Charging pile grid-connected power quality analysis method, device, equipment, medium and program product

Abstract

The application relates to a charging pile grid-connected power quality analysis method, device, equipment, medium and program product. The method comprises the following steps: acquiring basic data of a grid-connected point and operation data of a charging pile; respectively establishing a disturbance model for each charging pile according to the basic data and the operation data; identifying and quantifying power quality problems caused by grid connection of each charging pile according to disturbance parameters to obtain a quantitative calculation result; performing multi-pile parallel superposition effect analysis to determine disturbance deterioration degree information of mixed grid connection of multiple charging piles; establishing a multi-scenario influence conduction model according to the disturbance deterioration degree information combined with environmental data; dividing current power quality problems into different severity levels according to disturbance influence information at all levels combined with multi-dimensional evaluation indexes, and outputting an evaluation result; and generating a charging pile grid-connected power quality analysis report according to the evaluation result. The method can systematically analyze power quality of multiple types of charging piles connected to the grid.

Description

Technical Field

[0001] This application relates to the field of power quality analysis technology, and in particular to a method, apparatus, equipment, medium, and program product for analyzing the power quality of a charging pile connected to the grid. Background Technology

[0002] With the rapid development of the electric vehicle industry, the scale and types of charging piles connected to urban power distribution networks are increasing day by day. Various types of charging piles, such as AC slow charging piles, DC fast charging piles, and high-power supercharging piles, are widely deployed in urban residential areas, commercial complexes, transportation hubs and other scenarios. Their nonlinear, impulsive and random load characteristics pose a severe challenge to the power quality of the power distribution network.

[0003] In traditional technologies, the analysis of grid-connected power quality of charging piles usually adopts a uniform nonlinear load modeling method, and harmonic assessment is carried out indiscriminately for all types of charging piles; or power quality testing is carried out only for a single charging pile or a single charging station, and the national standards are used to determine whether each indicator exceeds the standard.

[0004] However, traditional methods fail to distinguish the significant differences in harmonic spectrum, transient impact, and reactive power characteristics among different types of charging piles, such as AC slow charging, DC fast charging, and high-power supercharging, resulting in large errors in disturbance feature extraction. At the same time, traditional methods ignore the compound effects of multiple charging piles operating in parallel. Traditional methods are also difficult to support power distribution network planning, access, and governance decisions. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, device, equipment, medium, and program product for analyzing the grid-connected power quality of charging piles, which can systematically analyze the grid-connected power quality of various types of charging piles, in response to the above-mentioned technical problems.

[0006] Firstly, this application provides a method for analyzing the power quality of charging piles connected to the grid. The method includes:

[0007] Obtain basic data on grid connection points and operational data on charging piles;

[0008] Based on the basic data and the operational data, a disturbance model is established for each charging pile, and the disturbance model is used to extract disturbance parameters.

[0009] Based on the disturbance parameters, the power quality problems caused by the grid connection of each charging pile are identified and quantified, and the quantitative calculation results are obtained.

[0010] Based on the quantitative calculation results, the superposition effect of multiple charging piles in parallel is analyzed to determine the degree of disturbance deterioration after multiple charging piles are mixed and connected to the grid.

[0011] Based on the information on the degree of disturbance deterioration and combined with environmental data, a multi-scenario impact transmission model is established, which is used to output information on the impact of disturbances at all levels.

[0012] Based on the information on the impact of the disturbances at all levels and combined with multi-dimensional evaluation indicators, the current power quality problems are classified into different severity levels, and the evaluation results are output.

[0013] A power quality analysis report for the charging piles connected to the grid is generated based on the evaluation results.

[0014] In some embodiments of the method, the charging pile includes at least one of AC slow charging piles, DC conventional charging piles, DC fast charging piles, and supercharging piles; based on the basic data and the operational data, a disturbance model is established for each charging pile, including:

[0015] A single-phase harmonic and unbalance model is established for the AC slow charging pile, a multi-pulse rectifier harmonic model is established for the DC conventional charging pile, a high-frequency harmonic and transient fluctuation model is established for the DC fast charging pile, and a high-power transient impact and oscillation model is established for the supercharging pile.

[0016] In some embodiments of the method, the power quality problems include at least one of harmonic pollution, voltage deviation and flicker, three-phase imbalance, power factor deterioration, and transient power quality problems. The step of identifying and quantifying the power quality problems caused by grid connection of each charging pile based on the disturbance parameters, and obtaining the quantitative calculation results, includes:

[0017] Determine the extent to which each power quality issue exceeds the standard and the corresponding disturbance contribution rate of the charging pile.

[0018] In some embodiments of the method, the step of performing multi-pile parallel superposition effect analysis based on quantitative calculation results to determine the degree of disturbance deterioration after the mixed grid connection of multiple charging piles includes:

[0019] The harmonic superposition effect, transient impact coupling effect and three-phase imbalance cumulative effect of the charging pile cluster during parallel operation are analyzed. The degree of disturbance deterioration caused by each superposition effect is quantified, and the disturbance deterioration information after multiple charging piles are connected to the grid is determined.

[0020] In some embodiments of the method, the disturbance impact information at each level includes at least one of the following: the information on the cascading transmission of the disturbance from the charging pile through the grid connection point, distribution network line, transformer to the user equipment; and the information on the degree of impact on the distribution network equipment, electrical equipment, metering device and relay protection device; the evaluation index includes at least one of the following: disturbance intensity, exceedance multiple, affected area, and degree of harm.

[0021] In some embodiments of the method, the basic data includes at least one of rated voltage, line impedance, short-circuit capacity, transformer capacity, and load rate; the operating data includes at least one of rated power, current charging power, charging mode, start / stop status, number, and grid connection phase of each charging pile; and the environmental data includes at least one of load characteristics of the current scenario and grid constraints.

[0022] According to a second aspect of the present disclosure, a power quality analysis device for charging piles connected to the grid is provided. The device includes:

[0023] The first module is used to acquire basic data of the grid connection point and operational data of the charging pile;

[0024] The second module is used to establish a disturbance model for each charging pile based on the basic data and the operating data, and the disturbance model is used to extract disturbance parameters.

[0025] The third module is used to identify and quantify the power quality problems caused by the grid connection of each charging pile based on the disturbance parameters, and obtain the quantitative calculation results.

[0026] The fourth module is used to analyze the superposition effect of multiple charging piles in parallel based on the quantitative calculation results, and to determine the degree of disturbance deterioration after multiple charging piles are mixed and connected to the grid.

[0027] The fifth module is used to establish a multi-scenario impact transmission model based on the disturbance deterioration information and environmental data. The multi-scenario impact transmission model is used to output disturbance impact information at all levels.

[0028] The sixth module is used to classify the current power quality problem into different severity levels based on the information on the impact of the disturbance at all levels and in combination with multi-dimensional evaluation indicators, and output the evaluation results.

[0029] The seventh module is used to generate a power quality analysis report for the charging pile based on the evaluation results.

[0030] According to a third aspect of the present disclosure, a computer device is provided. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the above-described method for analyzing the grid-connected power quality of charging piles.

[0031] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the above-described method for analyzing the power quality of a charging pile connected to the grid.

[0032] According to a fifth aspect of the present disclosure, a computer program product is provided. The computer program product includes a computer program that, when executed by a processor, implements the above-described method for analyzing the power quality of a charging pile connected to the grid.

[0033] The charging pile grid-connected power quality analysis scheme provided in this application establishes differentiated disturbance models for different types of charging piles, accurately characterizing the inherent differences in disturbance features of each type of charging pile, thus solving the technical problem of large disturbance extraction errors in traditional unified modeling methods. Through the analysis of the superposition effect of multiple charging piles in parallel, the scheme quantifies the disturbance deterioration caused by each composite effect, making up for the evaluation blind spot caused by the neglect of cluster superposition effect in traditional methods. Through the multi-scenario influence transmission model, the scheme outputs the stepwise transmission law of disturbance from charging piles through grid connection points, distribution network lines, transformers to user equipment and the degree of impact on equipment at each stage, filling the gap in existing technologies that only focus on grid connection point indicators and ignore the impact of disturbance transmission downstream along the distribution network, effectively improving the accuracy and systematicness of the analysis of grid-connected power quality problems of multiple types of charging piles.

[0034] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0035] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0036] Figure 1 This is a flowchart illustrating a power quality analysis method for grid-connected charging piles according to an exemplary embodiment.

[0037] Figure 2 This is a comparison diagram of the harmonic spectrum characteristics of various types of charging piles according to an exemplary embodiment;

[0038] Figure 3 This is a graph illustrating the evolution of the three-phase imbalance of a charging pile cluster connected to the grid, according to an exemplary embodiment.

[0039] Figure 4 The diagram illustrates the evaluation results for different scenarios according to an exemplary embodiment.

[0040] Figure 5 This is a structural block diagram of a charging pile grid-connected power quality analysis device according to an exemplary embodiment;

[0041] Figure 6 This is a diagram illustrating the internal structure of a computer device according to an exemplary embodiment. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0043] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure. The terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, product, 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, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in a process, method, product, or apparatus that includes said elements is not excluded. For example, the use of terms such as "first," "second," etc., to denote names does not indicate any specific order.

[0044] In some embodiments provided in this disclosure, the execution of the charging pile grid-connected power quality analysis method can be controlled by a unified controller or by multiple controllers. These controllers may include controllers of local terminals or controllers of remote servers. In some embodiments, the controllers of local terminals and the controllers of servers may jointly assist in completing the grid-connected power quality analysis and control processing of charging piles. The local terminal mentioned in this disclosure may include, but is not limited to, various personal computers, laptops, smartphones, tablets, VR (Virtual Reality) devices, etc. The server may also be a server, server cluster, distributed subsystem, cloud processing platform, server containing blockchain nodes, and combinations thereof. The controllers described in this disclosure may include various control units capable of implementing logic processing functions, including but not limited to CPU (Central Processing Unit), PLC (Programmable Logic Controller), ECU (Electronic Control Unit), MCU (Microcontroller Unit), FPGA (Field Programmable Gate Array), and CPLD (Complex Programmable Logic Device), as well as controllers composed of one or more logic function units, chips, etc.

[0045] In some embodiments of this disclosure, a method for analyzing the power quality of a charging pile connected to the grid is provided, such as... Figure 1 As shown, it includes the following steps:

[0046] S20. Obtain basic data of the grid connection point and operation data of the charging pile.

[0047] Basic data may include at least one of the following: rated voltage, line impedance, short-circuit capacity, transformer capacity, and load rate.

[0048] Operational data may include at least one of the following: rated power, current charging power, charging mode, start / stop status, number, and grid connection phase of each charging pile.

[0049] S21. Based on the basic data and the operational data, establish a disturbance model for each charging pile, and use the disturbance model to extract disturbance parameters.

[0050] A disturbance model typically refers to a mathematical model or equivalent circuit model established for different types of charging piles based on their topology, rectification method, control strategy, and power level. This model describes the disturbance characteristics such as harmonics, reactive power, transient impacts, and three-phase imbalance generated when the charging pile is connected to the grid.

[0051] Disturbance parameters typically refer to the core characteristic quantities extracted from the disturbance model that can quantify the disturbance characteristics of various types of charging piles.

[0052] S22. Identify and quantify the power quality problems caused by grid connection of each charging pile based on the disturbance parameters, and obtain the quantitative calculation results.

[0053] Power quality issues typically refer to various problems caused by the grid connection of multiple types of charging piles.

[0054] The quantitative calculation results usually refer to the specific quantitative results of various power quality issues obtained after calculation.

[0055] S23. Based on the quantitative calculation results, conduct a multi-pile parallel superposition effect analysis to determine the degree of disturbance deterioration after multiple charging piles are mixed and connected to the grid.

[0056] Superposition effect analysis usually refers to the quantitative analysis of the combined disturbance effects when multiple charging piles are running in parallel.

[0057] Information on the degree of perturbation deterioration usually refers to the quantifiable assessment results output after superposition effect analysis.

[0058] S24. Based on the information on the degree of disturbance deterioration and combined with environmental data, establish a multi-scenario impact transmission model, which is used to output the impact information of each level of disturbance.

[0059] Environmental data may include at least one of the following: load characteristics of the current scenario and power grid constraints. The current scenario may include five typical scenarios: residential areas, commercial complexes, transportation hubs, old urban areas, and industrial parks.

[0060] Multi-scenario impact transmission model usually refers to a mathematical model that combines environmental data from different types of scenarios to describe the transmission law and degree of impact of disturbances from charging piles along each link of the power distribution network.

[0061] The disturbance impact information at all levels usually refers to the quantitative results of disturbance impact covering all aspects of the distribution network, output by the above-mentioned multi-scenario impact transmission model.

[0062] S25. Based on the information on the impact of the disturbance at each level and combined with multi-dimensional evaluation indicators, the current power quality problem is classified into different severity levels, and the evaluation results are output.

[0063] Severity levels typically refer to different levels of severity based on the current power quality problem. Severity levels can include four categories: minor, moderate, severe, and extremely severe.

[0064] S26. Generate a power quality analysis report for the charging pile based on the evaluation results.

[0065] A power quality analysis report typically refers to the final output file generated by combining various analysis results. A power quality analysis report may include a list of issues, risk points, remediation priorities, and scenario optimization suggestions.

[0066] In some embodiments of this disclosure, differentiated disturbance models are established for different types of charging piles to accurately characterize the inherent differences in disturbance features of each type of charging pile, thus solving the technical problem of large disturbance extraction errors in traditional unified modeling methods. Through the analysis of the superposition effect of multiple charging piles in parallel, the disturbance deterioration caused by each compound effect is quantified, making up for the evaluation blind spot caused by the neglect of cluster superposition effect in traditional methods. Through the multi-scenario influence transmission model, the step-by-step transmission law of disturbance from charging piles through grid connection points, distribution network lines, transformers to user equipment and the degree of impact on equipment at each stage are output, filling the gap of existing technology that only focuses on grid connection point indicators and ignores the impact of disturbance transmission downstream along the distribution network, effectively improving the accuracy and systematicness of the analysis of power quality problems of grid connection for multiple types of charging piles.

[0067] In some embodiments of this disclosure, the charging pile includes at least one of AC slow charging pile, DC conventional charging pile, DC fast charging pile, and supercharging pile. S21 includes:

[0068] A single-phase harmonic and unbalance model is established for the AC slow charging pile, a multi-pulse rectifier harmonic model is established for the DC conventional charging pile, a high-frequency harmonic and transient fluctuation model is established for the DC fast charging pile, and a high-power transient impact and oscillation model is established for the supercharging pile.

[0069] Reference Figure 2 AC slow charging stations typically employ a single-phase rectifier topology, with single-phase AC input and DC output to charge vehicle batteries. During operation, these charging stations generate odd-order harmonic currents, primarily third, fifth, and seventh harmonics, on the grid side. Furthermore, the single-phase connection leads to random load distribution across phases, making it a significant source of three-phase imbalance in the distribution network. This model describes the amplitude and phase characteristics of the harmonic currents during steady-state operation of AC slow charging stations, as well as the degree of three-phase current imbalance under random grid connection conditions.

[0070] Conventional DC pile drivers typically employ a six-pulse or twelve-pulse rectifier topology, with a three-phase alternating current input and a direct current output. The harmonics generated by this type of rectification exhibit typical characteristics: six-pulse rectification primarily produces harmonics of the sixth octave band, while twelve-pulse rectification can effectively cancel some lower-order harmonics. This model is used to describe the spectral distribution and amplitude characteristics of characteristic harmonics during the rectification process of conventional DC pile drivers.

[0071] DC fast charging stations typically employ a PWM (Pulse Width Modulation) rectifier topology, which has a high switching frequency. This generates high-frequency harmonics over a wide frequency band and produces significant transient voltage fluctuations during charging start-up, shutdown, and power transitions. This model describes the harmonic distribution characteristics of DC fast charging stations over a wide frequency band, as well as the amplitude and duration of transient voltage fluctuations during dynamic power changes.

[0072] A high-power transient impact and oscillation model is established for supercharging piles. Supercharging piles typically employ cascaded H-bridges or multi-level topologies, with a single unit reaching hundreds of kilowatts. Their switching process generates significant power surges within milliseconds, triggering voltage dips, swells, and high-frequency oscillations. This model describes the transient impact amplitude, duration, and oscillation frequency characteristics of supercharging piles at the moment of switching.

[0073] In some embodiments of this disclosure, adaptive disturbance models are constructed for the different topologies, rectification methods, power levels, and control strategies of AC slow charging piles, DC conventional charging piles, DC fast charging piles, and supercharging piles. This allows for the accurate characterization of the inherent differences in harmonic spectrum distribution, transient impact intensity, reactive power characteristics, and three-phase asymmetry among various types of charging piles. This effectively solves the technical problems of large disturbance feature extraction errors and low analysis accuracy caused by using a unified model to describe all types of charging piles in traditional technologies.

[0074] In some embodiments of this disclosure, the power quality problem includes at least one of the following: harmonic pollution problem, voltage deviation and flicker problem, three-phase imbalance problem, power factor deterioration problem, and transient power quality problem. S22 includes:

[0075] Determine the extent to which each power quality issue exceeds the standard and the corresponding disturbance contribution rate of the charging pile.

[0076] Harmonic pollution refers to the phenomenon of voltage waveform distortion caused by the non-sinusoidal current generated by the rectifier of the charging pile injected into the distribution network, manifested as the voltage content of each harmonic and the total harmonic distortion rate deviating from the normal range; voltage deviation refers to the phenomenon of the voltage amplitude at the grid connection point deviating from the rated value due to the charging load, manifested as voltage being too high or too low; voltage fluctuation and flicker refers to the phenomenon of rapid voltage changes caused by the start-up, shutdown or power jump of the charging pile, manifested as short-time flicker and long-time flicker values ​​deviating from the normal range; three-phase imbalance refers to the phenomenon of uneven distribution of three-phase load caused by the random connection of a single-phase charging pile to different phase lines, manifested as voltage imbalance or current imbalance deviating from the normal range and neutral point offset; power factor degradation refers to the phenomenon of the power factor at the grid connection point being lower than the assessment standard due to the reactive power consumption or feedback of the charging pile; transient power quality refers to the millisecond-level voltage dips, dips, and high-frequency oscillations caused by the switching of high-power charging piles.

[0077] For each identified power quality problem, based on the relevant national standards, the comparison results between the measured value of the quantitative index for that problem and the standard limit are calculated, including the measured value of the index, the multiple exceeding the limit, or the deviation. For example, for harmonic pollution problems, the specific percentage of total harmonic distortion (THD) of voltage and the difference or multiple exceeding the national standard limit are calculated; for three-phase imbalance problems, the specific percentage of voltage imbalance and the multiple exceeding the standard are calculated; for voltage fluctuation and flicker problems, the measured values ​​of short-time flicker and long-time flicker and the extent of exceeding the standard are calculated; for transient power quality problems, the voltage sag amplitude, duration, and sag amplitude are calculated.

[0078] Based on the disturbance parameters of various types of charging piles and their superposition results at the grid connection point, the contribution ratio of AC slow charging piles, DC conventional charging piles, DC fast charging piles, and supercharging piles to the exceeding of the above-mentioned power quality indicators was calculated. This contribution rate is used to reflect the degree of participation of each type of charging pile in causing specific power quality problems, providing a basis for subsequent superposition effect analysis and priority ranking of governance.

[0079] In some embodiments of this disclosure, the quantitative calculation method covers all typical power quality problems that may be caused by grid connection of various types of charging piles. By combining the degree of exceedance and contribution rate of various indicators, it can accurately reflect the differences of the dominant problems in different scenarios, thereby providing accurate data support for subsequent superposition analysis, transmission assessment and level evaluation.

[0080] In some embodiments of this disclosure, S23 includes:

[0081] The harmonic superposition effect, transient impact coupling effect and three-phase imbalance cumulative effect of the charging pile cluster during parallel operation are analyzed. The degree of disturbance deterioration caused by each superposition effect is quantified, and the disturbance deterioration information after multiple charging piles are connected to the grid is determined.

[0082] Reference Figure 3 When multiple charging piles are connected to the same grid connection point at the same time, the disturbances generated by each charging pile are not simply added linearly, but there is a complex nonlinear superposition and amplification phenomenon.

[0083] When harmonic currents of the same frequency generated by multiple charging piles converge at the grid connection point, if the phases of the harmonic currents tend to be the same, the amplitude of the combined harmonic voltage increases in a vector superposition manner. The degree of amplification depends on the magnitude and phase consistency of the harmonic currents of each charging pile. This analysis is used to determine the increase in the combined amplitude of each harmonic at the grid connection point compared to the amplitude of a single charging pile operating alone, as well as the level of voltage harmonic distortion caused by the distribution network impedance.

[0084] When multiple fast-charging or supercharging piles start, stop, or experience power jumps simultaneously or sequentially, the voltage dips, swells, and high-frequency oscillations generated by each pile superimpose in time and space, and the amplitude of the combined transient disturbance may exceed the level when a single charging pile is switched on. This analysis is used to determine the amplification factor of the transient impact amplitude under multi-pile coupling relative to the amplitude when a single charging pile is switched on.

[0085] Each single-phase AC slow-charging pile is randomly connected to different phase lines. The unbalanced current generated by each pile converges on the low-voltage side of the distribution transformer, causing the three-phase current imbalance and the degree of voltage deviation in each phase to continuously worsen with changes in the number of connected piles and their distribution patterns. This analysis is used to determine the increase in voltage imbalance and neutral current under cluster connection conditions compared to single-pile connection.

[0086] In some embodiments of this disclosure, compared with the traditional evaluation method that ignores the superposition effect or only uses simple arithmetic superposition, the evaluation accuracy and reliability in cluster scenarios are significantly improved, providing a reliable technical basis for the evaluation of the carrying capacity of charging piles in power distribution networks and the design of access schemes.

[0087] In some embodiments of this disclosure, the disturbance impact information at each level includes at least one of the following: the information on the step-by-step transmission of the disturbance from the charging pile through the grid connection point, distribution network line, transformer to the user equipment; and the information on the degree of impact on the distribution network equipment, electrical equipment, metering device and relay protection device; the evaluation index includes at least one of the following: disturbance intensity, exceedance multiple, affected range, and degree of harm.

[0088] This paper analyzes five typical scenarios and four types of charging piles in urban power distribution networks. Two implementation examples are designed: a single-scenario single-type charging pile and a mixed-scenario multi-type charging pile cluster. These examples verify the accuracy and applicability of the analytical method. The analysis is based on national standards such as GB / T14549, GB / T15543, GB / T12326, and GB / T18487.1. The rated voltage of the power distribution network is 0.4kV, and the transformer capacity covers 400kVA–1600kVA.

[0089] In some examples, refer to Figure 4 Taking an old urban residential area as an example, and using a single-phase 7kW AC slow charging pile as the analysis object, there are 30 charging piles, randomly connected to the A, B, and C phases. The power distribution line impedance is 0.25 + j0.5Ω, the transformer capacity is 400kVA, and the load rate is 65%. The specific analysis process is as follows:

[0090] The first step is to collect grid connection point parameters: rated voltage 0.4kV, line impedance 0.25+j0.5Ω, transformer capacity 400kVA, load rate 65%; collect charging pile data: AC slow charging piles, single phase 220V, rated power 7kW, quantity 30 units, disordered charging, no orderly control; calibration scenario: old urban residential area, concentrated charging during evening peak 18:00-22:00, aging distribution network lines, and high impedance.

[0091] The second step is to establish a single-phase AC pile disturbance model, extract the characteristic harmonics as the 3rd, 5th and 7th orders, and the current THD≈25%–35%; determine the unbalance characteristics: single-phase random grid connection, uneven distribution of three-phase loads, and a significant increase in neutral line current.

[0092] Third, harmonic pollution: After 30 units are connected in parallel, the harmonic superposition factor is taken as 0.9, and the voltage THDu at the PCC point is ≈7.2%, exceeding the national standard limit of 5%; Three-phase imbalance: The imbalance degree ε is ≈8.5%, exceeding the national standard limit of 4%, and the neutral line current reaches 52% of the phase line current; Voltage deviation: The maximum deviation is -7.1%, close to the national standard limit of -7%; Power factor: The average power factor is 0.88, which drops to 0.79 under light load; Transient disturbance: There is no high power impact, and the transient problem is minor.

[0093] The fourth step is the harmonic superposition effect: a single THDi unit is qualified, but the voltage harmonics exceed the standard after the cluster is connected in parallel; affecting the conduction: it leads to increased transformer losses in the distribution area, local heating, and slight flickering and noise in corridor lighting and household electronic devices.

[0094] Step 5, Level Evaluation: Three-phase imbalance is severe, harmonic pollution is severe, and voltage deviation is moderate; Output Recommendations: Adopt phase-balanced connection, install reactive power compensation and light filtering devices, and implement orderly charging.

[0095] In other examples, refer to Figure 4 Taking an urban transportation hub scenario as an example, the system includes a mixed cluster of multiple types of charging stations, including 120kW DC fast charging piles, 480kW supercharging piles, and 7kW AC slow charging piles, with a total installed capacity of 3.6MW, a transformer capacity of 1600kVA, a load factor of 82%, and a line impedance of 0.15+j0.3Ω. The specific analysis process is as follows:

[0096] The first step is to collect grid connection point parameters: 0.4kV distribution network, impedance 0.15+j0.3Ω, transformer capacity 1600kVA, load rate 82%; collect charging pile data: 10 120kW fast charging piles, 4 480kW supercharging piles, and 20 7kW AC charging piles; calibration scenario: transportation hub, charging vehicles arrive continuously, start and stop frequently, and load fluctuates drastically.

[0097] The second step involves fast charging stations: PWM rectification, containing high-frequency harmonics, resulting in significant start-stop impact; supercharging stations: cascaded topology, millisecond-level high-power switching, generating sag / boost and high-frequency oscillations; AC charging stations: superposition of single-phase harmonics and three-phase imbalance.

[0098] The third step is harmonic pollution: broadband harmonics, voltage THDu≈8.9%, with prominent high-frequency harmonic components; voltage fluctuation and flicker: short-time flicker Pst≈1.35, exceeding the national standard limit of 1.0; transient disturbance: voltage drop of 8.2% during overcharge startup, lasting 150ms; three-phase imbalance: ε≈4.8%, exceeding the standard; power factor: average 0.93, fluctuation range 0.86–0.97.

[0099] The fourth step involves multiple types of coupled disturbances: the superposition of harmonics, imbalance, and transient impacts significantly increases the risk of distribution network operation; the impact of transmission leads to instability in sensitive equipment, monitoring systems, and lighting systems within the station, and increases transformer harmonic losses by 12%.

[0100] Step 5, Level Evaluation: Harmonic pollution is extremely serious, voltage flicker is serious, and transient disturbances are serious; Output Recommendation: Adopt dedicated comprehensive treatment, soft start control for supercharging piles, and orderly grid connection of charging piles in different time periods.

[0101] The embodiments provided in this disclosure verify the accuracy, quantitative calculation, and impact assessment of power quality problems of charging piles connected to the grid in multiple types and scenarios through single-scenario and mixed-scenario examples. They verify the applicability and accuracy of the method under the access of charging piles in all scenarios and of all types in urban power distribution networks. The analysis results can provide a reliable basis for the construction of charging pile sites, the upgrading and transformation of power distribution networks, and the comprehensive management of power quality.

[0102] This disclosure provides several methods for analyzing the grid-connected power quality of charging piles. By establishing differentiated disturbance models for different types of charging piles, it accurately characterizes the inherent differences in disturbance features among various types of charging piles, solving the technical problem of large disturbance extraction errors in traditional unified modeling methods. Through the analysis of the superposition effect of multiple charging piles in parallel, it quantifies the disturbance deterioration caused by each compound effect, making up for the evaluation blind spot caused by the neglect of cluster superposition effect in traditional methods. Through the multi-scenario influence transmission model, it outputs the step-by-step transmission law of disturbance from charging piles through grid connection points, distribution network lines, transformers to user equipment and the degree of impact on equipment at each stage, filling the gap in existing technologies that only focus on grid connection point indicators and ignore the impact of disturbance transmission downstream along the distribution network, effectively improving the accuracy and systematicness of the analysis of grid-connected power quality problems of multiple types of charging piles.

[0103] It is understood that the various embodiments of the methods described in this specification are presented in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. Related details can be found in the descriptions of other method embodiments.

[0104] It should be understood that although the steps in the flowcharts shown in the accompanying drawings are displayed sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the accompanying drawings may include multiple steps or stages, which are not necessarily completed at the same time, but may be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but may be performed alternately or in turn with other steps or at least a portion of the steps or stages of other steps.

[0105] Based on the description of the above-described embodiments of the charging pile grid-connected power quality analysis method, this disclosure also provides a charging pile grid-connected power quality analysis device for implementing the above-described charging pile grid-connected power quality analysis method. The device may include a system (including a distributed system), software (application), module, component, controller, server, terminal, etc., using the method described in the embodiments of this specification, combined with necessary implementation hardware. Based on the same innovative concept, the devices in one or more embodiments provided by this disclosure are as described in the following embodiments. Since the implementation schemes and methods for solving the problem are similar, the implementation of specific devices in the embodiments of this specification can refer to the implementation of the aforementioned method, and repeated details will not be repeated. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0106] Figure 5 This is a schematic block diagram of a charging pile grid-connected power quality analysis device according to an exemplary embodiment. The device can be the aforementioned terminal, a server, or a module, component, device, control unit, etc., integrated into the terminal. For details, please refer to... Figure 5 The device 100 may include: a first module 110, a second module 120, a third module 130, a fourth module 140, a fifth module 150, a sixth module 160, and a seventh module 170. The system comprises the following modules: Module 110, which acquires basic data of the grid connection point and operational data of the charging piles; Module 120, which establishes disturbance models for each charging pile based on the basic data and operational data, and extracts disturbance parameters from these models; Module 130, which identifies and quantifies power quality issues caused by grid connection of each charging pile based on the disturbance parameters, and obtains quantitative calculation results; Module 140, which performs multi-pile parallel superposition effect analysis based on the quantitative calculation results, and determines the degree of disturbance deterioration after multi-pile mixed grid connection; Module 150, which establishes a multi-scenario impact transmission model based on the disturbance deterioration information and environmental data, and outputs disturbance impact information at each level; Module 160, which classifies the current power quality issues into different severity levels based on the disturbance impact information at each level and multi-dimensional evaluation indicators, and outputs evaluation results; and Module 170, which generates a charging pile grid connection power quality analysis report based on the evaluation results.

[0107] Each module in the aforementioned charging pile grid-connected power quality analysis device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0108] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, communication interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for analyzing the power quality of a charging pile connected to the grid.

[0109] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0110] Based on the foregoing description of the relevant methods and apparatus embodiments, this disclosure also provides a computer device, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, implements the power quality analysis method for charging piles connected to the grid as described in any embodiment of this specification.

[0111] Based on the foregoing description of the relevant methods and apparatus embodiments, this disclosure also provides a computer-readable storage medium that, when the instructions in the computer-readable storage medium are executed by the processor of a computer device, enables the computer device to implement the charging pile grid-connected power quality analysis method as described in any embodiment of this disclosure.

[0112] Based on the foregoing description of the relevant methods and apparatus embodiments, this disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the power quality analysis method for charging piles connected to the grid as described in any embodiment of this specification.

[0113] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, hardware + program embodiments are relatively simple in description because they are fundamentally similar to method embodiments; relevant parts can be referred to the descriptions in the method embodiments.

[0114] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0115] It should be noted that the apparatus, computer equipment, storage medium, and computer program products described above may also include other implementation methods according to the description of the method embodiments. Specific implementation methods can be found in the description of the relevant method embodiments. Furthermore, new embodiments formed by combinations of features from various methods, apparatuses, devices, and server embodiments still fall within the scope of this disclosure and will not be elaborated upon here.

[0116] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, when implementing one or more of these specifications, the functions of each module can be implemented in the same or different software and / or hardware, or a module that performs the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling and communication connections between the devices or units shown or described can be implemented through direct and / or indirect coupling / connection, through standard or custom interfaces or protocols, and can be implemented electrically, mechanically, or in other forms.

[0117] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0118] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for analyzing the power quality of a charging pile connected to the grid, characterized in that, The method includes: Obtain basic data on grid connection points and operational data on charging piles; Based on the basic data and the operational data, a disturbance model is established for each charging pile, and the disturbance model is used to extract disturbance parameters. Based on the disturbance parameters, the power quality problems caused by the grid connection of each charging pile are identified and quantified, and the quantitative calculation results are obtained. Based on the quantitative calculation results, the superposition effect of multiple charging piles in parallel is analyzed to determine the degree of disturbance deterioration after multiple charging piles are mixed and connected to the grid. Based on the information on the degree of disturbance deterioration and combined with environmental data, a multi-scenario impact transmission model is established, which is used to output information on the impact of disturbances at all levels. Based on the information on the impact of the disturbances at all levels and combined with multi-dimensional evaluation indicators, the current power quality problems are classified into different severity levels, and the evaluation results are output. A power quality analysis report for the charging piles connected to the grid is generated based on the evaluation results.

2. The method according to claim 1, characterized in that, The charging piles include at least one of AC slow charging piles, DC conventional charging piles, DC fast charging piles, and supercharging piles; based on the basic data and the operational data, disturbance models are established for each charging pile, including: A single-phase harmonic and unbalance model is established for the AC slow charging pile, a multi-pulse rectifier harmonic model is established for the DC conventional charging pile, a high-frequency harmonic and transient fluctuation model is established for the DC fast charging pile, and a high-power transient impact and oscillation model is established for the supercharging pile.

3. The method according to claim 1, characterized in that, The power quality issues mentioned include at least one of the following: harmonic pollution, voltage deviation and flicker, three-phase imbalance, power factor deterioration, and transient power quality problems. The process of identifying and quantifying the power quality issues caused by grid connection of each charging pile based on the disturbance parameters, and obtaining the quantified calculation results, includes: Determine the extent to which each power quality issue exceeds the standard and the corresponding disturbance contribution rate of the charging pile.

4. The method according to claim 1, characterized in that, The analysis of the multi-pile parallel superposition effect based on the quantitative calculation results, to determine the degree of disturbance deterioration after the mixed grid connection of multiple charging piles, includes: The harmonic superposition effect, transient impact coupling effect and three-phase imbalance cumulative effect of the charging pile cluster during parallel operation are analyzed. The degree of disturbance deterioration caused by each superposition effect is quantified, and the disturbance deterioration information after multiple charging piles are connected to the grid is determined.

5. The method according to claim 1, characterized in that, The disturbance impact information at each level includes at least one of the following: the information on the step-by-step transmission of the disturbance from the charging pile through the grid connection point, distribution network line, transformer to the user equipment; and the information on the degree of impact on distribution network equipment, electrical equipment, metering devices and relay protection devices. The evaluation index includes at least one of the following: disturbance intensity, exceedance multiple, affected area, and degree of harm.

6. The method according to claim 1, characterized in that, The basic data includes at least one of rated voltage, line impedance, short-circuit capacity, transformer capacity, and load rate; the operational data includes at least one of rated power, current charging power, charging mode, start / stop status, number, and grid connection phase of each charging pile; the environmental data includes at least one of load characteristics of the current scenario and grid constraints.

7. A power quality analysis device for charging piles connected to the grid, characterized in that, The device includes: The first module is used to acquire basic data of the grid connection point and operational data of the charging pile; The second module is used to establish a disturbance model for each charging pile based on the basic data and the operating data, and the disturbance model is used to extract disturbance parameters. The third module is used to identify and quantify the power quality problems caused by the grid connection of each charging pile based on the disturbance parameters, and obtain the quantitative calculation results. The fourth module is used to analyze the superposition effect of multiple charging piles in parallel based on the quantitative calculation results, and to determine the degree of disturbance deterioration after multiple charging piles are mixed and connected to the grid. The fifth module is used to establish a multi-scenario impact transmission model based on the disturbance deterioration information and environmental data. The multi-scenario impact transmission model is used to output disturbance impact information at all levels. The sixth module is used to classify the current power quality problem into different severity levels based on the information on the impact of the disturbance at all levels and in combination with multi-dimensional evaluation indicators, and output the evaluation results. The seventh module is used to generate a power quality analysis report for the charging pile based on the evaluation results.

8. A computer device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, It stores a computer program thereon, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1 to 6.

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