CN103411213B - Fan for Circulating Fluidized Bed Boiler power consumption prognoses system and method - Google Patents
Fan for Circulating Fluidized Bed Boiler power consumption prognoses system and method Download PDFInfo
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Abstract
The invention discloses a kind of Fan for Circulating Fluidized Bed Boiler power consumption prognoses system and method, system comprises the field intelligent instrument, database, database interface, control station and the host computer that are connected with CFBB; Field intelligent instrument is connected with control station, database and host computer, and host computer comprises: standardization module, for gathering the training sample of key variables from database, and column criterion of going forward side by side process; Forecasting mechanism forms module, for setting up forecast model; Prediction Executive Module, for real-time estimate blower fan power consumption; Model modification module; Signal acquisition module; Result display module.The present invention predicts blower fan power consumption according to the operating condition of CFBB and performance variable, so that suggestion and guides operation, thus reduce the blower fan power consumption of CFBB, effective raising boiler operating efficiency, and lay the foundation for being optimized operational efficiency further.
Description
Technical Field
The invention relates to the field of energy engineering, in particular to a power consumption prediction system and method for a circulating fluidized bed boiler fan.
Background
The circulating fluidized bed boiler has the advantages of less pollutant discharge, wide fuel adaptability, strong load regulation capacity and the like, and is more and more widely applied to industries such as electric power, heat supply and the like in recent years. With the increasing shortage of energy and the continuous enhancement of energy-saving and environment-friendly awareness of people, users urgently need to dig the operation potential of the boiler unit and improve the operation efficiency of the unit. However, most circulating fluidized bed boilers have the characteristics of low automation degree and dependence on manual experience in operation, so that the energy-saving potential of the boiler is difficult to fully exploit, and a significant reason for the situation is lack of a reasonable prediction system and method. The primary fan, the secondary fan and the induced draft fan are main power consumption auxiliary equipment of the circulating fluidized bed boiler, and the unit value of the electric energy is much larger than the heat loss of the boiler because the electric energy is secondary energy, so that the power consumption of the three fans has an important influence on the overall operation efficiency of the circulating fluidized bed boiler. Based on the consideration of the energy-saving purpose, a prediction system of the power consumption of the fan of the circulating fluidized bed boiler is established, and the prediction system has important significance on the high-energy-efficiency operation, the operation analysis and the operation optimization of the circulating fluidized bed boiler.
Disclosure of Invention
The invention aims to provide a system and a method for predicting heat loss of exhaust smoke of a circulating fluidized bed boiler aiming at the defects of the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: a power consumption prediction system for a fan of a circulating fluidized bed boiler comprises an on-site intelligent instrument, a database, a data interface, a control station and an upper computer, wherein the on-site intelligent instrument, the database, the data interface, the control station and the upper computer are connected with the circulating fluidized bed boiler; on-spot intelligent instrument and control station, database and host computer are connected, the host computer include:
a standardization processing module for collecting historical records of operation condition variables and operation variables from the database, forming a training sample matrix X of independent variables, and collecting corresponding primary fan current, secondary fan current and guideHistorical records of fan current signals form a dependent variable training sample matrix Y, the training sample X, Y is standardized, the mean value of each variable is 0, the variance is 1, and a standardized independent variable training sample matrix X is obtained*(nxp), normalized dependent variable training sample matrix Y*(n × 3), using the following procedure to complete:
1.1) averaging:
1.2) calculating the standard deviation
1.3) normalization
Wherein x isij、yikIs the original value of the training sample point, n is the number of training samples, p is the number of independent variables,is the mean of the training samples, sx,j、sy,kIn order to train the standard deviation of the sample,for training sample pointsAnd normalizing the values, wherein subscripts i, j and k respectively represent an ith training sample point, a jth independent variable and a kth dependent variable.
The prediction mechanism forming module is used for establishing a prediction model and comprises the following implementation steps:
2.1) solving a prediction coefficient matrix beta according to the formula (7):
β=(X*TX*)-1X*TY* （7）
wherein, the superscript: t, -1 respectively represents the transposition of the matrix and the inverse of the matrix;
2.2) transferring and storing the prediction coefficient matrix beta to a prediction execution module.
The prediction execution module is used for predicting the power consumption of the fan according to the operation condition of the circulating fluidized bed boiler and the set operation variable, and the implementation steps are as follows:
3.1) processing the input independent variable signal according to the formula (8):
wherein, x (t)jFor the jth original value of the independent variable at the time t,is the mean, s, of the jth independent variable training samplex,jFor the standard deviation of the jth independent variable training sample,is the jth independent variable dimensionless value at the t moment, and t represents time and unit is second;
3.2) solving the dimensionless predicted values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,respectively carrying out dimensionless predicted values of primary fan current, secondary fan current and induced fan current at the time t;
3.3) solving the original dimensional prediction values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,respectively obtaining original dimensional predicted values of primary fan current, secondary fan current and induced fan current at the time t, namely current predicted values of all fans;
3.4) calculating the predicted value of the power consumption of the fan of the circulating fluidized bed boiler according to the following formula:
wherein, U1、U2、U3The power supply voltages of the primary fan, the secondary fan and the induced draft fan are respectively, and the unit is kV; respectively a primary air fan and a secondary airThe unit of the current prediction values of the machine and the induced draft fan is A;the power factors of the primary fan, the secondary fan and the induced draft fan are respectively; p is the predicted value of the power consumption of the fan of the circulating fluidized bed boiler, and the unit is kW.
As a preferred solution: the host computer still include: and the model updating module is used for comparing the actual primary fan current, secondary fan current and induced fan current with predicted values according to a set time interval, if the relative error is more than 10%, adding new data into training sample data, and executing the standardization processing module and the prediction mechanism forming module again.
Further, the host computer still include:
and the signal acquisition module is used for acquiring real-time data from the field intelligent instrument according to a set sampling time interval and acquiring historical data from the database.
And the result display module is used for reading the setting parameters from the control station, transmitting the predicted value of the power consumption of the fan to the control station for display and giving an operation suggestion: under the current working condition, how to adjust the operation variables is most beneficial to reducing the power consumption of the fan, so that the control station staff can adjust the operation conditions in time according to the predicted value and the operation suggestion of the power consumption of the fan, reduce the power consumption of the fan and improve the operation efficiency of the boiler. The method is characterized in that the current value of the operation variable fluctuates up and down and is substituted into a fan power consumption prediction system to obtain a new fan power consumption prediction value, so that the new fan power consumption prediction value can be obtained visually by comparing the current value with the current value.
As another preferred solution: the independent variables include: the operation condition variables are as follows: main steam flow, environment temperature, water supply temperature, hearth negative pressure, bed pressure, coal moisture, coal volatile matter, coal ash and coal sulfur; the operation variables are as follows: the total air volume of the primary air and the total air volume of the secondary air.
A power consumption prediction method for a fan of a circulating fluidized bed boiler comprises the following steps:
1) collecting historical records of operation condition variables and operation variables from a database to form an independent variable training sample matrix X, collecting corresponding historical records of primary fan current, secondary fan current and induced fan current signals to form a dependent variable training sample matrix Y, standardizing a training sample X, Y to enable the mean value of each variable to be 0 and the variance to be 1, and obtaining the standardized independent variable training sample matrix X*(nxp), normalized dependent variable training sample matrix Y*(n × 3), using the following procedure to complete:
1.1) averaging:
1.2) calculating the standard deviation
1.3) normalization
Wherein x isij、yikIs the original value of the training sample point, n is the number of training samples, p is the number of independent variables,is the mean of the training samples, sx,j、sy,kIn order to train the standard deviation of the sample,the subscripts i, j, and k represent the ith training sample point, the jth independent variable, and the kth dependent variable, respectively.
2) And establishing a prediction model by the obtained standardized training sample through the following processes:
2.1) solving a prediction coefficient matrix beta according to the formula (7):
β=(X*TX*)-1X*TY* （7）
wherein, the superscript: t, -1 respectively represents the transposition of the matrix and the inverse of the matrix;
2.2) storing the obtained prediction coefficient matrix beta.
3) The method comprises the following steps of taking operating condition variables and set operating variables of the circulating fluidized bed boiler as input signals, and predicting the power consumption of a fan according to a prediction coefficient vector, wherein the method comprises the following steps:
3.1) processing the input independent variable signal according to the formula (8):
wherein, x (t)jFor the jth original value of the independent variable at the time t,is the mean, s, of the jth independent variable training samplex,jFor the standard deviation of the jth independent variable training sample,is the jth independent variable dimensionless value at the t moment, and t represents time and unit is second;
3.2) solving the dimensionless predicted values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,primary fan current and secondary fan current at t momentThe non-dimensionalization predicted values of the current and the induced draft fan current;
3.3) solving the original dimensional prediction values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,respectively obtaining original dimensional predicted values of primary fan current, secondary fan current and induced fan current at the time t, namely current predicted values of all fans;
3.4) calculating the predicted value of the power consumption of the fan of the circulating fluidized bed boiler according to the following formula:
wherein, U1、U2、U3Are respectively one timeThe unit of the power supply voltage of the draught fan, the secondary fan and the induced draft fan is kV; respectively obtaining current predicted values of a primary fan, a secondary fan and an induced draft fan, wherein the unit is A;the power factors of the primary fan, the secondary fan and the induced draft fan are respectively; p is the predicted value of the power consumption of the fan of the circulating fluidized bed boiler, and the unit is kW.
As a preferred solution: the method further comprises the following steps: 4) acquiring field intelligent instrument signals according to a set sampling time interval, comparing the obtained actual primary fan current, secondary fan current and induced fan current with predicted values, if the relative error is more than 10%, adding new data into training sample data, and re-executing the steps 1) and 2) so as to update the prediction model.
Further, in the step 3), reading the setting parameters from the control station, transmitting the predicted value of the power consumption of the fan to the control station for displaying, and giving an operation suggestion: under the current working condition, how to adjust the operation variables is most beneficial to reducing the power consumption of the fan, so that the control station staff can adjust the operation conditions in time according to the predicted value and the operation suggestion of the power consumption of the fan, reduce the power consumption of the fan and improve the operation efficiency of the boiler. The method is characterized in that the current value of the operation variable fluctuates up and down and is substituted into a fan power consumption prediction system to obtain a new fan power consumption prediction value, so that the new fan power consumption prediction value can be obtained visually by comparing the current value with the current value.
As another preferred solution: the independent variables include: the operation condition variables are as follows: main steam flow, environment temperature, water supply temperature, hearth negative pressure, bed pressure, coal moisture, coal volatile matter, coal ash and coal sulfur; the operation variables are as follows: the total air volume of the primary air and the total air volume of the secondary air.
The invention has the following beneficial effects: the power consumption of the fan of the circulating fluidized bed boiler is predicted, production operation is suggested and guided, the power consumption of the fan is reduced, the energy-saving potential of the device is excavated, and the production benefit is improved.
Drawings
Fig. 1 is a hardware configuration diagram of the system proposed by the present invention.
FIG. 2 is a functional block diagram of the upper computer of the present invention.
Detailed Description
The invention is further illustrated by the following figures and examples.
Example 1
Referring to fig. 1 and 2, a power consumption prediction system for a fan of a circulating fluidized bed boiler comprises an intelligent field instrument 2, a data interface 3, a database 4, a control station 5 and an upper computer 6, wherein the intelligent field instrument 2 is connected with a field bus, the data bus is connected with the data interface 3, the data interface 3 is connected with the database 4, the control station 5 and the upper computer 6, and the upper computer 6 comprises:
a standardization processing module 7, configured to collect historical records of operating condition variables and operating variables from the database, form a training sample matrix X of independent variables, collect historical records of corresponding primary fan current, secondary fan current, and induced fan current signals, form a training sample matrix Y of dependent variables, standardize the training sample X, Y to make the mean value of each variable 0 and the variance 1, and obtain a standardized training sample matrix X of independent variables*(nxp), normalized dependent variable training sample matrix Y*(n×3)The method is completed by adopting the following processes:
1.1) averaging:
1.2) calculating the standard deviation
1.3) normalization
Wherein x isij、yikIs the original value of the training sample point, n is the number of training samples, p is the number of independent variables,is the mean of the training samples, sx,j、sy,kIn order to train the standard deviation of the sample,the subscripts i, j, and k represent the ith training sample point, the jth independent variable, and the kth dependent variable, respectively.
A prediction mechanism forming module 8, configured to build a prediction model, which includes the following steps:
2.1) solving a prediction coefficient matrix beta according to the formula (7):
β=(X*TX*)-1X*TY* （7）
wherein, the superscript: t, -1 respectively represents the transposition of the matrix and the inverse of the matrix;
2.2) transferring and storing the prediction coefficient matrix beta to a prediction execution module.
The prediction execution module 9 is used for predicting the power consumption of the fan according to the operation condition of the circulating fluidized bed boiler and the set operation variable, and the implementation steps are as follows:
3.1) processing the input independent variable signal according to the formula (8):
wherein, x (t)jFor the jth original value of the independent variable at the time t,is the mean, s, of the jth independent variable training samplex,jFor the standard deviation of the jth independent variable training sample,is the jth independent variable dimensionless value at the t moment, and t represents time and unit is second;
3.2) solving the dimensionless predicted values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,respectively carrying out dimensionless predicted values of primary fan current, secondary fan current and induced fan current at the time t;
3.3) solving the original dimensional prediction values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,respectively obtaining original dimensional predicted values of primary fan current, secondary fan current and induced fan current at the time t, namely current predicted values of all fans;
3.4) calculating the predicted value of the power consumption of the fan of the circulating fluidized bed boiler according to the following formula:
wherein, U1、U2、U3The power supply voltages of the primary fan, the secondary fan and the induced draft fan are respectively, and the unit is kV; respectively obtaining current predicted values of a primary fan, a secondary fan and an induced draft fan, wherein the unit is A;the power factors of the primary fan, the secondary fan and the induced draft fan are respectively; p is the air of the circulating fluidized bed boilerAnd predicting the power consumption of the machine in kW.
The upper computer 6 further comprises: and the signal acquisition module 11 is used for acquiring real-time data from the field intelligent instrument according to a set sampling time interval and acquiring historical data from a database.
The upper computer 6 further comprises: and the model updating module 12 is used for comparing the actual primary fan current, secondary fan current and induced fan current with predicted values according to a set time interval, adding new data into training sample data if the relative error is more than 10%, and executing the standardization processing module and the prediction mechanism forming module again.
The upper computer 6 further comprises: and the result display module 10 is used for reading the setting parameters from the control station, transmitting the predicted value of the power consumption of the fan to the control station for display, and giving an operation suggestion: under the current working condition, how to adjust the operation variables is most beneficial to reducing the power consumption of the fan, so that the control station staff can adjust the operation conditions in time according to the predicted value and the operation suggestion of the power consumption of the fan, reduce the power consumption of the fan and improve the operation efficiency of the boiler. The method is characterized in that the current value of the operation variable fluctuates up and down and is substituted into a fan power consumption prediction system to obtain a new fan power consumption prediction value, so that the new fan power consumption prediction value can be obtained visually by comparing the current value with the current value.
The hardware part of the upper computer 6 comprises: the I/O element is used for collecting data and transmitting information; the data memory is used for storing data samples, operation parameters and the like required by operation; a program memory storing a software program for realizing the functional module; an arithmetic unit that executes a program to realize a designated function; and the display module displays the set parameters and the running result and gives an operation suggestion.
Example 2
Referring to fig. 1 and 2, a method for predicting the power consumption of a fan of a circulating fluidized bed boiler comprises the following steps:
1) collecting historical records of operation condition variables and operation variables from a database to form an independent variable training sample matrix X, collecting corresponding historical records of primary fan current, secondary fan current and induced fan current signals to form a dependent variable training sample matrix Y, standardizing a training sample X, Y to enable the mean value of each variable to be 0 and the variance to be 1, and obtaining the standardized independent variable training sample matrix X*(nxp), normalized dependent variable training sample matrix Y*(n × 3), using the following procedure to complete:
1.1) averaging:
1.2) calculating the standard deviation
1.3) normalization
Wherein x isij、yikIs the original value of the training sample point, n is the number of training samples, p is the number of independent variables,is the mean of the training samples, sx,j、sy,kIn order to train the standard deviation of the sample,the subscripts i, j, and k represent the ith training sample point, the jth independent variable, and the kth dependent variable, respectively.
2) And establishing a prediction model by the obtained standardized training sample through the following processes:
2.1) solving a prediction coefficient matrix beta according to the formula (7):
β=(X*TX*)-1X*TY* （7）
wherein, the superscript: t, -1 respectively represents the transposition of the matrix and the inverse of the matrix;
2.2) storing the obtained prediction coefficient matrix beta.
3) The method comprises the following steps of taking operating condition variables and set operating variables of the circulating fluidized bed boiler as input signals, and predicting the power consumption of a fan according to a prediction coefficient vector, wherein the method comprises the following steps:
3.1) processing the input independent variable signal according to the formula (8):
wherein, x (t)jFor the jth original value of the independent variable at the time t,is the mean, s, of the jth independent variable training samplex,jFor the standard deviation of the jth independent variable training sample,is the jth independent variable dimensionless value at the t moment, and t represents time and unit is second;
3.2) solving the dimensionless predicted values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
where, what is t?Respectively carrying out dimensionless predicted values of primary fan current, secondary fan current and induced fan current at the time t;
3.3) solving the original dimensional prediction values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,respectively obtaining original dimensional predicted values of primary fan current, secondary fan current and induced fan current at the time t, namely current predicted values of all fans;
3.4) calculating the predicted value of the power consumption of the fan of the circulating fluidized bed boiler according to the following formula:
wherein, U1、U2、U3The power supply voltages of the primary fan, the secondary fan and the induced draft fan are respectively, and the unit is kV; respectively obtaining current predicted values of a primary fan, a secondary fan and an induced draft fan, wherein the unit is A;the power factors of the primary fan, the secondary fan and the induced draft fan are respectively; p is the predicted value of the power consumption of the fan of the circulating fluidized bed boiler, and the unit is kW.
The method further comprises the following steps: 4) acquiring field intelligent instrument signals according to a set sampling time interval, comparing the obtained actual primary fan current, secondary fan current and induced fan current with predicted values, if the relative error is more than 10%, adding new data into training sample data, and re-executing the steps 1) and 2) so as to update the prediction model.
In the step 3), reading the setting parameters from the control station, transmitting the predicted value of the power consumption of the fan to the control station for display, and giving an operation suggestion: under the current working condition, how to adjust the operation variables is most beneficial to reducing the power consumption of the fan, so that the control station staff can adjust the operation conditions in time according to the predicted value and the operation suggestion of the power consumption of the fan, reduce the power consumption of the fan and improve the operation efficiency of the boiler. The method is characterized in that the current value of the operation variable fluctuates up and down and is substituted into a fan power consumption prediction system to obtain a new fan power consumption prediction value, so that the new fan power consumption prediction value can be obtained visually by comparing the current value with the current value.
The independent variables include: the operation condition variables are as follows: main steam flow, environment temperature, water supply temperature, hearth negative pressure, bed pressure, coal moisture, coal volatile matter, coal ash and coal sulfur; the operation variables are as follows: the total air volume of the primary air and the total air volume of the secondary air.
While the system and method for predicting the power consumption of a circulating fluidized bed boiler fan have been described with reference to the above embodiments, it will be apparent to those skilled in the art that the present technology can be implemented by modifying or appropriately changing or combining the apparatus and method of operation described herein without departing from the spirit, scope and spirit of the present invention. It is expressly intended that all such similar substitutes and modifications which would be obvious to those skilled in the art are deemed to be within the spirit, scope and content of the invention.
Claims (2)
1. A power consumption prediction system for a fan of a circulating fluidized bed boiler is characterized by comprising an on-site intelligent instrument, a database, a data interface, a control station and an upper computer which are connected with the circulating fluidized bed boiler; on-spot intelligent instrument and control station, database and host computer are connected, the host computer include:
a standardization processing module for collecting historical records of operation condition variables and operation variables from the database, forming a training sample matrix X of independent variables, and collecting corresponding primary fan current, secondary fan current and induced fan current signalsHistorical records are formed to form a dependent variable training sample matrix Y, the training sample matrix X, Y is standardized to enable the mean value of each variable to be 0 and the variance to be 1, and a standardized independent variable training sample matrix X is obtained*(nxp), normalized dependent variable training sample matrix Y*(n × 3), using the following procedure to complete:
1.1) averaging:
1.2) calculating the standard deviation
1.3) normalization
Wherein x isij、yikIs the original value of the training sample point, n is the number of training samples, p is the number of independent variables,is the mean of the training samples, sx,j、sy,kIn order to train the standard deviation of the sample,the normalized values of the training sample points are shown, wherein subscripts i, j and k respectively represent the ith training sample point, the jth independent variable and the kth dependent variable;
the prediction mechanism forming module is used for establishing a prediction model and comprises the following implementation steps:
2.1) solving a prediction coefficient matrix beta according to the formula (7):
β＝(X*TX*)-1X*TY* (7)
wherein, the superscript: t, -1 respectively represents the transposition of the matrix and the inverse of the matrix;
2.2) transferring and storing the prediction coefficient matrix beta to a prediction execution module;
the prediction execution module is used for predicting the power consumption of the fan according to the operation condition of the circulating fluidized bed boiler and the set operation variable, and the implementation steps are as follows:
3.1) processing the input independent variable signal according to the formula (8):
wherein, x (t)jFor the jth original value of the independent variable at the time t,is the mean, s, of the jth independent variable training samplex,jFor the standard deviation of the jth independent variable training sample,is the jth independent variable dimensionless value at the t moment, and t represents time and unit is second;
3.2) solving the dimensionless predicted values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,respectively carrying out dimensionless predicted values of primary fan current, secondary fan current and induced fan current at the time t;
3.3) solving the original dimensional prediction values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,respectively obtaining original dimensional predicted values of primary fan current, secondary fan current and induced fan current at the time t, namely current predicted values of all fans;
3.4) calculating the predicted value of the power consumption of the fan of the circulating fluidized bed boiler according to the following formula:
wherein, U1、U2、U3The power supply voltages of the primary fan, the secondary fan and the induced draft fan are respectively, and the unit is kV; respectively obtaining predicted values of currents of the primary fan, the secondary fan and the induced fan at the time t, wherein the unit is A; the power factors of the primary fan, the secondary fan and the induced draft fan are respectively; p is the predicted value of the power consumption of the fan of the circulating fluidized bed boiler and the unit is kW;
the host computer still include:
the signal acquisition module is used for acquiring real-time data from the field intelligent instrument and historical data from the database according to a set sampling time interval;
the model updating module is used for comparing the actual primary fan current, secondary fan current and induced fan current with predicted values according to a set time interval, if the relative error is more than 10%, adding new data into training sample data, and executing the standardization processing module and the prediction mechanism forming module again;
and the result display module is used for reading the setting parameters from the control station, transmitting the predicted value of the power consumption of the fan to the control station for display and giving an operation suggestion: under the current working condition, how to adjust the operation variables is most beneficial to reducing the power consumption of the fan, so that a control station worker can adjust the operation conditions in time according to the predicted value and the operation suggestion of the power consumption of the fan, reduce the power consumption of the fan and improve the operation efficiency of the boiler; how to adjust the operation variables is most beneficial to reducing the power consumption of the fan, and the simple method is to substitute the current values of the operation variables into a fan power consumption prediction system to obtain a new fan power consumption prediction value, so that the new fan power consumption prediction value can be obtained very intuitively by comparing the sizes of the operation variables;
the independent variables include: the operation condition variables are as follows: main steam flow, environment temperature, water supply temperature, hearth negative pressure, bed pressure, coal moisture, coal volatile matter, coal ash and coal sulfur; the operation variables are as follows: the total air volume of the primary air and the total air volume of the secondary air.
2. A method for predicting power consumption of a fan of a circulating fluidized bed boiler by using the system for predicting power consumption of a fan of a circulating fluidized bed boiler according to claim 1, wherein the method for predicting power consumption of a fan comprises the following steps:
1) collecting historical records of operation condition variables and operation variables from a database to form an independent variable training sample matrix X, collecting corresponding historical records of primary fan current, secondary fan current and induced fan current signals to form a dependent variable training sample matrix Y, standardizing the training sample matrix X, Y to enable the mean value of each variable to be 0 and the variance to be 1, and obtaining the standardized independent variable training sample matrix X*(nxp), normalized dependent variable training sample matrix Y*(n × 3), using the following procedure to complete:
1.1) averaging:
1.2) calculating the standard deviation
1.3) normalization
Wherein x isij、yikIs the original value of the training sample point, n is the number of training samples, p is the number of independent variables,is the mean of the training samples, sx,j、sy,kIn order to train the standard deviation of the sample,the normalized values of the training sample points are shown, wherein subscripts i, j and k respectively represent the ith training sample point, the jth independent variable and the kth dependent variable;
2) and establishing a prediction model by the obtained standardized training sample through the following processes:
2.1) solving a prediction coefficient matrix beta according to the formula (7):
β＝(X*TX*)-1X*TY* (7)
wherein, the superscript: t, -1 respectively represents the transposition of the matrix and the inverse of the matrix;
2.2) storing the obtained prediction coefficient matrix beta;
3) the method comprises the following steps of taking operating condition variables and set operating variables of the circulating fluidized bed boiler as input signals, and predicting the power consumption of a fan according to a prediction coefficient vector, wherein the method comprises the following steps:
3.1) processing the input independent variable signal according to the formula (8):
wherein, x (t)jFor the jth original value of the independent variable at the time t,is the mean, s, of the jth independent variable training samplex,jFor the standard deviation of the jth independent variable training sample,is the jth independent variable dimensionless value at the t moment, and t represents time and unit is second;
3.2) solving the dimensionless predicted values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,respectively carrying out dimensionless predicted values of primary fan current, secondary fan current and induced fan current at the time t;
3.3) solving the original dimensional prediction values of the primary fan current, the secondary fan current and the induced fan current according to the following formula:
wherein,respectively obtaining original dimensional predicted values of primary fan current, secondary fan current and induced fan current at the time t, namely current predicted values of all fans;
3.4) calculating the predicted value of the power consumption of the fan of the circulating fluidized bed boiler according to the following formula:
wherein, U1、U2、U3The power supply voltages of the primary fan, the secondary fan and the induced draft fan are respectively, and the unit is kV; respectively obtaining current predicted values of a primary fan, a secondary fan and an induced draft fan, wherein the unit is A;the power factors of the primary fan, the secondary fan and the induced draft fan are respectively; p is the predicted value of the power consumption of the fan of the circulating fluidized bed boiler and the unit is kW;
the method further comprises the following steps: 4) acquiring on-site intelligent instrument signals according to a set sampling time interval, comparing the obtained actual primary fan current, secondary fan current and induced fan current with predicted values, if the relative error is more than 10%, adding new data into training sample data, and re-executing the steps 1) and 2) to update the prediction model;
in the step 3), reading the setting parameters from the control station, transmitting the predicted value of the power consumption of the fan to the control station for display, and giving an operation suggestion: under the current working condition, how to adjust the operation variables is most beneficial to reducing the power consumption of the fan, so that a control station worker can adjust the operation conditions in time according to the predicted value and the operation suggestion of the power consumption of the fan, reduce the power consumption of the fan and improve the operation efficiency of the boiler; how to adjust the operation variables is most beneficial to reducing the power consumption of the fan, and the simple method is to substitute the current values of the operation variables into a fan power consumption prediction system to obtain a new fan power consumption prediction value, so that the new fan power consumption prediction value can be obtained very intuitively by comparing the sizes of the operation variables;
the independent variables include: the operation condition variables are as follows: main steam flow, environment temperature, water supply temperature, hearth negative pressure, bed pressure, coal moisture, coal volatile matter, coal ash and coal sulfur; the operation variables are as follows: the total air volume of the primary air and the total air volume of the secondary air.
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