Parameter analysis method and device for aggregated IBR and load of power system, and medium

Abstract

The invention discloses a power system aggregation IBR and load parameter analysis method and device and a medium, and belongs to the technical field of power systems. The method comprises the following steps: acquiring power system operation data; identifying change modes of the operation data of the power system, and calculating voltage sensitivity values of the pre-constructed composite IBR and ZIP load models in each change mode; taking the deviation of the voltage sensitivity value as a steady-state index, and extracting a power system operation data window with a stable change mode from the power system operation data; and taking a power system operation data window with a stable change mode as a quasi-steady-state window, and performing parameter analysis on the composite IBR and ZIP load model according to the quasi-steady-state window to obtain a parameter analysis result. According to the method, the voltage-related behaviors of the load and the capacity of the adaptive mode to adapt to the IBR control mode change can be considered, and errors in parameter analysis are avoided.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a method, apparatus and medium for parameter analysis of power system integrated IBR and load. Background Technology

[0002] Modern power systems have developed rapidly in recent years due to the rapid integration of inverter-based resources (IBRs). Electricity consumers have become prosumers contributing a significant share of energy to the grid, and advancements in smart inverter technology mean that virtually all producers can provide some reactive power support to the network. This development has the potential to enable operators to address the uneven voltage distribution in the distribution network resulting from the distributed deployment of IBRs. For power system operators, understanding the voltage-related behavior of producers is crucial for the accuracy of power system research and the development of future control strategies.

[0003] The challenge lies in the fact that almost all IBRs in low-voltage distribution networks are behind-the-meter (BTM), and operators have very limited or no user-side generation curve data. Without such data, operators cannot properly plan voltage control while taking into account the reactive power capacity of these user-side generators. Therefore, a key motivation for power company operators is to decompose load and generation from aggregated consumption data. Many researchers have focused on photovoltaic-load decomposition to better understand the user-side generation-load combination, but there has been limited attention paid to inverter control mode estimation and aggregated load parameter estimation, considering IBR penetration at BTMs and the voltage-dependent behavior of the load. A key aspect missing from these decomposition studies is the lack of knowledge about the voltage-dependent behavior of IBRs and loads. Few studies have attempted to estimate IBR control parameters from decomposed data, but these studies do not consider all voltage control modes or model load voltage dependence. The main problems in online IBR control mode identification and load / IBR parameter estimation can be summarized as follows:

[0004] The lack of a composite aggregation modeling method for IBR and load, the current load and IBR decomposition methods do not take into account the voltage-dependent behavior of the load, which may lead to inaccuracies in the decomposition process, and the parameter estimation based on such decomposition is prone to error. Most load parameter estimation methods assume that the composition in the measured flow is the same, which leads to a lack of ability to adapt to IBR variation control modes in an adaptive manner. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method, device and medium for parameter analysis of power system integrated IBR and load, which can take into account the voltage-related behavior of the load and the ability to adapt to changes in IBR control mode in an adaptive manner, thus avoiding errors in parameter analysis.

[0006] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0007] On the one hand, the present invention provides a parameter analysis method for power system aggregated IBR and load, including:

[0008] Acquire power system operation data;

[0009] Identify the changing patterns of power system operation data, calculate the voltage sensitivity values ​​of pre-built composite IBR and ZIP load models under each changing pattern; obtain pre-built composite IBR and ZIP load models by aggregating the ZIP load model and the IBR model under voltage active control mode or voltage reactive control mode.

[0010] Using the deviation of voltage sensitivity as a steady-state index, a window of stable power system operation data with changing patterns is extracted from power system operation data.

[0011] Using the stable operating data window of the power system with a stable change mode as a quasi-steady-state window, the composite IBR and ZIP load models are subjected to parameter analysis based on the quasi-steady-state window, and the parameter analysis results are obtained.

[0012] Optionally, the ZIP load model is expressed as:

[0013] ;

[0014] ;

[0015] in, , These represent the active power and reactive power of the load at time t, respectively. , These represent the reference power of active load and the reference power of reactive load, respectively. This represents the load-side voltage at time t; , , The active power parameter representing the load; , , This represents the reactive power parameter of the load.

[0016] Optionally, the IBR model of the voltage active power control mode is represented as follows:

[0017] ;

[0018] ;

[0019] in, , These represent the active power and reactive power of the IBR under the voltage active power control mode at time t, respectively. This indicates the maximum active power of the inverter under voltage active control mode; This represents the load-side voltage at time t; , This represents the IBR parameters to be analyzed under voltage active mode; Indicates the constant power region; Represents a linear region; Indicates the area to be cut off or reduced; This indicates the reactive power output of the inverter.

[0020] Optionally, the IBR model of the voltage reactive power control mode is represented as follows:

[0021] ;

[0022] ;

[0023] ;

[0024] ;

[0025] in, , These represent the active power and reactive power of the IBR under voltage reactive power control mode at time t, respectively. This indicates the rated active power of the IBR; This indicates the rated apparent power of the IBR; This indicates the maximum active power available to the inverter under the current irradiance conditions; Indicates solar irradiance; This indicates the maximum reactive power of the inverter under voltage reactive power control mode. This represents the load-side voltage at time t; , , , This represents the IBR parameters to be analyzed under voltage reactive mode; Indicates the maximum reactive power supply area; Indicates the linear region of power generation; Indicates the dead zone; Indicates the linear absorption region; This indicates the region of maximum reactive power absorption.

[0026] Optionally, the composite IBR and ZIP load model is expressed as follows:

[0027] ;

[0028] ;

[0029] in, , Let represent the combined active power and combined reactive power of the combined IBR and ZIP load models at time t, respectively; , These represent the active power and reactive power of the load at time t, respectively. , These represent the active power and reactive power of the IBR under the voltage active power control mode at time t, respectively. , These represent the active power and reactive power of the IBR under voltage reactive power control mode at time t, respectively.

[0030] Optionally, the formula for calculating the voltage sensitivity value of the composite IBR and ZIP load model is as follows:

[0031] ;

[0032] ;

[0033] ;

[0034] in, , Let represent the voltage and active power of the composite IBR and ZIP load models at time t, respectively. , These represent the slopes of voltage and active power over time for the composite IBR and ZIP load models, respectively. , Indicates the offset; Indicates the length of time; This represents the voltage sensitivity value for the composite IBR and ZIP load models.

[0035] Optionally, the deviation of the voltage sensitivity value can be used as a steady-state index to obtain a power system operating data window with stable changing modes, including:

[0036] Obtain from power system operation data Using a sample as the k-th analysis window, calculate the voltage sensitivity value of the composite IBR and ZIP load model for the k-th analysis window. ;

[0037] like Then the k-th analysis window will be temporarily increased. The nth sample, yielding the nth... The temporary window calculates the... Voltage sensitivity values ​​of temporary window composite IBR and ZIP load models ;like Then move the window's starting point to the right. One sample, and the analysis window is re-obtained from the power system operation data;

[0038] like Then calculate the first Deviation of voltage sensitivity values ​​for temporary window composite IBR and ZIP load models ;like Then discard the first A temporary window is used, and the k-th analysis window is used as the operating data window for a power system with stable change patterns;

[0039] like And the length of the kth analysis window is less than If there are 10 samples, then move the starting point of the window to the right. For each sample, a new analysis window is obtained from the power system operation data; if And the length of the k-th analysis window is not less than The nth sample, then the nth Before the temporary window A new window composed of samples serves as the operating data window for a power system with a stable change pattern; if Then discard the first A temporary window is used, and the k-th analysis window is used as the operating data window for a power system with stable change patterns;

[0040] in, , These represent the minimum sample size and the maximum sample size, respectively. Indicates the sample shift; The threshold value representing the deviation of the voltage sensitivity value.

[0041] Optionally, based on the parameter eigenvectors, parameter analysis is performed on the composite IBR and ZIP load models to obtain the parameter analysis results, as shown in the formula:

[0042] ;

[0043] ;

[0044] ;

[0045] ;

[0046] in, Represents the parameter eigenvector; , These represent the voltage and active power of the composite IBR and ZIP load models, respectively. Indicates the feature extraction operator; , , The active power parameter representing the load; , , Represents the reactive power parameters of the load; This refers to a machine learning tool used for load parameter analysis. , This represents the IBR parameters to be analyzed under voltage active mode; This indicates the maximum active power of the inverter under voltage active control mode; This represents a machine learning tool used for IBR parameter analysis under voltage active control mode. , , , This represents the IBR parameters to be analyzed under voltage reactive mode; This indicates the maximum reactive power of the inverter under voltage reactive power control mode. This represents a machine learning tool used for IBR parameter analysis in voltage reactive power control mode.

[0047] Secondly, the present invention provides a parameter analysis device for power system integrated IBR and load, comprising:

[0048] The data acquisition module is used to acquire power system operation data.

[0049] The sensitivity calculation module is used to: identify the changing patterns of power system operation data, calculate the voltage sensitivity values ​​of pre-built composite IBR and ZIP load models under each changing pattern; and obtain pre-built composite IBR and ZIP load models by aggregating the ZIP load model and the IBR model under voltage active control mode or voltage reactive control mode.

[0050] The stability identification module is used to: use the deviation of voltage sensitivity value as a steady-state indicator to extract a stable power system operation data window from the power system operation data;

[0051] The parameter analysis module is used to: take the stable power system operation data window with changing modes as a quasi-steady-state window, perform parameter analysis on the composite IBR and ZIP load models based on the quasi-steady-state window, and obtain the parameter analysis results.

[0052] Thirdly, the present invention provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implements the steps of the parameter analysis method for power system aggregated IBR and load as described in the first aspect.

[0053] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0054] This invention captures the aggregation behavior of the load by combining IBR and load aggregation modeling, and considers the voltage-related behavior of the load, making the load and IBR decomposition process accurate. The parameter analysis based on this decomposition is less prone to error and has the ability to adapt to IBR change control mode in an adaptive manner. Based on data sensitivity analysis, the same sensitivity analysis and feature recognition framework is used to estimate the parameters of the aggregation model. Attached Figure Description

[0055] Figure 1 The diagram shown is a flowchart of one embodiment of the parameter analysis method for power system aggregated IBR and load of the present invention. Detailed Implementation

[0056] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0057] The term "and / or" simply describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0058] Example 1

[0059] like Figure 1 As shown in the figure, this embodiment introduces a parameter analysis method for power system aggregated IBR and load, including the following steps:

[0060] Step 1: Obtain power system operation data.

[0061] Step 2: Construct a composite IBR and ZIP load model, specifically as follows:

[0062] Traditionally, polynomial load models or static (Zonal Impact Parameter, ZIP) load models are used to model the voltage dependence of power system loads. This model divides the total load into three parts: a constant power component (independent of voltage), a constant current component (proportional to voltage), and a constant impedance component (proportional to the square of voltage). The model is expressed as:

[0063] ;

[0064] ;

[0065] in, , These represent the active power and reactive power of the load at time t, respectively. , These represent the reference power of active load and the reference power of reactive load, respectively. This represents the load-side voltage at time t; , , The active power parameter representing the load; , , This represents the reactive power parameter of the load.

[0066] The voltage-WATT (Volt-WATT) control mode curve of the inverter corresponds to three operating regions: constant power region, linear region, and cutoff / reduction region. The inverter-based integrated resources (IBR) model of the voltage-WATT control mode is represented as follows:

[0067] ;

[0068] ;

[0069] in, , Let represent the active power and reactive power of the IBR under the voltage active power control mode of the power system at time t, respectively. This indicates the maximum active power of the inverter under voltage active control mode; This represents the load-side voltage at time t; , This represents the IBR parameters to be analyzed under voltage active mode; Indicates the constant power region; Represents a linear region; Indicates the area to be cut off or reduced; This indicates the reactive power output of the inverter.

[0070] In the voltage-reactive power (VAR) control mode of the inverter, if there is available capacity (determined based on solar irradiance), reactive power output takes priority, and the remaining capacity of the inverter is used to provide active power support. The IBR model of the voltage-reactive power control mode is expressed as:

[0071] ;

[0072] ;

[0073] ;

[0074] ;

[0075] in, , These represent the active power and reactive power of the IBR under voltage reactive power control mode at time t, respectively. This indicates the rated active power of the IBR; This indicates the rated apparent power of the IBR; This indicates the maximum active power available to the inverter under the current irradiance conditions; Indicates solar irradiance; This indicates the maximum reactive power of the inverter under voltage reactive power control mode. , , , This represents the IBR parameters to be analyzed under voltage reactive mode; Indicates the maximum reactive power supply area; Indicates the linear region of power generation; Indicates the dead zone; Indicates the linear absorption region; This indicates the region of maximum reactive power absorption.

[0076] By aggregating the ZIP load model and the IBR model under voltage active control mode or voltage reactive control mode, a pre-constructed composite IBR and ZIP load model is obtained. The composite IBR and ZIP load model is defined as a combination of aggregated load and IBR output. Under a specific voltage control mode, considering the characteristics of the aggregated load model of ZIP load and individual IBR, the composite IBR and ZIP load model is expressed as follows:

[0077] ;

[0078] ;

[0079] in, , Let represent the combined active power and combined reactive power of the composite IBR and ZIP load models at time t, respectively.

[0080] It can be proven that the composite IBR and ZIP load models can be represented in the form of an equivalent ZIP model. The parameters of the equivalent ZIP model will depend on the operating mode and load characteristics of the IBR. Using a similar notation to the ZIP load model, the composite IBR and ZIP load models can be represented as follows:

[0081] ;

[0082] ;

[0083] in, , , These are comprehensive parameters of active power. , , It is a comprehensive parameter of reactive power.

[0084] Step 2: Voltage sensitivity analysis of the composite IBR and ZIP load models, specifically:

[0085] The quasi-steady-state characteristics of power system operation are used for steady-state analysis. A power system operation data window depicting quasi-steady-state behavior is considered for load and IBR parameter estimation. Voltage sensitivity values ​​for the composite IBR and ZIP load models within the aggregated power measurement window (and voltage measurements at the point of common coupling) can be used to identify patterns of variation in load and IBR parameter composition. If the sensitivity is approximately constant, the quasi-steady-state assumption holds, and these data can be used to estimate parameters considered constant. The voltage sensitivity of the observed bus can be positive (quasi-steady-state behavior) or negative (dynamic behavior). Aggregated load sensitivity can be mathematically defined as follows:

[0086] ;

[0087] ;

[0088] in, , These represent the derivatives of the combined active power with respect to the load-side voltage and the combined reactive power with respect to the load-side voltage for the composite IBR and ZIP load models, respectively. , These represent the derivatives of the load's active power with respect to the load-side voltage and the derivatives of its reactive power with respect to the load-side voltage, respectively. , These represent the derivatives of the active power and reactive power of the IBR with respect to the load-side voltage under the active power control mode of the power system voltage, respectively. , These represent the derivatives of the active power and reactive power of the IBR with respect to the load-side voltage under voltage-reactive control mode, respectively.

[0089] In voltage active power control mode:

[0090] When the changes in load parameters and IBR parameters are negligible, it is assumed that the changes in reference power, load parameters and solar irradiance are negligible. Within a specific window, the IBR parameters and load parameters remain constant, satisfying the quasi-steady-state assumption.

[0091] When the load parameters remain constant but the IBR parameters change, the voltage sensitivity will change abruptly, which does not conform to the quasi-steady-state behavior criterion and is therefore not suitable for parameter estimation.

[0092] When the IBR parameters remain constant but the load parameters change, the voltage sensitivity will change abruptly, which does not conform to the quasi-steady-state behavior criterion and is therefore not suitable for parameter estimation.

[0093] When load parameters and IBR parameters change significantly, voltage sensitivity will change abruptly, which does not conform to the quasi-steady-state behavior criterion, and therefore is not suitable for parameter estimation.

[0094] In voltage reactive power control mode:

[0095] When the changes in load parameters and IBR parameters are negligible, the aggregate sensitivity of active and reactive power is related because, in voltage reactive power control mode, the IBR controller is expected to follow certain reactive power setpoints to satisfy the quasi-steady-state assumption.

[0096] When the load parameters remain constant but the IBR parameters change, the voltage sensitivity will change abruptly, which does not conform to the quasi-steady-state behavior criterion and is therefore not suitable for parameter estimation.

[0097] When the IBR parameters remain constant but the load parameters change, the voltage sensitivity will change abruptly, which does not conform to the quasi-steady-state behavior criterion and is therefore not suitable for parameter estimation.

[0098] When load parameters and IBR parameters change significantly, voltage sensitivity will change abruptly, which does not conform to the quasi-steady-state behavior criterion, and therefore is not suitable for parameter estimation.

[0099] Step 3: Identify the analysis window with almost constant sensitivity, specifically:

[0100] Identifying the changing patterns of power system operating data and calculating the voltage sensitivity values ​​of composite IBR and ZIP load models under each changing pattern can be achieved by fitting linear models to the voltage and active power of normalized composite IBR and ZIP load models. The ratio of the slopes is used as a set of voltage sensitivity values ​​for voltage and active power. and The active power can be approximated as the derivative of the composite IBR and ZIP load models with respect to time t. The derivative of voltage with respect to time t .

[0101] The formulas for calculating the voltage sensitivity values ​​of the composite IBR and ZIP load models are as follows:

[0102] ;

[0103] ;

[0104] ;

[0105] in, , Let represent the voltage and active power of the composite IBR and ZIP load models at time t, respectively. , These represent the slopes of voltage and active power over time for the composite IBR and ZIP load models, respectively. , Indicates the offset; Indicates the length of time; This represents the voltage sensitivity value for the composite IBR and ZIP load models.

[0106] Using the deviation of voltage sensitivity as a steady-state indicator, a power system operation data window with stable change patterns is extracted from the power system operation data. The numerical features in the power system operation data window with stable change patterns are used to distinguish load parameters through machine learning. These features are also used to identify IBR parameters. To assist the machine learning algorithm in predicting load parameters and identifying IBR parameters, the parameter feature vector of the selected power system operation data includes the average energy of power measurement, load voltage sensitivity, comparison features based on Pearson correlation, average absolute change in power, power standard deviation, sample entropy, and asymmetric statistical features of the composite IBR and ZIP load models.

[0107] To achieve accurate load and inverter-type distributed energy parameter estimation, it is necessary to extract quasi-steady-state time windows with near-constant sensitivity. Using a window selection algorithm for parameter analysis, the deviation of voltage sensitivity values ​​is used as a steady-state indicator. Such windows are adaptively extracted from power system operating data.

[0108] First, the length of power system operation data depends on the frequency required for ZIP parameter estimation. This embodiment uses two durations, 30 seconds and 1 minute, and filters out bad data and noise to extract steady-state data.

[0109] Secondly, obtain from power system operation data Using a sample as the k-th analysis window, calculate the voltage sensitivity value of the composite IBR and ZIP load model for the k-th analysis window. ;

[0110] Then, if Then the first A temporary increase in the analysis window The nth sample, yielding the nth... The temporary window calculates the... Voltage sensitivity values ​​of temporary window composite IBR and ZIP load models ;like Then move the window's starting point to the right. One sample, and the analysis window is re-obtained from the power system operation data;

[0111] Then, if Then calculate the first Deviation of voltage sensitivity values ​​for temporary window composite IBR and ZIP load models ;like Then discard the first A temporary window is used, and the k-th analysis window is used as the operating data window for a power system with stable change patterns;

[0112] Finally, if And the length of the kth analysis window is less than If there are 10 samples, then move the starting point of the window to the right. For each sample, a new analysis window is obtained from the power system operation data; if And the length of the k-th analysis window is not less than The nth sample, then the nth Before the temporary window A new window composed of samples serves as the operating data window for a power system with a stable change pattern; if Then discard the first A temporary window is used, and the k-th analysis window is used as the operating data window for a power system with stable change patterns;

[0113] in, , These represent the minimum sample size and the maximum sample size, respectively. Indicates the sample shift; The threshold value representing the deviation of the voltage sensitivity value.

[0114] By setting , The values ​​of k are selected within the set maximum and minimum sample size range. Based on the deviation threshold of voltage sensitivity, an appropriate time window is selected. Once the window is extracted, the parameter feature vector of the power system operation data can be calculated, and parameter identification can be performed using supervised machine learning.

[0115] Step 4: Load parameter analysis, specifically:

[0116] A general framework was constructed that uses the parameter eigenvectors from the stable power system operation data window determined in step three for parameter estimation, employs supervised machine learning for load parameter analysis, and utilizes voltage and active power from composite IBR and ZIP load models to calculate parameter eigenvectors for load parameter analysis. The formula is as follows:

[0117] ;

[0118] ;

[0119] in, Represents the parameter eigenvector; Indicates the feature extraction operator; This refers to a machine learning tool used for load parameter analysis.

[0120] Step 5: IBR parameter analysis, specifically:

[0121] A general framework was constructed that uses the parameter eigenvectors from the stable power system operation data window determined in step three for parameter estimation, employs supervised machine learning for IBR parameter analysis, and utilizes the parameter eigenvectors to analyze the IBR parameters, as shown in the formula:

[0122] ;

[0123] ;

[0124] in, This represents a machine learning tool used for IBR parameter analysis under voltage active control mode. This represents a machine learning tool used for IBR parameter analysis in voltage reactive power control mode.

[0125] In this embodiment, composite IBR and ZIP load modeling is used to better understand the combination of consumer power generation loads. Through voltage sensitivity analysis based on composite IBR and ZIP load modeling, it can be seen that voltage sensitivity values ​​can be used to identify the patterns of changes in load composition and IBR parameter composition. Based on voltage sensitivity analysis, a suitable window with almost constant sensitivity is identified, which is therefore suitable for parameter analysis. Parameter analysis is performed through a supervised machine learning machine.

[0126] Example 2

[0127] This embodiment introduces a parameter analysis device for power system integrated IBR and load, characterized in that it includes:

[0128] The data acquisition module is used to acquire power system operation data.

[0129] The sensitivity calculation module is used to: identify the changing patterns of power system operation data, calculate the voltage sensitivity values ​​of pre-built composite IBR and ZIP load models under each changing pattern; and obtain pre-built composite IBR and ZIP load models by aggregating the ZIP load model and the IBR model under voltage active control mode or voltage reactive control mode.

[0130] The stability identification module is used to: use the deviation of voltage sensitivity value as a steady-state indicator to extract a stable power system operation data window from the power system operation data;

[0131] The parameter analysis module is used to: take the stable power system operation data window with changing modes as a quasi-steady-state window, perform parameter analysis on the composite IBR and ZIP load models based on the quasi-steady-state window, and obtain the parameter analysis results.

[0132] The specific functions of each module described above are explained in the relevant content of the method in Embodiment 1, and will not be repeated here.

[0133] Example 3

[0134] This embodiment introduces a computer-readable storage medium storing a computer program / instruction thereon, characterized in that, when the computer program / instruction is executed by a processor, it implements the steps of the parameter analysis method for power system aggregated IBR and load described in Embodiment 1.

[0135] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0136] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0137] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0138] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0139] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A parameter analysis method for power system integrated IBR and load, characterized in that, include: Obtain power system operation data; Identify the changing patterns of power system operation data, calculate the voltage sensitivity values ​​of pre-built composite IBR and ZIP load models under each changing pattern; obtain pre-built composite IBR and ZIP load models by aggregating the ZIP load model and the IBR model under voltage active control mode or voltage reactive control mode. Using the deviation of voltage sensitivity as a steady-state index, a window of stable power system operation data with changing patterns is extracted from power system operation data. Using the stable operating data window of the power system with a stable change mode as a quasi-steady-state window, the composite IBR and ZIP load models are subjected to parameter analysis based on the quasi-steady-state window, and the parameter analysis results are obtained.

2. The parameter analysis method for power system aggregated IBR and load according to claim 1, characterized in that, The ZIP load model is expressed as follows: ； ； in, , These represent the active power and reactive power of the load at time t, respectively. , These represent the reference power of active load and the reference power of reactive load, respectively. This represents the load-side voltage at time t; , , The active power parameter representing the load; , , This represents the reactive power parameter of the load.

3. The parameter analysis method for power system aggregated IBR and load according to claim 1, characterized in that, The IBR model of the voltage active power control mode is expressed as: ； ； in, , These represent the active power and reactive power of the IBR under the voltage active power control mode at time t, respectively. This indicates the maximum active power of the inverter under voltage active control mode; This represents the load-side voltage at time t; , This represents the IBR parameters to be analyzed under voltage active mode; Indicates a constant power region; Represents a linear region; Indicates the area to be cut off or reduced; This indicates the reactive power output of the inverter.

4. The parameter analysis method for power system aggregated IBR and load according to claim 1, characterized in that, The IBR model of the voltage reactive power control mode is expressed as: ； ； ； ； in, , These represent the active power and reactive power of the IBR under voltage reactive power control mode at time t, respectively. This indicates the rated active power of the IBR; This indicates the rated apparent power of the IBR; This indicates the maximum active power available to the inverter under the current irradiance conditions; Indicates solar irradiance; This indicates the maximum reactive power of the inverter under voltage reactive power control mode. This represents the load-side voltage at time t; , , , This represents the IBR parameters to be analyzed under voltage reactive mode; Indicates the maximum reactive power supply area; Indicates the linear region of power generation; Indicates the dead zone; Indicates the linear absorption region; This indicates the region of maximum reactive power absorption.

5. The parameter analysis method for power system aggregated IBR and load according to claim 1, characterized in that, The combined IBR and ZIP load model is expressed as follows: ； ； in, , Let represent the combined active power and combined reactive power of the combined IBR and ZIP load models at time t, respectively; , These represent the active power and reactive power of the load at time t, respectively. , These represent the active power and reactive power of the IBR under the voltage active power control mode at time t, respectively. , These represent the active power and reactive power of the IBR under voltage reactive power control mode at time t, respectively.

6. The parameter analysis method for power system aggregated IBR and load according to claim 1, characterized in that, The formula for calculating the voltage sensitivity value of the composite IBR and ZIP load model is as follows: ； ； ； in, , Let represent the voltage and active power of the composite IBR and ZIP load models at time t, respectively. , These represent the slopes of voltage and active power over time for the composite IBR and ZIP load models, respectively. , Indicates the offset; Indicates the length of time; This represents the voltage sensitivity value for the composite IBR and ZIP load models.

7. The parameter analysis method for power system aggregated IBR and load according to claim 1, characterized in that, Using the deviation of voltage sensitivity as a steady-state index, a stable power system operation data window is obtained, including: Obtain from power system operation data Using a sample as the k-th analysis window, calculate the voltage sensitivity value of the composite IBR and ZIP load model for the k-th analysis window. ; like Then the k-th analysis window will be temporarily increased. The nth sample, yielding the nth... The temporary window calculates the... Voltage sensitivity values ​​of temporary window composite IBR and ZIP load models ;like Then move the window's starting point to the right. One sample, and the analysis window is re-obtained from the power system operation data; like Then calculate the first... Deviation of voltage sensitivity values ​​for temporary window composite IBR and ZIP load models ;like Then discard the first A temporary window is used, and the k-th analysis window is used as the operating data window for a power system with stable change patterns; like And the length of the kth analysis window is less than If there are 10 samples, then move the starting point of the window to the right. For each sample, a new analysis window is obtained from the power system operation data; if And the length of the k-th analysis window is not less than The nth sample, then the nth Before the temporary window A new window composed of samples serves as the operating data window for a power system with a stable change pattern; if Then discard the first A temporary window is used, and the k-th analysis window is used as the operating data window for a power system with stable change patterns; in, , These represent the minimum sample size and the maximum sample size, respectively. Indicates the sample shift; The threshold value representing the deviation of the voltage sensitivity value.

8. The parameter analysis method for power system aggregated IBR and load according to claim 1, characterized in that, Based on the parameter feature vector, parameter analysis is performed on the composite IBR and ZIP load models to obtain the parameter analysis results, as shown in the formula: ； ； ； ； in, Represents the parameter eigenvector; , These represent the voltage and active power of the composite IBR and ZIP load models, respectively. Indicates the feature extraction operator; , , The active power parameter representing the load; , , Represents the reactive power parameters of the load; This refers to a machine learning tool used for load parameter analysis. , This represents the IBR parameters to be analyzed under voltage active mode; This indicates the maximum active power of the inverter under voltage active control mode; This represents a machine learning tool used for IBR parameter analysis under voltage active control mode. , , , This represents the IBR parameters to be analyzed under voltage reactive mode; This indicates the maximum reactive power of the inverter under voltage reactive power control mode. This represents a machine learning tool used for IBR parameter analysis in voltage reactive power control mode.

9. A parameter analysis device for power system integrating IBR and load, characterized in that, include: The data acquisition module is used to acquire power system operation data; The sensitivity calculation module is used to: identify the changing patterns of power system operation data, calculate the voltage sensitivity values ​​of pre-built composite IBR and ZIP load models under each changing pattern; and obtain pre-built composite IBR and ZIP load models by aggregating the ZIP load model and the IBR model under voltage active control mode or voltage reactive control mode. The stability identification module is used to: use the deviation of voltage sensitivity value as a steady-state indicator to extract a stable power system operation data window from the power system operation data; The parameter analysis module is used to: take the stable power system operation data window with changing modes as a quasi-steady-state window, perform parameter analysis on the composite IBR and ZIP load models based on the quasi-steady-state window, and obtain the parameter analysis results.

10. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the parameter analysis method for power system aggregated IBR and load as described in any one of claims 1-9.

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