CN107247994B - Fuzzy modeling method for desulfurization efficiency of tray tower desulfurization device - Google Patents
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Abstract
本发明公开了一种托盘塔湿法脱硫装置脱硫效率的模糊建模方法,包括如下步骤:首先选取烟气量、入口烟气中SO2浓度、液气比和吸收塔的pH值作为模糊模型的输入变量、选取托盘塔的脱硫效率作为输出变量;选用三角形隶属函数,确定各输入输出变量的语言变量论域和系统的模糊规则,计算模糊关系矩阵,解模糊并建立脱硫效率的模糊模型;其次根据烟气量、入口烟气中SO2浓度、液气比、吸收塔的pH值对脱硫效率的影响关系,修正模糊规则;最后选取正常运行工况的多组数据作为校验样本、其它时段的多组数据作为测试样本,将样本量化并进行脱硫效率仿真输出,通过对比分析来预调参数;本发明计算精度高、软件负荷小,可对系统的脱硫效率进行有效预测和调控。
The invention discloses a fuzzy modeling method for the desulfurization efficiency of a tray tower wet desulfurization device. Select the input variable of the tray tower as the output variable; select the triangular membership function to determine the linguistic variable universe of each input and output variable and the fuzzy rules of the system, calculate the fuzzy relationship matrix, solve the fuzzy and establish the fuzzy model of the desulfurization efficiency; Secondly, according to the influence of flue gas volume, SO 2 concentration in inlet flue gas, liquid-gas ratio, and pH value of absorption tower on desulfurization efficiency, the fuzzy rules are revised; Multiple sets of data in a period are used as test samples, the samples are quantified and desulfurization efficiency simulation output is performed, and parameters are pre-adjusted through comparative analysis; the invention has high calculation accuracy and small software load, and can effectively predict and control the desulfurization efficiency of the system.
Description
技术领域technical field
本发明涉及脱硫系统控制方法,尤其涉及一种托盘塔湿法脱硫装置脱硫效率的模糊建模方法。The invention relates to a desulfurization system control method, in particular to a fuzzy modeling method for desulfurization efficiency of a tray tower wet desulfurization device.
背景技术Background technique
热托盘塔脱硫工艺在吸收塔的喷淋层下方或喷淋层之间增设一块或多块穿流孔板托盘,烟气进入吸收塔后经托盘整流均匀分布到整个吸收塔截面上,强化传质和提高吸收剂的利用率,降低了液气比,脱硫效率可达到99%以上,同时降低了循环浆液泵的流量和功耗。具有效率高、能耗低、运行稳定、改造便利等优点。目前国内托盘塔脱硫装置应用越来越多,在未来具有较好的应用前景。In the hot tray tower desulfurization process, one or more through-flow orifice trays are added under the spray layer of the absorption tower or between the spray layers. Improve the quality of the absorbent and improve the utilization rate of the absorbent, reduce the liquid-gas ratio, the desulfurization efficiency can reach more than 99%, and at the same time reduce the flow rate and power consumption of the circulating slurry pump. It has the advantages of high efficiency, low energy consumption, stable operation, and convenient transformation. At present, there are more and more applications of domestic tray tower desulfurization devices, and it has a good application prospect in the future.
现有的托盘塔脱硫系统研究大多停留在对托盘装置的研究和脱硫效率的理论研究,例如通过改变托盘开孔区域和开孔率来增强烟气流动均匀性,对于脱硫系统运行进行在线监控的研究较少。在实际运行过程中,脱硫系统运行工况时常恶化,一旦没有及时发现问题,将不利于脱硫效率达标排放,对全厂造成巨大经济损失,故运行工况须控制在一定范围内。为了保证单元机组的安全连续运行,建立准确的湿法烟气脱硫效率预测模型来指导脱硫系统优化运行具有重要意义。同时脱硫效率模拟模型的算法复杂,对于实际工程应用复杂的非线性系统数学建模也比较困难。Most of the existing research on tray tower desulfurization systems remain in the study of tray devices and theoretical research on desulfurization efficiency. Less research. In the actual operation process, the operating conditions of the desulfurization system often deteriorate. Once the problem is not found in time, it will be unfavorable for the desulfurization efficiency to reach the standard emission and cause huge economic losses to the whole plant. Therefore, the operating conditions must be controlled within a certain range. In order to ensure the safe and continuous operation of the unit unit, it is of great significance to establish an accurate wet flue gas desulfurization efficiency prediction model to guide the optimal operation of the desulfurization system. At the same time, the algorithm of the simulation model of desulfurization efficiency is complex, and it is also difficult to mathematically model complex nonlinear systems in practical engineering applications.
发明内容SUMMARY OF THE INVENTION
发明目的:为了有效预测托盘塔脱硫系统的脱硫效率,在电厂复杂变化工况条件下对脱硫效率进行实时监测并对工况参数进行预调以防运行条件恶化,本发明提供了一种托盘塔湿法脱硫装置脱硫效率的模糊建模方法。Purpose of the invention: In order to effectively predict the desulfurization efficiency of the tray tower desulfurization system, monitor the desulfurization efficiency in real time under the complex changing working conditions of the power plant, and pre-adjust the working condition parameters to prevent the deterioration of the operating conditions, the present invention provides a tray tower. Fuzzy modeling method for desulfurization efficiency of wet desulfurization unit.
技术方案:本发明所述的一种托盘塔湿法脱硫装置脱硫效率的模糊建模方法,包括以下步骤:Technical solution: The fuzzy modeling method for the desulfurization efficiency of a tray tower wet desulfurization device according to the present invention includes the following steps:
(1)根据电厂托盘塔湿法烟气脱硫装置的实际运行情况,选取烟气量V、入口烟气中SO2浓度N、液气比E、吸收塔的pH值P作为模糊模型的输入变量,选取托盘塔的脱硫效率U为输出变量;(1) According to the actual operation of the tray tower wet flue gas desulfurization device in the power plant, the flue gas volume V, the SO 2 concentration N in the inlet flue gas, the liquid-gas ratio E, and the pH value P of the absorption tower are selected as the input variables of the fuzzy model , select the desulfurization efficiency U of the tray tower as the output variable;
(2)设定输入变量和输出变量的隶属函数为三角形隶属函数,将烟气量V、入口烟气中SO2浓度N、液气比E和脱硫效率U的语言变量论域定为[-n1,n1]、吸收塔的pH值语言变量论域定为[-n2,n2],其中,n1和n2均为正整数;通过长期的现场跟踪实验以及积累大量专家知识和脱硫文献资料,总结出模糊诊断系统的控制规则库;采用Mamdani算法进行模糊推理,选择质心法进行解模糊,建立脱硫效率的模糊模型;(2) The membership functions of the input variables and output variables are set as triangular membership functions, and the linguistic variables of the flue gas volume V, the SO 2 concentration N in the inlet flue gas, the liquid-gas ratio E and the desulfurization efficiency U are set as [- n 1 , n 1 ], the language variable domain of pH value of the absorption tower is set as [-n 2 , n 2 ], where n 1 and n 2 are both positive integers; through long-term field tracking experiments and accumulation of a large number of expert knowledge And desulfurization literature, summed up the control rule base of the fuzzy diagnosis system; used Mamdani algorithm to carry out fuzzy reasoning, selected the centroid method to defuzzify, and established the fuzzy model of desulfurization efficiency;
(2a)烟气量V、入口SO2浓度N、液气比E和脱硫效率U各分别取负大、负小、零、正小、正大五个模糊子集,表示为NB、NS、ZE、PS、PB;所述吸收塔的pH值P分别取小、中、大三个模糊子集,表示为L、Z、H。(2a) Five fuzzy subsets of flue gas volume V, inlet SO 2 concentration N, liquid-gas ratio E and desulfurization efficiency U are taken as negative large, negative small, zero, positive small, and positive large, respectively, denoted as NB, NS, ZE , PS, PB; the pH value P of the absorption tower is taken as three fuzzy subsets of small, medium and large respectively, expressed as L, Z, H.
(2b)模糊规则的模糊条件语句为“if A and B then C”,每一条规则可以建立一个模糊关系Ri,采用CRI合成法,得到该模型的模糊关系矩阵R计算公式如下:(2b) The fuzzy conditional statement of the fuzzy rule is "if A and B then C", each rule can establish a fuzzy relation R i , and the CRI synthesis method is used to obtain the fuzzy relation matrix R of the model. The calculation formula is as follows:
C=(A×B)οRC=(A×B)οR
μR(x,yz)=m ax[μA(x)∩μB(y)∩μc(z)]μ R (x, yz)=m ax[μ A (x)∩μ B (y)∩μ c (z)]
若已知系统的输入e0对应模糊变量E*,可得到模糊输出变量U*:If the input e 0 of the known system corresponds to the fuzzy variable E*, the fuzzy output variable U* can be obtained:
U*=E*οRU*=E*οR
(3)从电厂托盘塔脱硫数据库中导出在线监测小时数据,排除脱硫停运和仪表故障原因造成的异常数据,探究托盘塔脱硫系统中烟气量V、入口烟气中SO2浓度N、液气比E、吸收塔的pH值P对脱硫效率U的影响关系。(3) Export the online monitoring hourly data from the tray tower desulfurization database of the power plant, exclude abnormal data caused by desulfurization outages and instrument failures, and explore the flue gas volume V in the tray tower desulfurization system, the SO 2 concentration N in the inlet flue gas, liquid concentration The relationship between the gas ratio E and the pH value P of the absorption tower on the desulfurization efficiency U.
(4)选取正常运行工况的多组数据作为校验样本,其它时段的多组数据作为测试样本,利用步骤(2)中所述模糊模型,将样本量化后通过编写隶属度计算程序,分别对校验样本进行模型测试校验,并再次修正模糊规则库,得到125条脱硫系统的模糊规则;利用修改后的模型对测试样本进行脱硫效率仿真输出,通过对比分析来预调参数。(4) Select multiple sets of data in normal operating conditions as verification samples, and multiple sets of data in other periods as test samples, using the fuzzy model described in step (2) to quantify the samples by writing a membership calculation program, respectively. Model test and verify the verification samples, and amend the fuzzy rule base again to obtain 125 fuzzy rules of the desulfurization system; use the modified model to simulate the desulfurization efficiency of the test samples, and pre-adjust the parameters through comparative analysis.
有益效果:本发明与现有技术相比,具有如下显著优势:本发明能在电厂复杂变化工况条件下,对托盘塔脱硫系统的脱硫效率进行有效预测和实时监测,计算速度快、精度高,能够及时进行工况参数的预调,有助于托盘塔脱硫系统优化运行和节能降耗。Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: the present invention can effectively predict and monitor the desulfurization efficiency of the tray tower desulfurization system under the complex changing working conditions of the power plant, with fast calculation speed and high precision , which can pre-adjust the working parameters in time, which is helpful to optimize the operation of the tray tower desulfurization system and save energy and reduce consumption.
附图说明Description of drawings
图1为本发明的模糊建模方法流程图;Fig. 1 is the flow chart of the fuzzy modeling method of the present invention;
图2为本发明的托盘塔湿法脱硫装置脱硫效率模糊模型结构图;Fig. 2 is the fuzzy model structure diagram of the desulfurization efficiency of the tray tower wet desulfurization device of the present invention;
图3为本发明的校验样本脱硫效率仿真输出与实际值比较图;Fig. 3 is the comparison diagram of the simulation output of the desulfurization efficiency of the verification sample of the present invention and the actual value;
图4为本发明的测试样本脱硫效率仿真输出与实际值比较图。FIG. 4 is a comparison diagram of the simulation output of the desulfurization efficiency of the test sample of the present invention and the actual value.
具体实施方式Detailed ways
下面结合实施例和附图对本发明的技术方案作进一步详细说明。The technical solutions of the present invention will be described in further detail below with reference to the embodiments and the accompanying drawings.
以某热电厂改造后的托盘塔脱硫系统为例,如图1示,本发明的一种托盘塔湿法脱硫装置脱硫效率的模糊建模方法,具体包括以下步骤:Taking the reformed tray tower desulfurization system of a thermal power plant as an example, as shown in Figure 1, a fuzzy modeling method for the desulfurization efficiency of a tray tower wet desulfurization device of the present invention specifically includes the following steps:
(1)对电厂托盘塔湿法脱硫系统运行参数进行采集,选取烟气量V、入口烟气中SO2浓度N、液气比E、吸收塔的pH值P作为模糊模型的输入变量,托盘塔的脱硫效率U为输出变量,如图2所示;(1) Collect the operating parameters of the wet desulfurization system of the tray tower in the power plant, select the flue gas volume V, the SO 2 concentration N in the inlet flue gas, the liquid-gas ratio E, and the pH value P of the absorption tower as the input variables of the fuzzy model. The desulfurization efficiency U of the tower is the output variable, as shown in Figure 2;
对电厂采集的数据进行模糊化处理,利用量化因子对运行参数进行模糊化处理,将连续论域为[xL,xH]量化为整数集合{-n,-n+1,…,-1,0,1,…,n-1,n},则量化因子k:The data collected by the power plant is fuzzified, the operating parameters are fuzzified by the quantization factor, and the continuous universe [x L , x H ] is quantized into a set of integers {-n,-n+1,…,-1 ,0,1,…,n-1,n}, then the quantization factor k:
其中xL和xH分别为连续域的最大值和最小值,n为设定整数,本发明分别取n=2和n=4;Wherein x L and x H are the maximum and minimum values of the continuous domain respectively, n is a set integer, and the present invention takes n=2 and n=4 respectively;
再通过下式将连续域中的元素x转换为离散论域中的元素X:Then convert the element x in the continuous domain to the element X in the discrete universe by the following formula:
式中,<>代表对X采用四舍五入法取整运算,X为实际数据量化后的值,作为输入数据使用。In the formula, <> represents the rounding method for X, and X is the quantized value of the actual data, which is used as the input data.
(2)设定运行参数(输入变量)和脱硫效率(输出变量)的隶属函数为三角形隶属函数,将烟气量V、入口烟气中SO2浓度N、液气比E和脱硫效率U的语言变量论域定为[-4,4]、吸收塔的pH值P的语言变量论域定为[-2,2];通过长期的现场跟踪实验包括模型测试和校验(将结果和实际电厂数据对比修改),以及积累大量专家知识和脱硫文献资料,总结出了包括125条模糊规则的模糊诊断系统控制规则库;( 2 ) Set the membership functions of operating parameters (input variables) and desulfurization efficiency (output variables) as triangular membership functions. The linguistic variable universe is set as [-4, 4], and the linguistic variable universe of the pH value P of the absorption tower is set as [-2, 2]; Power plant data comparison and modification), and accumulated a lot of expert knowledge and desulfurization literature, summed up a fuzzy diagnosis system control rule base including 125 fuzzy rules;
采用Mamdani算法进行模糊推理,采用centroid(重心法)解模糊,建立脱硫效率的模糊模型;Mamdani algorithm is used for fuzzy reasoning, centroid (center of gravity method) is used to solve the fuzzy, and the fuzzy model of desulfurization efficiency is established;
(2a)烟气量V、入口SO2浓度N、液气比E和脱硫效率U分别取负大(NB)、负小(NS)、零(ZE)、正小(PS)、正大(PB)五个模糊子集;吸收塔的pH值P分别取小(L)、中(Z)、大(H)三个模糊子集;(2a) The flue gas volume V, the inlet SO 2 concentration N, the liquid-gas ratio E and the desulfurization efficiency U are taken as negative large (NB), negative small (NS), zero (ZE), positive small (PS), and positive large (PB), respectively. ) five fuzzy subsets; the pH value P of the absorption tower takes three fuzzy subsets of small (L), medium (Z) and large (H) respectively;
(2b)模糊规则的模糊条件语句“if A and B then C”,每一条规则可以建立一个模糊关系Ri,采用CRI合成法,得到该模型的模糊关系矩阵R计算公式如下:(2b) The fuzzy conditional statement "if A and B then C" of the fuzzy rules, each rule can establish a fuzzy relationship R i , and the CRI synthesis method is used to obtain the fuzzy relationship matrix R of the model. The calculation formula is as follows:
C=(A×B)οRC=(A×B)οR
μR(x,y,z)=m ax[μA(x)∩μB(y)∩μc(z)]μ R (x, y, z)=m ax[μ A (x)∩μ B (y)∩μ c (z)]
若已知系统的输入e0对应模糊变量E*,可得到模糊输出变量U*:If the input e 0 of the known system corresponds to the fuzzy variable E*, the fuzzy output variable U* can be obtained:
U*=E*οRU*=E*οR
(3)排除脱硫停运和仪表故障原因造成的异常数据,探究托盘塔脱硫系统中烟气量、入口烟气中SO2浓度、液气比、吸收塔的pH值对脱硫效率的影响关系:托盘塔脱硫系统的烟气量、入口SO2浓度、液气比、吸收塔pH对该系统的脱硫效率的影响关系具体为:在其他参数不变的情况下,烟气量和入口SO2浓度在一定范围内增加时,脱硫效率前期增长较为缓慢,基本保持不变,后期逐渐增加。但当两者超过一定范围时,脱硫效率将开始下降。液气比增大时,脱硫效率也增加,当液气比增大到14左右时,脱硫效率不再增加;浆液pH控制在5.0-6.0之间时脱硫效率最好;据此修正模糊规则库。(3) Exclude the abnormal data caused by desulfurization shutdown and instrument failure, and explore the influence of flue gas volume in the tray tower desulfurization system, SO 2 concentration in the inlet flue gas, liquid-gas ratio, and pH value of the absorption tower on the desulfurization efficiency: The effect of the flue gas volume, inlet SO 2 concentration, liquid-gas ratio, and absorption tower pH on the desulfurization efficiency of the tray tower desulfurization system is as follows: when other parameters remain unchanged, the flue gas volume and the inlet SO 2 concentration are When it increases within a certain range, the desulfurization efficiency increases slowly in the early stage, basically remains unchanged, and gradually increases in the later stage. But when the two exceed a certain range, the desulfurization efficiency will begin to decline. When the liquid-gas ratio increases, the desulfurization efficiency also increases. When the liquid-gas ratio increases to about 14, the desulfurization efficiency no longer increases; the desulfurization efficiency is the best when the pH of the slurry is controlled between 5.0 and 6.0; accordingly, the fuzzy rule library is corrected. .
(4)托盘塔脱硫监测数据作为检验样本和测试样本进行仿真测试;(4) The monitoring data of tray tower desulfurization are used as inspection samples and test samples for simulation test;
(4a)选取正常运行工况中395组数据作为校验样本,利用步骤(2)中建立的模糊模型,将样本的连续域量化,编写隶属度计算程序,对校验样本进行脱硫效率仿真输出,再次修正模糊规则库,进一步提高模型的精确性,得到125条模糊规则,如表1所示;图3为修正后的校验样本脱硫效率仿真输出与实际值比较图;(4a) Select 395 sets of data in normal operating conditions as verification samples, use the fuzzy model established in step (2) to quantify the continuous domain of the samples, write a membership calculation program, and simulate the desulfurization efficiency output for the verification samples , revise the fuzzy rule base again to further improve the accuracy of the model, and obtain 125 fuzzy rules, as shown in Table 1; Figure 3 is the comparison between the simulated output of the corrected sample desulfurization efficiency and the actual value;
表1Table 1
(4b)运用建立的模糊模型,对其它时段的336组测试样进行脱硫效率仿真输出,通过模拟结果析来预调运行参数,图4为测试样本脱硫效率仿真输出与实际值比较图。结果表明误差较小,预测准确率高。(4b) Using the established fuzzy model, the simulation output of desulfurization efficiency is carried out for 336 groups of test samples in other periods, and the operating parameters are pre-adjusted through the analysis of the simulation results. The results show that the error is small and the prediction accuracy is high.
如上所述,尽管参照特定的优选实施例已经表述和阐明了本发明,但其不得解释为对本发明自身的限制。在不脱离所附权利要求定义的本发明的精神和范围前提下,可对其在形式上和细节上作出各种变化。As mentioned above, although the present invention has been described and illustrated with reference to specific preferred embodiments, this should not be construed as limiting the invention itself. Various changes in form and details may be made therein without departing from the spirit and scope of the present invention as defined by the appended claims.
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