CN101718270B - Prediction and pressure regulation method for control system of air compressor - Google Patents
Prediction and pressure regulation method for control system of air compressor Download PDFInfo
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Abstract
The invention relates to a prediction and pressure regulation method for a control system of an air compressor, which comprises the following steps: adopting an impulse response-based non-parametric model as an internal model, and predicting the future output state of the control system of the air compressor; using the model for outputting errors, carrying out feedback correction, further being compared with the reference input trajectory, applying an quadratic performance index for rolling optimization, then further calculating the control action to be added on the system at the current time, and completing the whole control cycle. The prediction and pressure regulation method can obtain the running state and the pressure regulation set value of the air compressor by automatically detecting air-using time, air-using pressure and air-using flow rate of all air-using points, achieve the pressure balance regulation of a pipe network of an air compression plant, simultaneously effectively avoid the unloading operation of the air compressor and the emptying operation of a pipeline and achieve the purpose of energy-saving control.
Description
Technical field
The present invention relates to a kind of energy conservation of compressor and automatic control technology
Background technique
In actual motion, when the air compressor underrun, the gas holder internal pressure rises when reaching setting pressure, needs to regulate ductwork pressure, and prior art is most widely used to mainly contain three kinds:
The first is air compressor Self-tipping technology, it make pneumatics owner motor and compression member automatic trip from, therefore this moment, air compressor did not produce pressurized gas, motor is in no-load running, its power consumption is approximately about 10% of the specified operation of motor, and the electric energy reality of this part has gratuitously been consumed.
The second is air compressor superpressure interlocking start and stop Electrical Control Technology, and this technology will cause the frequent start-stop of motor in the situation that load variations is large and the gas holder capacity is less.Because the No Load Start electric current of air compressor approximately is 5～7 times of rated current, larger to electrical network and the impact of other consumer, power consumption is larger, and simultaneously, the motor of air compressor also can shorten working life.
The third is to adopt the constant pressure frequency conversion control technique, guarantees that the outlet pressure of separate unit air compressor is steady state value, the output power of self-regulation motor.In the situation that the different pressures grade is arranged in the pipe network, the aerogenesis pressure of air compressor can not change along with the requirement with the gas load and automatically regulate, existing method often adopts the pressure rating that improves the whole piece pipeline, adopts decompressor to supply with the low pressure gas equipment, thereby causes energy waste.
Summary of the invention
The present invention is the prediction pressure regulating method that a kind of control system of air compressor will be provided, this prediction pressure regulating method is automatically to detect each using the gas time, use atmospheric pressure and obtaining compressor operation state and pressure regulation setting value with throughput by the prediction pressure regulating method with gas point, reach air compressor plant ductwork pressure balance adjustment, simultaneously effectively avoid occurring air compressor unloading operation and pipeline emptying manipulation, reach energy-conservation control purpose.
For achieving the above object, technological scheme of the present invention is: a kind of prediction pressure regulating method of control system of air compressor may further comprise the steps:
1. predict the control system of air compressor output state in future
As internal model, namely compressed air supply system satisfies and makes the objective function of air feed maximization and the minimized medium-term and long-term scheduling model of electricity consumption be under the constraint conditio based on the nonparametric model of impulse response in employing:
In the formula:
Q
nBe n period pipe network total gas production and;
Q
GnIt is the total gas consumption of n period pipe network;
P
nIt is the power consumption of n period pipe network;
Compressed air pipe network pressure constraint conditio:
P
min(n)≤P(n)≤P
max(n)
P
Min(n) refer to the pipe network minimum pressure, can be used as one of condition that starts standby host;
P
Max(n) refer to maximum pressure, can be used as startup adjusting air compressor and go out one of condition of atmospheric pressure means;
The constraint conditio of pipe network power consumption: W
Gmin(n)≤W
g(n)≤W
Gmax(n)
W
Gmin(n) refer to corresponding to average quantity used in unit volume blasted delivery up to standard;
W
Gmax(n) refer to maximum delivery corresponding to the electrical network plan;
Pipe network is to the constraint conditio of air compressor gas production restriction: Q
Nmin(n)≤Q
n(n)≤Q
Max(n)
Q
Gmin(n) refer to the minimum tolerance of pipe network, by each minimum air demand with the minimum requirements of gas point usefulness gas of user;
Q
Gmax(n) refer to the maximum air demand of normal boot-strap in pipe network when (not containing air compressor for subsequent use);
With past and following pressure input/output information, according to internal model, the Output pressure state in predicting system future;
2. calculate the control action that current time should be added on system
After carrying out feedback compensation with the model output error, compare with the reference input track again, use quadratic performance index and carry out rolling optimization, and then calculate the control action that current time should be added on system, finish whole controlled circulation.
Use quadratic performance index and carry out rolling optimization calculation optimization algorithm steps:
(4) fitness E
i(X
j) calculate;
(5) crossover probability P
cWith the variation probability P
mCalculate;
(6) optimal solution is preserved.
Beneficial effect of the present invention really is: the present invention adopts predictive control algorithm to form several parts such as mainly comprising internal model, feedback compensation, rolling optimization calculating and reference input track based on the model algorithm control (MAC) of predictive control theory by 4 basic modules.Its adopts nonparametric model based on impulse response as internal model, with past and following pressure input/output information, according to internal model, the Output pressure state in predicting system future, process carries out with the model output error comparing with the reference input track after the feedback compensation again, uses quadratic performance index and carries out rolling optimization, and then calculate the control action that current time should be added on system, finish whole controlled circulation.This prediction pressure regulating method is automatically to detect each using the gas time, use atmospheric pressure and obtaining compressor operation state and pressure regulation setting value with throughput by the prediction pressure regulating method with gas point, reach air compressor plant ductwork pressure balance adjustment, simultaneously effectively avoid occurring air compressor unloading operation and pipeline emptying manipulation, reach energy-conservation control purpose.
Description of drawings
Fig. 1 is that air compressor prediction voltage control system forms module diagram;
Fig. 2 is the composition module diagram of predictive controller;
Fig. 3 is the arthmetic statement block diagram of rolling optimization computing module;
Fig. 4 is that the pressure before and after the prediction voltage control system is implemented changes schematic diagram, and wherein: a is before implementing, and b is after implementing.
Embodiment
The present invention is further illustrated below in conjunction with accompanying drawing and embodiment.
The prediction pressure regulating method of control system of air compressor of the present invention comprises:
(1) employing as internal model, is predicted the control system of air compressor output state in future based on the nonparametric model of impulse response;
(2) carry out feedback compensation with the model output error after, compare with the reference input track again, use quadratic performance index and carry out rolling optimization, and then calculate the control action that current time should be added on system, finish whole controlled circulation.
To be control system produce a large amount of feasible solutions and implicit these characteristics of concurrency design a kind of decision optimization method according to genetic algorithm per generation to core technology of the present invention, based on the performance Matrix Measure feasible solution of ordering, the fine or not vector of all target population performances is compared.Introduce in addition the calibration of ideal adaptation degree and keep population diversity, adopt the mode of adaptive change to determine the crossover and mutation probability, by once calculating the Noninferior Solution Set that can obtain problem, simplify the Optimization Solution step of multi-objective problem.
Concrete grammar is described below:
1, compressed air supply system satisfies and makes the objective function of air feed maximization and the minimized medium-term and long-term scheduling model of electricity consumption be under the constraint conditio:
In the formula:
Q
nBe n period pipe network total gas production and;
Q
GnIt is the total gas consumption of n period pipe network;
P
nIt is the power consumption of n period pipe network;
Compressed air pipe network pressure constraint conditio is described below:
P
min(n)≤P(n)≤P
max(n)
P
Min(n) refer to the pipe network minimum pressure, can be used as one of condition that starts standby host;
P
Max(n) refer to maximum pressure, can be used as startup adjusting air compressor and go out one of condition of atmospheric pressure means;
The constraint conditio of pipe network power consumption: W
Gmin(n)≤W
g(n)≤W
Gmax(n)
W
Gmin(n) refer to corresponding to average quantity used in unit volume blasted delivery up to standard;
W
Gmax(n) refer to maximum delivery corresponding to the electrical network plan;
Pipe network is to the constraint conditio of air compressor gas production restriction: Q
Nmin(n)≤Q
n(n)≤Q
Max(n)
Q
Gmin(n) refer to the minimum tolerance of pipe network, by each minimum air demand with the minimum requirements of gas point usefulness gas of user;
Q
Gmax(n) refer to the maximum air demand of normal boot-strap in pipe network when (not containing air compressor for subsequent use);
Above-mentioned constraint conditio is that optimized algorithm has been determined appropriate scope.
Optimized algorithm after the individuality generation variation to certain ductwork pressure representative, adds chromosome sequence with compressed air pipe network period average pressure value sequence structure chromosome, takes the way of random value simultaneously in appropriate scope.In the calculating of single air compressor individuality, at first satisfy pressure and the flow that guarantees usefulness gas point, residue tolerance is being avoided under the prerequisite of emptying manipulation, be assigned randomly to other gas holder and air feed branch road in the pipe network, and regulate thus the gas supply flow of monomer.When pressure and the individuality of flow, introducing punishment and the superseded mechanism that guarantees usefulness gas point occurring to satisfy.
Each gene can be characterized by the force value of day part in the individuality, utilizes above-mentioned constraint conditio, and the rationality of checking ductwork pressure sequence is got rid of the individuality that does not meet minimum requirements.
Adopt the initial conditions of multi-objective optimization algorithm to comprise individual population quantity, initial crossover probability, the variation probability, the progression of Noninferior Solution Set quantity and evolution obtains the result of Noninferior Solution Set thus.
The decision support of dispatching center derives from optimal dispatch control tactical software bag, and software kit is based on Client/Server pattern, and its core is the multiple-objection optimization computing module.All air compressors and attached controllable device thereof in the pipe network are controlled by the dispatching center, the input of optimal dispatch control tactical software bag is the operation information of full pipe network, and output comprises regulates the control information that pressure given value, valve opening and working time and state etc. have decision-making character.The key step of calculation optimization algorithm has fitness E
i(X
j) calculate, crossover probability P
cWith the variation probability P
mCalculating, optimal solution conversation strategy.
The final result of optimized algorithm is the noninferior solution relation of minimum power consumption under the compressed air pipe network optimal conditions and maximum gas production, be used in reference to air compressor and the running state of supplementary equipment and the automatic control of exerting oneself in the conduit network, reach the energy-conservation purpose of economical rationality operation.
The composition of air compressor prediction Regulation Control device of the present invention: (Fig. 1)
1) " pipe network process data acquisition module " finish comprise each with gas point with the gas time, with atmospheric pressure, with on-line data acquisition and the format analysis processing function of the process requirements information such as throughput, the input of data matrix ensemble conduct " predictive controller " module that the based on data blending theory generates.
2) " PID regulator " is the stable basis of control system.The output of " predictive controller " is given voltage-regulating system " baton ".
3) converter plant is based on the ac variable frequency speed regulation skill device of vector control algorithm, according to the output signal of " PID regulator ", changes the motor operation frequency of air compressor, thereby changes the delivery pressure of air compressor.
4) " air compressor " is the controlled device of control system, can adopt centrifugal, screw type or piston type air compressor.
5) " pressure transmitter " is the detection device of control system feedback element, is used for online detection compressed air pipe network pressure, and converts the signal transmission of standard to, can adopt the detection transmitter of condenser type or piezoelectricity type.
6) " predictive controller " finishes the optimized algorithm based on multiobjective decision-making, and predictive control algorithm forms several parts such as mainly comprising internal model, feedback compensation, rolling optimization calculating and reference input track based on the model algorithm control (MAC) of predictive control theory by 4 basic modules.
The composition of " predictive controller ": (Fig. 2)
Its adopts nonparametric model based on impulse response as internal model, with past and following pressure input/output information, according to internal model, the Output pressure state in predicting system future, process carries out with the model output error comparing with the reference input track after the feedback compensation again, uses quadratic performance index and carries out rolling optimization, and then calculate the control action that current time should be added on system, finish whole controlled circulation.Because the basic thought of this algorithm is: the output state in predicting system future at first, remove again to determine the control action of current time, namely predict afterwards first and control, so have foresight.
Rolling optimization computing module has wherein adopted the multi-objective optimization algorithm that is suitable for compressor operation, to be control system produce a large amount of feasible solutions and implicit these characteristics of concurrency design a kind of decision optimization method according to genetic algorithm per generation to core technology, based on the performance Matrix Measure feasible solution of ordering, the fine or not vector of all target population performances is compared.Introduce in addition the calibration of ideal adaptation degree and keep population diversity, adopt the mode of adaptive change to determine the crossover and mutation probability.This algorithm has been simplified the Optimization Solution step of multi-objective problem by once calculating the Noninferior Solution Set that can obtain problem.The key step of optimized algorithm has fitness calculating, crossover and mutation probability calculation and optimal solution decision-making output.
The arthmetic statement block diagram of rolling optimization computing module is seen Fig. 3.
1) pressure before and after the prediction voltage control system is implemented changes schematic diagram and sees Fig. 4.Pressure history before Fig. 4 a implements illustrates that there is the irregular variation of load in compressed-air actuated user, thereby air compressor aerogenesis pressure is changed.The fluctuation of aerogenesis pressure may cause air compressor to carry out continually to add unloading and emptying manipulation, caused energy waste, therefore objectively require control system of air compressor can effectively adapt to the variation of this load, with satisfy the user with gas demand and the prerequisite predicted under, keep the relatively constant of aerogenesis pressure.
As can be known, air compressor goes out atmospheric pressure because the broken line that occurred by load variations changes from Fig. 4 a, easily causes the power consumption operation that unloading or emptying occur.Fig. 4 b obviously eases up for predicting the pressure diagram after the pressure regulation, has eliminated the possible condition that unloading or emptying manipulation occur, and compares with original system, has obvious energy-saving effect.
Embodiment:
(1) at first, adopt programmable controller as predictive controller, purpose is to rely on the programmable controller hardware platform, according to prediction curve, adopts industry control programming language international standard IEC61131-3 to programme generation forecast control program module;
(2) input of predictive control program module is the status data according to actual conditions, and output is the predetermined value of air compressor and supplementary equipment thereof in the pipe network;
(3) setting value is carried out the voltage/current signals cell translation after, output to the long-range given signal end of original PID controller;
(4) in the PID controller arranges, given way is set to " long-range given " mode;
The method that (5) can adopt traditional engineering to adjust for the parameter tuning of PID controller is to improve Control system resolution, and control action should be selected astatic proportional integral regulating action.
Claims (1)
1. the prediction pressure regulating method of a control system of air compressor is characterized in that: may further comprise the steps:
(1) predicts the control system of air compressor output state in future
As internal model, namely compressed air supply system satisfies and makes the objective function of air feed maximization and the minimized medium-term and long-term scheduling model of electricity consumption be under the constraint conditio based on the nonparametric model of impulse response in employing:
In the formula:
Q
nBe n period pipe network total gas production and;
Q
GnIt is the total gas consumption of n period pipe network;
P
nIt is the power consumption of n period pipe network;
Compressed air pipe network pressure constraint conditio:
P
min(n)≤P(n)≤P
max(n)
P
Min(n) refer to the pipe network minimum pressure, as one of condition that starts standby host;
P
Max(n) refer to maximum pressure, go out one of condition of atmospheric pressure means as starting the adjusting air compressor;
The constraint conditio of pipe network power consumption:
W
Gmin(n) refer to corresponding to average quantity used in unit volume blasted delivery up to standard;
W
Gmax(n) refer to maximum delivery corresponding to the electrical network plan;
The constraint conditio that pipe network limits the air compressor gas production:
Q
Nmin(n) refer to the minimum tolerance of pipe network, by each minimum air demand with the minimum requirements of gas point usefulness gas of user;
Q
MaxMaximum air demand when (n) referring to normal boot-strap in the pipe network;
With past and following pressure input/output information, according to internal model, the Output pressure state in predicting system future;
(2) calculate the control action that current time should be added on system
After carrying out feedback compensation with the model output error, compare with the reference input track again, use quadratic performance index and carry out rolling optimization, and then calculate the control action that current time should be added on system, finish whole controlled circulation.
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| CN101718270B true CN101718270B (en) | 2013-02-20 |
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| CN101901014B (en) * | 2009-05-27 | 2012-02-22 | 宝山钢铁股份有限公司 | Method for controlling forecast pressure regulation in air compression stations |
| CN103049625A (en) * | 2011-10-11 | 2013-04-17 | 新鼎系统股份有限公司 | Forecast management method for air compressor operation |
| CN105201805B (en) * | 2015-10-16 | 2017-03-22 | 宝钢发展有限公司 | Air compressor set intelligent control system and method based on user informatization allocation |
| CN108087255B (en) * | 2017-12-08 | 2019-09-24 | 四川长虹空调有限公司 | The controller and self checking method of compressor |
| CN108361186B (en) * | 2018-02-27 | 2019-11-29 | 首钢京唐钢铁联合有限责任公司 | Optimization method for air compressor system of steel plant |
| CN109164704B (en) * | 2018-08-07 | 2021-03-26 | 大连理工大学 | Air compressor group optimal scheduling method based on hybrid model |
| CN108870078A (en) * | 2018-08-22 | 2018-11-23 | 江苏核电有限公司 | A kind of generator hydrogen dryer pneumatic operated valve control compressed air source unit and its control method |
| CN109213219B (en) * | 2018-09-29 | 2021-04-06 | 浙江工业大学 | Pressure prediction control method for gas phase replacement and medicine moistening process of traditional Chinese medicine decoction pieces |
| CN109340094B (en) * | 2018-11-16 | 2020-11-10 | 广东汇嵘绿色能源股份有限公司 | Load-based air compressor energy-saving control method |
| CN109931253B (en) * | 2019-03-29 | 2020-07-07 | 四川虹美智能科技有限公司 | Method and device for determining control parameters of compressor |
| CN110131147B (en) * | 2019-05-14 | 2020-06-05 | 南京尚爱机械制造有限公司 | Intelligent control mode for ensuring constant-pressure output of air compressor |
| CN110486261B (en) * | 2019-07-17 | 2020-12-29 | 北京中竞国际能源科技有限公司 | Air compressor set allocation system and method based on multipoint pressure track prediction |
| CN110456752B (en) * | 2019-08-19 | 2020-12-01 | 蘑菇物联技术（深圳）有限公司 | Air compression station control method based on combination of plan scheduling and algorithm scheduling |
| CN113050573B (en) * | 2021-03-26 | 2022-09-13 | 山东莱钢永锋钢铁有限公司 | Production rhythm-based energy-saving method for air compressor |
| CN113530790B (en) * | 2021-06-21 | 2022-10-04 | 蘑菇物联技术（深圳）有限公司 | Control method and device of air compressor and readable storage medium |
| CN113464415B (en) * | 2021-09-03 | 2021-12-03 | 蘑菇物联技术（深圳）有限公司 | Method, apparatus and computer storage medium for controlling air compressor of air compression station |
| CN114109777B (en) * | 2021-12-02 | 2022-06-24 | 广东鑫钻节能科技股份有限公司 | Electric energy management system for air compression station |
| CN117605660B (en) * | 2023-10-23 | 2024-07-26 | 意朗智能科技(南通)有限公司 | Dynamic energy-saving control method and system for air compressor |
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