Electric energy quality evaluation method, device, equipment, medium and program product

Abstract

The invention provides an electric energy quality assessment method, device and equipment, a medium and a program product, and particularly relates to the technical field of electric energy quality assessment. The method comprises the following steps: constructing a target power grid electromagnetic transient simulation model corresponding to a target power grid, and constructing a distributed resource electromagnetic transient simulation model of distributed resources connected with the target power grid; loading the target power grid electromagnetic transient simulation model and the distributed resource electromagnetic transient simulation model in the electromagnetic transient simulation software, and carrying out electromagnetic transient simulation to obtain electrical quantity dynamic time sequence data at the grid connection point under different operation conditions; and generating an electric energy quality evaluation result based on the electric quantity dynamic time sequence data at the grid-connected point under different operation conditions, the electric energy quality evaluation result being used for evaluating the electric energy quality at the distributed resource grid-connected point in the target power grid. The method is used for achieving the effect of improving the accuracy of power quality evaluation.

Description

Technical Field

[0001] This application relates to the field of power quality assessment technology, and in particular to a power quality assessment method, apparatus, equipment, medium and program product. Background Technology

[0002] With the large-scale integration of power electronic devices such as distributed photovoltaics, wind turbines, energy storage devices, and electric vehicle charging facilities, the traditional distribution network structure dominated by single feeders is gradually evolving into a new type of multi-source coordinated distribution system integrating distributed power sources, the grid, loads, and energy storage. This structural evolution significantly increases the complexity and coupling of system operation, leading to nonlinear and multi-source superposition characteristics in power quality issues. Traditional assessment methods are no longer sufficient to meet the refined planning requirements of scenarios with a high proportion of renewable energy integration.

[0003] Currently, power quality assessment suffers from the following technical shortcomings: Before the integration of distributed generation, static assessment methods based on simplified formulas or empirical curves are typically used. For example, voltage deviation is calculated using the steady-state equations of power and voltage at the grid connection point of distributed resources, or flicker is estimated through empirical table lookup. These methods essentially fall under the category of static steady-state analysis and do not consider the dynamic control characteristics of power electronic equipment and the dynamic response characteristics under multi-source coupling. This leads to significant errors in the assessment results, failing to accurately reflect the actual operating status of the distribution network after a high proportion of new energy sources are integrated, and also failing to support refined planning and decision-making in scenarios of source-grid-load-storage coordination. Summary of the Invention

[0004] This application provides power quality assessment methods, apparatus, equipment, media, and program products to improve the accuracy of power quality assessment.

[0005] In a first aspect, embodiments of this application provide a power quality assessment method, including:

[0006] Construct an electromagnetic transient simulation model of the target power grid corresponding to the target power grid, and construct a distributed resource electromagnetic transient simulation model of the distributed resources connected to the target power grid;

[0007] The electromagnetic transient simulation model of the target power grid and the electromagnetic transient simulation model of the distributed resources are loaded into the electromagnetic transient simulation software, and electromagnetic transient simulation is performed to obtain dynamic time-series data of electrical quantities at the grid connection point under different operating conditions.

[0008] Based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions, a power quality assessment result is generated. The power quality assessment result is an assessment of the power quality at the distributed resource grid connection point in the target power grid.

[0009] In one possible implementation, the method further includes:

[0010] Obtain meteorological and environmental data of the geographical location of the distributed resource;

[0011] A meteorological environment driving model is constructed based on the meteorological environment data. The meteorological environment driving model is used to simulate the changes in meteorological environment parameters and their impact on the output status of distributed resources.

[0012] The meteorological environment driving model is loaded into the electromagnetic transient simulation software, and the meteorological environment driving model is coupled with the distributed resource electromagnetic transient simulation model to simulate the dynamic linkage between meteorological environment parameters and distributed resource output status. The coupling is achieved by defining the mapping relationship between meteorological environment parameters and distributed resource output characteristics.

[0013] In one possible implementation, constructing the electromagnetic transient simulation model of the target power grid corresponding to the target power grid includes:

[0014] Acquire the technical parameters of each primary device in the target power grid, as well as the power dynamic time-series characteristic data of the target power grid under extreme load scenarios;

[0015] Based on the technical parameters of the primary equipment and the power dynamic time-series characteristic data under extreme load scenarios, an electromagnetic transient simulation model of the target power grid is constructed. The primary equipment includes at least one of power supply equipment, line equipment, power distribution equipment, power regulation equipment, control equipment, and charge equipment. The electromagnetic transient simulation model of the target power grid includes a power supply equipment model corresponding to the power supply equipment, a line equipment model corresponding to the line equipment, a power distribution equipment model corresponding to the power distribution equipment, a power regulation equipment model corresponding to the power regulation equipment, a control equipment model corresponding to the control equipment, and a charge equipment model corresponding to the charge equipment.

[0016] In one possible implementation, the construction of a distributed resource electromagnetic transient simulation model connected to the target power grid includes:

[0017] Obtain the technical parameters of distributed resources;

[0018] Based on the technical parameters of the distributed resources, an electromagnetic transient simulation model of the distributed resources is constructed. The distributed resources include at least one of wind power generation system, photovoltaic power generation system and energy storage power generation system. The electromagnetic transient simulation model of the distributed resources includes a wind power generation system model corresponding to the wind power generation system, a photovoltaic power generation system model corresponding to the photovoltaic power generation system and an energy storage power generation system model corresponding to the energy storage power generation system.

[0019] In one possible implementation, generating power quality assessment results based on the dynamic time-series electrical quantities at the grid connection point under different operating conditions includes:

[0020] Power quality assessment indicators are calculated based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions to generate the power quality assessment results. The power quality assessment indicators include at least one of voltage deviation, voltage fluctuation amplitude, flicker, harmonic distortion rate, voltage unbalance, and frequency deviation. Voltage deviation refers to the difference between the supply voltage and the nominal voltage at the grid connection point. Voltage fluctuation amplitude refers to the variation amplitude between adjacent extreme values ​​of the root mean square voltage curve at the grid connection point. Flicker refers to the impact of voltage fluctuation at the grid connection point on visual perception. Harmonic distortion rate refers to the ratio of harmonic voltage to fundamental voltage and / or the ratio of harmonic current to fundamental current at the grid connection point. Voltage unbalance refers to the degree of decrease in the symmetry of the three-phase voltage at the grid connection point. Frequency deviation refers to the difference between the average frequency at the grid connection point and the rated frequency.

[0021] In one possible implementation, the operating conditions include at least one of extreme load operating conditions, extreme weather operating conditions, and fault operating conditions.

[0022] In one possible implementation, generating power quality assessment results based on the dynamic time-series electrical quantities at the grid connection point under different operating conditions includes:

[0023] Based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions, a long-term power quality assessment is performed, and a long-term power quality assessment report is generated. The long-term power quality assessment report includes at least one of the following: annual power quality assessment report, quarterly power quality assessment report, and monthly power quality assessment report.

[0024] Secondly, embodiments of this application provide a power quality assessment device, comprising:

[0025] The construction module is used to construct an electromagnetic transient simulation model of the target power grid corresponding to the target power grid, and to construct a distributed resource electromagnetic transient simulation model of the distributed resources connected to the target power grid.

[0026] The electromagnetic transient simulation module is used to load the target power grid electromagnetic transient simulation model and the distributed resource electromagnetic transient simulation model into the electromagnetic transient simulation software, and to perform electromagnetic transient simulation to obtain dynamic time-series data of electrical quantities at the grid connection point under different operating conditions.

[0027] The generation module is used to generate power quality assessment results based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions. The power quality assessment results are used to assess the power quality at the distributed resource grid connection point in the target power grid.

[0028] In one possible implementation, the power quality assessment device is further used for:

[0029] Obtain meteorological and environmental data of the geographical location of the distributed resource;

[0030] A meteorological environment driving model is constructed based on the meteorological environment data. The meteorological environment driving model is used to simulate the changes in meteorological environment parameters and their impact on the output status of distributed resources.

[0031] The meteorological environment driving model is loaded into the electromagnetic transient simulation software, and the meteorological environment driving model is coupled with the distributed resource electromagnetic transient simulation model to simulate the dynamic linkage between meteorological environment parameters and distributed resource output status. The coupling is achieved by defining the mapping relationship between meteorological environment parameters and distributed resource output characteristics.

[0032] In one possible implementation, the building module is specifically used for:

[0033] Acquire the technical parameters of each primary device in the target power grid, as well as the power dynamic time-series characteristic data of the target power grid under extreme load scenarios;

[0034] Based on the technical parameters of the primary equipment and the power dynamic time-series characteristic data under extreme load scenarios, an electromagnetic transient simulation model of the target power grid is constructed. The primary equipment includes at least one of power supply equipment, line equipment, power distribution equipment, power regulation equipment, control equipment, and charge equipment. The electromagnetic transient simulation model of the target power grid includes a power supply equipment model corresponding to the power supply equipment, a line equipment model corresponding to the line equipment, a power distribution equipment model corresponding to the power distribution equipment, a power regulation equipment model corresponding to the power regulation equipment, a control equipment model corresponding to the control equipment, and a charge equipment model corresponding to the charge equipment.

[0035] In one possible implementation, the building module is specifically used for:

[0036] Obtain the technical parameters of distributed resources;

[0037] Based on the technical parameters of the distributed resources, an electromagnetic transient simulation model of the distributed resources is constructed. The distributed resources include at least one of wind power generation system, photovoltaic power generation system and energy storage power generation system. The electromagnetic transient simulation model of the distributed resources includes a wind power generation system model corresponding to the wind power generation system, a photovoltaic power generation system model corresponding to the photovoltaic power generation system and an energy storage power generation system model corresponding to the energy storage power generation system.

[0038] In one possible implementation, the generation module is specifically used for:

[0039] Power quality assessment indicators are calculated based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions to generate the power quality assessment results. The power quality assessment indicators include at least one of voltage deviation, voltage fluctuation amplitude, flicker, harmonic distortion rate, voltage unbalance, and frequency deviation. Voltage deviation refers to the difference between the supply voltage and the nominal voltage at the grid connection point. Voltage fluctuation amplitude refers to the variation amplitude between adjacent extreme values ​​of the root mean square voltage curve at the grid connection point. Flicker refers to the impact of voltage fluctuation at the grid connection point on visual perception. Harmonic distortion rate refers to the ratio of harmonic voltage to fundamental voltage and / or the ratio of harmonic current to fundamental current at the grid connection point. Voltage unbalance refers to the degree of decrease in the symmetry of the three-phase voltage at the grid connection point. Frequency deviation refers to the difference between the average frequency at the grid connection point and the rated frequency.

[0040] In one possible implementation, the operating conditions include at least one of extreme load operating conditions, extreme weather operating conditions, and fault operating conditions.

[0041] In one possible implementation, the generation module is specifically used for:

[0042] Based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions, a long-term power quality assessment is performed, and a long-term power quality assessment report is generated. The long-term power quality assessment report includes at least one of the following: annual power quality assessment report, quarterly power quality assessment report, and monthly power quality assessment report.

[0043] Thirdly, embodiments of this application provide a power quality assessment device, including: a memory and a processor;

[0044] The memory stores computer-executed instructions;

[0045] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0046] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0047] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0048] The power quality assessment methods, apparatus, equipment, media, and program products provided in this application can construct an electromagnetic transient simulation model of the target power grid that accurately reflects the topology and component parameters of the target power grid. The distributed resource electromagnetic transient simulation model can simulate in detail the generation characteristics, control strategies, and interaction methods with the power grid of distributed resources (such as solar photovoltaic, wind power, etc.). By performing electromagnetic transient simulations under different operating conditions, the dynamic response characteristics under multi-source coupling can be comprehensively reflected. This data not only includes steady-state information but also various dynamic changes during the transient process. By acquiring the actual dynamic changes of electrical quantities at the grid connection point under multi-source coupling, accurate data support can be provided for power quality assessment, thereby improving the accuracy of power quality assessment. Attached Figure Description

[0049] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0050] Figure 1 Flowchart of the power quality assessment method provided in this application Figure 1 ;

[0051] Figure 2 Flowchart of the power quality assessment method provided in this application Figure 2 ;

[0052] Figure 3 A schematic diagram of the evaluation process for the power quality assessment method provided in this application;

[0053] Figure 4 A schematic diagram of the power quality assessment device provided in this application;

[0054] Figure 5 A schematic diagram of the power quality assessment equipment provided in this application.

[0055] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0056] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0057] Currently, power quality assessment before and after distributed resources are connected to the distribution network mainly adopts the following two methods:

[0058] Monitoring and evaluation method: Under the grid-connected operation of distributed power sources, power quality monitoring devices are deployed at the point of common coupling (PCC) to collect and record the measured values ​​of power quality assessment indicators. The measurement results are compared with national standard limits to determine whether the power quality meets the requirements. This method relies on actual operating data and is typically used for power quality assessment after the commissioning of distributed power sources.

[0059] Predictive Assessment Method: Before the integration of distributed power sources, a method based on simplified formulas or empirical models is used to predict power quality assessment indicators. The specific operational process includes: First, obtaining grid topology parameters, bus short-circuit capacity, load data, and basic parameters of distributed power sources; second, calculating the predicted values ​​of each power quality assessment indicator using simplified formulas or lookup tables; finally, comparing the predicted results with national standard limits to provide an assessment conclusion.

[0060] Existing assessment methods rely on simplified formulas or empirical models, typically using power-voltage steady-state relationship derivation or empirical table lookup methods to calculate power quality indicators such as voltage deviation and flicker. These methods suffer from insufficient dynamic characteristic capture capabilities and cannot accurately quantify the dynamic impact of distributed resources on power quality under different operating conditions. Furthermore, existing technologies lack a unified modeling and simulation system, failing to construct an integrated, fully electromagnetic transient simulation model covering grid equipment and distributed resources. This results in the inability to achieve coordinated analysis of steady-state and transient characteristics, and presents a technical limitation due to the lack of description of multi-source coupled dynamic response characteristics.

[0061] This application addresses the technical shortcomings of existing power quality assessment methods for distributed resource access distribution networks, which rely on simplified formula calculations and lack refined model support. It proposes a pre-assessment method for power quality in distributed resource access distribution networks based on electromagnetic transient simulation. This method constructs a comprehensive electromagnetic transient model system covering primary equipment and distributed resources in the distribution network. Combined with typical operating conditions and meteorological load data, it performs continuous simulation for at least 24 hours to extract multi-dimensional power quality assessment indicators such as voltage deviation, voltage fluctuation amplitude, flicker, harmonic distortion rate, voltage imbalance, and frequency deviation. This enables dynamic, full-condition quantitative assessment of power quality before and after distributed resource access, overcoming the technical limitations of traditional methods that cannot reflect the dynamic characteristics of equipment and multi-source coupling effects.

[0062] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0063] Figure 1 Flowchart of the power quality assessment method provided in this application Figure 1 ,like Figure 1 As shown, the method includes:

[0064] S101. Construct an electromagnetic transient simulation model of the target power grid corresponding to the target power grid, and construct an electromagnetic transient simulation model of the distributed resources connected to the target power grid.

[0065] Electromagnetic transient simulation models of the target power grid are designed to accurately simulate the behavior of the target power grid during electromagnetic transient processes. This model needs to reflect the grid's topology, component parameters (such as the resistance, reactance, and capacitance of transmission lines, and the turns ratio and impedance of transformers), and the grid's operating mode (such as power flow distribution under different load levels). Electromagnetic transient simulation models of distributed resources are designed to simulate the dynamic behavior of distributed resources (such as solar photovoltaic, wind power, and energy storage systems) during electromagnetic transient processes. This model needs to consider the generation characteristics of distributed resources, control strategies, and their interaction with the power grid.

[0066] S102. Load the target power grid electromagnetic transient simulation model and the distributed resource electromagnetic transient simulation model into the electromagnetic transient simulation software, and perform electromagnetic transient simulation to obtain dynamic time-series data of electrical quantities at the grid connection point under different operating conditions.

[0067] Loading the constructed target power grid electromagnetic transient simulation model and the distributed resource electromagnetic transient simulation model into the electromagnetic transient simulation software is to integrate these two models into a unified simulation environment for subsequent simulations. Electromagnetic transient simulation aims to obtain dynamic time-series data of electrical quantities at the grid connection point under different operating conditions. This data includes information such as the amplitude, frequency, and phase of electrical quantities like voltage and current during transient processes, realistically reflecting the dynamic behavior of the power grid and distributed resources under various conditions.

[0068] S103. Based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions, generate power quality assessment results. The power quality assessment results are used to assess the power quality at the grid connection point of distributed resources in the target power grid.

[0069] Processing and analyzing the acquired dynamic time-series data of electrical quantities is to extract characteristic information related to power quality, providing a basis for power quality assessment. Based on the extracted power quality characteristic values, assessing the power quality at the grid connection points of distributed resources in the target power grid is to determine whether the power quality of the grid meets relevant standards and requirements after the distributed resources are connected.

[0070] The power quality assessment method provided in this application constructs an electromagnetic transient simulation model of the target power grid, which can accurately reflect the topology and component parameters of the target power grid. The distributed resource electromagnetic transient simulation model can simulate in detail the generation characteristics, control strategies, and interaction methods with the power grid of distributed resources (such as solar photovoltaic, wind power, etc.). By performing electromagnetic transient simulations under different operating conditions, the dynamic response characteristics under multi-source coupling can be comprehensively reflected. This data not only includes steady-state information but also various dynamic changes during the transient process. By acquiring the actual dynamic changes of electrical quantities at the grid connection point under multi-source coupling, accurate data support can be provided for power quality assessment, thereby improving the accuracy of power quality assessment.

[0071] Figure 2 Flowchart of the power quality assessment method provided in this application Figure 2 ,like Figure 2 As shown, in this embodiment... Figure 1 Based on the examples, the power quality assessment method is described in detail, which includes:

[0072] S201. Construct an electromagnetic transient simulation model of the target power grid corresponding to the target power grid, and construct an electromagnetic transient simulation model of the distributed resources connected to the target power grid.

[0073] When constructing an electromagnetic transient simulation model of a target power grid, basic structural information about the target power grid can be obtained. This information is crucial for understanding the overall structure and characteristics of the power grid. For example, the backbone network topology diagram shows the connection relationships between major transmission lines and substations in the power grid, illustrating its skeleton structure; the power grid equivalent impedance diagram is a simplified diagram that represents the various electrical components (such as transformers and transmission lines) in the power grid as impedances; and the short-circuit capacity table for each bus level records the maximum short-circuit current and short-circuit capacity of each bus level in the power grid during a short-circuit fault. The backbone network topology diagram and equivalent impedance diagram clearly demonstrate the connection structure of the power grid, aiding in the analysis of power flow distribution, fault propagation paths, etc. The equivalent impedance diagram and short-circuit capacity table can be used to assess the strength and weakness characteristics of the power grid. In power grid analysis and modeling, basic structural information is the starting point for constructing detailed models. By obtaining the backbone network topology diagram, equivalent impedance diagram, and short-circuit capacity table, a backbone framework can be provided for subsequent detailed model construction.

[0074] In one possible implementation, constructing an electromagnetic transient simulation model of the target power grid corresponding to the target power grid may specifically include the following steps:

[0075] Acquire the technical parameters of each primary device in the target power grid, as well as the power dynamic time-series characteristic data of the target power grid under extreme load scenarios;

[0076] Based on the technical parameters of primary equipment and the power dynamic time-series characteristic data under extreme load scenarios, an electromagnetic transient simulation model of the target power grid is constructed. The primary equipment includes at least one of power supply equipment, line equipment, power distribution equipment, power regulation equipment, control equipment, and charge equipment. The electromagnetic transient simulation model of the target power grid includes a power supply equipment model corresponding to the power supply equipment, a line equipment model corresponding to the line equipment, a power distribution equipment model corresponding to the power distribution equipment, a power regulation equipment model corresponding to the power regulation equipment, a control equipment model corresponding to the control equipment, and a charge equipment model corresponding to the charge equipment.

[0077] Primary equipment is the main physical equipment in a power grid, and its technical parameters determine the electrical characteristics and operational behavior of the grid. Obtaining these parameters is essential for accurately simulating the behavior of primary equipment in electromagnetic transient simulation models.

[0078] Primary equipment includes power supply equipment (such as generators), line equipment (such as transmission lines), power distribution equipment (such as transformers), power regulation equipment (such as reactive power compensation devices), control equipment (such as relay protection devices), and load equipment (such as loads). For each type of equipment, detailed technical parameters are required. For example, for power plants, their total installed capacity should be collected, including the installed capacity, unit type, rated voltage, rated power, apparent power, and power factor adjustment range of both traditional power plants (such as thermal power plants and hydropower plants) and new energy power plants (such as wind farms and photovoltaic power stations). For transformers, collect parameters such as rated capacity, rated voltage, impedance, and cooling method; for transmission lines, collect parameters such as active power, reactive power, and current distribution data; for reactive power compensation devices, collect parameters such as reactive power, current, and switching status data; for circuit breakers and disconnectors, collect parameters such as rated voltage, rated current, and opening / closing time; for each load node, collect parameters such as rated voltage, capacity, and power factor; for substation busbars, collect information on voltage, frequency, active power, reactive power, current, and tap position. Additionally, collect operating signals from protection and secondary equipment to understand the operation of protection devices and the running status of secondary equipment.

[0079] Extreme load scenarios (such as maximum and minimum loads) are extreme cases in power grid operation. Obtaining power dynamic time-series characteristic data under these scenarios is to simulate the operating behavior of the power grid under these extreme conditions in the simulation model, thereby more comprehensively evaluating the performance of the power grid.

[0080] Based on the technical parameters of primary equipment and the power dynamic time-series characteristic data under extreme load scenarios, an electromagnetic transient simulation model of the target power grid is constructed.

[0081] The electromagnetic transient simulation software includes several models. Power supply equipment models simulate the dynamic behavior of power supply equipment (such as generators) during electromagnetic transients, including their generation and regulation characteristics. For example, a rotating electrical machine model can be built based on the Park transform to simulate the electromechanical coupling characteristics of a synchronous generator. Transmission line equipment models simulate the electrical characteristics of transmission lines during electromagnetic transients, including the impact of impedance and capacitance on the process. Based on the obtained technical parameters of the transmission line equipment (such as length, cross-sectional area, and materials), a suitable transmission line model is selected in the simulation software, such as the π-type equivalent model or the Bergeron model. Transformer and distribution equipment models simulate the dynamic behavior of transformers and other transformer and distribution equipment during electromagnetic transients. For transformers, the model can reflect leakage reactance, excitation branches, core losses, and nonlinear saturation characteristics, as well as simulate the impact of tap changers and transient inrush currents on grid operation. Power regulation equipment models simulate the dynamic behavior of power regulation equipment such as reactive power compensation devices during electromagnetic transients, including the impact of their compensation capacity and response time on grid operation. The control equipment model is used to simulate the dynamic behavior of control equipment such as relay protection devices during electromagnetic transient processes, including the impact of their protection settings and operating times on power grid operation. The load equipment model is used to simulate the dynamic behavior of loads during electromagnetic transient processes, including the impact of their power factor and load characteristics on power grid operation. For example, a combination of static ZIP and dynamic motor models can be used to reflect the influence of voltage and frequency on load characteristics.

[0082] In one possible implementation, constructing a distributed resource electromagnetic transient simulation model connected to the target power grid may specifically include the following steps:

[0083] Obtain the technical parameters of distributed resources;

[0084] Based on the technical parameters of distributed resources, an electromagnetic transient simulation model of distributed resources is constructed. Distributed resources include at least one of wind power generation systems, photovoltaic power generation systems, and energy storage power generation systems. The electromagnetic transient simulation model of distributed resources includes a wind power generation system model corresponding to the wind power generation system, a photovoltaic power generation system model corresponding to the photovoltaic power generation system, and an energy storage power generation system model corresponding to the energy storage power generation system.

[0085] Obtaining the technical parameters of distributed resources is essential for accurately simulating their electrical characteristics and dynamic behavior in electromagnetic transient simulation models. For example, for wind power systems, parameters such as rated power, rated voltage, speed range, motor type, converter parameters, and pitch angle control parameters of the wind turbine can be obtained. For photovoltaic power systems, parameters such as rated power, rated voltage, photoelectric conversion efficiency, temperature coefficient, and maximum power point voltage of the photovoltaic cells, as well as converter parameters and boost / buck converter parameters, can be obtained. For energy storage power generation systems, parameters such as rated capacity, rated voltage, charge / discharge rate, internal resistance, and cycle life of the storage battery, as well as converter parameters, can be obtained.

[0086] Based on the technical parameters of distributed resources, an electromagnetic transient simulation model of distributed resources is constructed, including a wind power generation system model, a photovoltaic power generation system model, and an energy storage power generation system model. The wind power generation system model includes a motor model (selecting an appropriate motor model based on the type of wind turbine (e.g., permanent magnet synchronous motor, doubly-fed induction generator, etc.), a machine-side converter model (simulating the electrical characteristics of the machine-side converter), a grid-side converter model (simulating the electrical characteristics of the grid-side converter), a DC circuit model (simulating the electrical characteristics of the DC circuit), a filter circuit model (simulating the electrical characteristics of the filter circuit), a pitch angle control model (simulating the pitch angle control strategy), a machine-side converter control model (simulating the control strategy of the machine-side converter), a grid-side converter control model (simulating the control strategy of the grid-side converter), a low-voltage ride-through control model (simulating the low-voltage ride-through control strategy), and a high-voltage ride-through control model (simulating the high-voltage ride-through control strategy).

[0087] The photovoltaic power generation system model includes a photovoltaic cell model (selecting an appropriate photovoltaic cell model based on the type of photovoltaic cell (e.g., monocrystalline silicon, polycrystalline silicon, etc.), a converter model (simulating the electrical characteristics of the converter), a boost / buck converter model (simulating the electrical characteristics of the boost / buck converter), a filter circuit model (simulating the electrical characteristics of the filter circuit), a maximum power point tracking control model (simulating the maximum power point tracking (MPPT) control strategy), a converter control model (simulating the converter control strategy), a boost / buck converter control model (simulating the boost / buck converter control strategy), a low voltage ride-through control model (simulating the low voltage ride-through control strategy), and a high voltage ride-through control model (simulating the high voltage ride-through control strategy).

[0088] The energy storage power generation system model includes a battery model (selecting an appropriate battery model based on the type of battery (such as lithium-ion battery, lead-acid battery, etc.), a converter model (simulating the electrical characteristics of the converter), a filter circuit model (simulating the electrical characteristics of the filter circuit), and a converter control model (simulating the control strategy of the converter).

[0089] Based on the above simulation model and through the electromagnetic transient simulation platform, the power quality assessment of distributed resources after grid connection can be realized.

[0090] S202. Load the target power grid electromagnetic transient simulation model and the distributed resource electromagnetic transient simulation model into the electromagnetic transient simulation software, and perform electromagnetic transient simulation to obtain dynamic time-series data of electrical quantities at the grid connection point under different operating conditions.

[0091] Different operating conditions are set in the electromagnetic transient simulation software, such as normal operating conditions (different load levels, different distributed resource outputs), fault conditions (line short circuits, line breaks, etc.), and distributed resource access and disconnection conditions. Then, the simulation is started, and the software calculates the changes in electrical quantities of the power grid and distributed resources during the transient process based on the set operating conditions and model parameters. During the simulation, the curves of these electrical quantities can be observed in real time, and this data is recorded. For example, when simulating a short-circuit fault in the power grid line, the simulation software calculates the sudden changes in voltage and current at the grid connection point at the moment of the fault, and records the curves of these electrical quantities changing over time.

[0092] In one possible implementation, the operating conditions include at least one of extreme load operating conditions, extreme weather operating conditions, and fault operating conditions.

[0093] Extreme load operating conditions refer to the operating state under maximum or minimum load conditions. Extreme weather operating conditions refer to the operating state under extreme weather conditions, such as high temperature, low temperature, heavy rain, blizzard, lightning, etc. Fault operating conditions refer to the operating state when a fault occurs, such as short circuit, open circuit, equipment failure, etc.

[0094] S203. Based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions, generate power quality assessment results. The power quality assessment results are used to assess the power quality at the grid connection point of distributed resources in the target power grid.

[0095] In one possible implementation, power quality assessment results are generated based on dynamic time-series data of electrical quantities at the grid connection point under different operating conditions. Specifically, this may include the following steps:

[0096] Power quality assessment indicators are calculated based on dynamic time-series data of electrical quantities at the grid connection point under different operating conditions to generate power quality assessment results. Power quality assessment indicators include at least one of the following: voltage deviation, voltage fluctuation amplitude, flicker, harmonic distortion rate, voltage unbalance, and frequency deviation. Voltage deviation refers to the difference between the supply voltage and the nominal voltage at the grid connection point. Voltage fluctuation amplitude refers to the variation amplitude between adjacent extreme values ​​of the root mean square voltage curve at the grid connection point. Flicker refers to the impact of voltage fluctuation at the grid connection point on visual perception. Harmonic distortion rate refers to the ratio of harmonic voltage to fundamental voltage and / or the ratio of harmonic current to fundamental current at the grid connection point. Voltage unbalance refers to the degree of decrease in the symmetry of the three-phase voltage at the grid connection point. Frequency deviation refers to the difference between the average frequency at the grid connection point and the rated frequency.

[0097] In this embodiment, voltage deviation refers to the difference between the supply voltage at the grid connection point and the nominal voltage. The supply voltage at the grid connection point can be sampled and processed to obtain a voltage RMS value sequence. The RMS value sequence is then averaged to obtain the average RMS voltage measurement. Finally, the voltage deviation is calculated using the following formula:

[0098] ;

[0099] in, The average value of the voltage RMS is measured. This is the nominal voltage.

[0100] Voltage fluctuation amplitude refers to the variation between adjacent extreme values ​​of the root-mean-square (RMS) voltage curve at the grid connection point. The supply voltage at the grid connection point can be sampled and processed to obtain a voltage RMS sequence. Based on this sequence, a RMS voltage curve is generated. Adjacent extreme values ​​of the RMS voltage curve are compared to obtain the voltage fluctuation amplitude. Then, using the nominal voltage as a benchmark, a voltage fluctuation index is calculated to quantitatively assess the short-term voltage fluctuation level. The calculation formula is as follows:

[0101] ;

[0102] in, The difference between two adjacent extreme values ​​on the root-mean-square voltage curve obtained from electromagnetic transient simulation. This is the nominal voltage.

[0103] Flicker refers to the impact of voltage fluctuations at the grid connection point on visual perception. Based on the voltage waveform output at the grid connection point using electromagnetic transient simulation, a preset digital flicker algorithm is used to calculate the short-time flicker value. and long-term flicker value By comparing the long-term flicker values ​​of distributed resources during grid-connected operation and during shutdown, the contribution of distributed resources to the flicker level is obtained. The calculation formula is as follows:

[0104] ;

[0105] in, , These are the long-term flicker values ​​when distributed resources are running in the network and when they are shut down, respectively.

[0106] Harmonic distortion rate refers to the ratio of harmonic voltage to fundamental voltage and / or the ratio of harmonic current to fundamental current at the grid connection point. Based on the voltage and current waveforms output at the grid connection point from electromagnetic transient simulation, Fast Fourier Transform (FFT) is used to decompose the fundamental and harmonic components, and the harmonic distortion rate is calculated.

[0107] The harmonic distortion rate R5 reflects the ratio of harmonic current to fundamental current, and is calculated using the following formula:

[0108] ;

[0109] in, Harmonic current, This is the fundamental current (root mean square value).

[0110] The voltage harmonic distortion rate R6 reflects the ratio of harmonic voltage to fundamental voltage, and is calculated using the following formula:

[0111] ;

[0112] in, Harmonic voltage content, This is the fundamental voltage (root mean square value).

[0113] The above calculations can be used to assess the level of harmonic pollution caused by distributed resource grid connection.

[0114] Voltage unbalance refers to the degree of decrease in the symmetry of the three-phase voltage at the grid connection point. The three-phase voltage waveform at the grid connection point can be extracted and decomposed using the symmetrical component method to obtain the positive-sequence, negative-sequence, and zero-sequence components. The negative-sequence voltage unbalance R7 is calculated to characterize the degree of decrease in the symmetry of the three-phase voltage after grid connection. The calculation formula is as follows:

[0115] ;

[0116] in, This refers to the negative sequence voltage imbalance. This represents the root-mean-square value of the negative-sequence fundamental component of the three-phase voltage. This represents the root mean square value of the positive sequence fundamental component of the three-phase voltage.

[0117] Frequency deviation refers to the difference between the average frequency at the grid connection point and the rated frequency. By tracking the voltage phasor in electromagnetic transient simulation using a synchronous coordinate system phase-locked loop (PLL), the instantaneous frequency at the grid connection point is extracted, and the average frequency is calculated. The frequency deviation R8 is then calculated to evaluate the impact of distributed resource grid connection on system frequency stability. The calculation formula is as follows:

[0118] ;

[0119] Where f is the average frequency of grid connection points. This is the system's rated frequency.

[0120] By using dynamic time-series data of electrical quantities at the grid connection point under different operating conditions, power quality assessment indicators are calculated. These indicators are then compared with standard limits to comprehensively evaluate the impact of distributed generation on grid power quality. If all indicators meet the standard requirements, grid-connected operation of distributed generation is recommended; otherwise, improvement measures are needed. This method provides a scientific basis for the integration of distributed generation, ensuring the safe, stable, and efficient operation of the power grid.

[0121] In one possible implementation, power quality assessment results are generated based on dynamic time-series data of electrical quantities at the grid connection point under different operating conditions. Specifically, this may include the following steps:

[0122] Based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions, a long-term power quality assessment is conducted, and a long-term power quality assessment report is generated. The long-term power quality assessment report includes at least one of the following: annual power quality assessment report, quarterly power quality assessment report, and monthly power quality assessment report.

[0123] Long-term power quality assessment refers to the continuous monitoring and evaluation of power quality in order to generate assessment reports for different time periods.

[0124] S204. Obtain meteorological and environmental data of the geographical location of the distributed resource.

[0125] Given the strong correlation between distributed renewable energy output and meteorological conditions, this application further collects key meteorological data at the grid connection point, including ambient temperature, solar radiation intensity, and eastward wind speeds at 10 meters and 50 meters above the ground. This meteorological data will serve as the core input for driving the dynamic response of electromagnetic transient simulation models of distributed resources such as photovoltaics and wind power, ensuring that the simulation results are highly sensitive and reliable to environmental changes, thereby providing an accurate data foundation for subsequent power quality assessments.

[0126] S205. Construct a meteorological environment-driven model based on meteorological environment data. The meteorological environment-driven model is used to simulate the changes in meteorological environment parameters and their impact on the output status of distributed resources.

[0127] A model is constructed to simulate changes in meteorological environmental parameters and their impact on the output status of distributed energy resources.

[0128] S206. Load the meteorological environment driving model into the electromagnetic transient simulation software, and couple the meteorological environment driving model with the distributed resource electromagnetic transient simulation model to simulate the dynamic linkage between meteorological environment parameters and distributed resource output status. The coupling is achieved by defining the mapping relationship between meteorological environment parameters and distributed resource output characteristics.

[0129] By coupling a meteorological environment-driven model and a distributed resource electromagnetic transient simulation model, the dynamic interaction between meteorological environment parameters and the output state of distributed resources is simulated. During the simulation, the meteorological environment parameters output by the meteorological environment-driven model are transmitted to the distributed resource electromagnetic transient simulation model in real time, and the distributed resource electromagnetic transient simulation model dynamically adjusts its output state based on these parameters.

[0130] Reference Figure 3 The diagram illustrates the evaluation process of the power quality assessment method provided in this application. Specifically, it includes: collecting target grid equipment parameters; collecting power dynamic time-series characteristic data under extreme load scenarios to construct an electromagnetic transient simulation model of the target grid; collecting meteorological environment data at the grid connection point to construct a meteorological environment-driven model; collecting technical parameters of distributed resources to construct an electromagnetic transient simulation model of distributed resources; determining various power quality assessment indicators and their corresponding standard limits; constructing a full electromagnetic transient simulation model of the assessment grid and distributed resources and performing simulations in electromagnetic transient simulation software, specifically integrating the target grid electromagnetic transient simulation model, the meteorological environment-driven model, and the distributed resource electromagnetic transient simulation model to construct a comprehensive electromagnetic transient simulation model; calculating various power quality assessment indicators based on the simulation data; and generating a final assessment result report based on the calculated power quality assessment indicators.

[0131] The power quality assessment method provided in this application constructs an electromagnetic transient simulation model of the target power grid, which can accurately reflect the topology and component parameters of the target power grid. The distributed resource electromagnetic transient simulation model can simulate in detail the generation characteristics, control strategies, and interaction methods with the power grid of distributed resources (such as solar photovoltaic, wind power, etc.). By performing electromagnetic transient simulations under different operating conditions, the dynamic response characteristics under multi-source coupling can be comprehensively reflected. This data not only includes steady-state information but also various dynamic changes during the transient process. By acquiring the actual dynamic changes of electrical quantities at the grid connection point under multi-source coupling, accurate data support can be provided for power quality assessment, thereby improving the accuracy of power quality assessment.

[0132] Figure 4 A schematic diagram of the power quality assessment device provided in this application is shown below. Figure 4 As shown, the power quality assessment device 40 provided in this embodiment includes:

[0133] Module 401 is used to construct an electromagnetic transient simulation model of the target power grid corresponding to the target power grid, and to construct an electromagnetic transient simulation model of the distributed resources connected to the target power grid.

[0134] The electromagnetic transient simulation module 402 is used to load the target power grid electromagnetic transient simulation model and the distributed resource electromagnetic transient simulation model into the electromagnetic transient simulation software, and to perform electromagnetic transient simulation to obtain dynamic time-series data of electrical quantities at the grid connection point under different operating conditions.

[0135] The generation module 403 is used to generate power quality assessment results based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions. The power quality assessment results are used to assess the power quality at the grid connection point of distributed resources in the target power grid.

[0136] In one possible implementation, the power quality assessment device is further used for:

[0137] Obtain meteorological and environmental data of the geographical location of the distributed resources;

[0138] A meteorological environment-driven model is constructed based on meteorological environment data. The meteorological environment-driven model is used to simulate the changes in meteorological environment parameters and their impact on the output status of distributed resources.

[0139] A meteorological environment-driven model is loaded into the electromagnetic transient simulation software, and the meteorological environment-driven model is coupled with the distributed resource electromagnetic transient simulation model to simulate the dynamic linkage between meteorological environment parameters and the output state of distributed resources. The coupling is achieved by defining the mapping relationship between meteorological environment parameters and the output characteristics of distributed resources.

[0140] In one possible implementation, the building module is specifically used for:

[0141] Acquire the technical parameters of each primary device in the target power grid, as well as the power dynamic time-series characteristic data of the target power grid under extreme load scenarios;

[0142] Based on the technical parameters of primary equipment and the power dynamic time-series characteristic data under extreme load scenarios, an electromagnetic transient simulation model of the target power grid is constructed. The primary equipment includes at least one of power supply equipment, line equipment, power distribution equipment, power regulation equipment, control equipment, and charge equipment. The electromagnetic transient simulation model of the target power grid includes a power supply equipment model corresponding to the power supply equipment, a line equipment model corresponding to the line equipment, a power distribution equipment model corresponding to the power distribution equipment, a power regulation equipment model corresponding to the power regulation equipment, a control equipment model corresponding to the control equipment, and a charge equipment model corresponding to the charge equipment.

[0143] In one possible implementation, the building module is specifically used for:

[0144] Obtain the technical parameters of distributed resources;

[0145] Based on the technical parameters of distributed resources, an electromagnetic transient simulation model of distributed resources is constructed. Distributed resources include at least one of wind power generation systems, photovoltaic power generation systems, and energy storage power generation systems. The electromagnetic transient simulation model of distributed resources includes a wind power generation system model corresponding to the wind power generation system, a photovoltaic power generation system model corresponding to the photovoltaic power generation system, and an energy storage power generation system model corresponding to the energy storage power generation system.

[0146] In one possible implementation, the generation module is specifically used for:

[0147] Power quality assessment indicators are calculated based on dynamic time-series data of electrical quantities at the grid connection point under different operating conditions to generate power quality assessment results. Power quality assessment indicators include at least one of the following: voltage deviation, voltage fluctuation amplitude, flicker, harmonic distortion rate, voltage unbalance, and frequency deviation. Voltage deviation refers to the difference between the supply voltage and the nominal voltage at the grid connection point. Voltage fluctuation amplitude refers to the variation amplitude between adjacent extreme values ​​of the root mean square voltage curve at the grid connection point. Flicker refers to the impact of voltage fluctuation at the grid connection point on visual perception. Harmonic distortion rate refers to the ratio of harmonic voltage to fundamental voltage and / or the ratio of harmonic current to fundamental current at the grid connection point. Voltage unbalance refers to the degree of decrease in the symmetry of the three-phase voltage at the grid connection point. Frequency deviation refers to the difference between the average frequency at the grid connection point and the rated frequency.

[0148] In one possible implementation, the operating conditions include at least one of extreme load operating conditions, extreme weather operating conditions, and fault operating conditions.

[0149] In one possible implementation, the generation module is specifically used for:

[0150] Based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions, a long-term power quality assessment is conducted, and a long-term power quality assessment report is generated. The long-term power quality assessment report includes at least one of the following: annual power quality assessment report, quarterly power quality assessment report, and monthly power quality assessment report.

[0151] The power quality assessment device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0152] Figure 5 A schematic diagram of the power quality assessment equipment provided in this application. Figure 5 As shown, the power quality assessment device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus.

[0153] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0154] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0155] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0156] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0157] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0158] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0159] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0160] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0161] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0162] The division of units is merely 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 or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0163] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0164] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0165] If a function 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 invention, or the part that contributes to the prior art, or a 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 includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0166] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0167] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and 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. The scope of the invention is limited only by the appended claims.

Claims

1. A method for assessing power quality, characterized in that, include: Construct an electromagnetic transient simulation model of the target power grid corresponding to the target power grid, and construct a distributed resource electromagnetic transient simulation model of the distributed resources connected to the target power grid; The electromagnetic transient simulation model of the target power grid and the electromagnetic transient simulation model of the distributed resources are loaded into the electromagnetic transient simulation software, and electromagnetic transient simulation is performed to obtain dynamic time-series data of electrical quantities at the grid connection point under different operating conditions. Based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions, a power quality assessment result is generated. The power quality assessment result is an assessment of the power quality at the grid connection point of distributed resources in the target power grid.

2. The method according to claim 1, characterized in that, The method further includes: Obtain meteorological and environmental data of the geographical location of the distributed resource; A meteorological environment driving model is constructed based on the meteorological environment data. The meteorological environment driving model is used to simulate the changes in meteorological environment parameters and their impact on the output status of distributed resources. The meteorological environment driving model is loaded into the electromagnetic transient simulation software, and the meteorological environment driving model is coupled with the distributed resource electromagnetic transient simulation model to simulate the dynamic linkage between meteorological environment parameters and distributed resource output status. The coupling is achieved by defining the mapping relationship between meteorological environment parameters and distributed resource output characteristics.

3. The method according to claim 1 or 2, characterized in that, The construction of the electromagnetic transient simulation model of the target power grid corresponding to the target power grid includes: Acquire the technical parameters of each primary device in the target power grid, as well as the power dynamic time-series characteristic data of the target power grid under extreme load scenarios; Based on the technical parameters of the primary equipment and the power dynamic time-series characteristic data under extreme load scenarios, an electromagnetic transient simulation model of the target power grid is constructed. The primary equipment includes at least one of power supply equipment, line equipment, power distribution equipment, power regulation equipment, control equipment, and charge equipment. The electromagnetic transient simulation model of the target power grid includes a power supply equipment model corresponding to the power supply equipment, a line equipment model corresponding to the line equipment, a power distribution equipment model corresponding to the power distribution equipment, a power regulation equipment model corresponding to the power regulation equipment, a control equipment model corresponding to the control equipment, and a charge equipment model corresponding to the charge equipment.

4. The method according to claim 1 or 2, characterized in that, The construction of a distributed resource electromagnetic transient simulation model connected to the target power grid includes: Obtain the technical parameters of distributed resources; Based on the technical parameters of the distributed resources, an electromagnetic transient simulation model of the distributed resources is constructed. The distributed resources include at least one of wind power generation system, photovoltaic power generation system and energy storage power generation system. The electromagnetic transient simulation model of the distributed resources includes a wind power generation system model corresponding to the wind power generation system, a photovoltaic power generation system model corresponding to the photovoltaic power generation system and an energy storage power generation system model corresponding to the energy storage power generation system.

5. The method according to claim 1 or 2, characterized in that, The generation of power quality assessment results based on the dynamic time-series electrical quantities at the grid connection point under different operating conditions includes: Power quality assessment indicators are calculated based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions to generate the power quality assessment results. The power quality assessment indicators include at least one of voltage deviation, voltage fluctuation amplitude, flicker, harmonic distortion rate, voltage unbalance, and frequency deviation. Voltage deviation refers to the difference between the supply voltage and the nominal voltage at the grid connection point. Voltage fluctuation amplitude refers to the variation amplitude between adjacent extreme values ​​of the root mean square voltage curve at the grid connection point. Flicker refers to the impact of voltage fluctuation at the grid connection point on visual perception. Harmonic distortion rate refers to the ratio of harmonic voltage to fundamental voltage and / or the ratio of harmonic current to fundamental current at the grid connection point. Voltage unbalance refers to the degree of decrease in the symmetry of the three-phase voltage at the grid connection point. Frequency deviation refers to the difference between the average frequency at the grid connection point and the rated frequency.

6. The method according to claim 1 or 2, characterized in that, The operating conditions include at least one of the following: extreme load operating conditions, extreme weather operating conditions, and fault operating conditions.

7. The method according to claim 1 or 2, characterized in that, The generation of power quality assessment results based on the dynamic time-series electrical quantities at the grid connection point under different operating conditions includes: Based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions, a long-term power quality assessment is performed, and a long-term power quality assessment report is generated. The long-term power quality assessment report includes at least one of the following: annual power quality assessment report, quarterly power quality assessment report, and monthly power quality assessment report.

8. A power quality assessment device, characterized in that, include: The construction module is used to construct an electromagnetic transient simulation model of the target power grid corresponding to the target power grid, and to construct a distributed resource electromagnetic transient simulation model of the distributed resources connected to the target power grid. The electromagnetic transient simulation module is used to load the target power grid electromagnetic transient simulation model and the distributed resource electromagnetic transient simulation model into the electromagnetic transient simulation software, and to perform electromagnetic transient simulation to obtain dynamic time-series data of electrical quantities at the grid connection point under different operating conditions. The generation module is used to generate power quality assessment results based on the dynamic time-series data of electrical quantities at the grid connection point under different operating conditions. The power quality assessment results are used to assess the power quality at the distributed resource grid connection point in the target power grid.

9. A power quality assessment device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium or computer program product, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7; or, The computer program product includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

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