CN101718270A - 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:
First kind is the automatic Unloading Technology of air compressor, it breaks away from air compressor master motor and compression member automatically, and therefore this moment, air compressor did not produce pressurized gas, and 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.
Second kind is air compressor superpressure interlocking start and stop Electrical Control Technology, under the situation that this technology is big in load variations and the gas holder capacity is less, will cause the frequent start-stop of motor.Because the No Load Start electric current of air compressor approximately is 5～7 times of rated current, bigger to electrical network and the impact of other consumer, power consumption is bigger, 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 a steady state value, the output power of self-regulation motor.In pipe network, have under the situation of different pressures grade, the aerogenesis pressure of air compressor can not change along with the requirement with the gas load and regulate automatically, 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 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 automatically, 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, promptly 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;
Pressurized air pipe network pressure constraint conditio:
P
min(n)≤P(n)≤P
max(n)
P
Min(n) be meant the pipe network minimum pressure, can be used as one of condition that starts standby host;
P
Max(n) be meant 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) be meant corresponding to average quantity used in unit volume blasted delivery up to standard;
W
Gmax(n) be meant maximum delivery corresponding to the electrical network plan;
The constraint conditio that pipe network limits the air compressor gas production:
Q
Gmin(n) be meant the minimum tolerance of pipe network, by each minimum air demand of user with the minimum requirements of gas point usefulness gas;
Q
Gmax(n) be meant the maximum air demand of normal boot-strap in pipe network when (not containing standby air compressor);
With the past and following pressure input/output information, according to internal model, the pressure output 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 trajectory 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 the The whole control 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 be made up of 4 basic modules based on the model algorithm of predictive control theory control (MAC) mainly to comprise internal model, feedback compensation, rolling optimization calculating and with reference to several parts such as input trajectories.Its adopts nonparametric model based on impulse response as internal model, with the past and following pressure input/output information, according to internal model, the pressure output state in predicting system future, process carries out with the model output error comparing with the reference input trajectory 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 the The whole control circulation.This prediction pressure regulating method is 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 automatically, 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 is formed 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 the variation in pressure schematic representation before and after the prediction voltage control system is implemented, 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 trajectory 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 the The whole control 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 the calibration of ideal adaptation degree in addition and keep the diversity of population, adopt the mode of adaptive change to determine to intersect and the variation probability,, simplify the optimization solution procedure of multi-objective problem by once calculating the noninferior solution collection of the problem that can obtain.
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;
Pressurized air pipe network pressure constraint conditio is described below:
P
min(n)≤P(n)≤P
max(n)
P
Min(n) be meant the pipe network minimum pressure, can be used as one of condition that starts standby host;
P
Max(n) be meant 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) be meant corresponding to average quantity used in unit volume blasted delivery up to standard;
W
Gmax(n) be meant maximum delivery corresponding to the electrical network plan;
The constraint conditio that pipe network limits the air compressor gas production:
Q
Gmin(n) be meant the minimum tolerance of pipe network, by each minimum air demand of user with the minimum requirements of gas point usefulness gas;
Q
Gmax(n) be meant the maximum air demand of normal boot-strap in pipe network when (not containing standby air compressor);
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 pressurized 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, in that 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 the gas supply flow of monomer thus.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 collection quantity and evolution obtains the result of noninferior solution collection thus.
The decision support of dispatching center derives from Optimization Dispatching control strategy software kit, and software kit is based on Client, 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 Optimization Dispatching control strategy software kit 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 or the like 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 hose network optimization condition 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 the on-line data acquisition and the format analysis processing function of process requirements information such as throughput, the input of data matrix ensemble conduct " predictive controller " module that generates based on Data-Fusion theory.
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 pressurized air pipe network pressure, and converts the transmission signal 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 is made up of 4 basic modules based on the model algorithm of predictive control theory control (MAC) and is mainly comprised internal model, feedback compensation, rolling optimization calculating and with reference to several parts such as input trajectories.
The composition of " predictive controller ": (Fig. 2)
Its adopts nonparametric model based on impulse response as internal model, with the past and following pressure input/output information, according to internal model, the pressure output state in predicting system future, process carries out with the model output error comparing with the reference input trajectory 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 the The whole control circulation.Because this basic idea is: the output state in predicting system future at first, remove to determine the control action of current time again, promptly predict afterwards earlier 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 the calibration of ideal adaptation degree in addition and keep the diversity of population, adopt the mode of adaptive change to determine to intersect and the variation probability.This algorithm has been simplified the optimization solution procedure of multi-objective problem by once calculating the noninferior solution collection of the problem that can obtain.The key step of optimized Algorithm has fitness to calculate, intersect and variation probability calculation and optimal solution decision-making output.
The arthmetic statement block diagram of rolling optimization computing module is seen Fig. 3.
1) the variation in pressure schematic representation before and after the prediction voltage control system is implemented is seen 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 adapt to the variation of this load effectively, with satisfy the user with gas demand and the prerequisite predicted under, keep the constant relatively 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, causes the power consumption operation that unloading or emptying occur easily.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 remarkable 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 is provided with, given way is set to " long-range given " mode;
(5) method that can adopt traditional engineering to adjust for the parameter tuning of PID controller is to improve the control system precision, and control action should be selected astatic proportional integral regulating action.
Claims (2)
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, promptly 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;
Pressurized air pipe network pressure constraint conditio:
P
min(n)≤P(n)≤P
max(n)
P
Min(n) be meant the pipe network minimum pressure, as one of condition that starts standby host;
P
Max(n) be meant 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) be meant corresponding to average quantity used in unit volume blasted delivery up to standard;
W
Gmax(n) be meant 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) be meant the minimum tolerance of pipe network, by each minimum air demand of user with the minimum requirements of gas point usefulness gas;
Q
Gmax(n) be meant the maximum air demand of normal boot-strap in pipe network when (not containing standby air compressor);
With the past and following pressure input/output information, according to internal model, the pressure output 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 trajectory 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 the The whole control circulation.
2. the prediction pressure regulating method of control system of air compressor according to claim 1, it is characterized in that: described application quadratic performance index is carried out rolling optimization calculation optimization algorithm steps and is:
(1) fitness E
i(X
j) calculate;
(2) crossover probability P
cWith the variation probability P
mCalculate;
(3) optimal solution is preserved.
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