CN-121993351-A - Intelligent wind power generation method and system suitable for subway piston wind shaft

CN121993351ACN 121993351 ACN121993351 ACN 121993351ACN-121993351-A

Abstract

The invention discloses an intelligent wind power generation method and system suitable for a subway piston wind well, and relates to the field of parameter regulation, wherein the method and system are used for dynamically predicting future working conditions and target angles by collecting multi-source field data in real time, effectively eliminating invalid fine adjustment and false triggering caused by instantaneous data jitter by combining threshold judgment, repeated prediction and weighted smooth filtering mechanisms, precisely locking reasonable waiting time, relying on time-consuming models to precisely calculate and front-set planning regulation and control starting time, guaranteeing precise positioning of angle regulation advance, finally introducing a periodic power deviation closed-loop evaluation iteration mechanism, dynamically and adaptively optimizing regulation and control triggering threshold, prediction smoothing times and weight distribution core parameters, and continuously correcting adaptive deviation of initial parameters and complex variable working conditions, thereby remarkably improving system energy capturing efficiency, operation stability and long-term self-adaptive service performance under complex reciprocating airflow disturbance.

Inventors

FENG DI
LIU HAONAN
SU WENXUAN
WANG YUAN
REN JIE

Assignees

河海大学

Dates

Publication Date: 20260508
Application Date: 20260410

Claims (10)

1. An intelligent wind power generation method suitable for a subway piston wind shaft is characterized by comprising the following steps of: S1, setting a plurality of wind well air flow characteristic types and subway operation information types, and collecting wind well air flow characteristics, subway operation information and corresponding optimal blade angle data at a plurality of time points on the basis of the wind well air flow characteristic types and the subway operation information types; s2, constructing a final wind power generation blade angle mapping model based on the data acquired in the S1; S3, collecting time-consuming associated data of a plurality of angle adjustments in the process of carrying out angle adjustment on the current blade to be adjusted for a plurality of times in history, and constructing a final blade angle adjustment time-consuming mapping model based on the time-consuming associated data; S4, acquiring current wind well airflow characteristics, subway operation information and blade angle data in real time, predicting the airflow characteristics and the subway operation data at multiple time points in the future based on the data, and inputting the airflow characteristics and the subway operation data into a mapping model in S2 for mapping; S5, comparing the mapping result in S4 with the current initial blade angle, if the difference value meets the standard, determining the moment to be adjusted, repeatedly predicting and weighting and smoothing after the determination, and if the difference value still meets the standard, inputting the time-consuming related data of angle adjustment of the previous predicting moment of the moment to be adjusted into the mapping model in S3 for mapping and determining the starting adjustment moment, otherwise, taking no measure; S6, comparing actual and theoretical simulation average power deviation in a preset period, if the deviation exceeds the standard, updating a blade angle adjustment starting threshold value, initial prediction smoothing times and corresponding initial weight value sets, repeating S4 and S5, and calculating the average power deviation until the average power deviation reaches the standard, otherwise, not needing adjustment.
2. The intelligent wind power generation method suitable for the subway piston wind shaft according to claim 1, wherein the step S1 comprises the following steps: S11, setting a plurality of airflow characteristic types in a subway piston air shaft and a plurality of subway operation information types with influence on airflow to obtain an air shaft airflow characteristic type set and a subway operation information type set, wherein the air shaft airflow characteristic type set comprises real-time wind speed, wind direction, airflow time sequence change, airflow periodicity and reciprocative characteristics; S12, according to the wind well airflow characteristic type set and the subway operation information type set, various wind well airflow characteristic data, subway operation information data and optimal blade angle data corresponding to a wind power generation system corresponding to a plurality of time points in history are obtained, and a first historical wind well airflow characteristic data set, a first historical subway operation information data set and a historical wind power generation blade angle data set are obtained.
3. An intelligent wind power generation method suitable for a subway piston wind shaft according to claim 2, wherein S2 comprises the following steps: s21, constructing a mapping model which is input into wind well airflow characteristic data and subway operation information data and output into wind power generation blade angle data according to the first historical wind well airflow characteristic data set, the first historical subway operation information data set and the historical wind power generation blade angle data set, and obtaining a final wind power generation blade angle mapping model.
4. An intelligent wind power generation method suitable for a subway piston wind shaft according to claim 3, wherein S3 comprises the following steps: S31, selecting a current blade to be adjusted, and acquiring angle data before adjustment, angle data after adjustment, wind well air flow characteristic data, subway operation information data, working time of the current blade to be adjusted and corresponding time-consuming data for blade angle adjustment, which correspond to the current blade to be adjusted in the angle adjustment process for a plurality of times in history, according to the wind well air flow characteristic type set and the subway operation information type set, so as to obtain an angle data set before adjustment of the historical blade, an angle data set after adjustment of the historical blade, a second historical wind well air flow characteristic data set, a second historical subway operation information data set, an operating time data set of the historical blade and a time-consuming data set for angle adjustment of the historical blade.
5. The intelligent wind power generation method for a subway piston wind shaft according to claim 4, wherein the step S3 further comprises the steps of: S32, constructing a mapping model which is input into angle data before blade adjustment, angle data after blade adjustment, wind well air flow characteristic data, subway operation information data, and time-consuming data after blade adjustment according to the angle data set before blade adjustment, the angle data set after blade adjustment, the second historical wind well air flow characteristic data set, the second historical subway operation information data set, the historical blade operated duration data set and the historical blade angle adjustment time-consuming data set, and outputting the mapping model into the blade angle adjustment time-consuming data to obtain a final blade angle adjustment time-consuming mapping model.
6. The intelligent wind power generation method for a subway piston wind shaft according to claim 5, wherein S4 comprises the following steps: S41, acquiring various airflow characteristic data, subway operation information data and blade angle data of a current wind power generation system in a plurality of groups of current subway piston wind wells in real time to obtain a current real-time wind well airflow characteristic data set, a current real-time subway operation information data set and a current initial blade angle data; S42, respectively inputting various airflow characteristic data and subway operation information data of each time point in the future wind well airflow characteristic data set and the future subway operation information data set into a final wind power generation blade angle mapping model for mapping, and obtaining a future blade angle data set.
7. The intelligent wind power generation method for a subway piston wind shaft according to claim 6, wherein S5 comprises the following steps: S51, setting a blade angle adjustment starting threshold value and an initial blade angle prediction smoothing frequency, and setting a weight value corresponding to each prediction according to the initial blade angle prediction smoothing frequency to obtain a current initial angle prediction weight value set; If the absolute value of the difference between the future blade angle data and the current initial blade angle data is larger than or equal to the blade angle adjustment starting threshold value in the future blade angle data set, taking the corresponding moment of the future blade angle data as the future moment of the blade to be adjusted; S52, correspondingly multiplying and summing the predicted data in the current blade angle predicted data set to be smoothed and the weight value in the current initial angle predicted weight value set to obtain current smoothed blade angle predicted data, executing S53 if the absolute value of the difference between the current smoothed blade angle predicted data and the current initial blade angle data is greater than or equal to the blade angle adjustment starting threshold value, otherwise, not taking measures; S53, acquiring working time length data of the blades of the current wind power generation system at the future moment of blade adjustment to obtain the working time length data of the current blades; inputting the current initial blade angle data, the current smooth back blade angle prediction data, various airflow characteristic data at the previous prediction time of the future time of blade adjustment, subway operation information data and the current working time length data of the blade into a final blade angle adjustment time-consuming mapping model for mapping to obtain current blade adjustment time-consuming data; And taking the time corresponding to the difference value of the time-consuming data of the current blade adjustment and the future time of the blade to be adjusted as the current blade adjustment starting time.
8. The intelligent wind power generation method for a subway piston wind shaft according to claim 7, wherein the step S6 comprises the following steps: S61, setting a current blade angle adjustment effect statistics period, based on the S4 and the S5, counting average power data of a current wind power generation system in the period according to the current blade angle adjustment effect statistics period to obtain current initial average power data, and calculating an absolute value of a difference value between the current initial average power data and average power data obtained by theoretical optimal angle simulation in the current blade angle adjustment effect statistics period to obtain current initial average power deviation data.
9. The intelligent wind power generation method for a subway piston wind shaft according to claim 8, wherein the step S6 further comprises the steps of: S62, setting a current average power deviation threshold value, if the current initial average power deviation data is larger than or equal to the current average power deviation threshold value, adjusting all weight values in a blade angle adjustment starting threshold value, initial blade angle prediction smoothing times and current initial angle prediction weight value set, and repeating S4, S5 and S61 until the current initial average power deviation data is smaller than the current average power deviation threshold value, so as to obtain a blade angle adjustment starting final threshold value, a final blade angle prediction smoothing times and a current final angle prediction weight value set; And S63, starting a final threshold value, predicting the smooth times of the final blade angle according to the blade angle adjustment, and performing angle adjustment operation on the blades of the current wind power generation system by using the current final angle predicting weight value set.
10. A system for realizing the intelligent wind power generation method suitable for the subway piston wind well according to any one of claims 1-9, which is characterized by comprising a historical blade angle data acquisition module, a wind power generation blade angle mapping model construction module, a blade angle adjustment time-consuming mapping model construction module, a future blade angle mapping module, a current blade adjustment time-consuming mapping module and a blade angle adjustment reference value adjustment module; the historical blade angle data acquisition module is used for setting a plurality of wind well air flow characteristic types and subway operation information types, and acquiring wind well air flow characteristics, subway operation information and corresponding optimal blade angle data at a plurality of time points in history based on the wind well air flow characteristic types and the subway operation information types; The wind power generation blade angle mapping model construction module constructs a final wind power generation blade angle mapping model based on the data acquired by the historical blade angle data acquisition module; The blade angle adjustment time-consuming mapping model construction module acquires the angle before and after adjustment, the air flow characteristics of the air shaft, subway operation information, the working time length and adjustment time-consuming data in the process of adjusting the angle of the current blade to be adjusted for a plurality of times in the history, and constructs a final blade angle adjustment time-consuming mapping model based on the angle; the future blade angle mapping module acquires current wind well airflow characteristics, subway operation information and blade angle data in real time, predicts airflow characteristics and subway operation data at multiple time points in the future based on the data, and inputs the airflow characteristics and the subway operation data into the mapping model in the wind power generation blade angle mapping model construction module for mapping; The current blade adjustment time-consuming mapping module sets a blade angle adjustment starting threshold value, initial prediction smoothing times and corresponding initial weight value sets, and compares mapping results in the future blade angle mapping module with the current initial blade angle; if the difference value meets the standard, determining a moment to be regulated, repeatedly predicting and carrying out weighted smoothing, and if the difference value still meets the standard, inputting corresponding angles before and after regulation, wind well air flow characteristics, subway operation information and working time length into a mapping model in a blade angle regulation time-consuming mapping model construction module for mapping and determining a starting regulation moment, otherwise, taking no measures; The blade angle adjustment reference value adjustment module compares the actual and theoretical simulation average power deviation in a preset period, adjusts the blade angle adjustment starting threshold value, the initial prediction smoothing times and the corresponding initial weight value set if the deviation exceeds the standard, repeatedly executes the future blade angle mapping module, the current blade adjustment time-consuming mapping module and the calculation average power deviation until reaching the standard, otherwise, does not need adjustment.

Description

Intelligent wind power generation method and system suitable for subway piston wind shaft Technical Field The invention belongs to the field of parameter regulation and control, and particularly relates to an intelligent wind power generation method and system suitable for a subway piston wind shaft. Background The method is characterized in that the optimal blade angle under the coupling of the complex reciprocating airflow and the dynamic train is difficult to accurately predict in the intelligent wind power generation process of the subway piston wind shaft at present, energy peaks caused by lag go wrong of regulation and control or energy waste caused by rapid and erroneous regulation are easy to occur, actual regulation time consumption under different working conditions and in the aging state of the blade cannot be quantified, in addition, regulation unset or idle waiting is difficult to accurately plan starting time, in addition, tiny invalid regulation is frequently performed due to the fact that the current blade angle regulation process is easy to be interfered by instantaneous data sampling shake, and further mechanical abrasion is aggravated, useless energy consumption is increased, and running smoothness is reduced. Disclosure of Invention Aiming at the problems in the related art, the invention provides an intelligent wind power generation method and system suitable for a subway piston wind shaft, so as to overcome the technical problems in the prior art. In order to solve the technical problems, the invention is realized by the following technical scheme: the invention relates to an intelligent wind power generation method suitable for a subway piston wind shaft, which comprises the following steps: S1, setting a plurality of wind well air flow characteristic types and subway operation information types, and collecting wind well air flow characteristics, subway operation information and corresponding optimal blade angle data at a plurality of time points on the basis of the wind well air flow characteristic types and the subway operation information types; s2, constructing a final wind power generation blade angle mapping model based on the data acquired in the S1; S3, collecting time-consuming associated data of a plurality of angle adjustments in the process of carrying out angle adjustment on the current blade to be adjusted for a plurality of times in history, and constructing a final blade angle adjustment time-consuming mapping model based on the time-consuming associated data; S4, acquiring current wind well airflow characteristics, subway operation information and blade angle data in real time, predicting the airflow characteristics and the subway operation data at multiple time points in the future based on the data, and inputting the airflow characteristics and the subway operation data into a mapping model in S2 for mapping; s5, comparing the mapping result in S4 with the current initial blade angle, if the difference value meets the standard, determining the moment to be adjusted, repeatedly predicting and carrying out weighted smoothing, and if the difference value still meets the standard, inputting the corresponding angle adjustment time-consuming associated data into the mapping model in S3 for mapping and determining the starting adjustment moment, otherwise, taking no measure; S6, comparing actual and theoretical simulation average power deviation in a preset period, if the deviation exceeds the standard, updating a blade angle adjustment starting threshold value, initial prediction smoothing times and corresponding initial weight value sets, repeating S4 and S5, and calculating the average power deviation until the average power deviation reaches the standard, otherwise, not needing adjustment. Preferably, the step S1 includes the steps of: S11, obtaining a wind-shaft airflow characteristic type set and a subway operation information type set, wherein the wind-shaft airflow characteristic type set comprises real-time wind speed, wind direction, airflow time sequence change, airflow periodicity, reciprocative characteristics and the like, and the subway operation information type set comprises a subway train operation schedule, train arrival time, train operation time sequence, time nodes of a train entering and exiting a tunnel and the like; S12, according to the wind well airflow characteristic type set and the subway operation information type set, acquiring various wind well airflow characteristic data, subway operation information data and optimal blade angle data corresponding to a wind power generation system corresponding to a plurality of time points in history, and acquiring a first historical wind well airflow characteristic data set, a first historical subway operation information data set and a historical wind power generation blade angle data set; And the airflow characteristic data, subway operation information data and matched optimal blade angle data corresp