Novel power system key electrical quantity oscillation monitoring method and device, electronic equipment and storage medium

Abstract

The invention provides a novel power system key electrical quantity oscillation monitoring method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a monitoring electrical quantity collected by an electrical measurement point; according to the monitored electrical quantity and the periodic time parameter, calculating an oscillation characteristic value, the oscillation characteristic values comprise a single-cycle rolling characteristic value based on the reciprocating motion mileage, a long-cycle nested characteristic value based on the reciprocating motion mileage, a single-cycle rolling characteristic value based on the oscillation waveform area and a long-cycle nested characteristic value based on the oscillation waveform area; setting an oscillation alarm threshold value according to the oscillation characteristic value; and determining whether abnormal oscillation occurs or not according to the oscillation characteristic value and the oscillation alarm threshold value, and performing oscillation early warning. Through multi-dimensional and multi-time-scale feature extraction, the oscillation feature value is extracted from the monitored electrical quantity, and adaptive threshold setting is carried out, so that the accuracy, sensitivity and adaptability of oscillation monitoring of the power system are remarkably improved.

Description

Technical Field

[0001] This application relates to the field of power technology, and in particular to a novel method, device, electronic equipment, and storage medium for monitoring the oscillation of key electrical quantities in a power system. Background Technology

[0002] Abnormal fluctuations in key electrical quantities such as active power and voltage, especially low-frequency and ultra-low-frequency oscillations, pose significant and unique risks to the safe and stable operation of new power systems. The generation mechanisms, propagation paths, and dynamic evolution processes of these oscillations differ fundamentally from those of traditional synchronous machine-dominated systems, and their risks primarily manifest in the continuous and periodic fluctuations of power and voltage. 1) Power Oscillations and Frequency Risks: Reduced system equivalent inertia leads to fragile frequency stability. More importantly, the large-scale integration of new energy sources (such as wind and solar power) and the complex control dynamics of their power electronic converters (such as phase-locked loop dynamics, current loop response, and virtual inertia control) are highly susceptible to inducing low-frequency or even ultra-low-frequency power oscillations under system disturbances or specific operating conditions. These power oscillations not only directly cause periodic frequency fluctuations, making frequency regulation more difficult, but their energy can also be transmitted and amplified through the grid structure, threatening the power stability of inter-regional tie lines and, in severe cases, leading to grid disconnection. New energy inverters generally lack the inherent damping characteristics of synchronous machines, making it difficult to effectively suppress such oscillations.

[0003] 2) Voltage Oscillation and Instability Risks: In systems dominated by renewable energy inverters, the dynamic voltage characteristics undergo fundamental changes. On the one hand, the interaction between the inverter's rapid tracking of grid voltage and reactive power control can easily induce voltage oscillations (ranging from subsynchronous to ultra-low frequency) under weak grid conditions. For example, excessively fast reactive power regulation response in photovoltaic power plants may trigger local voltage oscillations when interacting with grid impedance or nearby reactive power compensation equipment. On the other hand, during grid faults or fault recovery processes, renewable energy lacks the dynamic reactive power support capabilities of traditional synchronous machines. Its rapid current limiting and protection action characteristics may cause oscillations or even collapses during voltage recovery. These voltage oscillations not only degrade power quality but also directly threaten system voltage stability.

[0004] 3) Equipment stress and collaborative risks: Continuous low-frequency / ultra-low-frequency power and voltage oscillations impose additional stress on power equipment. Thermal power units are forced to frequently adjust their output to follow the oscillations, accelerating the wear of mechanical components such as turbines; renewable energy inverters themselves are also subjected to the impact of power and voltage fluctuations, which may lead to DC bus voltage fluctuations, increased capacitor current, aggravated losses, and even malfunctions of overvoltage / overcurrent protection. At the same time, the power forecast deviation superimposed on the complex oscillation dynamics causes the dispatch plan to deviate significantly from the actual operating state, not only increasing the risk of wind and solar curtailment but also forcing traditional units to make more frequent and larger-amplitude adjustments, significantly increasing system operating costs and equipment maintenance costs.

[0005] The existing technologies for oscillation detection in power systems are not comprehensive enough, and the factors considered in the detection process are relatively limited, resulting in low accuracy of oscillation detection in power systems. Summary of the Invention

[0006] This application aims to at least partially address one of the technical problems in the related art.

[0007] Therefore, this application proposes a method, apparatus, electronic device, and storage medium.

[0008] One embodiment of this application proposes a novel method for monitoring oscillations of key electrical quantities in a power system, including: Select the electrical measurement point to be monitored, obtain the monitored electrical quantities collected by the electrical measurement point, and set the period time parameters related to oscillation monitoring; The oscillation characteristic value is calculated based on the monitored electrical quantity and the cycle time parameter, wherein the oscillation characteristic value includes: a single-cycle rolling characteristic value based on the reciprocating motion mileage, a long-cycle nested characteristic value based on the reciprocating motion mileage, a single-cycle rolling characteristic value based on the oscillation waveform area, and a long-cycle nested characteristic value based on the oscillation waveform area. The oscillation alarm threshold value is adjusted based on the oscillation characteristic value; Based on the oscillation characteristic value and the oscillation alarm threshold value, determine whether abnormal oscillation has occurred and issue an oscillation warning.

[0009] Optionally, the monitored electrical quantities include: active power, reactive power, voltage, and frequency; the setting of the cycle time parameters related to oscillation monitoring includes: Set the time length of the sampling refresh cycle for the monitored electrical quantities; A first time length is set as the cycle time length for a single-cycle roll, and the first time length is an integer multiple of the sampling refresh cycle; A second time length is set as the sub-cycle time length of a long-cycle nesting, and the second time length is an integer multiple of the sampling refresh cycle; A third time length is set as the parent period length of the long-period nesting, and the third time length is an integer multiple of the second time length.

[0010] Optionally, the step of calculating the oscillation characteristic value based on the monitored electrical quantity and the period time parameter includes: Within the first period corresponding to the first time length, determine the change value of the monitored electrical quantity between each sampling refresh period and the adjacent sampling refresh period; Within the first cycle, the sum of the absolute values ​​of the changes in the monitored electrical quantities corresponding to all sampling refresh cycles, minus the absolute value of the algebraic sum of the changes in the monitored electrical quantities corresponding to all sampling refresh cycles, is taken as the single-cycle rolling characteristic value based on the reciprocating motion mileage.

[0011] Optionally, the step of calculating the oscillation characteristic value based on the monitored electrical quantity and the period time parameter includes: Within the second period corresponding to the second time length, the sampled values ​​of the monitored electrical quantities in each sampling refresh period and the changes in the monitored electrical quantities between each sampling refresh period and adjacent sampling refresh periods are determined. Within the second cycle, the sum of the absolute values ​​of the monitored electrical quantity samples corresponding to all sampling refresh cycles is subtracted from the algebraic sum of the monitored electrical quantity samples corresponding to all sampling refresh cycles, and this sum is used as the first sub-feature value. Within the second cycle, the change value of the monitored electrical quantity corresponding to the last sampling refresh cycle is subtracted from the change value of the monitored electrical quantity corresponding to the first sampling refresh cycle, and this is used as the second sub-feature value. Within the third period corresponding to the third time length, the first sub-feature values ​​corresponding to each second period are added together to obtain the third sub-feature value; wherein, the third period corresponding to the third time length includes multiple second periods; Within the third period, the absolute values ​​of the second sub-feature values ​​corresponding to each second period are added together, and the algebraic sum of the second sub-feature values ​​corresponding to each second period is subtracted to obtain the fourth sub-feature value. The third sub-feature value is added to the fourth sub-feature value to obtain the long-period nested feature value based on the reciprocating motion mileage.

[0012] Optionally, the step of calculating the oscillation characteristic value based on the monitored electrical quantity and the period time parameter includes: Within the first period corresponding to the first time length, determine the maximum and minimum values ​​of the monitored electrical quantity, and take multiple intermediate values ​​from the values ​​between the maximum and minimum values; Using the maximum value, minimum value, or any intermediate value as the integration cross-section, calculate the integration area of ​​the integration cross-section with all other integration cross-sections, and use the minimum value of the integration area as the area of ​​the first oscillation waveform corresponding to the integration cross-section. The minimum value of the area of ​​the first oscillating waveform is taken as the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform.

[0013] Optionally, the step of calculating the oscillation characteristic value based on the monitored electrical quantity and the period time parameter includes: Within the first period corresponding to the first time length, determine the maximum and minimum values ​​of the monitored electrical quantity, and take multiple intermediate values ​​from the values ​​between the maximum and minimum values; The maximum, minimum, and average values ​​are respectively used as integration cross-sections. The integration area of ​​the integration cross-section with all other integration cross-sections is calculated. The minimum value of the integration area is used as the area of ​​the first oscillation waveform corresponding to the integration cross-section. The minimum value of the area of ​​the first oscillating waveform is taken as the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform.

[0014] Optionally, the step of calculating the oscillation characteristic value based on the monitored electrical quantity and the period time parameter includes: Within the second period corresponding to the second time length, determine the monitored electrical quantities for each sampling refresh cycle; Determine the maximum, minimum, and multiple intermediate values ​​of the monitored electrical quantity in each sampling refresh cycle of the second cycle; Using the intermediate value as the integration section line, calculate the integrated area of ​​the integration section line with all other integration section lines. A set of second oscillation waveform areas and integral cross-sections corresponding to a target number of second periods is determined, wherein each second period in the set is a group; the long-period nested feature value based on the oscillation waveform area is determined according to the frequency of occurrence of the value of each integral cross-section in the set; wherein the target number is an integer multiple of the third time length to the second time length.

[0015] Optionally, determining the long-period nested feature value based on the occurrence frequency of each integral cross-section value in the set includes any one of the following: In response to the fact that the frequency of occurrence of the value of only one integral cross section line in all groups of the set is equal to the target number, the integral cross section line is determined as the target integral cross section line, and the value of the target integral cross section line is accumulated in the second oscillation waveform area corresponding to each second period to obtain the long-period nested feature value based on the oscillation waveform area; In response to the fact that the frequency of occurrence of the values ​​of at least two of the integral cross-sections in all groups of the set is equal to the target number, these integral cross-sections are determined as the target integral cross-sections. For each target integral cross-section, the second oscillation waveform surface corresponding to the target integral cross-section in each second period is accumulated to obtain multiple accumulated values. The minimum value among the accumulated values ​​is taken as the long-period nested feature value based on the oscillation waveform area. In response to the fact that the frequency of occurrence of the value of the integral cross section line in all groups of the set is less than the target number, the set is regrouped.

[0016] Optionally, adjusting the oscillation alarm threshold value based on the oscillation characteristic value includes: The single-cycle rolling feature value based on the reciprocating motion mileage and the single-cycle rolling feature value based on the oscillation waveform area are stored. At the end of the first storage period, the maximum value of the single-cycle rolling feature value based on the reciprocating motion mileage and the maximum value of the single-cycle rolling feature value based on the oscillation waveform area are recorded. The duration of the first storage period is an integer multiple of the sampling refresh period. The long-cycle nested feature values ​​based on reciprocating motion mileage and the long-cycle nested feature values ​​based on oscillating waveform area are stored. At the end of the second storage period, the maximum value among the long-cycle nested feature values ​​based on reciprocating motion mileage and the maximum value among the long-cycle nested feature values ​​based on oscillating waveform area are recorded. The time length of the second storage period is an integer multiple of the time length of the long-cycle nested sub-cycles. The oscillation alarm threshold value corresponding to each of the oscillation feature values ​​is determined based on the maximum value among the single-cycle rolling feature values ​​based on the reciprocating motion mileage, the maximum value among the single-cycle rolling feature values ​​based on the oscillation waveform area, the maximum value among the long-cycle nested feature values ​​based on the reciprocating motion mileage, and the maximum value among the long-cycle nested feature values ​​based on the oscillation waveform area.

[0017] Optionally, determining the oscillation alarm threshold value based on the maximum value among the single-cycle rolling feature values ​​based on the reciprocating motion mileage, the maximum value among the single-cycle rolling feature values ​​based on the oscillation waveform area, the maximum value among the long-cycle nested feature values ​​based on the reciprocating motion mileage, and the maximum value among the long-cycle nested feature values ​​based on the oscillation waveform area includes: The maximum value among the single-cycle rolling feature values ​​based on reciprocating motion mileage and the maximum value among the single-cycle rolling feature values ​​based on the area of ​​the oscillation waveform are stored in each first storage cycle. At the end of the first threshold value update cycle, the maximum value among the single-cycle rolling feature values ​​based on reciprocating motion mileage and the maximum value among the single-cycle rolling feature values ​​based on the area of ​​the oscillation waveform corresponding to each first storage cycle is used as the first candidate alarm threshold value. The time length of the first threshold value update cycle is an integer multiple of the first storage cycle. The first candidate alarm threshold value is used to determine the first oscillation alarm threshold value. In response to the candidate alarm threshold value being higher than a preset first upper limit threshold, the first upper limit threshold is increased, or the correction is skipped; or, in response to the candidate alarm threshold value being lower than or equal to the first upper limit threshold, the lower limit threshold data of the single-cycle rolling characteristic value under normal operating conditions is used as the first oscillation alarm threshold value. If the candidate alarm threshold value is less than the first oscillation alarm threshold value, the correction is skipped. If the candidate alarm threshold value is greater than or equal to the first oscillation alarm threshold value, the first oscillation alarm threshold value is corrected to the candidate alarm threshold value.

[0018] Optionally, determining the oscillation alarm threshold value based on the maximum value among the single-cycle rolling feature values ​​based on the reciprocating motion mileage, the maximum value among the single-cycle rolling feature values ​​based on the oscillation waveform area, the maximum value among the long-cycle nested feature values ​​based on the reciprocating motion mileage, and the maximum value among the long-cycle nested feature values ​​based on the oscillation waveform area includes: The maximum value among the long-period nested feature values ​​based on reciprocating motion mileage and the maximum value among the long-period nested feature values ​​based on the area of ​​oscillation waveforms are stored in each second storage cycle. At the end of the second threshold value update cycle, the maximum value among the long-period nested feature values ​​based on reciprocating motion mileage and the maximum value among the long-period nested feature values ​​based on the area of ​​oscillation waveforms corresponding to each second storage cycle is used as the second candidate alarm threshold value. The time length of the second threshold value update cycle is an integer multiple of the second storage cycle. The second candidate alarm threshold value is used to determine the second oscillation alarm threshold value. In response to the candidate alarm threshold value being higher than a preset second upper limit threshold, the second upper limit threshold is increased, or the correction is skipped; or, in response to the candidate alarm threshold value being lower than or equal to the second upper limit threshold, the lower limit threshold data of the long-cycle nested feature value under normal operating conditions is used as the second oscillation alarm threshold value. If the candidate alarm threshold value is less than the second oscillation alarm threshold value, the correction is skipped; if the candidate alarm threshold value is greater than or equal to the second oscillation alarm threshold value, the second oscillation alarm threshold value is corrected to the candidate alarm threshold value.

[0019] Optionally, the step of determining whether abnormal oscillation has occurred and issuing an oscillation warning based on the oscillation characteristic value and the oscillation alarm threshold value includes any one of the following: When the oscillation characteristic value is greater than or equal to the oscillation alarm threshold value, an abnormal oscillation is determined to have occurred, and an alarm is triggered. In response to the oscillation characteristic value being less than the oscillation alarm threshold value, it is determined that no abnormal oscillation has occurred.

[0020] Another embodiment of this application proposes a novel power system critical electrical quantity oscillation monitoring device, comprising: The acquisition module is used to select the electrical measurement points to be monitored, acquire the monitored electrical quantities collected by the electrical measurement points, and set the period time parameters related to oscillation monitoring. The feature determination module is used to calculate oscillation feature values ​​based on the monitored electrical quantity and the cycle time parameter, wherein the oscillation feature values ​​include: single-cycle rolling feature values ​​based on reciprocating motion mileage, long-cycle nested feature values ​​based on reciprocating motion mileage, single-cycle rolling feature values ​​based on the area of ​​the oscillation waveform, and long-cycle nested feature values ​​based on the area of ​​the oscillation waveform. The threshold setting module is used to set the oscillation alarm threshold value based on the oscillation characteristic value; The early warning module is used to determine whether abnormal oscillation has occurred and to issue an oscillation early warning based on the oscillation characteristic value and the oscillation alarm threshold value.

[0021] Another embodiment of this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the method described in the foregoing aspect.

[0022] Another embodiment of this application proposes a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the foregoing aspect.

[0023] Another embodiment of this application proposes a chip including processing circuitry configured to perform the method described in one aspect above.

[0024] Another embodiment of this application proposes a computer program product that, when executed by a processor, implements the method described in the foregoing aspect.

[0025] The novel power system key electrical quantity oscillation monitoring method, device, electronic equipment, chip, and storage medium proposed in this application extract oscillation characteristic values ​​from the monitored electrical quantities through multi-dimensional and multi-time-scale feature extraction and adaptive threshold tuning, which significantly improves the accuracy, sensitivity, and adaptability of power system oscillation monitoring.

[0026] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0027] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1A flowchart illustrating a novel method for monitoring oscillations of key electrical quantities in a power system, provided in an embodiment of this application; Figure 2 A schematic diagram of the structure of a novel power system key electrical quantity oscillation monitoring device provided in the embodiments of this application; Figure 3 A flowchart illustrating a novel method for monitoring oscillations of key electrical quantities in a power system, provided in an embodiment of this application; Figure 4 A flowchart illustrating a method for calculating single-cycle rolling characteristic values ​​based on reciprocating motion mileage, provided in an embodiment of this application; Figure 5 A flowchart illustrating a method for calculating long-period nested feature values ​​based on reciprocating motion mileage, provided in an embodiment of this application; Figure 6 A flowchart illustrating a method for calculating single-cycle rolling characteristic values ​​based on the area of ​​an oscillating waveform, provided in an embodiment of this application; Figure 7 A flowchart illustrating a method for calculating long-period nested eigenvalues ​​based on the area of ​​an oscillating waveform, provided in an embodiment of this application; Figure 8 This is a schematic diagram of a normal change identification curve of active power provided in an embodiment of this application; Figure 9 A schematic diagram of an active power anomaly change identification curve provided in an embodiment of this application; Figure 10 This is a schematic diagram of a normal change identification curve of active power provided in an embodiment of this application; Figure 11 A schematic diagram of an active power abnormal fluctuation identification curve provided in an embodiment of this application; Figure 12 This is a schematic diagram of a single-cycle identification curve for normal changes in active power provided in an embodiment of this application; Figure 13 This is a schematic diagram of a single-cycle identification curve for low-frequency active power oscillation provided in an embodiment of this application. Figure 14 This is a schematic diagram of a single-cycle identification curve for normal changes in active power provided in an embodiment of this application; Figure 15 This is a schematic diagram of a single-cycle identification curve for low-frequency active power oscillation provided in an embodiment of this application. Figure 16 This is a schematic diagram of a long-cycle identification curve for normal changes in active power provided in an embodiment of this application; Figure 17This is a schematic diagram of a long-period identification curve for low-frequency active power oscillation provided in an embodiment of this application; Figure 18 This is a schematic diagram of a long-cycle identification curve for normal changes in active power provided in an embodiment of this application; Figure 19 This is a schematic diagram of a long-period identification curve for low-frequency active power oscillation provided in an embodiment of this application; Figure 20 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application; Figure 21 This is a schematic diagram of the structure of a chip proposed in an embodiment of this application. Detailed Implementation

[0028] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0029] The following description, with reference to the accompanying drawings, describes a novel method, apparatus, electronic device, chip, and storage medium for monitoring oscillations of key electrical quantities in a power system according to embodiments of this application.

[0030] Figure 1 This is a schematic diagram of a novel power system key electrical quantity oscillation monitoring process provided in an embodiment of this application.

[0031] As one implementation, the novel power system critical electrical quantity oscillation monitoring method of this application embodiment can be configured in a novel power system critical electrical quantity oscillation monitoring device. The novel power system critical electrical quantity oscillation monitoring device can be applied to any electronic device so that the electronic device can perform the novel power system critical electrical quantity oscillation monitoring function.

[0032] Among them, electronic devices can be any device with computing capabilities, such as mobile terminals, which can be hardware devices with various operating systems, touch screens and / or displays, such as mobile phones, tablets, personal digital assistants, wearable devices, etc.

[0033] As another implementation, the novel power system key electrical quantity oscillation monitoring method of this application embodiment can also be executed by a chip with processing capabilities. The chip includes an image signal processing chip (ISP), a central processing unit (CPU), an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a field-programmable gate array (FPGA), a system on a chip (SOC), a reduced instruction set computer (RISC), etc., which will not be listed here.

[0034] It should be noted that all data collection operations related to users in this application are conducted with the user's authorization and in strict compliance with relevant laws and regulations such as privacy and security.

[0035] like Figure 1 As shown, the method may include the following steps: Step 101: Select the electrical measurement point to be monitored, acquire the monitored electrical quantities collected by the electrical measurement point, and set the period time parameters related to oscillation monitoring; Step 102: Calculate the oscillation characteristic value based on the monitored electrical quantity and the cycle time parameter, wherein the oscillation characteristic value includes: single-cycle rolling characteristic value based on reciprocating motion mileage, long-cycle nested characteristic value based on reciprocating motion mileage, single-cycle rolling characteristic value based on oscillation waveform area, and long-cycle nested characteristic value based on oscillation waveform area. Step 103: Adjust the oscillation alarm threshold value according to the oscillation characteristic value; Step 104: Determine whether abnormal oscillation has occurred and issue an oscillation warning based on the oscillation characteristic value and the oscillation alarm threshold value.

[0036] In this embodiment, within the power system, it is first necessary to determine which key electrical quantities require oscillation monitoring. These electrical quantities may include active power, reactive power, voltage, frequency, etc., which are important indicators of the power system's operating status. After selecting appropriate measurement points, real-time data of these electrical quantities are collected using sensors or monitoring equipment.

[0037] To perform oscillation monitoring, it is also necessary to set the relevant periodic time parameters. These parameters include the sampling refresh period, the duration of a single-cycle roll, and the duration of nested sub-cycles and parent cycles. Setting these time parameters is crucial for subsequent oscillation characteristic calculations, as they determine the data processing window and the timescale of the analysis.

[0038] Oscillation eigenvalues ​​are key parameters used to describe the oscillation characteristics of electrical quantities. By calculating these eigenvalues, the intensity and characteristics of the oscillation can be quantified. Specifically: Single-cycle rolling characteristic value based on reciprocating motion mileage: The reciprocating motion characteristics of oscillation are reflected by calculating the difference between the sum of the absolute values ​​of the changes in electrical quantities within a single cycle and the algebraic sum.

[0039] Long-period nested eigenvalues ​​based on reciprocating motion mileage: Within a long period, the long-term evolution trend of oscillations is captured by nesting eigenvalues ​​of multiple sub-periods.

[0040] Single-cycle rolling characteristic value based on the area of ​​the oscillating waveform: The amplitude variation characteristics of the oscillation are reflected by calculating the area of ​​the waveform.

[0041] Long-period nested eigenvalues ​​based on the area of ​​oscillating waveforms: Within a long period, the long-term trend of oscillation is captured by nesting the waveform area eigenvalues ​​of multiple sub-periods.

[0042] The oscillation alarm threshold is a key parameter for determining whether electrical quantities are experiencing abnormal oscillations. By statistically analyzing the maximum oscillation characteristic value in historical data, the alarm threshold can be dynamically adjusted to adapt to different operating states of the power system. This method can effectively reduce false alarms and missed alarms, and improve monitoring accuracy.

[0043] Finally, by comparing the calculated oscillation characteristic value with the set alarm threshold value, it is determined whether the electrical quantity is experiencing abnormal oscillation. If the oscillation characteristic value exceeds the alarm threshold value, a warning signal is issued to remind maintenance personnel to take appropriate measures to prevent the oscillation from causing greater impact on the power system.

[0044] Optionally, the monitored electrical quantities include: active power, reactive power, voltage, and frequency; the setting of the cycle time parameters related to oscillation monitoring includes: Set the time length of the sampling refresh cycle for the monitored electrical quantities; A first time length is set as the cycle time length for a single-cycle roll, and the first time length is an integer multiple of the sampling refresh cycle; A second time length is set as the sub-cycle time length of a long-cycle nesting, and the second time length is an integer multiple of the sampling refresh cycle; A third time length is set as the parent period length of the long-period nesting, and the third time length is an integer multiple of the second time length.

[0045] In this embodiment, the sampling refresh cycle time for monitored electrical quantities is set. t The cycle time t Parameters are either manually set or are inherent characteristics of the system. Set the first time length T 1 represents the cycle time length of a single-cycle rolling process. T 1 is the monitoring electrical quantity sampling refresh cycle. t multiples of x ; Set the second time length T 2 represents the time length of a nested sub-period within a long-period structure. T 2 is the sampling refresh cycle for monitored electrical quantities. t multiples of y ; Set the third time length T 3 is the length of the parent cycle in a long-cycle nested structure. T 3 is the sub-cycle time length T multiples of 2 z .

[0046] Optionally, the step of calculating the oscillation characteristic value based on the monitored electrical quantity and the period time parameter includes: Within the first period corresponding to the first time length, determine the change value of the monitored electrical quantity between each sampling refresh period and the adjacent sampling refresh period; Within the first cycle, the sum of the absolute values ​​of the changes in the monitored electrical quantities corresponding to all sampling refresh cycles, minus the absolute value of the algebraic sum of the changes in the monitored electrical quantities corresponding to all sampling refresh cycles, is taken as the single-cycle rolling characteristic value based on the reciprocating motion mileage.

[0047] In this embodiment, the setting includes x- An array of 1 element x for T 1 relative to t Multiples of; the elements in the array are marked as △ P 1. △ P 2 until △ P x-1 ; The change value of the monitored electrical quantity is calculated at each monitoring electrical quantity sampling refresh cycle to obtain Δ. P , △ P The sampled value of the electrical quantity monitored in the current cycle is subtracted from the sampled value of the electrical quantity monitored in the previous cycle. In each first cycle, △P x-2 Assign a value to △ P x-1 , will △ P x-3 Assign a value to △ P x-2 until △ P 1 is assigned to △ P 2. Finally, △ P Assign a value to △ P 1; In each first cycle, calculate the single-cycle rolling characteristic value based on the reciprocating motion mileage. δ The calculation formula is: .

[0048] Optionally, the step of calculating the oscillation characteristic value based on the monitored electrical quantity and the period time parameter includes: Within the second period corresponding to the second time length, the sampled values ​​of the monitored electrical quantities in each sampling refresh period and the changes in the monitored electrical quantities between each sampling refresh period and adjacent sampling refresh periods are determined. Within the second cycle, the sum of the absolute values ​​of the monitored electrical quantity samples corresponding to all sampling refresh cycles is subtracted from the algebraic sum of the monitored electrical quantity samples corresponding to all sampling refresh cycles, and this sum is used as the first sub-feature value. Within the second cycle, the change value of the monitored electrical quantity corresponding to the last sampling refresh cycle is subtracted from the change value of the monitored electrical quantity corresponding to the first sampling refresh cycle, and this is used as the second sub-feature value. Within the third period corresponding to the third time length, the first sub-feature values ​​corresponding to each second period are added together to obtain the third sub-feature value; wherein, the third period corresponding to the third time length includes multiple second periods; Within the third period, the absolute values ​​of the second sub-feature values ​​corresponding to each second period are added together, and the algebraic sum of the second sub-feature values ​​corresponding to each second period is subtracted to obtain the fourth sub-feature value. The third sub-feature value is added to the fourth sub-feature value to obtain the long-period nested feature value based on the reciprocating motion mileage.

[0049] In this embodiment, two containing z Two arrays, A and B, each containing n elements, are named as follows: a 1. a 2 until a z , b 1. b 2 until bz express, z for T 3 relative to T Multiples of 2; Settings include y An array C of n elements, where each element is named as follows: c 1. c 2 until c y express, y for T 2 relative to t Multiples of; The following operations are performed during each monitoring electrical quantity sampling refresh cycle, including: The sampling data of the current monitoring electrical quantity sampling refresh cycle p 1 Assigned to c 1. The sampling data for the next monitoring electrical quantity sampling refresh cycle is: p 2 assigned to c 2, until y Sampling data from the second period p y Assign to c y ; Nested sub-period time intervals between long periods T 2. Perform the following operations, including: Calculate the eigenvalues ​​of the sub-period α , β ,in: ; .

[0050] Will a z-1 Assign to a z ,Will a z-2 Assign to a z-1 until a 1 Assigned to a 2. Finally, α Assign to a 1; Will b z-1 Assign to b z ,Will b z-2 Assign to b z-1 until b 1 Assigned to b 2. Finally, β Assign tob ; Clear arrays C and D.

[0051] Calculate long-period nested rolling eigenvalues ​​based on reciprocating motion mileage γ ,include: ; ; .

[0052] Optionally, the step of calculating the oscillation characteristic value based on the monitored electrical quantity and the period time parameter includes: Within the first period corresponding to the first time length, determine the maximum and minimum values ​​of the monitored electrical quantity, and take multiple intermediate values ​​from the values ​​between the maximum and minimum values; Using the maximum value, minimum value, or any intermediate value as the integration cross-section, calculate the integration area of ​​the integration cross-section with all other integration cross-sections, and use the minimum value of the integration area as the area of ​​the first oscillation waveform corresponding to the integration cross-section. The minimum value of the area of ​​the first oscillating waveform is taken as the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform.

[0053] In this embodiment, the setting includes x An array of elements E , x for T 1 relative to t Multiples of; The array E The elements in are respectively labeled as P 1. P 2 until P x ; The monitored electrical quantities are sampled in each first cycle to obtain... P ; Each first cycle will P x-1 Assign to P x ,Will P x-2 Assign to P x-1 until P 1 Assigned to P 2. Finally, P Assign to P 1; For arrays E We evaluate the elements in the array to obtain the maximum value. P max and minimum valueP min and average P avg , ; In each first cycle, a single-cycle rolling characteristic value based on the area of ​​the oscillating waveform is calculated, including: Calculate the single-cycle rolling eigenvalue based on the area of ​​the oscillating waveform. ε The optional methods are as follows: The values ​​are taken from the minimum possible value to the maximum possible value of the monitored electrical quantity at fixed difference intervals; Find the values ​​between the maximum and minimum values ​​of the monitored electrical quantities. P max and minimum value P min The values ​​between, and the maximum value P max and minimum value P min Together they form the integral cross-section lines, and are sorted from smallest to largest. Assume there are a total of... m A number between the maximum value P max and minimum value P min The values ​​between these ranges are then the integral cross-sections are respectively q min , q 1. q 2…… q m , q max ,in q 1. q 2…… q m The value is between the maximum value and the maximum value. P max and minimum value P min The values ​​between q min equal P min , q max equal P max .

[0054] The following calculations are performed based on each integral section line, to... q j For example ( q j for P min , q 1. q 2…… qm , P max (a value in the equation), to obtain the integral area. Q j , ; right Q min , Q max as well as Q 1 to Q m The minimum value among the comparisons is taken as the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform. ε , .

[0055] Optionally, the step of calculating the oscillation characteristic value based on the monitored electrical quantity and the period time parameter includes: Within the first period corresponding to the first time length, determine the maximum and minimum values ​​of the monitored electrical quantity, and take multiple intermediate values ​​from the values ​​between the maximum and minimum values; The maximum, minimum, and average values ​​are respectively used as integration cross-sections. The integration area of ​​the integration cross-section with all other integration cross-sections is calculated. The minimum value of the integration area is used as the area of ​​the first oscillation waveform corresponding to the integration cross-section. The minimum value of the area of ​​the first oscillating waveform is taken as the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform.

[0056] In this embodiment, an optional method for calculating the single-period rolling characteristic value ε based on the area of ​​the oscillating waveform is as follows: The aforementioned maximum value P max Minimum value P min ,average value P avg These are respectively used as integral cross-sections; The integral area is obtained by performing the following calculations based on each integral section line: , , ; right Q min , Q max , Q avg The minimum value among the comparisons is taken as the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform. ε , .

[0057] Optionally, the step of calculating the oscillation characteristic value based on the monitored electrical quantity and the period time parameter includes: Within the second period corresponding to the second time length, determine the monitored electrical quantities for each sampling refresh cycle; Determine the maximum, minimum, and multiple intermediate values ​​of the monitored electrical quantity in each sampling refresh cycle of the second cycle; Using the intermediate value as the integration section line, calculate the integrated area of ​​the integration section line with all other integration section lines. A set of second oscillation waveform areas and integral cross-sections corresponding to a target number of second periods is determined, wherein each second period in the set is a group; the long-period nested feature value based on the oscillation waveform area is determined according to the frequency of occurrence of the value of each integral cross-section in the set; wherein the target number is an integer multiple of the third time length to the second time length.

[0058] In this embodiment, the minimum and maximum possible values ​​of the monitored electrical quantities are taken at fixed difference intervals. Settings include y An array of elements D The elements therein are d 1. d 2 until d y express, y for T 2 relative to t Multiples of; The following operations are performed during each monitoring electrical quantity sampling refresh cycle, including: Each monitoring electrical quantity sampling refresh cycle samples the change value of the monitoring electrical quantity, obtaining... P ; Refresh the sampling of each monitored electrical quantity for each cycle. P Stored sequentially in an array D middle; Nested sub-period time intervals between long periods T 2. Perform the following operations, including: For arrays D The maximum value is obtained by judging the included elements. d max and minimum value d min ; The value between the maximum and the minimum values d max and minimum value d min The values ​​between these points are used as the integral cross-section, and sorted from smallest to largest. Assume there are a total of... u The integral cross-sections are respectively... q1、 q 2…… q u ; The following calculations are performed based on each integral section line, to... q j For example ( q j for d min , d 1. d 2…… d y , d max (a value in the equation), to obtain the integral area. Q j , ; generate u An array with 2 rows and 2 columns, the first column stores... u The integral cross-sections are respectively... q 1、 q 2…… q u The second column stores the corresponding... u The integral areas are respectively Q 1、 Q 2…… Q u .

[0059] Clear array D.

[0060] Save the generated array D, sort it by generation time, and exclude the most recently generated array. z Delete any arrays created earlier than the one specified in the previous array. z For the T 3 relative to T Multiples of 2; List z All integral cross-sections contained in the array are counted, and the values ​​of each integral cross-section are calculated. z The frequency of an array is easily understood to be greater than or equal to 1 and less than or equal to 1. z Integers.

[0061] Then, based on the integral cross-sections, each is... z The frequency contained in each array is determined based on long-period nested eigenvalues ​​of the oscillating waveform area.

[0062] Optionally, determining the long-period nested feature value based on the occurrence frequency of each integral cross-section value in the set includes any one of the following: In response to the fact that the frequency of occurrence of the value of only one integral cross section line in all groups of the set is equal to the target number, the integral cross section line is determined as the target integral cross section line, and the value of the target integral cross section line is accumulated in the second oscillation waveform area corresponding to each second period to obtain the long-period nested feature value based on the oscillation waveform area; In response to the fact that the frequency of occurrence of the values ​​of at least two of the integral cross-sections in all groups of the set is equal to the target number, these integral cross-sections are determined as the target integral cross-sections. For each target integral cross-section, the second oscillation waveform surface corresponding to the target integral cross-section in each second period is accumulated to obtain multiple accumulated values. The minimum value among the accumulated values ​​is taken as the long-period nested feature value based on the oscillation waveform area. In response to the fact that the frequency of occurrence of the value of the integral cross section line in all groups of the set is less than the target number, the set is regrouped.

[0063] In this embodiment, the following situations apply: When an integral section line is z The frequency contained in each array is z At that time, perform the following operations: quilt z The frequency contained in each array is z When there is only one integration section line, the integration section line is placed in... z The corresponding integral areas in each array are summed, that is, the elements in the second column of each array that are in the same row as the integral cross-section line are summed to obtain the long-period nested eigenvalue based on the area of ​​the oscillating waveform. η .

[0064] quilt z The frequency contained in each array is z When there is more than one integration section line, perform the following operation: They will be z The frequency contained in each array is z The integral section line, in z The integral areas corresponding to each array are summed up, that is, the elements in the same row as the integral section line in each array are summed up to obtain multiple summed values; The minimum value among multiple accumulated values ​​is the long-period nested eigenvalue based on the area of ​​the oscillating waveform. η .

[0065] When the integral section line is z The frequency of the array is less than z At that time, perform the following operations: According to the principle of least grouping, zThe arrays are grouped such that for each group, the integral cross-sections contained in all arrays within that group can be found. Specifically, this includes: Set variables k , k The initial value is 2. k ; Will z The arrays are divided into k Group, exhaustively list all grouping methods; Under each grouping method, determine whether it is possible to find the integral cross-section line contained in all arrays of that group in each group; If there is a grouping method such that, under this method, the integral cross-section line contained in all arrays of that group can be found in each group, then randomly select one of the grouping methods that meets the condition and use it, and end the process; otherwise, determine... k Is it less than z ,if k equal z The same applies if... k Less than z ,make k = k +1; Repeat the process of exhaustively enumerating all grouping methods.

[0066] For each group, calculate the long-period nested grouping feature value. Taking a certain group as an example, it includes: When there is only one integral cross-section line contained in all arrays of the group, the integral area corresponding to the integral cross-section line in all arrays of the group is accumulated, that is, the elements in the same row as the integral cross-section line in each array are accumulated to obtain the long-period nested group characteristic value of the group. When there is more than one integral cross-section line contained in all arrays of the group, the integral areas corresponding to these integral cross-section lines in all arrays of the group are accumulated. That is, the elements in the same row as the integral cross-section line in each array are accumulated to obtain multiple accumulated values. The minimum value is then taken to obtain the long-period nested grouping characteristic value of the group.

[0067] The summation of the long-period nested eigenvalues ​​of all groups yields the long-period nested eigenvalue based on the area of ​​the oscillation waveform. η .

[0068] Optionally, adjusting the oscillation alarm threshold value based on the oscillation characteristic value includes: The single-cycle rolling feature value based on the reciprocating motion mileage and the single-cycle rolling feature value based on the oscillation waveform area are stored. At the end of the first storage period, the maximum value of the single-cycle rolling feature value based on the reciprocating motion mileage and the maximum value of the single-cycle rolling feature value based on the oscillation waveform area are recorded. The duration of the first storage period is an integer multiple of the sampling refresh period. The long-cycle nested feature values ​​based on reciprocating motion mileage and the long-cycle nested feature values ​​based on oscillating waveform area are stored. At the end of the second storage period, the maximum value among the long-cycle nested feature values ​​based on reciprocating motion mileage and the maximum value among the long-cycle nested feature values ​​based on oscillating waveform area are recorded. The time length of the second storage period is an integer multiple of the time length of the long-cycle nested sub-cycles. The oscillation alarm threshold value corresponding to each of the oscillation feature values ​​is determined based on the maximum value among the single-cycle rolling feature values ​​based on the reciprocating motion mileage, the maximum value among the single-cycle rolling feature values ​​based on the oscillation waveform area, the maximum value among the long-cycle nested feature values ​​based on the reciprocating motion mileage, and the maximum value among the long-cycle nested feature values ​​based on the oscillation waveform area.

[0069] In this embodiment, upper and lower threshold values ​​for normal operating conditions are set for the calculated oscillation characteristic values ​​of the monitored electrical quantities. The calculated oscillation characteristic values ​​are stored in the real-time data register, including: Set the duration T 4 is the time for real-time storage of feature values. T 4 is the monitoring electrical quantity sampling refresh cycle. t multiples of w 1; Settings include w Array of 1 element W 1; Perform single-cycle rolling characteristic value based on reciprocating motion mileage δ Single-period rolling eigenvalue based on the area of ​​the oscillating waveform ε The storage mechanism is to store the array in each sampling period. W 1 of w Assigning 1-1 elements to the first element w 1 element, the first w Assigning 1-2 elements to the first w 1-1 elements, until the first element is assigned to the second element, and finally... δ or ε Assign the value to the first element.

[0070] Set the duration T 5 is stored in real time as a feature value.T 5 represents the time length of a long-term nested sub-cycle. T multiples of 2 w 2; Settings include w Array of 2 elements W 2; Perform long-period nested feature values ​​based on reciprocating motion mileage γ Long-period nested eigenvalues ​​based on the area of ​​oscillating waveforms η The storage mechanism is based on the period in which feature values ​​are generated nested within each long period, i.e., the interval. T 2. Time, the array W 2nd w 2-1 elements are assigned to the first element. w 2 elements, the first w Assigning 2-2 elements to the first w 2-1 elements, until the first element is assigned to the second element, and finally... γ or η Assign the value to the first element.

[0071] Optionally, determining the oscillation alarm threshold value based on the maximum value among the single-cycle rolling feature values ​​based on the reciprocating motion mileage, the maximum value among the single-cycle rolling feature values ​​based on the oscillation waveform area, the maximum value among the long-cycle nested feature values ​​based on the reciprocating motion mileage, and the maximum value among the long-cycle nested feature values ​​based on the oscillation waveform area includes: The maximum value among the single-cycle rolling feature values ​​based on reciprocating motion mileage and the maximum value among the single-cycle rolling feature values ​​based on the area of ​​the oscillation waveform are stored in each first storage cycle. At the end of the first threshold value update cycle, the maximum value among the single-cycle rolling feature values ​​based on reciprocating motion mileage and the maximum value among the single-cycle rolling feature values ​​based on the area of ​​the oscillation waveform corresponding to each first storage cycle is used as the first candidate alarm threshold value. The time length of the first threshold value update cycle is an integer multiple of the first storage cycle. The first candidate alarm threshold value is used to determine the first oscillation alarm threshold value. In response to the candidate alarm threshold value being higher than a preset first upper limit threshold, the first upper limit threshold is increased, or the correction is skipped; or, in response to the candidate alarm threshold value being lower than or equal to the first upper limit threshold, the lower limit threshold data of the single-cycle rolling characteristic value under normal operating conditions is used as the first oscillation alarm threshold value. If the candidate alarm threshold value is less than the first oscillation alarm threshold value, the correction is skipped. If the candidate alarm threshold value is greater than or equal to the first oscillation alarm threshold value, the first oscillation alarm threshold value is corrected to the candidate alarm threshold value.

[0072] In this embodiment, the calculated oscillation characteristic value of the monitored electrical quantity ( δ , ε , γ , η ), to perform upper limit calculation, including: Settings include g Array of 1 element G 1; Every cycle time T 4. For the array W Take the maximum value of all elements that are 1; Every cycle time T 4. Transfer the array G 1 of g Assigning 1-1 elements to the first element g 1 element, the first g Assigning 1-2 elements to the first g 1-1 elements, until the first element is assigned to the second element, and finally the maximum value of the resulting elements is assigned to the first element.

[0073] When an abnormal operating condition related to the monitored electrical quantity occurs, the array should be switched off until the operating condition returns to normal. G 1 and array G Clear several elements of 2 from the beginning to the end to zero.

[0074] Every g 1× T The alarm threshold value for single-cycle rolling characteristic values ​​is corrected over a 4-cycle period, including retrieving an array. G The maximum value of all elements that are 1; array G The maximum value of all elements of 1 is compared with the upper limit threshold data of the single-cycle rolling characteristic value under normal operating conditions, including: If array G If the maximum value of all elements of 1 is greater than the upper limit threshold data of the single-cycle rolling characteristic value under normal working conditions, then manual judgment is required to either increase the upper limit threshold data or skip this correction. If array G If the maximum value of all elements of 1 is less than the upper limit threshold data of the single-cycle rolling characteristic value under normal working conditions, then proceed to the subsequent correction steps; Initially, the lower limit threshold value of the single-cycle rolling characteristic value under normal operating conditions is used as the alarm threshold value.

[0075] array G The maximum value of all elements in 1 is compared with the alarm threshold value, including: If array G If the maximum value of all elements in 1 is less than or equal to the alarm threshold, then skip this correction. If array GIf the maximum value of all elements in 1 is greater than the alarm threshold, then the alarm threshold is adjusted to an array. G The maximum value of all elements that are 1.

[0076] Optionally, determining the oscillation alarm threshold value based on the maximum value among the single-cycle rolling feature values ​​based on the reciprocating motion mileage, the maximum value among the single-cycle rolling feature values ​​based on the oscillation waveform area, the maximum value among the long-cycle nested feature values ​​based on the reciprocating motion mileage, and the maximum value among the long-cycle nested feature values ​​based on the oscillation waveform area includes: The maximum value among the long-period nested feature values ​​based on reciprocating motion mileage and the maximum value among the long-period nested feature values ​​based on the area of ​​oscillation waveforms are stored in each second storage cycle. At the end of the second threshold value update cycle, the maximum value among the long-period nested feature values ​​based on reciprocating motion mileage and the maximum value among the long-period nested feature values ​​based on the area of ​​oscillation waveforms corresponding to each second storage cycle is used as the second candidate alarm threshold value. The time length of the second threshold value update cycle is an integer multiple of the second storage cycle. The second candidate alarm threshold value is used to determine the second oscillation alarm threshold value. In response to the candidate alarm threshold value being higher than a preset second upper limit threshold, the second upper limit threshold is increased, or the correction is skipped; or, in response to the candidate alarm threshold value being lower than or equal to the second upper limit threshold, the lower limit threshold data of the long-cycle nested feature value under normal operating conditions is used as the second oscillation alarm threshold value. If the candidate alarm threshold value is less than the second oscillation alarm threshold value, the correction is skipped; if the candidate alarm threshold value is greater than or equal to the second oscillation alarm threshold value, the second oscillation alarm threshold value is corrected to the candidate alarm threshold value.

[0077] In this embodiment, the calculated oscillation characteristic value of the monitored electrical quantity ( δ , ε , γ , η ), to perform upper limit calculation, including: Settings include g Array of 2 elements G 2; Every cycle time T 5. For the array W Take the maximum value of all elements in 2; Every cycle time T 5. The array G 2nd g 2-1 elements are assigned to the first element. g 2 elements, the first g Assigning 2-2 elements to the first g2-1 elements, until the first element is assigned to the second element, and finally the maximum value of the resulting elements is assigned to the first element.

[0078] When an abnormal operating condition related to the monitored electrical quantity occurs, the array should be switched off until the operating condition returns to normal. G 1 and array G Clear several elements of 2 from the beginning to the end to zero.

[0079] Every g 2× T The alarm threshold value for long-period nested feature values ​​is adjusted over a 5-cycle period, including: Get array G 2 is the maximum value of all elements; array G The maximum value of all elements in 2 is compared with the upper limit threshold data of the long-period nested feature value under normal operating conditions, including: If array G If the maximum value of all elements in 2 is greater than the upper limit threshold data of the long-cycle nested feature value under normal operating conditions, then manual judgment is required to either increase the upper limit threshold data or skip this correction. If array G If the maximum value of all elements in 2 is less than the upper limit threshold data of long-period nested feature values ​​under normal operating conditions, then proceed to the subsequent correction steps. Initially, the lower limit threshold data of long-cycle nested feature values ​​under normal operating conditions is used as the alarm threshold value.

[0080] array G The maximum value of all elements in 2 is compared with the alarm threshold value, including: If array G If the maximum value of all elements in 2 is less than or equal to the alarm threshold, then skip this correction. If array G If the maximum value of all elements in array 2 is greater than the alarm threshold, then the alarm threshold is adjusted to an array. G The maximum value of all elements of 2.

[0081] Optionally, the step of determining whether abnormal oscillation has occurred and issuing an oscillation warning based on the oscillation characteristic value and the oscillation alarm threshold value includes any one of the following: When the oscillation characteristic value is greater than or equal to the oscillation alarm threshold value, an abnormal oscillation is determined to have occurred, and an alarm is triggered. In response to the oscillation characteristic value being less than the oscillation alarm threshold value, it is determined that no abnormal oscillation has occurred.

[0082] In this embodiment, determining whether abnormal oscillation has occurred and issuing an oscillation warning based on the oscillation characteristic value and the oscillation alarm threshold value includes any one of the following: When the oscillation characteristic value is greater than or equal to the oscillation alarm threshold value, an abnormal oscillation is determined to have occurred; In response to the oscillation characteristic value being less than the oscillation alarm threshold value, it is determined that no abnormal oscillation has occurred.

[0083] To achieve the above embodiments, this application also proposes a novel power system key electrical quantity oscillation monitoring device.

[0084] Figure 2 This is a schematic diagram of the structure of a novel power system key electrical quantity oscillation monitoring device provided in an embodiment of this application.

[0085] like Figure 2 As shown, the device may include: The acquisition module 210 is used to select the electrical measurement point to be monitored, acquire the monitored electrical quantity collected by the electrical measurement point, and set the period time parameters related to oscillation monitoring. The feature determination module 220 is used to calculate oscillation feature values ​​based on the monitored electrical quantity and the cycle time parameter, wherein the oscillation feature values ​​include: single-cycle rolling feature values ​​based on reciprocating motion mileage, long-cycle nested feature values ​​based on reciprocating motion mileage, single-cycle rolling feature values ​​based on the area of ​​the oscillation waveform, and long-cycle nested feature values ​​based on the area of ​​the oscillation waveform. The threshold setting module 230 is used to set the oscillation alarm threshold value according to the oscillation characteristic value; The early warning module 240 is used to determine whether abnormal oscillation has occurred and to issue an oscillation early warning based on the oscillation characteristic value and the oscillation alarm threshold value.

[0086] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and will not be repeated here.

[0087] To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method described in the foregoing method embodiments.

[0088] To implement the above embodiments, this application also proposes a computer program product having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in the foregoing method embodiments.

[0089] To implement the above embodiments, this application also proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the method described in the foregoing method embodiments.

[0090] Figure 3 A flowchart illustrating a novel method for monitoring oscillations of critical electrical quantities in a power system, provided in this application embodiment; as shown in the figure, the method includes: S1000) Select the electrical measurement points to be monitored, including active power, reactive power, voltage, and frequency, input them into the ultra-low frequency oscillation monitoring module, and set the corresponding cycle time parameters, including: S1100) Set the monitoring electrical quantity sampling refresh cycle time t The cycle time t These are either manually set parameters or inherent system characteristic parameters. This embodiment uses the Azhutian Photovoltaic Power Station and Jinghong Power Plant of Huaneng Lancang River Hydropower Co., Ltd. as examples. The monitored electrical quantity is the active power of power generation, and its sampling refresh cycle time is... t It lasts for 1 second; S1200) Set time length T 1 represents the cycle time length of a single-cycle rolling process. T 1 is the monitoring electrical quantity sampling refresh cycle. t multiples of x The cycle time length of a single-cycle rolling process T 1 represents 60 seconds. x = T 1 / t =60; S1300) Set time length T 2 represents the time length of a nested sub-period within a long-period structure. T 2 is the sampling refresh cycle for monitored electrical quantities. t multiples of y The time length of the nested sub-cycles within the long-term cycle T 2 is 60 seconds. x = T 2 / t =60; S1400) Set time length T 3 is the length of the parent cycle in a long-cycle nested structure. T 3 is the sub-cycle time length T multiples of 2 z For the Jinghong Power Plant, the length of the nested parent cycle is... T 3 represents 300 seconds. z =5, for the Azhutian photovoltaic power station, the length of the parent cycle in the long-cycle nesting. T 3 is 600 seconds, then z =10.

[0091] Figure 4 This is a flowchart illustrating a method for calculating single-cycle rolling characteristic values ​​based on reciprocating motion mileage, as provided in an embodiment of this application; as shown in the figure, S2000) Single-cycle rolling characteristic values ​​based on reciprocating motion mileage δ The calculation methods include: S2100) settings include x-1 An array of elements x As described in S1200 T 1 relative to t Multiples of, among which x =60, which means setting an array containing 59 elements; The elements in the arrays described in S2200 and S2100 are respectively marked as △ P 1. △ P 2 until △ P 59 ; S2300 calculates the change in monitored electrical quantities in each sampling period to obtain Δ. P , △ P The active power value is calculated by subtracting the sampled value of the electrical quantity from the previous period from the sampled value of the electrical quantity monitored in the current period. In this embodiment, the active power value collected in the current sampling period is set to... P 1. The active power value collected in the next sampling period is P 2. The change in active power monitored during this period is Δ P = P 2 －P 1; S2400) will Δ in each sampling period P x-2 Assign a value to △ P x-1 , will △ P x-3 Assign a value to △ P x-2 until △ P 1 is assigned to △ P 2. Finally, △ P Assign a value to △ P 1; S2500) calculates the single-cycle rolling characteristic value based on the reciprocating motion mileage in each sampling period. δ , In this embodiment, T Within one cycle, the active power is based on the single-cycle rolling characteristic value of the reciprocating motion mileage. δ This is the step increment value of the data in rows 1 to 59 of the array, i.e.: P=(|△P 1 |+|△P 2 |+|△P 3 |+……+|△P57 |+|△P 58 |+|△P 59 )－|△P 1 +△P 2 +△P 3 +……+△P 57 +△P 58 +△P 59 | For the Azhutian photovoltaic power station and Jinghong power plant, calculations were performed under two operating conditions: normal and abnormal fluctuations in active power. T Within one cycle, the active power is based on the single-cycle rolling characteristic value of the reciprocating motion mileage. δ This includes calculating the characteristic values ​​of active power waves for 1 to 60 seconds, 2 to 61 seconds, 3 to 62 seconds, ..., 60 to 119 seconds. δ The Azhutian photovoltaic power station continuously calculated 3654 sets of normal fluctuations in active power and 2399 sets of abnormal fluctuations in active power sampling data. For details, please refer to [link to results]. Figure 8 Schematic diagram of active power normal change identification curve; Figure 9 A schematic diagram of the active power anomaly identification curve; Jinghong Power Plant continuously calculated 4200 sets of normal active power fluctuations and 4201 sets of abnormal active power fluctuation sampling data. See the results for details. Figure 10 Schematic diagram of active power normal change identification curve; Figure 11 Schematic diagram of active power abnormal fluctuation identification curve.

[0092] Figure 5 This is a flowchart illustrating a method for calculating long-period nested feature values ​​based on reciprocating motion mileage, as provided in an embodiment of this application. Figure 5 As shown: S3000) Based on long-period nested feature values ​​of reciprocating motion mileage γ The calculation methods include: S3100) sets two including z Two arrays, A and B, each containing n elements, are named as follows: a 1. a 2 until a z , b 1. b 2 until b z express, z As described in S1400 T 3 relative to T In this embodiment, for the Jinghong Power Plant, multiples of 2, arrays A and B each contain 5 elements, i.e. z=5For the Azhutian photovoltaic power station, arrays A and B each contain 10 elements, that is... z =10; S3200) settings include y An array C of n elements, where each element is named as follows: c 1. c 2 until c y express, y As described in S1300 T 2 relative to t Multiples of, in this embodiment y =60; S3210) settings include m-1 An array D of n elements, wherein the elements are defined by... d 1. d 2 until d m-1 express, m As described in S1300 T 2 relative to t Multiples of, in this embodiment m =60; S3300 performs the following operations in each sampling period, including: Sample data for the current sampling period p 1 Assigned to c 1. The sampling data for the next sampling period is p 2 assigned to c 2, until y Sampling data during the sampling period p y Assign to c y In this embodiment, the active power data for the current sampling period is set as follows: p 1. The active power data for the next sampling period is as follows: p 2, then in T 2. Within a 60-second period, the active power data for the 60th sampling period is: p 60 Assign values ​​to array C sequentially to obtain c 1= p 1. c 2= p 2. c 3= p 3, ... c 60= p 60 ; S3310) calculates the change value of the monitored electrical quantity to obtain Δ P , △ P The active power value is calculated by subtracting the sampled value of the electrical quantity from the previous period from the sampled value of the electrical quantity monitored in the current period. In this embodiment, the active power value collected in the current sampling period is set to... P 1. The active power value collected in the next sampling period is P 2. The change in active power monitored during this period is Δ P = P 2 －P 1. After assigning values ​​to array C, we get △ P= c 2- c 1; S3320) Each sampling period will d m-2 Assign to d m-1 ,Will d m-3 Assign to d m-2 until d 1 Assigned to d 2. Finally, △ P Assign to d 1; S3400) Sub-period time nested every long period T 2. Perform the following operations, including: S3410) Calculate the eigenvalues ​​of the sub-periods α , β ,in: S3411) In this embodiment, in T Within a period of 2 = 60 seconds, the eigenvalues ​​of the sub-periods α This is the step increment value of the data in rows 1 to 59 of array D, i.e.: ; S3412) In this embodiment, in T Within a period of 2 = 60 seconds, the eigenvalues ​​of the sub-periods β is taken at the 60th second. The difference between the sample value and the sample value in the first second, i.e. ; S3420) will a z-1 Assign to a z ,Will a z-2 Assign to a z-1 until a 1 Assigned to a 2. Finally, α Assign to a 1. InT Within 2 cycles, array A is updated in real time based on the calculation results, that is, array A is updated once every 60 seconds; S3430) will b z-1 Assign to b z ,Will b z-2 Assign to b z-1 until b 1 Assigned to b 2. Finally, β Assign to b ,exist T Within 2 cycles, array B is updated in real time based on the calculation results, that is, array B is updated once every 60 seconds; S3440) Clears arrays C and D; S3450) Calculates long-period nested rolling characteristic values ​​based on reciprocating motion mileage. γ ,include: S3451) In this embodiment, for the Jinghong Power Plant, array A is calculated once each time it is updated. Value, of which For the Azhutian photovoltaic power station, the calculation is performed once every time array A is updated. Value, of which ; S3452) In this embodiment, for the Jinghong Power Plant, array B is calculated once each time it is updated. Value, of which For the Azhutian photovoltaic power station, the calculation is performed once every time array B is updated. Value, of which ; S3453) In this embodiment, for the Azhutian photovoltaic power station, in T 3 =600 Within a second period, long-cycle nested rolling characteristic values ​​γ based on reciprocating motion mileage were calculated for both normal and abnormal active power fluctuations at time intervals of 1-10 minutes, 2-11 minutes, 3-12 minutes, ..., 9-13 minutes, and 10-14 minutes. The Azhutian photovoltaic power station continuously calculated 3654 sets of normal active power fluctuation data and 2399 sets of abnormal active power fluctuation data. For detailed results, see [link to results]. Figure 8 This is a schematic diagram of a normal change identification curve of active power provided in an embodiment of this application; Figure 9 This is a schematic diagram of an active power anomaly identification curve provided in an embodiment of this application; as shown in the figure, for the Jinghong Power Plant, in TWithin a period of 300 seconds, long-cycle nested rolling characteristic values ​​based on reciprocating motion mileage are calculated for both normal and abnormal fluctuations in active power at intervals of 1 to 5 minutes, 2 to 6 minutes, 3 to 7 minutes, 4 to 8 minutes, and 5 to 9 minutes. γ Jinghong Power Plant continuously calculated 4200 sets of active power total power normal fluctuation and abnormal fluctuation sampling data. See the results for details. Figure 10 Schematic diagram of active power normal change identification curve; Figure 11 Schematic diagram of active power abnormal fluctuation identification curve.

[0093] Figure 6 This is a flowchart illustrating a method for calculating the single-cycle rolling characteristic value based on the area of ​​an oscillating waveform, as provided in an embodiment of this application. Figure 6 As shown: S4000) Single-period rolling eigenvalue based on the area of ​​the oscillating waveform ε The calculation methods include: S4100) settings include x An array of elements E , x As described in S1200 T 1 relative to t The multiple of, in this embodiment ，T 1 = 60 seconds t =1 second ， but x =60; The array described in S4200 and S4100 E The elements in are respectively labeled as P 1. P 2 until P x ,in P x =P 60 ; The S4300 samples the monitored electrical quantities in each sampling cycle to obtain... P In this embodiment, the monitored electrical quantities are the active power of the entire Azhutian photovoltaic power station and the single unit power generation of the Jinghong power plant; S4400) will each sampling period will P x-1 Assign to P x ,Will P x-2 Assign to P x-1 until P 1 Assigned to P 2. Finally, P Assign to P 1. Based on real-time sampling data, adjust the array...E Perform rolling updates; S4500) judges the array elements described in S4100 to obtain the maximum value. P max and minimum value P min and average P avg , When array E Each time the array is updated, E middle P 1- P 60 Use data to make judgments; S4600) calculates a single-cycle rolling characteristic value based on the area of ​​the oscillating waveform in each sampling period, including: S4610) Calculate the single-period rolling eigenvalue based on the area of ​​the oscillating waveform. ε Option one is as follows: S4611) The value is taken from the minimum possible value to the maximum possible value of the monitored electrical quantity at a fixed difference interval. In this embodiment, the minimum possible value of the active power of the Azhutian photovoltaic power station is set to 0, the maximum possible value is set to 425, the minimum possible value of the active power of the Jinghong power plant is set to 0, the maximum possible value is set to 350, and the fixed difference interval is set to 5. (S4612) Find the value between the maximum and the minimum values ​​in S4611. P max and minimum value P min The values ​​between, and the maximum value P max and minimum value P min Together they form the integral cross-section lines, and are sorted from smallest to largest. Assume there are a total of... m A number between the maximum value P max and minimum value P min The values ​​between these ranges are then the integral cross-sections are respectively q min , q 1. q 2…… q m , q max ,in q 1. q 2…… q m The value of S4611 is between the maximum and the maximum value. P max and minimum value P min The values ​​betweenq min equal P min , q max equal P max In this embodiment, 60-second power sampling data were collected from the Azhutian Photovoltaic Power Station and the Jinghong Power Plant for calculation. For the Jinghong Power Plant, the following results were obtained: P max =300.88, P min =299, the three integral cross-sections are respectively q min =299、 q 1=300 q max =300.88; This is the value obtained for the Azhutian photovoltaic power station. P max =204.25, P min =198.14, the three integral cross-sections are respectively q min =198.14、 q 1=200 q max =204.25; S4613) The following calculations are performed based on each integral section line, to... q j For example ( q j for P min , q 1. q 2…… q m , P max (a value in the equation), to obtain the integral area. Q j , By calculating the integration area of ​​the three integration cross-sections obtained from the Jinghong Hydropower Plant, we can obtain... Q min =57.58 、Q 1 = 27.86 、Q max =55.21; Calculate the integration area of ​​the three integration cross-sections obtained for the Azhutian photovoltaic power station, and obtain the following: Q min =153.457 、Q 1 =91.377、Q max =213.171; S4614)Q min , Q max as well as Q 1 to Q m The minimum value among the comparisons is taken as the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform. ε , The integral area of ​​Jinghong Power Plant was calculated. Q min =57.58 、Q 1 = 27.86 、Q max Compare 55.21, where the minimum value is... Q 1, that is, the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform within that 60-second time period. ε is 27.86; the integral area of ​​the Azhutian photovoltaic power station. Q min =153.457 、Q 1 = 91.377 、Q max Compare 213.171 with the minimum value. Q 1, that is, the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform within that 60-second time period. ε It is 91.377; In this embodiment, to accurately distinguish between normal changes and abnormal fluctuations in active power within a single cycle, 2800 sets of data on normal power changes and 4200 sets of data on abnormal power fluctuations from Jinghong Power Plant were collected and continuously calculated. The results are detailed in [link to relevant documentation]. Figure 12 A schematic diagram of a single-cycle identification curve for normal changes in active power; Figure 13 A schematic diagram of the single-cycle identification curve for low-frequency oscillation of active power; as shown in the figure, 3654 sets of data on normal power changes and 2500 sets of data on abnormal power fluctuations were collected from the Azhutian photovoltaic power station, and continuous rolling calculations were performed. See details for the results. Figure 14 A schematic diagram of a single-cycle identification curve for normal changes in active power; Figure 15 A schematic diagram of the single-cycle identification curve of low-frequency oscillation of active power.

[0094] S4620) Calculate the single-period rolling eigenvalue based on the area of ​​the oscillating waveform. ε The second optional method is as follows: S4621) The maximum value obtained from S4500 P max Minimum value P min ,average value P avg These are respectively used as integral cross-sections; S4622) The integral area is obtained by performing the following calculations based on each integral section line, respectively. , , ; S4623) Q min , Q max , Q avg The minimum value among the comparisons is taken as the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform. ε , .

[0095] Figure 7 This is a flowchart illustrating a method for calculating long-period nested eigenvalues ​​based on the area of ​​an oscillating waveform, as provided in an embodiment of this application. Figure 7 As shown: S5000) Long-period nested eigenvalues ​​based on the area of ​​the oscillating waveform η The calculation methods include: (S5100) Monitor the minimum and maximum possible values ​​of electrical quantities, taking values ​​at fixed difference intervals. In this embodiment, the monitored electrical quantities are the active power generated by the Azhutian photovoltaic power station and the Jinghong power plant. The minimum possible value of the active power of the Azhutian photovoltaic power station is set to 0, and the maximum possible value is set to 425. The minimum possible value of the active power of the Jinghong power plant is set to 0, and the maximum possible value is set to 350. The fixed difference interval for both is set to 5. S5200) settings include y An array of elements D The elements therein are d 1. d 2 until d y express, y As described in S1300 T 2 relative to t In this embodiment, the multiple is for the Azhutian photovoltaic power station. y Set the value to 120 ， Regarding the Jinghong Power Plant, y Set the value to 60; S5300 performs the following operations in each sampling period, including: S5310) Samples the changes in monitored electrical quantities in each sampling period to obtain... P In this embodiment, the monitored electrical quantities are the active power generated by the Azhutian photovoltaic power station and the Jinghong power plant; S5320) stores P for each sampling period into array D in sequence, and updates array D in a rolling manner according to the real-time sampling data.

[0096] S5400) Sub-cycle time nested every long cycle T 2. Perform the following operations, including: S5410) Determine the maximum value by evaluating the elements contained in array D. d max and minimum value d min In this embodiment, 60-second active power sampling data of Azhutian Photovoltaic Power Station and Jinghong Power Plant are collected and calculated. For Jinghong Power Plant, the following can be obtained: d max =300.88 ，d min =299; For the Azhutian photovoltaic power station, we can obtain... d max =204.25 ，d min =198.14; S5420) takes the value between the maximum and the minimum values ​​of S5310. d max and minimum value d min The values ​​between these values ​​are used as the integral cross-section, and sorted from smallest to largest. Assume there are a total of... u The integral cross-sections are respectively... q 1、 q 2…… q u For Jinghong Power Plant, S5310 is between its maximum value. d max and minimum value d min The value between them is 300, and there is only one integration section line. q 1; For the Azhutian photovoltaic power station, S5310 is between its maximum value. d max and minimum value d min The value between them is 200, and there is only one integral section line. q 1。

[0097] S5430) The following calculations are performed based on each integral section line, to... q j For example ( q j for d min , d 1. d 2…… d y , d max (a value in the equation), to obtain the integral area.Q j , According to the integral section line q 1. Calculate the integrated area of ​​Jinghong Power Plant and Azhutian Photovoltaic Power Plant. Q 1. S5440) generated u An array with 2 rows and 2 columns, the first column stores... u The integral cross-sections are respectively... q 1、 q 2…… q u The second column stores the corresponding... u The integral areas are respectively Q 1、 Q 2…… Q u .

[0098] S5450) clears array D.

[0099] S5500) saves the array generated by S5440, sorts it by generation time, and excludes the most recently generated array. z Delete any arrays created earlier than the one specified in the previous array. z As described in S1400 T 3 relative to T Multiples of 2; in this embodiment, for the Azhutian photovoltaic power station, the length of the long-cycle nested parent cycle is... T 3 is 600 seconds, then z=10 For the Jinghong Power Plant, the length of the nested parent cycle is... T 3 represents 300 seconds. z=5。

[0100] S5600) List z All integral cross-sections contained in the array are counted, and the values ​​of each integral cross-section are calculated. z The frequency of an array is easily understood to be greater than or equal to 1 and less than or equal to 1. z The integers. In this embodiment, for the Azhutian photovoltaic power station and for the Jinghong power plant, all integral cross-sections contained in 10 and 5 arrays are listed respectively, and the frequency of each integral cross-section contained in each array is counted.

[0101] S5700) When an integral section line is... z The frequency contained in each array is z At that time, perform the following operations: S5710) was z The frequency contained in each array is zWhen there is only one integration section line, the integration section line is placed in... z The corresponding integral areas in each array are summed, that is, the elements in the second column of each array that are in the same row as the integral cross-section line are summed, as described in S5440, to obtain the long-period nested eigenvalue based on the area of ​​the oscillating waveform. η ; S5720) was z The frequency contained in each array is z When there is more than one integration section line, perform the following operation: S5721) will be respectively z The frequency contained in each array is z The integral section line, in z The corresponding integral areas in each array are summed up, that is, the elements in the second column of each array that are in the same row as the integral section line, as described in S5440, are summed up to obtain multiple summed values. S5722) Takes the minimum value from the multiple accumulated values ​​of S5721, which is the long-period nested eigenvalue based on the area of ​​the oscillating waveform. η .

[0102] S5800) When the integral section line is z The frequency of the array is less than z At that time, perform the following operations: S5810) According to the principle of least grouping, z The arrays are grouped such that for each group, the integral cross-sections contained in all arrays within that group can be found. Specifically, this includes: S5811) Setting variables k , k The initial value is 2. k In this embodiment, the Azhutian photovoltaic power station k Jinghong Power Plant k ; S5812) will z The arrays are divided into k Group, exhaustively list all grouping methods; S5813) Under each grouping method, determine whether the integral cross-section line contained in all arrays of the group can be found in each group; S5814) If there is a grouping method such that, under this grouping method, the integral cross-section line contained in all arrays of that group can be found in each group, then randomly select one of the grouping methods that meets the condition and use it, and end S5810; otherwise, determine... k Is it less than z ,if k equalz Similarly, S5810 will end if k Less than z ,make k = k +1; (S5815) Jump back to S5812 and repeat S5812 and subsequent steps.

[0103] (S5820) For each group, refer to S5700 to calculate the long-period nested grouping feature value. Taking a certain group as an example, it includes: (S5821) When there is only one integral cross-section line contained in all arrays of the group, the integral area corresponding to the integral cross-section line in all arrays of the group is accumulated, that is, the elements in the same row as the integral cross-section line in the second column of each array as described in S5440 are accumulated to obtain the long-period nested grouping characteristic value of the group. (S5822) When there is more than one integral cross-section line contained in all arrays of the group, the integral cross-section lines are summed up in all arrays of the group. That is, the elements in the same row as the integral cross-section line in the second column of each array as described in S5440 are summed up to obtain multiple summed values. The minimum value is taken from these summed values ​​to obtain the long-period nested grouping characteristic value of the group.

[0104] (S5830) The long-period nested grouping eigenvalues ​​of all groups are summed to obtain the long-period nested eigenvalues ​​based on the area of ​​the oscillation waveform. η .

[0105] To accurately distinguish between normal changes and abnormal fluctuations in active power over long periods, 2800 sets of data on normal power changes and 4200 sets of data on abnormal power fluctuations were collected from Jinghong Power Plant for continuous rolling calculations. The results are detailed in [link to results]. Figure 16 Schematic diagram of long-cycle identification curve for normal changes in active power; Figure 17 A schematic diagram of the long-period identification curve for low-frequency oscillations of active power; 3654 sets of data on normal power changes and 2500 sets of data on abnormal power fluctuations were collected from the Azhutian photovoltaic power station, and continuous rolling calculations were performed. See details for the results. Figure 18 Schematic diagram of long-cycle identification curve for normal changes in active power; Figure 19 A schematic diagram of the long-period identification curve for low-frequency oscillation of active power.

[0106] The manual adjustment of the oscillation alarm threshold value in S6000 includes: S6100) The oscillation characteristic values ​​of the monitored electrical quantities calculated by S2000, S3000, S4000, and S5000 are stored in the historical data respectively. In this embodiment, the oscillation characteristic values ​​of the monitored electrical quantities calculated by S2000, S3000, S4000, and S5000 of Jinghong Power Plant are stored in the historical data respectively. S6200) takes the highest historical value of the oscillation characteristic value stored in S6100 under normal operating conditions. For Jinghong Power Plant under normal operating conditions, the maximum value of s2000 is 9.96, the maximum value of s3000 is 30.6, the maximum value of s4000 is 1563, and the maximum value of s5000 is 1534. S6300 sets a parameter that is greater than the highest historical data value obtained from S6200 as the manual threshold value for oscillation alarm. For Jinghong Power Plant, the manual threshold value for oscillation alarm can be set to 100 for S2000, 250 for S3000, 300 for S4000, and 2000 for S5000.

[0107] S7000) Automatic tuning of the oscillation alarm threshold value includes: S7100 sets upper and lower threshold values ​​for the oscillation characteristic values ​​of the monitored electrical quantities calculated by S2000, S3000, S4000, and S5000 under normal operating conditions. These values ​​are set manually based on experience. For the Jinghong Power Plant under normal operating conditions, the upper and lower threshold values ​​for S2000 are 15 and 0.3, respectively; the maximum values ​​for S4000 are 50 and 15, respectively; the upper and lower threshold values ​​for S3000 are 1700 and 5, respectively; and the upper and lower threshold values ​​for S5000 are 1700 and 165, respectively. S7200 stores the oscillation characteristic values ​​of the monitored electrical quantities calculated by S2000, S3000, S4000, and S5000 into the real-time data register, including: S7210) Set time length T 4 is the time for real-time storage of feature values. T 4 is the monitoring electrical quantity sampling refresh cycle. t multiples of w 1; In this embodiment, a single-cycle rolling characteristic value is set for Jinghong Power Plant ( δ, ε The storage period T4 is 60 seconds. w 1=60, meaning it stores data from the most recent 60 sampling periods; S7220) settings include w Array of 1 element W1. Create an array with a capacity of 60 elements. W 1; S7230) stores the single-cycle rolling feature values ​​obtained in S2000 and S4000. The mechanism is that in each sampling cycle, the array described in S7220 is used to store the single-cycle rolling feature values. w Assigning 1-1 elements to the first element w 1 element, the first w Assigning 1-2 elements to the first w The process proceeds 1-1 times until the first element is assigned to the second element. Finally, the single-cycle rolling characteristic value obtained in S2000 or S4000 is assigned to the first element. In this embodiment, the array... W 1st w Assigning the 1st to the 1st bit data w 1st place w Assigning 1-2 bits to w 1-1 bits, and so on, in each sampling period, a new calculation is performed. δ or ε Store in array W First, taking Jinghong Power Plant as an example, updates every second. δ or ε Values, arrays W 1. Always retain the feature value sequence of the most recent 60 seconds.

[0108] S7240) Set time length T 5 is stored in real time as a feature value. T 5 represents the time length of a long-term nested sub-cycle. T multiples of 2 w 2; In this embodiment, a long-period nested sub-period storage duration is set for the Jinghong Power Plant. T5 For 300 seconds, w 2=5, meaning it stores the calculation data of the most recent 5 nested sub-cycles over long periods; S7250) settings include w Array of 2 elements W 2. Create an array with a capacity of 5 elements. W 2; S7260) stores the long-period nested eigenvalues ​​obtained from S3000 and S5000. The mechanism is based on the period in which each long-period nested eigenvalue is generated, i.e., the interval. T 2. At time 2, the array described in S7250 will be... w 2-1 elements are assigned to the first element. w 2 elements, the first w Assigning 2-2 elements to the first w2-1 elements, until the first element is assigned to the second element, and finally the long-period nested feature value obtained from S3000 or S5000 is assigned to the first element. In this embodiment, the array is... W 2nd w Assigning the 1st to the 1st bit of data w 1st place w Assigning 1-2 bits to w 1-1, and so on, then store each newly calculated long-period nested eigenvalue into an array. W 2. Taking Jinghong Hydropower Plant as an example, the first element is updated every 60 seconds with long-period nested feature values ​​in the array. W 2. Always retain the 5 most recent long-period nested feature values.

[0109] S7300 performs an upper limit calculation on the oscillation characteristic values ​​of the monitored electrical quantities calculated by S2000, S3000, S4000, and S5000, including: S7310) settings include g Array of 1 element G 1, of which g 1 = 60; S7320) Every cycle time T 4. Take the maximum value of all elements in the array described in S7220, that is, calculate the single-cycle rolling characteristic value for Jinghong Power Plant every 60 seconds. δ, ε Take the maximum value; S7330) Every cycle time T 4. The array described in S7310 is... g Assigning 1-1 elements to the first element g 1 element, the first g Assigning 1-2 elements to the first g The process proceeds one element at a time until the first element is assigned to the second element. Finally, the maximum value obtained in step S7320 is assigned to the first element. In this embodiment, the Jinghong Power Plant updates the array described in step S7220 every 60 seconds. W1 The maximum value is used for rolling assignment, i.e., array. G 1. Store the most recent 60 single-cycle rolling feature values; S7340) settings include g Array of 2 elements G 2, of which g 2 = 12; S7350) every cycle time T 5. Take the maximum value of all elements of the array described in S7250, that is, take the maximum value of the long-period nested characteristic value calculated for Jinghong Power Plant every 300 seconds. S7360) Every cycle time T5. The array described in S7340 is... g 2-1 elements are assigned to the first element. g 2 elements, the first g Assigning 2-2 elements to the first g The process iterates through the array from 2 to 1 elements until the first element is assigned to the second element, and finally assigns the maximum value obtained in S7350 to the first element. In this embodiment, the Jinghong Power Plant updates the array described in S7340 every 300 seconds. W2 The maximum value is assigned in a rolling manner, that is, in the array G 2. Store the most recent 12 long-period nested feature values; (S7400) When an abnormal operating condition related to the monitored electrical quantity occurs, several elements of the array described in S7310 and S7340 are cleared to 0 until the operating condition returns to normal. That is, when an abnormal operating condition related to the monitored electrical quantity occurs at Jinghong Power Plant, the array described in S7310 and S7340 is cleared to 0 until the operating condition returns to normal. G 1 and G 2. Reset to zero.

[0110] S7500) every g 1× T The alarm threshold value for the single-cycle rolling characteristic value is corrected over a 4-cycle period, including: S7510) Take the maximum value of all elements in the array described in S7310, that is, take the maximum value of the array described in S7310 within 1 hour. G The maximum value of all elements that are 1; S7520 compares the maximum value taken by S7510 with the upper limit threshold data of the single-cycle rolling characteristic value under normal operating conditions set by S7100, including: (S7521) If the maximum value taken by S7510 is greater than the upper limit threshold data of the single-cycle rolling characteristic value under normal operating conditions set by S7100, then manual judgment is initiated to increase the upper limit threshold data, or the correction is skipped. Taking Jinghong Power Plant as an example, within 1 hour, the maximum values ​​of s2000 and s4000 taken by S7510 are 20 and 60 respectively, which are greater than the upper limit threshold data of the single-cycle rolling characteristic value under normal operating conditions set by S7100, which are 15 and 50. Then manual judgment is initiated to increase the upper limit threshold data of s2000 and s4000, or the correction is skipped. S7522) If the maximum value taken by S7510 is less than the upper limit threshold data of the single-cycle rolling characteristic value under normal operating conditions set by S7100, then proceed to the subsequent correction step. Taking Jinghong Power Plant as an example, within 1 hour, the maximum values ​​of s2000 and s4000 taken by S7510 are 10 and 40 respectively, which are less than the upper limit thresholds of 15 and 50, then proceed to the subsequent correction step. S7530) Initially, the lower limit threshold data of the single-cycle rolling characteristic value under normal operating conditions is set as the alarm threshold value using S7100. S7540 compares the maximum value taken by S7510 with the alarm threshold value, including: S7541) If the maximum value taken by S7510 is less than or equal to the alarm threshold value, then skip this correction. Taking Jinghong Power Plant as an example, the lower limit thresholds of s2000 and s4000 single-cycle rolling characteristic values ​​of 0.3 and 15 are used as alarm threshold values. If the maximum values ​​of s2000 and s4000 taken by S7510 are 0.2 and 10 respectively within 1 hour, which are less than the lower limit thresholds of 0.3 and 15, then skip this correction. (S7542) If the maximum value taken by S7510 is greater than the alarm threshold value, then the alarm threshold value is corrected to the maximum value taken by S7510. If the maximum values ​​of s2000 and s4000 taken by S7510 are 0.5 and 20 respectively within 1 hour, which are greater than the lower limit thresholds of 0.3 and 15, then the alarm threshold values ​​of s2000 and s4000 are corrected to 0.5 and 20 respectively.

[0111] S7600) every g 2× T The alarm threshold value for long-period nested feature values ​​is adjusted over a 5-cycle period, including: S7610) Take the maximum value of all elements in the array described in S7340, that is, take the maximum value of the array described in S7340 within 1 hour. G 2 is the maximum value of all elements; S7620 compares the maximum value taken by S7610 with the upper limit threshold data of the long-cycle nested characteristic value for normal operating conditions set by S7100, including: (S7621) If the maximum value taken by S7610 is greater than the upper limit threshold data of the long-cycle nested feature value under normal operating conditions set by S7100, then manual judgment is initiated to increase the upper limit threshold data, or this correction is skipped. Taking Jinghong Power Plant as an example, within 1 hour, the maximum values ​​of s3000 and s5000 taken by S7610 are 1800 and 1850 respectively, which are greater than the upper limit threshold data of the long-cycle nested feature value under normal operating conditions set by S7100 of 1700. Then manual judgment is initiated to increase the upper limit threshold data of s3000 and s5000, or this correction is skipped. S7622) If the maximum value taken by S7610 is less than the upper limit threshold data of normal operating conditions set by S7100, then proceed to the subsequent correction step. Taking Jinghong Power Plant as an example, within 1 hour, the maximum values ​​of s3000 and s5000 taken by S7610 are 1700 and 1750 respectively, which are less than the upper limit threshold of 1700, then proceed to the subsequent correction step. S7630) Initially, the lower limit threshold data of the long-cycle nested feature value under normal operating conditions is set as the alarm threshold value using S7100. S7640 compares the maximum value taken by S7610 with the alarm threshold value, including: (S7641) If the maximum value taken by S7610 is less than or equal to the alarm threshold value, then skip this correction. Taking Jinghong Power Plant as an example, the lower limit threshold of 1700 for the long-cycle nested characteristic values ​​of s3000 and s5000 is used as the alarm threshold value. If the maximum values ​​of s3000 and s5000 taken by S7610 are 4 and 150 respectively within 1 hour, which are less than the lower limit thresholds of 5 and 165, then skip this correction. (S7642) If the maximum value taken by S7610 is greater than the alarm threshold value, then the alarm threshold value is corrected to the maximum value taken by S7610. If, within one hour, the maximum values ​​of s3000 and s5000 taken by S7610 are 12 and 170 respectively, which are greater than the lower threshold values ​​of 5 and 165, then the alarm threshold values ​​of s3000 and s5000 are corrected to 12 and 170 respectively.

[0112] S8000 compares the oscillation characteristic value with the oscillation alarm threshold value and issues an alarm, including: S8100) At fixed intervals, the oscillation characteristic values ​​of the monitored electrical quantities calculated by S2000, S3000, S4000, and S5000 are taken. In this embodiment, the oscillation characteristic values ​​of the monitored electrical quantities calculated by S2000, S3000, S4000, and S5000 are taken every hour. (S8200) When the oscillation characteristic value obtained by S8100 is greater than or equal to the alarm threshold value obtained by S7500 or S7600, an oscillation alarm is triggered. (S8300) When the oscillation characteristic value obtained by S8100 is less than the alarm threshold value obtained by S7500 or S7600, the oscillation alarm will not be triggered.

[0113] Figure 20 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. For example, the electronic device 800 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0114] Reference Figure 20 The electronic device 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input / output (I / O) interface 812, sensor component 814, and communication component 816.

[0115] Processing component 802 typically controls the overall operation of electronic device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0116] Memory 804 is configured to store various types of data to support the operation of electronic device 800. Examples of such data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, pictures, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0117] Power component 806 provides power to various components of electronic device 800. Power component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 800.

[0118] Multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0119] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when electronic device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0120] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0121] Sensor assembly 814 includes one or more sensors for providing state assessments of various aspects of electronic device 800. For example, sensor assembly 814 can detect the on / off state of electronic device 800, the relative positioning of components such as the display and keypad of electronic device 800, changes in position of electronic device 800 or a component of electronic device 800, the presence or absence of user contact with electronic device 800, orientation or acceleration / deceleration of electronic device 800, and temperature changes of electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0122] Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices. Electronic device 800 can access wireless networks based on communication standards, such as WiFi, 4G, or 5G, or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0123] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0124] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, which can be executed by a processor 820 of an electronic device 800 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0125] To implement the above embodiments, this application also proposes a chip, including: the chip includes a processing circuit configured to perform the methods provided in the foregoing embodiments.

[0126] Figure 21 This is a schematic diagram of the structure of a chip according to an embodiment of this application. See also... Figure 21 The diagram shown is a schematic representation of the structure of chip 1100, but it is not limited to this.

[0127] Chip 1100 includes processing circuitry 1101, which is configured to perform any of the above methods.

[0128] In some embodiments, chip 1100 further includes one or more interface circuits 1102. Optionally, the interface circuit 1102 is connected to memory 1103, and the interface circuit 1102 can be used to receive signals from memory 1103 or other devices, and the interface circuit 1102 can be used to send signals to memory 1103 or other devices. For example, the interface circuit 1102 can read instructions stored in memory 1103 and send the instructions to processing circuit 1101.

[0129] In some embodiments, the interface circuit 1102 performs at least one of the communication steps such as sending and / or receiving in the above method, while the processing circuit 1101 performs other steps.

[0130] In some embodiments, the terms interface circuit, interface, transceiver pin, transceiver, etc., can be used interchangeably.

[0131] In some embodiments, chip 1100 further includes one or more memories 1103 for storing instructions. Optionally, all or part of the memories 1103 may be located outside of chip 1100.

[0132] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0133] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0134] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0135] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0136] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0137] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it includes one or a combination of the steps of the method embodiments.

[0138] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0139] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A novel method for monitoring oscillations of key electrical quantities in a power system, characterized in that, include: Select the electrical measurement point to be monitored, obtain the monitored electrical quantities collected by the electrical measurement point, and set the period time parameters related to oscillation monitoring; The oscillation characteristic value is calculated based on the monitored electrical quantity and the cycle time parameter, wherein the oscillation characteristic value includes: a single-cycle rolling characteristic value based on the reciprocating motion mileage, a long-cycle nested characteristic value based on the reciprocating motion mileage, a single-cycle rolling characteristic value based on the oscillation waveform area, and a long-cycle nested characteristic value based on the oscillation waveform area. The oscillation alarm threshold value is adjusted based on the oscillation characteristic value; Based on the oscillation characteristic value and the oscillation alarm threshold value, determine whether abnormal oscillation has occurred and issue an oscillation warning.

2. The method according to claim 1, characterized in that, The monitored electrical quantities include: active power, reactive power, voltage, and frequency. The set period time parameters related to oscillation monitoring include: Set the time length of the sampling refresh cycle for the monitored electrical quantities; A first time length is set as the cycle time length for a single-cycle roll, and the first time length is an integer multiple of the sampling refresh cycle; A second time length is set as the sub-cycle time length of a long-cycle nesting, and the second time length is an integer multiple of the sampling refresh cycle; A third time length is set as the parent period length of the long-period nesting, and the third time length is an integer multiple of the second time length.

3. The method according to claim 2, characterized in that, The calculation of the oscillation characteristic value based on the monitored electrical quantity and the periodic time parameter includes: Within the first period corresponding to the first time length, determine the change value of the monitored electrical quantity between each sampling refresh period and the adjacent sampling refresh period; Within the first cycle, the sum of the absolute values ​​of the changes in the monitored electrical quantities corresponding to all sampling refresh cycles, minus the absolute value of the algebraic sum of the changes in the monitored electrical quantities corresponding to all sampling refresh cycles, is taken as the single-cycle rolling characteristic value based on the reciprocating motion mileage.

4. The method according to claim 2, characterized in that, The calculation of the oscillation characteristic value based on the monitored electrical quantity and the periodic time parameter includes: Within the second period corresponding to the second time length, the sampled values ​​of the monitored electrical quantities in each sampling refresh period and the changes in the monitored electrical quantities between each sampling refresh period and adjacent sampling refresh periods are determined. Within the second cycle, the sum of the absolute values ​​of the monitored electrical quantity samples corresponding to all sampling refresh cycles is subtracted from the algebraic sum of the monitored electrical quantity samples corresponding to all sampling refresh cycles, and this sum is used as the first sub-feature value. Within the second cycle, the change value of the monitored electrical quantity corresponding to the last sampling refresh cycle is subtracted from the change value of the monitored electrical quantity corresponding to the first sampling refresh cycle, and this is used as the second sub-feature value. Within the third period corresponding to the third time length, the first sub-feature values ​​corresponding to each second period are added together to obtain the third sub-feature value; wherein, the third period corresponding to the third time length includes multiple second periods; Within the third period, the absolute values ​​of the second sub-feature values ​​corresponding to each second period are added together, and the algebraic sum of the second sub-feature values ​​corresponding to each second period is subtracted to obtain the fourth sub-feature value. The third sub-feature value is added to the fourth sub-feature value to obtain the long-period nested feature value based on the reciprocating motion mileage.

5. The method according to claim 2, characterized in that, The calculation of the oscillation characteristic value based on the monitored electrical quantity and the periodic time parameter includes: Within the first period corresponding to the first time length, determine the maximum and minimum values ​​of the monitored electrical quantity, and take multiple intermediate values ​​from the values ​​between the maximum and minimum values; Using the maximum value, minimum value, or any intermediate value as the integration cross-section, calculate the integration area of ​​the integration cross-section with all other integration cross-sections, and use the minimum value of the integration area as the area of ​​the first oscillation waveform corresponding to the integration cross-section. The minimum value of the area of ​​the first oscillating waveform is taken as the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform.

6. The method according to claim 2, characterized in that, The calculation of the oscillation characteristic value based on the monitored electrical quantity and the periodic time parameter includes: Within the first period corresponding to the first time length, determine the maximum and minimum values ​​of the monitored electrical quantity, and take multiple intermediate values ​​from the values ​​between the maximum and minimum values; The maximum, minimum, and average values ​​are respectively used as integration cross-sections. The integration area of ​​the integration cross-section with all other integration cross-sections is calculated. The minimum value of the integration area is used as the area of ​​the first oscillation waveform corresponding to the integration cross-section. The minimum value of the area of ​​the first oscillating waveform is taken as the single-cycle rolling characteristic value based on the area of ​​the oscillating waveform.

7. The method according to claim 2, characterized in that, The calculation of the oscillation characteristic value based on the monitored electrical quantity and the periodic time parameter includes: Within the second period corresponding to the second time length, determine the monitored electrical quantities for each sampling refresh cycle; Determine the maximum, minimum, and multiple intermediate values ​​of the monitored electrical quantity in each sampling refresh cycle of the second cycle; Using the intermediate value as the integration section line, calculate the integrated area of ​​the integration section line with all other integration section lines. A set of second oscillation waveform areas and integral cross-sections corresponding to a target number of second periods is determined, wherein each second period in the set is a group; the long-period nested feature value based on the oscillation waveform area is determined according to the frequency of occurrence of the value of each integral cross-section in the set; wherein the target number is an integer multiple of the third time length to the second time length.

8. The method according to claim 7, characterized in that, The determination of the long-period nested characteristic value based on the area of ​​the oscillating waveform according to the frequency of occurrence of the values ​​of each integral cross-section line in the set includes any one of the following: In response to the fact that the frequency of occurrence of the value of only one integral cross section line in all groups of the set is equal to the target number, the integral cross section line is determined as the target integral cross section line, and the value of the target integral cross section line is accumulated in the second oscillation waveform area corresponding to each second period to obtain the long-period nested feature value based on the oscillation waveform area; In response to the fact that the frequency of occurrence of the values ​​of at least two of the integral cross-sections in all groups of the set is equal to the target number, these integral cross-sections are determined as the target integral cross-sections. For each target integral cross-section, the second oscillation waveform surface corresponding to the target integral cross-section in each second period is accumulated to obtain multiple accumulated values. The minimum value among the accumulated values ​​is taken as the long-period nested feature value based on the oscillation waveform area. In response to the fact that the frequency of occurrence of the value of the integral cross section line in all groups of the set is less than the target number, the set is regrouped.

9. The method according to any one of claims 1-8, characterized in that, The step of adjusting the oscillation alarm threshold value based on the oscillation characteristic value includes: The single-cycle rolling feature value based on the reciprocating motion mileage and the single-cycle rolling feature value based on the oscillation waveform area are stored. At the end of the first storage period, the maximum value of the single-cycle rolling feature value based on the reciprocating motion mileage and the maximum value of the single-cycle rolling feature value based on the oscillation waveform area are recorded. The duration of the first storage period is an integer multiple of the sampling refresh period. The long-cycle nested feature values ​​based on reciprocating motion mileage and the long-cycle nested feature values ​​based on oscillating waveform area are stored. At the end of the second storage period, the maximum value among the long-cycle nested feature values ​​based on reciprocating motion mileage and the maximum value among the long-cycle nested feature values ​​based on oscillating waveform area are recorded. The time length of the second storage period is an integer multiple of the time length of the long-cycle nested sub-cycles. The oscillation alarm threshold value corresponding to each of the oscillation feature values ​​is determined based on the maximum value among the single-cycle rolling feature values ​​based on the reciprocating motion mileage, the maximum value among the single-cycle rolling feature values ​​based on the oscillation waveform area, the maximum value among the long-cycle nested feature values ​​based on the reciprocating motion mileage, and the maximum value among the long-cycle nested feature values ​​based on the oscillation waveform area.

10. The method according to claim 9, characterized in that, The step of determining the oscillation alarm threshold value based on the maximum value among the single-cycle rolling feature values ​​based on the reciprocating motion mileage, the maximum value among the single-cycle rolling feature values ​​based on the oscillation waveform area, the maximum value among the long-cycle nested feature values ​​based on the reciprocating motion mileage, and the maximum value among the long-cycle nested feature values ​​based on the oscillation waveform area includes: The maximum value among the single-cycle rolling feature values ​​based on reciprocating motion mileage and the maximum value among the single-cycle rolling feature values ​​based on the area of ​​the oscillation waveform are stored in each first storage cycle. At the end of the first threshold value update cycle, the maximum value among the single-cycle rolling feature values ​​based on reciprocating motion mileage and the maximum value among the single-cycle rolling feature values ​​based on the area of ​​the oscillation waveform corresponding to each first storage cycle is used as the first candidate alarm threshold value. The time length of the first threshold value update cycle is an integer multiple of the first storage cycle. The first candidate alarm threshold value is used to determine the first oscillation alarm threshold value. In response to the candidate alarm threshold value being higher than a preset first upper limit threshold, the first upper limit threshold is increased, or the correction is skipped; or, in response to the candidate alarm threshold value being lower than or equal to the first upper limit threshold, the lower limit threshold data of the single-cycle rolling characteristic value under normal operating conditions is used as the first oscillation alarm threshold value. If the candidate alarm threshold value is less than the first oscillation alarm threshold value, the correction is skipped. If the candidate alarm threshold value is greater than or equal to the first oscillation alarm threshold value, the first oscillation alarm threshold value is corrected to the candidate alarm threshold value.

11. The method according to claim 9, characterized in that, The step of determining the oscillation alarm threshold value based on the maximum value among the single-cycle rolling feature values ​​based on the reciprocating motion mileage, the maximum value among the single-cycle rolling feature values ​​based on the oscillation waveform area, the maximum value among the long-cycle nested feature values ​​based on the reciprocating motion mileage, and the maximum value among the long-cycle nested feature values ​​based on the oscillation waveform area includes: The maximum value among the long-period nested feature values ​​based on reciprocating motion mileage and the maximum value among the long-period nested feature values ​​based on the area of ​​oscillation waveforms are stored in each second storage cycle. At the end of the second threshold value update cycle, the maximum value among the long-period nested feature values ​​based on reciprocating motion mileage and the maximum value among the long-period nested feature values ​​based on the area of ​​oscillation waveforms corresponding to each second storage cycle is used as the second candidate alarm threshold value. The time length of the second threshold value update cycle is an integer multiple of the second storage cycle. The second candidate alarm threshold value is used to determine the second oscillation alarm threshold value. In response to the candidate alarm threshold value being higher than a preset second upper limit threshold, the second upper limit threshold is increased, or the correction is skipped; or, in response to the candidate alarm threshold value being lower than or equal to the second upper limit threshold, the lower limit threshold data of the long-cycle nested feature value under normal operating conditions is used as the second oscillation alarm threshold value. If the candidate alarm threshold value is less than the second oscillation alarm threshold value, the correction is skipped; if the candidate alarm threshold value is greater than or equal to the second oscillation alarm threshold value, the second oscillation alarm threshold value is corrected to the candidate alarm threshold value.

12. The method according to claim 10 or 11, characterized in that, The step of determining whether abnormal oscillation has occurred and issuing an oscillation warning based on the oscillation characteristic value and the oscillation alarm threshold value includes any one of the following: When the oscillation characteristic value is greater than or equal to the oscillation alarm threshold value, an abnormal oscillation is determined to have occurred, and an alarm is triggered. In response to the oscillation characteristic value being less than the oscillation alarm threshold value, it is determined that no abnormal oscillation has occurred.

13. A novel power system key electrical quantity oscillation monitoring device, characterized in that, include: The acquisition module is used to select the electrical measurement points to be monitored, acquire the monitored electrical quantities collected by the electrical measurement points, and set the period time parameters related to oscillation monitoring. The feature determination module is used to calculate oscillation feature values ​​based on the monitored electrical quantity and the cycle time parameter, wherein the oscillation feature values ​​include: single-cycle rolling feature values ​​based on reciprocating motion mileage, long-cycle nested feature values ​​based on reciprocating motion mileage, single-cycle rolling feature values ​​based on the area of ​​the oscillation waveform, and long-cycle nested feature values ​​based on the area of ​​the oscillation waveform. The threshold setting module is used to set the oscillation alarm threshold value based on the oscillation characteristic value; The early warning module is used to determine whether abnormal oscillation has occurred and to issue an oscillation early warning based on the oscillation characteristic value and the oscillation alarm threshold value.

14. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the method as described in any one of the preceding claims 1-12.

15. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of the preceding claims 1-12.

16. A chip, characterized in that, The chip includes processing circuitry configured to perform the method described in any one of claims 1-12.

17. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the method as described in any one of claims 1-12.

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