Online monitoring and dynamic performance evaluation method, system and equipment for excitation operation state of hydroelectric generating set and medium

Abstract

The invention discloses an on-line monitoring and dynamic performance evaluation method, system, equipment and medium for the excitation operation state of a hydroelectric generating set, and relates to the field of dynamic monitoring of an electric power system.The method comprises the steps that operation data of an excitation system of the generating set is collected, whether the generating set is offline or not is judged, and the input rate of a PSS and the input rate of an AVR are counted; based on the collected data, monitoring and analyzing the electrical quantity of the unit, and judging the current operation state of the system through a preset threshold value; calculating the average damping ratio of the active power disturbance response curve to judge the PSS suppression effect; evaluating the limited action of the excitation regulator, and judging whether the excitation regulator has the phenomena of maloperation and refusal to act or not; and calculating state parameters of the excitation system based on the current operation state of the system, the PSS suppression effect and the misoperation and rejection phenomenon, and determining the performance level of the excitation system. According to the invention, full-period, full-scene and full-structure coverage type monitoring and analysis of the operation state and performance of the excitation system of the hydroelectric generating set are realized, and the monitoring accuracy and real-time performance are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of dynamic monitoring of power systems, and in particular to a method, system, equipment, and medium for online monitoring and dynamic performance evaluation of the excitation operation status of hydropower units. Background Technology

[0002] In power systems, hydropower units, as important power generation equipment, rely heavily on their excitation systems for stable operation and reliable power output. With the continuous expansion of power system scale and increasingly stringent requirements for power supply stability, the operational status of hydropower unit excitation systems directly impacts the safety and reliability of the entire power system.

[0003] Traditional monitoring methods for hydropower unit excitation systems are relatively simple, relying mostly on regular manual inspections and basic instrument measurements. This approach is not only inefficient but also fails to provide real-time and comprehensive operational information about the excitation system. When the excitation system malfunctions or deteriorates, it is difficult to detect and take effective measures in a timely manner, potentially leading to serious consequences such as unit shutdowns and power supply interruptions, posing a significant threat to the stable operation of the power system. Furthermore, existing excitation system performance evaluation methods lack systematicity and scientific rigor, making it difficult to accurately assess the dynamic performance of the excitation system under different operating conditions and failing to provide strong support for equipment maintenance, upgrades, and optimization. Therefore, developing an efficient and accurate online monitoring and dynamic performance evaluation method and device for hydropower unit excitation systems is of significant practical importance. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the problem that this invention aims to solve is that traditional monitoring methods for hydropower unit excitation systems are relatively simple, mostly relying on manual periodic inspections and simple instrument measurements. This method is not only inefficient, but also unable to obtain real-time and comprehensive operating information of the excitation system.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: an online monitoring and dynamic performance evaluation method for the excitation operating status of a hydropower unit, comprising: collecting operating data of the hydropower unit's excitation system; determining whether the unit is disconnected from the grid; and statistically analyzing the engagement rates of the excitation regulator PSS and the automatic voltage regulator AVR; based on the collected data, monitoring and analyzing the unit's electrical quantities; determining the current operating status of the system through preset thresholds; calculating the average damping ratio of the active power disturbance response curve to determine the PSS suppression effect; evaluating the limiting actions of the excitation regulator to determine whether the excitation regulator exhibits maloperation or failure to operate; and calculating the excitation system state parameters based on the current operating status of the system, the PSS suppression effect, and the maloperation or failure to operate phenomena to determine the excitation system performance level.

[0007] As a preferred embodiment of the online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit as described in this invention, the operating data of the hydropower unit excitation system includes the positive sequence voltage amplitude, the main excitation voltage amplitude, and the main excitation current amplitude; based on the collected data, the peak voltage multiple, peak current multiple, voltage response time, and damping ratio are calculated.

[0008] As a preferred embodiment of the online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit as described in this invention, the following steps are included: determining whether the unit is disconnected from the grid includes: if the unit's active power output is less than a set grid-connected power threshold and the duration meets a first set time, the unit is disconnected from the grid, triggering a fault alarm; otherwise, it is connected to the grid. The step of calculating the engagement rate of the excitation regulator PSS and the automatic voltage regulator AVR includes: if the unit's active power is above the unit's stable combustion load and the PSS activation / deactivation signal is 0 within a set duration, the unit's PSS is deactivated, triggering a fault alarm; otherwise, the PSS is considered activated. When the unit has not reached the lower limit of the stable combustion load, the PSS is defaulted to being activated. After the unit is connected to the grid, if the AVR activation / deactivation signal is 0 and the duration meets a second set time, the AVR is determined to be deactivated; otherwise, the AVR is activated.

[0009] As a preferred embodiment of the online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit as described in this invention, the following steps are included: monitoring and analyzing the electrical quantities of the unit, based on the equivalent diagram of normal generator operation, analyzing the active power output and maximum stable active power output of the generator under different excitation modes, and obtaining the effect of the automatic operation mode of the excitation system on the generator performance and system stability; determining the current operating status of the system through a preset threshold, including monitoring and analyzing relevant data of the power plant generator unit through a preset threshold, displaying the monitoring data and waveforms in real time, and immediately issuing a fault alarm and storing the data once an abnormality is detected.

[0010] As a preferred embodiment of the online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit as described in this invention, the method for judging the PSS suppression effect includes: when the PSS output voltage is greater than a certain value, determining that a low-frequency oscillation has occurred and storing the relevant waveform; calculating the average damping ratio of the active power disturbance response curve; judging the PSS suppression effect by comparing it with the suppression threshold; and when the effect is judged to be poor, triggering a fault alarm and correcting the parameters.

[0011] As a preferred embodiment of the online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit as described in this invention, the method for determining whether the excitation regulator has malfunctions or failures to operate includes: performing model calculations based on the collected generator unit data and the unit's internal protection mechanism and limiting logic, comparing the results with the actual protection and limiting action switching quantities, and determining whether the excitation regulator has malfunctions or failures to operate.

[0012] As a preferred embodiment of the online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit as described in this invention, the method for determining the performance level of the excitation system includes: introducing the number of excitation system faults as an influencing factor, correcting the severity of the faults, and setting corresponding correction coefficients ω according to different ranges of the number of fault occurrences; the number of excitation system faults is the number of times an alarm is triggered during excitation system monitoring; calculating the generator unit excitation system state parameter S based on the sum of the product of the information score of each fault alarm corresponding item and the correction coefficient, and determining the excitation system performance level based on S.

[0013] To address the aforementioned technical problems, this invention provides the following technical solution: a system for online monitoring and dynamic performance evaluation of the excitation operating status of a hydropower unit, comprising: a unit grid connection status judgment module, an excitation system operating status monitoring module, and an excitation system performance level determination module; the unit grid connection status judgment module is used to collect operating data of the hydropower unit's excitation system, determine whether the unit is disconnected from the grid, and statistically analyze the engagement rate of the excitation regulator PSS and the automatic voltage regulator AVR; the excitation system operating status monitoring module, based on the collected data, monitors and analyzes the unit's electrical quantities, determines the current operating status of the system through preset thresholds, calculates the average damping ratio of the active power disturbance response curve to determine the PSS suppression effect, evaluates the excitation regulator's limiting action, and determines whether the excitation regulator exhibits maloperation or failure to operate; the excitation system performance level determination module calculates excitation system state parameters based on the current system operating status, the PSS suppression effect, and the maloperation or failure to operate phenomena, and determines the excitation system performance level.

[0014] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit as described above.

[0015] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the online monitoring and dynamic performance evaluation method for the excitation operating status of a hydropower unit as described above.

[0016] The beneficial effects of this invention are as follows: By monitoring the working status data in real time, this invention deeply analyzes the active power output and maximum stable active power output of the generator under different excitation modes, clarifies the role of the excitation system operation mode on the generator performance and system stability, quantifies its status, accurately judges the health status and performance degradation of the equipment, and provides a basis for maintenance decisions. It realizes full-cycle, full-scenario, and full-structure coverage monitoring and analysis of the operating status and performance of the hydropower unit excitation system, which greatly improves the accuracy and real-time performance of monitoring. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of an online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit, as described in Example 1.

[0019] Figure 2 This is an equivalent diagram of the generator's normal operation in the online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit in Example 1.

[0020] Figure 3 This is a logic diagram for judging the correctness of low excitation limiting action in an online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit in Example 1. Detailed Implementation

[0021] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] Example 1, referring to Figures 1-3 This is the first embodiment of the present invention, which provides a method for online monitoring and dynamic performance evaluation of the excitation operation status of a hydropower unit, including, as follows: Figure 1 As shown:

[0024] Step 1: Collect operating data of the hydropower unit's excitation system, determine whether the unit is disconnected from the grid, and calculate the engagement rate of the excitation regulator PSS and the automatic voltage regulator AVR.

[0025] The operating data of the hydropower unit excitation system includes the positive sequence voltage amplitude, the main excitation voltage amplitude, and the main excitation current amplitude.

[0026] Based on the collected data, the peak voltage multiple, peak current multiple, voltage response time, and damping ratio were calculated.

[0027] Specifically, a large hydropower plant was selected as the subject of this example. This plant has multiple hydropower generating units of different models, undertaking important power supply tasks. In the generator excitation event detection process, established detection standards and procedures were strictly followed. Taking one of the units with a rated power of 100MW as an example, high-precision sensors and data acquisition equipment were used to ensure the accuracy and real-time performance of the data when monitoring the positive sequence voltage amplitude, the main excitation voltage amplitude, and the main excitation current amplitude.

[0028] When determining data validity, if the positive sequence voltage in the first 2 seconds of the calculation window is less than 0.2 times the rated voltage, the system automatically marks and discards that data segment. For example, in a monitoring session, if the positive sequence voltage in the first 2 seconds of the calculation window is 0.15 times the rated voltage, the system immediately determines the data is abnormal and does not participate in subsequent calculations. For voltage mutation detection, when calculating the voltage change in the 3rd second of the statistical window, if the difference between the maximum and minimum values ​​is greater than 0.02 times the rated voltage, a mutation is identified. Assuming the rated voltage of the unit is U, at a certain moment, the maximum voltage value in the 3rd second of the window is U1, and the minimum value is U2. After calculation, U1-U2>0.02U, the system determines that a mutation has occurred and quickly starts relevant algorithms to calculate indicators such as the peak voltage multiple, peak current multiple, voltage response time, and damping ratio.

[0029] To further clarify, regarding the detection of unit grid disconnection and connection, the grid-connected power threshold is set at 0.1MW for a duration of 5 seconds. When the unit's active power output is less than 0.1MW for 5 seconds, the system determines that the unit is disconnected from the grid; otherwise, it is determined to be connected to the grid. If, within a certain time period, the unit's active power output remains below 0.1MW for 5 seconds, the system accurately identifies the unit's grid disconnection status and records the relevant time information.

[0030] For PSS (Power Supply Service) activation / deactivation judgment, the stable load is set at 0.3MW. When the unit's active power is above 0.3MW and the PSS activation / deactivation signal is 0 for 300 seconds, the PSS is considered deactivated; otherwise, the PSS is activated. When the unit's load has not reached 0.3MW, the PSS is assumed to be activated. For example, during a gradual increase in unit load, when the active power reaches 0.35MW and the PSS activation / deactivation signal is 0 for 300 seconds, the system determines that the PSS is deactivated and records the relevant data.

[0031] The AVR activation / deactivation determination is performed after the unit is connected to the grid. When the AVR activation / deactivation signal is 0 and remains so for 300 seconds, the AVR is determined to be deactivated; otherwise, the AVR is activated. During unit grid-connected operation, if the AVR activation / deactivation signal changes to 0 and remains so for 300 seconds, the system promptly detects this change, determines that the AVR is deactivated, and stores the relevant information in the database.

[0032] Phantom Measurement Unit (PMU) fault detection is achieved by monitoring the number and validity of real-time data. A PMU fault is determined when the number of real-time data reads is zero, or when all data are invalid for more than 60 seconds. If the unit was offline or PSS (Power Supply Service) deactivated before the PMU fault, the program automatically continues the previous state. In one monitoring instance, if a PMU communication failure caused a real-time data interruption for more than 60 seconds, the system determined a PMU fault and retained the unit's previous offline state record.

[0033] The operational rates of the PSS and AVR for each generating unit are statistically analyzed monthly. Assuming the unit's monthly grid-connected time is 200 hours, the monthly PSS de-connection time is 10 hours, and the allowed monthly PSS de-connection time is 5 hours, the PSS operational rate is calculated as follows: PSS operational rate = (Monthly grid-connected time - Monthly PSS de-connection time + Monthly allowed PSS de-connection time) / Monthly grid-connected time * 100%, resulting in a PSS operational rate of (200 - 10 + 5) / 200 * 100% = 97.5%. If the monthly AVR de-connection time is 8 hours, the AVR operational rate is calculated as follows: AVR operational rate = (Monthly grid-connected time - Monthly AVR de-connection time) / Monthly grid-connected time * 100%, resulting in an AVR operational rate of (200 - 8) / 200 * 100% = 96%. These data provide important information for evaluating the operational stability of the PSS and AVR.

[0034] Step 2: Based on the collected data, monitor and analyze the electrical quantities of the unit, and determine the current operating status of the system by setting preset thresholds.

[0035] Monitoring and analyzing the electrical quantities of the generator unit includes analyzing the generator's active power output and maximum stable active power output under different excitation modes based on the generator's normal operation equivalent diagram, and obtaining the effect of the automatic operation mode of the excitation system on generator performance and system stability.

[0036] Specifically, the equivalent diagram of normal generator operation is as follows: Figure 2 As shown. When the excitation system operates in "automatic mode," it effectively maintains a constant generator terminal voltage, i.e., U. t If the active power output of the generator is constant, then the formula for P is... e Represented as:

[0037]

[0038] Where δ is the generator power angle, i.e., Ut With generator excitation current E q The angle between the two sides, where U is the system voltage and X is the angle between the two sides. t X1 is the transformer short-circuit reactance, and X2 is the line reactance. When δ = 90°, the maximum stable output active power of the generator in "automatic mode" operation is...

[0039]

[0040] Taking the aforementioned hydropower plant unit as an example, based on the PMU data upload cycle (set to 1 second), remote measurements such as generator terminal voltage, generator terminal current, generator frequency, excitation voltage, excitation current, generator active power, and generator reactive power are continuously collected.

[0041] In analog quantity calculation, the terminal voltage (stator voltage) U is used as an example. t For example, the voltage signal acquired by the sensor, after signal conditioning and analog-to-digital conversion, enters the system for calculation. Assume the acquired raw voltage signal is U. raw After specific calibration and calculation methods, U is obtained. t The specific results. Similarly, for the terminal current (stator current) I... t Generator frequency F r Generator active power P e Generator reactive power Q e Excitation current I f Precise calculations are performed on parameters such as these.

[0042] In another alternative embodiment, if the excitation system is operated in "manual mode" (non-automatic mode), it effectively maintains a constant generator excitation current, i.e., E. q The output power of the generator is constant. Therefore, the formula for the generator's active power output is:

[0043]

[0044] Among them, X d The generator's direct-axis reactance; the generator's maximum stable output active power P under "manual mode" operation. emax2 Represented as,

[0045]

[0046] From the calculation results of the two sets of formulas above, it can be seen that P emax1 >P emax2 .

[0047] Therefore, when a generator is connected to the grid, engaging the excitation regulator in automatic mode can effectively improve the generator's active power output stability limit. When the generator excitation system operates in automatic mode, the terminal voltage drops due to increased power and a larger power angle. Through the regulation of "automatic mode," the excitation current increases, and the proportional electromotive force E increases accordingly. q It will continuously increase, maintaining a constant generator voltage. When E q When the increase of δ is greater than the decrease of sinδ, the generator can remain stable and the maximum active power also increases when δ>90°.

[0048] Determining the current operating status of the system by setting preset thresholds includes monitoring and analyzing relevant data of the power plant generator set based on preset thresholds, displaying the monitoring data and waveforms in real time, and immediately issuing fault alarms and storing data once an abnormality is detected.

[0049] During electrical quantity monitoring and analysis, a series of preset thresholds are used to determine the system's operating status. When the generator terminal voltage exceeds the preset upper limit (e.g., 1.1 times the rated voltage) or falls below the preset lower limit (e.g., 0.9 times the rated voltage), a generator terminal voltage over-limit alarm is triggered. Assume the unit's rated voltage is U. n When the terminal voltage U t >1.1Un or U t <0.9U n Upon failure, the system immediately issues a terminal voltage over-limit alarm signal and records information such as fault time, fault list (terminal voltage Ut over-limit alarm), and number of faults. Simultaneously, it stores data curves for terminal voltage, terminal current, excitation voltage, excitation current, generator frequency, active power, and reactive power for 4 seconds before and 16 seconds after the fault, facilitating further in-depth analysis of the fault cause.

[0050] At a certain moment, the terminal voltage reaches 1.15 times the rated voltage. The system responds quickly, issuing a terminal voltage over-limit alarm, recording detailed fault-related information, and storing various data curves for the corresponding time period. Staff can view this data through the system interface to analyze the cause of the fault, such as whether it was due to sudden load changes, excitation system abnormalities, or other factors leading to the abnormal increase in terminal voltage.

[0051] Step 3: Calculate the average damping ratio of the active power disturbance response curve to determine the PSS suppression effect.

[0052] When the PSS output voltage is greater than a set value, it is determined that a low-frequency oscillation has occurred and the relevant waveform is stored. The average damping ratio of the active power disturbance response curve is calculated and compared with the suppression threshold to determine the PSS suppression effect. If the effect is poor, a fault alarm is triggered and the parameters are corrected.

[0053] Specifically, during the operation of this hydropower plant, active power and PSS output voltage Urpss are continuously monitored. When the PSS output voltage Urpss exceeds a set value (e.g., 0.5V), low-frequency oscillation is detected. At this time, the system immediately starts the data storage program to store relevant waveforms such as terminal voltage, excitation current, active power, and reactive power.

[0054] Taking a low-frequency oscillation event as an example, assume that during the low-frequency oscillation process, the first power peak P1 is 100MW, the second power peak P2 is 90MW, and the 2N+1th power peak P... 2N+1 It is 85MW, the 2N+2nd power peak P 2N+2 The value is 80MW. The average damping ratio ξ, calculated using the formula for the active power disturbance response curve, is expressed as follows:

[0055]

[0056] Where N is the number of calculation cycles. Assuming N = 1 here, substituting the data yields:

[0057]

[0058] The calculated average damping ratio was 0.08, which is less than the preset threshold of 0.1, indicating that the PSS (Power Suppressor) is not effective in suppressing low-frequency oscillations. The system promptly issued an alarm, prompting staff to correct the PSS parameters. Based on the alarm information and relevant data provided by the system, staff analyzed whether the PSS parameter settings were reasonable, such as whether parameters like the time constant and gain of the lead / lag elements needed adjustment to improve the PSS's ability to suppress low-frequency oscillations.

[0059] After adjusting the PSS parameters, the system operation was continuously monitored. If low-frequency oscillations occurred again, the average damping ratio was recalculated to evaluate the suppression effect of the adjusted PSS. Assuming that after parameter adjustment, the calculated average damping ratio increased to 0.12 in the new low-frequency oscillation event, which is greater than the preset threshold of 0.1, it indicates that the PSS suppression effect on low-frequency oscillations has been significantly improved, and the system's operational stability has been enhanced.

[0060] Step 4: Evaluate the limiting action of the excitation regulator to determine whether the excitation regulator has any malfunctions or failures to operate.

[0061] Based on the collected generator set data and the internal protection mechanism and limiting logic of the generator set, model calculations are performed and compared with the actual protection and limiting action switching quantities to determine whether the excitation regulator has malfunctions or fails to operate.

[0062] Specifically, such as Figure 3As shown, in evaluating the limiting action of the excitation regulator, the correctness of the low-excitation action can be assessed. The critical value of reactive power on the low-excitation limiting curve is calculated based on active and reactive power. Assume that at a certain moment, the active power is filtered by a value P at 0.1s. e01 Given a reactive power limit of 0.5MW, the critical reactive power value Q is calculated based on the parameters of the low excitation limit curve (active power intersection points P1-P5, reactive power intersection points Q1-Q5). e The critical value is -0.3 Mvar. At this point, the reactive power 0.1s filter value Q e01 =-0.4Mvar, satisfying Q e01 ≤Q e The critical point, or low excitation limit condition, is determined by the WAMS system if it does not issue a low excitation limit alarm signal. If so, the system will determine that the low excitation limit operation is abnormal and issue an alarm. Based on this alarm information, personnel can check whether the low excitation limit logic of the excitation regulator and related equipment are functioning correctly.

[0063] In another alternative embodiment, evaluating the excitation regulator's limiting action can also involve assessing the correctness of the forced excitation action, when the excitation current I... f When the calorific value exceeds 1.1 PU, forced excitation inverse time calculation begins. The forced excitation limit condition is met when the actual calorific value exceeds the rated calorific value. If the forced excitation limit alarm signal from the WAMS system is inconsistent with the calculation result, it is determined that the forced excitation limit action is abnormal, and the system issues an alarm. For example, during a forced excitation process, if the calculated actual calorific value exceeds the rated calorific value, but the WAMS system does not issue a forced excitation limit alarm signal, the system will immediately issue a "forced excitation limit action abnormal" alarm, prompting personnel to check the forced excitation limit related equipment and logic.

[0064] In another alternative embodiment, evaluating the excitation regulator's limiting action can also involve assessing the correctness of the volt-hertz action by calculating U. t / F r The difference between the magnetic flux density M2 and the rated magnetic flux density M1 is calculated, and the difference is integrated. When the integral sum is greater than (M2-M1)*C2*25 (program cycle is 40ms), or U... t / F r If the M2 state persists for more than 2 seconds, the volt-hertz limit condition is met. If the volt-hertz limit alarm signal of the WAMS system is inconsistent with the calculation result, it is determined that "the volt-hertz limit action is abnormal", and the system issues an alarm.

[0065] The accuracy of stator current overload limiting operation is assessed using a specific formula. Assume the stator operating time limit I... tt Action value I tx According to the formula:

[0066]

[0067] Where T is the performance indicator; when the calculated result T meets the relevant conditions, it is determined whether the stator current overload limiting action is correct. If it is inconsistent with the actual stator current overload limiting action signal, it is determined that "the stator current overload limiting action is abnormal", and the system issues an alarm.

[0068] Step 5: Calculate the excitation system state parameters based on the current operating status of the system, the PSS suppression effect, and the maloperation and nonoperation phenomena, and determine the excitation system performance level.

[0069] The number of excitation system faults is introduced as an influencing factor to correct the severity of the faults. A corresponding correction coefficient ω is set according to the different ranges of the number of fault occurrences. The number of excitation system fault occurrences is the number of times an alarm is triggered during excitation system monitoring. The generator set excitation system state parameter S is calculated based on the sum of the information scores of each fault alarm corresponding to the item and the correction coefficient. The excitation system performance level is determined based on S.

[0070] Specifically, the excitation system status is evaluated based on the assessment results of the generator condition monitoring, PSS performance evaluation, and limitation evaluation modules. A fault information database is established, and each fault is assigned a corresponding score to quantify its impact on the excitation system performance, as shown in Table 1.

[0071] Table 1: Correspondence between Faults and Scores

[0072]

[0073] The frequency of excitation system failures is introduced as an influencing factor to adjust the severity of the failures. A corresponding correction coefficient ω is set according to different ranges of the number of failures. When the number of failures is 1-3 times, ω is 1; 4-5 times, ω is 1.3; 7-9 times, ω is 1.5; and more than 10 times, ω is 2.

[0074] Suppose that during a one-month monitoring period, a certain generating unit experienced the following faults: 2 instances of over-limit generator terminal voltage, 1 instance of over-limit generator active power, and 1 instance of under-excitation limitation failure. The fault information score fr1 for over-limit generator terminal voltage is 3 points, and the correction coefficient ω1 is 1 (the number of fault occurrences is 2, within the range of 1-3). Then, what is the score f′ of this fault under a certain fault information? r1 =ω1×f r1 =1×3=3 points; Similarly, the fault information score f for generator active power exceeding the limit r2 The score for this item is 3 points, with a correction coefficient ω2 of 1; the score for the fault information of low excitation limitation failure is 3 points, with a correction coefficient ω3 of 1.

[0075] Score and F under all fault informationr =f′ r1 +f′ r2 +f′ r3 =3+3+3=9 points. According to the formula, the excitation system state parameter S of the generator set can be obtained as 100-9=91 points.

[0076] According to the evaluation grading standards, a score < 60 indicates that the excitation system is not operating properly and a shutdown for maintenance is required; a score between 60 and 80 indicates an abnormality in the excitation system, triggering an alarm signal and requiring immediate maintenance; a score between 80 and 90 indicates an abnormality in the excitation system, requiring vigilance; and a score > 90 indicates that the excitation system is operating normally. Since this unit scored 91 points, its excitation system is deemed to be operating properly.

[0077] Based on the alarms and suggestions provided by the system, staff can conduct a comprehensive overhaul of the excitation system. During the overhaul, any problems discovered are recorded and analyzed in detail, such as replacing faulty voltage sensors or adjusting excitation regulator parameters. After the overhaul is completed, the unit is restarted, and the excitation system status is continuously monitored. Through timely handling of faults and continuous system monitoring, the stable operation of the excitation system is ensured, improving the overall reliability of the power system.

[0078] Example 2, the second embodiment of the present invention, differs from the first embodiment in that: an online monitoring and dynamic performance evaluation system for the excitation operation status of a hydropower unit includes a unit grid connection status judgment module, an excitation system operation status monitoring module, and an excitation system performance level determination module; the unit grid connection status judgment module is used to collect the operation data of the hydropower unit's excitation system, determine whether the unit is disconnected from the grid, and statistically analyze the engagement rate of the excitation regulator PSS and the automatic voltage regulator AVR; the excitation system operation status monitoring module, based on the collected data, monitors and analyzes the unit's electrical quantities, determines the current operating status of the system through preset thresholds, calculates the average damping ratio of the active power disturbance response curve to determine the PSS suppression effect, evaluates the excitation regulator's limiting action, and determines whether the excitation regulator has malfunctions or failures to operate; the excitation system performance level determination module calculates the excitation system state parameters based on the current system operating status, the PSS suppression effect, and the malfunctions or failures to operate, and determines the excitation system performance level.

[0079] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0080] 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.

[0081] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), 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). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because 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 computer memory.

[0082] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in 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 in combination with any 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.

[0083] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for online monitoring and dynamic performance evaluation of the excitation operation status of a hydropower unit, characterized in that: include, Collect operating data of the hydropower unit's excitation system to determine whether the unit is disconnected from the grid, and count the engagement rate of the excitation regulator PSS and the automatic voltage regulator AVR. Based on the collected data, the electrical quantities of the unit are monitored and analyzed, and the current operating status of the system is determined by preset thresholds; The average damping ratio of the active power disturbance response curve is calculated to determine the PSS suppression effect; The excitation regulator's limiting action is evaluated to determine whether the excitation regulator exhibits malfunction or failure to operate. Based on the current operating status of the system, the PSS suppression effect, and the phenomena of false activation and failure to activate, the state parameters of the excitation system are calculated, and the performance level of the excitation system is determined.

2. The method for online monitoring and dynamic performance evaluation of the excitation operation status of a hydropower unit as described in claim 1, characterized in that: The operating data of the hydropower unit excitation system includes the positive sequence voltage amplitude, the main excitation voltage amplitude, and the main excitation current amplitude. Based on the collected data, the peak voltage multiple, peak current multiple, voltage response time, and damping ratio were calculated.

3. The method for online monitoring and dynamic performance evaluation of the excitation operation status of a hydropower unit as described in claim 2, characterized in that: The determination of whether the unit is disconnected from the grid includes: if the active power output of the unit is less than the set grid-connected power threshold and the duration meets the first set time, it means that the unit is disconnected from the grid and a fault alarm is triggered; otherwise, it is connected to the grid. The engagement rate of the Statistical Excitation Regulator (PSS) and Automatic Voltage Regulator (AVR) includes the following: if the unit's active power is above the unit's stable combustion load and the PSS engagement / disengagement signal is 0 for a set duration, it indicates that the unit's PSS is disengaged and triggers a fault alarm; otherwise, it is considered that the PSS is engaged. When the unit has not reached the lower limit of the stable combustion load, the default PSS status is engaged. After the unit is connected to the grid, if the AVR activation / deactivation signal is 0 and the duration meets the second set time, the AVR is determined to be deactivated; otherwise, the AVR is activated.

4. The method for online monitoring and dynamic performance evaluation of the excitation operation status of a hydropower unit as described in claim 3, characterized in that: The monitoring and analysis of the unit's electrical quantities includes, based on the generator's normal operation equivalent diagram, analyzing the generator's active power output and maximum stable active power output under different excitation modes, and obtaining the effect of the excitation system's automatic operation mode on generator performance and system stability. The step of determining the current operating status of the system by setting a preset threshold includes monitoring and analyzing relevant data of the power plant generator set by setting a preset threshold, displaying the monitoring data and waveforms in real time, and immediately issuing a fault alarm and storing the data once an abnormality is detected.

5. The method for online monitoring and dynamic performance evaluation of the excitation operation status of a hydropower unit as described in claim 4, characterized in that: The process of determining the PSS suppression effect includes: when the PSS output voltage is greater than a certain value, determining that a low-frequency oscillation has occurred and storing the relevant waveform; calculating the average damping ratio of the active power disturbance response curve; comparing it with the suppression threshold to determine the PSS suppression effect; and if the effect is poor, triggering a fault alarm and correcting the parameters.

6. The method for online monitoring and dynamic performance evaluation of the excitation operation status of a hydropower unit as described in claim 5, characterized in that: The determination of whether the excitation regulator has malfunctions or failures to operate includes performing model calculations based on the collected generator set data and the unit's internal protection mechanisms and limiting logic, comparing the results with the actual protection and limiting action switching quantities, and determining whether the excitation regulator has malfunctions or failures to operate.

7. The method for online monitoring and dynamic performance evaluation of the excitation operation status of a hydropower unit as described in claim 6, characterized in that: The process of determining the performance level of the excitation system includes introducing the number of excitation system failures as an influencing factor, correcting the severity of the failures, and setting a corresponding correction coefficient ω based on the different ranges of the number of failures. The number of excitation system faults is the number of times an alarm is triggered during excitation system monitoring; The excitation system state parameter S of the generator set is calculated by multiplying the information score of each fault alarm item with the correction coefficient, and the performance level of the excitation system is determined based on S.

8. An online monitoring and dynamic performance evaluation system for the excitation operating status of a hydropower unit, employing the online monitoring and dynamic performance evaluation method for the excitation operating status of a hydropower unit as described in any one of claims 1 to 7, characterized in that: This includes a module for determining the grid connection status of the generating unit, a module for monitoring the operating status of the excitation system, and a module for determining the performance level of the excitation system; The unit grid connection status judgment module is used to collect the operating data of the hydropower unit excitation system, determine whether the unit is disconnected from the grid, and count the commissioning rate of the excitation regulator PSS and the automatic voltage regulator AVR. The excitation system operation status monitoring module monitors and analyzes the unit's electrical quantities based on the collected data, determines the current operating status of the system by setting a preset threshold, calculates the average damping ratio of the active power disturbance response curve to determine the PSS suppression effect, evaluates the limiting action of the excitation regulator, and determines whether the excitation regulator has erroneous or non-operational phenomena. The excitation system performance level determination module calculates the excitation system state parameters based on the current operating state of the system, the PSS suppression effect, and the malfunction and failure to operate phenomena, and determines the excitation system performance level.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the online monitoring and dynamic performance evaluation method for the excitation operation status of a hydropower unit as described in any one of claims 1 to 7.

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