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CN-122006486-A - Control optimization method of ultrafiltration system

CN122006486ACN 122006486 ACN122006486 ACN 122006486ACN-122006486-A

Abstract

The invention provides an ultrafiltration system control optimization method, which relates to the technical field of water treatment and comprises the steps of taking a chemical cleaning interval as an operation period, collecting data such as period water yield Q, ton water power consumption E and the like after each operation period is finished, calculating comprehensive operation scores S according to a predefined scoring function model S=w 1 •F(Q)+w 2 . G (E), comparing the S with a preset scoring threshold, and carrying out differential adjustment (maintenance, fine adjustment or large adjustment) on control parameters of the next period according to a comparison result. The scoring function model can be extended to a multi-objective form s=w 1 •F(Q)+w 2 •G(E)+w 3 .h (Δ) that contains a film state score H (Δ). The weight coefficient w 1 、w 2 can be dynamically configured according to the water inlet pollution index SDI value through a mapping relation. According to the invention, through long-period integral evaluation and multi-objective scoring, the self-adaptive optimization of the cleaning strategy is realized, and the water production capacity of the ultrafiltration system can be improved, the energy consumption is reduced and the membrane pollution is delayed.

Inventors

  • WANG JINLONG
  • WU DI
  • WANG CHAO
  • LIU TAO
  • XIE YONGMING
  • SUN LEI

Assignees

  • 青岛锦龙弘业环保有限公司

Dates

Publication Date
20260512
Application Date
20260213

Claims (9)

  1. 1. The control optimization method of the ultrafiltration system is characterized by comprising the following steps of: S1, executing control parameters of an ultrafiltration system in a current operation period, and collecting operation result data of the current operation period, wherein the operation period is a time period between two adjacent chemical cleaning steps, the control parameters comprise parameters for adjusting physical cleaning operation characteristics in the operation period, and the operation result data comprise total water yield Q of the current operation period and ton water electricity consumption E of the current operation period; S2, calculating a comprehensive operation score S of the current period according to a predefined scoring function model based on the operation result data of the current operation period, wherein the scoring function model is as follows: S=w 1 •F(Q)+w 2 •G(E); Wherein F (Q) is a water yield score, G (E) is an energy consumption score, w 1 is a water yield weight coefficient, w 2 is an energy consumption weight coefficient, and w 1 +w 2 =1; S3, comparing the comprehensive operation score S with a preset score threshold, wherein the score threshold comprises a first score threshold S_high and a second score threshold S_low, and S_high > S_low; S4, adjusting control parameters of the next operation period according to the comparison result: If S is more than or equal to S_high, keeping the control parameters unchanged in the next operation period; If S_low is less than or equal to S < S_high, fine tuning the control parameters according to a first preset adjustment rule in the next operation period; And if S is less than S_low, performing larger amplitude adjustment on the control parameter according to a second preset adjustment rule in the next operation period.
  2. 2. The ultrafiltration system control optimization method of claim 1, wherein the control parameters further comprise parameters for controlling a maintenance chemical cleaning process.
  3. 3. The ultrafiltration system control optimization method according to claim 1, wherein the water yield score term F (Q) =q/q_ref, the energy consumption score term G (E) =1-E/e_ref, e_ref is a ton water consumption reference value, q_ref is a water yield reference value, and the method for evaluating q_ref and e_ref includes any one of the following: adopting a preset fixed constant; Or alternatively Adopting an arithmetic average value of data corresponding to the first M running periods, wherein M is more than or equal to 3; Or alternatively A moving average of the data corresponding to the first M run periods is used.
  4. 4. A method of optimizing control of an ultrafiltration system according to claim 1 or 3, wherein said operational result data further comprises a rate of transmembrane pressure differential increase Δ over a current operational period; accordingly, the scoring function model is: S=w 1 •F(Q)+w 2 •G(E)+w 3 •H(Δ); Where H (Δ) is a film state score term, w 3 is a film state weight coefficient, and w 1 +w 2 +w 3 =1.
  5. 5. The method according to claim 4, wherein the membrane state score H (Δ) =1- Δ/Δ_ref, Δ_ref is a reference value of the membrane permeation pressure difference increase rate, and the value of Δ_ref is obtained by experimental calibration according to the material and the design service life of the ultrafiltration membrane element.
  6. 6. The ultrafiltration system control optimization method according to claim 1, wherein the determination method of the water yield weight coefficient w 1 and the energy consumption weight coefficient w 2 comprises: Acquiring a pollution index SDI of the water quality of the inlet water of the ultrafiltration system; Determining a group of intermediate weight coefficients w 1 _temp and w 2 _temp according to a preset pollution interval to which the pollution index SDI belongs, wherein the preset pollution interval is divided into at least three continuous pollution intervals, and each pollution interval corresponds to a group of preset intermediate weight coefficients w 1 _temp and w 2 _temp; normalizing the intermediate weight coefficient to obtain a final weight coefficient: w 1 =w 1 _temp/(w 1 _temp+w 2 _temp); w 2 =w 2 _temp/( w 1 _temp+w 2 _temp)。
  7. 7. the ultrafiltration system control optimization method according to claim 4 or 5, wherein the membrane state weight coefficient w 3 is valued by any one of the following methods: adopting a preset fixed constant; Or alternatively Determining according to the accumulated running time of the ultrafiltration membrane element; Or alternatively Is determined from the long-term trend of the transmembrane pressure differential increase rate delta in the historical operating period.
  8. 8. The ultrafiltration system control optimization method according to claim 1 or 2, wherein the parameters for adjusting the physical cleaning operation characteristics include a backwash cycle T and a backwash duration T; Correspondingly, the first preset regulation rule is that the backwashing period T is regulated to be T x k 1 , and the backwashing time length T is regulated to be T x k 2 , wherein k 1 ≤1.05,0.95≤k 2 is more than or equal to 0.95 and less than or equal to 1.05, and k 1 and k 2 are not simultaneously 1; The second preset regulation rule is that the backwashing period T is regulated to be T x K 1 , and the backwashing duration T is regulated to be T x K 2 , wherein K 1 ≤0.95,1.05≤K 2 is more than or equal to 0.8 and less than or equal to 1.2.
  9. 9. The method for optimizing control of an ultrafiltration system of claim 1, wherein said calibrating said first scoring threshold S_high and said second scoring threshold S_low according to a predetermined statistical updating rule after continuously running for N running periods comprises: Updating the first scoring threshold value s_high to be alpha times the highest value of the comprehensive operation score S in the past N operation periods, wherein 0< alpha <1; the second scoring threshold s_low is updated to be β times the average of the composite running scores S over the past N running cycles, where 0< β <1.

Description

Control optimization method of ultrafiltration system Technical Field The invention relates to the technical field of water treatment, in particular to an ultrafiltration system control optimization method. Background In the field of ultrafiltration water treatment, the running performance of ultrafiltration systems is closely related to the cleaning strategy. At present, the main control mode of the ultrafiltration system mainly depends on two types, namely, a fixed backwash period, a fixed backwash duration and other parameters are adopted for operation, and the control mode is manually adjusted by an operator according to experience. However, the two modes have obvious limitations that the fixed parameter operation cannot adapt to the change of the water quality, the water temperature and the membrane pollution state, often causes insufficient cleaning (causing aggravation of membrane pollution and reduction of water yield) or excessive cleaning (causing shortening of water yield time and increase of energy consumption and water consumption), the manual experience adjustment is highly dependent on personal experience, response is lagged, and a plurality of mutually restricted targets such as 'water yield', 'energy consumption', 'membrane long-term health' and the like are difficult to quantitatively balance, so that an operation strategy is unstable, and the whole life cycle cost is high. The prior art lacks a set of models capable of quantitatively evaluating the comprehensive operation effect of a complete operation period (namely, the time period between two adjacent chemical cleaning) and cannot automatically and intelligently guide the optimization adjustment of the operation parameters of the next operation period based on the evaluation result. Therefore, the ultrafiltration system runs in a non-optimal state for a long time, and the energy efficiency and the economic benefit of the ultrafiltration system are restricted from being further improved. Disclosure of Invention Aiming at the problems existing in the prior art, the control optimization method of the ultrafiltration system comprises the following steps: S1, executing control parameters of an ultrafiltration system in a current operation period, and collecting operation result data of the current operation period, wherein the operation period is a time period between two adjacent chemical cleaning steps, the control parameters comprise parameters for adjusting physical cleaning operation characteristics in the operation period, and the operation result data comprise total water yield Q of the current operation period and ton water electricity consumption E of the current operation period; S2, calculating a comprehensive operation score S of the current period according to a predefined scoring function model based on the operation result data of the current operation period, wherein the scoring function model is as follows: S=w1•F(Q)+w2•G(E); Wherein F (Q) is a water yield score, G (E) is an energy consumption score, w 1 is a water yield weight coefficient, w 2 is an energy consumption weight coefficient, and w 1+w2 =1; S3, comparing the comprehensive operation score S with a preset score threshold, wherein the score threshold comprises a first score threshold S_high and a second score threshold S_low, and S_high > S_low; S4, adjusting control parameters of the next operation period according to the comparison result: If S is more than or equal to S_high, keeping the control parameters unchanged in the next operation period; If S_low is less than or equal to S < S_high, fine tuning the control parameters according to a first preset adjustment rule in the next operation period; And if S is less than S_low, performing larger amplitude adjustment on the control parameter according to a second preset adjustment rule in the next operation period. Optionally, the control parameters further comprise parameters for controlling a maintenance chemical cleaning process. Optionally, the water yield score term F (Q) =q/q_ref, the energy consumption score term G (E) =1-E/e_ref, e_ref is a ton water consumption reference value, q_ref is a water yield reference value, and the method for evaluating q_ref and e_ref includes any one of the following: adopting a preset fixed constant; Or alternatively Adopting an arithmetic average value of data corresponding to the first M running periods, wherein M is more than or equal to 3; Or alternatively A moving average of the data corresponding to the first M run periods is used. Optionally, the operation result data further includes a transmembrane pressure difference increase rate delta in the current operation period; accordingly, the scoring function model is: S=w1•F(Q)+w2•G(E)+w3•H(Δ); Where H (Δ) is a film state score term, w 3 is a film state weight coefficient, and w 1+w2+w3 =1. Optionally, the membrane state scoring term H (Δ) =1- Δ/Δ_ref, where Δ_ref is a reference value of the transmembrane pressure differe