CN112556258A - Heat pump intelligent control method for compensating time delay - Google Patents
Heat pump intelligent control method for compensating time delay Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
- F25B49/00—Arrangement or mounting of control or safety devices
- F25B49/02—Arrangement or mounting of control or safety devices for compression type machines, plants or systems
Abstract
The invention provides an intelligent heat pump control method for compensating time delay. Introducing a speed change temperature difference adjusting concept, monitoring the actual temperature difference of a loop circulation working medium supply return side of the fan at the tail end to represent the actual load of the system, intervening the rotating speed of the fan through frequency conversion, and adjusting the flow of the loop to enable the temperature difference to follow a set value; establishing a transfer function model of a terminal fan subsystem and identifying parameters; and then designing a fuzzy PID with a deviation amplification effect and combining a Smith estimation algorithm to accurately control the established terminal fan subsystem model. According to the method, the working frequency of the system is matched with the actual load through variable frequency speed regulation, a deviation gain link is added before a fuzzy control link to obtain higher error identification precision, and the hysteresis of a terminal fan subsystem is compensated through Smith estimation, so that the energy-saving benefit and the self-adaptive capacity of the control system are improved.
Description
Technical Field
The invention relates to the technical field of ground source heat pumps, in particular to an intelligent heat pump control method for compensating time delay.
Background
Although the installed capacity of renewable energy sources such as wind power generation, solar power generation and the like in China increases rapidly and the marginal cost is gradually reduced, the practical application of the renewable energy sources can not meet the requirements of climate strategies, the energy strategy needs to implement a policy of opening sources and reducing the energy consumption, the opening sources are to accept and use the renewable energy sources as much as possible, and the main task of reducing the energy consumption is to save energy and improve the energy use efficiency. Meanwhile, the shallow ground surface absorbs 47% of solar radiation energy, and the low-grade heat energy stored in the shallow ground surface is called as 'geothermal energy', and the shallow ground surface is taken as an unlimited renewable clean energy source, so that how to utilize the shallow ground surface is worthy of thinking. Under the background, an 'electric energy replacement strategy' is produced at the right moment, and a ground source heat pump is taken as a classic example of 'replacing coal with electricity' which is one of the core ideas of the strategy, so that the method is greatly popularized by national power grid companies. The cold and heat of the ground source heat pump system are obtained from a rock-soil layer with a relatively constant temperature working condition, the COP value of the unit is kept above 4, namely, 1kW high-grade electric energy is consumed, so that about 4kW cold or heat can be obtained, and the operation efficiency is extremely high; under the refrigeration working condition, compared with a common central air-conditioning system, the ground source heat pump air-conditioning system can save energy by 30-40 percent; under the heating working condition, compared with a gas boiler floor heating system, the energy can be saved by 40-50%, and the energy-saving and emission-reducing effects are obvious.
However, in the current process of operating the ground source heat pump system, the consumption of high-grade electric energy by devices such as a fan and a compressor is large, meanwhile, the response delay inevitably exists in the control system due to the characteristics of nonlinearity, time lag and the like of each subsystem of the ground source heat pump, and how to solve the two problems is the key point for the ground source heat pump to stand out in the field of electric energy substitution.
Therefore, a proper mathematical model is established for the key components of the ground source heat pump system, the performance of the ground source heat pump control system is improved by an advanced control algorithm strategy on the basis, the self-adaptive capacity of the ground source heat pump control system is improved, and the method has important significance for the popularization of the ground source heat pump system.
In order to solve the technical problem, publication No. CN204987374U discloses a ground source heat pump air-conditioning energy-saving system, which includes a heat pump unit, a ground source side water circulation pump, a primary side water circulation pump, a secondary side water circulation pump, a peak-regulation heating water circulation pump, a cooling tower, a user side and an underground pipe network, wherein the ground source side water circulation pump is connected with a ground source side water circulation pump controller, the secondary side water circulation pump is connected with a secondary side water circulation pump controller, the peak-regulation heating water circulation pump is connected with a peak-regulation heating water circulation pump controller, and the user side is connected with a user side controller. The energy-saving system of the ground source heat pump air conditioner adopts the PID frequency conversion technology to realize variable flow control of the system, eliminates energy waste caused by controlling the opening of a valve, and improves the control precision of the system. But the ground source heat pump air-conditioning energy-saving system still cannot solve the time delay problem of the control system.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the ground source heat pump system has large power consumption and the control system has the technical problem of time delay.
In order to solve the technical problem and compensate the control time delay of the heat pump, the invention provides an intelligent control method of the heat pump for compensating the time delay, which comprises the following steps:
B1. setting a standard value delta T of the temperature difference between the supply side and the return side of the circulating working medium of the loop of the tail end fan0，
B2. Acquiring an actual temperature difference value delta T between a supply side and a return side of a circulating working medium of a loop of the tail end fan, and calculating a deviation e between a standard temperature difference value and an actual temperature difference value0＝ΔT0- Δ T, while calculating e0Rate of change of (ec)0
B3. Establishing a transfer function model of a terminal fan subsystem, wherein the relation between the rotating speed of the terminal fan and the temperature of the return side of the circulating working medium is a second-order model with hysteresis
In an approximate representation of the above-described,
B4. the deviation e between the standard value and the actual value of the temperature difference0And the change rate of the deviation amount is used as an input amount, the system is controlled by combining fuzzy PID with the deviation amount amplification effect and the Smith estimation algorithm, and the transformation transfer function of the system is
When the e is a positive value, namely the set value is larger than the feedback value, the running speed of the fan is accelerated, the temperature difference follows the set value again, and the system state is kept constant; otherwise, the rotating speed of the fan is reduced, and the temperature difference is made to follow the set value, so that new balance is established. After the deviation value is amplified, the control method can capture a tiny input quantity, so that the breadth and the precision of the output quantity are improved, namely the PID parameter adjustment quantity is finer, and the control effect is better. A Smith estimation algorithm is introduced to control the system, and the time delay in the control process can be compensated.
Preferably, the step B3 includes the following steps
B31. The terminal fan model is regarded as the series connection of indoor heat transfer and a fan coil, and the transfer function of an indoor heat transfer link is
In the formula KrFor indoor transmissionGain of thermal system, TrIs the indoor heat transfer time constant
The transfer function of the fan coil is
In the formula KfFor fan coil system gain, TfIs the time constant of the fan coil
B32. Transfer function of the end fan model
In the formula Kfan＝Kr×Kf。
Preferably, the step B4 includes the following steps
B41. A deviation gain link for performing proportional amplification on the input of the fuzzy controller
(e,ec)＝K(e,ec)(e0,ec0) In the formula
e is the amplified temperature difference deviation amount, ec is the amplified temperature difference deviation amount change rate, K (e, ec) is the amplification factor,
B42. determining input and output variable discourse domain, fuzzy language subset and membership function, reasoning by fuzzy controller under the guidance of fuzzy rule, outputting variable quantity delta K of PID parameter after the process of clarificationP、ΔKiAnd Δ Kd,
B43. Variation Δ K according to PID parameterP、ΔKiAnd Δ KdAdjusting PID parameter KP、KiAnd Kd，
Kp＝Kp0+ΔKp
Ki＝Ki0+ΔKi
Kd＝Kd0+ΔKd
B43. A Smith estimation loop is connected in parallel outside the controller to move a system feedback point forward, and the introduced Smith estimation loop has the following form:
transfer function C(s) of the controller, and transfer function G of the Smith pre-estimation loopn(s) and transfer function G of end fan subsystemfan(s) the transformation transfer function of the system is obtained as
B44. When the supply-return side temperature difference deviation e is a positive value, namely the set value is larger than the feedback value, the running speed of the fan is accelerated, the temperature difference follows the set value again, and the system state is kept constant; otherwise, the rotating speed of the fan is reduced, and the temperature difference is made to follow the set value, so that new balance is established.
Preferably, the method further comprises the following steps:
B5. collecting indoor temperature D every other period Tw1When the heat pump is refrigerating, if the indoor temperature D is collected in X continuous periods1When the values are all lower than the set value of the heat pump, the power of the heat pump compressor is reduced, and the fan rotating speed control parameters return to the initial state; when the heat pump heats, if the indoor temperature D is collected in X continuous periods1When the values are all higher than the set value of the heat pump, the power of the heat pump compressor is reduced, and the control parameters of the rotating speed of the fan return to the initial state.
Preferably, the step B42 determines the input and output variable domains as follows:
an input variable e [ -3,3 ]; an input variable ec ∈ [ -3,3 ];
output variable Δ KP∈[-0.3,0.3](ii) a Output variable Δ Ki∈[-0.01,0.01](ii) a Output variable Δ Kd∈[-2,2]。
Preferably, the fuzzy language subset of the input and output variables of step B42 is divided into:
Variable＝{NB,NM,NS,ZO,PS,PM,PB}
wherein, the subsets from left to right respectively represent negative big, negative middle, negative small, zero, positive small, positive middle and positive big, the membership functions all adopt a triangular form, and the clarification process adopts an area barycenter method. In order to obtain accurate control quantity, a fuzzy method is required to well express the calculation result of the output membership function. The gravity center method is to take the gravity center of the area enclosed by the membership function curve and the abscissa as the final output value of the fuzzy inference. The center of gravity method has smoother output inference control. The output varies even in response to a slight variation in the input signal.
The substantial effects of the invention are as follows: based on a variable speed temperature difference control strategy, a fuzzy PID with a deviation amplification function is combined with a Smith estimation algorithm, the robustness of PID control and the flexibility of fuzzy control are combined, a deviation gain link is added before the fuzzy control link to obtain higher error identification precision, and finally the hysteresis of a terminal fan subsystem is compensated through Smith estimation, so that the established terminal fan subsystem model is accurately controlled, and the working frequency of the system is matched with the actual load through variable frequency speed regulation, so that the energy-saving benefit and the self-adaptive capacity of the control system are improved.
Drawings
Figure 1 is a schematic control principle diagram of the first embodiment,
figure 2 is a graph comparing the response characteristic of the embodiment one with that of the PID control algorithm only,
FIG. 3 is a graph comparing response curves of an embodiment with PID combined with a Smith prediction algorithm.
In the figure: 1. the response characteristic curve of the first embodiment, 2. the response characteristic curve under the PID control algorithm only, and 3. the response characteristic curve under the PID combined Smith estimation algorithm.
Detailed Description
The following provides a more detailed description of the present invention, with reference to the accompanying drawings.
As shown in fig. 1, the present invention provides an intelligent heat pump control method for compensating time delay, which includes the following steps:
B1. setting the supply side and the return flow of the circulating working medium of the loop of the tail end fanSide temperature difference standard value delta T0，
B2. Acquiring an actual temperature difference value delta T between a supply side and a return side of a circulating working medium of a loop of the tail end fan, and calculating a deviation e between a standard temperature difference value and an actual temperature difference value0＝ΔT0- Δ T, while calculating e0Rate of change of (ec)0
B3. Establishing a transfer function model of a terminal fan subsystem, wherein the relation between the rotating speed of the terminal fan and the temperature of the return side of the circulating working medium is a second-order model with hysteresis
In an approximate representation of the above-described,
B4. the deviation e between the standard value and the actual value of the temperature difference0And the change rate of the deviation amount is used as an input amount, the system is controlled by combining fuzzy PID with the deviation amount amplification effect and the Smith estimation algorithm, and the transformation transfer function of the system is
After the transfer function model identification parameters of the terminal fan subsystem are
And designing a fuzzy PID (proportion integration differentiation) combined Smith estimation algorithm with deviation amplification in the step B3. The algorithm comprises a deviation gain link, a fuzzy control link, a PID control link and a Smith estimation link.
Firstly, the deviation gain link amplifies the input of the fuzzy controller in proportion
(e,ec)＝K(e,ec)(e0,ec0)
In the formula e0,ec0And e, ec respectively represent the deviation amount of the temperature difference before and after amplification and the change rate thereof, K(e,ec)Is a gain factor to improve the error recognition accuracy.
Secondly, the input and output variables of the fuzzy controller are determined as follows
An input variable e [ -3,3 ]; an input variable ec ∈ [ -3,3 ];
output variable Δ KP∈[-0.3,0.3](ii) a Output variable Δ Ki∈[-0.01,0.01](ii) a Output variable Δ Kd∈[-2,2]。
The fuzzy language subset of input and output variables is divided into:
Variable＝{NB,NM,NS,ZO,PS,PM,PB}
wherein each subset respectively represents negative big, negative middle, negative small, zero, positive small, positive middle and positive big, the membership functions all adopt a triangular form, and the clarification process adopts an area barycenter method. The speed change temperature difference control process comprises the following steps: the real-time load of the real-time temperature difference representation system of the circulating working medium supply return side of the loop of the tail end fan is monitored, the deviation value and the change rate of the real-time temperature difference and the set temperature difference value are used as input, the variable frequency speed regulation is carried out on the fan under the fuzzy PID with the function of amplifying the deviation value and the Smith pre-estimation method, and the loop flow is adjusted to stabilize the real-time temperature difference of the circulating working medium supply return side and enable the circulating working medium supply return side to follow the set.
Further, the PID control link outputs delta K to the fuzzy control linkp,ΔKi,ΔKdAnd (3) superimposing the parameters to a PID parameter preset value as an optimal control parameter, wherein the parameter adjustment formula is as follows:
Kp＝Kp0+ΔKp
Ki＝Ki0+ΔKi
Kd＝Kd0+ΔKd
and finally, introducing a Smith predictor, namely connecting a Smith loop outside the controller in parallel, equivalently moving a system feedback point forward to compensate a pure time delay link of a terminal fan subsystem
The resulting loss of control performance, the introduced Smith prediction loop has the following form:
Gn(s)e-τs
wherein
And is
The transformation transfer function of the whole system is
In the above formula, c(s) is the transfer function of the controller.
Further, when the deviation of the temperature difference between the circulating working medium and the return temperature is a positive value, namely the set value is larger than the feedback value, namely the actual feedback value is smaller (the temperature of the return side of the circulating working medium is lower and the heat absorption is less), the frequency converter increases the output frequency, accelerates the running speed of the fan, enables the temperature difference to follow the set value again, and maintains the system state to be constant; otherwise, the frequency converter reduces the output frequency, the rotating speed of the fan is reduced, the output power is reduced, and the temperature difference is made to follow the set value, so that new balance is established, and the purpose of controlling the indoor temperature and the air quantity of the user side to be stable is achieved.
As shown in fig. 2 or fig. 3, based on a transfer function model of a terminal fan subsystem, a theoretical temperature difference value is set to 10 ℃, positive 1 ℃ disturbance is introduced at a certain time to simulate an indoor temperature mutation process, the robustness of the algorithm is verified, and the algorithm is compared with the control effect of a PID control algorithm alone and the control effect of a PID combined Smith estimation algorithm. Therefore, the following steps are carried out: compared with the control only by PID control and the control only by PID combined with Smith estimation, the fuzzy PID combined with Smith estimation algorithm with the deviation amplification effect has more excellent performance, small overshoot amount, quick rise time, fastest time for recovering stability after disturbance is introduced, almost no steady-state error, strong adaptive capacity of the control system running under the algorithm and good robustness. The practical benefits applied to the fan subsystem at the tail end of the ground source heat pump are as follows: the method has a good compensation effect on the lag response of the fan and the indoor heat transfer, and when the indoor temperature changes, the fan can run more reasonably and the temperature can be recovered to a set value more quickly.
The above-described embodiments are only preferred embodiments of the present invention, and are not intended to limit the present invention in any way, and other variations and modifications may be made without departing from the spirit of the invention as set forth in the claims.
Claims (6)
1. A heat pump intelligent control method for compensating time delay is used for controlling a fan at the tail end of a heat pump, and is characterized in that: the method comprises the following steps:
B1. setting a standard value delta T of the temperature difference between the supply side and the return side of the circulating working medium of the loop of the tail end fan0，
B2. Acquiring an actual temperature difference value delta T between a supply side and a return side of a circulating working medium of a loop of the tail end fan, and calculating a deviation e between a standard temperature difference value and an actual temperature difference value0＝ΔT0- Δ T, while calculating e0Rate of change of (ec)0
B3. Establishing a transfer function model of a terminal fan subsystem, wherein the relation between the rotating speed of the terminal fan and the temperature of the return side of the circulating working medium is a second-order model with hysteresis
In an approximate representation of the above-described,
B4. the deviation e between the standard value and the actual value of the temperature difference0And the change rate of the deviation amount is used as an input amount, the system is controlled by combining fuzzy PID with the deviation amount amplification effect and the Smith estimation algorithm, and the transformation transfer function of the system is
When the e is a positive value, namely the set value is larger than the feedback value, the running speed of the fan is accelerated, the temperature difference follows the set value again, and the system state is kept constant; otherwise, the rotating speed of the fan is reduced, and the temperature difference is made to follow the set value, so that new balance is established.
2. The intelligent control method for heat pump compensating time delay as claimed in claim 1, wherein said step B3 comprises the following steps
B31. The terminal fan model is regarded as the series connection of indoor heat transfer and a fan coil, and the transfer function of an indoor heat transfer link is
In the formula KrFor indoor heat transfer system gain, TrIs the indoor heat transfer time constant
The transfer function of the fan coil is
In the formula KfFor fan coil system gain, TfIs the time constant of the fan coil
B32. Transfer function of the end fan model
In the formula Kfan＝Kr×Kf。
3. The intelligent control method for heat pump compensating time delay as claimed in claim 1, wherein said step B4 comprises the following steps
B41. A deviation gain link for performing proportional amplification on the input of the fuzzy controller
(e,ec)＝K(e,ec)(e0,ec0) In the formula
e is the amplified temperature difference deviation amount, ec is the amplified temperature difference deviation amount change rate, K (e, ec) is the amplification factor,
B42. determining input and output variable discourse domain, fuzzy language subset and membership function, reasoning by fuzzy controller under the guidance of fuzzy rule, outputting variable quantity delta K of PID parameter after the process of clarificationP、ΔKiAnd Δ Kd,
B43. Variation Δ K according to PID parameterP、ΔKiAnd Δ KdAdjusting PID parameter KP、KiAnd Kd，
Kp＝Kp0+ΔKp
Ki＝Ki0+ΔKi
Kd＝Kd0+ΔKd
B43. A Smith estimation loop is connected in parallel outside the controller to move a system feedback point forward, and the introduced Smith estimation loop has the following form:
transfer function C(s) of the controller, and transfer function G of the Smith pre-estimation loopn(s) and transfer function G of end fan subsystemfan(s) the transformation transfer function of the system is obtained as
B44. When the supply-return side temperature difference deviation e is a positive value, namely the set value is larger than the feedback value, the running speed of the fan is accelerated, the temperature difference follows the set value again, and the system state is kept constant; otherwise, the rotating speed of the fan is reduced, and the temperature difference is made to follow the set value, so that new balance is established.
4. The intelligent control method for the heat pump compensating the time delay as claimed in claim 1, characterized by further comprising the following steps:
B5. collecting indoor temperature D every other period Tw1When the heat pump is refrigerating, if the indoor temperature D is collected in X continuous periods1When the values are all lower than the set value of the heat pump, the power of the heat pump compressor is reduced, and the fan rotating speed control parameters return to the initial state; when the heat pump is used for heating,if the indoor temperature D is collected in X continuous periods1When the values are all higher than the set value of the heat pump, the power of the heat pump compressor is reduced, and the control parameters of the rotating speed of the fan return to the initial state.
5. The intelligent control method for the heat pump compensating time delay as claimed in claim 3, wherein: the step B42 determines the input-output variable domains of discourse as follows:
an input variable e [ -3,3 ]; an input variable ec ∈ [ -3,3 ];
output variable Δ KP∈[-0.3,0.3](ii) a Output variable Δ Ki∈[-0.01,0.01](ii) a Output variable Δ Kd∈[-2,2]。
6. The intelligent control method for the heat pump compensating time delay as claimed in claim 3, wherein: the fuzzy language subset of the step B42 input/output variables is divided into:
Variable＝{NB,NM,NS,ZO,PS,PM,PB}
wherein, the subsets from left to right respectively represent negative big, negative middle, negative small, zero, positive small, positive middle and positive big, the membership functions all adopt a triangular form, and the clarification process adopts an area barycenter method.
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