Method, device and program product for determining resonance risk of high voltage system of substation

Abstract

This application relates to a method, apparatus, and program product for determining the resonance risk of a substation high-voltage system. The method includes: calculating the correlation coefficients of the medium-voltage harmonic voltage array and the high-voltage harmonic current array of the substation transformer within a preset time period, and determining the weights of the linear regression equations of the medium-voltage harmonic current array and the low-voltage harmonic current array to determine the harmonic resonance state of the transformer's high-voltage side; calculating the actual harmonic impedance of the transformer's high-voltage side when the harmonic resonance state indicates a resonance problem in the substation transformer; calculating the theoretical harmonic impedance of the transformer's high-voltage side based on the minimum short-circuit capacity; and determining the severity of the substation transformer resonance problem based on the actual harmonic impedance, the theoretical harmonic impedance, and preset judgment rules. This method can improve the accuracy of determining the severity of resonance problems.

Description

Technical Field

[0001] This application relates to the field of power quality technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for determining the resonance risk of a substation high-voltage system. Background Technology

[0002] High-voltage power transmission and the grid connection of large-capacity thermal power units in the region have become important means to optimize the allocation of power resources and meet the needs of energy production.

[0003] However, high-voltage power grids have complex structures, with interwoven transmission line rings, and long-distance transmission lines typically exhibit large distributed admittance. This complex network structure, coupled with the integration of large-capacity thermal power units, leads to significant differences in the input harmonic impedance characteristics (resistivity-inductance or resistance-capacitance) at different nodes of the power grid. This easily induces regional characteristic subharmonic resonances, directly threatening the safe and stable operation of power grid equipment.

[0004] In related technologies, harmonic resonance analysis is often performed in engineering using harmonic power flow discrimination methods based on harmonic impedance angle or harmonic power. Because the harmonic resonance state is extremely sensitive to harmonic phase, capacitive voltage transformers (CVTs) are commonly used for voltage signal measurement at voltage levels of 35kV and above. However, in actual operation, CVTs exhibit significant distortion in the measurement of harmonic voltage amplitude and phase at low frequencies. This directly leads to significant errors in the calculation of the harmonic impedance angle, resulting in misjudgments of the harmonic power flow direction and resonance type. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for determining the resonance risk of a substation high-voltage system, which can improve the accuracy of determining the severity of resonance risk in the substation high-voltage system, in response to the above-mentioned technical problems.

[0006] Firstly, this application provides a method for determining the resonance risk of a substation high-voltage system, including:

[0007] Within a preset time period, acquire the high-voltage harmonic current array, medium-voltage harmonic voltage array, medium-voltage harmonic current array, and low-voltage harmonic current array of the substation transformer for a preset number of times;

[0008] Calculate the correlation coefficient between the medium-voltage harmonic voltage array and the high-voltage harmonic current array, and determine the weights of the linear regression equations for the medium-voltage harmonic current array and the low-voltage harmonic current array;

[0009] Based on the correlation coefficient and the weight, the harmonic resonance state of the high-voltage side of the transformer is determined;

[0010] When the harmonic resonance state indicates that the substation transformer has a resonance problem, obtain the main transformer parameters, capacitor bank parameters, and minimum short-circuit capacity on the high-voltage side of the substation.

[0011] Based on the main transformer parameters, the capacitor bank parameters, the medium-voltage harmonic voltage array, and the high-voltage harmonic current array, calculate the actual harmonic impedance on the high-voltage side of the transformer;

[0012] Based on the minimum short-circuit capacity, calculate the theoretical harmonic impedance of the high-voltage side of the transformer;

[0013] Based on the actual harmonic impedance, the theoretical harmonic impedance, and the preset judgment rules, the severity of the substation transformer resonance problem is determined.

[0014] In one embodiment, the correlation coefficient is calculated using the following formula:

[0015] ;

[0016] Where r is the correlation coefficient. This is the nth data point in the high-voltage harmonic current array. Let N be the average value of the medium-voltage harmonic voltage array, and N be the array length. This represents the average value of the high-voltage harmonic current array. is the nth data point in the medium-voltage harmonic voltage data, and h is the preset number of times.

[0017] In one embodiment, determining the harmonic resonance state of the high-voltage side of the transformer based on the correlation coefficient and the weight includes:

[0018] If the correlation coefficient is greater than a preset first coefficient threshold and the coefficient of variation of the weight is less than a preset second coefficient threshold, it is determined that the substation transformer has a resonance problem.

[0019] In one embodiment, the formula for calculating the coefficient of variation of the weights is:

[0020] ;

[0021] Where cv is the coefficient of variation. The standard deviation of all weights It is the arithmetic mean of all weights.

[0022] In one embodiment, the formula for calculating the theoretical harmonic impedance is:

[0023] ;

[0024] in, For theoretical harmonic impedance, The rated voltage on the high-voltage side of the substation, This is the minimum short-circuit capacity.

[0025] In one embodiment, determining the severity of the substation transformer resonance problem based on the actual harmonic impedance, the theoretical harmonic impedance, and a preset judgment rule includes:

[0026] Calculate the ratio of the actual harmonic impedance to the theoretical harmonic impedance;

[0027] If the ratio is within a first preset range, the substation transformer resonance problem is determined to be of low risk.

[0028] If the ratio is within the second preset range, the substation transformer resonance problem is determined to be of medium risk.

[0029] If the ratio is within the third preset range, the substation transformer resonance problem is determined to be of high risk.

[0030] Secondly, this application also provides a device for determining the resonance risk of a substation high-voltage system, comprising:

[0031] The acquisition module is used to acquire the high-voltage harmonic current array, medium-voltage harmonic voltage array, medium-voltage harmonic current array and low-voltage harmonic current array of the substation transformer a preset number of times within a preset time period;

[0032] The determination module is used to calculate the correlation coefficient between the medium-voltage harmonic voltage array and the high-voltage harmonic current array, and to determine the weights of the linear regression equations of the medium-voltage harmonic current array and the low-voltage harmonic current array.

[0033] The determining module is also used to determine the harmonic resonance state of the high-voltage side of the transformer based on the correlation coefficient and the weight.

[0034] The acquisition module is also used to acquire the main transformer parameters, capacitor bank parameters, and minimum short-circuit capacity of the substation high-voltage side when the harmonic resonance state indicates that the substation transformer has a resonance problem.

[0035] The calculation module is used to calculate the actual harmonic impedance on the high-voltage side of the transformer based on the main transformer parameters, the capacitor bank parameters, the medium-voltage harmonic voltage array, and the high-voltage harmonic current array.

[0036] The calculation module is also used to calculate the theoretical harmonic impedance of the high-voltage side of the transformer based on the minimum short-circuit capacity.

[0037] The determining module is also used to determine the severity of the substation transformer resonance problem based on the actual harmonic impedance, the theoretical harmonic impedance, and the preset judgment rules.

[0038] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0039] Within a preset time period, acquire the high-voltage harmonic current array, medium-voltage harmonic voltage array, medium-voltage harmonic current array, and low-voltage harmonic current array of the substation transformer for a preset number of times;

[0040] Calculate the correlation coefficient between the medium-voltage harmonic voltage array and the high-voltage harmonic current array, and determine the weights of the linear regression equations for the medium-voltage harmonic current array and the low-voltage harmonic current array;

[0041] Based on the correlation coefficient and the weight, the harmonic resonance state of the high-voltage side of the transformer is determined;

[0042] When the harmonic resonance state indicates that the substation transformer has a resonance problem, obtain the main transformer parameters, capacitor bank parameters, and minimum short-circuit capacity on the high-voltage side of the substation.

[0043] Based on the main transformer parameters, the capacitor bank parameters, the medium-voltage harmonic voltage array, and the high-voltage harmonic current array, calculate the actual harmonic impedance on the high-voltage side of the transformer;

[0044] Based on the minimum short-circuit capacity, calculate the theoretical harmonic impedance of the high-voltage side of the transformer;

[0045] Based on the actual harmonic impedance, the theoretical harmonic impedance, and the preset judgment rules, the severity of the substation transformer resonance problem is determined.

[0046] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0047] Within a preset time period, acquire the high-voltage harmonic current array, medium-voltage harmonic voltage array, medium-voltage harmonic current array, and low-voltage harmonic current array of the substation transformer for a preset number of times;

[0048] Calculate the correlation coefficient between the medium-voltage harmonic voltage array and the high-voltage harmonic current array, and determine the weights of the linear regression equations for the medium-voltage harmonic current array and the low-voltage harmonic current array;

[0049] Based on the correlation coefficient and the weight, the harmonic resonance state of the high-voltage side of the transformer is determined;

[0050] When the harmonic resonance state indicates that the substation transformer has a resonance problem, obtain the main transformer parameters, capacitor bank parameters, and minimum short-circuit capacity on the high-voltage side of the substation.

[0051] Based on the main transformer parameters, the capacitor bank parameters, the medium-voltage harmonic voltage array, and the high-voltage harmonic current array, calculate the actual harmonic impedance on the high-voltage side of the transformer;

[0052] Based on the minimum short-circuit capacity, calculate the theoretical harmonic impedance of the high-voltage side of the transformer;

[0053] Based on the actual harmonic impedance, the theoretical harmonic impedance, and the preset judgment rules, the severity of the substation transformer resonance problem is determined.

[0054] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0055] Within a preset time period, acquire the high-voltage harmonic current array, medium-voltage harmonic voltage array, medium-voltage harmonic current array, and low-voltage harmonic current array of the substation transformer for a preset number of times;

[0056] Calculate the correlation coefficient between the medium-voltage harmonic voltage array and the high-voltage harmonic current array, and determine the weights of the linear regression equations for the medium-voltage harmonic current array and the low-voltage harmonic current array;

[0057] Based on the correlation coefficient and the weight, the harmonic resonance state of the high-voltage side of the transformer is determined;

[0058] When the harmonic resonance state indicates that the substation transformer has a resonance problem, obtain the main transformer parameters, capacitor bank parameters, and minimum short-circuit capacity on the high-voltage side of the substation.

[0059] Based on the main transformer parameters, the capacitor bank parameters, the medium-voltage harmonic voltage array, and the high-voltage harmonic current array, calculate the actual harmonic impedance on the high-voltage side of the transformer;

[0060] Based on the minimum short-circuit capacity, calculate the theoretical harmonic impedance of the high-voltage side of the transformer;

[0061] Based on the actual harmonic impedance, the theoretical harmonic impedance, and the preset judgment rules, the severity of the substation transformer resonance problem is determined.

[0062] The aforementioned method, apparatus, computer equipment, computer-readable storage medium, and computer program product for determining the resonance risk of a substation high-voltage system first acquire, within a preset time period, a preset number of high-voltage harmonic current arrays, medium-voltage harmonic voltage arrays, medium-voltage harmonic current arrays, and low-voltage harmonic current arrays of the substation transformer; calculate the correlation coefficients between the medium-voltage harmonic voltage arrays and the high-voltage harmonic current arrays, and determine the weights of the linear regression equations for the medium-voltage harmonic current arrays and the low-voltage harmonic current arrays; based on the correlation coefficients and weights, determine the harmonic resonance state of the transformer's high-voltage side; if the harmonic resonance state indicates a resonance problem in the substation transformer, acquire the main transformer parameters, capacitor bank parameters, and the minimum short-circuit capacity of the substation's high-voltage side; based on the main transformer parameters, capacitor bank parameters, medium-voltage harmonic voltage arrays, and high-voltage harmonic current arrays, calculate the actual harmonic impedance of the transformer's high-voltage side; based on the minimum short-circuit capacity, calculate the theoretical harmonic impedance of the transformer's high-voltage side; and based on the actual harmonic impedance, theoretical harmonic impedance, and preset judgment rules, determine the severity of the substation transformer resonance problem. Thus, by utilizing the correlation coefficient between the harmonic voltage on the medium-voltage side of the main transformer and the harmonic current on the high-voltage side, as well as the linear regression weights of the harmonic currents on the medium and low-voltage sides under reactive power switching disturbances on the low-voltage side, it is possible to accurately identify whether there is a harmonic resonance problem on the high-voltage side without relying on the accuracy of high-voltage side harmonic measurement. This effectively overcomes the misjudgment of resonance caused by the distortion of low-frequency CVT measurements in traditional methods. Furthermore, the actual harmonic impedance on the high-voltage side is calculated using the converted value of the medium-voltage side voltage and the parameters of the main transformer and capacitor bank. This is then combined with a ratio judgment based on the theoretical impedance based on the minimum short-circuit capacity, thereby achieving a quantitative assessment of the severity of resonance risk. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 This is an application environment diagram of a method for determining the resonance risk of a substation high-voltage system in one embodiment;

[0065] Figure 2 This is a flowchart illustrating a method for determining the resonance risk of a substation high-voltage system in one embodiment.

[0066] Figure 3 This is a schematic diagram of the structure of a harmonic impedance model in one embodiment;

[0067] Figure 4 This is a schematic diagram of the substation power grid topology in one embodiment;

[0068] Figure 5 This is a graph showing the trend of three-phase reactive power variation on the low-voltage side of a transformer in one embodiment;

[0069] Figure 6 This is a graph showing the trend of the fifth harmonic voltage content on the high-voltage side of a transformer in one embodiment;

[0070] Figure 7 This is a graph showing the trend of the fifth harmonic current content on the medium-voltage side of a transformer in one embodiment;

[0071] Figure 8 This is a graph showing the correlation trend between the 5th harmonic voltage content on the medium-voltage side and the 5th harmonic current content on the high-voltage side of a transformer in one embodiment.

[0072] Figure 9 This is a structural block diagram of a device for determining the resonance risk of a substation high-voltage system in one embodiment;

[0073] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0074] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0075] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0076] The method for determining the resonance risk of a substation high-voltage system provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located on the cloud or other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, projection devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0077] In one exemplary embodiment, such as Figure 2 As shown, a method for determining the resonance risk of a substation high-voltage system is provided, and this method is applied to... Figure 1 Taking terminal 102 as an example, the explanation includes the following steps 202 to 214. Wherein:

[0078] Step 202: Within a preset time period, obtain the high-voltage harmonic current array, medium-voltage harmonic voltage array, medium-voltage harmonic current array, and low-voltage harmonic current array of the substation transformer for a preset number of times.

[0079] For example, within a preset time period, the high-voltage harmonic current array of the high-voltage side of the substation transformer is acquired synchronously for a preset number of times h. Medium-voltage harmonic voltage array on the medium-voltage side Medium-voltage harmonic current array on the medium-voltage side and low-voltage harmonic current array on the low-voltage side .

[0080] In some embodiments, within a preset time period, a preset number of high-voltage harmonic voltage arrays and low-voltage harmonic voltage arrays of the substation transformer are also acquired.

[0081] The preset time period refers to the period when the reactive power on the low-voltage side of the transformer in the substation changes frequently. For example, in a 110kV and above voltage level substation, the reactive power compensation device normally operates according to the switching control strategy, and the frequency of switching is relatively low per day (generally less than 5 times in engineering experience, and less than 1 time per hour on average). The period when the reactive power changes frequently refers to the time period when the switching frequency is greater than or equal to 2 times per hour.

[0082] In some embodiments, the high-voltage side is the winding connected to the highest voltage level; the medium-voltage side is the winding connected to the intermediate voltage level; and the low-voltage side is the winding connected to the lowest voltage level. The high-voltage side, medium-voltage side, and low-voltage side are relative; for example, in a 220kV / 110kV / 10kV transformer, the 220kV end is the high-voltage side, the 110kV end is the medium-voltage side, and the 10kV end is the low-voltage side.

[0083] Step 204: Calculate the correlation coefficients of the medium-voltage harmonic voltage array and the high-voltage harmonic current array, and determine the weights of the linear regression equations of the medium-voltage harmonic current array and the low-voltage harmonic current array.

[0084] Optionally, the correlation coefficients of the medium-voltage harmonic voltage array and the high-voltage harmonic current array are calculated, and the weights of the linear regression equations of the medium-voltage harmonic current array and the low-voltage harmonic current array are determined.

[0085] In some embodiments, according to the different time periods when the reactive power compensation device on the low-voltage side of the transformer is activated at different capacities, the h-th harmonic current data on the medium-voltage side of the transformer is collected. Transformer low-voltage side h-th harmonic current data Divided into M groups.

[0086] For each set of data, a univariate linear regression equation is established, and the specific formula is shown below:

[0087]

[0088] in, For the reactive power compensation device, the data of the h-th harmonic current on the medium-voltage side of the transformer in the M linear regression equations for different capacity periods are used. For the reactive power compensation device, the data of the h-th harmonic current on the low-voltage side of the transformer in the M linear regression equations for different capacity periods are used. Weights of M linear regression equations for different capacity periods when the reactive power compensation device is used; The bias of M linear regression equations is applied to the reactive power compensation device during different capacity periods.

[0089] Calculate the weights of the linear regression equation using the least squares method. , ... The specific calculation formula is as follows:

[0090]

[0091] in, The number of data items for different capacity periods when the reactive power compensation device is supplied; for The sum of; for The sum of; for The sum of; for The sum of; for The sum of squares.

[0092] Step 206: Determine the harmonic resonance state of the high-voltage side of the transformer based on the correlation coefficient and weight.

[0093] For example, the harmonic resonance state of the high-voltage side of the transformer is determined based on the range of correlation coefficients and weights.

[0094] Step 208: If the harmonic resonance state indicates that the substation transformer has a resonance problem, obtain the main transformer parameters, capacitor bank parameters, and minimum short-circuit capacity on the high-voltage side of the substation.

[0095] Optionally, if the harmonic resonance state indicates that the substation transformer has a resonance problem, the main transformer parameters, capacitor bank parameters, and minimum short-circuit capacity on the high-voltage side of the substation can be obtained.

[0096] Among them, the main transformer parameters and capacitor bank parameters are the nameplate parameters of the transformer and capacitor bank.

[0097] Step 210: Calculate the actual harmonic impedance on the high-voltage side of the transformer based on the main transformer parameters, capacitor bank parameters, medium-voltage harmonic voltage array, and high-voltage harmonic current array.

[0098] For example, a harmonic impedance model is constructed based on the main transformer parameters, capacitor bank parameters, medium-voltage harmonic voltage array, and high-voltage harmonic current array, as shown in the schematic diagram below. Figure 3 As shown, calculate the actual harmonic impedance on the high-voltage side of the transformer.

[0099] like Figure 3 As shown, This is the array of medium-voltage side harmonic voltages for the h-th order of the transformer. This is the array of h-th harmonic impedances on the medium-voltage side. This is the actual h-th harmonic impedance array of the substation's high-voltage system; This is the array of h-th harmonic impedances on the high-voltage side of the transformer; This is the array of h-th harmonic impedances on the low-voltage side of the transformer; This is the array of h-th harmonic impedances of the series reactor in the capacitor bank on the low-voltage side of the transformer. This is the array of h-th harmonic impedances of the capacitor bank on the low-voltage side of the transformer; This is the array of h-th harmonic currents flowing into the high-voltage side of the transformer; h is the preset number.

[0100] Specifically, the resistance of the high-voltage system is much smaller than the reactance, so the resistance is ignored in the calculation. The impedance of the medium-voltage side winding of the three-winding transformer is close to 0 or negative, so it is determined to be zero in the calculation and ignored. The h-th harmonic voltage array of the medium-voltage side is referred to the high-voltage side. The specific calculation formula is as follows:

[0101]

[0102]

[0103] in, The actual h-th harmonic impedance of the high-voltage side system of the substation; This is the array of h-th harmonic impedances on the high-voltage side of the transformer; , , These are the impedance voltages of the transformer from high voltage to medium voltage, high voltage to low voltage, and medium voltage to low voltage, respectively. , These are the rated voltages of the high-voltage and medium-voltage sides of the transformer. is the rated capacity of the transformer; h is the harmonic order.

[0104] Step 212: Calculate the theoretical harmonic impedance of the high-voltage side of the transformer based on the minimum short-circuit capacity.

[0105] Optionally, the theoretical harmonic impedance of the transformer's high-voltage side can be calculated based on the minimum short-circuit capacity of the high-voltage side of the substation.

[0106] Step 214: Based on the actual harmonic impedance, theoretical harmonic impedance, and preset judgment rules, determine the severity of the transformer resonance problem in the substation.

[0107] For example, based on actual harmonic impedance, theoretical harmonic impedance and preset judgment rules, the substation transformer resonance problem is classified to determine the severity of the substation transformer resonance problem.

[0108] In the aforementioned method for determining the resonance risk of a substation high-voltage system, within a preset time period, the high-voltage harmonic current array, medium-voltage harmonic voltage array, medium-voltage harmonic current array, and low-voltage harmonic current array of the substation transformer are obtained for a preset number of cycles. The correlation coefficients between the medium-voltage harmonic voltage array and the high-voltage harmonic current array are calculated, and the weights of the linear regression equations for the medium-voltage harmonic current array and the low-voltage harmonic current array are determined. Based on the correlation coefficients and weights, the harmonic resonance state of the transformer's high-voltage side is determined. If the harmonic resonance state indicates a resonance problem in the substation transformer, the main transformer parameters, capacitor bank parameters, and the minimum short-circuit capacity of the substation's high-voltage side are obtained. Based on the main transformer parameters, capacitor bank parameters, medium-voltage harmonic voltage array, and high-voltage harmonic current array, the actual harmonic impedance of the transformer's high-voltage side is calculated. Based on the minimum short-circuit capacity, the theoretical harmonic impedance of the transformer's high-voltage side is calculated. Based on the actual harmonic impedance, theoretical harmonic impedance, and preset judgment rules, the severity of the substation transformer resonance problem is determined. Thus, by utilizing the correlation coefficient between the harmonic voltage on the medium-voltage side of the main transformer and the harmonic current on the high-voltage side, as well as the linear regression weights of the harmonic currents on the medium and low-voltage sides under reactive power switching disturbances on the low-voltage side, it is possible to accurately identify whether there is a harmonic resonance problem on the high-voltage side without relying on the accuracy of high-voltage side harmonic measurement. This effectively overcomes the misjudgment of resonance caused by the distortion of low-frequency CVT measurements in traditional methods. Furthermore, the actual harmonic impedance on the high-voltage side is calculated using the converted value of the medium-voltage side voltage and the parameters of the main transformer and capacitor bank. This is then combined with a ratio judgment based on the theoretical impedance based on the minimum short-circuit capacity, thereby achieving a quantitative assessment of the severity of resonance risk.

[0109] In one exemplary embodiment, the formula for calculating the correlation coefficient is as follows:

[0110]

[0111] Where r is the correlation coefficient. This is the nth data point in the high-voltage harmonic current array. Let N be the average value of the medium-voltage harmonic voltage array, and N be the array length. This represents the average value of the high-voltage harmonic current array. is the nth data point in the medium-voltage harmonic voltage data, and h is the preset number of times.

[0112] In the above embodiments, by calculating the correlation coefficient, the linear correlation strength between the medium-voltage side harmonic voltage and the high-voltage side harmonic current can be effectively characterized without relying on the accurate measurement of the high-voltage side CVT harmonic voltage. This avoids the inherent distortion problem of harmonic amplitude and phase measurement in the low-frequency band of CVT, significantly improves the accuracy and reliability of resonance state identification, and lays a solid foundation for the subsequent quantitative assessment of resonance risk level.

[0113] In an exemplary embodiment, determining the harmonic resonance state of the high-voltage side of the transformer based on the correlation coefficient and weights includes: determining that the substation transformer has a resonance problem when the correlation coefficient is greater than a preset first coefficient threshold and the coefficient of variation of the weights is less than a preset second coefficient threshold.

[0114] In practice, if the correlation coefficient is greater than the preset first coefficient threshold (e.g., 0.9) and the coefficient of variation of the weight is less than the preset second coefficient threshold (e.g., 0.1), it is determined that the substation transformer has a resonance problem.

[0115] In the above embodiments, by simultaneously satisfying the two conditions of "correlation coefficient greater than threshold" and "variance coefficient less than threshold", the resonance state can be locked from two dimensions: "harmonic response consistency" and "system linear time-invariant characteristics". This dual criterion significantly improves the robustness and accuracy of resonance identification, avoids misjudgment or omission that may be caused by a single indicator, and provides a reliable premise for subsequent risk level assessment.

[0116] In one exemplary embodiment, the formula for calculating the coefficient of variation of the weights is as follows:

[0117]

[0118] Where cv is the coefficient of variation. The standard deviation of all weights It is the arithmetic mean of all weights.

[0119] The formula for calculating the arithmetic mean is as follows:

[0120]

[0121] Where M is the number of weights, For the first The weights of each linear regression equation.

[0122] The formula for calculating standard deviation is as follows:

[0123]

[0124] In the above embodiments, by calculating the coefficient of variation, the consistency and stability of the linear relationship between the medium-voltage side harmonic current and the low-voltage side harmonic current can be quantitatively evaluated under different reactive power compensation device switching capacities.

[0125] In one exemplary embodiment, the formula for calculating the theoretical harmonic impedance is as follows:

[0126]

[0127] in, is the h - th order theoretical harmonic impedance of the high - voltage side, is the rated voltage of the high - voltage side of the substation, is the minimum short - circuit capacity.

[0128] In the above - mentioned embodiment, by directly deriving the theoretical harmonic impedance based on the given minimum short - circuit capacity of the high - voltage side of the substation, without the need for complex on - site measurements or modeling, a reference value reflecting the inherent harmonic tolerance of the system can be quickly obtained. This theoretical value, as a reference scale for judging the severity of resonance risk, is compared with the actual harmonic impedance, which can effectively quantify the relative deviation degree of the actual harmonic impedance, so as to accurately distinguish different risk levels of slight amplification, significant amplification or severe amplification of resonance.

[0129] In an exemplary embodiment, based on the actual harmonic impedance, the theoretical harmonic impedance and a preset judgment rule, the severity of the resonance problem of the substation transformer is determined, including: calculating the ratio of the actual harmonic impedance to the theoretical harmonic impedance; when the ratio is within the first preset range, determining that the resonance problem of the substation transformer is a low - risk; when the ratio is within the second preset range, determining that the resonance problem of the substation transformer is a medium - risk; when the ratio is within the third preset range, determining that the resonance problem of the substation transformer is a high - risk.

[0130] In actual implementation, the ratio of the actual harmonic impedance to the theoretical harmonic impedance is calculated, and the specific calculation formula is as follows:

[0131]

[0132] Where, is the actual harmonic impedance, is the theoretical harmonic impedance.

[0133] When the ratio is within the first preset range (for example, 1 < K < 3), the resonance of the high - voltage side system is slightly amplified, and it is determined that the resonance problem of the substation transformer is a low - risk; when the ratio is within the second preset range (for example, 3 < K < 6), the resonance of the high - voltage side system is significantly amplified, and it is determined that the resonance problem of the substation transformer is a medium - risk; when the ratio is within the third preset range (for example, K > 6), the resonance of the high - voltage side system is severely amplified, and it is determined that the resonance problem of the substation transformer is a high - risk.

[0134] In the above embodiments, by calculating the ratio of actual harmonic impedance to theoretical harmonic impedance and quantifying the resonance risk into low, medium, and high levels based on preset grading thresholds (such as 1~3, 3~6, ​​and greater than 6), an objective, quantitative, and graded assessment of the severity of resonance on the high-voltage side of the substation is achieved. Compared with the traditional binary judgment that only provides whether resonance has occurred, this method can provide maintenance personnel with a more refined risk situation awareness, enabling them to formulate differentiated response strategies according to different risk levels: enhanced monitoring for low risk, planned maintenance for medium risk, and immediate intervention for high risk.

[0135] To illustrate in detail the method for determining the resonance risk of a substation high-voltage system in this application, an embodiment is provided below. For example, this application describes the method for determining the resonance risk of a substation high-voltage system in a specific scenario.

[0136] A schematic diagram of the power grid topology of a certain substation is shown below. Figure 4 As shown in the diagram, #1 is a three-winding transformer. The 220kV side is the high-voltage side, the 110kV side is the medium-voltage side, and the capacitor bank side is the low-voltage side. This is the configuration of a 220kV substation. On the 220kV side, there are multiple 220kV feeder lines connecting to the substation on the opposite side; similarly, the 110kV side also has multiple feeder lines connecting to the substation on the opposite side. The low-voltage side of the transformer only has a single type of load: the capacitor bank.

[0137] like Figure 4 As shown, the transformer has a rated voltage of 230kV / 121kV / 10.5kV and a rated capacity of 180MVA. The impedance voltages between high voltage and medium voltage, high voltage and low voltage, and medium voltage and low voltage are 14.5%, 24%, and 7.5%, respectively. The minimum short-circuit capacity given on the high voltage side of the substation is 8000MVA.

[0138] The terminal detected that the 5th harmonic voltage on the medium-voltage side of the transformer exceeded the standard. Long-term (over 24 hours) data monitoring was conducted simultaneously on the high-voltage, medium-voltage, and low-voltage sides of the transformer. Data from periods of frequent switching of the reactive power compensation device on the low-voltage side of the main transformer during the testing period were selected, such as... Figure 5 As shown in the figure. During this period, the changing trends of the 5th harmonic voltage content and 5th harmonic current content simultaneously monitored on the high-voltage side and medium-voltage side of the transformer are as follows: Figure 6 , Figure 7 As shown.

[0139] According to correlation analysis, the correlation coefficient between the 5th harmonic voltage on the medium-voltage side and the 5th harmonic current on the high-voltage side of the main transformer is: , specifically Figure 8As shown. The low-voltage side capacitor bank has 6 different capacity switching periods. The h-th harmonic current content on the medium-voltage and low-voltage sides of the transformer is divided into 6 groups according to the switching periods. For each group of data, a univariate linear regression equation is established, and the weights (slopes) of each univariate linear regression equation are determined as follows: , , , , , Weighted (slope) arithmetic mean Standard deviation Calculate the coefficient of variation of the weights (slopes). The coefficient of variation is less than 10%.

[0140] Based on these two conditions, it was determined that the 5th harmonic of the substation's main transformer high-voltage system exhibits resonance. The 5th harmonic impedance on the high-voltage side of the main transformer was calculated using the transformer parameters. The actual value of the 5th harmonic impedance on the high-voltage side of the main transformer was calculated. The theoretical value of the 5th harmonic impedance on the high-voltage side of the main transformer is calculated based on the minimum short-circuit capacity on the high-voltage side of the substation. The ratio of the actual to the theoretical 5th harmonic impedance on the high-voltage side of the main transformer is K=10.69. Based on the criteria for judging the severity of resonance risk, the resonance of the high-voltage side system of the substation is severely amplified, and the transformer resonance problem in the substation is determined to be of high risk.

[0141] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0142] Based on the same inventive concept, this application also provides a device for determining the resonance risk of a substation high-voltage system, used to implement the method for determining the resonance risk of a substation high-voltage system as described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the device for determining the resonance risk of a substation high-voltage system provided below can be found in the limitations of the method for determining the resonance risk of a substation high-voltage system described above, and will not be repeated here.

[0143] In one exemplary embodiment, such as Figure 9 As shown, a device for determining the resonance risk of a substation high-voltage system is provided, comprising: an acquisition module 901, a determination module 902, and a calculation module 903, wherein:

[0144] The acquisition module is used to acquire the high-voltage harmonic current array, medium-voltage harmonic voltage array, medium-voltage harmonic current array, and low-voltage harmonic current array of the substation transformer a preset number of times within a preset time period.

[0145] The determination module is used to calculate the correlation coefficient between the medium-voltage harmonic voltage array and the high-voltage harmonic current array, and to determine the weights of the linear regression equations of the medium-voltage harmonic current array and the low-voltage harmonic current array.

[0146] The determining module is also used to determine the harmonic resonance state of the high-voltage side of the transformer based on the correlation coefficient and the weight.

[0147] The acquisition module is also used to acquire the main transformer parameters, capacitor bank parameters, and minimum short-circuit capacity of the substation high-voltage side when the harmonic resonance state indicates that the substation transformer has a resonance problem.

[0148] The calculation module is used to calculate the actual harmonic impedance on the high-voltage side of the transformer based on the main transformer parameters, the capacitor bank parameters, the medium-voltage harmonic voltage array, and the high-voltage harmonic current array.

[0149] The calculation module is also used to calculate the theoretical harmonic impedance of the high-voltage side of the transformer based on the minimum short-circuit capacity.

[0150] The determining module is also used to determine the severity of the substation transformer resonance problem based on the actual harmonic impedance, the theoretical harmonic impedance, and the preset judgment rules.

[0151] In one exemplary embodiment, the above-described calculation module is further configured to calculate the correlation coefficient:

[0152] ;

[0153] Where r is the correlation coefficient. This is the nth data point in the high-voltage harmonic current array. Let N be the average value of the medium-voltage harmonic voltage array, and N be the array length. This represents the average value of the high-voltage harmonic current array. is the nth data point in the medium-voltage harmonic voltage data, and h is the preset number of times.

[0154] In one exemplary embodiment, the determining module is further configured to:

[0155] If the correlation coefficient is greater than the preset first coefficient threshold and the coefficient of variation of the weight is less than the preset second coefficient threshold, it is determined that the substation transformer has a resonance problem.

[0156] In one exemplary embodiment, the above-described calculation module is further configured to calculate the coefficient of variation of the weights:

[0157] ;

[0158] Where cv is the coefficient of variation. The standard deviation of all weights It is the arithmetic mean of all weights.

[0159] In one exemplary embodiment, the above calculation formula is also used to calculate the theoretical harmonic impedance:

[0160] ;

[0161] in, For theoretical harmonic impedance, The rated voltage on the high-voltage side of the substation, This is the minimum short-circuit capacity.

[0162] In one exemplary embodiment, the determining module is further configured to:

[0163] Calculate the ratio of actual harmonic impedance to theoretical harmonic impedance;

[0164] If the ratio is within the first preset range, the substation transformer resonance problem is determined to be low risk;

[0165] If the ratio is within the second preset range, the substation transformer resonance problem is determined to be of medium risk.

[0166] If the ratio is within the third preset range, the substation transformer resonance problem is determined to be of high risk.

[0167] Each module in the aforementioned device for determining the resonance risk of a substation high-voltage system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0168] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 10 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for determining the resonance risk of a substation high-voltage system.

[0169] The display unit of this computer device is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of this computer device can be a touch layer covering the display screen, or buttons, a trackball, or a touchpad set on the casing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0170] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0171] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0172] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0173] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0174] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0175] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0176] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0177] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method of determining a substation high voltage system resonance risk, characterized by, The method includes: Within a preset time period, acquire the high-voltage harmonic current array, medium-voltage harmonic voltage array, medium-voltage harmonic current array, and low-voltage harmonic current array of the substation transformer for a preset number of times; Calculate the correlation coefficient between the medium-voltage harmonic voltage array and the high-voltage harmonic current array, and determine the weights of the linear regression equations for the medium-voltage harmonic current array and the low-voltage harmonic current array; Based on the correlation coefficient and the weight, the harmonic resonance state of the high-voltage side of the transformer is determined; When the harmonic resonance state indicates that the substation transformer has a resonance problem, obtain the main transformer parameters, capacitor bank parameters, and minimum short-circuit capacity on the high-voltage side of the substation. Based on the main transformer parameters, the capacitor bank parameters, the medium-voltage harmonic voltage array, and the high-voltage harmonic current array, calculate the actual harmonic impedance on the high-voltage side of the transformer; Based on the minimum short-circuit capacity, calculate the theoretical harmonic impedance of the high-voltage side of the transformer; Based on the actual harmonic impedance, the theoretical harmonic impedance, and the preset judgment rules, the severity of the substation transformer resonance problem is determined.

2. The method of claim 1, wherein, The formula for calculating the correlation coefficient is: ； Where r is the correlation coefficient. This is the nth data point in the high-voltage harmonic current array. Let N be the average value of the medium-voltage harmonic voltage array, and N be the array length. This represents the average value of the high-voltage harmonic current array. is the nth data point in the medium-voltage harmonic voltage data, and h is the preset number of times.

3. The method according to claim 1, characterized in that, The determination of the harmonic resonance state on the high-voltage side of the transformer based on the correlation coefficient and the weight includes: If the correlation coefficient is greater than a preset first coefficient threshold and the coefficient of variation of the weight is less than a preset second coefficient threshold, it is determined that the substation transformer has a resonance problem.

4. The method of claim 3, wherein, The formula for calculating the coefficient of variation of the weights is: ； wherein cv is the coefficient of variation, is the standard deviation of all weights, is the arithmetic mean of all weights.

5. The method of claim 1, wherein, The formula for calculating the theoretical harmonic impedance is as follows: ； wherein is the theoretical harmonic impedance, is the rated voltage at the high voltage side of the substation, is the minimum short circuit capacity.

6. The method of claim 1, wherein, The determination of the severity of transformer resonance problems in substations based on the actual harmonic impedance, the theoretical harmonic impedance, and preset judgment rules includes: Calculate the ratio of the actual harmonic impedance to the theoretical harmonic impedance; If the ratio is within a first preset range, the substation transformer resonance problem is determined to be of low risk. If the ratio is within the second preset range, the substation transformer resonance problem is determined to be of medium risk. If the ratio is within the third preset range, the substation transformer resonance problem is determined to be of high risk.

7. An apparatus for determining a substation high voltage system resonance risk, characterized by The device includes: The acquisition module is used to acquire the high-voltage harmonic current array, medium-voltage harmonic voltage array, medium-voltage harmonic current array and low-voltage harmonic current array of the substation transformer a preset number of times within a preset time period; The determination module is used to calculate the correlation coefficient between the medium-voltage harmonic voltage array and the high-voltage harmonic current array, and to determine the weights of the linear regression equations of the medium-voltage harmonic current array and the low-voltage harmonic current array. The determining module is also used to determine the harmonic resonance state of the high-voltage side of the transformer based on the correlation coefficient and the weight. The acquisition module is also used to acquire the main transformer parameters, capacitor bank parameters, and minimum short-circuit capacity of the substation high-voltage side when the harmonic resonance state indicates that the substation transformer has a resonance problem. The calculation module is used to calculate the actual harmonic impedance on the high-voltage side of the transformer based on the main transformer parameters, the capacitor bank parameters, the medium-voltage harmonic voltage array, and the high-voltage harmonic current array. The calculation module is also used to calculate the theoretical harmonic impedance of the high-voltage side of the transformer based on the minimum short-circuit capacity. The determining module is also used to determine the severity of the substation transformer resonance problem based on the actual harmonic impedance, the theoretical harmonic impedance, and the preset judgment rules.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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

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