Hydropower station dynamic grid-connected performance self-evaluation method, system, equipment and medium

Abstract

The invention discloses a hydropower station dynamic grid-connected performance self-evaluation method, system and device and a medium. The method comprises the steps of obtaining real-time operation data of a power grid; analyzing the obtained data, and evaluating the automatic voltage control performance to obtain a first dynamic grid-connected index; evaluating the performance of the excitation and power system stabilizer to obtain a second dynamic grid-connected index; evaluating the automatic power generation control performance to obtain a third dynamic grid-connected index; evaluating the primary frequency modulation performance to obtain a fourth dynamic grid-connected index; and based on the dynamic grid connection index, performing self-evaluation on the assessment index and the compensation index of the power plant, and generating early warning information. The safe and stable operation level of the hydropower station and good interaction with the power grid are improved.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a method, system, equipment and medium for self-evaluation of dynamic grid connection performance of hydropower stations. Background Technology

[0003] Currently, power plants in power systems typically collect electrical parameters for self-monitoring through locally deployed measurement and control devices, transmitters, or automation systems. However, due to the low accuracy of these measurement devices, limited sampling frequencies, simplified signal processing methods (such as using common FFT algorithms), and the frequent lack of high-precision frequency domain filtering modules, the monitoring results are somewhat distorted, especially under conditions of harmonic interference and system disturbances, making it difficult to accurately reflect the fundamental component. Furthermore, there are significant differences between these traditional measurement systems and the high-precision synchronous phasor measurement systems based on PMU equipment in dispatch centers. This leads to systematic deviations in key operating parameters, resulting in inconsistencies between dispatch assessments and power plant self-evaluations, and causing disputes related to the assessments.

[0004] Especially for power sources like hydropower stations, which have strong regulation capabilities, fast response speeds, but varied operating modes, their grid connection performance is not only affected by the characteristics of the main equipment, but also closely related to factors such as hydraulic structures, head fluctuations, and guide vane regulation characteristics, making assessment quite difficult. Traditional static indicators often fail to accurately reflect their dynamic response process.

[0005] Therefore, there is an urgent need to develop a local evaluation method that is compatible with scheduling assessment logic and has dynamic performance early warning capabilities. Summary of the Invention

[0006] In view of the aforementioned existing problems, the present invention is proposed.

[0007] Therefore, this invention provides a method, system, equipment, and medium for self-evaluation of the dynamic grid connection performance of hydropower stations to solve the problems of low accuracy and insufficient dynamic response evaluation capability of existing methods.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0009] In a first aspect, the present invention provides a method for self-evaluation of the dynamic grid connection performance of a hydropower station, comprising:

[0010] Obtain real-time power grid operation data;

[0011] The acquired data is analyzed, and the performance of automatic voltage control is evaluated to obtain the first dynamic grid connection index.

[0012] The second dynamic grid connection index is obtained by evaluating the excitation and power system stabilizer performance;

[0013] The third dynamic grid connection index is obtained by evaluating the performance of automatic generation control;

[0014] The fourth dynamic grid connection index is obtained by evaluating the performance of the primary frequency regulation.

[0015] Based on dynamic grid connection indicators, the power plant's assessment and compensation indicators are self-evaluated, and early warning information is generated.

[0016] As a preferred embodiment of the self-evaluation method for dynamic grid connection performance of hydropower stations described in this invention, the evaluation of automatic voltage control performance includes:

[0017] By real-time monitoring and comparison of bus voltage, it can be determined whether the voltage exceeds the preset range;

[0018] If the bus voltage exceeds the preset upper and lower limits, and the time of exceeding the limit exceeds the preset time threshold, a voltage over-limit event is considered to have occurred, and the corresponding assessment mechanism is activated.

[0019] If the bus voltage is within the range of the lower limit voltage for leading phase operation and the upper limit voltage for lagging phase operation, the assessment mechanism will not be activated.

[0020] Based on the voltage over-limit event, the difference between the unit's reactive power output and the voltage limit is integrated in the time domain to obtain the reactive power integral of a single event;

[0021] The reactive power integral energy of all single events is summarized and weighted by voltage fluctuation rate to obtain the final value of reactive power integral energy.

[0022] The beneficial effects of this preferred technical solution are that by real-time monitoring and analysis of the bus voltage, voltage over-limit events can be accurately identified and reactive power integral energy can be calculated. Then, the final reactive power integral energy value is obtained by weighted summation based on voltage fluctuation rate. This effectively realizes the accurate evaluation and optimization of automatic voltage control performance, ensures the stable operation of the power system, and reduces assessment risks.

[0023] As a preferred embodiment of the self-evaluation method for dynamic grid connection performance of hydropower stations described in this invention, the evaluation of the excitation and power system stabilizer performance includes:

[0024] The excitation system status is monitored, status monitoring results are obtained, and corresponding alarms are triggered when an anomaly is detected;

[0025] The limiting action of the excitation regulator is evaluated and quantified according to its severity to obtain the limiting action evaluation results;

[0026] Based on the condition monitoring results and the assessment results of restricted actions, a second dynamic grid connection index is generated.

[0027] As a preferred embodiment of the self-evaluation method for dynamic grid connection performance of hydropower stations described in this invention, the evaluation of automatic generation control performance includes:

[0028] By using the conversion curves of head, opening degree and power, the percentage of active power output under different head and guide vane opening conditions is determined;

[0029] Based on the current guide vane opening margin and the relationship between head, opening, and power, the upper and lower adjustment margins of the current active power are calculated.

[0030] As a preferred embodiment of the self-evaluation method for dynamic grid connection performance of hydropower stations described in this invention, the evaluation of primary frequency regulation performance includes:

[0031] Read the configuration parameters and initialize the primary frequency regulation configuration parameters;

[0032] The frequency of each unit is detected using real-time time series data from a wide-area measurement system.

[0033] If the detected frequency meets the corresponding unit primary frequency regulation configuration parameters, then the primary frequency regulation capture condition is considered to be met.

[0034] After confirming that the conditions for primary frequency regulation capture are met, the active power output of each unit is detected using real-time time series data from the wide-area measurement system.

[0035] Determine whether the unit is in grid-connected status based on whether the unit's active power output reaches the grid-connected power threshold configuration parameters;

[0036] After confirming that the unit is in grid-connected status, the primary frequency regulation performance index of the computer group is calculated based on the unit's active power output and written into the commercial database.

[0037] The beneficial effects of this preferred technical solution are that by real-time monitoring of the unit frequency and active power output, combined with configuration parameters, the occurrence of primary frequency regulation events and the grid connection status of the unit can be accurately determined, and the primary frequency regulation performance indicators can be calculated accordingly. This realizes the automated and refined evaluation and data management of the unit's primary frequency regulation performance, providing a reliable basis for grid frequency stability control.

[0038] As a preferred embodiment of the self-evaluation method for dynamic grid connection performance of hydropower stations described in this invention, the step of acquiring real-time grid operation data includes:

[0039] If the number of real-time power grid operation data obtained is empty or invalid, the data is deemed invalid.

[0040] If the number of real-time power grid operation data obtained is empty or invalid, and this continues for a predetermined time interval, the phasor measurement unit is considered to have malfunctioned, and the unit's operating status is updated.

[0041] As a preferred embodiment of the self-evaluation method for dynamic grid connection performance of hydropower stations described in this invention, the final value of the reactive power integral is expressed as:

[0042]

[0043] Where ΣkVar·h represents the total integrated electricity consumption of all events on that day, Dv represents the voltage fluctuation rate on that day, and Ref represents the reference voltage fluctuation rate.

[0044] Secondly, the present invention provides a dynamic grid connection performance self-evaluation system for hydropower stations, comprising:

[0045] The acquisition module is used to acquire real-time operating data of the power grid;

[0046] The automatic voltage control performance evaluation module is used to analyze the acquired data and obtain the first dynamic grid connection index by evaluating the automatic voltage control performance.

[0047] The excitation and power system stabilizer performance evaluation module is used to obtain a second dynamic grid connection index by evaluating the performance of the excitation and power system stabilizer.

[0048] The automatic generation control performance evaluation module is used to obtain a third dynamic grid connection index by evaluating the performance of automatic generation control.

[0049] The primary frequency regulation performance evaluation module is used to obtain the fourth dynamic grid connection index by evaluating the primary frequency regulation performance.

[0050] The self-assessment module is used to perform self-assessment of the power plant's performance indicators and compensation indicators based on dynamic grid connection indicators, and generate early warning information.

[0051] Thirdly, the present invention provides an electronic device, comprising:

[0052] Memory, used to store programs;

[0053] A processor is configured to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the self-evaluation method for the dynamic grid connection performance of the hydropower station.

[0054] Fourthly, the present invention provides a computer-readable storage medium, comprising: when the program is executed by a processor, the steps of implementing the self-evaluation method for dynamic grid connection performance of the hydropower station.

[0055] The beneficial effects of this invention are as follows: This invention uses a PMU / WAMS system to measure various data of the generator, resulting in more accurate data acquisition. Utilizing AVC performance evaluation and early warning modules, excitation and PSS performance evaluation and early warning modules, AGC performance evaluation and early warning modules, and primary frequency regulation performance evaluation and early warning modules, the system can monitor key parameters such as bus voltage, power factor, and unit reactive power output in real time, and perform detailed time-domain analysis or model predictive control performance evaluation. A PMU fault detection program is added, which can automatically determine the PMU's operating status, promptly stop data processing and issue an alarm when a PMU fault occurs, enhancing the system's robustness and automation, and further ensuring the accuracy and reliability of the data. Attached Figure Description

[0056] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. 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. Wherein:

[0057] Figure 1 This is a basic flowchart illustrating a method for self-evaluation of dynamic grid connection performance of a hydropower station, as provided in one embodiment of the present invention.

[0058] Figure 2 A flowchart illustrating the assessment steps of the AVC performance evaluation and early warning module in a self-evaluation method for dynamic grid connection performance of a hydropower station, as provided in an embodiment of the present invention;

[0059] Figure 3 The diagram shows the conversion curves of head, opening degree, and power for a dynamic grid connection performance self-evaluation method for hydropower stations provided in one embodiment of the present invention.

[0060] Figure 4 The flowchart shows a performance evaluation module of a dynamic grid connection performance self-evaluation method for hydropower stations, provided as an embodiment of the present invention. Detailed Implementation

[0061] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0062] Example 1, referring to Figure 1 As an embodiment of the present invention, a method for self-evaluation of the dynamic grid connection performance of a hydropower station is provided, comprising:

[0063] S100: Acquire real-time power grid operation data;

[0064] S200: Analyze the acquired data and obtain the first dynamic grid connection index by evaluating the performance of automatic voltage control;

[0065] S300: The second dynamic grid connection index is obtained by evaluating the performance of excitation and power system stabilizers;

[0066] S400: The third dynamic grid connection index is obtained by evaluating the performance of automatic generation control;

[0067] S500: The fourth dynamic grid connection index is obtained by evaluating the primary frequency regulation performance;

[0068] S600: Based on dynamic grid connection indicators, it performs self-assessment of the power plant's performance indicators and compensation indicators, and generates early warning information.

[0069] It should be noted that hydropower stations face a series of challenges during operation, such as head fluctuations, changes in guide vane regulation characteristics, and system disturbances. These factors directly affect the power generation efficiency and grid stability of the station. Grid connection performance evaluation, by accurately assessing key parameters such as voltage regulation capability, frequency response speed, and active and reactive power output stability, not only helps ensure the safe and stable operation of hydropower stations but also maximizes their grid connection benefits. A reasonable evaluation mechanism can encourage hydropower stations to optimize their operating procedures, improve the speed and accuracy of their response to grid dispatch instructions, and thus effectively support the safe and reliable operation of the power system under the background of large-scale renewable energy grid connection.

[0070] Therefore, to address the issues of low accuracy and insufficient dynamic response evaluation capabilities of existing methods, the system utilizes the AVC performance evaluation module, excitation and PSS performance evaluation module, AGC performance evaluation module, and primary frequency regulation performance evaluation module through steps S100-S600 to obtain dynamic grid connection indicators (such as reactive power integral, stability score, frequency regulation margin, and contribution rate). The system can self-evaluate the power plant's assessment and compensation indicators and generate corresponding early warning information, effectively improving the stability and operating efficiency of the power system and ensuring the safe and reliable operation of the power grid.

[0071] Example 2, refer to Figures 2-4 As an embodiment of the present invention, based on the previous embodiment, a method for self-evaluation of the dynamic grid connection performance of a hydropower station is provided, comprising:

[0072] In this embodiment of the application, obtaining real-time power grid operation data in step S100 includes acquiring and processing real-time data (including but not limited to bus voltage, power factor, and unit reactive power output) from the PMU (Phasor Measurement Unit) / WAMS (Wide Area Measurement System) system.

[0073] In this embodiment, step S100, which involves acquiring real-time power grid operation data, also includes a PMU fault detection program, primarily focusing on the reliability and validity of the data acquisition phase. Specifically, this involves checking the validity of the data and continuously monitoring and evaluating it. This step ensures that all subsequent analyses based on this data (such as automatic voltage control performance evaluation, excitation and power system stabilizer performance evaluation, automatic generation control performance evaluation, primary frequency regulation performance evaluation, etc.) are built upon an accurate and reliable data foundation.

[0074] In this embodiment, data validity checks and continuous monitoring and judgment include checking whether the read data is valid. If the number of read real-time data is 0 or the data is considered invalid, continuous monitoring and judgment are initiated. If the data is valid, normal operation continues, and the process returns to obtaining real-time power grid operation data.

[0075] In this embodiment of the application, continuous monitoring and judgment includes: if invalid data is detected, the system starts timing and continuously monitors the data status; if the data remains invalid within the next 60 seconds, it is determined that the PMU has failed and the unit operating status is updated.

[0076] In this embodiment of the application, updating the unit's operating status includes automatically changing the current operating status of the unit to "PMU fault" once a PMU fault is confirmed. This step ensures that operators and other relevant systems can be informed of the current data acquisition problems in a timely manner.

[0077] In this embodiment, if the unit is in a specific state such as grid disconnection, PSS exit, or primary frequency regulation exit before a PMU failure, the system will continue these states without making any changes. This step ensures that even in the event of a PMU failure, the original operating state configuration of the unit will not be incorrectly changed.

[0078] In this embodiment of the application, the evaluation of automatic voltage control performance in step S200 includes evaluating and assessing the AVC performance by calling the bus voltage, power factor, and reactive power output of the unit measured in real time in the PMU / WAMS system.

[0079] In this embodiment of the application, the evaluation of automatic voltage control (AVC) performance in step S200 also includes automatically performing exemption judgment and processing for phase-leading and phase-retarding assessments.

[0080] In this embodiment of the application, the time-domain analysis-based method in step S200 includes real-time monitoring of the bus voltage, determining whether the limit is exceeded and calculating the reactive power integral, weighting the reactive power integral value according to the daily voltage fluctuation rate to obtain the final reactive power integral value, and evaluating the voltage regulation effect of the AVC system.

[0081] In one optional implementation, the model predictive control (MPC) method in step S200 includes establishing a mathematical model of the power grid system, using real-time data for optimization prediction, adjusting model parameters based on the difference between actual measurement results and model predictions, and optimizing and evaluating the voltage regulation effect of the AVC system.

[0082] In another alternative implementation, the machine learning-based intelligent analysis in step S200 includes collecting and preprocessing historical operating data, training a machine learning model to identify voltage stability patterns, using the model to analyze and predict real-time data, evaluating the performance of the AVC system, and providing early warnings of potential problems.

[0083] It should be noted that this invention employs a time-domain analysis-based method to evaluate the performance of Automatic Voltage Control (AVC). Its main advantage lies in directly utilizing real-time measurement data for immediate calculation and evaluation, ensuring rapid response and accurate quantification to dynamic changes in the power grid. Compared to Model Predictive Control (MPC), the time-domain analysis-based method eliminates the need for complex mathematical modeling and future state prediction, reducing computational complexity and errors caused by model uncertainty. Furthermore, compared to machine learning-based intelligent analysis, it avoids large-scale historical data collection, model training, and potential overfitting issues, making the system simpler, more efficient, and easier to implement and maintain. This makes it particularly suitable for real-time monitoring scenarios requiring high precision and low latency response. In addition, the time-domain analysis method is closely integrated with existing power grid operation and management regulations, allowing direct application to comparisons of assessment standards, thus improving its applicability and reliability in practical operation.

[0084] In this embodiment of the application, step S200 evaluates the performance of automatic voltage control (AVC), such as... Figure 2 As shown, it also includes:

[0085] (1) Read the bus voltage and determine whether the bus voltage exceeds the limit. If the over-limit time exceeds the preset time, the over-limit event can be considered to have occurred, and the assessment will begin until the event ends.

[0086] (2) Based on the bus voltage read in step (1), determine whether the period is exempt from assessment by combining the lower limit voltage of the leading phase operation or the upper limit voltage of the lagging phase operation.

[0087] (3) Integrate the reactive power of the unit and the difference between the lower limit voltage of the advancing phase and the upper limit voltage of the lagging phase in the time domain to obtain the reactive power integral of the over-limit event.

[0088] (4) Sum the absolute values ​​of the reactive power integral energy of the unit each day to obtain the total reactive power integral energy for that day. Then, calculate the final value of the reactive power integral energy by weighting it according to the daily voltage fluctuation rate, as shown in the following formula:

[0089]

[0090] Wherein, ΣkVar·h represents the total integrated electricity consumption of all events on that day, Dv represents the voltage fluctuation rate on that day, which is calculated as (maximum voltage of the day - minimum voltage of the day) / reference voltage; Ref represents the reference voltage fluctuation rate, which is taken as 3.5% in a 220kV power grid and 3% in a 500kV power grid. The results are evaluated at 2 fen / 10,000 kVar·h.

[0091] In this embodiment, the first dynamic grid connection indicator in step S200 includes the final value of reactive power integral energy weighted by voltage fluctuation rate. Reactive power integral energy is calculated by real-time monitoring of whether the bus voltage exceeds limits, and by combining the lower limit voltage of the leading phase operation or the upper limit voltage of the lagging phase operation to determine whether the period is exempt from assessment. The absolute values ​​of reactive power integral energy for all limit-exceeding events are summed daily, and then weighted by voltage fluctuation rate to obtain the final value of voltage fluctuation rate-weighted reactive power integral energy. These indicators reflect the hydropower station's ability to regulate grid voltage and its operational effectiveness in maintaining stable voltage within specified ranges.

[0092] In this embodiment of the application, the evaluation of the excitation and power system stabilizer (PSS) performance in step S300 includes the ability to monitor the excitation system status and evaluate the limiting actions of the excitation regulator based on data from the PMU / WAMS system, ultimately achieving performance evaluation and early warning of the excitation and PSS.

[0093] In this embodiment, the excitation system status monitoring includes alarms for generator terminal voltage exceeding limits or sudden changes, generator terminal current exceeding limits or sudden changes, generator frequency exceeding limits, excitation current sudden changes, generator active power exceeding limits, and generator reactive power exceeding limits. Evaluating the various limiting actions of the excitation regulator refers to whether the limiting actions such as low excitation limit, strong excitation limit, volt-hertz limit, and stator current overload have failed to operate or have malfunctioned. Low excitation limit includes triggering when the excitation current is lower than the set value; strong excitation limit includes triggering when the excitation current exceeds the set value; volt-hertz limit includes preventing overvoltage and overfrequency; stator current overload limit includes preventing excessive stator current. The severity of the harm to the system caused by the above-mentioned exceeding limits, sudden changes, failure to operate, and malfunctions is graded and quantified. A higher level indicates a greater harm to the excitation system performance. Each level corresponds to a score, with the highest level being level 5 with 5 points and the lowest level being level 1 with 1 point. Table 1 shows the fault information, specific meanings, and score comparison.

[0094] Table 1. Fault Information, Specific Meaning, and Score Comparison Table

[0095]

[0096]

[0097] In this embodiment, the second dynamic grid connection index in step S300 consists of two parts: first, the excitation system status monitoring results, including whether parameters such as generator terminal voltage, current, generator frequency, excitation current, and active and reactive power exceed limits or undergo sudden changes; second, the limitation action assessment and classification, which quantifies the severity of limitation actions such as low excitation limitation and strong excitation limitation as they fail to operate or malfunction. These indicators provide an important reference for generator stability, ensuring that the power system maintains stable operation under dynamic conditions.

[0098] In this embodiment of the application, the evaluation of the automatic generation control (AGC) performance in step S400 includes calculating the primary frequency regulation margin of the grid-connected unit by collecting hydraulic head and guide vane opening data, and then evaluating the AGC performance of the grid-connected unit.

[0099] In this embodiment of the application, the evaluation of the automatic power generation control performance in step S400 also includes the ability to obtain the upper and lower adjustment margins of the current active power based on the conversion curves of head, opening degree and power, combined with the current guide vane opening margin.

[0100] In this embodiment of the application, the evaluation of the automatic power generation control performance in step S400 also includes constraints on the frequency regulation of the hydropower unit. These constraints include constraints on the primary frequency regulation loop operation cycle: requiring the primary frequency regulation loop program operation cycle of the hydropower unit to be no greater than 40ms; and constraints on the permanent slip coefficient as described in Section 7.3: requiring the permanent slip coefficient bp to be no greater than 4% in the opening-degree regulation mode, and the permanent power difference coefficient (slip rate) ep to be no greater than 3% in the power regulation mode.

[0101] In this embodiment, step S400, which evaluates the performance of the automatic power generation control, further includes real-time acquisition of head height and guide vane opening. Based on the conversion curve of head, opening, and power, the percentage of active power output under different heads and guide vane openings can be determined in real time. The upper and lower regulation margins of the primary frequency regulation are determined jointly based on the primary frequency regulation constraint and the current guide vane opening. The conversion curve of head, opening, and power is shown below. Figure 3 As shown.

[0102] In this embodiment, the third dynamic grid connection index in step S400 includes primary frequency regulation margin and permanent slip coefficient. By real-time acquisition of head height and guide vane opening data, the current active power output percentage is determined using the conversion curves of head, opening, and power. The primary frequency regulation margins of the unit are then evaluated in conjunction with primary frequency regulation constraints. Additionally, the permanent slip coefficient bp should not exceed 4% in the opening regulation mode, and the permanent power difference coefficient (slip rate) ep should not exceed 3% in the power regulation mode. These indicators reflect the flexibility and response speed of the hydropower station in participating in grid frequency regulation.

[0103] In this embodiment of the application, the evaluation of primary frequency regulation performance in step S500 includes real-time reading of time series real-time library data, determining whether a primary frequency regulation event has occurred, and evaluating the frequency regulation capability of the unit during the primary frequency regulation process.

[0104] In this embodiment of the application, step S500 based on the Wide Area Measurement System (WAMS) includes real-time acquisition of grid frequency and unit active power output data, detection of primary frequency regulation events, calculation of key indicators such as actual power contribution, theoretical power contribution and contribution rate, and evaluation of the unit's primary frequency regulation performance.

[0105] In one optional implementation, step S500, based on state estimation and filtering technology, includes using power system state estimation technology combined with historical data to estimate primary frequency regulation-related parameters, and using advanced filtering algorithms to process the raw measurement data to reduce noise interference. Finally, key indicators such as actual power contribution, theoretical power contribution, and contribution rate are calculated to evaluate the primary frequency regulation performance.

[0106] In another optional implementation, step S500 involves multi-source data fusion, which includes integrating information from WAMS, SCADA systems, local sensors, and other available data sources. Data fusion technology is used to comprehensively analyze these data, calculate key indicators such as actual power contribution, theoretical power contribution, and contribution rate, and comprehensively evaluate the primary frequency regulation performance.

[0107] It should be noted that the main advantage of this invention in using a Wide Area Measurement System (WAMS) to evaluate primary frequency regulation performance lies in its direct use of high-precision, time-synchronized real-time data, ensuring rapid response and accurate quantification to dynamic changes in the power grid. Compared to methods based on state estimation and filtering techniques, WAMS eliminates the need for complex mathematical modeling and additional data processing steps, reducing computational complexity and potential model errors, while providing more reliable raw data. Compared to methods based on multi-source data fusion, WAMS simplifies the data integration process, avoiding inconsistencies and complexities that may exist between different data sources, making the system more concise, efficient, and easier to implement and maintain. Furthermore, WAMS is closely integrated with existing power grid operation and management regulations, enabling direct application to comparisons of assessment standards, improving its applicability and reliability in practical operations, and is particularly suitable for real-time monitoring scenarios requiring high-precision, low-latency responses.

[0108] In this embodiment of the application, the evaluation of primary frequency regulation performance in step S500 includes capturing real-time data through an online detection system and calculating the actual power contribution of primary frequency regulation, the theoretical power contribution of primary frequency regulation, the contribution rate of primary frequency regulation, the monthly input rate of primary frequency regulation, and the stabilization time at different times.

[0109] In this embodiment of the application, the evaluation of primary frequency modulation performance in step S500 includes primary frequency modulation event detection and index calculation;

[0110] In this embodiment of the application, a single frequency modulation event detection, such as Figure 4 As shown, it includes:

[0111] (1) Read the parameters of table 8128 to determine the configuration parameters; read the plant, generator set and station frequency information of tables 411 / 8219 / 8130 / 8312 to complete the reading of the primary frequency regulation configuration parameters of the unit. The primary frequency regulation configuration parameters of the unit are used to determine whether the unit has experienced a primary frequency regulation event.

[0112] (2) Use the real-time data of the WAMS time series library to detect the frequency of each unit, and determine whether the unit meets the primary frequency regulation capture conditions based on whether the unit frequency meets the corresponding primary frequency regulation configuration parameters.

[0113] (3) After determining that the unit meets the primary frequency regulation capture conditions, the active power output of each unit is detected by using the real-time data of the WAMS time series library of the wide area measurement system, and the unit is determined to be connected to the grid based on whether the active power output of the unit meets the corresponding unit grid connection power threshold configuration parameters.

[0114] (4) After the unit is connected to the grid, the active power output of the unit is used to calculate the primary frequency regulation performance indicators such as the unit's contribution power, theoretical contribution power and contribution ratio, and the results are written into the commercial database.

[0115] (5) Determine whether a program termination signal has been issued. If not, return to step (2) and run in a loop.

[0116] In this embodiment of the application, the indicator calculation includes calculating indicators such as actual integrated electricity consumption, theoretical integrated electricity consumption, electricity contribution index, speed change rate, and monthly commissioning rate of primary frequency regulation. The specific calculation formula is as follows:

[0117] 1) Actual accumulated electricity consumption:

[0118]

[0119] In the formula: H i The power contribution for the primary frequency regulation of unit i; t0 is the moment when the system frequency exceeds the dead zone of the primary frequency regulation of unit i; t t P is the moment when the system frequency enters the dead zone of the primary frequency regulation operation of unit i; t Pi represents the actual active power generated by unit i at time t; P0 represents the average active power in the 2 seconds before the unit's frequency crosses the dead zone; T represents the integration interval (20 milliseconds); Hi i The sign convention is as follows: positive for high-frequency low-power generation or low-frequency high-power generation, and negative for high-frequency high-power generation or low-frequency low-power generation.

[0120] 2) Theoretical integral charge:

[0121]

[0122] ΔP(Δf,t)=Δf(t)×MCR / f n ×K c

[0123] In the formula: (Δf,t) corresponds to the frequency difference of the grid frequency change exceeding the dead zone, MCR refers to the rated active power output of the unit, and f n K is the system's rated frequency (i.e., 50Hz). c The corresponding unit speed change rate (permanent slip coefficient, which is negative).

[0124] 3) Power contribution rate: that is, actual power contribution / theoretical power contribution.

[0125] 4) Rate of change of speed:

[0126]

[0127] In the formula: Δf(t) is the difference between the frequency and the frequency modulation dead zone at time t; ΔP(t) is the difference between the active power P and the rated active power P0 at time t. The total speed variation rate is obtained by taking the overall average of the average speed variation rate over the four time periods of 15s, 30s, 45s, and 60s.

[0128] 5) Monthly commissioning rate of primary frequency regulation:

[0129] Primary frequency regulation monthly operational rate = Primary frequency regulation monthly operational time / Unit monthly grid connection time. Wherein, grid connection time is the operating time when the unit's active power is greater than the minimum output; primary frequency regulation monthly operational time is the operating time when the unit is judged to be in grid-connected operation and its primary frequency regulation is engaged or disengaged.

[0130] In this embodiment, the fourth dynamic grid-connection indicator in step S500 encompasses actual power contribution, theoretical power contribution, power contribution rate, velocity variation rate, and primary frequency regulation monthly commissioning rate. Based on data captured by the real-time detection system, the actual power contribution, theoretical power contribution, and power contribution rate are calculated, i.e., the ratio of actual power contribution to theoretical power contribution, reflecting the unit's effective response capability to grid frequency disturbances. Furthermore, the velocity variation rate is calculated, representing the rate of change of active power when the frequency changes, and the primary frequency regulation monthly commissioning rate is calculated, i.e., the proportion of functional activation time to total grid-connected operation time. These indicators collectively evaluate the unit's ability and reliability to quickly restore frequency stability in the face of grid frequency fluctuations.

[0131] In this embodiment, step S600 involves self-evaluating the power plant's performance indicators and compensation indicators, and generating early warning information. This includes, after completing various performance evaluations, the system will self-evaluate the power plant's performance indicators and compensation indicators according to the requirements of the power grid company's grid connection operation management rules and ancillary service management rules. This means using the various dynamic grid connection indicators obtained in the preceding steps to determine whether the power plant meets relevant standards or where improvements are needed; if any non-compliance with standards is found, or if there are trends that may lead to future problems, corresponding early warning information will be generated to help the power plant take measures in advance to avoid potential risks or losses.

[0132] Example 3 is an embodiment of the present invention. This embodiment differs from the first embodiment in that it provides a dynamic grid connection performance self-evaluation system for hydropower stations.

[0133] It should be noted that the technical solution of the hydropower station dynamic grid connection performance self-evaluation system is based on the same concept as the technical solution of the hydropower station dynamic grid connection performance self-evaluation method described above. For details not described in detail in the technical solution of the hydropower station dynamic grid connection performance self-evaluation system in this embodiment, please refer to the description of the technical solution of the hydropower station dynamic grid connection performance self-evaluation method described above.

[0134] This embodiment describes a dynamic grid connection performance self-evaluation system for hydropower stations, comprising:

[0135] The acquisition module is used to acquire real-time operating data of the power grid;

[0136] The automatic voltage control performance evaluation module is used to analyze the acquired data and obtain the first dynamic grid connection index by evaluating the automatic voltage control performance.

[0137] The excitation and power system stabilizer performance evaluation module is used to obtain a second dynamic grid connection index by evaluating the performance of the excitation and power system stabilizer.

[0138] The automatic generation control performance evaluation module is used to obtain a third dynamic grid connection index by evaluating the performance of automatic generation control.

[0139] The primary frequency regulation performance evaluation module is used to obtain the fourth dynamic grid connection index by evaluating the primary frequency regulation performance.

[0140] The self-assessment module is used to perform self-assessment of the power plant's performance indicators and compensation indicators based on dynamic grid connection indicators, and generate early warning information.

[0141] This embodiment also provides an electronic device applicable to a method for self-evaluating the dynamic grid connection performance of a hydropower station, including:

[0142] The system includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes these instructions to implement a method for self-evaluating the dynamic grid connection performance of a hydropower station, as proposed in the above embodiments.

[0143] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a method for self-evaluation of the dynamic grid connection performance of a hydropower station as proposed in the above embodiments.

[0144] The storage medium proposed in this embodiment and the method for implementing a dynamic grid connection performance self-evaluation method for hydropower stations proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0145] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0146] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not 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 self-evaluation of the dynamic grid connection performance of a hydropower station, characterized in that, include: Obtain real-time power grid operation data; The acquired data is analyzed, and the performance of automatic voltage control is evaluated to obtain the first dynamic grid connection index. The second dynamic grid connection index is obtained by evaluating the excitation and power system stabilizer performance; The third dynamic grid connection index is obtained by evaluating the performance of automatic generation control; The fourth dynamic grid connection index is obtained by evaluating the performance of the primary frequency regulation. Based on dynamic grid connection indicators, the power plant's assessment and compensation indicators are self-evaluated, and early warning information is generated.

2. The self-evaluation method for dynamic grid connection performance of hydropower stations as described in claim 1, characterized in that: The evaluation of automatic voltage control performance includes: By real-time monitoring and comparison of bus voltage, it can be determined whether the voltage exceeds the preset range; If the bus voltage exceeds the preset upper and lower limits, and the time of exceeding the limit exceeds the preset time threshold, a voltage over-limit event is considered to have occurred, and the corresponding assessment mechanism is activated. If the bus voltage is within the range of the lower limit voltage for leading phase operation and the upper limit voltage for lagging phase operation, the assessment mechanism will not be activated. Based on the voltage over-limit event, the difference between the unit's reactive power output and the voltage limit is integrated in the time domain to obtain the reactive power integral of a single event; The reactive power integral energy of all single events is summarized and weighted by voltage fluctuation rate to obtain the final value of reactive power integral energy.

3. The self-evaluation method for dynamic grid connection performance of hydropower stations as described in claim 1 or 2, characterized in that: The evaluation of excitation and power system stabilizer performance includes: The excitation system status is monitored, status monitoring results are obtained, and corresponding alarms are triggered when an anomaly is detected; The limiting action of the excitation regulator is evaluated and quantified according to its severity to obtain the limiting action evaluation results; Based on the condition monitoring results and the assessment results of restricted actions, a second dynamic grid connection index is generated.

4. The self-evaluation method for dynamic grid connection performance of hydropower stations as described in claim 3, characterized in that: The evaluation of the automatic power generation control performance includes: By using the conversion curves of head, opening degree and power, the percentage of active power output under different head and guide vane opening conditions is determined; Based on the current guide vane opening margin and the relationship between head, opening, and power, the upper and lower adjustment margins of the current active power are calculated.

5. The self-evaluation method for dynamic grid connection performance of hydropower stations as described in claim 4, characterized in that: The evaluation of primary frequency modulation performance includes: Read the configuration parameters and initialize the primary frequency regulation configuration parameters; The frequency of each unit is detected using real-time time series data from a wide-area measurement system. If the detected frequency meets the corresponding unit primary frequency regulation configuration parameters, then the primary frequency regulation capture condition is considered to be met. After confirming that the conditions for primary frequency regulation capture are met, the active power output of each unit is detected using real-time time series data from the wide-area measurement system. Determine whether the unit is in grid-connected status based on whether the unit's active power output reaches the grid-connected power threshold configuration parameters; After confirming that the unit is in grid-connected status, the primary frequency regulation performance index of the computer group is calculated based on the unit's active power output and written into the commercial database.

6. The self-evaluation method for dynamic grid connection performance of hydropower stations as described in claim 5, characterized in that: The acquisition of real-time power grid operation data includes: If the number of real-time power grid operation data obtained is empty or invalid, the data is deemed invalid. If the number of real-time power grid operation data obtained is empty or invalid, and this continues for a predetermined time interval, the phasor measurement unit is considered to have malfunctioned, and the unit's operating status is updated.

7. The self-evaluation method for dynamic grid connection performance of hydropower stations as described in claim 6, characterized in that: The final value of the reactive power integral is expressed as follows: Where ΣkVar·h represents the total integrated electricity consumption of all events on that day, Dv represents the voltage fluctuation rate on that day, and Ref represents the reference voltage fluctuation rate.

8. A dynamic grid connection performance self-evaluation system for hydropower stations, using the method described in any one of claims 1-7, characterized in that, include: The acquisition module is used to acquire real-time operating data of the power grid; The automatic voltage control performance evaluation module is used to analyze the acquired data and obtain the first dynamic grid connection index by evaluating the automatic voltage control performance. The excitation and power system stabilizer performance evaluation module is used to obtain a second dynamic grid connection index by evaluating the performance of the excitation and power system stabilizer. The automatic generation control performance evaluation module is used to obtain a third dynamic grid connection index by evaluating the performance of automatic generation control. The primary frequency regulation performance evaluation module is used to obtain the fourth dynamic grid connection index by evaluating the primary frequency regulation performance. The self-assessment module is used to perform self-assessment of the power plant's performance indicators and compensation indicators based on dynamic grid connection indicators, and generate early warning information.

9. An electronic device, characterized in that, include: Memory, used to store programs; A processor for loading the program to perform the steps of the method as claimed in any one of claims 1-7.

10. A computer-readable storage medium storing a program, characterized in that, When the program is executed by a processor, it implements the steps of the method as described in any one of claims 1-7.

Images