An analysis method, device and equipment for the influence of charging facilities on a power distribution network and a medium

Abstract

The application discloses a kind of charging facilities access to the analysis method, device, equipment and medium of influence of distribution network, applied to distribution network technical field, to solve the problem that actual influence of charging facilities cannot accurately reflect distribution network in relevant technology, for each access scene in the pre-established multiple different access scenes, according to the distribution network structure corresponding to access scene, charging load parameter and charging facility grid-connected control strategy, the simulation model of charging facility access distribution network is established;According to simulation model, obtain the distribution network operating data under corresponding access scene;Distribution network operating parameter includes at least two different types of index data;According to the distribution network operating parameter respectively corresponding to each access scene, the influence law of charging facility access distribution network is analyzed and key influencing factor is determined;The accuracy of influence analysis of charging facility access distribution network and the accuracy of key influencing factor identification are improved, so as to formulate more comprehensive and accurate strategy.

Description

Technical Field

[0001] This invention relates to the field of power distribution network technology, and in particular to a method, apparatus, equipment and medium for analyzing the impact of charging facility access on power distribution networks. Background Technology

[0002] With the rapid development of the electric vehicle industry, users' demand for convenient charging is increasing. High-power charging facilities, which can significantly shorten charging time, are gradually becoming an important load component in urban power distribution networks. However, high-power charging facilities are characterized by high single-gun power, large station capacity, and strong randomness in access location and time. Their large-scale access will have a significant impact on the original load characteristics, power quality, and power supply reliability of the power distribution network. If key influencing factors cannot be accurately assessed and identified, it may lead to problems such as line and transformer overload, voltage exceeding limits, and aggravated harmonic distortion, seriously threatening the safe and stable operation of the power distribution network. Therefore, quantitatively analyzing the multi-dimensional impact of high-power charging facility access on the power distribution network and identifying key influencing factors is of great significance for formulating effective response strategies and ensuring the efficient and stable operation of the power distribution network.

[0003] Currently, there is a certain research foundation for analyzing the impact of electric vehicle charging infrastructure on power distribution networks. For example, existing patents propose dynamic load balancing power supply systems for charging pile clusters to address transformer losses and harmonic pollution caused by the randomness of charging behavior; other studies assess the impact of large-scale charging pile cluster access through power flow calculation and spatiotemporal distribution prediction; in addition, some patents also involve methods for overload risk assessment of power distribution network branches and quantitative analysis of the impact on urban power distribution networks. However, existing solutions lack analysis of differentiated impacts under multiple scenarios and comprehensive multi-dimensional analysis, making it difficult to accurately reflect the actual impact of charging facilities on the power distribution network. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus, equipment, and medium for analyzing the impact of charging facility access on the power distribution network. During use, these methods improve the accuracy of analyzing the impact of charging facility access on the power distribution network and the accuracy of identifying key influencing factors, providing a more comprehensive and accurate basis for formulating targeted response strategies.

[0005] To address the aforementioned technical problems, the embodiments of the present invention provide the following technical solutions: This invention provides a method for analyzing the impact of charging facility access on the power distribution network, including: Pre-determine various charging facility access locations, various transformer load rates, and various optimization measures; By combining various charging facility access locations, various transformer load rates, and various optimization measures, a variety of different access scenarios can be obtained; For each of the various access scenarios, a simulation model for the charging facility's access to the distribution network is established based on the distribution network structure, charging load parameters, and charging facility grid connection control strategy corresponding to the access scenario. Based on the simulation model, the power distribution network operation data under the corresponding access scenario is obtained; wherein, the power distribution network operation parameters include at least two different types of indicator data; Based on the power distribution network operation parameters corresponding to each of the access scenarios, the impact of the charging facility's access to the power distribution network is analyzed and key influencing factors are determined.

[0006] In one implementation, a simulation model for charging facility access to the distribution network is established based on the distribution network structure, charging load parameters, and charging facility grid connection control strategy corresponding to the access scenario, including: Construct the power distribution network structure for the target area and configure the basic parameters of the power distribution network structure; Construct a basic load model of the distribution network in the target area; A charging facility model is constructed, which includes a grid-side access unit, a power conversion unit, and a charging output unit; wherein, the power conversion unit adopts a constant power control strategy. The basic load model of the distribution network and the charging facility model are connected to the corresponding target nodes in the distribution network structure, and the corresponding electrical topology connections are made to obtain a simulation model of the charging facility connected to the distribution network.

[0007] In one embodiment, the grid-side access unit includes a grid circuit breaker and an isolation transformer; The power conversion unit adopts a two-stage topology, in which the front stage is an AC / DC rectifier module and the rear stage is a DC / DC converter module. The charging output unit includes an electric vehicle battery model and a battery management system.

[0008] In one embodiment, the power conversion unit further includes a filter inductor and a filter capacitor, and the power conversion unit integrates a constant power control algorithm consisting of a phase-locked loop, an outer power loop, and an inner current loop.

[0009] In one implementation, obtaining the distribution network operation data under the corresponding access scenario based on the simulation model includes: Based on the simulation model, obtain the steady-state values ​​of active power, reactive power, and apparent power of key nodes in the corresponding access scenario; Obtain the effective voltage value and three-phase voltage waveform for each node in the power distribution network; Obtain the effective value of the line current and the three-phase current waveform of the critical circuit; Obtain the effective value of the current and the three-phase current waveform on both sides of the transformer corresponding to the charging facility; The three-phase voltage waveforms and three-phase current waveforms are subjected to spectrum analysis by Fast Fourier Transform to obtain the effective values ​​of voltage, each harmonic voltage, the fundamental current, and each harmonic current. Based on the effective values ​​of the fundamental voltage and each harmonic voltage, the total harmonic distortion rate of voltage and the harmonic voltage content are calculated. Similarly, based on the effective values ​​of the fundamental current and each harmonic current, the total harmonic distortion rate of current and the harmonic current content are calculated.

[0010] In one implementation, after obtaining the distribution network operation data for the corresponding access scenario based on the simulation model, the method further includes: The impact of the charging facilities on the distribution network is assessed based on the distribution network operation data.

[0011] In one implementation, assessing the impact of the charging facility on the distribution network based on the distribution network operation data includes: The effective voltage value corresponding to each node is compared with the nominal voltage of the system, the voltage deviation percentage corresponding to the node is calculated, and the voltage deviation percentage is compared with a preset deviation limit to identify the nodes with voltage quality problems. For each node in the distribution network, the voltage drop amplitude and duration of the node are recorded, and it is determined whether the voltage drop amplitude of the node is within a preset amplitude range and whether the duration is within a preset duration range, so as to determine the node where the voltage sag occurs and the severity of the sag. The effective value of the line current of the critical line is converted into the line load rate, and it is determined whether the line load rate exceeds the preset line load rate limit. The effective values ​​of the current on both sides of the transformer are converted into the transformer load rate, and it is determined whether the transformer load rate exceeds the preset transformer load rate limit. The total harmonic distortion rate of voltage, the harmonic voltage content rate, the total harmonic distortion rate of current, and the harmonic current content rate are compared with the corresponding preset limits. Based on the comparison results, it is determined whether there are nodes or lines with excessive harmonics, and the severity of harmonic distortion of the corresponding nodes or lines is determined.

[0012] In one implementation, based on the distribution network operating parameters corresponding to each of the access scenarios, the impact of the charging facility's access to the distribution network is analyzed and key influencing factors are determined, including: The control variable method was used to conduct a horizontal comparison of various indicator data in the power distribution network operation data under each access scenario, and to analyze the change patterns of indicators corresponding to the charging facility access location, transformer load rate and optimization measures. Based on the changing patterns of indicators corresponding to charging facility access location, transformer load rate, and optimization measures, the influence weights of charging facility access location, transformer load rate, and optimization measures on each indicator data are determined. Based on the influence weights of charging facility access location, transformer load rate, and optimization measures on each indicator data, key influencing factors are identified. Based on the changing patterns of the key influencing factors on various indicator data, a response strategy for charging facility access is generated.

[0013] This application also discloses an analysis device for the impact of charging facility access on the power distribution network, comprising: A module is established to create a simulation model of charging facility access to the distribution network for each of a variety of pre-established access scenarios, based on the distribution network structure, charging load parameters, and charging facility grid connection control strategy corresponding to the access scenario. The acquisition module is used to acquire power distribution network operation data under the corresponding access scenario based on the simulation model; wherein, the power distribution network operation parameters include at least two different types of indicator data; The analysis module is used to analyze the impact of the charging facility's connection to the distribution network and determine the key influencing factors based on the distribution network operation parameters corresponding to each of the access scenarios.

[0014] This application also discloses an electronic device, including: Memory, used to store computer programs; A processor is used to execute the computer program to implement the steps of the analysis method for the impact of charging facility access on the power distribution network as described above.

[0015] This application also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the analysis method for the impact of charging facility access on the power distribution network as described above.

[0016] As can be seen from the above technical solutions, the embodiments of the present invention have the following advantages: This invention provides a method for analyzing the impact of charging facility access on a power distribution network, comprising: pre-determining multiple different charging facility access locations, multiple different transformer load rates, and multiple different optimization measures; combining the multiple different charging facility access locations, multiple different transformer load rates, and multiple different optimization measures to obtain multiple different access scenarios; for each of the multiple different access scenarios, establishing a simulation model of charging facility access to the power distribution network based on the power distribution network structure, charging load parameters, and charging facility grid connection control strategy corresponding to the access scenario; obtaining power distribution network operation data under the corresponding access scenario based on the simulation model; wherein, the power distribution network operation parameters include at least two different types of indicator data; and analyzing the impact law of charging facility access to the power distribution network and determining key influencing factors based on the power distribution network operation parameters corresponding to each access scenario.

[0017] Therefore, this application establishes multiple access scenarios based on various charging facility access locations, transformer load rates, and optimization measures. For each access scenario, a corresponding simulation model is built according to the distribution network structure, charging load parameters, and charging facility grid connection control strategy. The application also comprehensively compares and analyzes the impact of charging facility access on the distribution network, including at least two types of indicator data, obtained under each access scenario, and identifies key influencing factors. This application overcomes the shortcomings of existing technologies, such as the lack of multi-scenario differentiated analysis and multi-dimensional comprehensive analysis, and the difficulty in accurately reflecting the actual impact of charging facilities on the distribution network. It achieves multi-scenario, multi-dimensional quantitative assessment of the impact of charging facility access on the distribution network and identification of key influencing factors, improving the accuracy of the analysis of the impact of charging facility access on the distribution network and the accuracy of identifying key influencing factors. This provides a more comprehensive and accurate basis for formulating targeted response strategies.

[0018] Furthermore, the present invention also provides a corresponding implementation device, electronic device, and computer-readable storage medium for the analysis method of the impact of charging facility access on the power distribution network, which further makes the method more practical. The device, electronic device, and computer-readable storage medium have corresponding advantages. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the prior art and embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1A flowchart illustrating an analysis method for the impact of charging facility access on the power distribution network, provided by an embodiment of the present invention; Figure 2 A schematic diagram illustrating the process of constructing a simulation model for connecting a charging facility to a power distribution network, as provided in an embodiment of the present invention; Figure 3 This invention provides a topology diagram of an IEEE 33-node distribution network after access to charging facilities. Figure 4 This invention provides a comparison diagram of voltage distribution at various nodes in the power distribution network before and after a charging facility is connected to the network. Figure 5 This invention provides a comparison diagram of voltage distribution at distribution network nodes under different load rates and optimization measures. Figure 6 A harmonic analysis diagram of the line head current provided in an embodiment of the present invention; Figure 7 A schematic diagram of the structure of an analysis device for the impact of charging facility access on the power distribution network provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention; Figure 9 This is a schematic diagram of the structure of a computer-readable storage medium provided in an embodiment of the present invention. Detailed Implementation

[0021] This invention provides a method, apparatus, equipment, and medium for analyzing the impact of charging facility access on power distribution networks. During use, these methods improve the accuracy of analyzing the impact of charging facility access on power distribution networks and the accuracy of identifying key influencing factors, providing a more comprehensive and accurate basis for formulating targeted response strategies.

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a method for analyzing the impact of charging facility access on a power distribution network, provided by an embodiment of the present invention. The method includes the following processes S110 to S140.

[0024] S110: Predetermine various charging facility access locations, various transformer load rates, and various optimization measures.

[0025] It should be noted that, in order to systematically analyze the differentiated impact of charging facility access on the distribution network and identify key influencing factors in this application embodiment, various different access scenarios can be pre-constructed. Specifically, various different charging facility access locations, various different transformer load rates, and various different optimization measures can be determined first. Among them, the charging facility access location may include, but is not limited to, the beginning, middle, and end of the feeder; the transformer load rate may include, but is not limited to, operating conditions such as 60% (medium load), 80% (heavy load), and 100% (full load); the optimization measures may include, but are not limited to, the deployment of reactive power compensation devices, the connection of distributed photovoltaic systems, and the coordinated operation of the two.

[0026] S120: Combining various charging facility access locations, various transformer load rates, and various optimization measures to obtain various access scenarios.

[0027] It is understood that, in the embodiments of this application, after determining various different charging facility access locations, various different transformer load rates, and various different optimization measures, these various charging facility access locations, various different transformer load rates, and various different optimization measures can be further combined to obtain various different access scenarios. For example, when the charging facility access locations include three types (A1, A2, A3), the transformer load rates include three types (B1, B2, B3), and the optimization measures include four types (C1, C2, C3, C4), 3×3×4=36 different access scenarios can be obtained through permutation and combination.

[0028] In practical applications, all or some typical combinations can be selected to construct scenarios according to actual needs. For example, the typical scenario combinations used in this application embodiment are shown in Table 1, where A1-B2-C1 represents the baseline scenario with access location A1, transformer load rate B2 (80%), and no optimization measures; A1-B1-C1 represents the comparative scenario with the transformer load rate reduced to B1 (60%) based on the baseline scenario; and A1-B2-C2 represents the optimized scenario with distributed photovoltaic access based on the baseline scenario. Through the above method, this application embodiment can systematically construct multiple scenario combinations covering different access locations, different load rates, and different optimization measures, providing a complete scenario foundation for subsequent horizontal comparison using the control variable method, analyzing the influence of various factors on the distribution network operation indicators, and identifying key influencing factors, ensuring the comprehensiveness and systematic nature of multi-scenario differentiated analysis.

[0029] Table 1. Multi-access scenario situation table

[0030] S130: For each of the various access scenarios, a simulation model for the charging facility's access to the distribution network is established based on the distribution network structure, charging load parameters, and grid connection control strategy of the charging facility corresponding to the access scenario.

[0031] It should be noted that, in this embodiment of the application, after establishing multiple different access scenarios, the distribution network structure, charging load parameters and charging facility grid connection control strategy corresponding to each access scenario can be determined. Then, based on the distribution network structure, charging load parameters and charging facility grid connection control strategy corresponding to each access scenario, a simulation model of the charging facility accessing the distribution network corresponding to that access scenario can be established.

[0032] S140: Based on the simulation model, obtain the distribution network operation data under the corresponding access scenario; among which, the distribution network operation parameters include at least two different types of indicator data.

[0033] In this application embodiment, for each access scenario, after completing the simulation model of the charging facility accessing the distribution network corresponding to that access scenario, simulation can be run on the simulation model to obtain the distribution network operation data under that access scenario. The obtained distribution network operation parameters include at least two different types of indicator data, such as at least two of voltage indicators, current indicators, power indicators, and harmonic indicators.

[0034] S150: Based on the distribution network operation parameters corresponding to each access scenario, analyze the impact of charging facilities accessing the distribution network and determine the key influencing factors.

[0035] In this embodiment, after obtaining the distribution network operation parameters corresponding to each access scenario, the distribution network operation data of these access scenarios can be compared and analyzed horizontally to analyze the impact of charging facilities accessing the distribution network and determine key influencing factors. Specifically, each access scenario can be established based on factors such as the location of the charging facility access, transformer load rate, and optimization measures.

[0036] Specifically, firstly, the controlled variable method can be used to conduct a horizontal comparison of various indicators in the distribution network operation data under different access scenarios, analyzing the changing patterns of indicators corresponding to the charging facility access location, transformer load rate, and optimization measures. Secondly, based on the changing patterns of indicators corresponding to the charging facility access location, transformer load rate, and optimization measures, the influence weights of each indicator can be determined. Specifically, the influence weights can be determined by calculating the rate of change of each factor before and after the change; the greater the rate of change, the higher the influence weight of the corresponding indicator. Then, based on the influence weights of the charging facility access location, transformer load rate, and optimization measures on each indicator, the key influencing factors that significantly affect the distribution network operation indicators can be identified.

[0037] Therefore, this application establishes multiple access scenarios based on various charging facility access locations, transformer load rates, and optimization measures. For each access scenario, a corresponding simulation model is built according to the distribution network structure, charging load parameters, and charging facility grid connection control strategy. The application also comprehensively compares and analyzes the impact of charging facility access on the distribution network, including at least two types of indicator data, obtained under each access scenario, and identifies key influencing factors. This application overcomes the shortcomings of existing technologies, such as the lack of multi-scenario differentiated analysis and multi-dimensional comprehensive analysis, and the difficulty in accurately reflecting the actual impact of charging facilities on the distribution network. It achieves multi-scenario, multi-dimensional quantitative assessment of the impact of charging facility access on the distribution network and identification of key influencing factors, improving the accuracy of the analysis of the impact of charging facility access on the distribution network and the accuracy of identifying key influencing factors. This provides a more comprehensive and accurate basis for formulating targeted response strategies.

[0038] Based on the above embodiments, the embodiments of this application will further explain and optimize the technical solution: In one implementation, please refer to Figure 2 The implementation process of S130 above may include the following steps S210 to 240: S210: Construct the distribution network structure of the target area and configure the basic parameters of the distribution network structure.

[0039] Specifically, the target area (i.e. the typical area to be analyzed) can be determined in advance, and then the distribution network structure of the target area and the basic parameters of the distribution network structure can be constructed, including topological connection relationship, line rated voltage level, line resistance and reactance, transformer rated capacity and turns ratio, transformer connection group, etc.

[0040] In this embodiment, the IEEE 33-node distribution system can be used as a typical distribution network model. Its topology, line parameters and basic load parameters are all based on standard example data. The rated voltage level of the line is set to 10kV, node 1 is the balancing node, and the remaining 32 nodes are load nodes.

[0041] S220: Build a basic load model of the distribution network in the target area.

[0042] Specifically, after constructing the distribution network structure and basic parameters of the target area, it is necessary to build a basic load model of the distribution network in the target area. In this embodiment, the basic load model includes three types of loads: residential load, commercial load, and industrial load, and it is necessary to configure the corresponding active power, reactive power, and load distribution nodes in the distribution network for each type of load.

[0043] In other words, the basic load model includes: the active power, reactive power and load distribution nodes in the distribution network corresponding to residential loads; the active power, reactive power and load distribution nodes in the distribution network corresponding to commercial loads; and the active power, reactive power and load distribution nodes in the distribution network corresponding to industrial loads.

[0044] S230: Build a charging facility model, which includes a grid-side access unit, a power conversion unit, and a charging output unit; among them, the power conversion unit adopts a constant power control strategy.

[0045] Specifically, after completing the construction of the distribution network structure and the basic load model of the target area, it is necessary to further build a charging facility model to simulate the electrical characteristics and operational behavior of high-power charging facilities after they are connected to the distribution network. In this embodiment, the charging facility model includes three main parts: a grid-side access unit, a power conversion unit, and a charging output unit. The power conversion unit adopts a constant power control strategy, and to meet the high-power charging demand, the entire power conversion unit adopts a modular parallel architecture, achieving a single-gun rated charging power output capacity of ≥250 kW through multiple modules connected in parallel.

[0046] In one embodiment, the grid-side access unit may include a grid circuit breaker and an isolation transformer; the power conversion unit may adopt a two-stage topology, in which the front stage is an AC / DC rectifier module and the rear stage is a DC / DC converter module; the charging output unit may include an electric vehicle battery model and a battery management system.

[0047] It should be noted that in practical applications, the front-end AC / DC rectifier module can adopt a three-phase VIENNA PFC rectifier topology. This VIENNA PFC rectifier topology has advantages such as high allowable power and low voltage stress, making it the mainstream choice for high-power charging modules. The rear-end DC / DC converter module can adopt a full-bridge LLC resonant converter topology, achieving high-efficiency power conversion through soft-switching technology. The charging output unit can include an electric vehicle battery model and a battery management system. This charging output unit can be used to simulate the dynamic response characteristics of an electric vehicle battery, adjusting the output voltage and current according to the battery state parameters. The electric vehicle battery model can be a lithium iron phosphate battery model.

[0048] The charging facility model in this embodiment consists of a grid-side access unit, a power conversion unit (including VIENNAPFC rectification and full-bridge LLC resonant converter), and a charging output unit. It is more suitable for analyzing the impact of the special attributes of high-power charging facilities (high single-gun power and large station capacity) on the distribution network after they are connected to the distribution network, ensuring that the simulation model can accurately simulate the electrical characteristics and impact behavior of high-power charging facilities.

[0049] In one embodiment, the power conversion unit further includes a filter inductor and a filter capacitor, and the power conversion unit integrates a constant power control algorithm consisting of a phase-locked loop, a power outer loop, and a current inner loop.

[0050] It should be noted that the power conversion unit in this embodiment may also include a filter inductor and a filter capacitor, and integrate a constant power control algorithm with a phase-locked loop, an outer power loop, and an inner current loop. By setting control parameters such as the proportional-integral coefficient of the dual loop, the switching frequency and dead time of the LLC converter, and inputting the three-phase voltage and current at the grid connection point and the charging power command with step changes, the control algorithm outputs a drive signal to control the power module to work, simulating the power step characteristics of high-power charging facilities during the charging start-up and shutdown phases.

[0051] In other words, the constant power control algorithm (i.e., constant power control strategy) in this embodiment can simulate the large power step change during the charging start-up and shutdown phases. Its amplitude and rate of change are dynamically adjusted according to different stages of the charging process, reflecting the impact characteristics of high-power charging facilities. In practical applications, the power conversion unit can track the grid connection point voltage phase in real time through a phase-locked loop, providing a reference phase for subsequent coordinate transformation. The outer power loop can calculate the current reference value of the inner current loop based on the set active power command and reactive power command. The inner current loop can adopt a feedforward decoupling control strategy to independently control the current on the d-axis (direct axis) and q-axis (quadrature axis). The inner current loop outputs a modulated switching transistor drive pulse, enabling the charging facility's output current to accurately track the command value, ensuring that the grid-connected power remains constant.

[0052] Specifically, the coordinate transformation method in the embodiments of this application may include: obtaining the fundamental phase angle of the power grid using a phase-locked loop. or frequency The three-phase voltage and three-phase current on the grid side in the three-phase symmetrical stationary coordinate system are transformed to a value consistent with the grid fundamental frequency. A synchronized rotating coordinate system, which has a d-axis and a q-axis.

[0053] Specifically, the power outer loop can calculate the current reference value of the current inner loop based on the set active power command and reactive power command, combined with the relationship between the power command and the current command. The relationship between the power command and the current command is as follows: ,in, This indicates a reference value for active power; the specific value can be set according to charging requirements. This represents the reactive power reference value, which is usually set to zero during electric vehicle charging mode. and These represent the d-axis and q-axis components of the grid connection point voltage, respectively. and These represent the d-axis and q-axis current reference values ​​for the inner current loop, respectively.

[0054] Specifically, in the process of independently controlling the current on the d-axis (direct axis) and q-axis (quadrature axis) in the aforementioned inner current loop, the control equation corresponding to the feedforward decoupling control strategy can be: ,in, and These represent the reference values ​​of the d-axis and q-axis output voltages on the AC side of the converter, respectively. and These represent the proportional gain and integral gain of the current loop, respectively. and These represent the d-axis and q-axis components of the output current, respectively. Indicates the angular frequency of the power grid; This indicates the AC side filter inductor.

[0055] S240: Connect the basic load model of the distribution network and the charging facility model to the corresponding target nodes in the distribution network structure, and make the corresponding electrical topology connections to obtain the completed simulation model of the charging facility connected to the distribution network.

[0056] Specifically, after completing the construction of the distribution network structure, the basic load model of the distribution network, and the charging facility model of the target area, it is necessary to connect the basic load model of the distribution network and the charging facility model to the corresponding target nodes in the distribution network structure and make the corresponding electrical topology connections, so as to obtain the completed simulation model of the charging facility connected to the distribution network.

[0057] For example, in this embodiment, to analyze the impact of high-power charging facility access, for the IEEE 33-node power distribution system, such as Figure 3 As shown, charging stations can be connected at nodes 8, 22, and 27 respectively, and these three charging stations are designated as Charging Station 1, Charging Station 2, and Charging Station 3. According to the design standards for electric vehicle charging and swapping facility systems (such as T / ASC 17-2021), when a charging station has high-capacity off-board chargers such as 240kW, 350kW, and 480kW, a dedicated transformer should be installed. Therefore, in this embodiment, all three charging stations are equipped with dedicated distribution transformers, with a uniform transformation ratio of 10kV / 0.4kV. Furthermore, to effectively suppress the third harmonic, the transformer connection group adopts the Dyn11 connection method. Considering the total power of the charging piles, load rate, power factor, and redundancy reserve, each charging station uses a high-capacity distribution transformer. The rated capacity of the transformer at Charging Station 1 is 2000kVA, the rated capacity at Charging Station 2 is 3150kVA, and the rated capacity at Charging Station 3 is 2500kVA. The distribution network topology diagram after connecting the high-power charging facilities can be referred to as shown in Figure 4.

[0058] In practical applications, during the construction of high-power charging facility models, the rated charging power of a single charging pile can be set to two specifications: 360kW and 480kW. The control strategy adopts constant power grid-connected control, and the control system consists of a phase-locked loop, a power outer loop, and a current inner loop. The operating condition is set with a transformer load rate of 80%, meaning the charging station operates at 80% of its distribution transformer's rated capacity. The overall power factor of the charging station is set to 0.98 (inductive). Therefore, the total power reference value for each charging station can be set as follows: Reference value P for total active power of charging station No. 1. ref1 =1568kW, reactive power reference value Q ref1 =318.4kvar; Charging Station P ref2 =2469.6kW, Q ref2 =501.5kvar; Charging Station P (No. 3) ref3 =1960kW, Q ref3 =398kvar.

[0059] In one implementation, the process of obtaining distribution network operation data under the corresponding access scenario based on the simulation model in S140 above may include: The steady-state values ​​of active power, reactive power, and apparent power of key nodes in the corresponding access scenario are obtained based on the simulation model. Obtain the effective voltage value and three-phase voltage waveform for each node in the power distribution network; Obtain the effective value of the line current and the three-phase current waveform of the critical circuit; Obtain the effective value of the current and the three-phase current waveform on both sides of the transformer corresponding to the charging facility; The three-phase voltage and current waveforms are analyzed by Fast Fourier Transform to obtain the effective values ​​of voltage, harmonic voltage, fundamental current, and harmonic current. Based on the effective values ​​of the fundamental voltage and harmonic voltage, the total harmonic distortion rate and the harmonic voltage content are calculated. Similarly, based on the effective values ​​of the fundamental current and harmonic current, the total harmonic distortion rate and the harmonic current content are calculated.

[0060] It should be noted that, in this application embodiment, for each access scenario, after completing the simulation model of the charging facility accessing the distribution network corresponding to the access scenario and running the simulation, it is necessary to obtain the distribution network operation data under the access scenario from the simulation model for subsequent impact assessment and key factor identification.

[0061] Specifically, in this embodiment, the steady-state values ​​of active power, reactive power, and apparent power of key nodes in the corresponding access scenario can be obtained first based on the simulation model. These key nodes include the grid connection point of high-power charging facilities, the starting node of a single feeder, and the bus node where multiple feeders converge. These key nodes can be used to analyze the impact of charging facility access on local line loads and the total regional load. For example, for the IEEE 33-node distribution system, key nodes may include node 1 (the balancing node at the starting end of the feeder), node 8 (the grid connection point of charging station 1), node 22 (the grid connection point of charging station 2), node 27 (the grid connection point of charging station 3), and node 18 (the end node of the feeder), etc. Furthermore, the dynamic power change amplitude during the charging start-up and shutdown phases of the key nodes can also be obtained to analyze the impact of charging facility access on local line loads and the total regional load.

[0062] In this embodiment, the effective voltage values ​​and three-phase voltage waveforms corresponding to all nodes in the distribution network can be further obtained. Specifically, the effective line voltage value and three-phase voltage waveform of each node in the distribution network are monitored, and the voltage deviations of the feeder end nodes, the charging facility grid connection points, and their upstream and downstream nodes are recorded to evaluate voltage stability. For example, the effective voltage values ​​of nodes 1 to 33, as well as the voltage drop waveforms of charging facility grid connection points such as nodes 8, 22, and 27 at the moment of charging start-up, can be recorded.

[0063] In this embodiment, the effective values ​​of line current and three-phase current waveforms of critical lines can be further obtained. These critical lines include the high-voltage and low-voltage branches of the high-power charging station's dedicated transformer and the main lines of the distribution network. For example, the effective values ​​of line current and three-phase current waveforms of the high-voltage and low-voltage branches of the charging station's dedicated transformer, as well as the effective values ​​of line current and three-phase current waveforms of each main line of the distribution network (such as the lines between nodes 1-2, 2-3, etc.), can be obtained to monitor the line and transformer load rates and assess overload risks.

[0064] In this embodiment, the effective current values ​​and three-phase current waveforms on both sides of the transformer corresponding to the charging facility can be further obtained. Specifically, at each charging station access point, the effective current values ​​and three-phase current waveforms on the high-voltage and low-voltage sides of the dedicated distribution transformer are obtained. For example, for charging station No. 1, the effective current values ​​and three-phase current waveforms on both the high-voltage and low-voltage sides of its 2000kVA transformer are obtained; for charging station No. 2, the effective current values ​​and three-phase current waveforms on both the high-voltage and low-voltage sides of its 3150kVA transformer are obtained; and for charging station No. 3, the effective current values ​​and three-phase current waveforms on both the high-voltage and low-voltage sides of its 2500kVA transformer are obtained, so that the transformer load rate can be calculated and the transformer overload risk can be assessed based on these data.

[0065] In addition, in this embodiment of the application, the three-phase voltage waveforms and the three-phase current waveforms can be subjected to spectrum analysis by fast Fourier transform to obtain the effective value of voltage, the effective value of each harmonic voltage, the effective value of fundamental current, and the effective value of each harmonic current. Based on the effective value of fundamental voltage and the effective value of each harmonic voltage, the total harmonic distortion rate of voltage and the content rate of each harmonic voltage are calculated. Based on the effective value of fundamental current and the effective value of each harmonic current, the total harmonic distortion rate of current and the content rate of each harmonic current are calculated to quantify the degree of harmonic distortion.

[0066] Specifically, the Fast Fourier Transform (FFT) is a mathematical method for converting a time-domain signal into a frequency-domain signal, for a discrete sequence of length N. Its discrete Fourier transform is: ,in, Represents the time domain The signal amplitude at each sampling point; This represents the total number of sampling points within one period; Represents the discrete frequency index, corresponding to the first frequency. Second harmonics; Indicates the first The complex spectral components corresponding to the subharmonics, with their real and imaginary parts representing the amplitudes of the cosine and sine components of the subharmonics, respectively; Represents the imaginary unit; This represents the rotation factor. In the embodiments of this application, it is represented by... The first one can be calculated Amplitude of subharmonics and phase .

[0067] In this embodiment, the total harmonic distortion rate is the ratio of the root-mean-square value of the harmonic content in a periodic alternating current quantity to the root-mean-square value of its fundamental component. The voltage total harmonic distortion rate... and total harmonic distortion of current The calculation formula is: ,in, Indicates the effective value of the fundamental voltage. Indicates the effective value of the fundamental current; Indicates the first RMS value of subharmonic voltage Indicates the first RMS value of subharmonic current; Indicates the harmonic order; Indicates the highest harmonic order.

[0068] In the embodiments of this application, the harmonic content of each harmonic is the ratio of the effective value of that harmonic to the effective value of the fundamental frequency, wherein the first harmonic content is... Subharmonic voltage content and the Subharmonic current content The calculation formula is: ,in, This represents the voltage content of the h-th harmonic. Indicates the first The content of subharmonic currents.

[0069] Through the above methods, the embodiments of this application can obtain multi-dimensional and multi-type distribution network operation parameters for each access scenario, including power indicators (i.e., active power, reactive power, apparent power), voltage indicators (i.e., effective voltage values ​​of each node and three-phase voltage waveforms), current indicators (i.e., critical line currents and currents on both sides of the transformer), and harmonic indicators (i.e., total harmonic distortion rate and harmonic content rate). This provides a comprehensive and accurate data foundation for subsequent impact assessment of charging facility access and identification of key influencing factors. The impact assessment may include voltage deviation assessment, voltage sag assessment, load rate assessment, harmonic distortion assessment, etc.

[0070] In one implementation, after obtaining the distribution network operation data for the corresponding access scenario based on the simulation model in S140 above, the method may further include: Assess the impact of charging facilities on the distribution network based on distribution network operation data.

[0071] It should be noted that, in this embodiment of the application, after obtaining the distribution network operation data for each access scenario, it is necessary to assess the impact of charging facility access on the distribution network based on this operation data, in order to determine whether the access of charging facilities causes the distribution network operation indicators to exceed the allowable range, thereby determining whether corresponding mitigation measures need to be taken. Specifically, assessing the impact of charging facilities on the distribution network may include assessing voltage deviation, voltage sag, line and transformer load rate, and harmonic distortion.

[0072] In one implementation, the process of assessing the impact of charging facilities on the distribution network based on distribution network operation data may include: (1) Compare the effective voltage value of each node with the nominal voltage of the system, calculate the voltage deviation percentage of the node, and compare the voltage deviation percentage with the preset deviation limit to identify the nodes with voltage quality problems.

[0073] It should be noted that, in this embodiment, the assessment of voltage deviation involves comparing the obtained effective voltage values ​​of each node with the system nominal voltage to calculate the voltage deviation percentage corresponding to the node. Specifically, the formula for calculating the voltage deviation percentage is: Voltage deviation percentage = (Node effective voltage value - System nominal voltage) / System nominal voltage × 100%. In practical applications, preset deviation limits can be set according to national standards. For example, according to GB / T 12325-2008, the voltage deviation of three-phase power supply of 20 kV and below should not exceed ±7% of the nominal voltage. Therefore, the preset deviation limits can be set to +7% and -7%. When the voltage deviation percentage of a node exceeds +7% or is lower than -7%, it is determined that the node has a voltage quality problem, and voltage regulation measures need to be taken.

[0074] (2) For each node in the distribution network, record the voltage drop amplitude and duration of the node, and determine whether the voltage drop amplitude of the node is within the preset amplitude range and whether the duration is within the preset duration range, so as to determine the node where the voltage sag occurs and the severity of the sag.

[0075] It should be noted that, in the embodiments of this application, the assessment of voltage sag can be performed on each node in the distribution network by recording the magnitude and duration of the voltage drop at that node, and further determining whether the magnitude of the voltage drop at that node is within a preset range and whether the duration is within a preset time range, thereby determining the node where the voltage sag occurs and the severity of the sag.

[0076] Specifically, the preset amplitude range in this application embodiment can be set according to national standards. For example, according to the definition in GB / T30137-2013, a voltage sag refers to the phenomenon where the root mean square value of the power frequency voltage at a certain point in a power system suddenly drops to 0.1pu-0.9pu and recovers to normal after a brief duration of 10 ms-1 min. Therefore, in practical applications, the preset amplitude range can be 0.1pu-0.9pu, and the preset duration range can be 10ms-1 min. When the voltage drop amplitude of a node is within the range of 0.1pu-0.9pu and the duration is within the range of 10ms-1 min, it is determined that a voltage sag event has occurred at that node. The severity of the sag can be graded and evaluated according to the sag depth and duration; for example, the smaller the sag amplitude, the more severe the sag, and the longer the duration, the more severe the sag. In addition, if a system fault occurs, it is also necessary to evaluate the impact of charging facility access on the voltage sag depth, duration, and recovery characteristics of each node in the distribution network during the fault and after the fault is cleared.

[0077] (3) Convert the effective value of the line current of the critical line into the line load rate and determine whether the line load rate exceeds the preset line load rate limit.

[0078] Specifically, in this embodiment of the application, for the assessment of line load rate, the effective value of the line current of the critical line can be converted into the line load rate, and then it can be further determined whether the line load rate exceeds the preset line load rate limit. The preset line load rate limit can be set according to industry standards. For example, according to DL / T 5542-2018, the normal operating load rate of a 10kV line should not exceed 80%. When the load rate of a critical line exceeds 80%, it can be determined that the critical line is in a heavy load state. At this time, the equipment is also in a heavy load state, and its overload risk needs to be monitored. The critical lines include the high-voltage side and low-voltage side branches of the high-power charging station special transformer, the main line of the distribution network, etc.

[0079] (4) Convert the effective values ​​of the current on both sides of the transformer into the transformer load rate, and determine whether the transformer load rate exceeds the preset transformer load rate limit.

[0080] Specifically, in this embodiment of the application, for the evaluation of transformer load rate, the effective value of the current on both sides of the transformer is converted into the transformer load rate, and then it is further determined whether the transformer load rate exceeds the preset transformer load rate limit. Specifically, the preset transformer load rate limit can be set according to national standards. For example, according to GB 51348-2019, the long-term working load rate of the distribution transformer should not be greater than 85%. Therefore, when the load rate of the transformer exceeds 85%, it can be determined that the transformer is in a heavy load state and its overload risk needs to be paid attention to. For example, in this embodiment of the application, the load rate of the transformer of charging station No. 1 is 99.7%, which exceeds the preset limit of 85%, and it is determined that the transformer has an overload risk. (5) The total harmonic distortion rate of voltage, the harmonic voltage content rate, the total harmonic distortion rate of current and the harmonic current content rate are compared with the corresponding preset limits, and the comparison results are used to determine whether there are nodes or lines with excessive harmonics, and to determine the severity of harmonic distortion of the corresponding nodes or lines.

[0081] It should be noted that, in the embodiments of this application, corresponding preset limits can be set for the total harmonic distortion rate of voltage, the content of each harmonic voltage, the total harmonic distortion rate of current, and the content of each harmonic current. Then, the total harmonic distortion rate of voltage, the content of each harmonic voltage, the total harmonic distortion rate of current, and the content of each harmonic current are compared with the corresponding preset limits to obtain the comparison results. Then, for each comparison result, it is determined whether there are nodes or lines with excessive harmonics, and the severity of harmonic distortion of the corresponding nodes or lines is determined.

[0082] Specifically, preset limits can be set according to national standards. For example, according to GB / T 14549-1993, the limit for the total harmonic distortion (THD) of 10kV public power grid voltage is 4.0%, the limit for the odd harmonic voltage content is 3.2%, and the limit for the even harmonic voltage content is 1.6%. The allowable value of harmonic current at the point of common coupling needs to be converted based on the reference short-circuit capacity. When the reference short-circuit capacity of the 10kV power grid is 100MVA, the allowable value for the 5th harmonic current is 20A. When the THD exceeds 4.0%, or the voltage content of a certain harmonic exceeds the corresponding limit, or the THD and current content of a certain harmonic exceed the corresponding limits, the node or line is judged to have a harmonic exceedance problem. The severity of harmonic distortion can be graded according to the magnitude of the exceedance; the greater the magnitude of the exceedance, the higher the severity. For example, in the embodiments of this application, the total harmonic distortion rate of the voltage at each node is within the allowable range of 4%, but the total harmonic distortion rate of the current at node 1 and the three charging station grid connection points is between 4% and 7%, exceeding the limit of 4.0%. It is determined that these nodes have harmonic exceedance problems and harmonic mitigation measures need to be taken.

[0083] For example, for a distribution system using the IEEE 33-bus system, the voltage curves corresponding to each node in the distribution network are as follows: Figure 4 As shown, the voltage distribution at the nodes before and after the charging facility was connected was compared. Figure 4 It can be seen that before the high-power charging facility was connected, the voltage of each node was higher than 0.94 pu, all within the allowable voltage deviation range; after connection, the voltage decreased overall, with an average voltage of 0.889 pu, showing a more obvious downward trend along the feeder, gradually decreasing from 1.05 pu at node 1 to 0.809 pu at the end node 18. In addition, the per-unit voltage values ​​of key nodes, the effective values ​​of the phase current on the low-voltage side of the transformer, and other data are shown in Table 2.

[0084] Table 2 Key Node Monitoring Data

[0085] As shown in Table 2, the voltage deviation at node 22 is -6.4%, which is still within the allowable deviation range. However, the voltage deviations at the grid connection points of charging stations Nodes 8 and 27, as well as at feeder terminal nodes such as Node 18, all significantly exceed the standard limit of ±7%. This indicates that the connection of high-power charging facilities not only affects the grid connection point voltage but also causes severe voltage drops at some terminal nodes, necessitating voltage support measures. Furthermore, the transformer current load rates at charging stations 1 and 3 reached 0.997 and 0.979, respectively. Although this embodiment sets the power load rate at 80%, the actual current increases accordingly to maintain constant power output because the grid connection point voltage is lower than the rated voltage. This phenomenon demonstrates that voltage drops increase the transformer's load current level, exacerbating the risk of equipment overload.

[0086] In terms of harmonic analysis, the total harmonic distortion rate of voltage at each node is within the allowable range of 4%. The total harmonic distortion rate of current at node 1 and the grid connection points of the three charging stations is between 4% and 7%, which is generally at a high level. This has an adverse impact on the power quality of the power grid and corresponding measures need to be taken to suppress and improve it.

[0087] In one implementation, the process of implementing S250 above may include the following steps.

[0088] (1) Using the control variable method, we compared the various indicators in the power distribution network operation data under different access scenarios, and analyzed the change patterns of the indicators corresponding to the charging facility access location, transformer load rate and optimization measures.

[0089] It should be noted that, in this embodiment, the controlled variable method can be used to compare various indicator data in the distribution network operation data under different access scenarios, and analyze the indicator change patterns corresponding to the charging facility access location, transformer load rate, and optimization measures. Specifically, the controlled variable method involves changing a certain factor while keeping other factors constant, observing the changes in various indicators, and thus analyzing the impact of that factor on the distribution network operation indicators.

[0090] In this embodiment of the application, based on the multi-scenario situation table shown in Table 1 above, multiple comparative scenarios are constructed. In Table 1, the factors include the charging facility access location (e.g., A1, A2, A3), transformer load rate (e.g., B1, B2, B3), and optimization measures (e.g., C1, C2, C3, C4). By combining different factors, multiple access scenarios are formed. For example, taking the baseline scenario A1-B2-C1 (access location A1, transformer load rate B2 i.e. 80%, no optimization measure C1) as a reference, two comparative scenarios are constructed: A1-B1-C1 (keeping the access location unchanged, optimization measures unchanged, and reducing the transformer load rate to 60%) and A1-B2-C2 (keeping the access location and load rate unchanged, and connecting distributed photovoltaic). The impact of distributed photovoltaic access and the reduction of transformer load rate on the distribution network are explored respectively.

[0091] Specifically, in scenario A1-B1-C1, keeping the connection location A1 and optimization measure C1 unchanged, the transformer load rate is reduced from B2 (80%) to B1 (60%) to analyze the impact of transformer load rate changes on distribution network operation indicators. In scenario A1-B2-C2, keeping the connection location A1 and transformer load rate B2 unchanged, distributed photovoltaic (PV) is connected (optimization measure C2) to analyze the impact of distributed PV connection on distribution network operation indicators.

[0092] In other words, by comparing the above scenarios horizontally, we can analyze the changing patterns of the indicators corresponding to each factor. For example, in scenario A1-B2-C2, distributed photovoltaic (PV) systems with a capacity of 2 MWp are connected to nodes 5, 7, 13, 21, and 28, respectively, and the PV output is set to peak power. Compared to the baseline scenario, scenario A1-B1-C1 reduces the transformer load rate to 60%, i.e., the load rate at charging station P1 is reduced to 60%. ref1 =1176 kW, Q ref1 =237.6 kvar; Charging Station No. 2 P ref2 =1852.2 kW, Q ref2 =375.1 kvar; Charging Station P ref3 =1470 kW, Q ref3 =297 kvar. The node voltage distribution in these three scenarios is as follows: Figure 5 As shown, Figure 5This is a comparison diagram of the voltage distribution at distribution network nodes under different load rates and optimization measures in the embodiments of this application. Figure 5 It can be seen that compared to the 80% load rate without optimization (baseline scenario), reducing the load rate to 60% improved the voltage at each node. The voltage at the end node 18 increased from 0.809 pu to 0.843 pu, but it was still below the lower limit of 0.93 pu, with an average voltage per unit of 0.914 pu. The voltage improvement effect was more significant after connecting photovoltaic (PV) power, with the lowest voltage occurring at node 22 (0.975 pu) and an average voltage reaching 0.999 pu. All node voltages were within ±7%. Therefore, reducing the transformer load rate can improve node voltage, but the improvement is limited. Connecting PV power can significantly improve voltage quality, but attention should be paid to the risk of exceeding the upper limit due to local voltage rises and the volatility of PV output.

[0093] In this embodiment, regarding current load, the power load rate of the charging station is set to 80% in the baseline scenario, but the actual current load rates of the transformers at charging stations 1, 2, and 3 are as high as 99.7%, 88.6%, and 97.9%, respectively. When the load rate drops to 60%, the voltage recovers, and the current load rates of the three charging stations drop to 71.2%, 63.8%, and 69.5%, respectively. After connecting photovoltaic power, under the 80% power load rate setting, the current load rates of the three charging stations are 84.0%, 85.0%, and 83.7%, respectively, close to the set power load rate level. Therefore, voltage drops cause the transformer to increase current to maintain constant power output, exacerbating the overload risk; connecting photovoltaic power can improve the voltage, allowing the current load rate to approach the set level.

[0094] In the embodiments of this application, regarding harmonic analysis, such as Figure 6 As shown, Figure 6 This is a harmonic analysis diagram of the current at the beginning of a line according to an embodiment of this application. After a total of 900kW of electric vehicle charging load is distributed and connected to various nodes of the same line, the total harmonic distortion rate of the current at the beginning of the line is 4.34%, with the main harmonic orders being the 5th, 7th, and 11th, among which the 5th harmonic content is significantly higher than other harmonic orders. Based on this, after connecting 300kW of distributed photovoltaic power to the middle and end nodes of the line respectively, the total harmonic distortion rate of the current at the beginning of the line increases to 4.68%, at which point the 5th harmonic is still dominant. It can be seen that the connection of charging facilities will generate harmonic currents dominated by the 5th, 7th, and 11th harmonics; after the connection of distributed photovoltaic power, the harmonic distortion rate increases, but the dominant harmonic order does not change.

[0095] (2) Based on the change patterns of the indicators corresponding to the charging facility access location, transformer load rate and optimization measures, determine the influence weights of the charging facility access location, transformer load rate and optimization measures on each indicator data.

[0096] It should be noted that the influence weight in this application embodiment can be used to measure the degree of influence of each factor on different power distribution network operation indicators. The larger the weight, the more significant the influence of the factor on the indicator.

[0097] Specifically, in this embodiment of the application, for a certain indicator, the rate of change of the indicator before and after the change of each factor can be calculated. The larger the rate of change, the higher the weight of the factor influencing the indicator. For example, taking the voltage deviation indicator as an example, when the transformer load rate drops from 80% to 60%, the voltage of the terminal node 18 increases from 0.809 pu to 0.843 pu, with a change rate of +4.2%; after the connection of distributed photovoltaic, the voltage of the terminal node 18 increases from 0.809 pu to 0.975 pu, with a change rate of +20.5%. Therefore, for the voltage deviation indicator, the influence weight of the distributed photovoltaic connection is greater than the influence weight of the transformer load rate change. As another example, taking the current load rate indicator as an example, when the transformer load rate drops from 80% to 60%, the transformer current load rate of charging station No. 1 drops from 99.7% to 71.2%, with a change rate of -28.6%; after the connection of distributed photovoltaic, the transformer current load rate of charging station No. 1 drops from 99.7% to 84.0%, with a change rate of -15.7%. Therefore, for the current load factor, the impact weight of changes in transformer load factor is greater than the impact weight of distributed photovoltaic access.

[0098] (3) Identify key influencing factors based on the impact weight of charging facility access location, transformer load rate and optimization measures on each indicator data.

[0099] It should be noted that the key influencing factors in the embodiments of this application can refer to factors that have a significant impact on the operation indicators of the distribution network, and can be identified by preset weight thresholds or sorting rules.

[0100] Specifically, for each indicator, the influence weight of all factors on the indicator can be sorted from largest to smallest, and the top two factors (e.g., two) can be identified as the key influencing factors of the indicator; or, when the influence weight of a factor on a certain indicator exceeds the corresponding preset value (e.g., 0.3 or 30%), the factor is determined to be the key influencing factor of the indicator.

[0101] For example, regarding voltage deviation, distributed photovoltaic (PV) grid connection has the greatest impact, followed by transformer load factor; therefore, distributed PV grid connection and transformer load factor are identified as key factors affecting voltage deviation. Regarding current overload, transformer load factor has the greatest impact, followed by the location of charging facility access; therefore, transformer load factor and charging facility access location are identified as key factors affecting current overload. Regarding harmonic distortion, the location of charging facility access (affecting harmonic source distribution) and optimization measures (affecting harmonic suppression effectiveness) have relatively large impacts; therefore, the location of charging facility access and optimization measures are identified as key factors affecting harmonic distortion.

[0102] (4) Generate a response strategy for charging facility access based on the changing patterns of key influencing factors on various indicator data.

[0103] It is understood that, in the embodiments of this application, a response strategy for charging facility access can be further generated based on the indicator change patterns of the identified key influencing factors and their influence patterns. The response strategy should propose a targeted solution for the identified key influencing factors and their influence patterns.

[0104] Specifically, regarding charging facility planning, charging stations with a transformer capacity of 4000 kVA or less can be connected to a 10 kV public power grid line, but the equipment's load-bearing capacity needs to be assessed; for capacities greater than 4000 kVA, dedicated lines are recommended. Furthermore, since identifying the charging facility's connection location is a key factor affecting voltage deviation and overload risk, proximity to the power source can effectively reduce voltage drops and line overloads. Therefore, charging station sites should be located as close as possible to the power supply source, avoiding centralized planning at the feeder end. Simultaneously, the current state of the distribution network and near- and long-term plans should be considered to meet the power quality requirements of the power grid for charging stations.

[0105] Regarding equipment upgrades and grid optimization, for feeder ends and heavily loaded lines, conductor cross-sections should be appropriately increased and transformer capacity increased to enhance equipment capacity margin; the distribution network structure should be optimized to improve power supply flexibility and fault transfer capability. In other words, since transformer load rate is identified as a key factor affecting current overload and voltage deviation, appropriately increasing equipment capacity can reduce load rate and improve voltage quality.

[0106] In terms of operation control and comprehensive management, the time-of-use pricing mechanism will be optimized, the application scope of vehicle-to-grid interaction will be expanded, and distributed photovoltaic and energy storage systems will be configured according to local conditions to avoid long-term heavy-load operation of transformers and feeders. Reactive power compensation and filtering devices will be configured at the grid connection points of charging stations and key locations on feeders to improve voltage quality and suppress harmonic distortion. In other words, since optimization measures (such as distributed photovoltaic access and reactive power compensation) have been identified as key factors affecting voltage deviation and harmonic distortion, the reasonable configuration of these measures can effectively improve power quality.

[0107] It is understood that the embodiments of this application use the control variable method to conduct a horizontal comparison of the distribution network operation data of various access scenarios, analyze the change patterns of indicators corresponding to each factor, determine the influence weight of each factor on each indicator, identify key influencing factors, and generate targeted response strategies accordingly, thereby providing a scientific and reliable decision-making basis for the optimization layout of the distribution network and the management of power quality.

[0108] This invention also provides a corresponding apparatus for analyzing the impact of charging facility access on the power distribution network, further enhancing the practicality of the method. The apparatus can be described from both functional module and hardware perspectives. The apparatus for analyzing the impact of charging facility access on the power distribution network described below corresponds to the analysis method for analyzing the impact of charging facility access on the power distribution network described above.

[0109] From the perspective of functional modules, see Figure 7 , Figure 7 This is a structural diagram of an analysis device for the impact of charging facility access on the power distribution network provided by the present invention. The device may include: The determination module 11 is used to predetermine various different charging facility access locations, various different transformer load rates, and various different optimization measures; The combination module 12 is used to combine various charging facility access locations, various transformer load rates and various optimization measures to obtain various access scenarios; Module 13 is used to establish a simulation model of charging facility access to the distribution network for each of the pre-established access scenarios, based on the distribution network structure, charging load parameters and charging facility grid connection control strategy corresponding to the access scenario. The acquisition module 14 is used to acquire the distribution network operation data under the corresponding access scenario based on the simulation model; wherein, the distribution network operation parameters include at least two different types of indicator data; Analysis module 15 is used to analyze the impact of charging facilities accessing the distribution network and determine key influencing factors based on the distribution network operation parameters corresponding to each access scenario.

[0110] In one implementation, module 11 includes: The first building unit is used to construct the distribution network structure of the target area and configure the basic parameters of the distribution network structure. The second building unit is used to build the basic load model of the distribution network in the target area; The third building unit is used to build a charging facility model, which includes a grid-side access unit, a power conversion unit, and a charging output unit; among them, the power conversion unit adopts a constant power control strategy. The connection unit is used to connect the basic load model of the distribution network and the charging facility model to the corresponding target nodes in the distribution network structure, and to make the corresponding electrical topology connections to obtain the established simulation model of the charging facility connected to the distribution network.

[0111] In one embodiment, the grid-side access unit includes a grid circuit breaker and an isolation transformer; The power conversion unit adopts a two-stage topology, with the front stage being an AC / DC rectifier module and the rear stage being a DC / DC converter module. The charging output unit includes an electric vehicle battery model and a battery management system.

[0112] In one embodiment, the power conversion unit further includes a filter inductor and a filter capacitor, and the power conversion unit integrates a constant power control algorithm consisting of a phase-locked loop, a power outer loop, and a current inner loop.

[0113] In one embodiment, the acquisition module 12 includes: The first acquisition unit is used to acquire the steady-state values ​​of active power, reactive power and apparent power of key nodes in the corresponding access scenario based on the simulation model. The second acquisition unit is used to acquire the effective voltage value and three-phase voltage waveform of each node in the distribution network. The third acquisition unit is used to acquire the effective value of the line current and the three-phase current waveform of the critical line. The fourth acquisition unit is used to acquire the effective value of the current on both sides of the transformer corresponding to the charging facility and the three-phase current waveform; The analysis unit is used to perform spectral analysis on the three-phase voltage waveforms and three-phase current waveforms through Fast Fourier Transform to obtain the effective values ​​of voltage, harmonic voltage, fundamental current, and harmonic current. Based on the effective values ​​of the fundamental voltage and harmonic voltage, it calculates the total harmonic distortion rate of voltage and the harmonic voltage content rate. Based on the effective values ​​of the fundamental current and harmonic current, it calculates the total harmonic distortion rate of current and the harmonic current content rate.

[0114] In one embodiment, the device may further include: The assessment module is used to evaluate the impact of charging facilities on the distribution network based on distribution network operation data.

[0115] In one implementation, the evaluation module includes: The first comparison unit is used to compare the effective voltage value corresponding to each node with the nominal voltage of the system, calculate the voltage deviation percentage corresponding to the node, and compare the voltage deviation percentage with the preset deviation limit to identify the nodes with voltage quality problems. The recording unit is used to record the voltage dip amplitude and duration of each node in the distribution network, and to determine whether the voltage dip amplitude is within a preset range and the duration is within a preset time range, so as to determine the node where the voltage dip occurs and the severity of the dip. The first conversion unit is used to convert the effective value of the line current of the critical line into the line load rate and determine whether the line load rate exceeds the preset line load rate limit. The second conversion unit is used to convert the effective values ​​of the current on both sides of the transformer into the transformer load rate and to determine whether the transformer load rate exceeds the preset transformer load rate limit. The second comparison unit is used to compare the total harmonic distortion rate of voltage, the harmonic voltage content rate, the total harmonic distortion rate of current, and the harmonic current content rate with the corresponding preset limits, and to determine whether there are nodes or lines with excessive harmonics based on the comparison results, and to determine the severity of harmonic distortion of the corresponding nodes or lines.

[0116] In one implementation, the analysis module 13 includes: The third comparison unit is used to compare the various indicator data in the power distribution network operation data under various access scenarios using the control variable method, and to analyze the change patterns of the indicators corresponding to the charging facility access location, transformer load rate and optimization measures respectively. The determination unit is used to determine the influence weights of the charging facility access location, transformer load rate, and optimization measures on each indicator data based on the indicator change patterns corresponding to the charging facility access location, transformer load rate, and optimization measures. The identification unit is used to identify key influencing factors based on the influence weight of each indicator data according to the charging facility access location, transformer load rate, and optimization measures. The generation unit is used to generate response strategies for charging facility access based on the changing patterns of key influencing factors on various indicator data.

[0117] It should be noted that the analysis device for the impact of charging facility access on the power distribution network provided in this application embodiment has the same beneficial effects as the analysis method for the impact of charging facility access on the power distribution network provided in the above embodiments. For a detailed description of the analysis method for the impact of charging facility access on the power distribution network involved in this application embodiment, please refer to the above embodiments. This application will not repeat it here.

[0118] The analysis device for the impact of charging facility access on the power distribution network mentioned above is described from the perspective of functional modules. Furthermore, the present invention also provides an electronic device, which is described from the perspective of hardware. Figure 8 A structural diagram of an electronic device provided in an embodiment of this application, such as... Figure 8 As shown, the electronic device includes: a memory 20 for storing computer programs; The processor 21 is used to execute a computer program to implement the steps of the method for analyzing the impact of charging facility access on the power distribution network as described in the above embodiment.

[0119] The electronic devices provided in this embodiment may include, but are not limited to, smartphones, tablets, laptops, or desktop computers.

[0120] The processor 21 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 21 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 21 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 21 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0121] The memory 20 may include one or more computer-readable storage media, which may be non-transitory. The memory 20 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the memory 20 may be an internal storage unit of an electronic device, such as a server hard drive. In other embodiments, the memory 20 may be an external storage device of an electronic device, such as a plug-in hard drive on a server, a smart media card (SMC), a secure digital card (SD), a flash card, etc. Furthermore, the memory 20 may include both internal and external storage units of the electronic device. The memory 20 can be used not only to store application software and various types of data installed in the electronic device, such as code in the process of executing the method for analyzing the impact of charging facility access on the power distribution network, but also to temporarily store data that has been output or will be output. In this embodiment, the memory 20 is used to store at least the following computer program 201, which, after being loaded and executed by the processor 21, can implement the relevant steps of the method for analyzing the impact of charging facility access on the power distribution network disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, and the storage method may be temporary storage or permanent storage. The operating system 202 may include Windows, Unix, Linux, etc. The data 203 may include, but is not limited to, data corresponding to the analysis results of the impact of charging facility access on the power distribution network.

[0122] In some embodiments, the electronic device may further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26. The display screen 22 and input / output interface 23, such as a keyboard, are user interfaces; optional user interfaces may also include standard wired interfaces, wireless interfaces, etc. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device and to display a visual user interface. The communication interface 24 may optionally include a wired interface and / or a wireless interface, such as a Wi-Fi interface, a Bluetooth interface, etc., typically used to establish communication connections between the electronic device and other electronic devices. The communication bus 26 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0123] Those skilled in the art will understand that Figure 8 The structures shown do not constitute a limitation on electronic devices and may include more or fewer components than those shown.

[0124] It is understood that if the analysis method for the impact of charging facility access on the power distribution network in the above embodiments is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and executes all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes: USB flash drive, mobile hard drive, read-only memory (ROM), random access memory (RAM), electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, magnetic disk, or optical disk, and other media capable of storing program code.

[0125] Based on this, such as Figure 9As shown, this embodiment of the invention also provides a computer-readable storage medium 30, on which a computer program 31 is stored. When the computer program 31 is executed by a processor, it implements the steps of the above-described method for analyzing the impact of charging facility access on the power distribution network.

[0126] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0127] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0128] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0129] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0130] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for analyzing the impact of charging facility access on the power distribution network, characterized in that, include: Pre-determine various charging facility access locations, various transformer load rates, and various optimization measures; By combining various charging facility access locations, various transformer load rates, and various optimization measures, a variety of different access scenarios can be obtained; For each of the various access scenarios, a simulation model for the charging facility's access to the distribution network is established based on the distribution network structure, charging load parameters, and charging facility grid connection control strategy corresponding to the access scenario. Based on the simulation model, the power distribution network operation data under the corresponding access scenario is obtained; wherein, the power distribution network operation parameters include at least two different types of indicator data; Based on the power distribution network operation parameters corresponding to each of the access scenarios, the impact of the charging facility's access to the power distribution network is analyzed and key influencing factors are determined.

2. The method for analyzing the impact of charging facility access on the power distribution network according to claim 1, characterized in that, Based on the distribution network structure, charging load parameters, and grid connection control strategy of charging facilities corresponding to the access scenario, a simulation model for charging facilities accessing the distribution network is established, including: Construct the power distribution network structure for the target area and configure the basic parameters of the power distribution network structure; Construct a basic load model of the distribution network in the target area; A charging facility model is constructed, which includes a grid-side access unit, a power conversion unit, and a charging output unit; wherein, the power conversion unit adopts a constant power control strategy. The basic load model of the distribution network and the charging facility model are connected to the corresponding target nodes in the distribution network structure, and the corresponding electrical topology connections are made to obtain a simulation model of the charging facility connected to the distribution network.

3. The method for analyzing the impact of charging facility access on the power distribution network according to claim 2, characterized in that, The grid-side access unit includes a grid circuit breaker and an isolation transformer; The power conversion unit adopts a two-stage topology, in which the front stage is an AC / DC rectifier module and the rear stage is a DC / DC converter module. The charging output unit includes an electric vehicle battery model and a battery management system.

4. The method for analyzing the impact of charging facility access on the power distribution network according to claim 3, characterized in that, The power conversion unit also includes a filter inductor and a filter capacitor, and integrates a constant power control algorithm consisting of a phase-locked loop, an outer power loop, and an inner current loop.

5. The method for analyzing the impact of charging facility access on the power distribution network according to claim 1, characterized in that, The step of obtaining distribution network operation data under the corresponding access scenario based on the simulation model includes: Based on the simulation model, obtain the steady-state values ​​of active power, reactive power, and apparent power of key nodes in the corresponding access scenario; Obtain the effective voltage value and three-phase voltage waveform for each node in the power distribution network; Obtain the effective value of the line current and the three-phase current waveform of the critical circuit; Obtain the effective value of the current and the three-phase current waveform on both sides of the transformer corresponding to the charging facility; The three-phase voltage waveforms and three-phase current waveforms are subjected to spectrum analysis by Fast Fourier Transform to obtain the effective values ​​of voltage, each harmonic voltage, the fundamental current, and each harmonic current. Based on the effective values ​​of the fundamental voltage and each harmonic voltage, the total harmonic distortion rate of voltage and the harmonic voltage content are calculated. Similarly, based on the effective values ​​of the fundamental current and each harmonic current, the total harmonic distortion rate of current and the harmonic current content are calculated.

6. The method for analyzing the impact of charging facility access on the power distribution network according to claim 5, characterized in that, After obtaining the distribution network operation data for the corresponding access scenario based on the simulation model, the process also includes: The impact of the charging facilities on the distribution network is assessed based on the distribution network operation data.

7. The method for analyzing the impact of charging facility access on the power distribution network according to claim 6, characterized in that, The impact of the charging facilities on the distribution network is assessed based on the aforementioned distribution network operation data, including: The effective voltage value corresponding to each node is compared with the nominal voltage of the system, the voltage deviation percentage corresponding to the node is calculated, and the voltage deviation percentage is compared with a preset deviation limit to identify the nodes with voltage quality problems. For each node in the distribution network, the voltage drop amplitude and duration of the node are recorded, and it is determined whether the voltage drop amplitude of the node is within a preset amplitude range and whether the duration is within a preset duration range, so as to determine the node where the voltage sag occurs and the severity of the sag. The effective value of the line current of the critical line is converted into the line load rate, and it is determined whether the line load rate exceeds the preset line load rate limit. The effective values ​​of the current on both sides of the transformer are converted into the transformer load rate, and it is determined whether the transformer load rate exceeds the preset transformer load rate limit. The total harmonic distortion rate of voltage, the harmonic voltage content rate, the total harmonic distortion rate of current, and the harmonic current content rate are compared with the corresponding preset limits. Based on the comparison results, it is determined whether there are nodes or lines with excessive harmonics, and the severity of harmonic distortion of the corresponding nodes or lines is determined.

8. The method for analyzing the impact of charging facility access on the power distribution network according to claim 5, characterized in that, Based on the distribution network operation parameters corresponding to each of the aforementioned access scenarios, the impact patterns of the charging facility's access to the distribution network are analyzed, and key influencing factors are identified, including: The control variable method was used to conduct a horizontal comparison of various indicator data in the power distribution network operation data under each access scenario, and to analyze the change patterns of indicators corresponding to the charging facility access location, transformer load rate and optimization measures. Based on the changing patterns of indicators corresponding to charging facility access location, transformer load rate, and optimization measures, the influence weights of charging facility access location, transformer load rate, and optimization measures on each indicator data are determined. Based on the influence weights of charging facility access location, transformer load rate, and optimization measures on each indicator data, key influencing factors are identified. Based on the changing patterns of the key influencing factors on various indicator data, a response strategy for charging facility access is generated.

9. An analysis device for the impact of charging facility access on the power distribution network, characterized in that, include: The determination module is used to pre-determine various charging facility access locations, various transformer load rates, and various optimization measures; The combination module is used to combine various charging facility access locations, various transformer load rates, and various optimization measures to obtain various access scenarios; A module is established to create a simulation model of charging facility access to the distribution network for each of a variety of pre-established access scenarios, based on the distribution network structure, charging load parameters, and charging facility grid connection control strategy corresponding to the access scenario. The acquisition module is used to acquire power distribution network operation data under the corresponding access scenario based on the simulation model; wherein, the power distribution network operation parameters include at least two different types of indicator data; The analysis module is used to analyze the impact of the charging facility's connection to the distribution network and determine the key influencing factors based on the distribution network operation parameters corresponding to each of the access scenarios.

10. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of the method for analyzing the impact of charging facility access on the power distribution network as described in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method for analyzing the impact of charging facility access on the power distribution network as described in any one of claims 1 to 8.

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