonably handled. Due to the dynamic change characteristics of distributed photovoltaic installed capacity, such as 500 kW of first-day installed capacity, 200 kW of second-day additional installed capacity, and third-day continuous additional installed capacity, the existing photovoltaic installed capacity presents the characteristics of time sequence change. In the calculation of the carrying capacity, there are two ways to value the existing photovoltaic installed capacity: one is a static way, that is, uniformly selecting the installed capacity at the end of the month within the calculation time scale as the reference. The other is a dynamic value way, that is, determining the existing photovoltaic installed capacity according to the date corresponding to the selected minimum net load moment, such as the minimum net load appearing on a certain day, and the photovoltaic installed capacity on that day is used for carrying capacity calculation. The total carrying capacity of the system is composed of the sum of the remaining accessible capacity and the existing photovoltaic installed capacity at the corresponding moment, which ensures the time consistency and accuracy of the calculation results and the actual installed capacity.

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

[0141] In step B2, the line transmission capacity and the lower-level distribution transformer constraint need to be considered, and the remaining accessible capacity of the line itself is calculated by the formula:

[0142] (8)

[0143] Wherein, is the remaining accessible photovoltaic capacity of the jth line itself, is the power reverse sending allowable coefficient of the jth line, which is obtained from formula (1), is the rated capacity of the jth line, is the daily minimum net load of the jth line, which is obtained from formula (3), is the maximum output coefficient of distributed photovoltaic in the power supply range of the jth line, which is obtained from formula (2), is the simultaneous rate coefficient, which is obtained from formula (4).

[0144] Taking line No. 2 as an example, the capacity is 9275 kVA, and the typical moment active power is-1089 kW, considering that the line can withstand 80% overload, =0.8, then the remaining access capacity of the line is 9044.1 kW.

[0145] In step B2, the actual carrying capacity of the line level is restricted by the capacity of the lower-level distribution transformer, and the smaller value is taken according to the principle of the barrel effect, which can ensure that the remaining accessible capacity of the line level will not exceed the actual carrying capacity of the lower-level distribution transformer, which is represented as:

[0146] (9)

[0147] wherein, is the actual remaining accessible photovoltaic capacity of the jth line level, is the remaining accessible photovoltaic capacity of the jth line itself, is the set of all distribution transformers under the jth line.

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

[0149] (10)

[0150] wherein, is the total line carrying capacity, is the accessible photovoltaic capacity of the line and the distribution transformers belonging to it.

[0151] There are 11 public transformers and 7 special transformers under line No. 5, and the sum of the remaining accessible capacity of the 11 public transformers is 8034 kW, which is less than 11694 kW, so the remaining photovoltaic accessible capacity of the line is limited by the distribution transformer link, and the actual value of the line level remaining accessible capacity is 8034 kW.

[0152] The sum of the remaining photovoltaic accessible capacity of the 24 lines in the supply area is 44559 kW, and the situation of each line is shown in Table 1.

[0153] Table 1: Calculation results of distributed photovoltaic carrying capacity of 24 lines in 110 kV supply area

[0154]

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

[0156] (11)

[0157] wherein, is the remaining accessible photovoltaic capacity of the kth main transformer itself, is the power reverse sending allowable coefficient of the kth main transformer, obtained from formula (1), is the rated capacity of the kth main transformer, is the minimum net load of the kth main transformer during the day, obtained from formula (3), is the maximum output coefficient of distributed photovoltaic in the power supply range of the kth main transformer, obtained from formula (2), is the simultaneous rate coefficient, obtained from formula (4).

[0158] Take #2 main transformer as an example, the capacity is 45000kVA, the active power at a typical moment (January 1, 2024, 12:00) is 279kW, since the main transformer bearing capacity is 80% overload, =0.8, the remaining access capacity under #2 main transformer is 51827kW. According to the above calculation rule, the total remaining access capacity of the two main transformers in the supply area is 81822kW.

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

[0160] (12)

[0161] Wherein, is the substation level remaining accessible photovoltaic capacity, is the number of main transformers in the substation, is the number of substation outgoing lines, is the jth line level actual remaining accessible photovoltaic capacity.

[0162] #2 main transformer has a total of 12 lines, the sum of line level remaining access capacity is 19065kW, which is less than 51827kW, so the remaining photovoltaic accessible capacity of #2 main transformer is limited by the line link, and the actual value of the main transformer level remaining accessible capacity is 19065kW. According to this algorithm, the #3 main transformer level remaining accessible capacity is 25494kW. Therefore, the distributed photovoltaic remaining accessible capacity in the 110kV substation supply area is 44559kW.

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

[0164] (13)

[0165] Wherein, is the total carrying capacity of the substation supply area distributed photovoltaic, is the developed photovoltaic installed capacity of the substation supply area.

[0166] In step S4, the three-level carrying capacity under complex electrical topology is calculated by using the grouping comparison principle, and the carrying capacity is aggregated according to the administrative division dimension, including:

[0167] C1: Calculate the three-circle transformer carrying capacity by using the grouping comparison principle;

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

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

[0170] The carrying capacity of the three-loop substation electrical topology is calculated using the grouping comparison principle. The carrying capacity of the high voltage side 110kV is compared with the sum of the carrying capacities of the medium voltage side 35kV and the low voltage side 10kV. The actual available carrying capacity is the minimum value of the two.

[0171] The calculation steps are as follows: first, calculate the carrying capacity of the high voltage side 110kV, the medium voltage side 35kV, and the low voltage side 10kV respectively;

[0172] As shown in Figure 5 , in the three-loop substation, the 110kV main transformer simultaneously supplies power to the low voltage side 10kV line of the substation and the lower-level 35kV substation. If the carrying capacity of the 110kV side and the carrying capacity of the 35kV side are calculated separately and then directly counted, the capacity of the 110kV main transformer will be calculated repeatedly. When calculating the total carrying capacity of the 110kV substation, the repeated calculation is corrected to avoid repeated calculation of the main transformer capacity when counting the total carrying capacity of the region.

[0173] The repeated calculation correction process is as follows: when counting the main transformer capacity of the medium voltage side 35kV and the high voltage side 110kV, the main transformer capacity is corrected by using the subtraction method. When calculating the total carrying capacity of the 110kV substation, the main transformer capacity of the 35kV part that has already been calculated needs to be deducted to ensure that each section of the main transformer capacity is calculated only once when counting the total carrying capacity of the region. The correction algorithm is:

[0174] (14)

[0175] wherein, is the remaining accessible photovoltaic capacity of the 110kV main transformer after correction, including the actual available capacity after the influence of the 35kV side photovoltaic access, is the original remaining accessible photovoltaic capacity of the 110kV main transformer, is the 35kV side photovoltaic access power.

[0176] Finally, the actual carrying capacity of the three-loop substation is determined using the minimum value principle:

[0177] (15)

[0178] wherein, is the actual carrying capacity of the three-loop substation, , The calculated bearing capacity is on the medium voltage side and the low voltage side, respectively.

[0179] In the regional bearing capacity aggregation process, for the regions containing two circle transformers and three circle transformers, a hierarchical statistical method is adopted: only the bearing capacity of the 10kV part is calculated, and the bearing capacity of the 35kV part is attributed to the upper two circle transformers for aggregation; when multiple main transformer substations are involved, the part of repeated calculation is deducted by substitution subtraction to ensure the accuracy of the total regional bearing capacity calculation.

[0180] For the 220kV substation with a low voltage side directly connected to a 10kV side, similar to the three circle transformer structure, the bearing capacity is calculated according to the above-mentioned three circle transformer bearing capacity calculation method.

[0181] The key to the bearing capacity calculation of the three circle transformer topology structure lies in the correct identification of the power transmission relationship and the constraint level relationship between voltage levels. The capacity of the lower level photovoltaic access will occupy the step-up transmission capacity of the upper level main transformer, so the corresponding deduction needs to be made in the bearing capacity calculation of the upper level main transformer. At the same time, the bearing capacity of the multi-level power supply system composed of three circle transformers is limited by the weakest link in the transmission path, which embodies the basic principle of the wood barrel effect of the power system.

[0182] In step C2, in the bearing capacity aggregation process according to the administrative region dimension, a hierarchical aggregation method is adopted, and multi-dimensional hierarchical aggregation is carried out according to the village, township, county, city, and province five levels to obtain the bearing capacity data of each level. The village-level bearing capacity is the sum of the bearing capacity of the distribution transformers within the village. The township-level needs to handle the attribution problem of cross-border lines and distribution transformers, and the minimum value of all distribution transformers and line bearing capacities in the corresponding township is taken. The county level and above are aggregated level by level according to the minimum constraint principle, realizing full coverage statistics from the equipment level to the administrative level.

[0183] The total bearing capacity aggregation of the substation supply area is to aggregate the calculated remaining accessible capacity of the distribution transformer level, the remaining accessible capacity of the line level, and the remaining accessible capacity of the main transformer level. The aggregation includes listing the calculation results of each level, identifying abnormal values after listing the table, checking whether there are negative values, out-of-limit values, and other abnormal data, and then verifying the data consistency to ensure that the data of the same device in different level statistics are consistent, ensuring the accuracy and reliability of the aggregation results, forming the final available total bearing capacity data of each level of the substation supply area distributed photovoltaic.

[0184] Embodiment 2

[0185] On the basis of the technical scheme of embodiment 1, further comprising:

[0186] S5: Construct a multi-time scale dynamic evaluation platform for multi-level distribution network photovoltaic carrying capacity, which is used to calculate the total carrying capacity of the substation supply area and output the calculation results of three-level carrying capacity and total carrying capacity.

[0187] In step S5, the multi-time scale dynamic evaluation platform for multi-level distribution network photovoltaic carrying capacity obtains the grid operation data in real time through the grid operation monitoring center, including load curve, photovoltaic output, equipment state and other key calculation parameters. The multi-time scale carrying capacity calculation results include: short-term results, with daily or weekly cycle, for operation scheduling and real-time monitoring; medium-term results, with monthly or quarterly cycle, for access planning and capacity reservation; long-term results, with annual cycle, for grid planning and investment decision-making, realizing fine carrying capacity management and technical support for orderly access of distributed photovoltaic.

[0188] The daily carrying capacity calculation takes a certain day as an example. The minimum net load of No. 9 distribution transformer at 12:00 is 4.60kW, and the remaining access capacity of 418kW is calculated according to formula (5); the remaining access capacity of No. 2 line is 9044.1kW according to formulas (8) and (9); and the remaining access capacity of #2 main transformer is 51827kW according to formula (11). The weekly carrying capacity calculation traverses the minimum net load time of each day in a week, and selects the minimum value corresponding to the time point as the calculation reference. The quarterly and annual carrying capacity calculations consider seasonal load changes and equipment maintenance plans respectively to ensure the accuracy of carrying capacity evaluation at different time scales.

[0189] In the calculation of line-level carrying capacity, the minimum net load of different distribution transformers appears at different times, for example, a distribution transformer may appear on May 30, and another distribution transformer may appear on May 18, so the minimum net load values of each distribution transformer cannot be directly added. In the calculation process of line-level carrying capacity, a unified time scale is adopted, that is, the calculation method of adding first 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 time is calculated, then the net loads of each distribution transformer at the same time are added and summed, and finally the minimum value among all the added values at all times is selected as the minimum net load of the line level. For example, through traversal calculation, it is found that the cumulative sum of the net loads of all distribution transformers under the line at 14:00 on May 15 is the minimum value, so the cumulative result at that time is taken as the reference for the calculation of the line-level carrying capacity, which improves the accuracy and safety of the calculation result.

[0190] According to the formula (3), (5), (8), (11), it can be seen that the minimum net load during the day is a key parameter for calculating the remaining accessible capacity of each level. Identifying the minimum net load time is to find the time corresponding to the minimum net power load carried by the power equipment in the photovoltaic output period, and the minimum net power load is the difference between the actual power load and the photovoltaic power output. The minimum net load time is the time when the photovoltaic reverse sending risk is the largest, which is taken as the calculation reference.

[0191] In the multi-time scale dynamic evaluation platform, a dynamic evaluation platform early warning module is included, three-color early warning at two levels of device level and regional level is established in the dynamic evaluation platform early warning module, three-level early warning standards are set according to the device reverse sending condition and load rate for the device level early warning, the green early warning standard is that the high-voltage main transformer is not caused by reverse sending due to distributed photovoltaic or the reverse sending does not occur in the medium and low-voltage main / distribution transformer and line, the yellow early warning standard is that the reverse load rate is less than 80% when the reverse sending occurs in the high-voltage main transformer or the medium and low-voltage main / distribution transformer or the line, and the red early warning standard is that the reverse sending power flow is caused by the distributed photovoltaic and the reverse load rate is greater than or equal to 80% when the high-voltage main transformer or the medium and low-voltage main / distribution transformer or the line, and the device level early warning follows the hierarchical conduction principle, when the upper-level device (main transformer or line) is determined as red early warning, all lower-level devices in the power supply range of the upper-level device are automatically determined as red early warning, so as to improve the hierarchical consistency of the early warning mechanism and the integrity of the safe operation of the power grid; the regional level early warning is managed by hierarchical early warning according to five administrative levels of village, township, county, city and province, and the early warning determination is based on the early warning state of the distribution transformer in each level range, as shown in Table 2, the green early warning standard is that there is no red early warning distribution transformer in the administrative division range and the proportion of yellow early warning distribution transformer is less than 20%, the yellow early warning standard is that there is no red early warning distribution transformer in the administrative division range or the proportion of red early warning distribution transformer is less than 10% and the total proportion of yellow and red early warning distribution transformers is less than 70%, and the red early warning standard is that the proportion of red early warning distribution transformer is greater than or equal to 10% or the total proportion of yellow and red early warning distribution transformers is greater than or equal to 70% in the administrative division range.

[0192] Table 2: Regional level early warning determination standard table

[0193]

[0194] The dynamic evaluation platform adopts hierarchical early warning, as shown in Table 2, the steps are as follows: Figure 6

[0195] ​Firstly, the carrying capacity data of 220 / 330 kV main transformer at typical time is called as the starting point of analysis, and the warning level of 220 / 330 kV main transformer is evaluated. When the evaluation result is red warning, the openable capacity of the corresponding main transformer and the lower main / distribution transformer can be automatically set to 0, and the subsequent analysis process is stopped; when the evaluation result is green normal state, the next level of analysis is automatically entered, and the carrying capacity of 110 / 66 kV and below main / distribution transformer is evaluated step by step.

[0196] Then, the warning level of 110 / 66 kV and below main / distribution transformer is evaluated step by step, and the corresponding control measures are executed according to the evaluation result. When the evaluation result is red warning, the openable capacity of the main / distribution transformer and the lower main / distribution transformer is set to 0, and the access application processing of the corresponding branch is terminated; the corresponding branch refers to the entire power supply path composed of the red warning main transformer / distribution transformer and all lines and distribution transformers at the lower level. When the evaluation result is yellow warning, a queuing warning mechanism is established to manage and dynamically monitor the distributed photovoltaic power generation devices applying for access; when the evaluation result is green normal state, the grid connection application is accepted and the subsequent processing flow is entered.

[0197] Finally, in the grid connection application processing stage, the sum of the distributed photovoltaic access capacity of the main / distribution transformer at the current level does not exceed the openable capacity of the main / distribution transformer at the upper level, and the hierarchical constraint mechanism is used to ensure the safe operation of the power grid.

[0198] After the dynamic evaluation platform in the embodiment is put into use, the accuracy rate of carrying capacity analysis reaches 91.2%, and the analysis efficiency is improved by 45.2%, which provides technical support for the safe operation of the power grid and the orderly access of distributed photovoltaic.

[0199] Embodiment 3

[0200] On the basis of the technical scheme of embodiment 2, the method further comprises:

[0201] S6: evaluating the calculation result data to evaluate the credibility of the calculation result.

[0202] In step S6, the result evaluation includes consistency verification of the aggregated carrying capacity data and the historical access load data to identify the credibility of the calculation result, including:

[0203] It is checked whether the total carrying capacity calculated is matched with the historical maximum access load. If the total carrying capacity is less than the historical actual access amount safely operated, it indicates that the carrying capacity calculation value is too small, and the key calculation parameters of the multi-level photovoltaic carrying capacity calculation model need to be adjusted, including correcting the safety margin coefficient or the photovoltaic output coefficient, so that the error between the carrying capacity calculation result and the historical operation data is within the set value range, and the carrying capacity evaluation is safe and reliable and fully utilizes the power grid resources.

[0204] Example 4

[0205] A computer system comprising a memory, a processor and a computer program stored on the memory, the processor executing the computer program to implement the steps of the method as described in examples 1-3.

[0206] Example 5

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

[0208] The present application is described in reference to the flowchart and / or block diagram of the method, apparatus (system) and computer program product according to an embodiment of the present application. It is understood that each flow and / or block in the flowchart and / or block diagram, and a combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, a special purpose computer, an embedded processor or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the function specified in the flowchart block or blocks.

[0209] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flowchart and / or block diagram block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the function specified in the flowchart block or blocks.

[0210] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flowchart and / or block diagram block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the function specified in the flowchart block or blocks.

[0211] The above description is only preferred embodiments of the present application, it should be pointed out that for those skilled in the art, without departing from the technical principles of the present application, a number of improvements and modifications can be made, these improvements and modifications should be considered as the protection scope of the present application.

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. 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. The key calculation parameters include: The allowable factor for reverse power transmission of the equipment is calculated using the following formula: ； in This refers to the allowable factor for reverse power transmission from 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: ； 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: ； 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: ； 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 photovoltaic output in the region at time t, and n be the total number of photovoltaic units in the region. 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 a two-circuit transformer topology is calculated using a progressive algorithm, including: The formula for calculating the remaining available capacity of each distribution transformer is as follows: ； 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: ； 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. ； 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: ； 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: ； 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: ； 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: ； 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: ； 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: ； in, The total carrying capacity of distributed photovoltaic power generation in the substation supply area, The photovoltaic installed capacity has been developed in the substation supply area; The carrying capacity of a three-level distributed photovoltaic system under a three-circuit transformer electrical topology is 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: ； 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: ； 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.

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, 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.

5. 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.

6. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 5, 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.

7. The method for assessing the photovoltaic carrying capacity of a distribution network according to claim 6, 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.

8. 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 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-7.

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