CN-122001095-A - Intelligent power generation operation control method and system based on equipment health data

CN122001095ACN 122001095 ACN122001095 ACN 122001095ACN-122001095-A

Abstract

The invention relates to the technical field of power generation operation, and discloses a smart power generation operation control method and system based on equipment health data. On the basis, the current running state of the generator set and the fluctuation state of an external power grid are identified, and important situation information is provided for subsequent analysis. By the method, the limitation of the existing system on early wear signal identification under the complex working condition is effectively overcome, the potential hidden danger is prevented from being misjudged to be normal response, the accuracy of equipment health assessment is improved, the risk of unplanned shutdown is reduced, and the power generation efficiency and the stability of a power grid are ensured.

Inventors

Mei Yuefei
MA DI
Chi Xindi
HU JUAN
SONG ZHAORUI
YIN HANG
MENG FANLING
Fu Shuqiang

Assignees

内蒙古蒙东能源有限公司

Dates

Publication Date: 20260508
Application Date: 20260206

Claims (10)

1. An intelligent power generation operation control method based on equipment health data is characterized by comprising the following steps: Acquiring internal operation information and external power grid operation information of a generator set; preprocessing the internal operation information and the external power grid operation information to obtain operation data and power grid data for analysis; according to the operation data and the power grid data, the current operation state of the generator set and the fluctuation state of an external power grid are identified; Performing association analysis on vibration information and pressure information contained in the operation data to obtain association degree between the vibration information and the pressure information; According to the current running state of the generator set and the fluctuation state of the external power grid, adjusting the discriminant criterion of the association degree; under the adjusted discriminant standard, carrying out physical characteristic analysis on the vibration information and the pressure information to obtain frequency composition, time domain representation and physical characteristics of the vibration information and the pressure information; and generating a device health assessment report according to the physical characteristics, and formulating an operation intervention strategy.
2. The method according to claim 1, wherein the performing physical feature analysis on the vibration information and the pressure information under the adjusted criterion to obtain frequency composition, time domain representation and physical features of the vibration information and the pressure information comprises: Acquiring the operation parameters of the generator set, the bearing temperature and the viscosity information of lubricating oil; According to the operation parameters, the bearing temperature and the viscosity information of the lubricating oil, the instantaneous viscosity, the oil film thickness and the shear rate distribution of the lubricating oil film in the bearing are deduced; based on the instantaneous viscosity of the lubricating oil film, the oil film thickness and the shear rate distribution, correcting a physical transmission model of early wear signals transmitted in the oil film, and predicting the deviation of the vibration information in a frequency spectrum energy drift range, amplitude envelope change and the pressure information in a time delay and amplitude attenuation ratio; performing multidimensional matching on the vibration information and the pressure information and the dynamic feature set, and calculating matching degree; Evaluating whether the current vibration information and the pressure information better conform to a normal transient response under the complex situation of the generator set; And identifying an anomaly caused by the early wear signal according to the degree of deviation of the degree of matching from the normal transient response.
3. The intelligent power generation operation control method based on the equipment health data according to claim 1, wherein the adjusting the criterion for the association degree according to the current operation state of the generator set and the fluctuation state of the external power grid comprises: acquiring current operation parameters of the generator set and fluctuation parameters of the external power grid; calculating an internal operation stability index according to the current operation parameters of the generator set; Calculating an external fluctuation influence index according to the fluctuation parameters of the external power grid; Determining a criterion adjustment direction and calculating a situation weight factor according to the internal operation stability index and the external fluctuation influence index; adjusting weights of the internal running stability index and the external fluctuation influence index according to the situation weight factors; and determining a discriminant criterion adjustment strategy according to the adjusted weight of the internal operation stability index and the adjusted weight of the external fluctuation influence index so as to adjust the discriminant criterion of the association degree.
4. The method according to claim 1, wherein the performing physical feature analysis on the vibration information and the pressure information under the adjusted criterion to obtain frequency composition, time domain representation and physical features of the vibration information and the pressure information comprises: Acquiring vibration information and pressure information contained in the operation data; carrying out spectral energy distribution analysis on the vibration information to obtain spectral energy distribution of the vibration information; carrying out asynchronous frequency component analysis on the vibration information to obtain asynchronous frequency components of the vibration information; Performing time domain envelope feature analysis on the vibration information to obtain time domain envelope features of the vibration information; Carrying out specific fluctuation mode analysis on the pressure information to obtain a specific fluctuation mode of the pressure information; Performing aperiodic pulse characteristic analysis on the pressure information to obtain aperiodic pulse characteristics of the pressure information; Calculating the time delay between the vibration information and the pressure information according to the vibration information and the pressure information, and obtaining the time delay; calculating the amplitude attenuation ratio between the vibration information and the pressure information to obtain the amplitude attenuation ratio; Comparing the analysis results of the vibration information and the pressure information with the early wear characteristic evolution law according to the frequency spectrum energy distribution of the vibration information, the asynchronous frequency components of the vibration information, the time domain envelope characteristic of the vibration information, the specific fluctuation mode of the pressure information, the aperiodic pulse characteristic of the pressure information, the time delay and the amplitude attenuation ratio; Identifying the stage of early abrasion according to the comparison result; And evaluating the progress speed of the abrasion according to the stage of the early abrasion.
5. The method for intelligent power generation operation control based on equipment health data according to claim 4, wherein the step of identifying the early wear stage based on the comparison result comprises: continuously monitoring the operation time, load accumulation and degradation degree of bearing lubricating oil of the generator set; When the running time, the load accumulation or the degradation degree of the bearing lubricating oil reaches a preset threshold value, starting an adaptive adjustment mechanism; According to actual vibration information and pressure information and historical wear information, locally correcting an early wear characteristic evolution rule; Adjusting definition of characteristic boundaries between different abrasion stages in the early abrasion characteristic evolution rule; updating typical ranges of vibration spectrum energy distribution, unsynchronized frequency components, time domain envelope characteristics, pressure fluctuation modes, aperiodic pulse characteristics, time delay and amplitude attenuation ratios in a specific stage in the early wear characteristic evolution law; And re-evaluating the comparison result by using the corrected early wear characteristic evolution rule so as to identify the stage of early wear.
6. The method for intelligent power generation operation control based on equipment health data according to claim 4, wherein the step of identifying the early wear stage according to the comparison result comprises: identifying an overlapping region of the current stage feature and the adjacent stage feature; When the comparison result falls into the overlapping area, calculating the similarity degree of the vibration information and the pressure information and typical characteristics of each stage in the overlapping area; Acquiring the recognition accuracy of each stage in the overlapping area in the historical data, and calculating the membership degree of each stage according to the similarity degree and the recognition accuracy; When the membership degree of each stage is lower than a preset threshold value, triggering fuzzy processing of stage identification, marking the current abrasion state as a stage transition zone, and starting an enhanced monitoring mode; in the enhanced monitoring mode, shortening a data acquisition period, and continuously comparing the vibration information and the pressure information which are acquired subsequently; And when the continuity comparison result stably points to a preset stage in a specific time, the fuzzy processing is relieved, and the stage in which early abrasion is located is identified.
7. The method for intelligent power generation operation control based on equipment health data according to claim 1, wherein the generating an equipment health assessment report according to the physical characteristics and formulating an operation intervention strategy comprises: generating a device health assessment report comprising a wear stage, a progress speed and a risk level according to the physical characteristics; acquiring current load information, power grid demand prediction information and available standby capacity information of the generator set; according to the risk level in the equipment health evaluation report and the current load information of the generator set, primarily determining a load adjustment amplitude; according to the preliminarily determined load adjustment amplitude, the power grid demand prediction information and the available standby capacity information, evaluating the influence of the preliminarily determined load adjustment amplitude on the power grid stability; When the primarily determined load adjustment amplitude negatively affects the stability of the power grid, correcting the primarily determined load adjustment amplitude according to the power grid demand prediction information and the available reserve capacity information to obtain corrected load adjustment amplitude; and according to the corrected load adjustment amplitude, an operation intervention strategy is formulated, wherein the operation intervention strategy comprises a load adjustment suggestion, a maintenance plan suggestion and a cooling system parameter adjustment suggestion.
8. The method according to claim 7, wherein when the primarily determined load adjustment range adversely affects the grid stability, correcting the primarily determined load adjustment range according to the grid demand prediction information and the available backup capacity information to obtain a corrected load adjustment range, comprising: Acquiring the load adjustment amplitude; acquiring the power grid demand prediction information, the available standby capacity information and real-time power grid operation data; checking the accuracy of the power grid demand prediction information and the available spare capacity information according to the real-time power grid operation data; When the power grid demand prediction information or the available spare capacity information has significant deviation or hysteresis, real-time correction is carried out on the power grid demand prediction information and the available spare capacity information according to the real-time power grid operation data; Calculating stability indexes of power grid frequency, voltage and tide under different load adjustment situations according to the corrected power grid demand prediction information, the available standby capacity information and the preliminary load adjustment amplitude; and when the stability index exceeds a preset safety range, adjusting the preliminary load adjustment amplitude according to feedback of the stability index until the stability index meets the safety requirement and the corrected load adjustment amplitude is obtained.
9. The intelligent power generation operation control method based on equipment health data according to claim 8, wherein when the stability index exceeds a preset safety range, adjusting the preliminary load adjustment range according to feedback of the stability index until the stability index meets a safety requirement and a corrected load adjustment range is obtained, comprising: acquiring current operation mode and load structure information of the power grid; According to the current running mode of the power grid and the load structure information, the inertia level, damping characteristics and frequency modulation capacity of the power grid are evaluated; And adjusting the stability index safety range of the power grid frequency, the voltage and the tide based on the evaluated power grid inertia level, the damping characteristic and the frequency modulation capability, and generating a parameter set of a load adjustment strategy, wherein the parameter set comprises the speed, the step length and the priority of the adjustment direction of the load adjustment.
10. A power generation operation control system, characterized by comprising: The detection end is used for acquiring the internal operation information of the generator set and the external power grid operation information; the method comprises the steps of preprocessing the internal operation information and the external power grid operation information to obtain operation data and power grid data for analysis, identifying the current operation state of the generator set and the fluctuation state of the external power grid according to the operation data and the power grid data, and carrying out association analysis on vibration information and pressure information contained in the operation data to obtain association degree between the vibration information and the pressure information; The adjusting end is used for adjusting the judging standard of the association degree according to the current running state of the generator set and the fluctuation state of the external power grid; the output end is used for carrying out physical characteristic analysis on the vibration information and the pressure information under the adjusted discriminant standard to obtain frequency composition, time domain performance and physical characteristics of the vibration information and the pressure information, generating a device health evaluation report according to the physical characteristics, and formulating an operation intervention strategy.

Description

Intelligent power generation operation control method and system based on equipment health data Technical Field The invention relates to the technical field of power generation operation, in particular to an intelligent power generation operation control method and system based on equipment health data. Background In modern power plants, the operation control system of the generator set evaluates the health of the plant and adjusts the operating parameters by integrating the multisource sensor data. However, existing systems are designed based primarily on the relatively stable correlation characteristics of the generator set between physical quantities under typical operating conditions. Early wear of key parts such as generator rotor bearings may occur when the generator set is subjected to severe operating conditions such as high rotational speeds, high loads, etc. for a long period of time. This early wear is extremely weak and can cause asynchronous vibration and a small increase in local temperature, which in turn can lead to weak fluctuations in the pressure of the cooling water in the cooling system pipes. These weak vibration signals and pressure fluctuation signals caused by early wear are extremely low in amplitude and exhibit correlation characteristics very similar to the response of a generator set to accommodate the normal small fluctuations of the power grid. For example, transient frequency or voltage fluctuations of the power grid may lead to small adjustments of the unit output power, which in turn may lead to synchronous small changes in the bearing load and cooling system load, which produce vibrations and pressure signal characteristics with high similarity in intensity and periodicity to those produced by early wear. The "multi-source sensor information merging processing logic" of the existing system, when receiving these weak and correlated signals, due to the high similarity of the system response under normal working conditions, tends to wrongly attribute the signals to the "adaptive response of the unit to the normal fluctuation of the power grid", rather than the internal health problems caused by the early wear of the bearings. Such misjudgment results in the equipment health status evaluation system continuously outputting the evaluation result of "normal operation", so that the operation parameter adjustment rule set cannot perform preventive intervention against potential hidden danger. Finally, due to the fact that composite abnormal signals caused by early abrasion cannot be accurately identified, the power generation efficiency is slightly influenced in an imperceptible way, more importantly, bearing abrasion is continuously increased, the risk of future unplanned shutdown is accumulated, and the economic benefit of a power plant and the stability of a power grid are seriously influenced. In view of the above, there is a need in the art for improvements. Disclosure of Invention The invention provides an intelligent power generation operation control method and system based on equipment health data, and aims to solve the technical problems that when an early wear signal of a generator set is identified by an existing power generation operation control system, the early wear signal is easily misjudged as a self-adaptive response to normal fluctuation of a power grid, so that equipment health evaluation is inaccurate, preventive intervention cannot be timely performed, power generation efficiency is affected, and an unplanned shutdown risk is accumulated. The technical scheme of the application is as follows: In a first aspect, the application discloses a smart power generation operation control method based on equipment health data, which comprises the following steps: Acquiring internal operation information and external power grid operation information of a generator set; Preprocessing the internal operation information and the external power grid operation information to obtain operation data and power grid data for analysis; According to the operation data and the power grid data, the current operation state of the generator set and the fluctuation state of an external power grid are identified; Performing association analysis on vibration information and pressure information contained in the operation data to obtain association degree between the vibration information and the pressure information; according to the current running state of the generator set and the fluctuation state of an external power grid, adjusting a judgment standard for the association degree; Under the adjusted discrimination standard, carrying out physical characteristic analysis on the vibration information and the pressure information to obtain frequency constitution, time domain representation and physical characteristics of the vibration information and the pressure information; and generating a device health assessment report according to the physical characteristics, and formulating an ope