Energy-saving control method and system for air-conditioning equipment group driven by big data

Abstract

The present invention discloses an energy-saving control method and system for an air-conditioning equipment group driven by big data, which relates to the technical field of air-conditioning equipment group control. According to the target environment where the air-conditioning equipment group is located, the corresponding arrangement information is obtained. According to the air-conditioning arrangement position in the target environment, the preliminary coverage area of any air conditioner can be determined by adjusting the temperature by X1 degrees Celsius within a set time. Then, the preliminary coverage area of the air conditioner is updated according to the cooling rate for the area not yet divided, so as to obtain the approved coverage area of each air conditioner, and the number of seats in the approved coverage area is obtained synchronously; then, the number of air conditioners to be turned on is determined according to the number of students in the next class at the current time, the corresponding number of air conditioners is turned on, and the opening objects are determined, so as to reasonably arrange the number of air conditioners to be turned on and how to turn them on specifically.

Description

Technical Field

[0001] The present invention belongs to the technical field of group control of air conditioning equipment, and specifically relates to an energy-saving control method and system for an air conditioning equipment group driven by big data. Background Art

[0002] In the prior art, an energy-saving mode is set for each air conditioner. After the user turns on the energy-saving mode, the air conditioner will limit the operating current to reduce the operating power of the compressor, thereby achieving the purpose of energy saving.

[0003] However, at present, most of the air conditioners used in various public buildings are independently controlled in a decentralized manner, which is greatly affected by human factors, and the control and management are extensive, resulting in extremely high energy consumption of the air conditioners. For example, Chinese Patent CN102734893A discloses a linkage control device to achieve more energy-efficient air conditioning control. In a linkage control device for controlling multiple devices via a network, it is characterized in that setting information for linkage control is used, and the setting information includes linkage source device information, linkage source condition number information, linkage source condition action information, linkage target device information, and linkage target control action information as a corresponding piece of information.

[0004] However, for the air conditioning equipment group in school classrooms, especially how to perform reasonable analysis and control of the opening of air conditioning equipment according to different teaching numbers and different teaching arrangements is a difficult problem; based on this, the present application provides a solution. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art;

[0006] To this end, the present invention proposes an energy-saving control method for an air conditioning equipment group driven by big data, which specifically includes the following steps:

[0007] According to the target environment where the air conditioning equipment group is located, obtain the corresponding arrangement information, and the arrangement information is used to represent the specific arrangement of the class time and the number of students in each class in the corresponding target environment;

[0008] According to the air conditioning arrangement position in the target environment, determine the preliminary coverage area of any air conditioner by being able to adjust the temperature by X1 degrees Celsius within a set time, and then update the preliminary coverage area of the air conditioner according to the cooling rate for the area not yet divided, so as to obtain the approved coverage area of each air conditioner, and synchronously obtain the number of seats in the approved coverage area;

[0009] Then, determine the number of air conditioners to be turned on according to the number of students in the next class at the current time, turn on the corresponding number of air conditioners, and determine the opening objects.

[0010] Further, the target environment is the classroom where the controlled air conditioning equipment group is located.

[0011] Further, the specific method for determining the preliminary coverage area of the air conditioner is as follows:

[0012] Conduct environmental simulation. In the same target environment, with the doors and windows closed, turn on the air conditioner at any position, and then take the position directly below the center of the air conditioner as the center of the circle;

[0013] Obtain the area range where the temperature change reaches X1 degrees Celsius within the set time T2 when the air conditioner cools or heats up, and mark it as the preliminary area; X1 is a preset value;

[0014] Then mark all the desks within this preliminary area as the preliminary coverage area corresponding to the air conditioner equipment;

[0015] After that, process the remaining air conditioners in the same way;

[0016] Further, update the preliminary coverage area. The specific method for determining the approved coverage area is as follows:

[0017] Obtain the preliminary coverage areas of adjacent air conditioners. When there is an overlapping area in the preliminary coverage area of any air conditioner, obtain all the air conditioners corresponding to the overlapping area, and determine which air conditioner the overlapping area belongs to according to the length of time required to adjust the temperature change value in the overlapping area to reach X1 degrees Celsius; when there is an area that has not been divided into any preliminary coverage area, mark the undivided area as a blank area, obtain all the air conditioners within the preset value L1 of the straight-line distance from the center point of the blank area, and determine which air conditioner the blank area belongs to according to the length of time required to adjust the temperature change value in the blank area to reach X1 degrees Celsius; if the lengths of time required for the overlapping area or the blank area are the same, randomly divide which air conditioner the overlapping area or the blank area belongs to, and ensure that the square difference of the areas covered by each air conditioner is not more than X2 during the division process, where X2 is a preset value;

[0018] Mark the preliminary coverage area after adjusting the area as the approved coverage area to obtain the approved coverage area of each air conditioner.

[0019] Further, the specific method for determining the number of air conditioners to be turned on according to the number of people in class is as follows:

[0020] Obtain the approved coverage areas of all air conditioners and their number of seats, combine the number of seats, select the approved coverage areas of at least one air conditioner, add up the number of seats in the selected approved coverage areas to obtain the total number of seats, and obtain several combinations of the approved coverage areas of air conditioners, which are marked as coverage groups;

[0021] Subtract the number of people in class from the total number of seats, and mark the obtained value as the seat difference corresponding to the coverage group;

[0022] Then divide the classroom seats into front-row seats, middle seats, and rear-row seats. The front-row seats refer to the seats in the first one-third of the rows in the classroom, and the rear-row seats refer to the seats in the last one-third of the rows in the classroom. The rest are middle seats;

[0023] Then obtain the numbers of front-row seats, middle seats, and rear-row seats in each coverage group, and mark them as the front-row number, middle number, and rear-row number in sequence. Calculate the optimal value using the formula:

[0024] Optimal value = 2 * front-row number + middle number;

[0025] Obtain the optimal value of each coverage group, and then calculate the confirmed value of each coverage group using the formula. The specific formula is:

[0026] Confirmed value = 0.58 * optimal value + 0.42 / seat difference;

[0027] In the formula, 0.58 and 0.42 are preset weights;

[0028] Mark the air conditioner corresponding to the approved coverage area in the coverage group with the largest confirmed value as the opening object.

[0029] Further, after obtaining the opening object, turn on the air conditioner according to the opening object;

[0030] After reaching the end-of-class time, the arrangement information of the corresponding target environment will be automatically obtained. If there is no class schedule within T3 time, all air conditioners will be automatically turned off. Here, T3 is a preset value.

[0031] Further, the value of T2 can also be determined in the following way:

[0032] In a room equipped with the same air conditioning equipment, obtain the time required for its temperature to change by X1 degrees Celsius;

[0033] Then obtain the same air conditioning equipment in several different rooms, and obtain the time required for the temperature change to reach X1 degrees Celsius; obtain several times and mark them as the adjustment duration Ci, i = 1,..., n, indicating that the simulation is carried out in n rooms;

[0034] Then obtain the mean value P of Ci, obtain the mean value of the values in Ci that are greater than P, and mark it as the transcendental number, and mark the mean value of the values in Ci that are less than P as the sub-mean number;

[0035] When the transcendental number is less than the sub-mean number, mark the P value as the value of T2 at this time;

[0036] Otherwise, automatically mark the median value of the P value and the transcendental number as the value of T2.

[0037] Further, T2 is a preset value.

[0038] An energy-saving control system for a group of air-conditioning devices driven by big data. This system uses the aforementioned energy-saving control method to achieve energy-saving control of air-conditioning devices.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0040] This application obtains the corresponding arrangement information according to the target environment where the group of air-conditioning devices is located. According to the air-conditioning arrangement position in the target environment, it can adjust the temperature by X1 degrees Celsius within a set time to determine the preliminary coverage area of any air-conditioning device. Then, for the area not yet divided, the preliminary coverage area of the air-conditioning device is updated according to the cooling rate, so as to obtain the approved coverage area of each air-conditioning device, and synchronously obtain the number of seats in the approved coverage area. Then, according to the number of people in the next class at the current time, the number of air-conditioning devices to be turned on is determined, the corresponding number of air-conditioning devices is turned on, and the objects to be turned on are determined, so as to reasonably arrange the number of air-conditioning devices to be turned on and how to turn them on specifically. The present invention is simple and effective, and is easy to use.

[0041] Of course, it is not necessary for any product implementing the present invention to achieve all the above-mentioned advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0043] Figure 1 It is a flowchart of the energy-saving control method for a group of air-conditioning devices driven by big data according to the present invention;

[0044] Figure 2 It is a flowchart for determining the preliminary coverage area of an air-conditioning device according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0046] It should be understood that, as used in the specification of this application and the appended claims, the term "comprising" indicates the presence of the described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or their groups.

[0047] It should also be understood that the term "and / or" as used in the specification of this application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0048] As used in the specification of this application and the appended claims, the term "if" can be interpreted as "when", "once", "in response to determining", or "in response to detecting" according to the context. Similarly, the phrases "if determined" or "if [the described condition or event] is detected" can be interpreted as meaning "once determined", "in response to determining", "once [the described condition or event] is detected", or "in response to detecting [the described condition or event]" according to the context.

[0049] In addition, in the description of the specification of this application and the appended claims, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0050] Reference to "one embodiment" or "some embodiments" or the like described in the specification of this application means that a specific feature, structure or characteristic described in connection with that embodiment is included in one or more embodiments of this application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0051] Embodiment 1:

[0052] Please refer to Figure 1 As shown, this application provides an energy-saving control method for an air-conditioning equipment group driven by big data;

[0053] As Embodiment 1 of this application, the method specifically includes the following steps:

[0054] Step 1: Obtain the air-conditioning equipment group and the target environment where it is located. The target environment is the environment where the corresponding air-conditioning equipment group is located. Specifically for this application, it is which classroom, office, or activity venue. The air-conditioning equipment group includes several air-conditioning equipment;

[0055] Step 2: Obtain the target environment. First, obtain the arrangement information of the corresponding target environment. The arrangement information is the planned air-conditioning usage duration and the number of users in the target environment. Further, the arrangement information includes the class time of each specific class and the number of students in class at the corresponding class time. When it is T1 time before the class time (T1 is a preset time value, generally 5 minutes), energy-saving analysis will be automatically performed. The specific method of energy-saving analysis is as follows:

[0056] First, the number of students in class will be automatically obtained, and then the number of seats in the target environment and the distribution information of the air-conditioning equipment will be synchronized. The distribution information refers to the location where the air-conditioning is located. Then, the coverage area of the air-conditioning will be analyzed. As Figure 2 shown, the analysis method is as follows:

[0057] First, perform environmental simulation. In the corresponding same target environment, with the doors and windows closed, turn on the air-conditioning at any position, and then take the position directly below the center of the air-conditioning as the center of the circle to observe its coverage area;

[0058] First, determine the preliminary area; obtain the area range where the temperature change reaches X1 degrees Celsius within the set time T2 when the air-conditioning cools or warms up, and mark it as the preliminary area; both X1 and T2 are preset values, and X1 generally takes a value of 2 degrees Celsius;

[0059] Then, mark all the desks in this preliminary area as the preliminary coverage area of the corresponding air-conditioning equipment;

[0060] After that, process the remaining air-conditioning in the same way;

[0061] Obtain the preliminary coverage areas of adjacent air-conditioning. When there is an overlapping area in the preliminary coverage area of any air-conditioning, obtain all the air-conditioning corresponding to the overlapping area, and determine which air-conditioning the overlapping area belongs to according to the length of time required to adjust the temperature change value of the overlapping area to reach X1 degrees Celsius; when there is an area that has not been divided into any preliminary coverage area, mark the undivided area as the blank area, and obtain all the air-conditioning within the preset value L1 of the straight-line distance from the center point of the blank area, and determine which air-conditioning the blank area belongs to according to the length of time required to adjust the temperature change value of the blank area to reach X1 degrees Celsius; if the lengths of time required for the overlapping area or the blank area are the same, randomly divide which air-conditioning the overlapping area or the blank area belongs to, and ensure that the square difference of the areas covered by each air-conditioning is not more than X2 during the division process. X2 is a preset value;

[0062] Mark the preliminary coverage area of the adjusted area as the approved coverage area to obtain the approved coverage area of each air conditioner, and at the same time synchronize the number of seats in the approved coverage area;

[0063] Determine the number of air conditioners to be turned on according to the number of people in class. The rule followed here is to turn on the minimum number of air conditioners to ensure that the number of seats covered is greater than or equal to the number of people in class. Obtain the approved coverage area and its number of seats of all air conditioners, combine the number of seats, select the approved coverage area of at least one air conditioner, add up the number of seats in the selected approved coverage area to get the total number of seats, and obtain several combinations of the approved coverage areas of air conditioners, which are marked as coverage groups;

[0064] Subtract the number of people in class from the total number of seats, and mark the obtained value as the seat difference of the corresponding coverage group;

[0065] Then divide the classroom seats into front-row seats, middle seats and rear-row seats. The front-row seats refer to the seats in the first one-third row of the classroom, the rear-row seats refer to the seats in the last one-third row of the classroom, and the rest are middle seats;

[0066] Then obtain the number of front-row seats, middle seats and rear-row seats in each coverage group, and mark them as the front-row number, middle number and rear-row number in sequence, and calculate the preferred value using the formula. The formula is:

[0067] Preferred value = 2 * front-row number + middle number;

[0068] Obtain the preferred value of each coverage group, and then calculate the confirmed value of each coverage group using the formula. The specific formula is:

[0069] Confirmed value = 0.58 * preferred value + 0.42 / seat difference;

[0070] In the formula, 0.58 and 0.42 are preset weight values used to highlight the different importance of different factors;

[0071] Mark the air conditioner corresponding to the approved coverage area in the coverage group with the largest confirmed value as the object to be turned on;

[0072] Step 3: After obtaining the object to be turned on, turn on the air conditioner according to the object to be turned on;

[0073] Step 4: After the class is over, the arrangement information of the corresponding target environment will be automatically obtained. If there is no class arrangement within T3 time, all air conditioners will be automatically turned off. Here, T3 is a preset value, and generally, the specific value is 20 minutes.

[0074] Embodiment 2:

[0075] As the second embodiment of the present application, the present application is implemented on the basis of the first embodiment. Here, T2 is determined in the following manner. In a room equipped with an identical air-conditioning device, the time required for its temperature to change by X1 degrees Celsius is obtained.

[0076] Then, for the same air-conditioning device in several different rooms, the time required to adjust the temperature change to reach X1 degrees Celsius is obtained. A number of such times are obtained and marked as the adjustment duration Ci, where i = 1,..., n, indicating that the simulation is carried out in n rooms.

[0077] Then, the mean value P of Ci is obtained, the mean value of the values in Ci that are greater than P is obtained and marked as the transcendental number, and the mean value of the values in Ci that are less than P is marked as the sub-mean number.

[0078] When the transcendental number is less than the sub-mean number, the P value is marked as the value of T2 at this time.

[0079] Otherwise, the median value of the P value and the transcendental number is automatically marked as the value of T2.

[0080] Embodiment Three:

[0081] As the third embodiment of the present application, the present application is implemented on the basis of the first embodiment. The difference from the first embodiment is that after reaching the end of class time in step four, before turning off all air conditioners, a continuation analysis needs to be carried out. The specific method of the continuation analysis is as follows:

[0082] The number of students studying by themselves in the next class of this classroom is obtained, which is specifically realized through predictive analysis. It is located in the way of the same month and specific day of the week. For example, if today is Monday in March, then in a similar way, the number of students studying by themselves in the time period belonging to the next class every day in the past year is obtained, and then the mean value of the number of students studying by themselves is automatically calculated. When the mean value is divided by the number of people that can sit in all the seats of the classroom, the obtained value is marked as the self-study ratio. If the self-study ratio exceeds B1, then the air conditioner in this classroom will not be turned off, and in the same way as in the first embodiment mentioned above, according to the mean value of the number of students studying by themselves, the number of air conditioners to be turned on is analyzed. When reaching the end of class time, it is automatically obtained whether there is a teaching arrangement in the next class. If there is, it is analyzed in the way of the first embodiment. If not, it is analyzed in the way of this embodiment whether there are people studying by themselves, and the air conditioner is adjusted accordingly.

[0083] Embodiment Four:

[0084] Of course, the present application provides an embodiment four. This embodiment is used to implement the integration of the first to the third embodiments. At the same time, on the basis of this embodiment, the present application also provides an energy-saving control device for an air-conditioning device group based on big data drive. This device uses the energy-saving control method for an air-conditioning device group mentioned in this embodiment to realize the energy-saving control of the air-conditioning device group.

[0085] In the description of this specification, the description referring to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0086] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An energy-saving control method for air-conditioning equipment groups driven by big data, characterized in that: The method comprises the following steps: Step S1: According to the target environment where the air-conditioning equipment group is located, corresponding arrangement information is obtained, where the arrangement information is the planned air-conditioning usage time and number of users in the target environment; Step S2: determining a preliminary coverage area of ​​any air conditioner according to the arrangement position of the air conditioner in the target environment and the degree Celsius to which the temperature can be adjusted within a set time; Step S3: for the overlapping area or the undivided area, the preliminary coverage area of ​​the air conditioner is updated according to the cooling speed, the approved coverage area of ​​each air conditioner is obtained, and the number of seats in the approved coverage area is simultaneously obtained; Step S4: Determine the number of air conditioners to be turned on according to the number of students in the next class at the current time, determine the objects to be turned on and turn on the corresponding air conditioners, specifically in the following manner: Obtain the approved coverage areas and corresponding seat numbers of all air conditioners, combine the seat numbers, select at least one approved coverage area of ​​the air conditioner, add the seat numbers of the selected approved coverage areas to obtain the total number of seats, obtain a combination of approved coverage areas of several air conditioners, and mark it as a coverage group; Subtract the number of students in class from the total number of seats, and mark the resulting value as the seat difference of the corresponding coverage group; Classroom seats are divided into front row seats, middle seats and back row seats. The front row seats refer to the seats in the first third of the classroom, the back row seats refer to the seats in the last third of the classroom, and the rest are middle seats. Then, the number of front seats, middle seats, and back seats in each coverage group is obtained, and marked as the front row number, middle number, and back row number respectively, and the preferred value is calculated using the formula: Optimal value = 2*number of front rows + number of middle rows; Get the optimal value of each covering group, and then use the formula to calculate the confirmed value of each covering group. The specific formula is: Confirmed value = 0.58*preferred value + 0.42 / seat difference; In the formula, 0.58 and 0.42 are preset weights; Marking the air conditioner corresponding to the approved coverage area in the coverage group with the largest selected value as an on-target; after obtaining the on-target, turning on the air conditioner according to the on-target; When the get out of class is over, the scheduling information of the corresponding target environment will be automatically obtained. If there are no classes scheduled within T3 time, all air conditioners will be automatically turned off. T3 is the preset value.

2. The energy-saving control method for air-conditioning equipment groups based on big data drive according to claim 1 is characterized in that: The target environment is the classroom where the controlled air-conditioning equipment group is located; the arrangement information is used to indicate the class time and number of students for each class in the corresponding target environment.

3. The energy-saving control method for air-conditioning equipment groups based on big data drive according to claim 1 is characterized in that: In step S2, the specific method of determining the preliminary coverage area of ​​the air conditioner is: Step S21: Perform environmental simulation. In the same target environment, with doors and windows closed, turn on the air conditioner at any position, and take the position directly below the center of the air conditioner as the center of the circle; Step S22: When the air conditioner is turned on to cool down or heat up, the area where the temperature change reaches X1 degrees Celsius within the set time T2 is circled, and the circled area is marked as a preliminary area; X1 is a preset value; Step S23: Mark all the desks in the preliminary area as the preliminary coverage area of ​​the corresponding air conditioner; Step S24: Process the air conditioners at other locations according to steps S21 to S23 to obtain preliminary coverage areas of all air conditioners.

4. The energy-saving control method for air-conditioning equipment groups based on big data drive according to claim 1 is characterized in that: In step S3, the preliminary coverage area is updated, and the specific method of determining the approved coverage area is: Step S31: obtaining the preliminary coverage area of ​​adjacent air conditioners; Step S32: when there is an overlapping area in the preliminary coverage area of ​​any air conditioner, all air conditioners corresponding to the overlapping area are obtained, and the air conditioner to which the overlapping area belongs is determined according to the length of time required to adjust the temperature change value of the overlapping area to reach X1 degrees Celsius; Step S33: when there is an area that is not divided into any preliminary coverage area, the undivided area is marked as a blank area, and all air conditioners whose straight-line distance from the center point of the blank area is within the preset value L1 are obtained, and the blank area is determined to which air conditioner it belongs according to the length of time required to adjust the temperature change value of the blank area to reach X1 degrees Celsius; Step S34: In step S32 and step S33, if the required time corresponding to the overlapping area or the blank area is the same, the overlapping area or the blank area is randomly divided to determine which air conditioner it belongs to; During random division, ensure that the square difference of the initial coverage area of ​​all air conditioners does not exceed X2, where X1 and X2 are preset values; Step S35: Mark the updated and adjusted preliminary coverage area as the approved coverage area, and obtain the approved coverage area of ​​each air conditioner.

5. The energy-saving control method for air-conditioning equipment groups based on big data drive according to claim 3 is characterized in that: The value of T2 can also be determined in the following manner: In a room with the same air conditioner installed, get the time required for the temperature to change by X1 degree Celsius; Then, the time required for the same air-conditioning equipment in several different rooms to adjust the temperature to change by X1 degrees Celsius is obtained; the obtained several time marks are the adjustment time Ci, i=1, ..., n, indicating that the simulation is performed in n rooms; Then obtain the mean value P of Ci, obtain the mean of the values ​​in Ci that are greater than P, mark it as a transcendental number, and mark the mean of the values ​​in Ci that are less than P as a submean number; When the exceedance number is less than the average lower number, the P value is marked as the value of T2; Otherwise, the median of the P value and the transcendental number is automatically marked as the value of T2.

6. The energy-saving control method for air-conditioning equipment groups based on big data drive according to claim 3 is characterized in that: The T2 is a preset value.

7. An energy-saving control system for air-conditioning equipment groups driven by big data, characterized in that: The system adopts the energy-saving control method as described in any one of claims 1 to 6 to realize energy-saving control of air-conditioning equipment.

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