A new energy station power quality dynamic evaluation method and system

Abstract

The present application relates to the technical field of measuring electric variable, in particular to a new energy station power quality dynamic evaluation method and system, comprising: determining the voltage change correlation between monitoring points at each moment, combining the connection between monitoring points on the power grid, starting from the monitoring points in the new energy station to construct a local network several times, and according to the active power difference of the monitoring points in the local network at different moments and the new energy station output fluctuation of the monitoring points in the new energy station at each moment, dynamically updating the local network to obtain the final local network at each moment, and determining the new energy station power quality at the current moment in the final local network at the current moment. The present application considers the dynamic update of the local network under the change of power grid load and meteorological condition fluctuation, so as to meet the maximum performance of new energy station power fluctuation in the local network and realize the dynamic evaluation of new energy station power quality.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of measuring electrical variables, and in particular to a new energy station power quality dynamic evaluation method and system. BACKGROUND

[0002] New energy stations are increasingly important in power systems, but due to the intermittent and fluctuating nature of their power generation, power quality problems are increasingly prominent. Therefore, it is particularly important to study new energy station power quality dynamic evaluation methods. Power quality refers to the ability of the power output of a power system to meet the load demand in terms of frequency, amplitude, waveform, etc. New energy stations are affected by natural environment, such as photovoltaic new energy stations which are limited by light intensity, making them more prone to voltage fluctuations, frequency fluctuations and other problems, affecting the stability and reliability of the power system.

[0003] Existing problems: Existing new energy station power quality often directly monitors the station output, which can easily miss some small fluctuations. However, after the new energy station is connected to the power grid, the station output fluctuations may be amplified in the local range of the power grid. However, the local network connected to the new energy station has dynamic fluctuation characteristics under the influence of factors such as power grid load changes and weather condition fluctuations, so a fixed local network cannot guarantee that the new energy station's power quality will be consistently exhibited. SUMMARY

[0004] The present application provides a new energy station power quality dynamic evaluation method and system to solve the existing problems.

[0005] The new energy station power quality dynamic evaluation method and system of the present application adopts the following technical solution:

[0006] One embodiment of the present application provides a new energy station power quality dynamic evaluation method, which comprises the following steps:

[0007] The rated voltage, rated frequency of each monitoring point on the power grid, and the voltage, frequency and active power at each time are obtained, and the new energy station output fluctuation of the monitoring point in the new energy station at each time is obtained;

[0008] According to the voltage change difference between the monitoring points at the same time, the voltage change correlation between the monitoring points at each time is determined;

[0009] On the power grid, according to the voltage difference of each monitoring point at adjacent time, the voltage change correlation between monitoring points at each time, and the connection between monitoring points, a local network is constructed by expanding several times from the monitoring points in the new energy station, and the final local network at each time is obtained by dynamically updating the local network according to the active power difference of the monitoring points in the local network at different times and the new energy station output fluctuation of the monitoring points in the new energy station at each time.

[0010] In the final local network at the current time, the power quality of the new energy station at the current time is determined according to the voltage difference between each monitoring point at the current time and the rated voltage, the frequency difference, and the voltage difference and frequency difference at adjacent time.

[0011] Further, the specific steps of determining the voltage change correlation between monitoring points at each time include the following steps:

[0012] The difference between the voltage of each monitoring point at the first time and the voltage at the second time is recorded as the voltage change value of each monitoring point at the first time.

[0013] The preset number threshold is , and the voltages of each monitoring point at all times in the period from the first time to the second time are polynomial fitted to obtain the regression difference of each monitoring point at the first time.

[0014] According to the voltage change value and the regression difference of any two monitoring points at the first time, the voltage change correlation of the two monitoring points at the first time is determined.

[0015] Further, the specific steps of determining the voltage change correlation of any two monitoring points at the first time according to the voltage change value and the regression difference of the two monitoring points at the first time include the following steps:

[0016] The absolute value of the difference between the voltage change values of any two monitoring points at the first time is recorded as the first difference value, the inverse proportional normalized value of the mean of the regression difference of any two monitoring points at the first time is recorded as the first similarity value, and the inverse proportional normalized value of the product of the first similarity value and the first difference value is taken as the voltage change correlation of the two monitoring points at the first time. ​​​​​​​​​​​​​

[0017] Furthermore, the specific steps for obtaining the final local network at each time step are as follows:

[0018] The monitoring points within the new energy power station are used as the benchmark monitoring points, and the monitoring points directly connected to the benchmark monitoring points are used as the monitoring points to be merged.

[0019] Based on the voltage difference between each monitoring point to be merged at adjacent time points, and combining the reference monitoring point with the voltage difference between each monitoring point to be merged at the [missing information] time... The correlation of voltage changes at time t, to determine the first The merging probability of the baseline monitoring point and each monitoring point to be merged at the given time;

[0020] Based on the merging probability, merged monitoring points are selected;

[0021] The first extended local network is composed of the benchmark monitoring points and the merged monitoring points;

[0022] Based on the merging probability and the connection between monitoring points, new merging monitoring points are selected from the monitoring points directly connected to the merging monitoring points.

[0023] The newly merged monitoring points are incorporated into the first extended local network to obtain the second extended local network;

[0024] Preset number of expansions And so on, until the 1st The next extended local network, denoted as the [number]th [type of network]... The final local network at that moment;

[0025] Preset local network update interval Every Then, based on the difference in active power of the monitoring points within the final local network at different times and the magnitude of the power output fluctuation of the new energy power station at each time, the final local network at each time is updated and judged to obtain the final local network at each time.

[0026] Furthermore, based on the voltage difference between each monitoring point to be merged at adjacent times, and combined with the reference monitoring point and each monitoring point to be merged at the [missing information] time... The correlation of voltage changes at time t, to determine the first The specific steps involved in determining the merging probability between the baseline monitoring point and each monitoring point to be merged at a given time are as follows:

[0027] In the Time to the During the time period of time, the first The monitoring points to be merged are in the first Time and the The absolute value of the difference of the voltage at the time is recorded as the voltage difference value at the time The time when the voltage difference value is greater than the preset fluctuation threshold is recorded as the voltage fluctuation time

[0028] The preset time range The time interval between the first time and the second time is , and ;

[0029] The time interval set composed of the time interval between the first voltage fluctuation time and all other voltage fluctuation times is obtained, and the maximum value of the absolute value of the autocorrelation function value of the time interval set in different lags is taken as the regularity of the first voltage fluctuation time

[0030] The product of the inverse proportion value of the regularity of the first voltage fluctuation time and the voltage difference value is recorded as the influence degree of the first voltage fluctuation time on the station voltage

[0031] The inverse proportion normalized value of the influence degree of each voltage fluctuation time on the station voltage is recorded as the influence adjustment value of each voltage fluctuation time, and the sum value of the influence adjustment values of all voltage fluctuation times is recorded as the first sum value, and the normalized value of the product of the voltage change correlation between the reference monitoring point and the first to-be-merged monitoring point at the first time and the first sum value is taken as the merging probability of the reference monitoring point and the first to-be-merged monitoring point at the first time.

[0032] Further, the specific steps of screening the merged monitoring point according to the merging probability include the following:

[0033] The to-be-merged monitoring point corresponding to the merging probability greater than the preset merging threshold among the merging probabilities of the reference monitoring point and all to-be-merged monitoring points at the first time is recorded as the merged monitoring point.

[0034] Further, the specific steps of screening the new merged monitoring point from the monitoring points directly connected to the merged monitoring point according to the merging probability and the connection condition between the monitoring points include the following:

[0035] The monitoring points directly connected to the new reference monitoring point and not in the first extended local network are taken as secondary to-be-merged monitoring points.

[0036] Obtaining a plurality of propagation paths from the reference monitoring point, through only one new reference monitoring point, to the first second to-be-merged monitoring point;

[0037] On the first propagation path, all monitoring points except the first second to-be-merged monitoring point are recorded as reference monitoring points;

[0038] Obtaining the reciprocal of the number of monitoring points directly connected to each reference monitoring point, as the credibility of each reference monitoring point, obtaining the normalized value of the product of the merging probability of the first second to-be-merged monitoring point and each reference monitoring point at the first moment, as the merging characteristic value, obtaining the mean value of the merging characteristic values of the first second to-be-merged monitoring point and all reference monitoring points at the first moment, as the merging probability on the first propagation path;

[0039] Obtaining the mean value of the merging probabilities on all propagation paths, as the merging probability of the first second to-be-merged monitoring point at the first moment;

[0040] Recording the second to-be-merged monitoring point whose merging probability is greater than the preset merging threshold at the first moment as a new merged monitoring point.

[0041] Further, the preset local network update time interval is , and after every , the update judgment is performed according to the active power difference of the monitoring points in the final local network at different moments and the size of the new energy station output fluctuation of the monitoring points in the new energy station at each moment, to obtain the final local network at each moment, including the following specific steps:

[0042] Obtaining the maximum value of the new energy station output fluctuation of the monitoring points in the new energy station at all moments in the period from the first moment to the first moment, as a target output fluctuation, obtaining the normalized value of the range of the active power of each monitoring point at all moments, as the power fluctuation value of each monitoring point, obtaining the mean value of the power fluctuation values of all monitoring points in the final local network at the first moment, as a first mean value, and recording the normalized value of the product of the first mean value and the target output fluctuation as the local network update possibility at the first moment.

[0043] Wherein, the first time interval between the first time and the second time is , and ;

[0044] When the local network update possibility at the first time is greater than the preset update threshold, the final local network at the first time is obtained according to the acquisition manner of the final local network at the first time;

[0045] When the local network update possibility at the first time is less than or equal to the preset update threshold, the final local network at the first time is taken as the final local network at the first time.

[0046] Further, the specific steps of determining the new energy station electric energy quality at the current time include the following:

[0047] The absolute value of the difference between the voltage at each monitoring point at the current time and the rated voltage is obtained, denoted as a second difference value, the absolute value of the difference between the voltage at each monitoring point at the current time and the adjacent previous time is obtained, denoted as a third difference value, in the final local network at the current time, the mean value of the second difference value corresponding to all monitoring points and the mean value of the third difference value are obtained, respectively denoted as a second mean value and a third mean value, and the normalized value of the sum of the second mean value and the third mean value is denoted as the electric energy quality represented by the voltage at the current time;

[0048] The absolute value of the difference between the frequency at each monitoring point at the current time and the rated frequency is obtained, denoted as a fourth difference value, the absolute value of the difference between the frequency at each monitoring point at the current time and the adjacent previous time is obtained, denoted as a fifth difference value, in the final local network at the current time, the mean value of the fourth difference value corresponding to all monitoring points and the mean value of the fifth difference value are obtained, respectively denoted as a fourth mean value and a fifth mean value, and the normalized value of the sum of the fourth mean value and the fifth mean value is denoted as the electric energy quality represented by the frequency at the current time;

[0049] The mean value of the electric energy quality represented by the voltage at the current time and the electric energy quality represented by the frequency at the current time is obtained as the new energy station electric energy quality at the current time.

[0050] The application further provides a new energy station electric energy quality dynamic evaluation system, which comprises a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor executes the computer program stored in the memory to realize the steps of the new energy station electric energy quality dynamic evaluation method.

[0051] The beneficial effects of the technical scheme of the present application are: by connecting the new energy station to the power grid, then setting a monitoring point in the power grid, using the monitoring point to amplify the power fluctuation of the new energy station, realizing the monitoring of the fine fluctuation of the station, and combining the consistent relationship between the dynamic changes of the new energy station and other monitoring points, constructing a local network of the new energy station, and more accurately amplifying the power fluctuation of the new energy station in the local network. Further, the present application considers that the local network changes under the load change of the power grid and the fluctuation of the weather condition, dynamically updates the local network, so as to satisfy the maximum performance of the new energy station power fluctuation in the local network, and realizes the dynamic evaluation of the power quality of the new energy station. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical scheme in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced as follows. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings.

[0053] Figure 1 The step flow chart of the new energy station power quality dynamic evaluation method of the present application;

[0054] Figure 2 The diagram structure diagram. DETAILED DESCRIPTION

[0055] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the specific implementation, structure, features and effects of the new energy station power quality dynamic evaluation method and system according to the present application will be described in detail as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0057] The specific scheme of the new energy station power quality dynamic evaluation method and system provided by the present application will be specifically described below with reference to the drawings.

[0058] Please refer to Figure 1 which shows the step flow chart of the new energy station power quality dynamic evaluation method provided by one embodiment of the present application, and the method comprises the following steps:

[0059] Step S001: Obtain the rated voltage, rated frequency of each monitoring point on the power grid, and the voltage, frequency, active power at each moment, and then obtain the new energy station output fluctuation of the monitoring point in the new energy station at each moment.

[0060] It is necessary to explain that the photovoltaic new energy station (hereinafter referred to as "photovoltaic station") is a power generation facility that converts light energy into electric energy by using solar photovoltaic effect. Its core function is to convert intermittent solar energy into stable electric energy and connect to the power grid, which is one of the important forms of new energy power generation. The electric energy generated generally needs to be connected to the power grid to complete the transmission and use of electric power. Therefore, when evaluating the power quality, monitoring points need to be arranged in the connected power grid. The specific arrangement of monitoring points needs to cover the key nodes of the interaction between the photovoltaic station and the power grid to ensure comprehensive capture of power quality problems. This mainly includes the station side, the grid-connected side, and the load side. Therefore, the arrangement of monitoring points is mainly the inverter outlet point in the station, the grid-connected point, and the branching point in the grid-connected line, wherein the branching point is the intersection point with a line distance of less than 50 kilometers from the grid-connected point.

[0061] In order to ensure the accuracy and effectiveness of the monitoring data, the data acquisition needs to meet the following requirements:

[0062] (1) Monitoring parameter requirements:

[0063] Core power quality indicators need to be covered: voltage, frequency, current, active power, reactive power, total harmonic distortion (THD), harmonic content, voltage fluctuation and flicker.

[0064] (2) Equipment and parameters:

[0065] The core equipment of photovoltaic station power quality monitoring is the power quality monitoring device (PQM), also known as "power quality analyzer". The parameters of the power quality monitoring device need to cover sampling accuracy, measurement range, functional adaptability, etc., and the specific requirements are as follows:

[0066]

[0067]

[0068] Finally, the collected data is transmitted to the evaluation center, and the data is processed while being cached. The evaluation center is connected to the station control center and can read the station data, including: photovoltaic angle, air temperature, light intensity, etc.

[0069] Therefore, the rated voltage, rated frequency of each monitoring point on the power grid, and the voltage, frequency, active power at each moment can be obtained. There is a monitoring point in the new energy station on the power grid (i.e. the inverter outlet monitoring point in the new energy station), and then the new energy station output fluctuation of the monitoring point in the new energy station at each moment is obtained.

[0070] It should be noted that in this embodiment, the acquisition of new energy station output fluctuation is a known technology, and the specific method is not introduced here.

[0071] Step S002: According to the voltage change difference between the monitoring points at the same time, the voltage change correlation between the monitoring points at each time is determined.

[0072] It should be noted that: at present, the evaluation of power quality in the station needs to connect the station to the power grid, and then monitor at different positions in the power grid to accurately reflect the power quality of the station. When using different monitoring points to reflect the power quality of the station, it is necessary to ensure that the different monitoring points in the power grid and the monitoring points in the station have consistent fluctuations, that is, the monitoring points need to have a correlation. At each sampling time, each monitoring point corresponds to a voltage data, at this time the change correlation between the monitoring points can be represented by the correlation of voltage change. The correlation between the monitoring points is the consistency of voltage change, and the deviation of the corresponding monitoring point at a single time needs to be considered, wherein the greater the deviation, the less the voltage change can represent the correlation of voltage change between monitoring points.

[0073] Subtract the voltage difference of each monitoring point at the first time from the voltage at the first time, and record it as the voltage change value of each monitoring point at the first time.

[0074] Among them, the voltage change value at the first time is not analyzed.

[0075] The preset number threshold is 9, which is taken as an example for description.

[0076] In the period from the first time to the first time, the voltage of each monitoring point at all times is polynomial fitted to obtain the regression difference of each monitoring point at the first time.

[0077] Among them, the polynomial fitting adopts the least square method, which is a known technology, and the specific method is not introduced here. The greater the regression difference, the greater the difference between the fitted value and the actual value.

[0078] The absolute value of the difference between the voltage change values of any two monitoring points at the first time is obtained, recorded as the first difference value, and the inverse proportional normalized value of the mean of the regression difference of any two monitoring points at the first time is obtained, recorded as the first similarity value, and the product of the first similarity value and the first difference value is inverse proportional normalized value of the first difference value, as the voltage change correlation of any two monitoring points at the first time.

[0079] It should be noted that in this embodiment, the first difference value is taken as the inverse proportional normalized value of the first difference value, as the voltage change correlation of any two monitoring points at the first time. and respectively as the inverse proportional normalized value of the first difference value, as the voltage change correlation of any two monitoring points at the first time. and respectively as the inverse proportional normalized value of the first difference value, as the voltage change correlation of any two monitoring points at the first time. is a linear normalization function for normalizing data values to between 0 and 1. The smaller the regression difference, the more reliable the first difference value, so the first difference value is adjusted by the first similarity value. The larger the first difference value, the more dissimilar the voltage change of any two monitoring points at the first time, thereby obtaining the voltage change correlation of any two monitoring points at the first time.

[0080] Step S003: On the power grid, according to the voltage difference of each monitoring point at adjacent times, the voltage change correlation between monitoring points at each time, and the connection between monitoring points, a local network is constructed several times starting from the monitoring points in the new energy station, and the local network is dynamically updated according to the active power difference of the monitoring points at different times and the size of the new energy station output fluctuation of the monitoring points in the new energy station at each time, to obtain the final local network at each time.

[0081] It should be noted that the construction of the local network based on the current station is mainly to utilize the power quality of the local network station, so the monitoring points in the local network to be constructed and the power fluctuation between the monitoring points need to be shown at this time. Therefore, the construction of the current local network mainly depends on the consistent relationship between the monitoring points in the station and other monitoring points, starting from the monitoring points in the station, merging other monitoring points to construct the final local network. The key to the construction of the local network at this time is to merge the monitoring points, that is, to start from the monitoring points in the station and merge other monitoring points.

[0082] It should be further noted that for the local network to be constructed at the current time, a monitoring point needs to be started, and then adjacent monitoring points are searched based on the connection relationship between the monitoring points, and then the related relationship of the adjacent monitoring points is used to determine the merged monitoring points. Since the current local network is used to reflect the power quality of the station, the monitoring points to be merged need to be determined starting from the monitoring points in the current station, that is, the inverter outlet monitoring points in the station.

[0083] Among all the monitoring points on the power grid, the monitoring points are connected by line connections to form a graph structure, which is a known operation.

[0084] Among all the monitoring points on the power grid, the monitoring points are connected by line connections to form a graph structure, which is a known operation. Figure 2 ​​​As shown, Figure 2 There are monitoring points 0, 1, 2, 3, and 4. The side length between the monitoring points is the line length between the monitoring points.

[0085] In the graph structure, the monitoring points within the new energy power station are used as the baseline monitoring points, and the monitoring points directly connected to the baseline monitoring points are used as the monitoring points to be merged.

[0086] It should be noted that after identifying the monitoring points to be merged, the corresponding merging probability needs to be determined to identify the specific monitoring points to be merged. The merged monitoring points need to have similar variation relationships to the baseline monitoring point. Fluctuations in grid-side load (such as industrial motor start-up and shutdown, and peak and valley electricity consumption in residential areas) and fluctuations in renewable energy output may "superimpose" or "cancel out." Therefore, the smaller the voltage fluctuation of the monitoring point to be merged, the smaller its coverage effect on the current voltage fluctuation within the power station, and the higher the probability of merging. Furthermore, loads for different purposes have different electricity consumption times, and the current fluctuations in photovoltaic-based power station output also exhibit certain temporal patterns, such as a certain trend in output during the morning, noon, and evening. Therefore, the stronger the regularity of the voltage fluctuation of the monitoring point to be merged, the smaller its coverage effect on the power station's voltage fluctuation, and the higher the probability of merging.

[0087] Preset time range The timeframe is 10 days, and the preset fluctuation threshold is 3. This will be used as an example for explanation.

[0088] In the Time to the During the time period of time, the first The monitoring points to be merged are in the first Time and the The absolute value of the voltage difference at time t is denoted as the th. The monitoring points to be merged are in the first The voltage difference value at a given time is recorded as the voltage fluctuation time when the voltage difference value exceeds the preset fluctuation threshold.

[0089] Among them, the Time to the The voltage change at the first moment within the time period is not analyzed. Time and the The time interval is ,and .

[0090] Get the The time interval set consisting of the time intervals between the first voltage fluctuation moment and all other voltage fluctuation moments is used to obtain the maximum absolute value of the autocorrelation function values ​​of the time interval set in different lags, which is taken as the first... The regularity of voltage fluctuations at specific times.

[0091] It should be noted that obtaining the autocorrelation function values ​​of the time interval set at different lags is a well-known operation, and the specific method will not be described here. When the timing of a voltage fluctuation is regular, the voltage fluctuation is easily identified, so the "superposition" or "cancellation" with the station voltage fluctuation is unlikely to occur, that is, the degree of influence on the station voltage is low.

[0092] The first The regular inverse proportional value of the voltage fluctuation at the first moment and the first The product of the voltage difference values ​​at each voltage fluctuation moment is denoted as the product of the voltage difference values ​​at the nth voltage fluctuation moment. The degree of impact of voltage fluctuations on the station voltage at any given time.

[0093] Since the autocorrelation function value ranges from -1 to 1, the regularity is between 0 and 1. Therefore, in this embodiment, the difference between 1 and the regularity is used as the inverse proportional value of the regularity.

[0094] Obtain the degree of impact on the station voltage at each voltage fluctuation moment. The inversely proportional normalized value is denoted as the impact adjustment value for each voltage fluctuation moment. The sum of the impact adjustment values ​​for all voltage fluctuation moments is obtained and denoted as the first sum. The benchmark monitoring point is then compared with the first sum. The monitoring points to be merged are in the first The product of the correlation of voltage changes at time t and the first sum The normalized value, as the first At time 10, the benchmark monitoring point and the first The probability of merging a monitoring point to be merged.

[0095] It should be noted that in this embodiment, is used as As The inverse proportional normalized value, in As The normalized value is calculated as follows: The smaller the impact of voltage fluctuations at the monitoring points to be merged on the station voltage, i.e., the larger the first sum, the more reliable the correlation between voltage changes between the benchmark monitoring point and the monitoring points to be merged. Therefore, the first sum is used to adjust the voltage change correlation to obtain the merging probability.

[0096] The preset merging threshold is 0.7, and we will use this as an example for explanation.

[0097] The first The monitoring point to be merged is the one whose merging probability among the baseline monitoring point and all monitoring points to be merged is greater than the preset merging threshold.

[0098] In the graph structure, the first extended local network consisting of the baseline monitoring point and all merged monitoring points is obtained.

[0099] It should be noted that the above merging process only starts from the monitoring points within the station, merging adjacent monitoring points to form the first expanded local network, which is the initial local network. Because voltage fluctuations within the station can be transmitted not only to directly connected monitoring points but also to other indirectly connected monitoring points in the graph structure, it is necessary to continue merging other monitoring points based on the initial local network, i.e., to perform continuous merging of monitoring points.

[0100] Using the merged monitoring point as the new baseline monitoring point, in the graph structure, the monitoring points directly connected to the new baseline monitoring point are obtained as secondary monitoring points to be merged. These secondary monitoring points are not located within the first extended local network.

[0101] It should be noted that a secondary monitoring point to be merged may correspond to multiple new baseline monitoring points. Therefore, there is more than one propagation path between the secondary monitoring point to be merged and the monitoring points within the site. Thus, the multiple propagation paths from the secondary monitoring point to be merged to the monitoring points within the site must be determined first.

[0102] For the Given a set of secondary monitoring points to be merged, in the graph structure, obtain the data from the baseline monitoring point, passing through only one new baseline monitoring point, to reach the [missing information]. Several transmission paths from two secondary monitoring points to be merged.

[0103] In the On the transmission path, except for the first All other monitoring points besides the two secondary monitoring points to be merged are recorded as reference monitoring points.

[0104] According to the At time 10, the benchmark monitoring point and the first The method for obtaining the merging probability of the nth monitoring point to be merged, and obtaining the nth At this moment The merging probability of each secondary monitoring point to be merged with each reference monitoring point.

[0105] In the graph structure, the reciprocal of the number of monitoring points directly connected to each reference monitoring point is obtained, denoted as the reliability of each reference monitoring point, and the i-th value is obtained. At this moment The product of the merging probability of each secondary monitoring point to be merged with each reference monitoring point and the reliability of each reference monitoring point. The normalized value, denoted as the th The secondary monitoring points to be merged and each reference monitoring point on the [number]th ... The merged feature value at time t is obtained to obtain the first time. The secondary monitoring points to be merged and all reference monitoring points at the [number]th ... The mean of the merged eigenvalues ​​at time t is used as the first... The merging probability of each propagation path.

[0106] The average of the merging probabilities of all propagation paths is taken as the merging probability of the first time point. The merging probability of the second

[0107] It should be noted that the more the number of directly connected monitoring points of the monitoring points passed through by a to-be-merged monitoring point in a propagation path, the more complex the voltage fluctuation source of the monitoring points passed through, and the less reliable the calculated merging probability between the to-be-merged monitoring point and the to-be-merged monitoring point. Therefore, the reciprocal of the number of directly connected monitoring points of each reference monitoring point is taken as the reliability of each reference monitoring point, and the merging probability is adjusted to obtain the merging probability of each propagation path. The merging probability of each propagation path is taken as the merging probability of the first time point. as a normalized value.

[0108] The merging probability of the second time point is taken as the merging probability of the second time point.

[0109] In the graph structure, the new merged monitoring point is merged into the first extended local network to obtain the second extended local network.

[0110] The preset number of extensions is 7, which is taken as an example for description.

[0111] By analogy, the first extended local network is taken as the final local network at the first time point.

[0112] It should be noted that the third extended local network is taken as an example, that is, the new merged monitoring point is taken as the updated reference monitoring point, and in the graph structure, the monitoring points directly connected to the updated reference monitoring point are obtained as the third to-be-merged monitoring points. Among them, the third to-be-merged monitoring points are not in the second extended local network. For any one of the third to-be-merged monitoring points, in the graph structure, a plurality of propagation paths are obtained, which start from the reference monitoring point, pass through a new reference monitoring point first, then pass through an updated reference monitoring point, and finally arrive at the arbitrary third to-be-merged monitoring point. Then the merging probability of each propagation path is obtained, thereby obtaining the merging probability of each third to-be-merged monitoring point at the third time point, which is used to select the latest merged monitoring point.

[0113] It should be further explained that: While a local grid has been constructed to represent the current fluctuations in power generation at renewable energy plants, these plants are currently generating photovoltaic power. In this case, the plant's output is directly affected by sunlight intensity. In actual operation, there are significant variations in sunlight intensity throughout the day, leading to output fluctuations. Even with energy storage regulation within the plant, its regulation capacity is limited, and sudden weather changes further exacerbate the problem, resulting in unavoidable output fluctuations. Furthermore, the local grid may contain peak and low-load periods, and different types of loads have different peak periods; for example, the peak periods for residential and industrial electricity consumption differ. Fluctuations in load consumption also affect the local grid's fluctuations. Therefore, the relationship between the aforementioned monitoring points and the monitoring points within the plant changes at different times. To ensure dynamic identification of plant voltage fluctuations and dynamic assessment of power quality, different local grids need to be constructed at different times, requiring dynamic updates to the local grid.

[0114] Preset local network update interval The interval is 30 minutes, and the preset update threshold is 0.6. This will be used as an example for explanation.

[0115] In the Time to the Within a given time period, the maximum value of the power output fluctuation of the new energy power station at all monitoring points at all times is obtained and recorded as the target power output fluctuation. The range of active power at each monitoring point at all times is also obtained. The normalized value is denoted as the power fluctuation value at each monitoring point, and the th value is obtained. The average power fluctuation value of all monitoring points in the final local network at the given time is denoted as the first average. The product of the first average and the target output fluctuation is then calculated. The normalized value, denoted as the th The possibility of local network updates at any given moment.

[0116] When the When the probability of a local network update at a given time is greater than a preset update threshold, according to the first... The method for obtaining the final local network at a given time, obtaining the first The final local network at that moment.

[0117] When the When the probability of a local network update at a given time is less than or equal to a preset update threshold, the [number]th [time] will be [updated / reset]. The final local network at time t, as the first The final local network at that moment.

[0118] It should be noted that in this embodiment, the following is used: and As respectively and the normalized value of the sum of the second average value and the third average value is the power quality represented by the voltage at the current time. The time interval from the current time to the time point 30 minutes later is T, and The final local network at each time point in the time period from the current time to the time point 30 minutes later is the final local network at the time point 30 minutes later, and the final local network at each time point in the time period from the time point 30 minutes later to the time point 60 minutes later is the final local network at the time point 60 minutes later, and so on, so as to obtain the real-time final local network. In this way, the dynamic updating of the local network is completed. The final local network at each time point in the time period from the current time to the time point 30 minutes later is the final local network at the time point 30 minutes later, and the final local network at each time point in the time period from the time point 30 minutes later to the time point 60 minutes later is the final local network at the time point 60 minutes later, and so on, so as to obtain the real-time final local network. In this way, the dynamic updating of the local network is completed. The final local network at each time point in the time period from the current time to the time point 30 minutes later is the final local network at the time point 30 minutes later, and the final local network at each time point in the time period from the time point 30 minutes later to the time point 60 minutes later is the final local network at the time point 60 minutes later, and so on, so as to obtain the real-time final local network. In this way, the dynamic updating of the local network is completed. The final local network at each time point in the time period from the current time to the time point 30 minutes later is the final local network at the time point 30 minutes later, and the final local network at each time point in the time period from the time point 30 minutes later to the time point 60 minutes later is the final local network at the time point 60 minutes later, and so on, so as to obtain the real-time final local network. In this way, the dynamic updating of the local network is completed. The final local network at each time point in the time period from the current time to the time point 30 minutes later is the final local network at the time point 30 minutes later, and the final local network at each time point in the time period from the time point 30 minutes later to the time point 60 minutes later is the final local network at the time point 60 minutes later, and so on, so as to obtain the real-time final local network. In this way, the dynamic updating of the local network is completed.

[0119] Step S004: In the final local network at the current time, the power quality of the new energy station at the current time is determined according to the voltage difference between the voltage at the current time and the rated voltage, the frequency difference between the frequency at the current time and the rated frequency, and the voltage difference and the frequency difference at the adjacent time.

[0120] It should be noted that based on the above operation, a dynamic local network in the power grid accessed by the current new energy station is constructed, and based on the dynamic fluctuation of all monitoring points, the dynamic evaluation of the power quality of the station is realized. Because the power quality of the current station needs to be dynamically evaluated, the designed parameters are selected as real-time data as much as possible, among which the real-time change of the voltage can directly reflect the power quality of the station, and the greater the voltage deviation of a single monitoring point and the dynamic change of the voltage, the worse the power quality of the station, and the greater the frequency deviation of the monitoring point and the dynamic change, the worse the power quality of the station.

[0121] The absolute value of the difference between the voltage at the current time and the rated voltage of each monitoring point is obtained, denoted as a second difference value, and the absolute value of the difference between the voltage at the current time and the voltage at the adjacent previous time of each monitoring point is obtained, denoted as a third difference value. In the final local network at the current time, the average value of the second difference value corresponding to all monitoring points is obtained, denoted as a second average value, and the average value of the third difference value corresponding to all monitoring points is obtained, denoted as a third average value. The normalized value of the sum of the second average value and the third average value is the power quality represented by the voltage at the current time. The absolute value of the difference between the frequency at the current time and the rated frequency of each monitoring point is obtained, denoted as a fourth difference value, and the absolute value of the difference between the frequency at the current time and the frequency at the adjacent previous time of each monitoring point is obtained, denoted as a fifth difference value. In the final local network at the current time, the average value of the fourth difference value corresponding to all monitoring points is obtained, denoted as a fourth average value, and the average value of the fifth difference value corresponding to all monitoring points is obtained, denoted as a fifth average value. The normalized value of the sum of the fourth average value and the fifth average value is the power quality represented by the frequency at the current time.

[0122] ​​​​The normalized value of the voltage is recorded as the power quality represented by the frequency at the current time.

[0123] The average of the power quality represented by the voltage at the current time and the power quality represented by the frequency at the current time is obtained as the power quality of the new energy station at the current time.

[0124] It should be noted that in the embodiment, the normalized value of the voltage is recorded as the power quality represented by the frequency at the current time. The normalized value of the voltage is recorded as the power quality represented by the frequency at the current time. The normalized value of the voltage is recorded as the power quality represented by the frequency at the current time. The normalized value of the voltage is recorded as the power quality represented by the frequency at the current time. The preset dynamic evaluation time interval is 5 seconds, and the embodiment is described by taking the 5 seconds as an example. That is, the power quality of the new energy station is evaluated every 5 seconds, so that the dynamic evaluation of the power quality of the new energy station is realized.

[0125] The application further provides a new energy station power quality dynamic evaluation system, which comprises a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor executes the computer program stored in the memory to realize the steps of the new energy station power quality dynamic evaluation method.

[0126] Thus, the application is completed.

[0127] In summary, in the embodiment of the application, the voltage change correlation between the monitoring points at each time is determined, on the power grid, the voltage difference between each monitoring point at adjacent times, the voltage change correlation between the monitoring points at each time, and the connection between the monitoring points are combined, the local network is constructed several times from the monitoring points in the new energy station, the local network is dynamically updated according to the active power difference between the monitoring points in the local network at different times and the size of the new energy station output fluctuation of the monitoring points in the new energy station at each time, the final local network at each time is obtained, and the power quality of the new energy station at the current time is determined in the final local network at the current time. The application considers the dynamic update of the local network according to the load change of the local network and the fluctuation of the weather condition, so as to satisfy the maximum performance of the new energy station power fluctuation in the local network, and realize the dynamic evaluation of the power quality of the new energy station.

[0128] The above only describes the preferred embodiments of the application and is not used to limit the application. Any modification, equivalent replacement, improvement, etc. made within the principles of the application shall be included in the protection scope of the application.​

Claims

1. A new energy station power quality dynamic evaluation method, characterized in that, The method includes the following steps: The rated voltage and rated frequency of each monitoring point on the power grid, as well as the voltage, frequency, and active power at each moment, are obtained. The output fluctuation of the new energy power station at each monitoring point within the new energy power station is also obtained. Based on the differences in voltage changes among monitoring points at the same time, determine the correlation of voltage changes among monitoring points at each time point; On the power grid, based on the voltage difference of each monitoring point at adjacent times, the correlation of voltage changes between monitoring points at each time, and the connection between monitoring points, a local network is constructed by expanding several times from the monitoring points in the new energy power station. The local network is dynamically updated based on the active power difference of the monitoring points in the local network at different times and the magnitude of the power output fluctuation of the new energy power station at each time, so as to obtain the final local network at each time. In the final local network at the current moment, the power quality of the new energy power station at the current moment is determined based on the voltage difference and frequency difference between the current and rated voltages and the rated frequencies of each monitoring point at the current moment, as well as the voltage and frequency differences between adjacent moments. The specific steps for obtaining the final local network at each time step are as follows: The monitoring points within the new energy power station are used as the benchmark monitoring points, and the monitoring points directly connected to the benchmark monitoring points are used as the monitoring points to be merged. In the period from the first moment to the second moment, the absolute value of the difference between the voltages of the first to-be-merged monitoring point at the first moment and the second moment is recorded as the voltage difference value at the second moment, and the moment when the voltage difference value is greater than the preset fluctuation threshold is recorded as the voltage fluctuation moment; Pre-set time range , the first moment and the second moment are separated by a time interval of , and ; Get the The time interval set consisting of the time intervals between the first voltage fluctuation moment and all other voltage fluctuation moments is used to obtain the maximum absolute value of the autocorrelation function values ​​of the time interval set in different lags, which is taken as the first... The regularity of voltage fluctuations at any given moment; The first The product of the regular inverse proportional value of the voltage fluctuation at each moment and the voltage difference value is denoted as the i-th. The degree of impact of voltage fluctuations on the station voltage at each moment; An inverse proportional normalized value of the influence degree of each voltage fluctuation moment on the substation voltage is obtained, denoted as an influence adjustment value of each voltage fluctuation moment, a sum value of the influence adjustment values of all voltage fluctuation moments is obtained, denoted as a first sum value, and a normalized value of the product of the voltage change correlation between the reference monitoring point and the first to be-merged monitoring point at the first moment and the first sum value is taken as a merging probability of the reference monitoring point and the first to be-merged monitoring point at the first moment. ​​​​ Based on the merging probability, merged monitoring points are selected; The first extended local network is composed of the benchmark monitoring points and the merged monitoring points; Based on the merging probability and the connection between monitoring points, new merging monitoring points are selected from the monitoring points directly connected to the merging monitoring points. The newly merged monitoring points are incorporated into the first extended local network to obtain the second extended local network; Pre-set expansion times In this way, the first local network is expanded, denoted as the second local network at the second time point; Pre-set local network update time interval every After that, according to the active power difference of the final local network monitoring point at different times and the size of the new energy station output fluctuation of the new energy station monitoring point at each time, the update judgment is made to obtain the final local network at each time.

2. The method of claim 1, wherein, The specific steps for determining the correlation of voltage changes between monitoring points at each time point are as follows: The voltage difference of each monitoring point at the time of the 1st moment minus the voltage at the time of the 2nd moment is recorded as the voltage change value of each monitoring point at the time of the 1st moment. Pre-set quantity threshold In the period from the first moment to the second moment, the voltage of each monitoring point at all moments is polynomially fitted to obtain the regression difference of each monitoring point at the first moment. According to the voltage change value of any two monitoring points at the first time and the regression difference, the voltage change correlation of the any two monitoring points at the first time is determined.

3. The method of claim 2, wherein, The voltage change value of the arbitrary two monitoring points at the first moment is obtained, and the regression difference is obtained. The voltage change correlation of the arbitrary two monitoring points at the first moment is determined, and the specific steps include the following. Obtain any two monitoring points at the th The absolute value of the difference between the voltage changes at time t is denoted as the first difference value. The difference value is obtained for any two monitoring points at time t. The inversely normalized value of the mean of the regression difference at time t is denoted as the first similarity value. The inversely normalized value of the product of the first similarity value and the first difference value is taken as the value of the regression difference between any two monitoring points at time t. Correlation of voltage changes at any given time.

4. The method of claim 1, wherein, The specific steps for selecting merged monitoring points based on the merging probability are as follows: The first The merging probability of the reference monitoring point and all the to-be-merged monitoring points at the moment is greater than the preset merging threshold, and the to-be-merged monitoring point is recorded as a merging monitoring point.

5. The method of claim 1, wherein, The specific steps for selecting new merged monitoring points from those directly connected to the merged monitoring points based on the merging probability and the connectivity between monitoring points are as follows: Using the merged monitoring point as the new baseline monitoring point, the monitoring points that are directly connected to the new baseline monitoring point and are not in the first extended local network are obtained as the second monitoring points to be merged. Obtaining a plurality of propagation paths from the reference monitoring point, through only one new reference monitoring point, to the first secondary monitoring point to be merged; On the first propagation path, all the monitoring points except the second quadratic monitoring points to be combined are recorded as reference monitoring points; obtaining the reciprocal of the number of monitoring points directly connected to each reference monitoring point as the credibility of each reference monitoring point, obtaining the normalized value of the product of the merging probability of each secondary monitoring point to be merged and each reference monitoring point and the credibility of each reference monitoring point at the moment t as a merging characteristic value, obtaining the mean value of the merging characteristic values of all reference monitoring points at the moment t as the merging probability on the i-th propagation path. the merging probability on the i-th propagation path.​​​​ The average of the merging probabilities on all propagation paths is taken as the merging probability of the i-th secondary merging monitoring point at the j-th time instant The merging probability of the i-th secondary merging monitoring point at the j-th time instant The merging probability of the i-th secondary merging monitoring point at the j-th time instant The first The secondary monitoring points corresponding to the merging probabilities greater than the preset merging threshold among all the secondary merging monitoring points at the moment are recorded as new merging monitoring points.

6. The method of claim 1, wherein, The preset local network updating time interval every After that, according to the active power difference of the final local network monitoring point at different time and the new energy field station output fluctuation size of the new energy field station monitoring point at each time, the updating judgment is carried out to obtain the final local network at each time, including the following specific steps: In the Time to the Within the time period of time, obtain the maximum value of the power output fluctuation of the new energy power station at all times, denoted as the target power output fluctuation. Obtain the normalized value of the range of active power at each monitoring point at all times, denoted as the power fluctuation value of each monitoring point. The mean of the power fluctuation values ​​of all monitoring points in the final local network at time t is denoted as the first mean. The normalized value of the product of the first mean and the target output fluctuation is denoted as the second mean. The probability of local network updates at any given moment; wherein the first time point is the second time point is the time interval between the first time point and the second time point is , and ; When the When the probability of a local network update at a given time is greater than a preset update threshold, according to the first... The method for obtaining the final local network at a given time, obtaining the first The final local network at that moment; When the When the probability of a local network update at a given time is less than or equal to a preset update threshold, the [number]th [time] will be [updated / reset]. The final local network at time t, as the first The final local network at that moment.

7. The method of claim 1, wherein, The specific steps for determining the power quality of the new energy power station at the current moment are as follows: Obtain the absolute value of the difference between the voltage and the rated voltage at each monitoring point at the current moment, and record it as the second difference value. Obtain the absolute value of the difference between the voltage at each monitoring point at the current moment and the voltage at the adjacent previous moment, and record it as the third difference value. In the final local network at the current moment, obtain the mean of the second difference value and the mean of the third difference value corresponding to all monitoring points, and record them as the second mean and the third mean, respectively. The normalized value of the sum of the second mean and the third mean is recorded as the power quality represented by the voltage at the current moment. An absolute value of a difference between the frequency of each monitoring point at the current time and the rated frequency is obtained, denoted as a fourth difference value. An absolute value of a difference between the frequency of each monitoring point at the current time and the frequency at the adjacent previous time is obtained, denoted as a fifth difference value. In the final local network at the current time, a mean value of the fourth difference values corresponding to all monitoring points and a mean value of the fifth difference values are obtained, denoted as a fourth mean value and a fifth mean value respectively. A normalized value of a sum value of the fourth mean value and the fifth mean value is denoted as an electric energy quality represented by the frequency at the current time. A mean value of the electric energy quality represented by the voltage at the current time and the electric energy quality represented by the frequency at the current time is obtained as the electric energy quality of the new energy station at the current time.

8. A new energy station power quality dynamic evaluation system, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The computer program, when executed by the processor, implements the steps of the new energy station electric energy quality dynamic evaluation method according to any one of claims 1-7.

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