CN108803309A - It is a kind of that ammonia optimization method and system are intelligently sprayed based on the SCR denitration of hard measurement and model adaptation - Google Patents
It is a kind of that ammonia optimization method and system are intelligently sprayed based on the SCR denitration of hard measurement and model adaptation Download PDFInfo
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- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 title claims abstract description 146
- 229910021529 ammonia Inorganic materials 0.000 title claims abstract description 70
- 238000000034 method Methods 0.000 title claims abstract description 26
- 238000005457 optimization Methods 0.000 title claims abstract description 17
- 238000005259 measurement Methods 0.000 title claims abstract description 14
- 230000006978 adaptation Effects 0.000 title description 2
- MWUXSHHQAYIFBG-UHFFFAOYSA-N Nitric oxide Chemical compound O=[N] MWUXSHHQAYIFBG-UHFFFAOYSA-N 0.000 claims abstract description 240
- 238000002347 injection Methods 0.000 claims abstract description 65
- 239000007924 injection Substances 0.000 claims abstract description 65
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 37
- 230000003044 adaptive effect Effects 0.000 claims abstract description 34
- 238000002485 combustion reaction Methods 0.000 claims abstract description 21
- 239000003245 coal Substances 0.000 claims description 12
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 9
- 239000003546 flue gas Substances 0.000 claims description 9
- XKMRRTOUMJRJIA-UHFFFAOYSA-N ammonia nh3 Chemical compound N.N XKMRRTOUMJRJIA-UHFFFAOYSA-N 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 6
- 230000007274 generation of a signal involved in cell-cell signaling Effects 0.000 claims description 5
- 238000013135 deep learning Methods 0.000 claims description 4
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- 238000010531 catalytic reduction reaction Methods 0.000 claims description 2
- 238000012843 least square support vector machine Methods 0.000 claims 2
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- 238000000738 capillary electrophoresis-mass spectrometry Methods 0.000 description 5
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- 230000008859 change Effects 0.000 description 4
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- 239000000243 solution Substances 0.000 description 3
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- 238000005070 sampling Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000003638 chemical reducing agent Substances 0.000 description 1
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- 238000012544 monitoring process Methods 0.000 description 1
- 238000010298 pulverizing process Methods 0.000 description 1
- 238000009418 renovation Methods 0.000 description 1
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Abstract
本发明公开了一种基于软测量和模型自适应的SCR脱硝智能喷氨优化方法及系统。本方法为：1)基于燃煤火电机组燃烧系统的运行数据，建立入口氮氧化物浓度模型；然后利用该模型和当前采集的运行数据，得到入口氮氧化物浓度的预测值；2)根据预测值计算当前运行工况下喷氨量作为前馈信号发送给SCR脱硝系统；3)将出口氮氧化物浓度的实测值与出口氮氧化物浓度设定值做偏差后输入自适应PID控制器，得到喷氨量反馈控制信号并发送给SCR脱硝系统；其中，自适应PID控制器采用自适应PID控制算法调整当前工况下的PID参数；4)SCR脱硝系统根据该喷氨量前馈信号和喷氨量反馈控制信号控制SCR脱硝反应器的喷氨量。
The invention discloses an SCR denitrification intelligent ammonia injection optimization method and system based on soft measurement and model self-adaptation. The method is as follows: 1) based on the operating data of the combustion system of the coal-fired thermal power unit, establish the inlet nitrogen oxide concentration model; then use the model and the currently collected operating data to obtain the predicted value of the inlet nitrogen oxide concentration; 2) according to the prediction Value calculation Under the current operating conditions, the amount of ammonia injection is sent to the SCR denitrification system as a feed-forward signal; 3) After the actual measured value of the outlet nitrogen oxide concentration is deviated from the outlet nitrogen oxide concentration set value, it is input into the adaptive PID controller, The ammonia injection quantity feedback control signal is obtained and sent to the SCR denitrification system; wherein, the adaptive PID controller adopts the adaptive PID control algorithm to adjust the PID parameters under the current working condition; 4) the SCR denitration system is based on the ammonia injection quantity feedforward signal and The ammonia injection quantity feedback control signal controls the ammonia injection quantity of the SCR denitration reactor.
Description
技术领域technical field
本发明属于燃煤火电厂脱硝技术领域，具体涉及一种基于软测量和模型自适应的SCR(选择性催化还原)脱硝智能喷氨优化方法及系统。The invention belongs to the technical field of denitrification in coal-fired thermal power plants, and in particular relates to an intelligent ammonia injection optimization method and system for SCR (Selective Catalytic Reduction) denitrification based on soft measurement and model self-adaptation.
背景技术Background technique
目前，为了实现氮氧化物超低排放，大部分燃煤火电厂都安装了SCR脱硝装置，采用CEMS系统(烟气在线监测系统)采集入口、出口氮氧化物浓度，然后再进行PID(比例-积分-微分)反馈控制。At present, in order to achieve ultra-low emissions of nitrogen oxides, most coal-fired thermal power plants have installed SCR denitrification devices, using the CEMS system (flue gas online monitoring system) to collect the concentration of nitrogen oxides at the inlet and outlet, and then perform PID (proportion- Integral-derivative) feedback control.
PID反馈控制如图1所示，氨流量计算值为(入口氮氧化物浓度测量值-出口氮氧化物浓度测量值)×烟气量×氨氮摩尔比，其中氨氮摩尔比基本为固定值，入口氮氧化物浓度，出口氮氧化物浓度，烟气量通过仪表测量得到。The PID feedback control is shown in Figure 1. The calculated value of the ammonia flow rate is (the measured value of the inlet nitrogen oxide concentration - the measured value of the outlet nitrogen oxide concentration) x flue gas volume x ammonia nitrogen molar ratio, where the ammonia nitrogen molar ratio is basically a fixed value, and the inlet The concentration of nitrogen oxides, the concentration of nitrogen oxides at the outlet, and the amount of flue gas are measured by instruments.
上述方案存在下述问题：There is following problem in above-mentioned scheme:
1.入口、出口氮氧化物浓度采用CEMS系统测量，CEMS系统采样管线比较长，造成测量纯迟延较大，测量值有2-3分钟延迟；1. The concentration of nitrogen oxides at the inlet and outlet is measured by the CEMS system. The sampling pipeline of the CEMS system is relatively long, resulting in a large pure delay in measurement, and the measured value has a delay of 2-3 minutes;
2.现有CEMS系统采用单点取样测量，因此导致测量数据不能代表整个截面平均浓度；2. The existing CEMS system uses single-point sampling measurement, so the measurement data cannot represent the average concentration of the entire cross-section;
3.采用PID控制，PID参数在初始设定好后就不再改变，所以在机组负荷运行工况变化时，脱硝系统调整不及时，容易出现超标排放；3. PID control is adopted, and the PID parameters will not change after the initial setting. Therefore, when the operating conditions of the unit load change, the denitrification system is not adjusted in time, and excessive emissions are prone to occur;
4.为了保证达标排放，电厂运行人员将PID参数的设定值设定得非常低，导致喷氨量过大，控制系统超调量较大，系统响应速率较低。不仅浪费还原剂，还增加了后续设备堵塞的风险。4. In order to ensure that the emissions meet the standards, the power plant operators set the setting values of the PID parameters very low, resulting in excessive ammonia injection, a large overshoot of the control system, and a low system response rate. Not only is the reducing agent wasted, but also increases the risk of subsequent equipment blockage.
因此，开发一种SCR智能优化喷氨系统，实现精准喷氨对于SCR脱硝装置安全经济运行具有重要意义。Therefore, it is of great significance to develop an SCR intelligent optimized ammonia injection system to achieve precise ammonia injection for the safe and economical operation of SCR denitrification devices.
发明内容Contents of the invention
针对现有技术中存在的技术问题，本发明的目的在于提供一种基于软测量和模型自适应的SCR脱硝智能喷氨优化方法及系统。In view of the technical problems existing in the prior art, the object of the present invention is to provide a method and system for optimizing ammonia injection for SCR denitrification based on soft sensor and model self-adaptation.
本发明技术方案为：Technical scheme of the present invention is:
一种基于软测量和模型自适应的SCR脱硝智能喷氨优化方法，其步骤包括：An intelligent ammonia injection optimization method for SCR denitrification based on soft measurement and model adaptation, the steps of which include:
1)基于燃煤火电机组燃烧系统的运行数据，建立入口氮氧化物浓度模型；然后利用该入口氮氧化物浓度模型和当前采集的运行数据，得到入口氮氧化物浓度的预测值；1) Based on the operating data of the combustion system of the coal-fired thermal power unit, establish the inlet nitrogen oxide concentration model; then use the inlet nitrogen oxide concentration model and the currently collected operating data to obtain the predicted value of the inlet nitrogen oxide concentration;
2)根据入口氮氧化物浓度预测值计算当前运行工况下喷氨量作为前馈信号，将该喷氨量前馈信号发送给SCR脱硝系统；2) Calculate the amount of ammonia injection under the current operating condition according to the predicted value of the inlet nitrogen oxide concentration as a feed-forward signal, and send the feed-forward signal of the amount of ammonia injection to the SCR denitrification system;
3)测量燃煤火电机组燃烧系统的出口氮氧化物浓度的实测值，将该实测值与出口氮氧化物浓度设定值做偏差后输入自适应PID控制器，自适应PID控制器基于该偏差得到喷氨量反馈控制信号并发送给SCR脱硝系统；其中，自适应PID控制器采用自适应PID控制算法调整当前工况下的PID参数；3) Measure the actual measured value of the outlet nitrogen oxide concentration of the combustion system of the coal-fired thermal power unit, make a deviation between the actual measured value and the outlet nitrogen oxide concentration set value, and then input it into the adaptive PID controller, and the adaptive PID controller is based on the deviation Get the feedback control signal of the ammonia injection amount and send it to the SCR denitrification system; among them, the adaptive PID controller adopts the adaptive PID control algorithm to adjust the PID parameters under the current working condition;
4)SCR脱硝系统根据该喷氨量前馈信号和喷氨量反馈控制信号控制SCR脱硝反应器的喷氨量。4) The SCR denitrification system controls the ammonia injection amount of the SCR denitrification reactor according to the ammonia injection amount feed-forward signal and the ammonia injection amount feedback control signal.
进一步的，通过主元分析算法对所述运行数据进行划分，确定出与入口氮氧化物关联紧密的参数；然后将确定出的与入口氮氧化物关联紧密的参数作为训练数据，采用深度学习算法或者最小二乘支持向量机算法，建立入口氮氧化物浓度模型。Further, the operating data is divided by the principal component analysis algorithm, and the parameters closely related to the inlet nitrogen oxides are determined; then the determined parameters closely related to the inlet nitrogen oxides are used as training data, and the deep learning algorithm is used to Or the least squares support vector machine algorithm to establish the inlet nitrogen oxide concentration model.
进一步的，所述运行数据包括机组负荷、一次风量、二次风量、总煤量、磨煤机运行台数。Further, the operation data includes unit load, primary air volume, secondary air volume, total coal volume, and the number of coal mills in operation.
进一步的，得到所述喷氨量前馈信号的方法为：将所述预测值乘以烟气量，然后再乘以氨氮摩尔比计算出氨气量需求量，作为SCR脱硝系统的所述喷氨量前馈信号。Further, the method for obtaining the feed-forward signal of the ammonia injection amount is: multiply the predicted value by the flue gas amount, and then multiply the ammonia nitrogen molar ratio to calculate the ammonia gas demand, which is used as the ammonia injection amount of the SCR denitrification system. Feedforward signal.
进一步的，所述自适应PID控制器根据入口氮氧化物浓度和出口氮氧化物浓度建立SCR喷氨系统模型；然后采用遗传算法或者PSO优化算法对SCR喷氨系统模型参数进行优化，得到所述自适应PID控制器的PID最佳参数。Further, the adaptive PID controller establishes the SCR ammonia injection system model according to the inlet nitrogen oxide concentration and the outlet nitrogen oxide concentration; then optimizes the parameters of the SCR ammonia injection system model by using a genetic algorithm or a PSO optimization algorithm to obtain the PID optimal parameters for an adaptive PID controller.
进一步的，所述自适应PID控制器采用自适应PID控制算法调整当前工况下的PID参数的方法为：初次调试时根据现场测试，得到燃煤火电机组燃烧系统不同工况下的特性参数，建立SCR脱硝输入输出系统模型，通过该SCR脱硝输入输出系统模型确定所述自适应PID控制器的PID参数；在运行过程中，实时采集燃煤火电机组燃烧系统的运行数据，并对该SCR脱硝输入输出系统模型进行修正，然后基于修正后的SCR脱硝输入输出系统模型得到当前工况下的最佳PID参数。Further, the adaptive PID controller adopts the adaptive PID control algorithm to adjust the PID parameters under the current working conditions as follows: during the initial commissioning, according to the field test, the characteristic parameters of the combustion system of the coal-fired thermal power unit under different working conditions are obtained, Establish the SCR denitration input and output system model, and determine the PID parameters of the adaptive PID controller through the SCR denitration input and output system model; The input and output system model is corrected, and then the optimal PID parameters under the current working conditions are obtained based on the revised SCR denitration input and output system model.
一种基于软测量和模型自适应的SCR脱硝智能喷氨优化系统，其特征在于，包括喷氨量前馈信号产生单元、自适应PID控制器和SCR脱硝系统；其中，An intelligent ammonia injection optimization system for SCR denitrification based on soft measurement and model self-adaptation, characterized in that it includes an ammonia injection amount feedforward signal generation unit, an adaptive PID controller and an SCR denitrification system; wherein,
所述喷氨量前馈信号产生单元，连接煤火电机组燃烧系统运行数据传感器，基于燃煤火电机组燃烧系统运行数据传感器采集的运行数据，建立入口氮氧化物浓度模型；并利用该入口氮氧化物浓度模型和当前采集的运行数据，得到入口氮氧化物浓度的预测值，然后根据入口氮氧化物浓度预测值计算当前运行工况下的喷氨量前馈信号；The feed-forward signal generating unit for the amount of ammonia injection is connected to the coal-fired power unit combustion system operation data sensor, based on the operation data collected by the coal-fired thermal power unit combustion system operation data sensor, an inlet nitrogen oxide concentration model is established; and the inlet nitrogen oxide is used to oxidize The concentration model and the currently collected operating data are used to obtain the predicted value of the inlet nitrogen oxide concentration, and then calculate the feedforward signal of the ammonia injection amount under the current operating condition according to the predicted value of the inlet nitrogen oxide concentration;
所述自适应PID控制器，连接出口氮氧化物浓度测量仪表，用于根据燃煤火电机组燃烧系统的出口氮氧化物浓度的实测值与出口氮氧化物浓度设定值的偏差得到喷氨量反馈控制信号；其中，自适应PID控制器采用自适应PID控制算法调整当前工况下的PID参数；The self-adaptive PID controller is connected to the outlet nitrogen oxide concentration measuring instrument, and is used to obtain the amount of ammonia injection according to the deviation between the actual measured value of the outlet nitrogen oxide concentration of the combustion system of the coal-fired thermal power unit and the outlet nitrogen oxide concentration set value Feedback control signal; wherein, the adaptive PID controller adopts the adaptive PID control algorithm to adjust the PID parameters under the current working condition;
所述SCR脱硝系统，分别连接所述喷氨量前馈信号产生单元和所述自适应PID控制器以接收所述喷氨量前馈信号和喷氨量反馈控制信号，用于根据该喷氨量前馈信号和喷氨量反馈控制信号控制SCR脱硝反应器的喷氨量。The SCR denitrification system is respectively connected to the ammonia injection amount feed-forward signal generation unit and the adaptive PID controller to receive the ammonia injection amount feed-forward signal and the ammonia injection amount feedback control signal, and is used to The ammonia injection amount of the SCR denitration reactor is controlled by the amount feedforward signal and the ammonia injection amount feedback control signal.
本发明首先采集燃煤火电机组燃烧系统一次风、二次风、负荷等数据，然后基于采集数据建立入口氮氧化物浓度模型，然后根据当前采集数据和入口氮氧化物浓度模型得到入口氮氧化物浓度预测值，然后根据入口氮氧化物浓度预测值计算当前运行工况下喷氨量前馈，将前馈加入到氮氧化物浓度反馈控制回路，实现精准喷氨。另外，基于运行数据建立SCR喷氨系统模型，检测到运行工况变化时，自适应调整PID参数，从而实现优化控制。The present invention firstly collects the primary air, secondary air, load and other data of the coal-fired thermal power unit combustion system, then establishes the inlet nitrogen oxide concentration model based on the collected data, and then obtains the inlet nitrogen oxide according to the current collected data and the inlet nitrogen oxide concentration model. The concentration prediction value, and then calculate the ammonia injection amount feed-forward under the current operating condition according to the inlet nitrogen oxide concentration prediction value, and add the feed-forward to the nitrogen oxide concentration feedback control loop to achieve precise ammonia injection. In addition, the SCR ammonia injection system model is established based on the operating data, and when the operating condition changes are detected, the PID parameters are adaptively adjusted to achieve optimal control.
入口氮氧化物浓度预测方法：Inlet nitrogen oxide concentration prediction method:
根据锅炉运行数据，初步选择机组负荷、一次风量、二次风量、总煤量、磨煤机运行台数参数及对应的入口氮氧化物浓度，首先通过主元分析算法对所选参数进行分析，确定出与入口氮氧化物关联紧密的参数，即确定出主要参数和次要参数。然后，将确定出的与入口氮氧化物关联紧密的参数作为训练数据，采用深度学习算法或者最小二乘支持向量机算法，建立入口氮氧化物浓度模型，从而利用该入口氮氧化物浓度模型实现对入口氮氧化物浓度的预测。其中，与入口氮氧化物关联紧密的参数包括总风量、总煤量、风煤比、一次风与二次风比值。According to the boiler operation data, the parameters of unit load, primary air volume, secondary air volume, total coal volume, number of pulverizers and the corresponding inlet nitrogen oxide concentration are initially selected. First, the selected parameters are analyzed through the principal component analysis algorithm to determine The parameters that are closely related to the inlet nitrogen oxides are determined, that is, the main parameters and secondary parameters are determined. Then, use the determined parameters that are closely related to the inlet nitrogen oxides as training data, and use the deep learning algorithm or the least squares support vector machine algorithm to establish the inlet nitrogen oxide concentration model, so as to use the inlet nitrogen oxide concentration model to achieve Prediction of Inlet NOx Concentrations. Among them, the parameters closely related to the inlet nitrogen oxides include total air volume, total coal volume, air-to-coal ratio, and ratio of primary air to secondary air.
然后，基于运行数据建立SCR喷氨系统模型，检测到运行工况变化时，自适应调整PID参数，从而实现优化控制。Then, a model of the SCR ammonia injection system is established based on the operating data, and when changes in the operating conditions are detected, the PID parameters are adaptively adjusted to achieve optimal control.
SCR喷氨系统模型是根据入口氮氧化物浓度和出口氮氧化物浓度建立的脱硝模型，基于机理与数据相结合建立(比如首先通过机理分析假定一个模型的结构公式：a＝bx+c,通过实际运行数据确定模型参数，a,b,c。)，数据为入口氮氧化物浓度和出口氮氧化物浓度参数。基于当前喷氨系统模型参数，采用遗传算法或者PSO优化算法，可得到当前工况下的最佳PID控制参数。在实际运行中，系统不断在线辨识SCR喷氨模型，当监测到模型变化比较大的时候，重新计算PID参数，从而实现PID参数自适应调整，始终保持较好的控制参数。The SCR ammonia injection system model is a denitrification model established based on the inlet nitrogen oxide concentration and outlet nitrogen oxide concentration, and is established based on the combination of mechanism and data (for example, first assume the structural formula of a model through mechanism analysis: a=bx+c, through The actual operating data determine the model parameters, a, b, c.), and the data are the inlet nitrogen oxide concentration and outlet nitrogen oxide concentration parameters. Based on the current ammonia injection system model parameters, the optimal PID control parameters under the current working conditions can be obtained by using genetic algorithm or PSO optimization algorithm. In actual operation, the system continuously identifies the SCR ammonia injection model online, and recalculates the PID parameters when it detects a large change in the model, so as to realize the self-adaptive adjustment of the PID parameters and maintain good control parameters.
本发明也可通过现场测试获得典型工况的系统特性参数。然后，根据不同典型工况，确定几组PID控制器参数。在实际运行中，自动检测运行工况，然后确定采用当前工况对应的较优PID参数，即根据运行工况不同进行切换，实现分段PID。The present invention can also obtain system characteristic parameters of typical working conditions through on-site testing. Then, according to different typical working conditions, several groups of PID controller parameters are determined. In actual operation, the operating conditions are automatically detected, and then the optimal PID parameters corresponding to the current operating conditions are determined, that is, switching is performed according to different operating conditions to realize segmental PID.
本方案的创新之处包括三点：The innovation of this program includes three points:
第一，传统控制方案入口氮氧化物浓度通过CEMS仪表测量，测量滞后较大。本方案基于机理和数据建模获得，实时性较好。First, the concentration of nitrogen oxides at the inlet of the traditional control scheme is measured by a CEMS instrument, which has a large measurement lag. This solution is based on mechanism and data modeling, and has good real-time performance.
第二，当锅炉燃烧系统发生变化时，传统方案是被动调节，本方案在控制方案中引入了燃烧系统变化前馈信号，可以提前进行调节。Second, when the boiler combustion system changes, the traditional scheme is passive adjustment. This scheme introduces the combustion system change feedforward signal into the control scheme, which can be adjusted in advance.
第三，传统方案PID控制参数整定后保持不变，本方案根据系统运行工况实时调整PID控制参数，实现控制参数优化。Third, the PID control parameters of the traditional scheme remain unchanged after being set. This scheme adjusts the PID control parameters in real time according to the operating conditions of the system to realize the optimization of the control parameters.
与现有技术相比，本发明的有益效果如下：Compared with the prior art, the beneficial effects of the present invention are as follows:
1.脱硝出口氮氧化物浓度偏差可以控制在5-10mg/Nm3之间，可以保证在变工况情况下稳定达标排放。1. The concentration deviation of nitrogen oxides at the denitrification outlet can be controlled between 5-10mg/Nm 3 , which can ensure stable and up-to-standard discharge under variable working conditions.
2.脱硝控制系统的系统响应速率较高，投资较小，改造工期短。2. The system response rate of the denitrification control system is high, the investment is small, and the renovation period is short.
附图说明Description of drawings
图1为现有系统控制流程图；Fig. 1 is the control flowchart of existing system;
图2为本发明的控制流程图；Fig. 2 is the control flowchart of the present invention;
图3为本发明的系统控制平台架构图。FIG. 3 is an architecture diagram of the system control platform of the present invention.
具体实施方式Detailed ways
下面通过具体实施例和附图，对本发明做进一步详细说明。The present invention will be described in further detail below through specific embodiments and accompanying drawings.
本方案主要是提出一种入口氮氧化物浓度软测量与工况自适应PID相结合的脱硝优化控制方法。This program mainly proposes a denitrification optimization control method that combines the inlet nitrogen oxide concentration soft measurement and the working condition self-adaptive PID.
本发明首先采集燃煤火电机组燃烧系统一次风、二次风、负荷等数据及与这些参数对应的入口氮氧化物浓度，建立入口氮氧化物浓度模型。The invention firstly collects the primary air, secondary air, load and other data of the combustion system of the coal-fired thermal power unit and the inlet nitrogen oxide concentration corresponding to these parameters, and establishes the inlet nitrogen oxide concentration model.
如图2所示，基于锅炉一次风量、二次风量、给煤量、制粉系统运行台数等参数，根据上述入口氮氧化物浓度模型，得到入口氮氧化物浓度预测值，再乘以烟气量，然后再乘以氨氮摩尔比计算出氨气量需求量，作为SCR脱硝系统前馈信号(即喷氨量快速跟踪信号)，前馈信号可以保证负荷变化时，可以快速调节喷氨量。出口氮氧化物浓度设定值与实测值做偏差后进入自适应PID控制器，作为喷氨量反馈控制信号。自适应PID控制器参数根据锅炉燃烧工况自适应调整。As shown in Figure 2, based on parameters such as boiler primary air volume, secondary air volume, coal feed volume, and the number of pulverizing system operating units, according to the above inlet nitrogen oxide concentration model, the inlet nitrogen oxide concentration prediction value is obtained, and then multiplied by the flue gas Amount, and then multiplied by the ammonia nitrogen molar ratio to calculate the ammonia demand, which is used as the feed-forward signal of the SCR denitrification system (that is, the fast tracking signal of the ammonia injection amount). The feed-forward signal can ensure that the ammonia injection amount can be quickly adjusted when the load changes. After the deviation between the set value of the outlet nitrogen oxide concentration and the measured value, it enters the adaptive PID controller as a feedback control signal for the amount of ammonia injection. Adaptive PID controller parameters are adaptively adjusted according to the boiler combustion conditions.
其中，“入口氮氧化物浓度预测值”的计算方法是：基于运行参数和入口氮氧化物浓度历史数据，采用机器学习算法或者最小二乘支持向量机模型，建立入口氮氧化物浓度模型，在实际运行中，实时采集输入数据并输入到模型中，可以得到入口氮氧化物浓度预测值。Among them, the calculation method of the "predicted value of the concentration of nitrogen oxides at the inlet" is: based on the operating parameters and the historical data of the concentration of nitrogen oxides at the inlet, a machine learning algorithm or a least squares support vector machine model is used to establish a model of the concentration of nitrogen oxides at the inlet. In actual operation, the input data is collected in real time and input into the model, and the predicted value of the inlet nitrogen oxide concentration can be obtained.
反馈控制回路PID采用自适应PID控制算法。所述“自适应PID控制算法”的步骤为：The feedback control loop PID adopts adaptive PID control algorithm. The steps of the "adaptive PID control algorithm" are:
1)初次调试时根据现场测试，得到系统不同工况下特性参数，建立SCR脱硝输入输出系统模型，通过模型可以确定PID参数；1) During the initial commissioning, according to the on-site test, the characteristic parameters of the system under different working conditions are obtained, and the SCR denitration input and output system model is established, and the PID parameters can be determined through the model;
2)在运行过程中，实时采集运行数据，并对模型进行修正，然后再基于修正后模型，采用优化算法得到当前工况下最佳PID参数，从而实现自适应PID控制。2) During the running process, the running data is collected in real time, and the model is corrected, and then based on the corrected model, an optimization algorithm is used to obtain the best PID parameters under the current working conditions, thereby realizing adaptive PID control.
其中，“烟气量”是指(实际测量的锅炉烟气量)，单位是(NM3/h)。“氨氮摩尔比”是指(脱硝中氨气和氮氧化物浓度的比值，是脱硝中常用概念，一般为0.7-0.9)。“氨气量需求量”的计算公式是：(氨气需求量＝入口氮氧化物乘以烟气量乘以氨氮摩尔比)。Wherein, "flue gas volume" refers to (actually measured boiler flue gas volume), and the unit is (NM 3 /h). "Ammonia nitrogen molar ratio" refers to (the ratio of ammonia gas to nitrogen oxide concentration in denitrification, which is a commonly used concept in denitrification, generally 0.7-0.9). The calculation formula of "ammonia gas demand" is: (ammonia gas demand = inlet nitrogen oxide multiplied by flue gas multiplied by ammonia nitrogen molar ratio).
为了保证该算法可以在现场应用，并对控制算法进行保密，本方案的实施基于脱硝优化控制平台实现。该平台的核心是一个高性能的控制器，通过数据采集卡件从DCS系统获得计算所需参数(负荷、一次风量、二次风量、总煤量、等锅炉运行参数)，经过计算后，再返回原DCS系统，实现闭环控制。控制器与原DCS系统通信采用modbus、RS485等通信方式，可以与国内主流DCS系统进行双向通信。脱硝优化控制器与DCS现场控制器可以实现无扰切换。控制平台如图3所示，优化控制器中主要包括系统通信模块和核心算法计算模块，系统通信模块主要负责实现与DCS进行数据输入，输出。核心算法模块主要是实现优化控制算法。系统运行时，首先通过系统通信模块采集运行数据，然后输入到核心算法模块，核心算法模块再输出到DCS系统，从而实现闭环控制。In order to ensure that the algorithm can be applied in the field and keep the control algorithm confidential, the implementation of this scheme is based on the denitrification optimization control platform. The core of the platform is a high-performance controller, which obtains the parameters required for calculation (load, primary air volume, secondary air volume, total coal volume, and other boiler operating parameters) from the DCS system through the data acquisition card. Return to the original DCS system to realize closed-loop control. The communication between the controller and the original DCS system adopts communication methods such as modbus and RS485, and can carry out two-way communication with domestic mainstream DCS systems. The denitrification optimization controller and the DCS field controller can realize undisturbed switching. The control platform is shown in Figure 3. The optimization controller mainly includes a system communication module and a core algorithm calculation module. The system communication module is mainly responsible for realizing data input and output with DCS. The core algorithm module is mainly to realize the optimal control algorithm. When the system is running, the operating data is first collected through the system communication module, and then input to the core algorithm module, which is then output to the DCS system, thereby realizing closed-loop control.
表1为采用本发明方法和现有方法在实际运行中的对比，从这些对比中可以看出，采用本发明方法，可以实现SCR脱硝装置的精准喷氨，提高系统运行效率，降低成本。Table 1 is the comparison between the method of the present invention and the existing method in actual operation. From these comparisons, it can be seen that the method of the present invention can realize accurate ammonia injection of the SCR denitrification device, improve the operating efficiency of the system, and reduce costs.
表1为实际运行效果对比Table 1 is the comparison of actual operation effect
动态工况运行效果对比分析Comparative analysis of operating effects under dynamic conditions
1改造前运行效果1 Operation effect before transformation
【1】机组升负荷工况【1】Unit load increase condition
变工况下反应器出口NOx含量的动态特性是考察脱硝系统自动控制效果最重要的部分之一。此部分分析升负荷过程中反应器出口NOx含量的动态特性。The dynamic characteristics of the NOx content at the reactor outlet under variable working conditions is one of the most important parts to investigate the automatic control effect of the denitrification system. This part analyzes the dynamic characteristics of the NO x content at the reactor outlet during the process of increasing the load.
负荷由365MW附近升至395MW附近过程中，脱硝系统甲、乙侧反应器出口NOx含量的统计分析如表2。Table 2 shows the statistical analysis of the NO x content at the outlet of the A and B side reactors of the denitrification system during the process of increasing the load from around 365MW to around 395MW.
表2为365MW升至395MW负荷段脱硝性能数据Table 2 shows the denitrification performance data in the load section from 365MW to 395MW
【2】机组降负荷工况【2】Unit load reduction condition
以下是降负荷过程中反应器出口NOx含量的动态特性的分析。The following is an analysis of the dynamic characteristics of the NOx content at the reactor outlet during the load reduction process.
负荷由500MW附近降至330MW附近过程中，脱硝系统甲、乙侧反应器出口NOx含量的统计分析如表3。When the load is reduced from around 500MW to around 330MW, the statistical analysis of the NO x content at the outlet of the A and B side reactors of the denitrification system is shown in Table 3.
表3为500MW降至330MW负荷段脱硝性能数据Table 3 shows the denitrification performance data in the load section from 500MW to 330MW
2改造后运行效果2 Operation effect after transformation
【1】机组升负荷工况【1】Unit load increase condition
以下为机组负荷从400MW上升至500MW时的运行过程，一般在此升负荷区间，会启动一台磨煤机。磨的启停期间对反应器入口NOx含量的短时影响很大，反应器出口NOx含量超标也多半是受此影响。The following is the operation process when the load of the unit rises from 400MW to 500MW. Generally, a coal pulverizer will be started during this load increase range. The short-term impact on the NO x content of the reactor inlet during the start and stop of the mill is very large, and the excessive NO x content of the reactor outlet is also mostly affected by this.
负荷由400MW升至500MW过程中，脱硝系统甲、乙侧反应器出口NOx含量的统计分析如表4。During the load increase from 400MW to 500MW, the statistical analysis of the NOx content at the outlet of the A and B side reactors of the denitrification system is shown in Table 4.
表4为负荷由400MW升至500MW运行区间脱硝性能数据Table 4 shows the denitrification performance data in the operating range from 400MW to 500MW when the load is increased
负荷由550MW升至600MW运行区间，脱硝系统甲、乙侧反应器出口NOx含量的统计分析如表5。Table 5 shows the statistical analysis of the NOx content at the outlets of the A and B side reactors of the denitrification system when the load increases from 550MW to 600MW.
表5为负荷由550MW升至600MW运行区间脱硝性能数据Table 5 shows the denitrification performance data in the operating range from 550MW to 600MW
【2】机组降负荷工况【2】Unit load reduction condition
此部分将用同样的方式对降负荷过程中脱硝反应器的性能进行了分析。This part will use the same way to analyze the performance of the denitrification reactor during the load reduction process.
负荷由600MW降至550MW运行区间，脱硝系统甲、乙侧反应器出口NOx含量的统计分析如表6。The load is reduced from 600MW to 550MW in the operating range, and the statistical analysis of the NOx content at the outlet of the A and B side reactors of the denitrification system is shown in Table 6.
表6为负荷由600MW降至550MW运行区间脱硝性能数据Table 6 shows the denitrification performance data in the operating range from 600MW to 550MW
负荷由550MW降至500MW运行区间，脱硝系统甲、乙侧反应器出口NOx含量统计分析如表7。The load is reduced from 550MW to 500MW in the operating range, and the statistical analysis of the NOx content at the outlet of the A and B side reactors of the denitrification system is shown in Table 7.
表7为负荷由550MW降至500MW运行区间脱硝性能数据Table 7 shows the denitrification performance data in the operating range from 550MW to 500MW
负荷由500MW降至400MW运行区间，脱硝系统甲、乙侧反应器出口NOx含量统计分析如表8。The load is reduced from 500MW to 400MW in the operating range, and the statistical analysis of the NOx content at the outlet of the A and B side reactors of the denitrification system is shown in Table 8.
表8为负荷由500MW降至400MW运行区间脱硝性能数据Table 8 shows the denitrification performance data in the operating range from 500MW to 400MW
以上实施例仅用以说明本发明的技术方案而非对其进行限制，本领域的普通技术人员可以对本发明的技术方案进行修改或者等同替换，而不脱离本发明的精神和范围，本发明的保护范围应以权利要求书所述为准。The above embodiments are only used to illustrate the technical solution of the present invention and not to limit it. Those of ordinary skill in the art can modify or equivalently replace the technical solution of the present invention without departing from the spirit and scope of the present invention. The scope of protection should be determined by the claims.
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