CN115978720B - Unequal grouping method for air source heat pump units - Google Patents
Unequal grouping method for air source heat pump units Download PDFInfo
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Abstract
The invention belongs to the field of refrigeration and heating of air source heat pump units, and provides a non-equivalent grouping method of the air source heat pump units, which comprises the steps of collecting external data, analyzing the data, grouping control, periodically detecting the running state, and realizing the effect of non-equivalent adjustment of the work arrangement of each component according to the use condition by collecting external influence factor data, analyzing the collected data and grouping control; by automatically and regularly evaluating the running condition of the system, timely finding problems and adjusting a grouping scheme, the effects of automatic maintenance and regular fault checking are realized; the system solves the problems that the existing air source heat pump unit is low in energy efficiency ratio, high in energy cost and short of a group monitoring management mechanism due to a single regulation mode, and high in operation cost due to the fact that workers are required to go to the site for maintenance under the condition of faults, improves the operation efficiency of the heat pump unit and reduces the operation cost.
Description
Technical Field
The invention belongs to the field of refrigeration and heating of air source heat pump units, in particular to a non-equivalent grouping method of air source heat pump units, and the optimization of the operation flow of the air source heat pump units is realized by optimizing the grouping method of the air source heat pump units.
Background
The air source heat pump unit is one kind of indoor heating and refrigerating equipment with outside air as energy source, and has the operation principle of compressing outside air via compressor, changing the operation of the evaporator and the condenser in the heat pump unit via the reversing valve to heat or cool the air exhausted to indoor, so as to realize the heating and refrigerating effect in winter.
The existing air source heat pump unit can realize the effect that each component is started and stopped simultaneously, but the existing air source heat pump unit still has the following problems:
1. each heat pump in the existing air source heat pump unit operates independently, and is usually started and stopped automatically only according to user instructions or external environment, however, under certain scenes needing the heat pump unit to be closed in advance or in a delayed manner, the idle running of the heat pump unit causes energy waste, and the single regulation mode of the traditional heat pump unit causes the problems of low energy efficiency ratio and high energy cost;
2. the existing air source heat pump unit has the advantages of multiple product series, wide user distribution range, higher failure rate of the product in the operation process, timely feedback of the user is required for various problems, and the existing air source heat pump unit lacks a group monitoring management mechanism, requires engineers to go to on-site maintenance, and causes the problem of high operation cost.
Disclosure of Invention
The invention provides a non-equivalent grouping method of an air source heat pump unit, which aims to solve the problems that the energy efficiency ratio is low, the energy cost is high and a group monitoring management mechanism is lacked due to a single adjustment mode of the existing air source heat pump unit, and certain components are not operated effectively under specific conditions, so that the operation cost is high.
The invention provides the following technical scheme:
an unequal grouping method of air source heat pump units comprises the following steps:
s1: collecting external influence factor data such as building load, design temperature, indoor and outdoor temperature and user use habit, and transmitting the external influence factor data to a central control system;
s2: analyzing the collected data, and analyzing the influence of different factors on the operation of the air source heat pump unit by using a correlation analysis method;
s3: the grouping control is realized, the working time, the working mode and the load proportion of each grouping are adjusted according to the load capacity of each grouping of the heat pump machine, the task distribution with different intensities is carried out on each grouping, and the unequal grouping of the heat pump units is realized;
s4: the running state of the system is detected regularly, and the running condition of the system is evaluated regularly, so that problems are found timely and a grouping scheme is adjusted, and the running efficiency of the system is improved.
Further, in the step S1, the building area is obtained by laser ranging, and then transmitted to the central control system, and the current building load is determined according to the building area.
Further, in the step S1, the indoor and outdoor temperatures are measured by the temperature sensor, the indoor and outdoor temperature difference is calculated, and then the heat which needs to be increased or decreased at present is calculated according to the predetermined temperature target.
Further, in the step S1, the information of the user 'S use habit is collected through the automatic collection system and is transmitted to the central control system for subsequent study of the user' S use habit, so as to make a more humanized, energy-saving and environment-friendly grouping plan.
Further, in the step S2, the collected environmental information may analyze the influence of external factors on the operation of the air source heat pump unit by means of correlation analysis, and build a model to predict the time required for reaching the set temperature in different environments, so as to improve the operation mode of the heat pump unit.
Furthermore, in the step S2, a statistical method is used to collect some behavior habits of the user when using the heat pump, for example, the distribution condition of the frequency and time of use, and cluster analysis may be used to group different users and study the differences between different groups.
Further, in the step S3, the controller is used to implement grouping control on each component in the heat pump machine, and the controller monitors the operation state of each component in the heat pump machine and controls according to a preset rule, so that the operation state of each heat pump machine can be more effectively controlled by grouping the operation of each component in the heat pump machine, thereby improving the efficiency of the system.
Further, in S4, the operation state of the heat pump machine is determined by checking parameters such as temperature, pressure, and flow rate of components in the heat pump machine.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the unequal grouping method of the air source heat pump unit, the effects of unequal adjustment of the work arrangement of each component according to the use condition are achieved by collecting external influence factor data, analyzing the collected data and performing grouping control, the problems that the energy efficiency ratio is low and the energy cost is high due to a single adjustment mode of the existing air source heat pump unit are solved, and the operation efficiency of the heat pump unit is improved.
2. According to the unequal grouping method of the air source heat pump unit, the running condition of the system is automatically and regularly evaluated, problems are timely found, the grouping scheme is adjusted, the effects of automatic maintenance and regular fault checking are achieved, the problem that the existing air source heat pump unit lacks a group monitoring management mechanism, workers are required to go to the site for maintenance under the condition of faults, and the running cost is high is solved.
Drawings
FIG. 1 is a schematic diagram of the components of the air-source heat pump unit of the present invention.
Fig. 2 is a flow chart of the operation of the present invention.
Fig. 3 is a flow chart of unequal grouping of air source heat pump units.
Detailed Description
Embodiments of the present invention are described in further detail below with reference to the accompanying drawings and examples. The following examples are illustrative of the invention but are not intended to limit the scope of the invention.
The invention provides a non-equivalent grouping method of an air source heat pump unit, which is used for realizing the effect of non-equivalent adjustment of the work arrangement of each component according to the use condition by collecting external influence factor data, analyzing the collected data and performing grouping control, and comprises the following specific steps:
step 1: refrigerating by a heat pump unit;
as shown in fig. 1 and 2, when indoor cooling is required in summer, the air source heat pump unit operates according to a refrigerating condition, outdoor gas enters the compressor, the compressor increases the pressure and temperature of the outdoor gas through compression, a condition for transferring heat of the outdoor gas to an external environment medium is created, namely, the low-temperature low-pressure outdoor gas is compressed to a high-temperature high-pressure state, namely, a refrigerant, at the moment, the boiling point of the refrigerant increases along with the increase of the pressure, the refrigerant with the high boiling point enters the condenser to start liquefying, at the moment, the refrigerant emits heat to become liquid, and passes through the expansion valve before entering the evaporator, the expansion valve reduces the pressure of the refrigerant again to slow down the flowing speed, the flow is saved, the refrigerant with the reduced pressure begins evaporating again in the evaporator, at the moment, the refrigerant absorbs heat to cool the indoor, and then becomes low-pressure gas again, and the refrigerant enters the compressor again, and the whole refrigerant refrigerating circulation system is formed.
Step 2: heating by a heat pump unit;
as shown in fig. 1 and 2, when heating is needed in winter, the reversing valve is first turned to the working position of the heat pump, high-pressure refrigerant vapor discharged from the compressor flows into the indoor evaporator (used as a condenser) after passing through the reversing valve, heat is released when the refrigerant vapor condenses, indoor air is heated, the purpose of indoor heating is achieved, the condensed liquid refrigerant reversely flows through the throttling device to enter the condenser (used as the evaporator), external heat is absorbed and evaporated, the evaporated vapor is sucked by the compressor after passing through the reversing valve, and heating circulation is completed, so that heat in the external air is pumped into a room with higher temperature, and the indoor heating function is achieved.
Step 3: collecting external influence factor data;
as shown in fig. 3, during the cooling or heating process of the heat pump unit, external influencing factor data such as building load, indoor and outdoor temperature and user usage habit are collected at the same time and transmitted to the central control system, when building load data are collected, the current building load can be determined through the building area because the building area and the building load are in positive correlation, when the building area is large, the balance temperature point is increased, the auxiliary heating amount in the whole heating season is increased, so that the heating season performance coefficient is reduced, when the building area is small, the balance temperature point is reduced, the auxiliary heating amount in the whole heating season is reduced, so that the heating season performance coefficient is improved, the heat pump unit obtains the building area through laser ranging and then transmits the building area to the central control system, and the current building load is determined through the building area;
when collecting indoor and outdoor temperature data, measuring indoor and outdoor temperatures through a temperature sensor, calculating an indoor and outdoor temperature difference value, calculating heat which is required to be increased or reduced currently according to a preset temperature target, regulating the running temperature through regulating the evaporation pressure of an evaporator, the condensation pressure of a condenser and the fan rotating speed of a compressor, and adopting measures such as increasing high-low pressure bypass and the like under the low-temperature heating condition to prevent the liquid return problem of a unit;
the statistical method is used for collecting user characteristics and some behavior habits when the heat pump machine is used, such as age, housing type, duration of using the heat pump machine, frequency of using the heat pump machine and the like, information of the user using habits is automatically collected through the system and is transmitted to the central control system for subsequent study of the user using habits so as to formulate a more humanized, energy-saving and environment-friendly grouping plan, the automatic collection system can also record the time when the user normally turns on and off the heat pump machine, and the working state of the heat pump machine is automatically adjusted according to the information in the future so as to better meet the demands of the user and realize the functions of energy conservation and emission reduction.
Step 4: analyzing the collected data;
as shown in fig. 3, the collected environmental information may analyze the influence of external factors on the operation of the air source heat pump unit by means of correlation analysis, which is a statistical analysis method that may be used to measure the correlation between two variables, for example, when researching the influence of external temperature on the operation of the heat pump unit, the daily operation condition of the heat pump unit and the daily external temperature may be collected, and then the correlation between the two variables is measured by using the correlation analysis, and a model is built to predict the time required to reach the set temperature under different environments so as to improve the operation mode of the heat pump unit;
the clustering analysis is used for analyzing different user behaviors and researching differences among different groups, and is an unsupervised learning method which can help us to divide data samples into a plurality of categories without the need of designating the categories in advance; for users of the heat pump machine to group, user behaviors (such as use duration, use frequency, power consumption and the like) of the heat pump machine can be taken as data samples, and data are preprocessed before cluster analysis is performed, so that a cluster analysis algorithm can process the data samples, for example, non-numerical data in collected information is converted into numerical data, and then normalization processing is performed on the data by using a Min-Max method, wherein the formula is as follows: x_scaled= (X-Xmin)/(Xmax-Xmin), where X is the raw data, xmin and Xmax are the minimum and maximum values of the raw data, respectively, and x_scaled is the normalized data, so that the data is scaled to be within the range of [0,1] or [ -1,1], so that the computer algorithm can better process the data, improving the efficiency of data analysis.
Step 5: realizing grouping control;
as shown in fig. 3, according to the load capacity of each group of the heat pump machine, the working time, the working mode and the load proportion of each group are adjusted, and the task allocation with different intensities is carried out on each group, so that unequal grouping of the heat pump units is realized; the controller is used for realizing grouping control of all components in the heat pump machine, and the controller controls the running state of each component in the heat pump machine according to a preset rule by monitoring the running state of each component in the heat pump machine, so that the running state of each heat pump machine can be more effectively controlled by grouping the running of each component in the heat pump machine, and the efficiency of the system is improved; the task grouping of different components in the heat pump machine is performed by using a clustering algorithm such as a K-Means clustering method, the K-Means clustering is a popular clustering algorithm, the main idea of the K-Means clustering method is to divide data points into K clusters, so that the sum of the distances of the data points in each cluster is minimum, a more accurate grouping result is obtained, finally, the grouping result can be checked and adjusted according to the requirement to obtain a better grouping effect, and the basic flow of the K-Means clustering method is as follows:
step 5.1: initializing a clustering center;
k data points are selected as initial cluster centers and these data points will be the cluster centers of the respective clusters.
Step 5.2: assigning data points;
for each data point, its distance to each cluster center is calculated and assigned to the cluster where the closest cluster center is located.
Step 5.3: updating a clustering center;
the method realizes the real-time updating of the clustering center by calculating the average value of all data points in each cluster and taking the average value as a new clustering center, so that the data is kept up to date and is suitable for different use environments.
Step 5.4: and 5.2 and 5.3 are repeated until the clustering center is not changed any more or the maximum iteration number is reached, then each cluster is analyzed, the difference of the use habits of different users is known, and a corresponding work plan is formulated for the heat pump unit.
Step 5.5: setting up an operation plan aiming at different scenes;
when the system load is large, such as the peak period of the heat pump machine, the controller can call more heat pump machines to meet the requirement, and when the load is small, such as the low valley of the machine utilization rate, the controller can stop running some heat pump machines, so that the energy is saved when the temperature control effect is achieved.
Step 6: detecting the running state of the system regularly;
as shown in fig. 3, the operation condition of the system is evaluated, problems are found out in time, a grouping scheme is adjusted to improve the operation efficiency of the system, the operation state of the heat pump is determined by checking parameters such as the temperature, the pressure and the flow of components in the heat pump, whether the temperature difference of water inlet and outlet is proper or not is checked, whether the pressure and the temperature of a compressor are normal or not is checked, the water flow in the system is ensured to be proper, when any abnormal condition is found, the operation of the heat pump is immediately stopped, and a professional is reported to carry out maintenance.
While embodiments of the present invention have been shown and described above for purposes of illustration and description, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (5)
1. The unequal grouping method of the air source heat pump unit is characterized by comprising the following steps of:
s1: collecting external influence factor data such as building load, design temperature, indoor and outdoor temperature and user use habit, and transmitting the external influence factor data to a central control system;
s2: analyzing the collected data, and analyzing the influence of different factors on the operation of the air source heat pump unit by using a correlation analysis method;
in the step S2, the collected environmental information can analyze the influence of external factors on the operation of the air source heat pump unit through a correlation analysis method, collect the behavior habit of a user when using the heat pump unit through a statistical method, group different users through cluster analysis, and study the difference among different groups, and through the analysis, the user using habit can be better known, and a basis is provided for providing better products and services;
s3: the grouping control is realized, the working time, the working mode and the load proportion of each grouping are adjusted according to the load capacity of each grouping of the heat pump machine, the task distribution with different intensities is carried out on each grouping, and the unequal grouping of the heat pump units is realized;
in the step S3, the controller is used to implement grouping control on each component in the heat pump machine, and the controller monitors the operation state of each component in the heat pump machine and controls according to a preset rule, so that the operation state of each heat pump machine can be more effectively controlled by grouping the operation of each component in the heat pump machine, thereby improving the efficiency of the system, and a clustering algorithm such as a K-Means clustering method is used to perform task grouping of different components in the heat pump machine, and the basic flow is as follows:
(1) Initializing a cluster center, and selecting K data points as the initial cluster center, wherein the data points are used as the cluster centers of respective clusters;
(2) Assigning data points, calculating the distance from each data point to each cluster center, and assigning the data points to clusters where the closest cluster centers are located;
(3) Updating the clustering center, namely, updating the clustering center in real time by calculating the average value of all data points in each cluster and taking the average value as a new clustering center, so that the data are kept up to date and adapt to different use environments;
(4) Repeating the steps (2) and (3) until the clustering center is not changed any more or the maximum iteration number is reached, then analyzing each cluster, knowing the difference of the use habits among different users, and making a corresponding work plan for the heat pump unit;
(5) Setting up an operation plan aiming at different scenes;
s4: the running state of the system is detected regularly, and the running condition of the system is evaluated regularly, so that problems are found timely and a grouping scheme is adjusted, and the running efficiency of the system is improved.
2. The unequal grouping method of the air source heat pump unit as claimed in claim 1, wherein: in the step S1, the building area is obtained by laser ranging, then the building area is transmitted to a central control system, and the current building load is determined through the building area.
3. The unequal grouping method of the air source heat pump unit as claimed in claim 1, wherein: in the step S1, the indoor and outdoor temperatures are measured through a temperature sensor, the indoor and outdoor temperature difference is calculated, and then the heat which is required to be increased or decreased at present is calculated according to a preset temperature target.
4. The unequal grouping method of the air source heat pump unit as claimed in claim 1, wherein: in the step S1, information of the user using habit is collected through an automatic collecting system and is transmitted to a central control system for subsequent study of the user using habit, so that a more humanized, energy-saving and environment-friendly grouping plan is formulated.
5. The unequal grouping method of the air source heat pump unit as claimed in claim 1, wherein: in S4, the operation state of the heat pump machine is determined by checking parameters such as temperature, pressure and flow of components in the heat pump machine.
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