CN116972516A - Intelligent control method, system and storage medium for central air conditioner - Google Patents
Intelligent control method, system and storage medium for central air conditioner Download PDFInfo
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 139
- 238000001816 cooling Methods 0.000 claims description 29
- 238000004378 air conditioning Methods 0.000 claims description 23
- 239000000498 cooling water Substances 0.000 claims description 17
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Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/80—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air
- F24F11/83—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air by controlling the supply of heat-exchange fluids to heat-exchangers
- F24F11/85—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air by controlling the supply of heat-exchange fluids to heat-exchangers using variable-flow pumps
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/54—Control or safety arrangements characterised by user interfaces or communication using one central controller connected to several sub-controllers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/56—Remote control
- F24F11/58—Remote control using Internet communication
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/20—Humidity
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2140/00—Control inputs relating to system states
- F24F2140/20—Heat-exchange fluid temperature
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Abstract
The invention relates to a central air conditioner control intelligent control method, which is used for controlling sparsity filling of a strategy library by a multidimensional interpolation algorithm, realizing strategy simulation of the whole working condition of a central air conditioner system, providing a dynamic optimization strategy of the running working condition of an on-line dynamic simulation system, providing a control strategy on line by predicting cold load and measuring the outside temperature and relative humidity in real time, solving the defects of poor energy saving effect and overlong time of the optimization strategy caused by the running mode set by expert experience of the current control strategy, providing dynamic strategy output and ensuring the continuous stability of equipment by a comparison algorithm.
Description
Technical Field
The invention relates to the technical field of automatic control, in particular to a central air conditioner control intelligent control method, a system and a storage medium.
Background
In recent years, a central air conditioning system of a large building is accessed to the BAS for unified management, but most of the application of machine room equipment in the BAS is simple logic control and data monitoring, the automation degree is low, and the optimal operation is difficult to realize. Because the central air conditioning system is in a state of partial load operation for a long time in the actual operation process, and because the operation working condition is set according to seasonal load change or working time by means of expert experience, the data monitored by the BAS system is a large amount of repeated actual operation data in the stable operation state, so that sparsity of the operation data is caused.
In practical application, the control strategy of the central air conditioning system in the prior art generally adopts the operation parameters of the cold source system and the environmental parameters as the control strategy of the working condition according to the specific application environment of the central air conditioning system, including the influence of the geographical position on the temperature and humidity, the system topology structure, the influence of the load and the performance of each device on the response and the like. For such control strategy optimization, there are two existing optimization strategy modes, one is offline optimization and the other is online optimization. For online optimization, due to limitation of calculation speed (overlong optimization time) and time-lag characteristics of a central air conditioning system, a strategy cannot be provided for the current working condition in real time, and online strategies are frequently provided, so that the service life of equipment is reduced by continuously adjusting control parameters of the equipment. For offline optimization, the optimization control strategy under the working condition can only be calculated in advance for a limited number of times, and for the combination of actual working condition diversity, the offline optimization strategy is sparse. Once the working condition changes slightly, the corresponding optimal control strategy cannot be found out from the offline strategy library.
Disclosure of Invention
In order to solve the technical problems, the invention provides a risk control method, a risk control system, a server and a storage medium.
The utility model provides a central air conditioning control intelligent control method, central air conditioning includes cold source system and control system, cold source system includes a plurality of chilled water pumps, a plurality of cooling towers and a plurality of cooling water sets and a plurality of temperature sensor, humidity transducer, flow sensor, control system includes control strategy storehouse, its characterized in that, control strategy storehouse's input is system cooling load, ambient temperature, environment relative humidity, chilled water system water supply temperature, chilled water system total flow and chilled water system water supply return pressure differential, control strategy storehouse's output is the operating parameter of cold source system, control strategy optimization method includes:
s10, establishing an expression model between input and output of a control strategy, wherein the input is discretized according to a numerical range;
s20, performing inverse distance weight interpolation based on k nearest neighbors on the discretized input parameters, and calculating output of each interpolation;
s30, determining an optimal control strategy based on the output of each interpolation;
s40, comparing the control strategy with the control strategy in the current state, and determining the executed control strategy according to the comparison result.
The utility model provides a central air conditioning control intelligent control system, central air conditioning includes cold source system and control system, cold source system includes a plurality of chilled water pumps, a plurality of cooling water pump, a plurality of cooling tower and a plurality of cooling water set and a plurality of temperature sensor, humidity transducer, flow sensor, control system includes control strategy storehouse and control strategy storehouse optimization module, control strategy storehouse's input is system cooling load, ambient temperature, environment relative humidity, chilled water system water supply temperature, chilled water system total flow and chilled water system water supply return pressure differential, control strategy storehouse's output is the operating parameter of cold source system, control strategy storehouse optimization module includes:
the model building module is used for building an expression model between the input and the output of the control strategy, wherein the input is discretized according to the numerical range;
the interpolation module is used for interpolating the discretized input parameters by adopting inverse distance weights based on k nearest neighbors and calculating the output of each interpolation;
the optimization module is used for determining an optimal control strategy based on the output of each interpolation;
and the determining module is used for comparing the control strategy with the control strategy in the current state and determining the executed control strategy according to the comparison result.
The invention has the following beneficial technical effects:
1. the method for establishing the offline strategy library is adopted to convert the online optimization which is overlong in time into the offline optimization, so that the efficiency of searching the optimization strategy is improved.
2. The multi-dimensional interpolation algorithm is used for filling the sparsity of the strategy library, so that the strategy simulation of the all-working condition of the central air conditioning system is realized.
3. And a dynamic optimization strategy for dynamically simulating the operation condition of the system on line is provided, and a control strategy is provided on line through the prediction of the cold load and the real-time measurement of the temperature and the relative humidity of an external dry bulb.
4. And providing a preferred strategy library comparison algorithm in the preferred strategies, and selecting the most energy-saving strategy under the condition of ensuring the stability of the actual operation.
5. Calculating the strategy in real time for too long, and optimizing by utilizing the off-line strategy library; compared with optimization, the system can run stably, the real-time processing mode related to the actual processing mode is adopted for the optimization strategy, for example, a forward tracing mode is adopted for frequent switching, and damage to a unit caused by repeated start and stop is avoided.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
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The foregoing and/or additional aspects and advantages of the invention will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
fig. 1 is a diagram illustrating a comparison between a to-be-inserted point and a grid node according to an embodiment of the present invention.
Fig. 2 is a diagram showing upper and lower boundaries of finding points to be interpolated according to an embodiment of the present invention.
Fig. 3 is a grid node division diagram of an embodiment of the present invention.
Fig. 4 is a flowchart of the calculation and screening of the optimal strategy according to the embodiment of the present invention.
Fig. 5 is a flowchart of an intelligent control method according to an embodiment of the present invention.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
A typical central air conditioning system includes a plurality of chilled water pumps, a plurality of cooling towers and a plurality of chiller units, as well as a plurality of temperature sensors, humidity sensors, and flow sensors. The conventional central air conditioning cold source control system generally provides a static strategy, and one or more combinations of a system cold load, an environment temperature, an environment relative humidity, a chilled water system water supply temperature, a chilled water system total flow and a chilled water system water supply and return pressure difference are generally adopted as input of the air conditioning system control strategy, and the opening states of each water chilling unit, the chilled water pump, the cooling water pump and the cooling tower and corresponding operation frequencies are adopted as output of the control strategy. Because the experience of operators is limited, equipment opening modes are often selected according to seasonal load changes or working time, and the central air conditioning system is stable in operation within a period of time. Even if each device of the system is continuously monitored, the obtained data is a large number of repeated actual operation data, so that the sparsity of the data is caused.
The invention provides an intelligent control method of a central air conditioner, the central air conditioner comprises a cold source system and a control system, the cold source system comprises a plurality of chilled water pumps, a plurality of cooling towers, a plurality of water chilling units, a plurality of temperature sensors, humidity sensors and flow sensors, the control system comprises a control strategy library, the input of the control strategy library is a system cold load, an environment temperature, an environment relative humidity, a chilled water system water supply temperature, a chilled water system total flow and a chilled water system water supply return pressure difference, the output of the control strategy library is an operation parameter of the cold source system, and the control strategy optimization method comprises the following steps: s10, establishing an expression model between input and output of a control strategy, wherein the input is discretized according to a numerical range of the input.
For the purpose of explanation, the foregoing control method is exemplified in detail. Specifically, the input of the central air conditioning control strategy library is 6 external constraint variables: the system cooling load, the environment temperature, the environment relative humidity, the chilled water system water supply temperature, the chilled water system total flow and the chilled water system water supply return pressure difference. The 3 external constraint variables that are not artificially regulated are: system cooling load, ambient temperature, and ambient relative humidity; the 3 external constraint variables determined according to the load distribution characteristics of the air conditioning system are: the water supply temperature of the chilled water system, the total flow of the chilled water system and the pressure difference of the water supply and return of the chilled water system. The output of the central air-conditioning control strategy library is the opening states of the water chilling unit, the chilled water pump, the cooling water pump and the cooling tower and the corresponding operating frequencies. In the prior art, the 6 external constraint variables are generally respectively and uniformly matched with 5 different level values to form 15625 different combinations. In detail, the six dimensions are the cooling load X, respectively 0 Outdoor dry bulb temperature X 1 Outdoor ambient relative humidity X 2 (independent variables); chilled water system water supply temperature X 3 Total flow X of chilled water system 4 Pressure difference X of water supply and return of chilled water system pipe network 5 (dependent variable). Distribution of policy libraries is 5× 5×5 x 5 = 15625 conditions.
Under certain conditions of system cooling load, environment temperature and environment relative humidity, the water supply temperature of the chilled water system, the total flow of the chilled water system and the water supply and return pressure difference of the chilled water system can be combined in various ways, and the 3 constraint variables are strongly coupled instead of independent variables and are required to be determined according to building load prediction or experience. The synergistic relationship can be expressed generally as follows:
the water supply temperature of the chilled water system is t_bowl_out respectively 0 、t_chiller_out 1 、……、t_chiller_out n The method comprises the steps of carrying out a first treatment on the surface of the The total flow range of the chilled water system corresponding to the water supply temperature of each chilled water system is G-pipe 0 (0)～G_chiller 0 (n)]、[G_chiller 1 (0)～G_chiller 1 (n)]、
……、[G_chiller n (0)～G_chiller n (n)]The method comprises the steps of carrying out a first treatment on the surface of the The pressure difference range of the water supply and return of the chilled water system corresponding to the total flow of each chilled water system is [ delta P ] 0_0 (0)～ΔP 0_0 (n)]、[ΔP 0_1 (0)～ΔP 0_1 (n)]、……、[ΔP n_n (0)～ΔP n_n (n)]。
From the above, it is clear that a certain chilled water supply temperature necessarily corresponds to a certain chilled water flow range (not lower than the minimum flow requirement), a certain chilled water flow corresponds to a certain water supply/return pressure difference range (not lower than the minimum water supply/return pressure difference), and such a correspondence is related to load characteristics, and it is necessary to perform load calculation analysis and prediction in advance, and when the conditions are not satisfied, the mutual constraint relationship may be empirically set.
The invention firstly uses the determined water supply temperature range of the chilled water system (t_bowl_out) 0 ～t_chiller_out n ]The method can be divided into 20 partitions, and can be divided into any mode which is larger than 5, namely [ t_impeller_out ] 0 ，t_chiller_out 1 ，…，t_chiller_out 20 ]The water supply temperature of each chilled water system corresponds to one G-bowl 0 (0)，G_chiller 0 (1)，…，G_chiller 0 (20)]And each chilled water flow corresponds to one [ delta P ] 0_0 (0)，ΔP 0_0 (1)，…ΔP 0_0 (20)]Wherein G_bowl 0 (0) To correspond to the minimum flow rate at the water supply temperature, deltaP 00 (0) Is the minimum supply water back pressure difference corresponding to the minimum flow. Therefore, the flow range can be obtained according to the temperature, and then the pressure difference change range can be obtained according to the flow, and the combination modes are as follows: 21×21×21=9261.
Under a certain condition of the set value of the differential pressure bypass regulating valve, a certain chilled water supply temperature is known, and then a certain minimum chilled water flow is necessarily corresponding to a certain minimum water supply return pressure difference. For such a coupling relationship, theoretically, in order to ensure that the flow rate of the pipe network side and the pressure difference of the required water supply and return can completely coincide with the flow rate and the effective pressure difference provided by the cold source side, the set value of the pressure difference bypass regulating valve needs to be regulated in real time so as to be equal to the effective pressure difference provided by the cold source side, so that if the flow rate of the required chilled water of the pipe network is smaller than the flow rate of the chilled water provided by the cold source system, the excessive chilled water returns to the cold source system through the bypass pipeline, and meanwhile, the pressure difference of the water supply and return of the pipe network can be maintained to be the same as the pressure difference provided by the cold source system (on the premise of dynamically regulating the set value of the pressure difference bypass regulating valve), and the offline optimization control strategy can be played to the greatest extent at this time. However, in fact, the cooperative relationship of the water supply temperature, the flow and the pressure difference cannot be obtained very accurately through the load analysis in advance, and certain uncertainty is necessarily present, so that comparison and analysis with a strategy library cannot be performed according to the uncertainty, and in order to solve the contradiction, compromise treatment is required, part of energy saving rate is sacrificed, and the system is exchanged for stable operation. In actual engineering, the differential pressure bypass adjustment valve setting is usually set at a certain value, and adjustment is rarely performed. In some cases, the bypass regulating valve can be regulated according to seasons, different values can be set in different seasons, but dynamic real-time regulation setting is almost impossible unless the bypass regulating valve has a remote communication function and supports remote dynamic regulation.
Based on the above consideration, in practical application, due to the inevitable existence of the bypass loop of the chilled water system design, it is impossible to dynamically adjust the set value of the differential pressure bypass regulating valve in real time. Therefore, the relation among the water outlet temperature, the flow and the pressure difference of the chilled water under the coupling of different cold loads and wet loads can be obtained through calculation and analysis (or experience) in advance, a cooperative database of the corresponding relation is constructed in advance, and the selection can be performed according to the system cold loads, the environment temperature and humidity, the time and the like during actual operation. The scope may be determined approximately from engineering experience when the collaborative database is not calculated. If a synergistic relationship is selected, the discrete processing can be performed as follows:
the water supply temperature of the chilled water system is t_bowl_out respectively 0 、t_chiller_out 1 、……、t_chiller_out 20 The method comprises the steps of carrying out a first treatment on the surface of the The total flow range of the chilled water system corresponding to the water supply temperature of each chilled water system is G-pipe 0 (0)～G_chiller 0 (20)]、[G_chiller 1 (0)～G_chiller 1 (20)]、…、[G_chiller 20 (0)～G_chiller 20 (20)]The method comprises the steps of carrying out a first treatment on the surface of the The corresponding pressure difference range of the water supply and return of the chilled water system is [ delta P ] 0 (0)～ΔP 0 (20)]、[ΔP 1 (0)～ΔP 1 (20)]、…、[ΔP 20 (0)～ΔP 20 (20)]。
S20, performing inverse distance weight interpolation based on k nearest neighbors on the discretized input parameters, and calculating output of each interpolation.
Specifically, after discretization treatment of the chilled water supply temperature, the chilled water flow and the chilled water pipe network water supply and return pressure difference according to the above rules, under the condition of knowing the cooling load, the outdoor environment temperature and the relative humidity of the actual operation data, the following combination mode can be adopted:
wherein Q is a cold load, t Environment (environment) Is the temperature of the dry ball in the external environment,g_bowl for relative humidity of external environment n (0) And DeltaP n (0) The minimum chilled water flow and the pipe network water supply and return pressure difference corresponding to the water supply temperature are changed along with the change of the water supply temperature; g_bowl n (20) The maximum possible chilled water flow (settable to a fixed value), Δp, of the position system can be set n (20) The pressure differential bypass regulator valve is manually set (typically, not frequently adjusted, and may be considered constant over time). Therefore, there are (20+21) ×21=861 combinations in a certain state, that is, 861 times of inverse distance weight interpolation calculation is required in a certain operation state, and the optimal operation strategy is selected from the 861 times of interpolation results.
For multidimensional interpolation, the inputs are 861 combinations, and interpolation calculation is performed once for each input. Interpolation calculation adopts inverse distance weight interpolation based on k neighbor. The basic idea is that the closer the discrete point is to the estimated point, the greater the impact on the estimated point and the greater the weight; conversely, the farther a discrete point is from an estimated point, the less impact.
The processing of the independent variables is: aliquoting the 3-dimensional mesh nodes 20;
judging the inputted cooling load X 0 _input、X 1 _input、X 2 In which section of 20 equal divisions the input is located, the median is taken as the input calculated value
The processing of dependent variables is: and searching a corresponding coupling rule of the dependent variable according to the independent variable, namely the external environment parameter. 41 combinations of chilled water supply temperature t_bowl_out; the water supply temperature of 21 chilled water is 861 in total.I.e. each of the above combinationsThe corresponding value of the mode.
The above combinations are summarized, namely 861 combinations are available under an external working condition.
For points to be interpolated，
The normalized points are
And finding the upper and lower boundary points of each dimension of the point to be interpolated.
Combining the upper boundary node and the lower boundary node of each dimension one by one to obtain 2 adjacent to the point to be interpolated 6 =64 neighbors.
Since the distribution intervals of six-dimensional grid nodes in the policy repository are 3125, 625, 125, 25, 5, 1, respectively.
For each upper and lower boundary combination mode, a distributed line label in a strategy library:
64 neighboring points (X) are extracted by 64 labels 0 (j),X 1 (j),X 2 (j),X 3 (j),X 4 (j),X 5 (j))。
Interpolation calculation adopts inverse distance weight interpolation based on k neighbor. The basic idea is that the closer the discrete point is to the estimated point, the greater the impact on the estimated point and the greater the weight; conversely, the farther a discrete point is from an estimated point, the less impact.
Definition d t For the distance of the point to be interpolated from the neighboring points (t=1, 2, …, 64)
Definition omega t Weights corresponding to the t-th neighbor (t=1, 2, …, 64)
The result of the multidimensional inverse distance weighted interpolation is:
since the operating frequency ranges of the chilled water pump, the cooling water pump and the cooling tower are equivalently processed by the operating frequency range set values, such as the operating frequency ranges of the chilled water pump [30Hz,50Hz ], the operating frequency ranges of the cooling water pump [30Hz,50Hz ], and the operating frequency ranges of the cooling tower fan [25Hz,50Hz ], in order to avoid interpolation errors, whether the corresponding power equipment is in the operating state is firstly determined, if the operating frequency is zero, the minimum frequency is assigned in interpolation calculation, such as that a certain optimizing strategy corresponds to a certain chilled water pump operating frequency of 0, and if the interpolation is in interpolation, the minimum frequency is assigned to be 30 Hz.
S30, determining an optimal control strategy based on the output of each interpolation.
Specifically, for the interpolation results, the energy efficiency ratio EER ordering is performed on 861 interpolation results, the strategy screening is performed from high to low, and the operation strategy with reasonable interpolation results is output as the interpolation results. If the interpolation result is still unreasonable, the nearest optimal control strategy can be selected only for the result in the existing strategy library.
The screening rule is that the running number of the chilled water pump, the cooling water pump and the cooling tower should be equal to or greater than the running number of the water chilling unit and the running number of the water chilling unit is not in an open state between blind areas. The running number of the chilled water pump, the cooling water pump and the cooling tower is larger than or equal to that of the water chilling unit, and the rules are corrected before the control strategy is finally output.
When the interpolation calculation is carried out on the operation state of the tower pump, the interpolation is carried out within the range of 0-1. If the interpolation result is greater than or equal to 0.5, the device is considered to be in open control, otherwise, the device is considered to be in closed control. However, because whether the interpolation result around 0.5 is 0 or 1 is fuzzy, measures of setting blind areas for the interpolation result are adopted, and the results of the host, the chilled water pump, the cooling water pump and the cooling tower in the blind areas are screened and discarded, so that the fuzzy result of the opening state is avoided. For the result of the screening, it is the policy with the highest EER among the reasonable results. Although not the most energy efficient strategy, its stability and rationality are guaranteed.
S40, comparing the control strategy with the control strategy in the current state, and determining the executed control strategy according to the comparison result.
In one embodiment of the invention, the situation that the tower pumps are connected in parallel in the same type in the cold source system of the central air conditioner is considered. If the optimization strategy is not processed, the control strategy of the front and rear states (or the two strategy comparison time nodes) can be completely different, if the control input is directly carried out according to the result, the frequent start-stop operation of the equipment can be caused, and the service life of the equipment can be greatly influenced. Some large-scale and ultra-large-scale central air conditioning systems such as large buildings and factories are used in scenes, and the frequent start-stop operation is extremely easy to cause impact on a power grid. The invention can be processed as follows: compared with the start-stop control states of the front and rear water chilling units, if the running host numbers are different but the models are the same, the host running control strategy in the last state needs to be maintained at the moment, for example, the host group running control strategy in the last state is [1# on ，2# off ，3# on ，4# off ，5# on ]The host group control operation control strategy of the current state is [1 #) off ，2# on ，3# on ，4# off ，5# on ]Wherein the upper mark on/off represents the start-stop control state of the corresponding numbered host, and if the model of the 1# host and the 2# host is the same or the rated refrigerating capacity is the same, the current state is thatThe state host group control strategy should be adjusted to [1 #) on ，2# off ，3# on ，4# off ，5# on ]Thereby avoiding the operation and replacement of the host. And in the same way, the starting and stopping control strategy adjustment modes of the chilled water pump, the cooling water pump and the cooling tower are the same as those of the host, and the operation frequency of corresponding equipment is also adjusted accordingly. The interpolation results of the frequencies of the chilled water pump, the cooling water pump and the cooling tower are necessarily within the limited range of the operating frequency. If the frequency is used for judging the switch, all the devices are in an on state, so that the frequency of the device which is turned off is assigned 0 when the start-stop judgment is performed, and the frequency interpolation result is kept by the device which is turned on when the start-stop judgment is performed. The frequency can be changed along with the continuous operation of the equipment, but the fluctuation of the frequency cannot be too large, so that the stability of the unit can be greatly reduced, the variation of the current operation frequency and the operation frequency of the last state of the equipment can be set for the operation frequency control of the circulating water pump and the cooling tower, for example, the allowable variation is set to be 5Hz, and if the variation of the operation frequency in the front and back states is larger than the set value, the current operation frequency is maintained.
In one embodiment of the invention, the situation that different types of tower pumps are connected in parallel in a cold source system of a central air conditioner is considered. The cold source system comprises a high-power host and a low-power host, for example, the host group operation control strategy of the last state is [ 1] on ，2# off ，3# on ，4# off ，5# on ]The host group control operation control strategy of the current state is [1 #) off ，2# on ，3# on ，4# off ，5# on ]Wherein the upper mark on/off represents the start-stop control state of the host with corresponding number, if the host 1 is a low-power host or the rated refrigerating capacity is smaller, the host 2 is a high-power host or the rated refrigerating capacity is larger. When the load of the central air conditioning system is too small and the large opening rate causes too small flow rate of the refrigerating water, the machine set is easy to be down, so that judgment is needed and a strategy for opening the machine is forced to be made at the moment, namely, the current state host group control strategy is adjusted to be [1# on ，2# off ，3# on ，4# off ，5# on ]Thereby avoiding the operation and replacement of the host.
An embodiment of the invention provides a central air conditioner control strategy optimization system, which comprises a cold source system and a control system, wherein the cold source system comprises a plurality of chilled water pumps, a plurality of cooling towers, a plurality of water chilling units, a plurality of temperature sensors, humidity sensors and flow sensors, the control system comprises a control strategy library and a control strategy library optimization module, and the inputs of the control strategy library are system cold load, environment temperature, environment relative humidity, chilled water system water supply temperature and chilled water system total flow
And a chilled water system water supply and return pressure difference, wherein the output of the control strategy library is an operation parameter of the cold source system, and the control strategy library optimization module comprises:
the model building module is used for building an expression model between the input and the output of the control strategy, wherein the input is discretized according to the numerical range;
the interpolation module is used for interpolating the discretized input parameters by adopting inverse distance weights based on k nearest neighbors and calculating the output of each interpolation;
the optimization module is used for determining an optimal control strategy based on the output of each interpolation;
and the determining module is used for comparing the control strategy with the control strategy in the current state and determining the executed control strategy according to the comparison result.
The control strategy library optimization module adopts the central air conditioner control strategy optimization method of the previous embodiment.
In addition, one embodiment of the present invention also provides a computer apparatus including: the intelligent control system comprises a memory, a processor and a computer program which is stored in the memory and can run the intelligent control method of the central air conditioner on the processor. The processor and the memory may be connected by a bus or other means. The memory, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory remotely located relative to the processor, the remote memory being connectable to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
In addition, an embodiment of the present invention also provides a computer readable storage medium storing computer executable instructions that are executed by a processor or controller to perform the above-described intelligent control method of a central air conditioner.
Those of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the invention, and all changes of the equivalent structure or direct/indirect application of the present invention in this specification are included in the scope of the invention.
Claims (10)
1. The utility model provides a central air conditioning control intelligent control method, central air conditioning includes cold source system and control system, cold source system includes a plurality of chilled water pumps, a plurality of cooling towers and a plurality of cooling water sets and a plurality of temperature sensor, humidity transducer, flow sensor, control system includes control strategy storehouse, its characterized in that, control strategy storehouse's input is system cold load, ambient temperature, environment relative humidity, chilled water system water supply temperature, chilled water system total flow and chilled water system water supply return pressure differential, control strategy storehouse's output is the operating parameter of cold source system, intelligent control method includes:
s10, establishing an expression model between input and output of a control strategy, wherein the input is discretized according to a numerical range;
s20, performing inverse distance weight interpolation based on k nearest neighbors on the discretized input parameters, and calculating output of each interpolation;
s30, determining an optimal control strategy based on the output of each interpolation;
s40, comparing the control strategy with the control strategy in the current state, and determining the executed control strategy according to the comparison result.
2. The intelligent control method for controlling a central air conditioner according to claim 1, wherein the operation parameters of the cold source system include the on states of a water chiller, a chilled water pump, a cooling tower and corresponding operation frequencies.
3. The intelligent control method for controlling a central air conditioner according to claim 1, wherein the input is discretized according to a numerical range thereof into a plurality of level values discretized according to an integer multiple of 5 of the numerical range thereof.
4. The intelligent control method according to claim 1, wherein the determining an optimal control strategy based on the output of each interpolation comprises: and (3) sorting the energy efficiency ratio EER of the output of each interpolation, carrying out strategy screening from high to low, and taking the operation strategy with reasonable interpolation results as the optimal control strategy.
5. The intelligent control method for controlling a central air conditioner according to claim 1, wherein the plurality of water chilling units, chilled water pumps, cooling water pumps and cooling towers of the cold source system comprise at least two similar devices with the same model, the same power or the same specification, the step of comparing the control strategy with the control strategy in the current state, and determining the executed control strategy according to the comparison result comprises the following steps:
and if the comparison result of the control strategy and the control strategy in the current state is that the two similar devices with the same model, the same power or the same specification are exchanged in the start-stop state, the control strategy in the current state is continuously executed.
6. The utility model provides a central air conditioning intelligent control system, central air conditioning includes cold source system and control system, cold source system includes a plurality of chilled water pumps, a plurality of cooling water pump, a plurality of cooling tower and a plurality of cooling water set and a plurality of temperature sensor, humidity transducer, flow sensor, control system includes control strategy storehouse and control strategy storehouse optimization module, control strategy storehouse's input is system cold load, ambient temperature, environment relative humidity, chilled water system water supply temperature, chilled water system total flow and chilled water system water supply return pressure differential, control strategy storehouse's output is the operating parameter of cold source system, control strategy storehouse optimization module includes:
the model building module is used for building an expression model between the input and the output of the control strategy, wherein the input is discretized according to the numerical range;
the interpolation module is used for interpolating the discretized input parameters by adopting inverse distance weights based on k nearest neighbors and calculating the output of each interpolation;
the optimization module is used for determining an optimal control strategy based on the output of each interpolation;
and the determining module is used for comparing the control strategy with the control strategy in the current state and determining the executed control strategy according to the comparison result.
7. The intelligent control system of a central air conditioner according to claim 6, wherein the operation parameters of the cold source system include the on state of a chiller, a chilled water pump, a cooling tower and the corresponding operation frequency.
8. The intelligent control system according to claim 6, wherein the input is discretized according to its range of values into an integer multiple of horizontal values of 5 according to its range of values.
9. The central air conditioner control strategy optimization system of claim 6, wherein said determining an optimal control strategy based on said interpolated outputs comprises: the energy efficiency ratio EER is sequenced for the output of each interpolation, strategy screening is carried out from high to low, and the operation strategy with reasonable interpolation result is used as the optimal control strategy;
the plurality of water chilling units, the chilled water pump, the cooling water pump and the cooling tower of the cold source system comprise at least two similar devices with the same model, the same power or the same specification, the control strategy is compared with the control strategy in the current state, and the step of determining the executed control strategy according to the comparison result comprises the following steps: and if the comparison result of the control strategy and the control strategy in the current state is that the two similar devices with the same model, the same power or the same specification are exchanged in the start-stop state, the control strategy in the current state is continuously executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 5.
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