Setting calculation modeling method, device and equipment of active power distribution network and medium

Abstract

The invention discloses a setting calculation modeling method and device for an active power distribution network, equipment and a medium. The method comprises the following steps: acquiring distributed photovoltaic parameter management data, distributed photovoltaic access quantity and equipment parameters of a target power distribution network; according to a comparison result of the distributed photovoltaic access quantity and a preset threshold value and the distributed photovoltaic parameter management data, a first modeling mode is determined, and the first modeling mode comprises a conventional load modeling mode and a current source modeling mode; the current source modeling mode comprises a controlled current source fine modeling mode, a constant current source fine modeling mode and a constant current source aggregation modeling mode; and if it is determined that the first modeling mode is a current source modeling mode, determining a second modeling mode according to a preset priority, performing modeling and setting calculation on the target power distribution network based on the second modeling mode and the equipment parameters, and determining a setting value interval. According to the technical scheme, the distributed photovoltaic parameter management data and the distributed photovoltaic access quantity of the active power distribution network are analyzed, so that differential modeling of the active power distribution network is realized, and the adaptability of the constant value is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a setting calculation modeling method, device, equipment and medium for an active distribution network. Background Art

[0002] The traditional distribution network is characterized by single power supply and a radial structure. When a short circuit or other fault occurs in the system, protection can be implemented by simply disconnecting the circuit breaker on the system side. With the in-depth development of "dual carbon construction", a large number of distributed photovoltaic power sources are connected to the traditional distribution network, and the traditional radial power grid is transformed into a multi-terminal active network, resulting in fault current distribution, reverse fault current, auxiliary and external draining phenomena, and extended arc extinguishing time at the fault point. These problems have put forward higher requirements on the effectiveness of the defense of the traditional distribution network.

[0003] For the setting calculation modeling of distributed photovoltaic high penetration distribution network protection, there are currently relevant guidelines and technical regulations that clearly state that distributed photovoltaic power generation units should adopt a controlled current source model, which can also be simplified to a constant current source model. Relay protection should adapt to the safe and stable operation needs of photovoltaic power stations and power systems, and meet the requirements of reliability, selectivity, sensitivity and speed. However, the following problems still exist:

[0004] 1) The calculation efficiency of the controlled current source model of photovoltaic power generation units is low. For example, based on a setting calculation software test, the photovoltaic controlled current source model is used to rotate 15 stations. It takes 46.3 minutes to calculate the maximum short-circuit current of a switch. For each additional station, the calculation time is about 2.0654 times the original time. When the number of stations increases to 30, the calculation time is estimated to be 40,000 hours; while the method of manually analyzing the maximum and minimum short-circuit currents of photovoltaic power generation through the auxiliary increase effect or external pumping effect is still time-consuming and requires high analytical ability of the calculation personnel, which may cause the error of the shutdown.

[0005] 2) For lines with many photovoltaic stations, the workload of fine modeling is large and the efficiency is low. In recent years, it has been proposed to model photovoltaic power stations with the same box transformers by multiplying them, but a 10 kV line may connect to as many as 50 distributed photovoltaic power stations, and taking photovoltaic power stations as units is still fine modeling. Fine modeling has high requirements for distribution network parameter management and a large workload for parameter collection and maintenance. Therefore, fine modeling is not conducive to lines with many grid-connected photovoltaic power stations.

[0006] 3) The photovoltaic "controlled current source model-fine modeling" calculation has a high dependence on the setting calculation software. Tests show that using the photovoltaic "controlled current source model-fine modeling" for manual calculation, it takes about 7 days for two photovoltaic models to participate in the calculation. When the number of photovoltaic models exceeds 3, it is necessary to rely entirely on the setting calculation software, which is not conducive to promotion and application.

[0007] Therefore, how to provide a model that can quickly and accurately perform setting calculations is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the invention

[0008] The purpose of the present invention is to provide a method, device, equipment and medium for setting calculation modeling of an active distribution network, so as to solve the problems of long time consumption and low efficiency of setting calculation of the active distribution network. The purpose of the present invention is to realize differentiated modeling of the active distribution network and improve the adaptability of the setting value.

[0009] In order to achieve the above purpose, the beneficial effects of the present invention are: by analyzing the distributed photovoltaic parameter management data and the distributed photovoltaic access capacity of the active distribution network, differentiated modeling of the active distribution network is realized, thereby improving the adaptability of the set value.

[0010] According to one aspect of the present invention, a setting calculation modeling method for an active power distribution network is provided, the method comprising:

[0011] Obtain distributed photovoltaic parameter management data, distributed photovoltaic access capacity and equipment parameters of the target distribution network;

[0012] Determine a first modeling method according to a comparison result between the distributed photovoltaic access amount and a preset threshold value, and the distributed photovoltaic parameter management data; wherein the first modeling method includes a conventional load modeling method and a current source modeling method;

[0013] If it is determined that the first modeling method is the current source modeling method, the second modeling method is determined according to the preset priority, and the target distribution network is modeled and set based on the second modeling method and the equipment parameters to determine the setting value range; wherein, the current source modeling method includes a controlled current source fine modeling method, a constant current source fine modeling method and a constant current source aggregate modeling method, and the preset priorities are, from low to high, the controlled current source fine modeling method, the constant current source fine modeling method and the constant current source aggregate modeling method.

[0014] According to another aspect of the present invention, there is provided a setting calculation modeling device for an active power distribution network, the device comprising:

[0015] Parameter acquisition module, used to obtain distributed photovoltaic parameter management data, distributed photovoltaic access quantity and equipment parameters of the target distribution network;

[0016] A modeling method determination module is used to determine a first modeling method according to a comparison result between the distributed photovoltaic access amount and a preset threshold value, and the distributed photovoltaic parameter management data; wherein the first modeling method includes a conventional load modeling method and a current source modeling method;

[0017] A modeling and setting calculation module is used to determine the second modeling method according to a preset priority if it is determined that the first modeling method is a current source modeling method, model and set the target distribution network based on the second modeling method and the equipment parameters, and determine the setting value range; wherein the current source modeling method includes a controlled current source fine modeling method, a constant current source fine modeling method and a constant current source aggregate modeling method, and the preset priorities are, from low to high, the controlled current source fine modeling method, the constant current source fine modeling method and the constant current source aggregate modeling method.

[0018] According to another aspect of the present invention, there is provided an electronic device, the device comprising:

[0019] At least one processor; and a memory in communication with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the setting calculation modeling method for the active distribution network described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the setting calculation modeling method for the active distribution network described in any embodiment of the present invention when executed.

[0021] The technical solution provided by the present invention obtains the distributed photovoltaic parameter management data, distributed photovoltaic access quantity and equipment parameters of the target distribution network; determines the first modeling method according to the comparison result of the distributed photovoltaic access quantity and the preset threshold value, and the distributed photovoltaic parameter management data, wherein the first modeling method includes the conventional load modeling method and the current source modeling method; if the first modeling method is determined to be the current source modeling method, the second modeling method is determined according to the preset priority, and the target distribution network is modeled and set based on the second modeling method and the equipment parameters to determine the setting value range, wherein the second modeling method includes the controlled current source fine modeling method, the constant current source fine modeling method and the constant current source aggregate modeling method. This technical solution analyzes the distributed photovoltaic parameter management data and the distributed photovoltaic access quantity of the active distribution network to realize the differentiated modeling of the active distribution network, thereby improving the adaptability of the setting value.

[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic diagram of a flow chart of a setting calculation modeling method for an active distribution network provided in Embodiment 1 of the present invention;

[0024] Figure 2 A schematic diagram of a fixed value interval provided in Embodiment 1 of the present invention;

[0025] Figure 3 A flow chart of a method for setting calculation and modeling of an active distribution network provided in Embodiment 2 of the present invention;

[0026] Figure 4 A schematic diagram of a constant current source model provided in Embodiment 2 of the present invention;

[0027] Figure 5 A schematic diagram of a controlled current source model provided in Embodiment 2 of the present invention;

[0028] Figure 6 A schematic diagram of the structure of an active power distribution network provided in Embodiment 2 of the present invention;

[0029] Figure 7 A flow chart of a method for setting calculation and modeling of an active distribution network provided in Embodiment 3 of the present invention;

[0030] Figure 8 A schematic diagram of an equivalent external pumping effect provided in the third embodiment of the present invention;

[0031] Fig. 9 This is a schematic diagram of an equivalent boosting effect provided in the third embodiment of the present invention;

[0032] Fig.10 A schematic diagram of the structure of an active distribution network aggregation model provided in Embodiment 3 of the present invention;

[0033] Fig.11 A schematic diagram of the structure of another active distribution network aggregation model provided in the third embodiment of the present invention;

[0034] Fig.12 A schematic diagram of the structure of a setting calculation modeling device for an active power distribution network provided in a fourth embodiment of the present invention;

[0035] Fig.13 It is a structural schematic diagram of a device for implementing a setting calculation modeling method of an active distribution network in an embodiment of the present application. DETAILED DESCRIPTION

[0036] The present invention is further described in detail below through the accompanying drawings and specific embodiments.

[0037] Embodiment 1

[0038] Figure 1The present invention provides a flow chart of a method for setting calculation modeling of an active distribution network according to the first embodiment of the present invention. The present invention can be applied to the case of constructing a setting calculation model of an active distribution network. The method can be executed by a setting calculation modeling device of an active distribution network. The setting calculation modeling device of an active distribution network can be implemented in the form of hardware and / or software. The setting calculation modeling device of an active distribution network can be configured in a device with data processing capability. Figure 1 As shown, the method includes:

[0039] S110, obtaining distributed photovoltaic parameter management data, distributed photovoltaic access capacity and equipment parameters of the target distribution network.

[0040] Among them, the target distribution network can be an active distribution network, that is, a distribution network that is connected to distributed photovoltaic power sources and has bidirectional power flow, which can also be called an active distribution network.

[0041] Distributed photovoltaic parameter management data may be the collection and maintenance of distributed photovoltaic parameters, for example, management standards for distributed photovoltaic parameters, update cycles for distributed photovoltaic parameters, or collected distributed photovoltaic parameters.

[0042] The access capacity of distributed photovoltaic power generation can be the total capacity of distributed photovoltaic power generation devices in the target distribution network. Distributed photovoltaic power generation is built near the user's site, and the operation mode is mainly based on the user's self-generation and self-use, and the surplus electricity is connected to the grid. The access capacity is usually measured in kilowatts (kW) or megawatts (MW).

[0043] Specifically, the information of distributed photovoltaic projects that have been connected and are being connected can be obtained through the contract information of the target distribution network, that is, the current capacity of distributed photovoltaics, access location, etc. On this basis, the capacity of each distributed photovoltaic project in the target distribution network is accumulated to obtain the sum of the distributed photovoltaic access capacity. In order to avoid frequent adjustment of fixed values ​​caused by the successive access of distributed photovoltaics, the present invention uses distributed photovoltaic prospective capacity to participate in the calculation. Therefore, it is also necessary to obtain the distributed photovoltaic open capacity of the target distribution network, and take the sum of the distributed photovoltaic open capacity and the distributed photovoltaic current capacity as the distributed photovoltaic prospective capacity.

[0044] It should be noted that, considering that the actual power generation of distributed photovoltaics may be different in different time periods, the power monitoring data over a period of time can be averaged to obtain a more accurate current distributed photovoltaic access capacity.

[0045] The equipment parameters can be the grid topology information of the target distribution network, which may include the following parameters: 1) Topology: including the topological connection relationship between the substation 10kV bus, overhead lines, cable lines, distribution transformers, circuit breakers, distributed photovoltaics and other equipment; 2) Basic parameters of distribution lines: including line type, length, model, resistance per unit length, reactance, and current carrying capacity. Among them, line types are divided into overhead lines and cables; 3) Basic parameters of distribution transformers: including transformer model, ratio, rated capacity, and short-circuit impedance; 4) Switchgear data: including the current disconnection status of the circuit breaker; 5) Distributed photovoltaic parameters: photovoltaic capacity, photovoltaic access location, photovoltaic inverter control strategy, etc.

[0046] S120: Determine a first modeling method according to a comparison result between the distributed photovoltaic access amount and a preset threshold value and the distributed photovoltaic parameter management data, wherein the first modeling method includes a conventional load modeling method and a current source modeling method.

[0047] Among them, the preset standards may include whether the management standards of distributed photovoltaic parameters are unified, whether the update cycle of distributed photovoltaic parameters is timely, or whether the collected distributed photovoltaic parameters are comprehensive and accurate.

[0048] The preset threshold may be a threshold obtained based on historical working experience.

[0049] Specifically, for lines where the distributed photovoltaic access amount is less than the preset threshold and the distributed photovoltaic parameter management is insufficient, it indicates that the proportion of distributed photovoltaics in the distribution network is small and the impact on the distribution network is relatively small. At this time, the first modeling method can be determined as the conventional load modeling method; for lines where the distributed photovoltaic access amount is greater than the preset threshold and the distributed photovoltaic parameter management is better, the first modeling method can be determined as the current source modeling method.

[0050] Among them, the conventional load modeling method is to regard distributed photovoltaics as a traditional static or dynamic load model during the model establishment process, that is, the impact of distributed photovoltaics on short-circuit current is not considered, and modeling is usually not required.

[0051] The advantage of the above technical solution is that by conducting quantitative or qualitative analysis on distributed photovoltaic parameter management data and distributed photovoltaic access capacity, it is possible to select appropriate modeling methods according to different situations and better analyze the operating status and characteristics of the target distribution network.

[0052] S130. If it is determined that the first modeling method is the current source modeling method, the second modeling method is determined according to the preset priority, and the target distribution network is modeled and set based on the second modeling method and the equipment parameters to determine the setting value range. The current source modeling method includes a controlled current source fine modeling method, a constant current source fine modeling method, and a constant current source aggregate modeling method. The preset priorities are, from low to high, the controlled current source fine modeling method, the constant current source fine modeling method, and the constant current source aggregate modeling method.

[0053] Among them, the preset priority can be the order of the controlled current source fine modeling method, the constant current source fine modeling method and the constant current source aggregate modeling method.

[0054] Since different modeling methods simplify the target distribution network in different ways, the model constructed by them has inconsistent value intervals of the set value when calculating the short-circuit current, and even causes the set value interval to not exist. Therefore, the present invention can be determined according to the calculation accuracy of each modeling method and the range of the fixed value setting interval. For example, the lower the calculation accuracy and the smaller the interval range, the higher the priority.

[0055] Among them, the controlled current source fine modeling method is to treat the distributed photovoltaic as a controlled current source during the model establishment process, which can more accurately reflect the output characteristics of distributed photovoltaic. By modeling its control strategy in detail, the short-circuit state of the distribution network can be analyzed more accurately.

[0056] Among them, the constant current source fine modeling method is to treat distributed photovoltaics as a constant current source during the model establishment process, which simplifies the model of distributed photovoltaics to a certain extent, but can still more accurately reflect its impact on the distribution network.

[0057] Among them, the constant current source aggregation modeling method can be to aggregate multiple distributed photovoltaics during the model establishment process, which is equivalent to a larger constant current source. The purpose of this is to reduce the computational complexity, especially when there are a large number of distributed photovoltaics in the distribution network and they are relatively dispersed. Through aggregation, the complex multi-distributed photovoltaic system can be simplified into a relatively simple model, which is convenient for setting calculations.

[0058] In some embodiments of the present invention, a first modeling method is determined based on a comparison result between the distributed photovoltaic access amount and a preset threshold, and the distributed photovoltaic parameter management data, including: if the distributed photovoltaic parameter management data meets the preset standard and the distributed photovoltaic access amount is greater than the preset threshold, then the first modeling method is determined to be a current source modeling method; otherwise, the first modeling method is determined to be a conventional load modeling method.

[0059] The present invention models the target distribution network based on conventional load modeling, controlled current source fine modeling, constant current source fine modeling and constant current source aggregate modeling, and calculates the fixed value interval of the XX outgoing line switch in overcurrent section I, overcurrent section II and overcurrent section III based on the constructed setting calculation model. The results are as follows Figure 2 As shown, the red area represents the constant value interval solved by the model constructed based on the conventional load modeling method, the orange area represents the constant value interval solved by the model constructed based on the controlled current source fine modeling method, the blue area represents the constant value interval solved by the model constructed based on the constant current source fine modeling method, and the green area represents the constant value interval solved by the model constructed based on the constant current source aggregation modeling method.

[0060] Depend on Figure 2 It can be seen that the fixed value setting interval solved by the model constructed based on the conventional load modeling method is the largest and the calculation accuracy is the lowest; the fixed value setting interval solved by the model constructed based on the controlled current source fine modeling method is larger and the calculation accuracy is the highest; the fixed value setting interval solved by the model constructed based on the constant current source aggregation modeling method is the smallest and the calculation accuracy is lower; the parameter collection and system modeling workload of the models constructed based on the controlled current source fine modeling method and the constant current source fine modeling method is large; when constructing a model based on the constant current source aggregation modeling method, there is no need to consider the actual location of the photovoltaic power generation, the workload of parameter collection and modeling is greatly reduced, the calculation amount is minimized, and it does not rely on the setting calculation system for manual calculation, which is convenient for promotion and application.

[0061] Exemplarily, the preset priorities are, from high to low, constant current source aggregate modeling method, constant current source fine modeling method and controlled current source fine modeling method. The calculation is first based on the constant current source aggregate modeling method and device parameter modeling and setting; if the setting value range cannot be determined, the calculation is based on the constant current source fine modeling method and device parameter modeling and setting; if the setting value range cannot be determined, the calculation is based on the controlled current source fine modeling method and device parameter modeling and setting.

[0062] When modeling the target distribution network, the target distribution network can be equivalently processed based on the second modeling method, a setting calculation model can be constructed, and then the voltage and current of the lines in the target distribution network can be calculated using the equipment parameters to determine the value range of the setting value.

[0063] In some embodiments of the present invention, after determining the first modeling method based on the comparison result of the distributed photovoltaic access amount and the preset threshold, and the distributed photovoltaic parameter management data, the method also includes: if it is determined that the first modeling method is a conventional load modeling method, then each distributed photovoltaic in the target distribution network is used as a load unit, and a setting calculation model is constructed in combination with the equipment parameters.

[0064] Specifically, each distributed photovoltaic in the target distribution network is regarded as a load unit, and no modeling is required. The target distribution network is still calculated according to the fixed value setting of a single power source radial grid.

[0065] The benefit of this arrangement of the scheme is that by analyzing the distributed photovoltaic parameter management data of the active distribution network and the distributed photovoltaic access capacity, differentiated modeling of the active distribution network is achieved, thereby improving the adaptability of the set value.

[0066] Embodiment 2

[0067] Figure 3 The following is a flow chart of a method for setting calculation and modeling of an active distribution network provided in the second embodiment of the present invention. The embodiment of the present invention is optimized based on the above embodiment. Figure 3 As shown, the method includes:

[0068] S210, obtaining distributed photovoltaic parameter management data, distributed photovoltaic access capacity and equipment parameters of the target distribution network.

[0069] S220: Determine a first modeling method according to a comparison result between the distributed photovoltaic access amount and a preset threshold value and the distributed photovoltaic parameter management data, wherein the first modeling method includes a conventional load modeling method and a current source modeling method.

[0070] S230: If it is determined that the first modeling method is a current source modeling method, the second modeling method is determined to be a constant current source aggregate modeling method according to a preset priority, and the target distribution network is modeled and set based on the constant current source aggregate modeling method and the device parameters to determine whether there is a set value interval. The current source modeling method includes a controlled current source fine modeling method, a constant current source fine modeling method, and a constant current source aggregate modeling method.

[0071] Specifically, the aggregated distributed photovoltaics can be selected based on factors such as geographical location, access voltage level, and power generation characteristics. For example, the distributed photovoltaics in the same regional photovoltaic power station or connected to the same substation and the same line can be aggregated. Secondly, for the selected distributed photovoltaic set, calculate the parameters of the equivalent constant current source, such as current size and direction. For example, it can be the average value of the maximum output current of each distributed photovoltaic under typical operating conditions, or a weighted average calculation can be performed based on the capacity and power generation characteristics of the distributed photovoltaics. Thirdly, construct a constant current source unit based on the calculated equivalent current source parameters. Finally, combine the constant current source unit with the line equipment parameters of the target distribution network for setting calculation to determine whether there is a setting value range.

[0072] S240. If not, determine that the second modeling method is a constant current source fine modeling method, and model and set the target distribution network based on the constant current source fine modeling method and the equipment parameters to determine whether there is a setting value range.

[0073] It should be noted that if the target distribution network is modeled and set based on the constant current source aggregation modeling method and equipment parameters, and it is determined that there is a setting value range, then the setting value range will be used as the final output result.

[0074] The constant current source model is a current source calculation that provides a constant "maximum allowable current" for photovoltaics, which is generally considered to be 1.2 times the rated current. A single photovoltaic uses a constant current source model, and multiple photovoltaics are modeled separately according to the actual access location and capacity. When calculating the short-circuit current, the setting calculation system automatically identifies the photovoltaic model of auxiliary increase and external draw based on the photovoltaic effect, observation point and fault point, shortening the calculation time and effectively improving the fault tolerance rate.

[0075] Specifically, each power generation unit of the photovoltaic power station can be multiplied to be equivalent to a constant current source unit, and modeling and calculation can be performed according to the actual location of the distributed photovoltaic power station connected to the distribution network. Figure 4 This is a schematic diagram of a constant current source model provided in Example 2 of the present invention. The model is developed according to the "QGDW 12207-2022 Guidelines for Modeling New Energy Sites for Relay Protection Setting Calculations". Photovoltaic constant provides the maximum allowable current and is set at 1.2 times the rated current. When the three-phase short circuit occurs, the angle is consistent with the short-circuit current angle provided by the system. When the two-phase short circuit occurs, the photovoltaic negative sequence suppression characteristic is canceled, and the angle is consistent with the short-circuit current angle provided by the system.

[0076] In some embodiments of the present invention, the target distribution network is modeled and set based on the constant current source fine modeling method and the device parameters to determine whether there is a setting value range, including: modeling the target distribution network based on the constant current source fine modeling method and the device parameters to obtain a constant current source fine model of the target distribution network; determining the distributed photovoltaic units participating in the setting calculation in the constant current source fine model according to the photovoltaic effect, the fault point and the observation point; performing setting calculation according to the distributed photovoltaic units participating in the setting calculation and the device parameters to determine whether there is a setting value range.

[0077] Specifically, the distributed photovoltaics with auxiliary enhancement and external absorption effects can be determined according to the locations of the fault points and observation points.

[0078] In some embodiments of the present invention, the distributed photovoltaic units participating in the setting calculation in the constant current source fine model are determined according to the photovoltaic effect, the fault point and the observation point, including: if the photovoltaic effect is an external absorption effect, the distributed photovoltaic units between the fault point and the observation point are used as the distributed photovoltaic units participating in the setting calculation; if the photovoltaic effect is an auxiliary effect, the distributed photovoltaic units outside the fault point and the observation point are used as the distributed photovoltaic units participating in the setting calculation.

[0079] When performing setting calculations, if the auxiliary boosting effect needs to be considered, the distributed photovoltaics participating in the auxiliary boosting effect will be automatically turned on; if the external draw effect needs to be considered, the distributed photovoltaics participating in the external draw effect will be automatically turned on.

[0080] For example, when setting the calculation for overcurrent section I, it is necessary to consider the auxiliary effect but not the external draw effect, and the distributed photovoltaics participating in the auxiliary effect will be automatically turned on; for another example, when setting the calculation for overcurrent section III, the minimum short-circuit current is considered, and only the photovoltaics with external draw effect are considered, and the distributed photovoltaics participating in the auxiliary effect will be turned off.

[0081] S250. If it still does not exist, determine that the second modeling method is a controlled current source fine modeling method, and model and set the target distribution network based on the controlled current source fine modeling method and the equipment parameters to determine whether there is a setting value range.

[0082] It should be noted that if the target distribution network is modeled and set based on the constant current source fine modeling method and equipment parameters, and it is determined that there is a setting value range, then the setting value range is used as the final output result.

[0083] The controlled current source model can reflect the short-circuit current characteristics during the entire low voltage ride-through period. The short-circuit current is controlled by factors such as the inverter control target and the terminal voltage. When calculating the short circuit, it is necessary to iterate repeatedly according to the mapping relationship between voltage and current. The calculation accuracy is relatively high, and the amount of calculation is relatively large. A single photovoltaic uses a controlled current source model, and multiple photovoltaics are modeled according to the actual access location and capacity. When calculating the short-circuit current, the setting calculation system automatically identifies the photovoltaic model of auxiliary and external pumping according to the photovoltaic effect, observation point and fault point, shortening the calculation time and effectively improving the fault tolerance rate.

[0084] Specifically, each power generation unit of each photovoltaic power station can be multiplied to be equivalent to a controlled current source unit, and modeled and calculated according to the actual location where the photovoltaic power station is connected to the distribution network. Figure 5 This is a schematic diagram of a controlled current source model provided in Example 2 of the present invention. The model is developed according to "QGDW 12207-2022 Guidelines for Modeling New Energy Stations for Relay Protection Setting Calculations".

[0085] In some embodiments of the present invention, the target distribution network is modeled and set based on the controlled current source fine modeling method and the device parameters to determine whether there is a setting value range, including: modeling the target distribution network based on the controlled current source fine modeling method and the device parameters to obtain a controlled current source fine model of the target distribution network; determining the distributed photovoltaic units participating in the setting calculation in the controlled current source fine model according to the photovoltaic effect, the fault point and the observation point; performing setting calculation according to the distributed photovoltaic units participating in the setting calculation and the device parameters to determine whether there is a setting value range.

[0086] Specifically, the distributed photovoltaics with auxiliary enhancement and external absorption effects can be determined according to the locations of the fault points and observation points.

[0087] In some embodiments of the present invention, the distributed photovoltaic units participating in the setting calculation in the controlled current source fine model are determined according to the photovoltaic effect, the fault point and the observation point, including: if the photovoltaic effect is an external absorption effect, the distributed photovoltaic units between the fault point and the observation point are used as the distributed photovoltaic units participating in the setting calculation; if the photovoltaic effect is an auxiliary effect, the distributed photovoltaic units outside the fault point and the observation point are used as the distributed photovoltaic units participating in the setting calculation.

[0088] When performing setting calculations, if the auxiliary boosting effect needs to be considered, the distributed photovoltaics participating in the auxiliary boosting effect will be automatically turned on; if the external draw effect needs to be considered, the distributed photovoltaics participating in the external draw effect will be automatically turned on.

[0089] For example, when setting the calculation for overcurrent section I, it is necessary to consider the auxiliary effect but not the external draw effect, and the distributed photovoltaics participating in the auxiliary effect will be automatically turned on; for another example, when setting the calculation for overcurrent section III, the minimum short-circuit current is considered, and only the photovoltaics with external draw effect are considered, and the distributed photovoltaics participating in the auxiliary effect will be turned off.

[0090] Exemplarily, an active distribution network is used as an example for explanation. Figure 6 This is a schematic diagram of the structure of an active power distribution network provided in the second embodiment of the present invention. Figure 6 As shown in the figure, the 10kV busbar is connected with line 1 and line 2, where line 1 is connected with outgoing line switch XL1, section switch FD11, section switch FD12 and boundary switch FJ11 in sequence, and branch switch FZ11 is connected to the branch between outgoing line switch XL1 and section switch FD11. The end of branch switch FZ11 is connected with distributed photovoltaic I PV11 There is a branch switch FZ12 on the branch between the segment switch FD11 and the segment switch FD12, and the end of the branch switch FZ12 is connected to the distributed photovoltaic I PV12There is a branch switch FZ13 on the branch between the segment switch FD12 and the boundary switch FJ11. The end of the branch switch FZ13 is connected to the distributed photovoltaic I PV13 ; Line 2 is followed by the outgoing switch XL2, the segment switch FD21, the segment switch FD22 and the boundary switch FJ21. There is a branch switch FZ21 on the branch between the outgoing switch XL2 and the segment switch FD21. The end of the branch switch FZ21 is connected to the distributed photovoltaic I PV21 There is a branch switch FZ22 on the branch between the segment switch FD21 and the segment switch FD22, and the branch switch FZ22 is connected to the distributed photovoltaic I PV22 and I PV23 There is a branch switch FZ23 on the branch between the segment switch FD22 and the boundary switch FJ21. The end of the branch switch FZ23 is connected to the distributed photovoltaic I PV24 .

[0091] If the controlled current source is modeled in a detailed manner and the device parameters are Figure 6 The active distribution network shown is modeled with Figure 6 Taking the branch switch FZ22 as an example, the distributed photovoltaic units involved in the setting calculation in the controlled current source fine model are analyzed. When calculating the short-circuit current on the low-voltage side of the distribution transformer, the fault point is set on the low-voltage side of the distribution transformer, and the boost effect is selected. The system identifies the photovoltaic units outside the switch and the fault point as photovoltaic units that need to participate in the short-circuit calculation, that is, I PV11 ,I PV12 ,I PV13 ,I PV21 and I PV24 Automatically participate in the calculation; when calculating the short-circuit current of the line end fault, select the external draw effect, and the system will identify the photovoltaic between the switch and the fault point as the photovoltaic unit that needs to participate in the short-circuit calculation, that is, I PV22 and I PV23 Automatically participate in calculations.

[0092] The beneficial effect of the above technical solution is that by automatically identifying the distributed photovoltaic units participating in the auxiliary enhancement and external pumping effects, the setting calculation time is shortened and the fault tolerance rate is effectively improved.

[0093] The setting calculation modeling method for the active distribution network provided in the embodiment of the present invention uses a constant current source aggregation modeling method, a constant current source fine modeling method and a controlled current source fine modeling method in sequence to perform modeling through an advanced method, thereby improving the setting calculation efficiency.

[0094] Embodiment 3

[0095] Figure 7The flowchart of a method for setting calculation modeling of an active distribution network provided in the third embodiment of the present invention is optimized based on the second embodiment above, specifically, the target distribution network is modeled and set based on the constant current source aggregation modeling method and the device parameters, and the setting value interval is determined to be optimized. Figure 7 As shown, the method includes:

[0096] S310, obtaining distributed photovoltaic parameter management data, distributed photovoltaic access capacity and equipment parameters of the target distribution network.

[0097] S320. Determine a first modeling method based on a comparison result between the distributed photovoltaic access amount and a preset threshold, and the distributed photovoltaic parameter management data; wherein the first modeling method includes a conventional load modeling method and a current source modeling method, and the current source modeling method includes a controlled current source fine modeling method, a constant current source fine modeling method, and a constant current source aggregate modeling method.

[0098] S330. If it is determined that the first modeling method is the current source modeling method, the second modeling method is determined as the constant current source aggregation modeling method according to the preset priority, the external drawing effect of each switch in the target distribution network is analyzed, the external drawing aggregation point of the distributed photovoltaic after each switch is determined, and the distributed photovoltaic after each switch is aggregated into an external drawing aggregation unit at each external drawing aggregation point.

[0099] Among them, the external absorption effect refers to the phenomenon that when a fault occurs in the downstream distribution line of the distributed photovoltaic grid-connected point in the active distribution network, part of the distributed photovoltaic short-circuit current flows to the system, causing the short-circuit current of the upstream switch to decrease.

[0100] The external extraction aggregation point may be a location that can represent the external extraction effect of distributed photovoltaics, for example, it may be an access point of distributed photovoltaics, a branch point of a line, or other representative locations.

[0101] For example, the location of the fault point can be determined by analyzing the network topology of the target distribution network; then, according to the fault type and location, the power system analysis method can be used to determine the external current distribution of the distributed photovoltaic system; finally, according to the distribution of the external current, a suitable external aggregation point can be selected. For another example, the external aggregation point can be determined based on experience and historical operation data, such as selecting the line node near the distributed photovoltaic access point as the external aggregation point. For another example, the location where the external absorption effect of the distributed photovoltaic system is obvious in the historical fault data can be selected as the external aggregation point.

[0102] In some embodiments of the present invention, the external draw effect of each switch in the target distribution network is analyzed to determine the external draw aggregation point of the distributed photovoltaic behind each switch, including: for each switch in the target distribution network, according to the short-circuit current provided by the distributed photovoltaic, the bus equivalent impedance, and the impedance between the distributed photovoltaic access point and the bus, the impedance between the distributed photovoltaic access point and the fault point, and the distributed photovoltaic access point voltage, determine the external draw short-circuit current change of each switch in the target distribution network when the distributed photovoltaic is at different access points; and use the access point corresponding to the maximum external draw short-circuit current change as the external draw aggregation point.

[0103] Among them, the short-circuit current provided by distributed photovoltaics can be the current provided by distributed photovoltaics to the system when a short-circuit fault occurs in the distribution network. Its size depends on factors such as the capacity and output characteristics of the distributed photovoltaics and the state of the grid at the time of the fault.

[0104] Among them, the busbar equivalent impedance refers to the equivalent impedance of the busbar upper system. According to the superposition principle, when distributed photovoltaics are connected to the distribution network, the short-circuit current that can be equivalent to it will flow to the grounding point of the system equivalent voltage source through the busbar impedance, thereby affecting the short-circuit current at the protection device.

[0105] The impedance between the distributed photovoltaic access point and the fault point may be the sum of the line impedance between the distributed photovoltaic access point and the fault point and the equivalent impedance of other electrical components.

[0106] Specifically, the type and location of the fault in the distribution network can be determined first, such as three-phase short circuit, two-phase short circuit and other fault types, and the specific location of the fault point in the distribution network; then, based on the short-circuit current provided by the distributed photovoltaics, the bus impedance, the equivalent impedance between the distributed photovoltaic access point and the bus, the equivalent impedance between the distributed photovoltaic access point and the fault point, and the voltage of the distributed photovoltaic access point, the change in the external short-circuit current of the protection device at different access points of the distributed photovoltaics is determined; finally, the access point corresponding to the maximum external short-circuit current change is the external aggregation point, and the maximum external short-circuit current change indicates that the distributed photovoltaics have the greatest effect on the external short-circuit current draw at the protection device.

[0107] In some embodiments of the present invention, the access point corresponding to the maximum external short-circuit current change is used as the external aggregation point, including: if the switch is an outgoing line switch, a branch switch or a boundary switch, the lower port of the switch is used as the external aggregation point.

[0108] Figure 8 A schematic diagram of an external pumping equivalent provided in the third embodiment of the present invention is shown in FIG. Figure 8 Take this example to explain. Figure 8In this paper, the 2J switch at position 3 is taken as an example to analyze the external pumping effect. The fault point is set at position 5. The short-circuit current change of the 2J switch when the distributed photovoltaic is at position 3, position 4 and position 6 is determined respectively. Three-phase short circuit and two-phase short circuit are discussed separately.

[0109] When three-phase short circuit occurs:

[0110] Among them, the short-circuit current change of the 2J switch when the distributed photovoltaic is in position 3 is:

[0111] ΔI PV =I PV ((Z 34 +Z 45 ) / (Z s +Z 12 +Z 23 +Z 34 +Z 45 ))

[0112] When the distributed photovoltaic is in position 4, the short-circuit current change of the 2J switch is:

[0113] ΔI PV =I PV (Z 45 / (Z s +Z 12 +Z 23 +Z 34 +Z 45 )).

[0114] In the above formula, ΔI PV Indicates the change in short-circuit current due to external draw, I PV Represents the short-circuit current provided by distributed photovoltaics, Z s Indicates bus impedance, Z 12 represents the line impedance between position 1 and position 2, Z 23 represents the line impedance between position 2 and position 3, Z 34 represents the line impedance between position 3 and position 4, Z 45 Represents the line impedance between position 4 and position 5.

[0115] When the three phases are short-circuited, the distributed photovoltaic power generation in position 6 has no effect on the short-circuit current of the 2J switch.

[0116] From the above analysis, it can be seen that when the distributed photovoltaic is at position 3 during a three-phase short circuit, the change in the external short-circuit current of the 2J switch is the largest, that is, the external draw effect is the largest. Therefore, position 3 can be used as the external draw aggregation point.

[0117] When two phases are short-circuited:

[0118] Among them, the short-circuit current change of the 2J switch when the distributed photovoltaic is in position 3 is:

[0119]

[0120] When the distributed photovoltaic is in position 4, the short-circuit current change of the 2J switch is:

[0121]

[0122] In the above formula, ΔI PV Indicates the change in short-circuit current due to external draw, I PV Represents the short-circuit current provided by distributed photovoltaics, Z s Represents the busbar equivalent impedance, Z 12 represents the line impedance between position 1 and position 2, Z 23 represents the line impedance between position 2 and position 3, Z 34 represents the line impedance between position 3 and position 4, Z 45 represents the line impedance between position 4 and position 5, U T3 is the phase voltage at position 3, U T4 is the phase voltage at position 4, U M is the phase voltage at the fault point.

[0123] From the above analysis, it can be seen that the change in the external short-circuit current of the distributed photovoltaic when two phases are short-circuited is related to the impedance before and after the T-contact and the voltage of the T-contact. It is difficult to determine the maximum position of the external draw effect. Therefore, the three-phase short-circuit external draw aggregation point can be used as the two-phase short-circuit external draw aggregation point, that is, position 3 is used as the external draw aggregation point, and the maximum output short-circuit current of the photovoltaic is used as the short-circuit current change of the 2J switch.

[0124] It can be inferred from this that when the protection device is an outgoing line switch, branch switch or boundary switch, the distributed photovoltaic can be equivalent to the lower port of the switch.

[0125] S340, analyzing the boosting effect of each switch in the target distribution network, determining the boosting aggregation points of the distributed photovoltaics before each switch, and aggregating the distributed photovoltaics before each switch into boosting aggregation units at each boosting aggregation point.

[0126] Among them, the boosting effect refers to the phenomenon that in the active distribution network, the distributed photovoltaic power generation on the non-fault line provides fault current to the fault line, thereby increasing the current flowing through the fault line.

[0127] Among them, the auxiliary aggregation point can be a location that can represent the auxiliary effect of distributed photovoltaics, such as a key node close to a fault point, a node near a distributed photovoltaic access point, etc.

[0128] For example, the network topology of the target distribution network can be analyzed to determine the location where the fault may occur and the distribution of the fault current; then, the boost current at different locations can be calculated based on the access location and output characteristics of the distributed photovoltaics. For another example, a location with a large and representative boost current can be selected as the boost aggregation point. For another example, the boost aggregation point can also be determined based on experience and historical fault operation data.

[0129] In some embodiments of the present invention, the boosting effect of each switch in the target distribution network is analyzed to determine the boosting aggregation point of the distributed photovoltaics in front of each switch, including: for the distributed photovoltaics of other lines, the lower port of the outgoing switch of the other lines is used as the boosting aggregation point of the distributed photovoltaics of the other lines for the switch of this line; for the distributed photovoltaics of this line, according to the short-circuit current provided by the distributed photovoltaics, the bus equivalent impedance, the impedance between the distributed photovoltaic access point and the bus, and the impedance between the distributed photovoltaic access point and the fault point, the boosting short-circuit current change of the switch of the distributed photovoltaics of this line at different access points is determined; the access point corresponding to the maximum boosting short-circuit current change is used as the boosting aggregation point.

[0130] Specifically, since the auxiliary effect of photovoltaic power on this line on other lines is independent of the photovoltaic access location, the photovoltaic equivalent of this line to the lower port of the switch has the greatest effect on the external draw of the outgoing switch, so the lower port of the switch is selected as the auxiliary aggregation point for the distributed photovoltaic power of other lines to the switch of this line.

[0131] For the distributed photovoltaics of this line, the type and location of the fault in the distribution network can be determined first, such as three-phase short circuit, two-phase short circuit and other fault types, as well as the specific location of the fault point in the distribution network; then, based on the short-circuit current provided by the distributed photovoltaics, the bus impedance, and the equivalent impedance between the distributed photovoltaic access point and the bus, and the equivalent impedance between the distributed photovoltaic access point and the fault point, the change in the short-circuit current of the protection device at different access points of the distributed photovoltaics can be determined; finally, the access point corresponding to the maximum change in the short-circuit current is the auxiliary aggregation point, and the maximum change in the short-circuit current indicates that the distributed photovoltaics have the greatest auxiliary effect on the short-circuit current at the protection device.

[0132] In some embodiments of the present invention, the access point corresponding to the maximum boosting short-circuit current change is used as the boosting aggregation point, including: if the switch is an outgoing line switch, the lower port of the outgoing line switch of the remaining lines of the busbar of this station is used as the photovoltaic boosting aggregation point of the remaining lines of the busbar of this station; if the switch is a branch switch or a boundary switch, the lower port of the outgoing line switch of the remaining lines of the busbar of this station is used as the photovoltaic boosting aggregation point of the remaining lines of the busbar of this station, and the upper port of the switch is used as the photovoltaic boosting aggregation point of this line.

[0133] Fig. 9 This is a schematic diagram of an equivalent boosting effect provided by the third embodiment of the present invention. Fig. 9 Take this example to explain. Fig. 9 In this paper, the auxiliary boosting effect is analyzed by taking the 2J switch at position 3 as an example. The fault point is set on the low-voltage side of the distribution transformer, and the short-circuit current change of the 2J switch when the distributed photovoltaic is at position 1, position 2, position 3 and position 6 is determined respectively.

[0134] Among them, the short-circuit current change of the 2J switch when the distributed photovoltaic is in position 1 is:

[0135] ΔI PV =I PV (Z s / (Z s +Z 12 +Z 23 +Z 34 +Z 45 ))

[0136] When the distributed photovoltaic is in position 2 or position 6, the short-circuit current change of the 2J switch is:

[0137] ΔI PV =I PV ((Z s +Z 12 ) / (Z s +Z 12 +Z 23 +Z 34 +Z 45 ))

[0138] When the distributed photovoltaic is at position 3, the short-circuit current change of the 2J switch is:

[0139] ΔI PV =I PV ((Z s +Z 12 +Z 23 ) / (Z s +Z 12 +Z 23 +Z 34 +Z 45 ));

[0140] In the above formulas, ΔI PV Indicates the change in short-circuit current due to boosting effect, I PV Represents the short-circuit current provided by distributed photovoltaics, Z s Represents the busbar equivalent impedance, Z 12 represents the line impedance between position 1 and position 2, Z 23 represents the line impedance between position 2 and position 3, Z 34 represents the line impedance between position 3 and position 4, Z 45represents the line impedance between position 4 and position 5, Z T Represents the short-circuit impedance of the distribution transformer.

[0141] From the above analysis, it can be seen that when the distributed photovoltaic is at position 3, the change in the auxiliary short-circuit current of the 2J switch is the largest, that is, the auxiliary effect is the largest. Therefore, position 3 can be used as the photovoltaic auxiliary aggregation point of this line.

[0142] It can be inferred from this that when the protection device is a branch switch or a boundary switch, the distributed photovoltaic power of this line can be equivalent to the upper port of the switch.

[0143] When the protection device is an outgoing line switch, the auxiliary effect of the distributed photovoltaics on the remaining lines of this bus is independent of the photovoltaic access location. Therefore, the lower port of the switch on the remaining lines of this bus can be used as an auxiliary aggregation point.

[0144] S350, modeling and setting calculation are performed according to the external polymerization unit, the auxiliary polymerization unit, the equipment parameters and the photovoltaic effect to determine whether there is a setting value range.

[0145] Specifically, the photovoltaic units participating in the setting calculation can be selected as external absorption aggregation units or auxiliary aggregation units according to the photovoltaic effect, so as to establish a setting calculation model corresponding to the target distribution network, and perform setting calculation on the setting calculation model based on the equipment parameters to determine whether there is a setting value range.

[0146] In some embodiments of the present invention, modeling and setting calculations are performed based on the external extraction aggregation unit, the auxiliary aggregation unit, the equipment parameters and the photovoltaic effect to determine whether there is a setting value range, including: modeling the distributed photovoltaics in the target distribution network based on the external extraction aggregation unit, the auxiliary aggregation unit, the equipment parameters and the photovoltaic effect to determine a constant current source aggregation model corresponding to the target distribution network; and setting calculations are performed based on the constant current source aggregation model to determine whether there is a setting value range.

[0147] For example, Figure 6 Based on the active power distribution network structure schematic diagram shown in FIG. , the constant current source aggregation modeling method described in the embodiment of the present invention is used to model it, such as Fig.10 As shown, Fig.10 A structural schematic diagram of an active distribution network aggregation model provided in Embodiment 3 of the present invention.

[0148] Specifically, I of line 1 PV11 ,I PV12 and I PV13 All are gathered behind the outgoing switch XL1 and named I PV1 The photovoltaic open capacity of line 1 is aggregated behind the outgoing line switch XL1, named IPV1开放 , both of which serve as the equivalent power supply for the auxiliary effect of other lines and the equivalent power supply for the external effect of this line; I PV21 ,I PV22 ,I PV23 and I PV24 All are gathered behind the outgoing switch XL2 and named I PV2 The photovoltaic open capacity of line 2 is aggregated behind the outgoing line switch XL2, named I PV2开放 The two serve as the equivalent power source of the auxiliary effect of other lines and the equivalent power source of the external effect of this line. The photovoltaic unit processing method of this line for the calculation of short-circuit current of branch and boundary switches is as follows: Figure 7 The branch switch FZ22 in the circuit breaker is used to connect the I PV21 ,I PV22 ,I PV23 and I PV24 ,I PV2开放 All are gathered in front of the branch switch FZ22, which is I PV2 with I PV2开放 The sub-model of the sum is named I PV2(1) , as the equivalent power source of the boosting effect of this line, all photovoltaic I PV22 ,I PV23 Equivalent to the lower port of the switch, named I PV2(2) , as an equivalent power source for the external draw effect.

[0149] Among them, the mother photovoltaic model is after the outgoing line switch, and the child photovoltaic model is before FZ22, that is, I PV2(1) =I PV2 +I PV2开放 . It can be automatically calculated when there are changes, which is equivalent to a sub-photovoltaic model.

[0150] It should be noted that although I PV22 ,I PV23 It is not the equivalent power supply of the boost effect of the branch switch FZ22, but in order to simplify the calculation, the equivalent power supply of the boost effect of the whole line branch and boundary switch is equivalent to I PV2 with I PV2开放 The sum of the two factors makes the calculation more reliable. In order to improve the modeling efficiency, the extremeness of the aggregate modeling can be appropriately reduced, such as omitting I PV2(1) , will I PV2 and I PV2开放 As the equivalent power supply of the boosting effect of FZ22 circuit.

[0151] In the present invention, an aggregation model can be built behind the outgoing line switch, and two aggregation models can be built before and after each branch or boundary switch respectively. The auxiliary photovoltaic equivalent power supply or the external photovoltaic equivalent power supply can be turned on automatically according to actual needs. The auxiliary photovoltaic equivalent power supply of the entire line and the outgoing line external photovoltaic equivalent power supply can only maintain a mother photovoltaic model at the line outgoing line switch, and the rest of the positions are all its child photovoltaic models. If the photovoltaic capacity changes or there is a connecting line, only the parameters of the mother photovoltaic model are modified.

[0152] For example, Fig.11 This is a schematic diagram of the structure of another active distribution network aggregation model provided in the third embodiment of the present invention. Fig.11 As shown, I PV1 ,I PV2 is the parent photovoltaic model, I PV1(1) ,I PV2(1) If the XL1 switch is calculated to avoid the first tripping circuit breaker or the short-circuit current on the low-voltage side of the distribution transformer, the other line mother models I PV2 ; If the XL1 switch setting sensitivity is calculated, the mother model I of this line is turned on PV1 If the short-circuit current on the low-voltage side of the FZ1 switch is calculated, the other line mother models I PV2 、FZ1 switch helps increase photovoltaic equivalent power supply I PV1(1) ; If the FZ1 switch set value sensitivity is calculated, then the FZ1 switch is turned on to draw the photovoltaic equivalent power I PV1(2) .

[0153] The above modeling method improves the reliability of branch and boundary switches in avoiding faults on the low-voltage side of the distribution transformer. A qualitative analysis is conducted in combination with the photovoltaic boost external extraction mechanism and the setting principle of distribution network protection. The boost will expand the protection range and cause over-level tripping, while the branch switch can ensure selectivity through time and coordination with the lower-level protection. The setting calculation principle allows the boundary switch to trip and remove the fault when a fault occurs on the low-voltage side of the distribution transformer. Therefore, in order to improve the modeling efficiency, the extremeness of the aggregate modeling can be appropriately reduced. The sub-PV model can be omitted during modeling, and the mother PV model can be used as the equivalent power source of the boost effect of the branch and boundary switch line.

[0154] S360. If not, determine that the second modeling method is a constant current source fine modeling method, and model and set the target distribution network based on the constant current source fine modeling method and the equipment parameters to determine whether there is a setting value range.

[0155] S370. If it still does not exist, determine that the second modeling method is a controlled current source fine modeling method, and model and set the target distribution network based on the controlled current source fine modeling method and the equipment parameters to determine whether there is a setting value range.

[0156] An embodiment of the present invention provides a setting calculation modeling method for an active distribution network. The method constructs a setting calculation model by a constant current source aggregation modeling method, and takes the sum of each current grid-connected capacity and the open capacity as the photovoltaic access capacity of the line, thereby avoiding the problem of frequent calculation of fixed values ​​caused by the successive access of photovoltaics and improving the efficiency of the setting calculation.

[0157] Embodiment 4

[0158] Fig.12 This is a schematic diagram of the structure of a setting calculation modeling device for an active distribution network provided in the fourth embodiment of the present invention. Fig.12 As shown, the device comprises:

[0159] The parameter acquisition module 410 is used to acquire the distributed photovoltaic parameter management data, the distributed photovoltaic access quantity and the equipment parameters of the target distribution network;

[0160] The modeling method determination module 420 is used to determine a first modeling method according to the comparison result between the distributed photovoltaic access amount and the preset threshold value and the distributed photovoltaic parameter management data; wherein the first modeling method includes a conventional load modeling method and a current source modeling method;

[0161] The modeling and setting calculation module 430 is used to determine the second modeling method according to the preset priority if it is determined that the first modeling method is the current source modeling method, model and set the target distribution network based on the second modeling method and the equipment parameters, and determine the setting value range; wherein the current source modeling method includes a controlled current source fine modeling method, a constant current source fine modeling method and a constant current source aggregate modeling method, and the preset priorities are, from low to high, the controlled current source fine modeling method, the constant current source fine modeling method and the constant current source aggregate modeling method.

[0162] The benefit of this arrangement of the scheme is that by analyzing the distributed photovoltaic parameter management data of the active distribution network and the distributed photovoltaic access capacity, differentiated modeling of the active distribution network is achieved, thereby improving the adaptability of the set value.

[0163] Furthermore, the modeling method determination module 420 includes:

[0164] A current source modeling mode unit, configured to determine that the first modeling mode is a current source modeling mode if the distributed photovoltaic parameter management data meets a preset standard and the distributed photovoltaic access amount is greater than a preset threshold;

[0165] The conventional load modeling method unit is used to determine that the first modeling method is the conventional load modeling method.

[0166] Furthermore, the modeling and setting calculation module 430 includes:

[0167] A constant current source aggregate modeling mode unit, for, if the second modeling mode is determined to be the constant current source aggregate modeling mode according to a preset priority, modeling and setting calculation are performed on the target distribution network based on the constant current source aggregate modeling mode and the device parameters to determine whether there is a setting value interval;

[0168] A constant current source fine modeling mode unit is used to determine that the second modeling mode is a constant current source fine modeling mode if it does not exist, and to model and set the target distribution network based on the constant current source fine modeling mode and the device parameters to determine whether there is a setting value interval;

[0169] The controlled current source fine modeling method unit is used to determine that the second modeling method is the controlled current source fine modeling method if it still does not exist, and to model and set the target distribution network based on the controlled current source fine modeling method and the equipment parameters to determine whether there is a setting value range.

[0170] Furthermore, the constant current source fine modeling method unit includes:

[0171] A constant current source fine model building subunit is used to model the target distribution network based on the constant current source fine modeling method and the device parameters to obtain a constant current source fine model of the target distribution network;

[0172] A distributed photovoltaic unit determination subunit is used to determine the distributed photovoltaic units involved in the setting calculation in the constant current source fine model according to the photovoltaic effect, the fault point and the observation point;

[0173] The setting value interval determination subunit is used to perform setting calculation according to the distributed photovoltaic units participating in the setting calculation and the equipment parameters to determine whether there is a setting value interval.

[0174] Furthermore, the distributed photovoltaic unit determines the subunit, which is specifically used for:

[0175] If the photovoltaic effect is an external pumping effect, the distributed photovoltaic units between the fault point and the observation point are used as distributed photovoltaic units participating in the setting calculation;

[0176] If the photovoltaic effect is an auxiliary effect, the distributed photovoltaic units outside the fault point and the observation point will be regarded as distributed photovoltaic units participating in the setting calculation.

[0177] Furthermore, the controlled current source fine modeling method unit includes:

[0178] A controlled current source fine model building subunit is used to model the target distribution network based on the controlled current source fine modeling method and the device parameters to obtain a controlled current source fine model of the target distribution network;

[0179] A distributed photovoltaic unit determination subunit is used to determine the distributed photovoltaic units involved in the setting calculation in the controlled current source fine model according to the photovoltaic effect, the fault point and the observation point;

[0180] The setting value interval determination subunit is used to perform setting calculation according to the distributed photovoltaic units participating in the setting calculation and the equipment parameters to determine whether there is a setting value interval.

[0181] Furthermore, the distributed photovoltaic unit determines the subunit, which is specifically used for:

[0182] If the photovoltaic effect is an external pumping effect, the distributed photovoltaic units between the fault point and the observation point are used as distributed photovoltaic units participating in the setting calculation;

[0183] If the photovoltaic effect is an auxiliary effect, the distributed photovoltaic units outside the fault point and the observation point will be regarded as distributed photovoltaic units participating in the setting calculation.

[0184] Furthermore, the constant current source aggregation modeling method unit includes:

[0185] The external-draw aggregation unit determines a subunit, which is used to analyze the external-draw effect of each switch in the target distribution network, determine the external-draw aggregation points of the distributed photovoltaics after each switch, and aggregate the distributed photovoltaics after each switch into external-draw aggregation units at each external-draw aggregation point;

[0186] The boost aggregation unit determines a subunit, which is used to analyze the boost effect of each switch in the target distribution network, determine the boost aggregation points of the distributed photovoltaics before each switch, and aggregate the distributed photovoltaics before each switch into boost aggregation units at each boost aggregation point;

[0187] The subunit for determining the range of set values ​​is used to perform modeling and setting calculations based on the external polymerization unit, the auxiliary polymerization unit, the equipment parameters and the photovoltaic effect to determine whether there is a range of set values.

[0188] Further, the exo-polymerization unit determines the subunit, which is specifically used for:

[0189] For each switch in the target distribution network, according to the short-circuit current provided by the distributed photovoltaic, the bus equivalent impedance, the impedance between the distributed photovoltaic access point and the bus, the impedance between the distributed photovoltaic access point and the fault point, and the voltage at the distributed photovoltaic access point, determine the change in the external short-circuit current of each switch in the target distribution network when the distributed photovoltaic is at different access points;

[0190] The access point corresponding to the maximum external short-circuit current change is used as the external aggregation point.

[0191] Furthermore, the access point corresponding to the maximum external short-circuit current change is used as the external aggregation point, including:

[0192] If the switch is an outgoing line switch, a branch switch or a boundary switch, the lower port of the switch is used as the external extraction aggregation point.

[0193] Further, the polymerization promoting unit determines the subunit, which is specifically used for:

[0194] For the distributed photovoltaic power generation of other lines, the lower port of the outgoing line switch of other lines is used as the auxiliary aggregation point for the distributed photovoltaic power generation of other lines to the switch of this line;

[0195] For the distributed photovoltaics of this line, the change in the auxiliary short-circuit current of the switch at different access points of the distributed photovoltaics of this line is determined according to the short-circuit current provided by the distributed photovoltaics, the bus equivalent impedance, the impedance between the distributed photovoltaic access point and the bus, and the impedance between the distributed photovoltaic access point and the fault point; the access point corresponding to the maximum auxiliary short-circuit current change is used as the auxiliary aggregation point.

[0196] Furthermore, the access point corresponding to the maximum boosting short-circuit current change is used as the boosting aggregation point, including:

[0197] If the switch is an outgoing switch, the lower port of the outgoing switch of the remaining bus lines of the station will be used as the photovoltaic boosting aggregation point of the remaining bus lines of the station;

[0198] If the switch is a branch switch or a boundary switch, the lower port of the outgoing line switch of the remaining bus lines of this station will be used as the photovoltaic auxiliary aggregation point of the remaining bus lines of this station, and the upper port of this switch will be used as the photovoltaic auxiliary aggregation point of this line.

[0199] Furthermore, the setting value interval determination subunit is specifically used for:

[0200] Modeling the distributed photovoltaic in the target distribution network according to the external absorption aggregation unit, the auxiliary aggregation unit, the device parameters and the photovoltaic effect, and determining a constant current source aggregation model corresponding to the target distribution network;

[0201] A setting calculation is performed according to the constant current source aggregation model to determine whether there is a setting value range.

[0202] Furthermore, the device also includes:

[0203] The conventional load modeling module is used to determine the first modeling method based on the comparison result between the distributed photovoltaic access amount and the preset threshold value, and the distributed photovoltaic parameter management data. If the first modeling method is determined to be the conventional load modeling method, each distributed photovoltaic in the target distribution network is used as a load unit, and the target distribution network is modeled and set in combination with the equipment parameters to determine the setting value range.

[0204] The setting calculation modeling device of the active distribution network in the embodiment of the present invention can be a device, or a component, an integrated circuit, or a chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and the non-mobile electronic device can be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0205] The active power distribution network setting calculation modeling device in the embodiment of the present invention may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0206] The setting calculation modeling device for the active distribution network provided in the embodiment of the present invention can realize each process implemented by the above method embodiment, and has the functional modules and beneficial effects corresponding to the execution method.

[0207] Embodiment 5

[0208] Fig.13A schematic diagram of a device 10 that can be used to implement an embodiment of the present application is shown. The device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0209] like Fig.13 As shown, the device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the device 10 can also be stored. The processor 11, ROM 12 and RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0210] A number of components in the device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0211] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the setting calculation modeling method of the active distribution network.

[0212] In some embodiments, the setting calculation modeling method of the active power distribution network can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the setting calculation modeling method of the active power distribution network described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the setting calculation modeling method of the active power distribution network in any other appropriate manner (for example, by means of firmware).

[0213] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0214] The computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer programs are executed by the processor, the functions / operations specified in the flow charts and / or block diagrams are implemented. The computer programs may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0215] In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device or equipment. A computer readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. A more specific example of a machine readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0216] To provide interaction with a user, the systems and techniques described herein can be implemented on a device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0217] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0218] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of traditional physical hosts and VPS servers, which are difficult to manage and have weak business scalability.

[0219] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution of this application can be achieved, and this document is not limited here.

[0220] The above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from these are still within the scope of protection of the invention.

Claims

1. A setting calculation modeling method for an active distribution network, characterized in that: The method comprises: Obtain distributed photovoltaic parameter management data, distributed photovoltaic access capacity and equipment parameters of the target distribution network; Determine a first modeling method according to a comparison result between the distributed photovoltaic access amount and a preset threshold value, and the distributed photovoltaic parameter management data; wherein the first modeling method includes a conventional load modeling method and a current source modeling method; If it is determined that the first modeling method is the current source modeling method, the second modeling method is determined according to the preset priority, and the target distribution network is modeled and set based on the second modeling method and the equipment parameters to determine the setting value range; wherein, the current source modeling method includes a controlled current source fine modeling method, a constant current source fine modeling method and a constant current source aggregate modeling method; the preset priorities are, from low to high, the controlled current source fine modeling method, the constant current source fine modeling method and the constant current source aggregate modeling method.

2. The method according to claim 1, characterized in that According to the comparison result between the distributed photovoltaic access amount and the preset threshold value, and the distributed photovoltaic parameter management data, a first modeling method is determined, including: If the distributed photovoltaic parameter management data meets the preset standard, and the distributed photovoltaic access amount is greater than the preset threshold, determining that the first modeling method is the current source modeling method; Otherwise, the first modeling method is determined to be a conventional load modeling method.

3. The method according to claim 1, characterized in that: Determining a second modeling method according to a preset priority, modeling and setting calculation are performed on the target distribution network based on the second modeling method and the device parameters, and determining a setting value range, including: If the second modeling method is determined to be a constant current source aggregation modeling method according to the preset priority, the target distribution network is modeled and set based on the constant current source aggregation modeling method and the device parameters to determine whether there is a setting value interval; If not, determining that the second modeling method is a constant current source fine modeling method, and modeling and setting calculation are performed on the target distribution network based on the constant current source fine modeling method and the device parameters to determine whether there is a setting value interval; If it still does not exist, determine that the second modeling method is a controlled current source fine modeling method, and based on the controlled current source fine modeling method and the equipment parameters, model and set the target distribution network to determine whether there is a setting value range.

4. The method according to claim 3, characterized in that Modeling and setting calculation are performed on the target distribution network based on the constant current source fine modeling method and the device parameters to determine whether there is a setting value range, including: Modeling the target distribution network based on the constant current source fine modeling method and the device parameters to obtain a constant current source fine model of the target distribution network; Determining the distributed photovoltaic units involved in the setting calculation in the constant current source fine model according to the photovoltaic effect, the fault point and the observation point; A setting calculation is performed according to the distributed photovoltaic units involved in the setting calculation and the equipment parameters to determine whether there is a setting value range.

5. The method according to claim 4, characterized in that According to the photovoltaic effect, the fault point and the observation point, the distributed photovoltaic units participating in the setting calculation in the constant current source fine model are determined, including: If the photovoltaic effect is an external pumping effect, the distributed photovoltaic units between the fault point and the observation point are used as distributed photovoltaic units participating in the setting calculation; If the photovoltaic effect is an auxiliary effect, the distributed photovoltaic units outside the fault point and the observation point will be regarded as distributed photovoltaic units participating in the setting calculation.

6. The method according to claim 3, characterized in that Modeling and setting calculation are performed on the target distribution network based on the controlled current source fine modeling method and the device parameters to determine whether there is a setting value range, including: Modeling the target distribution network based on the controlled current source fine modeling method and the device parameters to obtain a controlled current source fine model of the target distribution network; Determining the distributed photovoltaic units participating in the setting calculation in the controlled current source fine model according to the photovoltaic effect, the fault point and the observation point; A setting calculation is performed according to the distributed photovoltaic units involved in the setting calculation and the equipment parameters to determine whether there is a setting value range.

7. The method according to claim 6, characterized in that According to the photovoltaic effect, the fault point and the observation point, the distributed photovoltaic units participating in the setting calculation in the controlled current source fine model are determined, including: If the photovoltaic effect is an external pumping effect, the distributed photovoltaic units between the fault point and the observation point are used as distributed photovoltaic units participating in the setting calculation; If the photovoltaic effect is an auxiliary effect, the distributed photovoltaic units outside the fault point and the observation point will be regarded as distributed photovoltaic units participating in the setting calculation.

8. The method according to claim 3, characterized in that Modeling and setting calculation are performed on the target distribution network based on the constant current source aggregation modeling method and the device parameters to determine whether there is a setting value range, including: Analyze the external draw function of each switch in the target distribution network, determine the external draw aggregation points of the distributed photovoltaics after each switch, and aggregate the distributed photovoltaics after each switch into external draw aggregation units at each external draw aggregation point; Analyze the boosting effect of each switch in the target distribution network, determine the boosting aggregation points of the distributed photovoltaics before each switch, and aggregate the distributed photovoltaics before each switch into boosting aggregation units at each boosting aggregation point; Modeling and setting calculation are performed according to the external polymerization unit, the auxiliary polymerization unit, the equipment parameters and the photovoltaic effect to determine whether there is a setting value range.

9. The method according to claim 8, characterized in that Analyzing the external draw effect of each switch in the target distribution network and determining the external draw aggregation point of the distributed photovoltaic behind each switch, including: For each switch in the target distribution network, according to the short-circuit current provided by the distributed photovoltaic, the bus equivalent impedance, the impedance between the distributed photovoltaic access point and the bus, the impedance between the distributed photovoltaic access point and the fault point, and the voltage at the distributed photovoltaic access point, determine the change in the external short-circuit current of each switch in the target distribution network when the distributed photovoltaic is at different access points; The access point corresponding to the maximum external short-circuit current change is used as the external aggregation point.

10. The method according to claim 9, characterized in that The access point corresponding to the maximum external short-circuit current change is used as the external aggregation point, including: If the switch is an outgoing line switch, a branch switch or a boundary switch, the lower port of the switch is used as the external extraction aggregation point.

11. The method according to claim 8, characterized in that Analyzing the boosting effect of each switch in the target distribution network and determining the boosting aggregation point of the distributed photovoltaic before each switch, including: For the distributed photovoltaic power generation of other lines, the lower port of the outgoing line switch of other lines is used as the auxiliary aggregation point for the distributed photovoltaic power generation of other lines to the switch of this line; For the distributed photovoltaics of this line, the change in the auxiliary short-circuit current of the switch at different access points of the distributed photovoltaics of this line is determined according to the short-circuit current provided by the distributed photovoltaics, the bus equivalent impedance, the impedance between the distributed photovoltaic access point and the bus, and the impedance between the distributed photovoltaic access point and the fault point; the access point corresponding to the maximum auxiliary short-circuit current change is used as the auxiliary aggregation point.

12. The method according to claim 11, characterized in that The access point corresponding to the maximum boost short-circuit current change is used as the boost aggregation point, including: If the switch is an outgoing switch, the lower port of the outgoing switch of the remaining bus lines of the station will be used as the photovoltaic boosting aggregation point of the remaining bus lines of the station; If the switch is a branch switch or a boundary switch, the lower port of the outgoing line switch of the remaining bus lines of this station will be used as the photovoltaic auxiliary aggregation point of the remaining bus lines of this station, and the upper port of this switch will be used as the photovoltaic auxiliary aggregation point of this line.

13. The method according to claim 8, characterized in that Modeling and setting calculation are performed according to the external polymerization unit, the auxiliary polymerization unit, the equipment parameters and the photovoltaic effect to determine whether there is a setting value range, including: Modeling the distributed photovoltaic in the target distribution network according to the external absorption aggregation unit, the auxiliary aggregation unit, the device parameters and the photovoltaic effect, and determining a constant current source aggregation model corresponding to the target distribution network; A setting calculation is performed according to the constant current source aggregation model to determine whether there is a setting value range.

14. The method according to claim 1, characterized in that After determining the first modeling method according to the comparison result between the distributed photovoltaic access amount and the preset threshold value and the distributed photovoltaic parameter management data, the method further includes: If it is determined that the first modeling method is a conventional load modeling method, each distributed photovoltaic in the target distribution network is used as a load unit, and the target distribution network is modeled and set in combination with the equipment parameters to determine the setting value range.

15. A setting calculation modeling device for an active distribution network, used to implement the setting calculation modeling method for an active distribution network as claimed in any one of claims 1 to 14, characterized in that: The device comprises: Parameter acquisition module, used to obtain distributed photovoltaic parameter management data, distributed photovoltaic access quantity and equipment parameters of the target distribution network; A modeling method determination module is used to determine a first modeling method according to a comparison result between the distributed photovoltaic access amount and a preset threshold value, and the distributed photovoltaic parameter management data; wherein the first modeling method includes a conventional load modeling method and a current source modeling method; A modeling and setting calculation module is used to determine the second modeling method according to a preset priority if it is determined that the first modeling method is the current source modeling method, model and set the target distribution network based on the second modeling method and the equipment parameters, and determine the setting value range; wherein the current source modeling method includes a controlled current source fine modeling method, a constant current source fine modeling method and a constant current source aggregate modeling method; the preset priorities are, from low to high, the controlled current source fine modeling method, the constant current source fine modeling method and the constant current source aggregate modeling method.

16. An electronic device, characterized in that: The device comprises: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the setting calculation modeling method for the active distribution network described in any one of claims 1 to 14.

17. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the setting calculation modeling method for an active power distribution network according to any one of claims 1 to 14 when executed.

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